Highly stretchable strain sensor based on SWCNTs/CB synergistic conductive network for wearable human-activity monitoring and recognition

NASA Astrophysics Data System (ADS)

Guo, Xiaohui; Huang, Ying; Zhao, Yunong; Mao, Leidong; Gao, Le; Pan, Weidong; Zhang, Yugang; Liu, Ping

2017-09-01

Flexible, stretchable, and wearable strain sensors have attracted significant attention for their potential applications in human movement detection and recognition. Here, we report a highly stretchable and flexible strain sensor based on a single-walled carbon nanotube (SWCNTs)/carbon black (CB) synergistic conductive network. The fabrication, synergistic conductive mechanism, and characterization of the sandwich-structured strain sensor were investigated. The experimental results show that the device exhibits high stretchability (120%), excellent flexibility, fast response (˜60 ms), temperature independence, and superior stability and reproducibility during ˜1100 stretching/releasing cycles. Furthermore, human activities such as the bending of a finger or elbow and gestures were monitored and recognized based on the strain sensor, indicating that the stretchable strain sensor based on the SWCNTs/CB synergistic conductive network could have promising applications in flexible and wearable devices for human motion monitoring.

Highly stretchable strain sensor based on polyurethane substrate using hydrogen bond-assisted laminated structure for monitoring of tiny human motions

NASA Astrophysics Data System (ADS)

Huang, Ying; Zhao, Yunong; Wang, Yang; Guo, Xiaohui; Zhang, Yangyang; Liu, Ping; Liu, Caixia; Zhang, Yugang

2018-03-01

Strain sensors used as flexible and wearable electronic devices have improved prospects in the fields of artificial skin, robotics, human-machine interfaces, and healthcare. This work introduces a highly stretchable fiber-based strain sensor with a laminated structure made up of a graphene nanoplatelet layer and a carbon black/single-walled carbon nanotube synergetic conductive network layer. An ultrathin, flexible, and elastic two-layer polyurethane (PU) yarn substrate was successively deposited by a novel chemical bonding-based layered dip-coating process. These strain sensors demonstrated high stretchability (˜350%), little hysteresis, and long-term durability (over 2400 cycles) due to the favorable tensile properties of the PU substrate. The linearity of the strain sensor could reach an adjusted R-squared of 0.990 at 100% strain, which is better than most of the recently reported strain sensors. Meanwhile, the strain sensor exhibited good sensibility, rapid response, and a lower detection limit. The lower detection limit benefited from the hydrogen bond-assisted laminated structure and continuous conductive path. Finally, a series of experiments were carried out based on the special features of the PU strain sensor to show its capacity of detecting and monitoring tiny human motions.

Continuous monitoring of large civil structures using a digital fiber optic motion sensor system

NASA Astrophysics Data System (ADS)

Hodge, Malcolm H.; Kausel, Theodore C., Jr.

1998-03-01

There is no single attribute which can always predict structural deterioration. Accordingly, we have developed a scheme for monitoring a wide range of incipient deterioration parameters, all based on a single motion sensor concept. In this presentation, we describe how an intrinsically low power- consumption fiber optic harness can be permanently deployed to poll an array of optical sensors. The function and design of these simple, durable, and naturally digital sensors is described, along with the manner in which they have been configured to collect information for changes in the most important structural aspects. The SIMS system is designed to interrogate each sensor up to five-thousand times per second for the life of the structure, and to report sensor data back to a remote computer base for current and long-term analysis, and is directed primarily towards bridges. By suitably modifying the actuation of this very precise motion sensor, SIMS is able to track bridge deck deflection and vibration, expansion joint travel, concrete and rebar corrosion, pothole development, pier scour and tilt. Other sensors will track bolt clamp load, cable tension, and metal fatigue. All of these data are received within microseconds, which means that appropriate computer algorithm manipulations can be carried out to correlate one sensor with other sensors in real time. This internal verification feature automatically enhances confidence in the system's predictive ability and alerts the user to any anomalous behavior.

Flexible Piezoelectric Sensor-Based Gait Recognition.

PubMed

Cha, Youngsu; Kim, Hojoon; Kim, Doik

2018-02-05

Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.

Highly Stretchable and Transparent Microfluidic Strain Sensors for Monitoring Human Body Motions.

PubMed

Yoon, Sun Geun; Koo, Hyung-Jun; Chang, Suk Tai

2015-12-16

We report a new class of simple microfluidic strain sensors with high stretchability, transparency, sensitivity, and long-term stability with no considerable hysteresis and a fast response to various deformations by combining the merits of microfluidic techniques and ionic liquids. The high optical transparency of the strain sensors was achieved by introducing refractive-index matched ionic liquids into microfluidic networks or channels embedded in an elastomeric matrix. The microfluidic strain sensors offer the outstanding sensor performance under a variety of deformations induced by stretching, bending, pressing, and twisting of the microfluidic strain sensors. The principle of our microfluidic strain sensor is explained by a theoretical model based on the elastic channel deformation. In order to demonstrate its capability of practical usage, the simple-structured microfluidic strain sensors were performed onto a finger, wrist, and arm. The highly stretchable and transparent microfluidic strain sensors were successfully applied as potential platforms for distinctively monitoring a wide range of human body motions in real time. Our novel microfluidic strain sensors show great promise for making future stretchable electronic devices.

Heart Rate Monitor for Portable MP3 Player.

PubMed

Kim, Jaywoo; Lee, Mi-Hee; Lee, Hyoung-Ki; Choi, Kiwan; Bang, Seokwon; Kim, Sangryong

2005-01-01

This paper presents a photoplethysmography sensor based on a heart rate monitor for a portable MP3 player. Two major design issues are addressed: one is to acquire the sensor signal with a proper amplitude despite a wide range of variation and the other is to handle the noise contaminated signal which is caused by a motion artifact. A benchmarking test with a professional medical photoplethysmography sensor shows that our device performs very well in calculating heart rate even though our photoplethysmography sensor module was designed to be cost effective.

Fiber-based generator for wearable electronics and mobile medication.

PubMed

Zhong, Junwen; Zhang, Yan; Zhong, Qize; Hu, Qiyi; Hu, Bin; Wang, Zhong Lin; Zhou, Jun

2014-06-24

Smart garments for monitoring physiological and biomechanical signals of the human body are key sensors for personalized healthcare. However, they typically require bulky battery packs or have to be plugged into an electric plug in order to operate. Thus, a smart shirt that can extract energy from human body motions to run body-worn healthcare sensors is particularly desirable. Here, we demonstrated a metal-free fiber-based generator (FBG) via a simple, cost-effective method by using commodity cotton threads, a polytetrafluoroethylene aqueous suspension, and carbon nanotubes as source materials. The FBGs can convert biomechanical motions/vibration energy into electricity utilizing the electrostatic effect with an average output power density of ∼0.1 μW/cm(2) and have been identified as an effective building element for a power shirt to trigger a wireless body temperature sensor system. Furthermore, the FBG was demonstrated as a self-powered active sensor to quantitatively detect human motion.

OFSETH: smart medical textile for continuous monitoring of respiratory motions under magnetic resonance imaging.

PubMed

De Jonckheere, J; Narbonneau, F; Jeanne, M; Kinet, D; Witt, J; Krebber, K; Paquet, B; Depre, A; Logier, R

2009-01-01

The potential impact of optical fiber sensors embedded into medical textiles for the continuous monitoring of the patient during Magnetic Resonance Imaging is presented. We report on two pure optical sensing technologies for respiratory movements monitoring - a macro bending sensor and a Bragg grating sensor, designed to measure the elongation due to abdominal and thoracic motions during breathing. We demonstrate that the two sensors can successfully sense textile elongation between, 0% and 3%, while maintaining the stretching properties of the textile substrates for a good comfort of the patient.

Flexible wire-shaped strain sensor from cotton thread for human health and motion detection.

PubMed

Li, Yuan-Qing; Huang, Pei; Zhu, Wei-Bin; Fu, Shao-Yun; Hu, Ning; Liao, Kin

2017-03-21

In this work, a wire-shaped flexible strain sensor was fabricated by encapsulating conductive carbon thread (CT) with polydimethylsiloxane (PDMS) elastomer. The key strain sensitive material, CT, was prepared by pyrolysing cotton thread in N 2 atmosphere. The CT/PDMS composite wire shows a typical piezo-resistive behavior with high strain sensitivity. The gauge factors (GF) calculated at low strain of 0-4% and high strain of 8-10% are 8.7 and 18.5, respectively, which are much higher than that of the traditional metallic strain sensor (GF around 2). The wire-shaped CT/PDMS composite sensor shows excellent response to cyclic tensile loading within the strain range of 0-10%, the frequency range of 0.01-10 Hz, to up to 2000 cycles. The potential of the wire senor as wearable strain sensor is demonstrated by the finger motion and blood pulse monitoring. Featured by the low costs of cotton wire and PDMS resin, the simple structure and fabrication technique, as well as high performance with miniaturized size, the wire-shaped sensor based on CT/PDMS composite is believed to have a great potential for application in wearable electronics for human health and motion monitoring.

Vital sign monitoring for elderly at home: development of a compound sensor for pulse rate and motion.

PubMed

Sum, K W; Zheng, Y P; Mak, A F T

2005-01-01

This paper describes the development of a miniaturized wearable vital sign monitor which is aimed for use by elderly at home. The development of a compound sensor for pulse rate, motion, and skin temperature is reported. A pair of infrared sensor working in reflection mode was used to detect the pulse rate from various sites over the body including the wrist and finger. Meanwhile, a motion sensor was used to detect the motion of the body. In addition, the temperature on the skin surface was sensed by a semiconductor temperature sensor. A prototype has been built into a box with a dimension of 2 x 2.5 x 4 cm3. The device includes the sensors, microprocessor, circuits, battery, and a wireless transceiver for communicating data with a data terminal.

Sensitive and Flexible Polymeric Strain Sensor for Accurate Human Motion Monitoring

PubMed Central

Khan, Hassan; Kottapalli, Ajay; Asadnia, Mohsen

2018-01-01

Flexible electronic devices offer the capability to integrate and adapt with human body. These devices are mountable on surfaces with various shapes, which allow us to attach them to clothes or directly onto the body. This paper suggests a facile fabrication strategy via electrospinning to develop a stretchable, and sensitive poly (vinylidene fluoride) nanofibrous strain sensor for human motion monitoring. A complete characterization on the single PVDF nano fiber has been performed. The charge generated by PVDF electrospun strain sensor changes was employed as a parameter to control the finger motion of the robotic arm. As a proof of concept, we developed a smart glove with five sensors integrated into it to detect the fingers motion and transfer it to a robotic hand. Our results shows that the proposed strain sensors are able to detect tiny motion of fingers and successfully run the robotic hand. PMID:29389851

Electromagnetic tracking of motion in the proximity of computer generated graphical stimuli: a tutorial.

PubMed

Schnabel, Ulf H; Hegenloh, Michael; Müller, Hermann J; Zehetleitner, Michael

2013-09-01

Electromagnetic motion-tracking systems have the advantage of capturing the tempo-spatial kinematics of movements independently of the visibility of the sensors. However, they are limited in that they cannot be used in the proximity of electromagnetic field sources, such as computer monitors. This prevents exploiting the tracking potential of the sensor system together with that of computer-generated visual stimulation. Here we present a solution for presenting computer-generated visual stimulation that does not distort the electromagnetic field required for precise motion tracking, by means of a back projection medium. In one experiment, we verify that cathode ray tube monitors, as well as thin-film-transistor monitors, distort electro-magnetic sensor signals even at a distance of 18 cm. Our back projection medium, by contrast, leads to no distortion of the motion-tracking signals even when the sensor is touching the medium. This novel solution permits combining the advantages of electromagnetic motion tracking with computer-generated visual stimulation.

Telehealth Management of Parkinson's Disease Using Wearable Sensors: An Exploratory Study.

PubMed

Heldman, Dustin A; Harris, Denzil A; Felong, Timothy; Andrzejewski, Kelly L; Dorsey, E Ray; Giuffrida, Joseph P; Goldberg, Barry; Burack, Michelle A

2017-09-01

Parkinson's disease (PD) motor symptoms can fluctuate and may not be accurately reflected during a clinical evaluation. In addition, access to movement disorder specialists is limited for many with PD. The objective was to assess the impact of motion sensor-based telehealth diagnostics on PD clinical care and management. Eighteen adults with PD were randomized to control or experimental groups. All participants were instructed to use a motion sensor-based monitoring system at home one day per week, for seven months. The system included a finger-worn motion sensor and tablet-based software interface that guided patients through tasks to quantify tremor, bradykinesia, and dyskinesia. Data were processed into motor symptom severity reports, which were reviewed by a movement disorders neurologist for experimental group participants. After three months and six months, control group participants visited the clinic for a routine appointment, while experimental group participants had a videoconference or phone call instead. Home based assessments were completed with median compliance of 95.7%. For a subset of participants, the neurologist successfully used information in the reports such as quantified response to treatment or progression over time to make therapy adjustments. Changes in clinical characteristics from study start to end were not significantly different between groups. Individuals with PD were able and willing to use remote monitoring technology. Patient management aided by telehealth diagnostics provided comparable outcomes to standard care. Telehealth technologies combined with wearable sensors have the potential to improve care for disparate PD populations or those unable to travel.

Strain System for the Motion Base Shuttle Mission Simulator

NASA Technical Reports Server (NTRS)

Huber, David C.; Van Vossen, Karl G.; Kunkel, Glenn W.; Wells, Larry W.

2010-01-01

The Motion Base Shuttle Mission Simulator (MBSMS) Strain System is an innovative engineering tool used to monitor the stresses applied to the MBSMS motion platform tilt pivot frames during motion simulations in real time. The Strain System comprises hardware and software produced by several different companies. The system utilizes a series of strain gages, accelerometers, orientation sensor, rotational meter, scanners, computer, and software packages working in unison. By monitoring and recording the inputs applied to the simulator, data can be analyzed if weld cracks or other problems are found during routine simulator inspections. This will help engineers diagnose problems as well as aid in repair solutions for both current as well as potential problems.

Interfraction patient motion and implant displacement in prostate high dose rate brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fox, C. D.; Kron, T.; Leahy, M.

Purpose: To quantify movement of prostate cancer patients undergoing treatment, using an in-house developed motion sensor in order to determine a relationship between patient movement and high dose rate (HDR) brachytherapy implant displacement. Methods: An electronic motion sensor was developed based on a three axis accelerometer. HDR brachytherapy treatment for prostate is delivered at this institution in two fractions 24 h apart and 22 patients were monitored for movement over the interval between fractions. The motion sensors functioned as inclinometers, monitoring inclination of both thighs, and the inclination and roll of the abdomen. The implanted HDR brachytherapy catheter set wasmore » assessed for displacement relative to fiducial markers in the prostate. Angle measurements and angle differences over a 2 s time base were binned, and the standard deviations of the resulting frequency distributions used as a metric for patient motion in each monitored axis. These parameters were correlated to measured catheter displacement using regression modeling. Results: The mean implant displacement was 12.6 mm in the caudal direction. A mean of 19.95 h data was recorded for the patient cohort. Patients generally moved through a limited range of angles with a mean of the exception of two patients who spent in excess of 2 h lying on their side. When tested for a relationship between movement in any of the four monitored axes and the implant displacement, none was significant. Conclusions: It is not likely that patient movement influences HDR prostate implant displacement. There may be benefits to patient comfort if nursing protocols were relaxed to allow patients greater freedom to move while the implant is in situ.« less

Wearable sensors for human health monitoring

NASA Astrophysics Data System (ADS)

Asada, H. Harry; Reisner, Andrew

2006-03-01

Wearable sensors for continuous monitoring of vital signs for extended periods of weeks or months are expected to revolutionize healthcare services in the home and workplace as well as in hospitals and nursing homes. This invited paper describes recent research progress in wearable health monitoring technology and its clinical applications, with emphasis on blood pressure and circulatory monitoring. First, a finger ring-type wearable blood pressure sensor based on photo plethysmogram is presented. Technical issues, including motion artifact reduction, power saving, and wearability enhancement, will be addressed. Second, sensor fusion and sensor networking for integrating multiple sensors with diverse modalities will be discussed for comprehensive monitoring and diagnosis of health status. Unlike traditional snap-shot measurements, continuous monitoring with wearable sensors opens up the possibility to treat the physiological system as a dynamical process. This allows us to apply powerful system dynamics and control methodologies, such as adaptive filtering, single- and multi-channel system identification, active noise cancellation, and adaptive control, to the monitoring and treatment of highly complex physiological systems. A few clinical trials illustrate the potentials of the wearable sensor technology for future heath care services.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, T; Kim, D; Kang, S

Purpose: Abdominal compression is known to be effective but, often makes external-marker-based monitoring of breathing motion not feasible. In this study, we developed and evaluated a system that enables both abdominal compression and monitoring of residual abdominal motion simultaneously. The system can also provide visual-biofeedback capability. Methods: The system developed consists of a compression belt, an abdominal motion monitoring sensor (gas pressure sensor) and a visual biofeedback device. The compression belt was designed to be able to compress the frontal side of the abdomen. The pressure level of the belt is controlled by air volume and monitored in real timemore » using the gas pressure sensor. The system displays not only the real-time monitoring curve but also a guiding respiration model (e.g., a breath hold or shallow breathing curve) simultaneously on the head mounted display to help patients keep their breathing pattern as consistent as possible. Three healthy volunteers were enrolled in this pilot study and respiratory signals (pressure variations) were obtained both with and without effective abdominal compression to investigate the feasibility of the developed system. Two guidance patterns, breath hold and shallow breathing, were tested. Results: All volunteers showed smaller abdominal motion with compression (about 40% amplitude reduction compared to without compression). However, the system was able to monitor residual abdominal motion for all volunteers. Even under abdominal compression, in addition, it was possible to make the subjects successfully follow the guide patterns using the visual biofeedback system. Conclusion: The developed abdominal compression & respiratory guiding system was feasible for residual abdominal motion management. It is considered that the system can be used for a respiratory motion involved radiation therapy while maintaining the merit of abdominal compression. This work was supported by the Radiation Technology R&D program (No. 2013M2A2A7043498) and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.« less

Hybrid-Aware Model for Senior Wellness Service in Smart Home.

PubMed

Jung, Yuchae

2017-05-22

Smart home technology with situation-awareness is important for seniors to improve safety and security. With the development of context-aware computing, wearable sensor technology, and ubiquitous computing, it is easier for seniors to manage their health problem in smart home environment. For monitoring senior activity in smart home, wearable, and motion sensors-such as respiration rate (RR), electrocardiography (ECG), body temperature, and blood pressure (BP)-were used for monitoring movements of seniors. For context-awareness, environmental sensors-such as gas, fire, smoke, dust, temperature, and light sensors-were used for senior location data collection. Based on senior activity, senior health status can be classified into positive and negative. Based on senior location and time, senior safety is classified into safe and emergency. In this paper, we propose a hybrid inspection service middleware for monitoring elderly health risk based on senior activity and location. This hybrid-aware model for the detection of abnormal status of seniors has four steps as follows: (1) data collection from biosensors and environmental sensors; (2) monitoring senior location and time of stay in each location using environmental sensors; (3) monitoring senior activity using biometric data; finally, (4) expectation-maximization based decision-making step recommending proper treatment based on a senior health risk ratio.

Implementation of accelerometer sensor module and fall detection monitoring system based on wireless sensor network.

PubMed

Lee, Youngbum; Kim, Jinkwon; Son, Muntak; Lee, Myoungho

2007-01-01

This research implements wireless accelerometer sensor module and algorithm to determine wearer's posture, activity and fall. Wireless accelerometer sensor module uses ADXL202, 2-axis accelerometer sensor (Analog Device). And using wireless RF module, this module measures accelerometer signal and shows the signal at ;Acceloger' viewer program in PC. ADL algorithm determines posture, activity and fall that activity is determined by AC component of accelerometer signal and posture is determined by DC component of accelerometer signal. Those activity and posture include standing, sitting, lying, walking, running, etc. By the experiment for 30 subjects, the performance of implemented algorithm was assessed, and detection rate for postures, motions and subjects was calculated. Lastly, using wireless sensor network in experimental space, subject's postures, motions and fall monitoring system was implemented. By the simulation experiment for 30 subjects, 4 kinds of activity, 3 times, fall detection rate was calculated. In conclusion, this system can be application to patients and elders for activity monitoring and fall detection and also sports athletes' exercise measurement and pattern analysis. And it can be expected to common person's exercise training and just plaything for entertainment.

Fault detection and isolation in motion monitoring system.

PubMed

Kim, Duk-Jin; Suk, Myoung Hoon; Prabhakaran, B

2012-01-01

Pervasive computing becomes very active research field these days. A watch that can trace human movement to record motion boundary as well as to study of finding social life pattern by one's localized visiting area. Pervasive computing also helps patient monitoring. A daily monitoring system helps longitudinal study of patient monitoring such as Alzheimer's and Parkinson's or obesity monitoring. Due to the nature of monitoring sensor (on-body wireless sensor), however, signal noise or faulty sensors errors can be present at any time. Many research works have addressed these problems any with a large amount of sensor deployment. In this paper, we present the faulty sensor detection and isolation using only two on-body sensors. We have been investigating three different types of sensor errors: the SHORT error, the CONSTANT error, and the NOISY SENSOR error (see more details on section V). Our experimental results show that the success rate of isolating faulty signals are an average of over 91.5% on fault type 1, over 92% on fault type 2, and over 99% on fault type 3 with the fault prior of 30% sensor errors.

Detection of abnormal living patterns for elderly living alone using support vector data description.

PubMed

Shin, Jae Hyuk; Lee, Boreom; Park, Kwang Suk

2011-05-01

In this study, we developed an automated behavior analysis system using infrared (IR) motion sensors to assist the independent living of the elderly who live alone and to improve the efficiency of their healthcare. An IR motion-sensor-based activity-monitoring system was installed in the houses of the elderly subjects to collect motion signals and three different feature values, activity level, mobility level, and nonresponse interval (NRI). These factors were calculated from the measured motion signals. The support vector data description (SVDD) method was used to classify normal behavior patterns and to detect abnormal behavioral patterns based on the aforementioned three feature values. The simulation data and real data were used to verify the proposed method in the individual analysis. A robust scheme is presented in this paper for optimally selecting the values of different parameters especially that of the scale parameter of the Gaussian kernel function involving in the training of the SVDD window length, T of the circadian rhythmic approach with the aim of applying the SVDD to the daily behavior patterns calculated over 24 h. Accuracies by positive predictive value (PPV) were 95.8% and 90.5% for the simulation and real data, respectively. The results suggest that the monitoring system utilizing the IR motion sensors and abnormal-behavior-pattern detection with SVDD are effective methods for home healthcare of elderly people living alone.

Remote Safety Monitoring for Elderly Persons Based on Omni-Vision Analysis

PubMed Central

Xiang, Yun; Tang, Yi-ping; Ma, Bao-qing; Yan, Hang-chen; Jiang, Jun; Tian, Xu-yuan

2015-01-01

Remote monitoring service for elderly persons is important as the aged populations in most developed countries continue growing. To monitor the safety and health of the elderly population, we propose a novel omni-directional vision sensor based system, which can detect and track object motion, recognize human posture, and analyze human behavior automatically. In this work, we have made the following contributions: (1) we develop a remote safety monitoring system which can provide real-time and automatic health care for the elderly persons and (2) we design a novel motion history or energy images based algorithm for motion object tracking. Our system can accurately and efficiently collect, analyze, and transfer elderly activity information and provide health care in real-time. Experimental results show that our technique can improve the data analysis efficiency by 58.5% for object tracking. Moreover, for the human posture recognition application, the success rate can reach 98.6% on average. PMID:25978761

Sensing human physiological response using wearable carbon nanotube-based fabrics

NASA Astrophysics Data System (ADS)

Wang, Long; Loh, Kenneth J.; Koo, Helen S.

2016-04-01

Flexible and wearable sensors for human monitoring have received increased attention. Besides detecting motion and physical activity, measuring human vital signals (e.g., respiration rate and body temperature) provide rich data for assessing subjects' physiological or psychological condition. Instead of using conventional, bulky, sensing transducers, the objective of this study was to design and test a wearable, fabric-like sensing system. In particular, multi-walled carbon nanotube (MWCNT)-latex thin films of different MWCNT concentrations were first fabricated using spray coating. Freestanding MWCNT-latex films were then sandwiched between two layers of flexible fabric using iron-on adhesive to form the wearable sensor. Second, to characterize its strain sensing properties, the fabric sensors were subjected to uniaxial and cyclic tensile load tests, and they exhibited relatively stable electromechanical responses. Finally, the wearable sensors were placed on a human subject for monitoring simple motions and for validating their practical strain sensing performance. Overall, the wearable fabric sensor design exhibited advances such as flexibility, ease of fabrication, light weight, low cost, noninvasiveness, and user comfort.

Ultra-wideband radar sensors and networks

DOEpatents

Leach, Jr., Richard R; Nekoogar, Faranak; Haugen, Peter C

2013-08-06

Ultra wideband radar motion sensors strategically placed in an area of interest communicate with a wireless ad hoc network to provide remote area surveillance. Swept range impulse radar and a heart and respiration monitor combined with the motion sensor further improves discrimination.

Piezoresistive Carbon-based Hybrid Sensor for Body-Mounted Biomedical Applications

NASA Astrophysics Data System (ADS)

Melnykowycz, M.; Tschudin, M.; Clemens, F.

2017-02-01

For body-mounted sensor applications, the evolution of soft condensed matter sensor (SCMS) materials offer conformability andit enables mechanical compliance between the body surface and the sensing mechanism. A piezoresistive hybrid sensor and compliant meta-material sub-structure provided a way to engineer sensor physical designs through modification of the mechanical properties of the compliant design. A piezoresistive fiber sensor was produced by combining a thermoplastic elastomer (TPE) matrix with Carbon Black (CB) particles in 1:1 mass ratio. Feedstock was extruded in monofilament fiber form (diameter of 300 microns), resulting in a highly stretchable sensor (strain sensor range up to 100%) with linear resistance signal response. The soft condensed matter sensor was integrated into a hybrid design including a 3D printed metamaterial structure combined with a soft silicone. An auxetic unit cell was chosen (with negative Poisson’s Ratio) in the design in order to combine with the soft silicon, which exhibits a high Poisson’s Ratio. The hybrid sensor design was subjected to mechanical tensile testing up to 50% strain (with gauge factor calculation for sensor performance), and then utilized for strain-based sensing applications on the body including gesture recognition and vital function monitoring including blood pulse-wave and breath monitoring. A 10 gesture Natural User Interface (NUI) test protocol was utilized to show the effectiveness of a single wrist-mounted sensor to identify discrete gestures including finger and hand motions. These hand motions were chosen specifically for Human Computer Interaction (HCI) applications. The blood pulse-wave signal was monitored with the hand at rest, in a wrist-mounted. In addition different breathing patterns were investigated, including normal breathing and coughing, using a belt and chest-mounted configuration.

Video-based respiration monitoring with automatic region of interest detection.

PubMed

Janssen, Rik; Wang, Wenjin; Moço, Andreia; de Haan, Gerard

2016-01-01

Vital signs monitoring is ubiquitous in clinical environments and emerging in home-based healthcare applications. Still, since current monitoring methods require uncomfortable sensors, respiration rate remains the least measured vital sign. In this paper, we propose a video-based respiration monitoring method that automatically detects a respiratory region of interest (RoI) and signal using a camera. Based on the observation that respiration induced chest/abdomen motion is an independent motion system in a video, our basic idea is to exploit the intrinsic properties of respiration to find the respiratory RoI and extract the respiratory signal via motion factorization. We created a benchmark dataset containing 148 video sequences obtained on adults under challenging conditions and also neonates in the neonatal intensive care unit (NICU). The measurements obtained by the proposed video respiration monitoring (VRM) method are not significantly different from the reference methods (guided breathing or contact-based ECG; p-value  =  0.6), and explain more than 99% of the variance of the reference values with low limits of agreement (-2.67 to 2.81 bpm). VRM seems to provide a valid solution to ECG in confined motion scenarios, though precision may be reduced for neonates. More studies are needed to validate VRM under challenging recording conditions, including upper-body motion types.

Hybrid motion sensing and experimental modal analysis using collocated smartphone camera and accelerometers

NASA Astrophysics Data System (ADS)

Ozer, Ekin; Feng, Dongming; Feng, Maria Q.

2017-10-01

State-of-the-art multisensory technologies and heterogeneous sensor networks propose a wide range of response measurement opportunities for structural health monitoring (SHM). Measuring and fusing different physical quantities in terms of structural vibrations can provide alternative acquisition methods and improve the quality of the modal testing results. In this study, a recently introduced SHM concept, SHM with smartphones, is focused to utilize multisensory smartphone features for a hybridized structural vibration response measurement framework. Based on vibration testing of a small-scale multistory laboratory model, displacement and acceleration responses are monitored using two different smartphone sensors, an embedded camera and accelerometer, respectively. Double-integration or differentiation among different measurement types is performed to combine multisensory measurements on a comparative basis. In addition, distributed sensor signals from collocated devices are processed for modal identification, and performance of smartphone-based sensing platforms are tested under different configuration scenarios and heterogeneity levels. The results of these tests show a novel and successful implementation of a hybrid motion sensing platform through multiple sensor type and device integration. Despite the heterogeneity of motion data obtained from different smartphone devices and technologies, it is shown that multisensory response measurements can be blended for experimental modal analysis. Getting benefit from the accessibility of smartphone technology, similar smartphone-based dynamic testing methodologies can provide innovative SHM solutions with mobile, programmable, and cost-free interfaces.

A Study on the Performance of Low Cost MEMS Sensors in Strong Motion Studies

NASA Astrophysics Data System (ADS)

Tanırcan, Gulum; Alçık, Hakan; Kaya, Yavuz; Beyen, Kemal

2017-04-01

Recent advances in sensors have helped the growth of local networks. In recent years, many Micro Electro Mechanical System (MEMS)-based accelerometers have been successfully used in seismology and earthquake engineering projects. This is basically due to the increased precision obtained in these downsized instruments. Moreover, they are cheaper alternatives to force-balance type accelerometers. In Turkey, though MEMS-based accelerometers have been used in various individual applications such as magnitude and location determination of earthquakes, structural health monitoring, earthquake early warning systems, MEMS-based strong motion networks are not currently available in other populated areas of the country. Motivation of this study comes from the fact that, if MEMS sensors are qualified to record strong motion parameters of large earthquakes, a dense network can be formed in an affordable price at highly populated areas. The goals of this study are 1) to test the performance of MEMS sensors, which are available in the inventory of the Institute through shake table tests, and 2) to setup a small scale network for observing online data transfer speed to a trusted in-house routine. In order to evaluate the suitability of sensors in strong motion related studies, MEMS sensors and a reference sensor are tested under excitations of sweeping waves as well as scaled earthquake recordings. Amplitude response and correlation coefficients versus frequencies are compared. As for earthquake recordings, comparisons are carried out in terms of strong motion(SM) parameters (PGA, PGV, AI, CAV) and elastic response of structures (Sa). Furthermore, this paper also focuses on sensitivity and selectivity for sensor performances in time-frequency domain to compare different sensing characteristics and analyzes the basic strong motion parameters that influence the design majors. Results show that the cheapest MEMS sensors under investigation are able to record the mid-frequency dominant SM parameters PGV and CAV with high correlation. PGA and AI, the high frequency components of the ground motion, are underestimated. Such a difference, on the other hand, does not manifest itself on intensity estimations. PGV and CAV values from the reference and MEMS sensors converge to the same seismic intensity level. Hence a strong motion network with MEMS sensors could be a modest option to produce PGV-based damage impact of an urban area under large magnitude earthquake threats in the immediate vicinity.

Transparent and stretchable strain sensors based on metal nanowire microgrids for human motion monitoring

NASA Astrophysics Data System (ADS)

Cho, Ji Hwan; Ha, Sung-Hun; Kim, Jong-Man

2018-04-01

Optical transparency is increasingly considered as one of the most important characteristics required in advanced stretchable strain sensors for application in body-attachable systems. In this paper, we present an entirely solution-processed fabrication route to highly transparent and stretchable resistive strain sensors based on silver nanowire microgrids (AgNW-MGs). The AgNW-MG strain sensors are readily prepared by patterning the AgNWs on a stretchable substrate into a MG geometry via a mesh-template-assisted contact-transfer printing. The MG has a unique architecture comprising the AgNWs and can be stretched to ɛ = 35%, with high gauge factors of ˜6.9 for ɛ = 0%-30% and ˜41.1 for ɛ = 30%-35%. The sensor also shows a high optical transmittance of 77.1% ± 1.5% (at 550 nm) and stably maintains the remarkable optical performance even at high strains. In addition, the sensor responses are found to be highly reversible with negligible hysteresis and are reliable even under repetitive stretching-releasing cycles (1000 cycles at ɛ = 10%). The practicality of the AgNW-MG strain sensor is confirmed by successfully monitoring a wide range of human motions in real time after firmly laminating the device onto various body parts.

Self-sensing paper-based actuators employing ferromagnetic nanoparticles and graphite

NASA Astrophysics Data System (ADS)

Phan, Hoang-Phuong; Dinh, Toan; Nguyen, Tuan-Khoa; Vatani, Ashkan; Md Foisal, Abu Riduan; Qamar, Afzaal; Kermany, Atieh Ranjbar; Dao, Dzung Viet; Nguyen, Nam-Trung

2017-04-01

Paper-based microfluidics and sensors have attracted great attention. Although a large number of paper-based devices have been developed, surprisingly there are only a few studies investigating paper actuators. To fulfill the requirements for the integration of both sensors and actuators into paper, this work presents an unprecedented platform which utilizes ferromagnetic particles for actuation and graphite for motion monitoring. The use of the integrated mechanical sensing element eliminates the reliance on image processing for motion detection and also allows real-time measurements of the dynamic response in paper-based actuators. The proposed platform can also be quickly fabricated using a simple process, indicating its potential for controllable paper-based lab on chip.

A System for Video Surveillance and Monitoring CMU VSAM Final Report

DTIC Science & Technology

1999-11-30

motion-based skeletonization, neural network , spatio-temporal salience Patterns inside image chips, spurious motion rejection, model -based... network of sensors with respect to the model coordinate system, computation of 3D geolocation estimates, and graphical display of object hypotheses...rithms have been developed. The first uses view dependent visual properties to train a neural network classifier to recognize four classes: single

A novel dynamic sensing of wearable digital textile sensor with body motion analysis.

PubMed

Yang, Chang-Ming; Lin, Zhan-Sheng; Hu, Chang-Lin; Chen, Yu-Shih; Ke, Ling-Yi; Chen, Yin-Rui

2010-01-01

This work proposes an innovative textile sensor system to monitor dynamic body movement and human posture by attaching wearable digital sensors to analyze body motion. The proposed system can display and analyze signals when individuals are walking, running, veering around, walking up and down stairs, as well as falling down with a wearable monitoring system, which reacts to the coordination between the body and feet. Several digital sensor designs are embedded in clothing and wear apparel. Any pressure point can determine which activity is underway. Importantly, wearable digital sensors and a wearable monitoring system allow adaptive, real-time postures, real time velocity, acceleration, non-invasive, transmission healthcare, and point of care (POC) for home and non-clinical environments.

Noncontact respiration-monitoring system using fiber grating sensor

NASA Astrophysics Data System (ADS)

Sato, Isao; Nakajima, Masato

2004-10-01

In this research, the new non-contact breathing motion monitoring system using Fiber Grating 3-dimension Sensor is used to measure the respiratory movement of the chest and the abdomen and the shape of the human body simultaneously. Respiratory trouble during sleep brings about various kinds of diseases. Particularly, Sleep Apnea Syndrome (SAS), which restricts respiration during sleep, has been in the spotlight in recent years. However, present equipment for analyzing the blessing motion requires attaching various sensors on the patient's body. This system adopted two CCD cameras to measure the movements of projected infrared bright spots on the patient's body which measure the body form, breathing motion of the chest and breathing motion of the abdomen in detail. Since the equipment does not contact the patient's body, the patient feels incompatibility, and there is no necessity to worry about the equipment coming off. Sleep Apnea Syndrome is classified into three types by their respiratory pattern-Obstructive, Central and Mixed SAS based on the characteristic. This paper reports the method of diagnosing SAS automatically. It is thought that this method will be helpful not only for the diagnosis of SAS but also for the diagnosis of other kinds of complicated respiratory disease.

Welding technology transfer task/laser based weld joint tracking system for compressor girth welds

NASA Technical Reports Server (NTRS)

Looney, Alan

1991-01-01

Sensors to control and monitor welding operations are currently being developed at Marshall Space Flight Center. The laser based weld bead profiler/torch rotation sensor was modified to provide a weld joint tracking system for compressor girth welds. The tracking system features a precision laser based vision sensor, automated two-axis machine motion, and an industrial PC controller. The system benefits are elimination of weld repairs caused by joint tracking errors which reduces manufacturing costs and increases production output, simplification of tooling, and free costly manufacturing floor space.

Structural action recognition in body sensor networks: distributed classification based on string matching.

PubMed

Ghasemzadeh, Hassan; Loseu, Vitali; Jafari, Roozbeh

2010-03-01

Mobile sensor-based systems are emerging as promising platforms for healthcare monitoring. An important goal of these systems is to extract physiological information about the subject wearing the network. Such information can be used for life logging, quality of life measures, fall detection, extraction of contextual information, and many other applications. Data collected by these sensor nodes are overwhelming, and hence, an efficient data processing technique is essential. In this paper, we present a system using inexpensive, off-the-shelf inertial sensor nodes that constructs motion transcripts from biomedical signals and identifies movements by taking collaboration between the nodes into consideration. Transcripts are built of motion primitives and aim to reduce the complexity of the original data. We then label each primitive with a unique symbol and generate a sequence of symbols, known as motion template, representing a particular action. This model leads to a distributed algorithm for action recognition using edit distance with respect to motion templates. The algorithm reduces the number of active nodes during every classification decision. We present our results using data collected from five normal subjects performing transitional movements. The results clearly illustrate the effectiveness of our framework. In particular, we obtain a classification accuracy of 84.13% with only one sensor node involved in the classification process.

Low-cost, distributed, sensor-based weigh-in-motion systems.

DOT National Transportation Integrated Search

2009-12-01

Monitoring truck weights is essential for traffic operations, roadway design, traffic safety, and regulations. : Traditional roadside static truck weighing stations have many operational shortcomings, and so there have : been ongoing efforts to devel...

Real-time weigh-in-motion measurement using fiber Bragg grating sensors

NASA Astrophysics Data System (ADS)

Huang, Ying; Palek, Leonard; Strommen, Robert; Worel, Ben; Chen, Genda

2014-03-01

Overloading truck loads have long been one of the key reasons for accelerating road damage, especially in rural regions where the design loads are expected to be small and in the cold regions where the wet-and-dry cycle places a significant role. To control the designed traffic loads and further guide the road design in future, periodical weight stations have been implemented for double check of the truck loads. The weight stations give chances for missing measurement of overloaded vehicles, slow down the traffic, and require additional labors. Infrastructure weight-in-motion sensors, on the other hand, keep consistent traffic flow and monitor all types of vehicles on roads. However, traditional electrical weight-in-motion sensors showed high electromagnetic interference (EMI), high dependence on environmental conditions such as moisture, and relatively short life cycle, which are unreliable for long-term weigh-inmotion measurements. Fiber Bragg grating (FBG) sensors, with unique advantages of compactness, immune to EMI and moisture, capability of quasi-distributed sensing, and long life cycle, will be a perfect candidate for long-term weigh-in-motion measurements. However, the FBG sensors also surfer from their frangible nature of glass materials for a good survive rate during sensor installation. In this study, the FBG based weight-in-motion sensors were packaged by fiber reinforced polymer (FRP) materials and further validated at MnROAD facility, Minnesota DOT (MnDOT). The design and layout of the FRP-FBG weight-in-motion sensors, their field test setup, data acquisition, and data analysis will be presented. Upon validation, the FRP-FBG sensors can be applied weigh-in-motion measurement to assistant road managements.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Polese, Luigi Gentile; Brackney, Larry

An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generatesmore » an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.« less

Monitoring eating habits using a piezoelectric sensor-based necklace.

PubMed

Kalantarian, Haik; Alshurafa, Nabil; Le, Tuan; Sarrafzadeh, Majid

2015-03-01

Maintaining appropriate levels of food intake and developing regularity in eating habits is crucial to weight loss and the preservation of a healthy lifestyle. Moreover, awareness of eating habits is an important step towards portion control and weight loss. In this paper, we introduce a novel food-intake monitoring system based around a wearable wireless-enabled necklace. The proposed necklace includes an embedded piezoelectric sensor, small Arduino-compatible microcontroller, Bluetooth LE transceiver, and Lithium-Polymer battery. Motion in the throat is captured and transmitted to a mobile application for processing and user guidance. Results from data collected from 30 subjects indicate that it is possible to detect solid and liquid foods, with an F-measure of 0.837 and 0.864, respectively, using a naive Bayes classifier. Furthermore, identification of extraneous motions such as head turns and walking are shown to significantly reduce the false positive rate of swallow detection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Accurate respiration measurement using DC-coupled continuous-wave radar sensor for motion-adaptive cancer radiotherapy.

PubMed

Gu, Changzhan; Li, Ruijiang; Zhang, Hualiang; Fung, Albert Y C; Torres, Carlos; Jiang, Steve B; Li, Changzhi

2012-11-01

Accurate respiration measurement is crucial in motion-adaptive cancer radiotherapy. Conventional methods for respiration measurement are undesirable because they are either invasive to the patient or do not have sufficient accuracy. In addition, measurement of external respiration signal based on conventional approaches requires close patient contact to the physical device which often causes patient discomfort and undesirable motion during radiation dose delivery. In this paper, a dc-coupled continuous-wave radar sensor was presented to provide a noncontact and noninvasive approach for respiration measurement. The radar sensor was designed with dc-coupled adaptive tuning architectures that include RF coarse-tuning and baseband fine-tuning, which allows the radar sensor to precisely measure movement with stationary moment and always work with the maximum dynamic range. The accuracy of respiration measurement with the proposed radar sensor was experimentally evaluated using a physical phantom, human subject, and moving plate in a radiotherapy environment. It was shown that respiration measurement with radar sensor while the radiation beam is on is feasible and the measurement has a submillimeter accuracy when compared with a commercial respiration monitoring system which requires patient contact. The proposed radar sensor provides accurate, noninvasive, and noncontact respiration measurement and therefore has a great potential in motion-adaptive radiotherapy.

Self-powered Real-time Movement Monitoring Sensor Using Triboelectric Nanogenerator Technology.

PubMed

Jin, Liangmin; Tao, Juan; Bao, Rongrong; Sun, Li; Pan, Caofeng

2017-09-05

The triboelectric nanogenerator (TENG) has great potential in the field of self-powered sensor fabrication. Recently, smart electronic devices and movement monitoring sensors have attracted the attention of scientists because of their application in the field of artificial intelligence. In this article, a TENG finger movement monitoring, self-powered sensor has been designed and analysed. Under finger movements, the TENG realizes the contact and separation to convert the mechanical energy into electrical signal. A pulse output current of 7.8 μA is generated by the bending and straightening motions of the artificial finger. The optimal output power can be realized when the external resistance is approximately 30 MΩ. The random motions of the finger are detected by the system with multiple TENG sensors in series. This type of flexible and self-powered sensor has potential applications in artificial intelligence and robot manufacturing.

Method for measuring tri-axial lumbar motion angles using wearable sheet stretch sensors

PubMed Central

Nakamoto, Hiroyuki; Yamaji, Tokiya; Ootaka, Hideo; Bessho, Yusuke; Nakamura, Ryo; Ono, Rei

2017-01-01

Background Body movements, such as trunk flexion and rotation, are risk factors for low back pain in occupational settings, especially in healthcare workers. Wearable motion capture systems are potentially useful to monitor lower back movement in healthcare workers to help avoid the risk factors. In this study, we propose a novel system using sheet stretch sensors and investigate the system validity for estimating lower back movement. Methods Six volunteers (female:male = 1:1, mean age: 24.8 ± 4.0 years, height 166.7 ± 5.6 cm, weight 56.3 ± 7.6 kg) participated in test protocols that involved executing seven types of movements. The movements were three uniaxial trunk movements (i.e., trunk flexion-extension, trunk side-bending, and trunk rotation) and four multiaxial trunk movements (i.e., flexion + rotation, flexion + side-bending, side-bending + rotation, and moving around the cranial–caudal axis). Each trial lasted for approximately 30 s. Four stretch sensors were attached to each participant’s lower back. The lumbar motion angles were estimated using simple linear regression analysis based on the stretch sensor outputs and compared with those obtained by the optical motion capture system. Results The estimated lumbar motion angles showed a good correlation with the actual angles, with correlation values of r = 0.68 (SD = 0.35), r = 0.60 (SD = 0.19), and r = 0.72 (SD = 0.18) for the flexion-extension, side bending, and rotation movements, respectively (all P < 0.05). The estimation errors in all three directions were less than 3°. Conclusion The stretch sensors mounted on the back provided reasonable estimates of the lumbar motion angles. The novel motion capture system provided three directional angles without capture space limits. The wearable system possessed great potential to monitor the lower back movement in healthcare workers and helping prevent low back pain. PMID:29020053

Real-Time Telemetry System for Monitoring Motion of Ships Based on Inertial Sensors.

PubMed

Núñez, José M; Araújo, Marta G; García-Tuñón, I

2017-04-25

A telemetry system for real-time monitoring of the motions, position, speed and course of a ship at sea is presented in this work. The system, conceived as a subsystem of a radar cross-section measurement unit, could also be used in other applications as ships dynamics characterization, on-board cranes, antenna stabilizers, etc. This system was designed to be stand-alone, reliable, easy to deploy, low-cost and free of requirements related to stabilization procedures. In order to achieve such a unique combination of functionalities, we have developed a telemetry system based on redundant inertial and magnetic sensors and GPS (Global Positioning System) measurements. It provides a proper data storage and also has real-time radio data transmission capabilities to an on-shore station. The output of the system can be used either for on-line or off-line processing. Additionally, the system uses dual technologies and COTS (Commercial Off-The-Shelf) components. Motion-positioning measurements and radio data link tests were successfully carried out in several ships of the Spanish Navy, proving the compliance with the design targets and validating our telemetry system.

Software Defined Doppler Radar as a Contactless Multipurpose Microwave Sensor for Vibrations Monitoring.

PubMed

Raffo, Antonio; Costanzo, Sandra; Di Massa, Giuseppe

2017-01-08

A vibration sensor based on the use of a Software-Defined Radio (SDR) platform is adopted in this work to provide a contactless and multipurpose solution for low-cost real-time vibrations monitoring. In order to test the vibration detection ability of the proposed non-contact method, a 1 GHz Doppler radar sensor is simulated and successfully assessed on targets at various distances, with various oscillation frequencies and amplitudes. Furthermore, an SDR Doppler platform is practically realized, and preliminary experimental validations on a device able to produce a harmonic motion are illustrated to prove the effectiveness of the proposed approach.

Thermal noise variance of a receive radiofrequency coil as a respiratory motion sensor.

PubMed

Andreychenko, A; Raaijmakers, A J E; Sbrizzi, A; Crijns, S P M; Lagendijk, J J W; Luijten, P R; van den Berg, C A T

2017-01-01

Development of a passive respiratory motion sensor based on the noise variance of the receive coil array. Respiratory motion alters the body resistance. The noise variance of an RF coil depends on the body resistance and, thus, is also modulated by respiration. For the noise variance monitoring, the noise samples were acquired without and with MR signal excitation on clinical 1.5/3 T MR scanners. The performance of the noise sensor was compared with the respiratory bellow and with the diaphragm displacement visible on MR images. Several breathing patterns were tested. The noise variance demonstrated a periodic, temporal modulation that was synchronized with the respiratory bellow signal. The modulation depth of the noise variance resulting from the respiration varied between the channels of the array and depended on the channel's location with respect to the body. The noise sensor combined with MR acquisition was able to detect the respiratory motion for every k-space read-out line. Within clinical MR systems, the respiratory motion can be detected by the noise in receive array. The noise sensor does not require careful positioning unlike the bellow, any additional hardware, and/or MR acquisition. Magn Reson Med 77:221-228, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

High Sensitivity, Wearable, Piezoresistive Pressure Sensors Based on Irregular Microhump Structures and Its Applications in Body Motion Sensing.

PubMed

Wang, Zongrong; Wang, Shan; Zeng, Jifang; Ren, Xiaochen; Chee, Adrian J Y; Yiu, Billy Y S; Chung, Wai Choi; Yang, Yong; Yu, Alfred C H; Roberts, Robert C; Tsang, Anderson C O; Chow, Kwok Wing; Chan, Paddy K L

2016-07-01

A pressure sensor based on irregular microhump patterns has been proposed and developed. The devices show high sensitivity and broad operating pressure regime while comparing with regular micropattern devices. Finite element analysis (FEA) is utilized to confirm the sensing mechanism and predict the performance of the pressure sensor based on the microhump structures. Silicon carbide sandpaper is employed as the mold to develop polydimethylsiloxane (PDMS) microhump patterns with various sizes. The active layer of the piezoresistive pressure sensor is developed by spin coating PSS on top of the patterned PDMS. The devices show an averaged sensitivity as high as 851 kPa(-1) , broad operating pressure range (20 kPa), low operating power (100 nW), and fast response speed (6.7 kHz). Owing to their flexible properties, the devices are applied to human body motion sensing and radial artery pulse. These flexible high sensitivity devices show great potential in the next generation of smart sensors for robotics, real-time health monitoring, and biomedical applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Monitoring stage fright outside the laboratory: an example in a professional musician using wearable sensors.

PubMed

Kusserow, Martin; Candia, Victor; Amft, Oliver; Hildebrandt, Horst; Folkers, Gerd; Tröster, Gerhard

2012-03-01

We implemented and tested a wearable sensor system to measure patterns of stress responses in a professional musician under public performance conditions. Using this sensor system, we monitored the cellist's heart activity, the motion of multiple body parts, and their gradual changes during three repeated performances of a skill-demanding piece in front of a professional audience. From the cellist and her teachers, we collected stage fright self-reports and performance ratings that were related to our sensor data analysis results. Concomitant to changes in body motion and heart rate, the cellist perceived a reduction in stage fright. Performance quality was objectively improved, as technical playing errors decreased throughout repeated renditions. In particular, from performance 1 to 3, the wearable sensors measured a significant increase in the cellist's bowing motion dynamics of approximately 6% and a decrease in heart rate. Bowing motion showed a marginal correlation to the observed heart rate patterns during playing. The wearable system did not interfere with the cellist's performance, thereby allowing investigation of stress responses during natural public performances.

Blood monitoring systems and methods thereof

NASA Technical Reports Server (NTRS)

Zander, Dennis (Inventor); Mir, Jose (Inventor)

2012-01-01

A blood monitoring system is capable of monitoring the blood of a subject in vivo. The blood monitoring system comprises: 1) an array of movable microneedle micromachined within associated wells; 2) array of motion actuators able to move each needle in and out of their associated wells; 3) array of microvalves associated with each microneedle able to control the flow of air around the microneedle; 4) an array of chemical sensors inserted into patient by movable microneedles; 5) an array of inductors able to measure chemical concentration in the vicinity of inserted chemical sensors; 6) conducting vias that provide timed actuating signal signals from a control system to each motion actuator; 7) conducting vias that transmit signal produced by array of chemical sensors to the control system for processing, although the blood monitoring system can comprise other numbers and types of elements in other configurations.

Monitoring diver kinematics with dielectric elastomer sensors

NASA Astrophysics Data System (ADS)

Walker, Christopher R.; Anderson, Iain A.

2017-04-01

Diving, initially motivated for food purposes, is crucial to the oil and gas industry, search and rescue, and is even done recreationally by millions of people. There is a growing need however, to monitor the health and activity of divers. The Divers Alert Network has reported on average 90 fatalities per year since 1980. Furthermore an estimated 1000 divers require recompression treatment for dive-related injuries every year. One means of monitoring diver activity is to integrate strain sensors into a wetsuit. This would provide kinematic information on the diver potentially improving buoyancy control assessment, providing a platform for gesture communication, detecting panic attacks and monitoring diver fatigue. To explore diver kinematic monitoring we have coupled dielectric elastomer sensors to a wetsuit worn by the pilot of a human-powered wet submarine. This provided a unique platform to test the performance and accuracy of dielectric elastomer strain sensors in an underwater application. The aim of this study was to assess the ability of strain sensors to monitor the kinematics of a diver. This study was in collaboration with the University of Auckland's human-powered submarine team, Team Taniwha. The pilot, completely encapsulated in a hull, pedals to propel the submarine forward. Therefore this study focused on leg motion as that is the primary motion of the submarine pilot. Four carbon-filled silicone dielectric elastomer sensors were fabricated and coupled to the pilot's wetsuit. The first two sensors were attached over the knee joints, with the remaining two attached between the pelvis and thigh. The goal was to accurately measure leg joint angles thereby determining the position of each leg relative to the hip. A floating data acquisition unit monitored the sensors and transmitted data packets to a nearby computer for real-time processing. A GoPro Hero 4 silver edition was used to capture the experiments and provide a means of post-validation. The ability of the sensors to measure joint angles was assessed by examining GoPro footage in the image processing software, ImageJ. This paper applies dielectric elastomer sensor technology to monitoring the leg motion of a diver. The experimental set-up and results are presented and discussed.

A Movement-Assisted Deployment of Collaborating Autonomous Sensors for Indoor and Outdoor Environment Monitoring

PubMed Central

Niewiadomska-Szynkiewicz, Ewa; Sikora, Andrzej; Marks, Michał

2016-01-01

Using mobile robots or unmanned vehicles to assist optimal wireless sensors deployment in a working space can significantly enhance the capability to investigate unknown environments. This paper addresses the issues of the application of numerical optimization and computer simulation techniques to on-line calculation of a wireless sensor network topology for monitoring and tracking purposes. We focus on the design of a self-organizing and collaborative mobile network that enables a continuous data transmission to the data sink (base station) and automatically adapts its behavior to changes in the environment to achieve a common goal. The pre-defined and self-configuring approaches to the mobile-based deployment of sensors are compared and discussed. A family of novel algorithms for the optimal placement of mobile wireless devices for permanent monitoring of indoor and outdoor dynamic environments is described. They employ a network connectivity-maintaining mobility model utilizing the concept of the virtual potential function for calculating the motion trajectories of platforms carrying sensors. Their quality and utility have been justified through simulation experiments and are discussed in the final part of the paper. PMID:27649186

A Movement-Assisted Deployment of Collaborating Autonomous Sensors for Indoor and Outdoor Environment Monitoring.

PubMed

Niewiadomska-Szynkiewicz, Ewa; Sikora, Andrzej; Marks, Michał

2016-09-14

Using mobile robots or unmanned vehicles to assist optimal wireless sensors deployment in a working space can significantly enhance the capability to investigate unknown environments. This paper addresses the issues of the application of numerical optimization and computer simulation techniques to on-line calculation of a wireless sensor network topology for monitoring and tracking purposes. We focus on the design of a self-organizing and collaborative mobile network that enables a continuous data transmission to the data sink (base station) and automatically adapts its behavior to changes in the environment to achieve a common goal. The pre-defined and self-configuring approaches to the mobile-based deployment of sensors are compared and discussed. A family of novel algorithms for the optimal placement of mobile wireless devices for permanent monitoring of indoor and outdoor dynamic environments is described. They employ a network connectivity-maintaining mobility model utilizing the concept of the virtual potential function for calculating the motion trajectories of platforms carrying sensors. Their quality and utility have been justified through simulation experiments and are discussed in the final part of the paper.

Monitoring Aircraft Motion at Airports by LIDAR

NASA Astrophysics Data System (ADS)

Toth, C.; Jozkow, G.; Koppanyi, Z.; Young, S.; Grejner-Brzezinska, D.

2016-06-01

Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.

Capacitive Pressure Sensor with High Sensitivity and Fast Response to Dynamic Interaction Based on Graphene and Porous Nylon Networks.

PubMed

He, Zhongfu; Chen, Wenjun; Liang, Binghao; Liu, Changyong; Yang, Leilei; Lu, Dongwei; Mo, Zichao; Zhu, Hai; Tang, Zikang; Gui, Xuchun

2018-04-18

Flexible pressure sensors are of great importance to be applied in artificial intelligence and wearable electronics. However, assembling a simple structure, high-performance capacitive pressure sensor, especially for monitoring the flow of liquids, is still a big challenge. Here, on the basis of a sandwich-like structure, we propose a facile capacitive pressure sensor optimized by a flexible, low-cost nylon netting, showing many merits including a high response sensitivity (0.33 kPa -1 ) in a low-pressure regime (<1 kPa), an ultralow detection limit as 3.3 Pa, excellent working stability after more than 1000 cycles, and synchronous monitoring for human pulses and clicks. More important, this sensor exhibits an ultrafast response speed (<20 ms), which enables its detection for the fast variations of a small applied pressure from the morphological changing processes of a droplet falling onto the sensor. Furthermore, a capacitive pressure sensor array is fabricated for demonstrating the ability to spatial pressure distribution. Our developed pressure sensors show great prospects in practical applications such as health monitoring, flexible tactile devices, and motion detection.

Flexible one-structure arched triboelectric nanogenerator based on common electrode for high efficiency energy harvesting and self-powered motion sensing

NASA Astrophysics Data System (ADS)

Chen, Xi; He, Jian; Song, Linlin; Zhang, Zengxing; Tian, Zhumei; Wen, Tao; Zhai, Cong; Chen, Yi; Cho, Jundong; Chou, Xiujian; Xue, Chenyang

2018-04-01

Triboelectric nanogenerators are widely used because of low cost, simple manufacturing process and high output performance. In this work, a flexible one-structure arched triboelectric nanogenerator (FOAT), based on common electrode to combine the single-electrode mode and contact-separation, was designed using silicone rubber, epoxy resin and flexible electrode. The peak-to-peak short circuit current of 18μ A and the peak-to-peak open circuit voltage of 570V can be obtained from the FOAT with the size of 5×7 cm2 under the frequency of 3Hz and the pressure of 300N. The peak-to-peak short circuit current of FOAT is increased by 29% and 80%, and the peak-to-peak open circuit voltage is increased by 33% and 54% compared with single-electrode mode and contact-separation mode, respectively. FOAT realizes the combination of two generation modes, which improves the output performance of triboelectric nanogenerator (TENG). 62 light-emitting-diodes (LEDs) can be completely lit up and 2.2μ F capacitor can be easily charged to 1.2V in 9s. When the FOAT is placed at different parts of the human body, the human motion energy can be harvested and be the sensing signal for motion monitoring sensor. Based on the above characteristics, FOAT exhibits great potential in illumination, power supplies for wearable electronic devices and self-powered motion monitoring sensor via harvesting the energy of human motion.

A system for respiratory motion detection using optical fibers embedded into textiles.

PubMed

D'Angelo, L T; Weber, S; Honda, Y; Thiel, T; Narbonneau, F; Luth, T C

2008-01-01

In this contribution, a first prototype for mobile respiratory motion detection using optical fibers embedded into textiles is presented. The developed system consists of a T-shirt with an integrated fiber sensor and a portable monitoring unit with a wireless communication link enabling the data analysis and visualization on a PC. A great effort is done worldwide to develop mobile solutions for health monitoring of vital signs for patients needing continuous medical care. Wearable, comfortable and smart textiles incorporating sensors are good approaches to solve this problem. In most of the cases, electrical sensors are integrated, showing significant limits such as for the monitoring of anaesthetized patients during Magnetic Resonance Imaging (MRI). OFSETH (Optical Fibre Embedded into technical Textile for Healthcare) uses optical sensor technologies to extend the current capabilities of medical technical textiles.

Beyond Line-of-Sight Information Dissemination for Force Protection

DTIC Science & Technology

2012-11-01

utilize ad hoc, mesh networks to support data-in-motion and remote data storage and access. These types of sensors are common among Force Protection...Operations and Forward Operating Base security . Current Force Protection Kits include a rich set of sensors that can be monitored from a core operator...and tactical war fighters in tactical network environments . Marti has the potential to improve situation awareness and Force Protection for

Physical activity classification using time-frequency signatures of motion artifacts in multi-channel electrical impedance plethysmographs.

PubMed

Khan, Hassan Aqeel; Gore, Amit; Ashe, Jeff; Chakrabartty, Shantanu

2017-07-01

Physical activities are known to introduce motion artifacts in electrical impedance plethysmographic (EIP) sensors. Existing literature considers motion artifacts as a nuisance and generally discards the artifact containing portion of the sensor output. This paper examines the notion of exploiting motion artifacts for detecting the underlying physical activities which give rise to the artifacts in question. In particular, we investigate whether the artifact pattern associated with a physical activity is unique; and does it vary from one human-subject to another? Data was recorded from 19 adult human-subjects while conducting 5 distinct, artifact inducing, activities. A set of novel features based on the time-frequency signatures of the sensor outputs are then constructed. Our analysis demonstrates that these features enable high accuracy detection of the underlying physical activity. Using an SVM classifier we are able to differentiate between 5 distinct physical activities (coughing, reaching, walking, eating and rolling-on-bed) with an average accuracy of 85.46%. Classification is performed solely using features designed specifically to capture the time-frequency signatures of different physical activities. This enables us to measure both respiratory and motion information using only one type of sensor. This is in contrast to conventional approaches to physical activity monitoring; which rely on additional hardware such as accelerometers to capture activity information.

Real-Time Telemetry System for Monitoring Motion of Ships Based on Inertial Sensors

PubMed Central

Núñez, José M.; Araújo, Marta G.; García-Tuñón, I.

2017-01-01

A telemetry system for real-time monitoring of the motions, position, speed and course of a ship at sea is presented in this work. The system, conceived as a subsystem of a radar cross-section measurement unit, could also be used in other applications as ships dynamics characterization, on-board cranes, antenna stabilizers, etc. This system was designed to be stand-alone, reliable, easy to deploy, low-cost and free of requirements related to stabilization procedures. In order to achieve such a unique combination of functionalities, we have developed a telemetry system based on redundant inertial and magnetic sensors and GPS (Global Positioning System) measurements. It provides a proper data storage and also has real-time radio data transmission capabilities to an on-shore station. The output of the system can be used either for on-line or off-line processing. Additionally, the system uses dual technologies and COTS (Commercial Off-The-Shelf) components. Motion-positioning measurements and radio data link tests were successfully carried out in several ships of the Spanish Navy, proving the compliance with the design targets and validating our telemetry system. PMID:28441330

Hybrid-Aware Model for Senior Wellness Service in Smart Home

PubMed Central

Jung, Yuchae

2017-01-01

Smart home technology with situation-awareness is important for seniors to improve safety and security. With the development of context-aware computing, wearable sensor technology, and ubiquitous computing, it is easier for seniors to manage their health problem in smart home environment. For monitoring senior activity in smart home, wearable, and motion sensors—such as respiration rate (RR), electrocardiography (ECG), body temperature, and blood pressure (BP)—were used for monitoring movements of seniors. For context-awareness, environmental sensors—such as gas, fire, smoke, dust, temperature, and light sensors—were used for senior location data collection. Based on senior activity, senior health status can be classified into positive and negative. Based on senior location and time, senior safety is classified into safe and emergency. In this paper, we propose a hybrid inspection service middleware for monitoring elderly health risk based on senior activity and location. This hybrid-aware model for the detection of abnormal status of seniors has four steps as follows: (1) data collection from biosensors and environmental sensors; (2) monitoring senior location and time of stay in each location using environmental sensors; (3) monitoring senior activity using biometric data; finally, (4) expectation-maximization based decision-making step recommending proper treatment based on a senior health risk ratio. PMID:28531157

Transparent Stretchable Self-Powered Patchable Sensor Platform with Ultrasensitive Recognition of Human Activities.

PubMed

Hwang, Byeong-Ung; Lee, Ju-Hyuck; Trung, Tran Quang; Roh, Eun; Kim, Do-Il; Kim, Sang-Woo; Lee, Nae-Eung

2015-09-22

Monitoring of human activities can provide clinically relevant information pertaining to disease diagnostics, preventive medicine, care for patients with chronic diseases, rehabilitation, and prosthetics. The recognition of strains on human skin, induced by subtle movements of muscles in the internal organs, such as the esophagus and trachea, and the motion of joints, was demonstrated using a self-powered patchable strain sensor platform, composed on multifunctional nanocomposites of low-density silver nanowires with a conductive elastomer of poly(3,4-ethylenedioxythiophene):polystyrenesulfonate/polyurethane, with high sensitivity, stretchability, and optical transparency. The ultra-low-power consumption of the sensor, integrated with both a supercapacitor and a triboelectric nanogenerator into a single transparent stretchable platform based on the same nanocomposites, results in a self-powered monitoring system for skin strain. The capability of the sensor to recognize a wide range of strain on skin has the potential for use in new areas of invisible stretchable electronics for human monitoring. A new type of transparent, stretchable, and ultrasensitive strain sensor based on a AgNW/PEDOT:PSS/PU nanocomposite was developed. The concept of a self-powered patchable sensor system integrated with a supercapacitor and a triboelectric nanogenerator that can be used universally as an autonomous invisible sensor system was used to detect the wide range of strain on human skin.

Acoustic monitoring of first responder's physiology for health and performance surveillance

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.

2002-08-01

Acoustic sensors have been used to monitor firefighter and soldier physiology to assess health and performance. The Army Research Laboratory has developed a unique body-contacting acoustic sensor that can monitor the health and performance of firefighters and soldiers while they are doing their mission. A gel-coupled sensor has acoustic impedance properties similar to the skin that facilitate the transmission of body sounds into the sensor pad, yet significantly repel ambient airborne noises due to an impedance mismatch. This technology can monitor heartbeats, breaths, blood pressure, motion, voice, and other indicators that can provide vital feedback to the medics and unit commanders. Diverse physiological parameters can be continuously monitored with acoustic sensors and transmitted for remote surveillance of personnel status. Body-worn acoustic sensors located at the neck, breathing mask, and wrist do an excellent job at detecting heartbeats and activity. However, they have difficulty extracting physiology during rigorous exercise or movements due to the motion artifacts sensed. Rigorous activity often indicates that the person is healthy by virtue of being active, and injury often causes the subject to become less active or incapacitated making the detection of physiology easier. One important measure of performance, heart rate variability, is the measure of beat-to-beat timing fluctuations derived from the interval between two adjacent beats. The Lomb periodogram is optimized for non-uniformly sampled data, and can be applied to non-stationary acoustic heart rate features (such as 1st and 2nd heart sounds) to derive heart rate variability and help eliminate errors created by motion artifacts. Simple peak-detection above or below a certain threshold or waveform derivative parameters can produce the timing and amplitude features necessary for the Lomb periodogram and cross-correlation techniques. High-amplitude motion artifacts may contribute to a different frequency or baseline noise due to the timing differences between the noise artifacts and heartbeat features. Data from a firefighter experiment is presented.

Shoe-Insole Technology for Injury Prevention in Walking

PubMed Central

Nagano, Hanatsu

2018-01-01

Impaired walking increases injury risk during locomotion, including falls-related acute injuries and overuse damage to lower limb joints. Gait impairments seriously restrict voluntary, habitual engagement in injury prevention activities, such as recreational walking and exercise. There is, therefore, an urgent need for technology-based interventions for gait disorders that are cost effective, willingly taken-up, and provide immediate positive effects on walking. Gait control using shoe-insoles has potential as an effective population-based intervention, and new sensor technologies will enhance the effectiveness of these devices. Shoe-insole modifications include: (i) ankle joint support for falls prevention; (ii) shock absorption by utilising lower-resilience materials at the heel; (iii) improving reaction speed by stimulating cutaneous receptors; and (iv) preserving dynamic balance via foot centre of pressure control. Using sensor technology, such as in-shoe pressure measurement and motion capture systems, gait can be precisely monitored, allowing us to visualise how shoe-insoles change walking patterns. In addition, in-shoe systems, such as pressure monitoring and inertial sensors, can be incorporated into the insole to monitor gait in real-time. Inertial sensors coupled with in-shoe foot pressure sensors and global positioning systems (GPS) could be used to monitor spatiotemporal parameters in real-time. Real-time, online data management will enable ‘big-data’ applications to everyday gait control characteristics. PMID:29738486

WISDOM: wheelchair inertial sensors for displacement and orientation monitoring

NASA Astrophysics Data System (ADS)

Pansiot, J.; Zhang, Z.; Lo, B.; Yang, G. Z.

2011-10-01

Improved wheelchair design in recent years has significantly increased the mobility of people with disabilities, which has also enhanced the competitive advantage of wheelchair sports. For the latter, detailed assessment of biomechanical factors influencing individual performance and team tactics requires real-time wireless sensing and data modelling. In this paper, we propose the use of a miniaturized wireless wheel-mounted inertial sensor for wheelchair motion monitoring and tracking in an indoor sport environment. Based on a combined use of 3D microelectromechanical system (MEMS) gyroscopes and 2D MEMS accelerometers, the proposed system provides real-time velocity, heading, ground distance covered and motion trajectory of the wheelchair across the sports court. The proposed system offers a number of advantages compared to existing platforms in terms of size, weight and ease of installation. Beyond sport applications, it also has important applications for training and rehabilitation for people with disabilities.

Advances in Rotational Seismic Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierson, Robert; Laughlin, Darren; Brune, Robert

2016-10-19

Rotational motion is increasingly understood to be a significant part of seismic wave motion. Rotations can be important in earthquake strong motion and in Induced Seismicity Monitoring. Rotational seismic data can also enable shear selectivity and improve wavefield sampling for vertical geophones in 3D surveys, among other applications. However, sensor technology has been a limiting factor to date. The US Department of Energy (DOE) and Applied Technology Associates (ATA) are funding a multi-year project that is now entering Phase 2 to develop and deploy a new generation of rotational sensors for validation of rotational seismic applications. Initial focus is onmore » induced seismicity monitoring, particularly for Enhanced Geothermal Systems (EGS) with fracturing. The sensors employ Magnetohydrodynamic (MHD) principles with broadband response, improved noise floors, robustness, and repeatability. This paper presents a summary of Phase 1 results and Phase 2 status.« less

Wearable strain sensors based on thin graphite films for human activity monitoring

NASA Astrophysics Data System (ADS)

Saito, Takanari; Kihara, Yusuke; Shirakashi, Jun-ichi

2017-12-01

Wearable health-monitoring devices have attracted increasing attention in disease diagnosis and health assessment. In many cases, such devices have been prepared by complicated multistep procedures which result in the waste of materials and require expensive facilities. In this study, we focused on pyrolytic graphite sheet (PGS), which is a low-cost, simple, and flexible material, used as wearable devices for monitoring human activity. We investigated wearable devices based on PGSs for the observation of elbow and finger motions. The thin graphite films were fabricated by cutting small films from PGSs. The wearable devices were then made from the thin graphite films assembled on a commercially available rubber glove. The human motions could be observed using the wearable devices. Therefore, these results suggested that the wearable devices based on thin graphite films may broaden their application in cost-effective wearable electronics for the observation of human activity.

Sunlight Intensity Based Global Positioning System for Near-Surface Underwater Sensors

PubMed Central

Gómez, Javier V.; Sandnes, Frode E.; Fernández, Borja

2012-01-01

Water monitoring is important in domains including documenting climate change, weather prediction and fishing. This paper presents a simple and energy efficient localization strategy for near surface buoy based sensors. Sensors can be dropped randomly in the ocean and thus self-calibrate in terms of geographic location such that geo-tagged observations of water quality can be made without the need for costly and energy consuming GPS-hardware. The strategy is based on nodes with an accurate clock and light sensors that can regularly sample the level of light intensity. The measurements are fitted into a celestial model of the earth motion around the sun. By identifying the trajectory of the sun across the skies one can accurately determine sunrise and sunset times, and thus extract the longitude and latitude of the sensor. Unlike previous localization techniques for underwater sensors, the current approach does not rely on stationary or mobile reference points. PMID:22438746

Sunlight intensity based global positioning system for near-surface underwater sensors.

PubMed

Gómez, Javier V; Sandnes, Frode E; Fernández, Borja

2012-01-01

Water monitoring is important in domains including documenting climate change, weather prediction and fishing. This paper presents a simple and energy efficient localization strategy for near surface buoy based sensors. Sensors can be dropped randomly in the ocean and thus self-calibrate in terms of geographic location such that geo-tagged observations of water quality can be made without the need for costly and energy consuming GPS-hardware. The strategy is based on nodes with an accurate clock and light sensors that can regularly sample the level of light intensity. The measurements are fitted into a celestial model of the earth motion around the sun. By identifying the trajectory of the sun across the skies one can accurately determine sunrise and sunset times, and thus extract the longitude and latitude of the sensor. Unlike previous localization techniques for underwater sensors, the current approach does not rely on stationary or mobile reference points.

Using Passive Sensing to Estimate Relative Energy Expenditure for Eldercare Monitoring

PubMed Central

2012-01-01

This paper describes ongoing work in analyzing sensor data logged in the homes of seniors. An estimation of relative energy expenditure is computed using motion density from passive infrared motion sensors mounted in the environment. We introduce a new algorithm for detecting visitors in the home using motion sensor data and a set of fuzzy rules. The visitor algorithm, as well as a previous algorithm for identifying time-away-from-home (TAFH), are used to filter the logged motion sensor data. Thus, the energy expenditure estimate uses data collected only when the resident is home alone. Case studies are included from TigerPlace, an Aging in Place community, to illustrate how the relative energy expenditure estimate can be used to track health conditions over time. PMID:25266777

Extremely Elastic Wearable Carbon Nanotube Fiber Strain Sensor for Monitoring of Human Motion.

PubMed

Ryu, Seongwoo; Lee, Phillip; Chou, Jeffrey B; Xu, Ruize; Zhao, Rong; Hart, Anastasios John; Kim, Sang-Gook

2015-06-23

The increasing demand for wearable electronic devices has made the development of highly elastic strain sensors that can monitor various physical parameters an essential factor for realizing next generation electronics. Here, we report an ultrahigh stretchable and wearable device fabricated from dry-spun carbon nanotube (CNT) fibers. Stretching the highly oriented CNT fibers grown on a flexible substrate (Ecoflex) induces a constant decrease in the conductive pathways and contact areas between nanotubes depending on the stretching distance; this enables CNT fibers to behave as highly sensitive strain sensors. Owing to its unique structure and mechanism, this device can be stretched by over 900% while retaining high sensitivity, responsiveness, and durability. Furthermore, the device with biaxially oriented CNT fiber arrays shows independent cross-sensitivity, which facilitates simultaneous measurement of strains along multiple axes. We demonstrated potential applications of the proposed device, such as strain gauge, single and multiaxial detecting motion sensors. These devices can be incorporated into various motion detecting systems where their applications are limited to their strain.

Active depth-guiding handheld micro-forceps for membranectomy based on CP-SSOCT

NASA Astrophysics Data System (ADS)

Cheon, Gyeong Woo; Lee, Phillip; Gonenc, Berk; Gehlbach, Peter L.; Kang, Jin U.

2016-03-01

In this study, we demonstrate a handheld motion-compensated micro-forceps system using common-path swept source optical coherence tomography with highly accurate depth-targeting and depth-locking for Epiretinal Membrane Peeling. Two motors and a touch sensor were used to separate the two independent motions: motion compensation and tool-tip manipulation. A smart motion monitoring and guiding algorithm was devised for precise and intuitive freehand control. Ex-vivo bovine eye experiments were performed to evaluate accuracy in a bovine retina retinal membrane peeling model. The evaluation demonstrates system capabilities of 40 um accuracy when peeling the epithelial layer of bovine retina.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edmunds, D; Donovan, E

Purpose: To determine whether the Microsoft Kinect Version 2 (Kinect v2), a commercial off-the-shelf (COTS) depth sensors designed for entertainment purposes, were robust to the radiotherapy treatment environment and could be suitable for monitoring of voluntary breath-hold compliance. This could complement current visual monitoring techniques, and be useful for heart sparing left breast radiotherapy. Methods: In-house software to control Kinect v2 sensors, and capture output information, was developed using the free Microsoft software development kit, and the Cinder creative coding C++ library. Each sensor was used with a 12m USB 3.0 active cable. A solid water block was used asmore » the object. The depth accuracy and precision of the sensors was evaluated by comparing Kinect reported distance to the object with a precision laser measurement across a distance range of 0.6m to 2.0 m. The object was positioned on a high-precision programmable motion platform and moved in two programmed motion patterns and Kinect reported distance logged. Robustness to the radiation environment was tested by repeating all measurements with a linear accelerator operating over a range of pulse repetition frequencies (6Hz to 400Hz) and dose rates 50 to 1500 monitor units (MU) per minute. Results: The complex, consistent relationship between true and measured distance was unaffected by the radiation environment, as was the ability to detect motion. Sensor precision was < 1 mm and the accuracy between 1.3 mm and 1.8 mm when a distance correction was applied. Both motion patterns were tracked successfully with a root mean squared error (RMSE) of 1.4 and 1.1 mm respectively. Conclusion: Kinect v2 sensors are capable of tracking pre-programmed motion patterns with an accuracy <2 mm and appear robust to the radiotherapy treatment environment. A clinical trial using Kinect v2 sensor for monitoring voluntary breath hold has ethical approval and is open to recruitment. The authors are supported by a National Institute of Health Research (NIHR) Career Development Fellowship (CDF-2013-06-005). Microsoft Corporation donated three sensors. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.« less

Structural health monitoring using wireless sensor networks

NASA Astrophysics Data System (ADS)

Sreevallabhan, K.; Nikhil Chand, B.; Ramasamy, Sudha

2017-11-01

Monitoring and analysing health of large structures like bridges, dams, buildings and heavy machinery is important for safety, economical, operational, making prior protective measures, and repair and maintenance point of view. In recent years there is growing demand for such larger structures which in turn make people focus more on safety. By using Microelectromechanical Systems (MEMS) Accelerometer we can perform Structural Health Monitoring by studying the dynamic response through measure of ambient vibrations and strong motion of such structures. By using Wireless Sensor Networks (WSN) we can embed these sensors in wireless networks which helps us to transmit data wirelessly thus we can measure the data wirelessly at any remote location. This in turn reduces heavy wiring which is a cost effective as well as time consuming process to lay those wires. In this paper we developed WSN based MEMS-accelerometer for Structural to test the results in the railway bridge near VIT University, Vellore campus.

[Wearable Devices for Movement Monitoring of Patients with Parkinson’s Disease].

PubMed

Li, Liang; Yu, Qian; Xu, Baoteng; Bai, Qifan; Zhang, Yunpeng; Zhang, Huijun; Mao, Chengjie; Liu, Chunfeng; Wang, Shouyan

2016-12-01

Quantitative assessment of the symptoms of Parkinson’s disease is the key for precise diagnosis and treatment and essential for long term management over years.The challenges of quantitative assessment on Parkinson’s disease are rich information,ultra-low load,long term and large range monitoring in free-moving condition.In this paper,we developed wearable devices with multiple sensors to monitor and quantify the movement symptoms of Parkinson’s disease.Five wearable sensors were used to record motion signals from bilateral forearms,legs and waist.A local area network based on low power Wi-Fi technology was built for long distance wireless data transmission.A software was developed for signal recording and analyzing.The size of each sensor was 39mm×33mm×16mm and the weight was 18 g.The sensors were rechargeable and able to run 12 hours.The wireless transmission radius is about 45 m.The wearable devices were tested in patients and normal subjects.The devices were reliable and accurate for movement monitoring in hospital.

A comparison of force and acoustic emission sensors in monitoring precision cylindrical grinding; Technical Digest

NASA Astrophysics Data System (ADS)

Marsh, Eric R.; Couey, Jeremiah A.; Knapp, Byron R.; Vallance, R. R.

2005-05-01

Aerostatic spindles are used in precision grinding applications requiring high stiffness and very low error motions (5 to 25 nm). Forces generated during precision grinding are small and present challenges for accurate and reliable process monitoring. These challenges are met by incorporating non-contact displacement sensors into an aerostatic spindle that are calibrated to measure grinding forces from rotor motion. Four experiments compare this force-sensing approach to acoustic emission (AE) in detecting workpiece contact, process monitoring with small depths of cut, detecting workpiece defects, and evaluating abrasive wheel wear/loading. Results indicate that force measurements are preferable to acoustic emission in precision grinding since the force sensor offers improved contact sensitivity, higher resolution, and is capable of detecting events occurring within a single revolution of the grinding wheel.

Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification

NASA Astrophysics Data System (ADS)

Sarrafi, Aral; Mao, Zhu; Niezrecki, Christopher; Poozesh, Peyman

2018-05-01

Vibration-based Structural Health Monitoring (SHM) techniques are among the most common approaches for structural damage identification. The presence of damage in structures may be identified by monitoring the changes in dynamic behavior subject to external loading, and is typically performed by using experimental modal analysis (EMA) or operational modal analysis (OMA). These tools for SHM normally require a limited number of physically attached transducers (e.g. accelerometers) in order to record the response of the structure for further analysis. Signal conditioners, wires, wireless receivers and a data acquisition system (DAQ) are also typical components of traditional sensing systems used in vibration-based SHM. However, instrumentation of lightweight structures with contact sensors such as accelerometers may induce mass-loading effects, and for large-scale structures, the instrumentation is labor intensive and time consuming. Achieving high spatial measurement resolution for a large-scale structure is not always feasible while working with traditional contact sensors, and there is also the potential for a lack of reliability associated with fixed contact sensors in outliving the life-span of the host structure. Among the state-of-the-art non-contact measurements, digital video cameras are able to rapidly collect high-density spatial information from structures remotely. In this paper, the subtle motions from recorded video (i.e. a sequence of images) are extracted by means of Phase-based Motion Estimation (PME) and the extracted information is used to conduct damage identification on a 2.3-m long Skystream® wind turbine blade (WTB). The PME and phased-based motion magnification approach estimates the structural motion from the captured sequence of images for both a baseline and damaged test cases on a wind turbine blade. Operational deflection shapes of the test articles are also quantified and compared for the baseline and damaged states. In addition, having proper lighting while working with high-speed cameras can be an issue, therefore image enhancement and contrast manipulation has also been performed to enhance the raw images. Ultimately, the extracted resonant frequencies and operational deflection shapes are used to detect the presence of damage, demonstrating the feasibility of implementing non-contact video measurements to perform realistic structural damage detection.

Biomechanics of the Sensor–Tissue Interface—Effects of Motion, Pressure, and Design on Sensor Performance and Foreign Body Response—Part II: Examples and Application

PubMed Central

Helton, Kristen L; Ratner, Buddy D; Wisniewski, Natalie A

2011-01-01

This article is the second part of a two-part review in which we explore the biomechanics of the sensor–tissue interface as an important aspect of continuous glucose sensor biocompatibility. Part I, featured in this issue of Journal of Diabetes Science and Technology, describes a theoretical framework of how biomechanical factors such as motion and pressure (typically micromotion and micropressure) affect tissue physiology around a sensor and in turn, impact sensor performance. Here in Part II, a literature review is presented that summarizes examples of motion or pressure affecting sensor performance. Data are presented that show how both acute and chronic forces can impact continuous glucose monitor signals. Also presented are potential strategies for countering the ill effects of motion and pressure on glucose sensors. Improved engineering and optimized chemical biocompatibility have advanced sensor design and function, but we believe that mechanical biocompatibility, a rarely considered factor, must also be optimized in order to achieve an accurate, long-term, implantable sensor. PMID:21722579

Ultrathin flexible piezoelectric sensors for monitoring eye fatigue

NASA Astrophysics Data System (ADS)

Lü, Chaofeng; Wu, Shuang; Lu, Bingwei; Zhang, Yangyang; Du, Yangkun; Feng, Xue

2018-02-01

Eye fatigue is a symptom induced by long-term work of both eyes and brains. Without proper treatment, eye fatigue may incur serious problems. Current studies on detecting eye fatigue mainly focus on computer vision detect technology which can be very unreliable due to occasional bad visual conditions. As a solution, we proposed a wearable conformal in vivo eye fatigue monitoring sensor that contains an array of piezoelectric nanoribbons integrated on an ultrathin flexible substrate. By detecting strains on the skin of eyelid, the sensors may collect information about eye blinking, and, therefore, reveal human’s fatigue state. We first report the design and fabrication of the piezoelectric sensor and experimental characterization of voltage responses of the piezoelectric sensors. Under bending stress, the output voltage curves yield key information about the motion of human eyelid. We also develop a theoretical model to reveal the underlying mechanism of detecting eyelid motion. Both mechanical load test and in vivo test are conducted to convince the working performance of the sensors. With satisfied durability and high sensitivity, this sensor may efficiently detect abnormal eyelid motions, such as overlong closure, high blinking frequency, low closing speed and weak gazing strength, and may hopefully provide feedback for assessing eye fatigue in time so that unexpected situations can be prevented.

A wearable wireless ECG monitoring system with dynamic transmission power control for long-term homecare.

PubMed

Wang, Yishan; Doleschel, Sammy; Wunderlich, Ralf; Heinen, Stefan

2015-03-01

This paper presents a wearable wireless ECG monitoring system based on novel 3-Lead electrode placements for long-term homecare. The experiment for novel 3-Lead electrode placements is carried out, and the results show that the distance between limb electrodes can be significantly reduced. Based on the new electrode position, a small size sensor node, which is powered by a rechargeable battery, is designed to detect, amplify, filter and transmit the ECG signals. The coordinator receives the data and sends it to PC. Finally the signals are displayed on the GUI. In order to control the power consumption of sensor node, a dynamic power adjustment method is applied to automatically adjust the transmission power of the sensor node according to the received signal strength indicator (RSSI), which is related to the distance and obstacle between sensor node and coordinator. The system is evaluated when the user, who wears the sensor, is walking and running. A promising performance is achieved even under body motion. The power consumption can be significantly reduced with this dynamic power adjustment method.

Remotely deployable aerial inspection using tactile sensors

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacLeod, C. N.; Cao, J.; Pierce, S. G.

For structural monitoring applications, the use of remotely deployable Non-Destructive Evaluation (NDE) inspection platforms offer many advantages, including improved accessibility, greater safety and reduced cost, when compared to traditional manual inspection techniques. The use of such platforms, previously reported by researchers at the University Strathclyde facilitates the potential for rapid scanning of large areas and volumes in hazardous locations. A common problem for both manual and remote deployment approaches lies in the intrinsic stand-off and surface coupling issues of typical NDE probes. The associated complications of these requirements are obviously significantly exacerbated when considering aerial based remote inspection and deployment,more » resulting in simple visual techniques being the preferred sensor payload. Researchers at Bristol Robotics Laboratory have developed biomimetic tactile sensors modelled on the facial whiskers (vibrissae) of animals such as rats and mice, with the latest sensors actively sweeping their tips across the surface in a back and forth motion. The current work reports on the design and performance of an aerial inspection platform and the suitability of tactile whisking sensors to aerial based surface monitoring applications.« less

An Activity Recognition Framework Deploying the Random Forest Classifier and A Single Optical Heart Rate Monitoring and Triaxial AccelerometerWrist-Band.

PubMed

Mehrang, Saeed; Pietilä, Julia; Korhonen, Ilkka

2018-02-22

Wrist-worn sensors have better compliance for activity monitoring compared to hip, waist, ankle or chest positions. However, wrist-worn activity monitoring is challenging due to the wide degree of freedom for the hand movements, as well as similarity of hand movements in different activities such as varying intensities of cycling. To strengthen the ability of wrist-worn sensors in detecting human activities more accurately, motion signals can be complemented by physiological signals such as optical heart rate (HR) based on photoplethysmography. In this paper, an activity monitoring framework using an optical HR sensor and a triaxial wrist-worn accelerometer is presented. We investigated a range of daily life activities including sitting, standing, household activities and stationary cycling with two intensities. A random forest (RF) classifier was exploited to detect these activities based on the wrist motions and optical HR. The highest overall accuracy of 89.6 ± 3.9% was achieved with a forest of a size of 64 trees and 13-s signal segments with 90% overlap. Removing the HR-derived features decreased the classification accuracy of high-intensity cycling by almost 7%, but did not affect the classification accuracies of other activities. A feature reduction utilizing the feature importance scores of RF was also carried out and resulted in a shrunken feature set of only 21 features. The overall accuracy of the classification utilizing the shrunken feature set was 89.4 ± 4.2%, which is almost equivalent to the above-mentioned peak overall accuracy.

Inertial Sensor-Based Touch and Shake Metaphor for Expressive Control of 3D Virtual Avatars

PubMed Central

Patil, Shashidhar; Chintalapalli, Harinadha Reddy; Kim, Dubeom; Chai, Youngho

2015-01-01

In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with a sensor fusion algorithm. The algorithm enables user hand motions to be tracked in 3D space via magnetic, angular rate, and gravity sensors. A quaternion-based complementary filter is implemented to reduce noise and drift. An algorithm based on dynamic time-warping is developed for efficient recognition of dynamic hand gestures with real-time automatic hand gesture segmentation. Our approach enables the recognition of gestures and estimates gesture variations for continuous interaction. We demonstrate the gesture expressivity using an interactive flexible gesture mapping interface for authoring and controlling a 3D virtual avatar and its motion by tracking user dynamic hand gestures. This synthesizes stylistic variations in a 3D virtual avatar, producing motions that are not present in the motion database using hand gesture sequences from a single inertial motion sensor. PMID:26094629

Respiration and body movement analysis during sleep in bed using hetero-core fiber optic pressure sensors without constraint to human activity.

PubMed

Nishyama, Michiko; Miyamoto, Mitsuo; Watanabe, Kazuhiro

2011-01-01

We describe respiration monitoring in sleep using hetero-core fiber optic pressure sensors. The proposed hetero-core fiber optic sensor is highly sensitive to macrobending as a result of the core diameter difference due to stable single-mode transmission. Pressure sensors based on hetero-core fiber optics were fabricated to have a high sensitivity to small pressure changes resulting from minute body motions, such as respiration, during sleep and large pressure changes, such as those caused by a rollover. The sensors are installed in a conventional bed. The pressure characteristic performance of all the fabricated hetero-core fiber optic pressure sensors is found to show a monotonic response with weight changes. A respiration monitoring test in seven subjects efficiently demonstrates the effective use of eight hetero-core pressure sensors installed in a bed. Additionally, even in the case of different body postures, such as lying on one's side, a slight body movement due to respiration is detected by the hetero-core pressure sensors.

Respiration and body movement analysis during sleep in bed using hetero-core fiber optic pressure sensors without constraint to human activity

NASA Astrophysics Data System (ADS)

Nishyama, Michiko; Miyamoto, Mitsuo; Watanabe, Kazuhiro

2011-01-01

We describe respiration monitoring in sleep using hetero-core fiber optic pressure sensors. The proposed hetero-core fiber optic sensor is highly sensitive to macrobending as a result of the core diameter difference due to stable single-mode transmission. Pressure sensors based on hetero-core fiber optics were fabricated to have a high sensitivity to small pressure changes resulting from minute body motions, such as respiration, during sleep and large pressure changes, such as those caused by a rollover. The sensors are installed in a conventional bed. The pressure characteristic performance of all the fabricated hetero-core fiber optic pressure sensors is found to show a monotonic response with weight changes. A respiration monitoring test in seven subjects efficiently demonstrates the effective use of eight hetero-core pressure sensors installed in a bed. Additionally, even in the case of different body postures, such as lying on one's side, a slight body movement due to respiration is detected by the hetero-core pressure sensors.

Reflective oxygen saturation monitoring at hypothenar and its validation by human hypoxia experiment.

PubMed

Guo, Tao; Cao, Zhengtao; Zhang, Zhengbo; Li, Deyu; Yu, Mengsun

2015-08-05

Pulse oxygen saturation (SpO2) is an important parameter for healthcare, and wearable sensors and systems for SpO2 monitoring have become increasingly popular. The aim of this paper is to develop a novel SpO2 monitoring system, which detects photoplethysmographic (PPG) signals at hypothenar with a reflection-mode sensor embedded into a glove. A special photo-detector section was designed with two photodiodes arranged symmetrically to the red and infrared light-emitting diodes (LED) to enhance the signal quality. The reflective sensor was placed in a soft silicon substrate sewn in a glove to fit the surface of the hypothenar. To lower the power consumption, the LED driving current was reduced and energy-efficient electronic components were applied. The performance for PPG signal detection and SpO2 monitoring was evaluated by human hypoxia experiments. Accelerometer-based adaptive noise cancellation (ANC) methods applying the least mean squares (LMS) and recursive least squares (RLS) algorithms were studied to suppress motion artifact. A total of 20 subjects participated in the hypoxia experiment. The degree of comfort for wearing this system was accepted by them. The PPG signals were detected effectively at SpO2 levels from about 100-70%. The experiment validated the accuracy of the system was 2.34%, compared to the invasive measurements. Both the LMS and RLS algorithms improved the performance during motion. The total current consumed by the system was only 8 mA. It is feasible to detect PPG signal and monitor SpO2 at the location of hypothenar. This novel system can achieve reliable SpO2 measurements at different SpO2 levels and on different individuals. The system is light-weighted, easy to wear and power-saving. It has the potential to be a solution for wearable monitoring, although more work should be conducted to improve the motion-resistant performance significantly.

Stepping-Motion Motor-Control Subsystem For Testing Bearings

NASA Technical Reports Server (NTRS)

Powers, Charles E.

1992-01-01

Control subsystem closed-loop angular-position-control system causing motor and bearing under test to undergo any of variety of continuous or stepping motions. Also used to test bearing-and-motor assemblies, motors, angular-position sensors including rotating shafts, and like. Monitoring subsystem gathers data used to evaluate performance of bearing or other article under test. Monitoring subsystem described in article, "Monitoring Subsystem For Testing Bearings" (GSC-13432).

Smart textile for respiratory monitoring and thoraco-abdominal motion pattern evaluation.

PubMed

Massaroni, Carlo; Venanzi, Cecilia; Silvatti, Amanda P; Lo Presti, Daniela; Saccomandi, Paola; Formica, Domenico; Giurazza, Francesco; Caponero, Michele A; Schena, Emiliano

2018-05-01

The use of wearable systems for monitoring vital parameters has gained wide popularity in several medical fields. The focus of the present study is the experimental assessment of a smart textile based on 12 fiber Bragg grating sensors for breathing monitoring and thoraco-abdominal motion pattern analysis. The feasibility of the smart textile for monitoring several temporal respiratory parameters (ie, breath-by-breath respiratory period, breathing frequency, duration of inspiratory and expiratory phases), volume variations of the whole chest wall and of its compartments is performed on 8 healthy male volunteers. Values gathered by the textile are compared to the data obtained by a motion analysis system, used as the reference instrument. Good agreement between the 2 systems on both respiratory period (bias of 0.01 seconds), breathing frequency (bias of -0.02 breaths/min) and tidal volume (bias of 0.09 L) values is demonstrated. Smart textile shows good performance in the monitoring of thoraco-abdominal pattern and its variation, as well. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The development and validation of using inertial sensors to monitor postural change in resistance exercise.

PubMed

Gleadhill, Sam; Lee, James Bruce; James, Daniel

2016-05-03

This research presented and validated a method of assessing postural changes during resistance exercise using inertial sensors. A simple lifting task was broken down to a series of well-defined tasks, which could be examined and measured in a controlled environment. The purpose of this research was to determine whether timing measures obtained from inertial sensor accelerometer outputs are able to provide accurate, quantifiable information of resistance exercise movement patterns. The aim was to complete a timing measure validation of inertial sensor outputs. Eleven participants completed five repetitions of 15 different deadlift variations. Participants were monitored with inertial sensors and an infrared three dimensional motion capture system. Validation was undertaken using a Will Hopkins Typical Error of the Estimate, with a Pearson׳s correlation and a Bland Altman Limits of Agreement analysis. Statistical validation measured the timing agreement during deadlifts, from inertial sensor outputs and the motion capture system. Timing validation results demonstrated a Pearson׳s correlation of 0.9997, with trivial standardised error (0.026) and standardised bias (0.002). Inertial sensors can now be used in practical settings with as much confidence as motion capture systems, for accelerometer timing measurements of resistance exercise. This research provides foundations for inertial sensors to be applied for qualitative activity recognition of resistance exercise and safe lifting practices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Control of a Quadcopter Aerial Robot Using Optic Flow Sensing

NASA Astrophysics Data System (ADS)

Hurd, Michael Brandon

This thesis focuses on the motion control of a custom-built quadcopter aerial robot using optic flow sensing. Optic flow sensing is a vision-based approach that can provide a robot the ability to fly in global positioning system (GPS) denied environments, such as indoor environments. In this work, optic flow sensors are used to stabilize the motion of quadcopter robot, where an optic flow algorithm is applied to provide odometry measurements to the quadcopter's central processing unit to monitor the flight heading. The optic-flow sensor and algorithm are capable of gathering and processing the images at 250 frames/sec, and the sensor package weighs 2.5 g and has a footprint of 6 cm2 in area. The odometry value from the optic flow sensor is then used a feedback information in a simple proportional-integral-derivative (PID) controller on the quadcopter. Experimental results are presented to demonstrate the effectiveness of using optic flow for controlling the motion of the quadcopter aerial robot. The technique presented herein can be applied to different types of aerial robotic systems or unmanned aerial vehicles (UAVs), as well as unmanned ground vehicles (UGV).

Balance Improvement Effects of Biofeedback Systems with State-of-the-Art Wearable Sensors: A Systematic Review.

PubMed

Ma, Christina Zong-Hao; Wong, Duo Wai-Chi; Lam, Wing Kai; Wan, Anson Hong-Ping; Lee, Winson Chiu-Chun

2016-03-25

Falls and fall-induced injuries are major global public health problems. Balance and gait disorders have been the second leading cause of falls. Inertial motion sensors and force sensors have been widely used to monitor both static and dynamic balance performance. Based on the detected performance, instant visual, auditory, electrotactile and vibrotactile biofeedback could be provided to augment the somatosensory input and enhance balance control. This review aims to synthesize the research examining the effect of biofeedback systems, with wearable inertial motion sensors and force sensors, on balance performance. Randomized and non-randomized clinical trials were included in this review. All studies were evaluated based on the methodological quality. Sample characteristics, device design and study characteristics were summarized. Most previous studies suggested that biofeedback devices were effective in enhancing static and dynamic balance in healthy young and older adults, and patients with balance and gait disorders. Attention should be paid to the choice of appropriate types of sensors and biofeedback for different intended purposes. Maximizing the computing capacity of the micro-processer, while minimizing the size of the electronic components, appears to be the future direction of optimizing the devices. Wearable balance-improving devices have their potential of serving as balance aids in daily life, which can be used indoors and outdoors.

A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles.

PubMed

Suhr, Jae Kyu; Jung, Ho Gi

2018-04-16

An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM) system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision.

Balance Improvement Effects of Biofeedback Systems with State-of-the-Art Wearable Sensors: A Systematic Review

PubMed Central

Ma, Christina Zong-Hao; Wong, Duo Wai-Chi; Lam, Wing Kai; Wan, Anson Hong-Ping; Lee, Winson Chiu-Chun

2016-01-01

Falls and fall-induced injuries are major global public health problems. Balance and gait disorders have been the second leading cause of falls. Inertial motion sensors and force sensors have been widely used to monitor both static and dynamic balance performance. Based on the detected performance, instant visual, auditory, electrotactile and vibrotactile biofeedback could be provided to augment the somatosensory input and enhance balance control. This review aims to synthesize the research examining the effect of biofeedback systems, with wearable inertial motion sensors and force sensors, on balance performance. Randomized and non-randomized clinical trials were included in this review. All studies were evaluated based on the methodological quality. Sample characteristics, device design and study characteristics were summarized. Most previous studies suggested that biofeedback devices were effective in enhancing static and dynamic balance in healthy young and older adults, and patients with balance and gait disorders. Attention should be paid to the choice of appropriate types of sensors and biofeedback for different intended purposes. Maximizing the computing capacity of the micro-processer, while minimizing the size of the electronic components, appears to be the future direction of optimizing the devices. Wearable balance-improving devices have their potential of serving as balance aids in daily life, which can be used indoors and outdoors. PMID:27023558

A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles

PubMed Central

2018-01-01

An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM) system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision. PMID:29659512

Wearable motion sensors to continuously measure real-world physical activities.

PubMed

Dobkin, Bruce H

2013-12-01

Rehabilitation for sensorimotor impairments aims to improve daily activities, walking, exercise, and motor skills. Monitoring of practice and measuring outcomes, however, is usually restricted to laboratory-based procedures and self-reports. Mobile health devices may reverse these confounders of daily care and research trials. Wearable, wireless motion sensor data, analyzed by activity pattern-recognition algorithms, can describe the type, quantity, and quality of mobility-related activities in the community. Data transmission from the sensors to a cell phone and the Internet enable continuous monitoring. Remote access to laboratory quality data about walking speed, duration and distance, gait asymmetry and smoothness of movements, as well as cycling, exercise, and skills practice, opens new opportunities to engage patients in progressive, personalized therapies with feedback about the performance. Clinical trial designs will be able to include remote verification of the integrity of complex physical interventions and compliance with practice, as well as capture repeated, ecologically sound, ratio scale outcome measures. Given the progressively falling cost of miniaturized wearable gyroscopes, accelerometers, and other physiologic sensors, as well as inexpensive data transmission, sensing systems may become as ubiquitous as cell phones for healthcare. Neurorehabilitation can develop these mobile health platforms for daily care and clinical trials to improve exercise and fitness, skills learning, and physical functioning.

Classification Models for Pulmonary Function using Motion Analysis from Phone Sensors.

PubMed

Cheng, Qian; Juen, Joshua; Bellam, Shashi; Fulara, Nicholas; Close, Deanna; Silverstein, Jonathan C; Schatz, Bruce

2016-01-01

Smartphones are ubiquitous, but it is unknown what physiological functions can be monitored at clinical quality. Pulmonary function is a standard measure of health status for cardiopulmonary patients. We have shown phone sensors can accurately measure walking patterns. Here we show that improved classification models can accurately measure pulmonary function, with sole inputs being sensor data from carried phones. Twenty-four cardiopulmonary patients performed six minute walk tests in pulmonary rehabilitation at a regional hospital. They carried smartphones running custom software recording phone motion. For every patient, every ten-second interval was correctly computed. The trained model perfectly computed the GOLD level 1/2/3, which is a standard categorization of pulmonary function as measured by spirometry. These results are encouraging towards field trials with passive monitors always running in the background. We expect patients can simply carry their phones during daily living, while supporting automatic computation ofpulmonary function for health monitoring.

Development of esMOCA RULA, Motion Capture Instrumentation for RULA Assessment

NASA Astrophysics Data System (ADS)

Akhmad, S.; Arendra, A.

2018-01-01

The purpose of this research is to build motion capture instrumentation using sensors fusion accelerometer and gyroscope to assist in RULA assessment. Data processing of sensor orientation is done in every sensor node by digital motion processor. Nine sensors are placed in the upper limb of operator subject. Development of kinematics model is done with Simmechanic Simulink. This kinematics model receives streaming data from sensors via wireless sensors network. The output of the kinematics model is the relative angular angle between upper limb members and visualized on the monitor. This angular information is compared to the look-up table of the RULA worksheet and gives the RULA score. The assessment result of the instrument is compared with the result of the assessment by rula assessors. To sum up, there is no significant difference of assessment by the instrument with an assessment by an assessor.

Highly sensitive, self-powered and wearable electronic skin based on pressure-sensitive nanofiber woven fabric sensor.

PubMed

Zhou, Yuman; He, Jianxin; Wang, Hongbo; Qi, Kun; Nan, Nan; You, Xiaolu; Shao, Weili; Wang, Lidan; Ding, Bin; Cui, Shizhong

2017-10-11

The wearable electronic skin with high sensitivity and self-power has shown increasing prospects for applications such as human health monitoring, robotic skin, and intelligent electronic products. In this work, we introduced and demonstrated a design of highly sensitive, self-powered, and wearable electronic skin based on a pressure-sensitive nanofiber woven fabric sensor fabricated by weaving PVDF electrospun yarns of nanofibers coated with PEDOT. Particularly, the nanofiber woven fabric sensor with multi-leveled hierarchical structure, which significantly induced the change in contact area under ultra-low load, showed combined superiority of high sensitivity (18.376 kPa -1 , at ~100 Pa), wide pressure range (0.002-10 kPa), fast response time (15 ms) and better durability (7500 cycles). More importantly, an open-circuit voltage signal of the PPNWF pressure sensor was obtained through applying periodic pressure of 10 kPa, and the output open-circuit voltage exhibited a distinct switching behavior to the applied pressure, indicating the wearable nanofiber woven fabric sensor could be self-powered under an applied pressure. Furthermore, we demonstrated the potential application of this wearable nanofiber woven fabric sensor in electronic skin for health monitoring, human motion detection, and muscle tremor detection.

Vital Sign Monitoring Through the Back Using an UWB Impulse Radar With Body Coupled Antennas.

PubMed

Schires, Elliott; Georgiou, Pantelis; Lande, Tor Sverre

2018-04-01

Radar devices can be used in nonintrusive situations to monitor vital sign, through clothes or behind walls. By detecting and extracting body motion linked to physiological activity, accurate simultaneous estimations of both heart rate (HR) and respiration rate (RR) is possible. However, most research to date has focused on front monitoring of superficial motion of the chest. In this paper, body penetration of electromagnetic (EM) wave is investigated to perform back monitoring of human subjects. Using body-coupled antennas and an ultra-wideband (UWB) pulsed radar, in-body monitoring of lungs and heart motion was achieved. An optimised location of measurement in the back of a subject is presented, to enhance signal-to-noise ratio and limit attenuation of reflected radar signals. Phase-based detection techniques are then investigated for back measurements of vital sign, in conjunction with frequency estimation methods that reduce the impact of parasite signals. Finally, an algorithm combining these techniques is presented to allow robust and real-time estimation of both HR and RR. Static and dynamic tests were conducted, and demonstrated the possibility of using this sensor in future health monitoring systems, especially in the form of a smart car seat for driver monitoring.

The effect of single engine fixed wing air transport on rate-responsive pacemakers.

PubMed

De Rotte, A A; Van Der Kemp, P

1999-09-01

Insufficient information exists about the safety of patients with accelerometer-based rate-responsive pacemakers in air transport by general aviation aircraft. The response in pacing rate of two types of accelerometer-based rate-responsive pacemakers with data logging capabilities was studied during test flights with single engine fixed wing aircraft. Results were compared with the rate-response of these pacemakers during transportation by car and were also interpreted in respect to physiological heart rate response of aircrew during flights in single engine fixed wing aircraft. In addition, a continuous accelerometer readout was recorded during a turbulent phase of flight. This recording was used for a pacemaker-simulator experiment with maximal sensitive motion-sensor settings. Only a minor increase in pacing rate due to aircraft motion could be demonstrated during all phases of flight at all altitudes with the pacemakers programmed in the normal mode. This increase was of the same magnitude as induced during transport by car and would be of negligible influence on the performance of the individual pacemaker patient equipped with such a pacemaker. Moreover, simultaneous Holter monitoring of the pilots during these flights showed a similar rate-response in natural heart rate compared with the increase in pacing rate induced by aircraft motion in accelerometer-based rate-responsive pacemakers. No sensor-mediated pacemaker tachycardia was seen during any of these recordings. However, a 15% increase in pacing rate was induced by severe air turbulence. Programming the maximal sensitivity of the motion sensor into the pacemaker could, on the other hand, induce a significant increase in pacing rate as was demonstrated by the simulation experiments. These results seem to rule out potentially dangerous or adverse effects from motional or vibrational influences during transport in single engine fixed wing aircraft on accelerometer-based rate-responsive pacemakers with normal activity sensor settings.

Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System.

PubMed

Choi, Hyundo; Seo, Keehong; Hyung, Seungyong; Shim, Youngbo; Lim, Soo-Chul

2018-02-13

In this paper, we propose a compact force sensor system for a hip-mounted exoskeleton for seniors with difficulties in walking due to muscle weakness. It senses and monitors the delivered force and power of the exoskeleton for motion control and taking urgent safety action. Two FSR (force-sensitive resistors) sensors are used to measure the assistance force when the user is walking. The sensor system directly measures the interaction force between the exoskeleton and the lower limb of the user instead of a previously reported force-sensing method, which estimated the hip assistance force from the current of the motor and lookup tables. Furthermore, the sensor system has the advantage of generating torque in the walking-assistant actuator based on directly measuring the hip-assistance force. Thus, the gait-assistance exoskeleton system can control the delivered power and torque to the user. The force sensing structure is designed to decouple the force caused by hip motion from other directional forces to the sensor so as to only measure that force. We confirmed that the hip-assistance force could be measured with the proposed prototype compact force sensor attached to a thigh frame through an experiment with a real system.

Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System

PubMed Central

Choi, Hyundo; Seo, Keehong; Hyung, Seungyong; Shim, Youngbo; Lim, Soo-Chul

2018-01-01

In this paper, we propose a compact force sensor system for a hip-mounted exoskeleton for seniors with difficulties in walking due to muscle weakness. It senses and monitors the delivered force and power of the exoskeleton for motion control and taking urgent safety action. Two FSR (force-sensitive resistors) sensors are used to measure the assistance force when the user is walking. The sensor system directly measures the interaction force between the exoskeleton and the lower limb of the user instead of a previously reported force-sensing method, which estimated the hip assistance force from the current of the motor and lookup tables. Furthermore, the sensor system has the advantage of generating torque in the walking-assistant actuator based on directly measuring the hip-assistance force. Thus, the gait-assistance exoskeleton system can control the delivered power and torque to the user. The force sensing structure is designed to decouple the force caused by hip motion from other directional forces to the sensor so as to only measure that force. We confirmed that the hip-assistance force could be measured with the proposed prototype compact force sensor attached to a thigh frame through an experiment with a real system. PMID:29438300

Elastomeric Sensing of Pressure with Liquid Metal and Wireless Inductive Coupling

NASA Technical Reports Server (NTRS)

Dick, Jacob; Zou, Xiyue; Hogan, Ben; Tumalle, Jonathan; Etikyala, Sowmith; Fung, Diego; Charles, Watley; Gu, Tianye; Hull, Patrick V.; Mazzeo, Aaron D.

2017-01-01

This project describes resistance-based soft sensors filled with liquid metal, which permit measurements of large strains (0 percent to 110 percent), associated with small forces of less than 30 Newtons. This work also demonstrates a methodology for wireless transfer of these strain measurements without connected electrodes. These sensors allow intermittent detection of pressure on soft membranes with low force. Adapting these sensors for passive wireless pressure sensing will eliminate the need for embedded batteries, and will allow the sensors to transmit pressure data through non-conductive materials including glass and acrylic. The absence of batteries allows us to embed these sensors into materials for long-term use because the sensors only use passive analog circuit elements. We found the oxidation of the liquid metal (eutectic gallium indium) plays a role in the repeatability of the soft sensors. We investigated how the oxidation layer affected the behavior of the sensor by encapsulating materials (silicone, fluorosilicone, and PVC) with varied permeabilities to oxygen. We measured the effects of mechanical loading on the oxidation layer and the effects of wireless inductive coupling on the oxidation layer. We concluded our research by investigating the effects of embedding self-resonant circuits into polydimethylsiloxane (PDMS). Efforts to design engineered systems with soft materials are a growing field with progress in soft robotics, epidermal electronics, and wearable electronics. In the field of soft robotics, PDMS-based grippers are capable of picking up delicate objects because their form-fitting properties allow them to conform to the shape of objects more easily than conventional robotic grippers. Epidermal devices also use PDMS as a substrate to hold electronic components such as radios, sensors, and power supply circuits. Additionally, PDMS-based soft sensors can monitor human motion with liquid metal embedded within micro-channels. Passive wireless sensors have applications in structural health monitoring and medical health monitoring. Doctors can take wireless blood pressure measurements inside arteries to monitor the progression of heart disease. Glaucoma patients can use this technology to monitor the pressure in their eyes to track the progression of the disease.

Unobtrusive Monitoring of Neonatal Brain Temperature Using a Zero-Heat-Flux Sensor Matrix.

PubMed

Atallah, Louis; Bongers, Edwin; Lamichhane, Bishal; Bambang-Oetomo, Sidarto

2016-01-01

The temperature of preterm neonates must be maintained within a narrow window to ensure their survival. Continuously measuring their core temperature provides an optimal means of monitoring their thermoregulation and their response to environmental changes. However, existing methods of measuring core temperature can be very obtrusive, such as rectal probes, or inaccurate/lagging, such as skin temperature sensors and spot-checks using tympanic temperature sensors. This study investigates an unobtrusive method of measuring brain temperature continuously using an embedded zero-heat-flux (ZHF) sensor matrix placed under the head of the neonate. The measured temperature profile is used to segment areas of motion and incorrect positioning, where the neonate's head is not above the sensors. We compare our measurements during low motion/stable periods to esophageal temperatures for 12 preterm neonates, measured for an average of 5 h per neonate. The method we propose shows good correlation with the reference temperature for most of the neonates. The unobtrusive embedding of the matrix in the neonate's environment poses no harm or disturbance to the care work-flow, while measuring core temperature. To address the effect of motion on the ZHF measurements in the current embodiment, we recommend a more ergonomic embedding ensuring the sensors are continuously placed under the neonate's head.

WiSPH: a wireless sensor network-based home care monitoring system.

PubMed

Magaña-Espinoza, Pedro; Aquino-Santos, Raúl; Cárdenas-Benítez, Néstor; Aguilar-Velasco, José; Buenrostro-Segura, César; Edwards-Block, Arthur; Medina-Cass, Aldo

2014-04-22

This paper presents a system based on WSN technology capable of monitoring heart rate and the rate of motion of seniors within their homes. The system is capable of remotely alerting specialists, caretakers or family members via a smartphone of rapid physiological changes due to falls, tachycardia or bradycardia. This work was carried out using our workgroup's WiSe platform, which we previously developed for use in WSNs. The proposed WSN architecture is flexible, allowing for greater scalability to better allow event-based monitoring. The architecture also provides security mechanisms to assure that the monitored and/or stored data can only be accessed by authorized individuals or devices. The aforementioned characteristics provide the network versatility and solidity required for use in health applications.

Extraction and Analysis of Respiratory Motion Using Wearable Inertial Sensor System during Trunk Motion

PubMed Central

Gaidhani, Apoorva; Moon, Kee S.; Ozturk, Yusuf; Lee, Sung Q.; Youm, Woosub

2017-01-01

Respiratory activity is an essential vital sign of life that can indicate changes in typical breathing patterns and irregular body functions such as asthma and panic attacks. Many times, there is a need to monitor breathing activity while performing day-to-day functions such as standing, bending, trunk stretching or during yoga exercises. A single IMU (inertial measurement unit) can be used in measuring respiratory motion; however, breathing motion data may be influenced by a body trunk movement that occurs while recording respiratory activity. This research employs a pair of wireless, wearable IMU sensors custom-made by the Department of Electrical Engineering at San Diego State University. After appropriate sensor placement for data collection, this research applies principles of robotics, using the Denavit-Hartenberg convention, to extract relative angular motion between the two sensors. One of the obtained relative joint angles in the “Sagittal” plane predominantly yields respiratory activity. An improvised version of the proposed method and wearable, wireless sensors can be suitable to extract respiratory information while performing sports or exercises, as they do not restrict body motion or the choice of location to gather data. PMID:29258214

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach

PubMed Central

Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

2015-01-01

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks. PMID:26729123

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

PubMed

Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

2015-12-30

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

Self-adapted and tunable graphene strain sensors for detecting both subtle and large human motions.

PubMed

Tao, Lu-Qi; Wang, Dan-Yang; Tian, He; Ju, Zhen-Yi; Liu, Ying; Pang, Yu; Chen, Yuan-Quan; Yang, Yi; Ren, Tian-Ling

2017-06-22

Conventional strain sensors rarely have both a high gauge factor and a large strain range simultaneously, so they can only be used in specific situations where only a high sensitivity or a large strain range is required. However, for detecting human motions that include both subtle and large motions, these strain sensors can't meet the diverse demands simultaneously. Here, we come up with laser patterned graphene strain sensors with self-adapted and tunable performance for the first time. A series of strain sensors with either an ultrahigh gauge factor or a preferable strain range can be fabricated simultaneously via one-step laser patterning, and are suitable for detecting all human motions. The strain sensors have a GF of up to 457 with a strain range of 35%, or have a strain range of up to 100% with a GF of 268. Most importantly, the performance of the strain sensors can be easily tuned by adjusting the patterns of the graphene, so that the sensors can meet diverse demands in both subtle and large motion situations. The graphene strain sensors show significant potential in applications such as wearable electronics, health monitoring and intelligent robots. Furthermore, the facile, fast and low-cost fabrication method will make them possible and practical to be used for commercial applications in the future.

Identifying compensatory movement patterns in the upper extremity using a wearable sensor system.

PubMed

Ranganathan, Rajiv; Wang, Rui; Dong, Bo; Biswas, Subir

2017-11-30

Movement impairments such as those due to stroke often result in the nervous system adopting atypical movements to compensate for movement deficits. Monitoring these compensatory patterns is critical for improving functional outcomes during rehabilitation. The purpose of this study was to test the feasibility and validity of a wearable sensor system for detecting compensatory trunk kinematics during activities of daily living. Participants with no history of neurological impairments performed reaching and manipulation tasks with their upper extremity, and their movements were recorded by a wearable sensor system and validated using a motion capture system. Compensatory movements of the trunk were induced using a brace that limited range of motion at the elbow. Our results showed that the elbow brace elicited compensatory movements of the trunk during reaching tasks but not manipulation tasks, and that a wearable sensor system with two sensors could reliably classify compensatory movements (~90% accuracy). These results show the potential of the wearable system to assess and monitor compensatory movements outside of a lab setting.

40 CFR 63.1363 - Standards for equipment leaks.

Code of Federal Regulations, 2014 CFR

2014-07-01

... heating and cooling systems which do not combine their materials with those in the processes they serve..., magnetic sensor, motion detector on the pressure relief valve stem, flow monitor, or pressure monitor. (B...

Development of a smartphone application to measure physical activity using sensor-assisted self-report.

PubMed

Dunton, Genevieve Fridlund; Dzubur, Eldin; Kawabata, Keito; Yanez, Brenda; Bo, Bin; Intille, Stephen

2014-01-01

Despite the known advantages of objective physical activity monitors (e.g., accelerometers), these devices have high rates of non-wear, which leads to missing data. Objective activity monitors are also unable to capture valuable contextual information about behavior. Adolescents recruited into physical activity surveillance and intervention studies will increasingly have smartphones, which are miniature computers with built-in motion sensors. This paper describes the design and development of a smartphone application ("app") called Mobile Teen that combines objective and self-report assessment strategies through (1) sensor-informed context-sensitive ecological momentary assessment (CS-EMA) and (2) sensor-assisted end-of-day recall. The Mobile Teen app uses the mobile phone's built-in motion sensor to automatically detect likely bouts of phone non-wear, sedentary behavior, and physical activity. The app then uses transitions between these inferred states to trigger CS-EMA self-report surveys measuring the type, purpose, and context of activity in real-time. The end of the day recall component of the Mobile Teen app allows users to interactively review and label their own physical activity data each evening using visual cues from automatically detected major activity transitions from the phone's built-in motion sensors. Major activity transitions are identified by the app, which cues the user to label that "chunk," or period, of time using activity categories. Sensor-driven CS-EMA and end-of-day recall smartphone apps can be used to augment physical activity data collected by objective activity monitors, filling in gaps during non-wear bouts and providing additional real-time data on environmental, social, and emotional correlates of behavior. Smartphone apps such as these have potential for affordable deployment in large-scale epidemiological and intervention studies.

Development of a Smartphone Application to Measure Physical Activity Using Sensor-Assisted Self-Report

PubMed Central

Dunton, Genevieve Fridlund; Dzubur, Eldin; Kawabata, Keito; Yanez, Brenda; Bo, Bin; Intille, Stephen

2013-01-01

Introduction: Despite the known advantages of objective physical activity monitors (e.g., accelerometers), these devices have high rates of non-wear, which leads to missing data. Objective activity monitors are also unable to capture valuable contextual information about behavior. Adolescents recruited into physical activity surveillance and intervention studies will increasingly have smartphones, which are miniature computers with built-in motion sensors. Methods: This paper describes the design and development of a smartphone application (“app”) called Mobile Teen that combines objective and self-report assessment strategies through (1) sensor-informed context-sensitive ecological momentary assessment (CS-EMA) and (2) sensor-assisted end-of-day recall. Results: The Mobile Teen app uses the mobile phone’s built-in motion sensor to automatically detect likely bouts of phone non-wear, sedentary behavior, and physical activity. The app then uses transitions between these inferred states to trigger CS-EMA self-report surveys measuring the type, purpose, and context of activity in real-time. The end of the day recall component of the Mobile Teen app allows users to interactively review and label their own physical activity data each evening using visual cues from automatically detected major activity transitions from the phone’s built-in motion sensors. Major activity transitions are identified by the app, which cues the user to label that “chunk,” or period, of time using activity categories. Conclusion: Sensor-driven CS-EMA and end-of-day recall smartphone apps can be used to augment physical activity data collected by objective activity monitors, filling in gaps during non-wear bouts and providing additional real-time data on environmental, social, and emotional correlates of behavior. Smartphone apps such as these have potential for affordable deployment in large-scale epidemiological and intervention studies. PMID:24616888

Impact of Sensor Misplacement on Dynamic Time Warping Based Human Activity Recognition using Wearable Computers.

PubMed

Kale, Nimish; Lee, Jaeseong; Lotfian, Reza; Jafari, Roozbeh

2012-10-01

Daily living activity monitoring is important for early detection of the onset of many diseases and for improving quality of life especially in elderly. A wireless wearable network of inertial sensor nodes can be used to observe daily motions. Continuous stream of data generated by these sensor networks can be used to recognize the movements of interest. Dynamic Time Warping (DTW) is a widely used signal processing method for time-series pattern matching because of its robustness to variations in time and speed as opposed to other template matching methods. Despite this flexibility, for the application of activity recognition, DTW can only find the similarity between the template of a movement and the incoming samples, when the location and orientation of the sensor remains unchanged. Due to this restriction, small sensor misplacements can lead to a decrease in the classification accuracy. In this work, we adopt DTW distance as a feature for real-time detection of human daily activities like sit to stand in the presence of sensor misplacement. To measure this performance of DTW, we need to create a large number of sensor configurations while the sensors are rotated or misplaced. Creating a large number of closely spaced sensors is impractical. To address this problem, we use the marker based optical motion capture system and generate simulated inertial sensor data for different locations and orientations on the body. We study the performance of the DTW under these conditions to determine the worst-case sensor location variations that the algorithm can accommodate.

Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

NASA Astrophysics Data System (ADS)

Olivares, A.; Górriz, J. M.; Ramírez, J.; Olivares, G.

2011-02-01

Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed.

Soft Sensors and Actuators based on Nanomaterials

NASA Astrophysics Data System (ADS)

Yao, Shanshan

The focus of this research is using novel bottom-up synthesized nanomaterials and structures to build up devices for wearable sensors and soft actuators. The applications of the wearable sensors towards motion detection and health monitoring are investigated. In addition, flexible heaters for bimorph actuators and stretchable patches made of microgel depots containing drug-loaded nanoparticles (NPs) for stretch-triggered wearable drug delivery are studied. Considerable efforts have been made to achieve highly sensitive and wearable sensors that can simultaneously detect multiple stimuli such as stretch, pressure, temperature or touch. Highly stretchable multifunctional sensors that can detect strain (up to 50%), pressure (up to 1 MPa) and finger touch with good sensitivity, fast response time ( 40 ms) and good pressure mapping function were developed. The sensors were demonstrated for several wearable applications including monitoring thumb movements and knee motions, illustrating the potential utilities of such sensors in robotic systems, prosthetics, healthcare and flexible touch panels. In addition to mechanical sensors, a wearable skin hydration sensor made of silver nanowires (AgNWs) in a polydimethylsiloxane (PDMS) matrix was demonstrated based on skin impedance measurement. The hydration sensors were packaged into a flexible wristband for skin hydration monitoring and a chest patch consisting of a strain sensor, three electrocardiogram (ECG) electrodes and a skin hydration sensor for multimodal sensing. The wearable wristband and chest patch may be used for low-cost, wireless and continuous sensing of skin hydration and other health parameters. Two representative applications of the nanomaterials for soft actuators were investigated. In the first application on bimorph actuation, low-voltage and extremely flexible electrothermal bimorph actuators were fabricated in a simple, efficient and scalable process. The bimorph actuators were made of flexible AgNW based heaters, which exhibited a fast heating rate of 18°C/s and stable heating performance under large bending. The actuators offered the largest bending angle (720°) or curvature (2.6 cm-1) at a very low actuation voltage (0.2 V sq-1 or 4.5 V) among all types of bimorph actuators that have been reported. The actuators can be designed and fabricated in different configurations that can achieve complex patterns and shapes upon actuation. Two applications of this type of soft actuators were demonstrated towards biomimetic robotics - a crawling robot that can walk spontaneously on ratchet surfaces and a soft gripper that is capable of manipulating lightweight and delicate objects. In another application towards wearable drug delivery, a wearable, tensile strain-triggered drug delivery device consisting of a stretchable elastomer and microgel depots containing drug loaded nanoparticles is described. By applying a tensile strain to the elastomer film, the release of drug from the micro-depot is promoted. Correspondingly, both sustained drug release by daily body motions and pulsatile release by intentional administration can be conveniently achieved. The work demonstrated that the tensile strain, applied to the stretchable device, facilitated release of therapeutics from micro-depots for anticancer and antibacterial treatments, respectively. Moreover, polymeric microneedles were further integrated with the stretch-responsive device for transcutaneous delivery of insulin and regulation of blood glucose levels of chemically-induced type 1 diabetic mice.

Visualizing the history of living spaces.

PubMed

Ivanov, Yuri; Wren, Christopher; Sorokin, Alexander; Kaur, Ishwinder

2007-01-01

The technology available to building designers now makes it possible to monitor buildings on a very large scale. Video cameras and motion sensors are commonplace in practically every office space, and are slowly making their way into living spaces. The application of such technologies, in particular video cameras, while improving security, also violates privacy. On the other hand, motion sensors, while being privacy-conscious, typically do not provide enough information for a human operator to maintain the same degree of awareness about the space that can be achieved by using video cameras. We propose a novel approach in which we use a large number of simple motion sensors and a small set of video cameras to monitor a large office space. In our system we deployed 215 motion sensors and six video cameras to monitor the 3,000-square-meter office space occupied by 80 people for a period of about one year. The main problem in operating such systems is finding a way to present this highly multidimensional data, which includes both spatial and temporal components, to a human operator to allow browsing and searching recorded data in an efficient and intuitive way. In this paper we present our experiences and the solutions that we have developed in the course of our work on the system. We consider this work to be the first step in helping designers and managers of building systems gain access to information about occupants' behavior in the context of an entire building in a way that is only minimally intrusive to the occupants' privacy.

ShakeNet: a portable wireless sensor network for instrumenting large civil structures

USGS Publications Warehouse

Kohler, Monica D.; Hao, Shuai; Mishra, Nilesh; Govindan, Ramesh; Nigbor, Robert

2015-08-03

We report our findings from a U.S. Geological Survey (USGS) National Earthquake Hazards Reduction Program-funded project to develop and test a wireless, portable, strong-motion network of up to 40 triaxial accelerometers for structural health monitoring. The overall goal of the project was to record ambient vibrations for several days from USGS-instrumented structures. Structural health monitoring has important applications in fields like civil engineering and the study of earthquakes. The emergence of wireless sensor networks provides a promising means to such applications. However, while most wireless sensor networks are still in the experimentation stage, very few take into consideration the realistic earthquake engineering application requirements. To collect comprehensive data for structural health monitoring for civil engineers, high-resolution vibration sensors and sufficient sampling rates should be adopted, which makes it challenging for current wireless sensor network technology in the following ways: processing capabilities, storage limit, and communication bandwidth. The wireless sensor network has to meet expectations set by wired sensor devices prevalent in the structural health monitoring community. For this project, we built and tested an application-realistic, commercially based, portable, wireless sensor network called ShakeNet for instrumentation of large civil structures, especially for buildings, bridges, or dams after earthquakes. Two to three people can deploy ShakeNet sensors within hours after an earthquake to measure the structural response of the building or bridge during aftershocks. ShakeNet involved the development of a new sensing platform (ShakeBox) running a software suite for networking, data collection, and monitoring. Deployments reported here on a tall building and a large dam were real-world tests of ShakeNet operation, and helped to refine both hardware and software. 

A Soft Sensor-Based Three-Dimensional (3-D) Finger Motion Measurement System

PubMed Central

Park, Wookeun; Ro, Kyongkwan; Kim, Suin; Bae, Joonbum

2017-01-01

In this study, a soft sensor-based three-dimensional (3-D) finger motion measurement system is proposed. The sensors, made of the soft material Ecoflex, comprise embedded microchannels filled with a conductive liquid metal (EGaln). The superior elasticity, light weight, and sensitivity of soft sensors allows them to be embedded in environments in which conventional sensors cannot. Complicated finger joints, such as the carpometacarpal (CMC) joint of the thumb are modeled to specify the location of the sensors. Algorithms to decouple the signals from soft sensors are proposed to extract the pure flexion, extension, abduction, and adduction joint angles. The performance of the proposed system and algorithms are verified by comparison with a camera-based motion capture system. PMID:28241414

A novel yet effective motion artefact reduction method for continuous physiological monitoring

NASA Astrophysics Data System (ADS)

Alzahrani, A.; Hu, S.; Azorin-Peris, V.; Kalawsky, R.; Zhang, X.; Liu, C.

2014-03-01

This study presents a non-invasive and wearable optical technique to continuously monitor vital human signs as required for personal healthcare in today's increasing ageing population. The study has researched an effective way to capture human critical physiological parameters, i.e., oxygen saturation (SaO2%), heart rate, respiration rate, body temperature, heart rate variability by a closely coupled wearable opto-electronic patch sensor (OEPS) together with real-time and secure wireless communication functionalities. The work presents the first step of this research; an automatic noise cancellation method using a 3-axes MEMS accelerometer to recover signals corrupted by body movement which is one of the biggest sources of motion artefacts. The effects of these motion artefacts have been reduced by an enhanced electronic design and development of self-cancellation of noise and stability of the sensor. The signals from the acceleration and the opto-electronic sensor are highly correlated thus leading to the desired pulse waveform with rich bioinformatics signals to be retrieved with reduced motion artefacts. The preliminary results from the bench tests and the laboratory setup demonstrate that the goal of the high performance wearable opto-electronics is viable and feasible.

The feasibility of using Microsoft Kinect v2 sensors during radiotherapy delivery.

PubMed

Edmunds, David M; Bashforth, Sophie E; Tahavori, Fatemeh; Wells, Kevin; Donovan, Ellen M

2016-11-08

Consumer-grade distance sensors, such as the Microsoft Kinect devices (v1 and v2), have been investigated for use as marker-free motion monitoring systems for radiotherapy. The radiotherapy delivery environment is challenging for such sen-sors because of the proximity to electromagnetic interference (EMI) from the pulse forming network which fires the magnetron and electron gun of a linear accelerator (linac) during radiation delivery, as well as the requirement to operate them from the control area. This work investigated whether using Kinect v2 sensors as motion monitors was feasible during radiation delivery. Three sensors were used each with a 12 m USB 3.0 active cable which replaced the supplied 3 m USB 3.0 cable. Distance output data from the Kinect v2 sensors was recorded under four condi-tions of linac operation: (i) powered up only, (ii) pulse forming network operating with no radiation, (iii) pulse repetition frequency varied between 6 Hz and 400 Hz, (iv) dose rate varied between 50 and 1450 monitor units (MU) per minute. A solid water block was used as an object and imaged when static, moved in a set of steps from 0.6 m to 2.0 m from the sensor and moving dynamically in two sinusoidal-like trajectories. Few additional image artifacts were observed and there was no impact on the tracking of the motion patterns (root mean squared accuracy of 1.4 and 1.1mm, respectively). The sensors' distance accuracy varied by 2.0 to 3.8 mm (1.2 to 1.4 mm post distance calibration) across the range measured; the precision was 1 mm. There was minimal effect from the EMI on the distance calibration data: 0 mm or 1 mm reported distance change (2 mm maximum change at one position). Kinect v2 sensors operated with 12 m USB 3.0 active cables appear robust to the radiotherapy treatment environment. © 2016 The Authors.

Micro-patterned graphene-based sensing skins for human physiological monitoring

NASA Astrophysics Data System (ADS)

Wang, Long; Loh, Kenneth J.; Chiang, Wei-Hung; Manna, Kausik

2018-03-01

Ultrathin, flexible, conformal, and skin-like electronic transducers are emerging as promising candidates for noninvasive and nonintrusive human health monitoring. In this work, a wearable sensing membrane is developed by patterning a graphene-based solution onto ultrathin medical tape, which can then be attached to the skin for monitoring human physiological parameters and physical activity. Here, the sensor is validated for monitoring finger bending/movements and for recognizing hand motion patterns, thereby demonstrating its future potential for evaluating athletic performance, physical therapy, and designing next-generation human-machine interfaces. Furthermore, this study also quantifies the sensor’s ability to monitor eye blinking and radial pulse in real-time, which can find broader applications for the healthcare sector. Overall, the printed graphene-based sensing skin is highly conformable, flexible, lightweight, nonintrusive, mechanically robust, and is characterized by high strain sensitivity.

Mechanical monolithic compact sensors for real-time linear and angular broadband low frequency monitoring and control of spacecrafts and satellites

NASA Astrophysics Data System (ADS)

Barone, F.; Giordano, G.

2017-09-01

In this paper we describe the characteristics and performances of a monolithic sensor designed for low frequency motion measurement of spacecrafts and satellites, whose mechanics is based on the UNISA Folded Pendulum. The latter, developed for ground-based applications, exhibits unique features (compactness, lightness, scalability, low resonance frequency and high quality factor), consequence of the action of the gravitational force on its inertial mass. In this paper we introduce and discuss the general methodology used to extend the application of ground-based folded pendulums to space, also in total absence of gravity, still keeping all their peculiar features and characteristics.

Flexible, Stretchable Sensors for Wearable Health Monitoring: Sensing Mechanisms, Materials, Fabrication Strategies and Features

PubMed Central

Liu, Yan; Wang, Hai; Zhao, Wei; Qin, Hongbo; Xie, Yongqiang

2018-01-01

Wearable health monitoring systems have gained considerable interest in recent years owing to their tremendous promise for personal portable health watching and remote medical practices. The sensors with excellent flexibility and stretchability are crucial components that can provide health monitoring systems with the capability of continuously tracking physiological signals of human body without conspicuous uncomfortableness and invasiveness. The signals acquired by these sensors, such as body motion, heart rate, breath, skin temperature and metabolism parameter, are closely associated with personal health conditions. This review attempts to summarize the recent progress in flexible and stretchable sensors, concerning the detected health indicators, sensing mechanisms, functional materials, fabrication strategies, basic and desired features. The potential challenges and future perspectives of wearable health monitoring system are also briefly discussed. PMID:29470408

Flexible, Stretchable Sensors for Wearable Health Monitoring: Sensing Mechanisms, Materials, Fabrication Strategies and Features.

PubMed

Liu, Yan; Wang, Hai; Zhao, Wei; Zhang, Min; Qin, Hongbo; Xie, Yongqiang

2018-02-22

Wearable health monitoring systems have gained considerable interest in recent years owing to their tremendous promise for personal portable health watching and remote medical practices. The sensors with excellent flexibility and stretchability are crucial components that can provide health monitoring systems with the capability of continuously tracking physiological signals of human body without conspicuous uncomfortableness and invasiveness. The signals acquired by these sensors, such as body motion, heart rate, breath, skin temperature and metabolism parameter, are closely associated with personal health conditions. This review attempts to summarize the recent progress in flexible and stretchable sensors, concerning the detected health indicators, sensing mechanisms, functional materials, fabrication strategies, basic and desired features. The potential challenges and future perspectives of wearable health monitoring system are also briefly discussed.

A Robust Random Forest-Based Approach for Heart Rate Monitoring Using Photoplethysmography Signal Contaminated by Intense Motion Artifacts.

PubMed

Ye, Yalan; He, Wenwen; Cheng, Yunfei; Huang, Wenxia; Zhang, Zhilin

2017-02-16

The estimation of heart rate (HR) based on wearable devices is of interest in fitness. Photoplethysmography (PPG) is a promising approach to estimate HR due to low cost; however, it is easily corrupted by motion artifacts (MA). In this work, a robust approach based on random forest is proposed for accurately estimating HR from the photoplethysmography signal contaminated by intense motion artifacts, consisting of two stages. Stage 1 proposes a hybrid method to effectively remove MA with a low computation complexity, where two MA removal algorithms are combined by an accurate binary decision algorithm whose aim is to decide whether or not to adopt the second MA removal algorithm. Stage 2 proposes a random forest-based spectral peak-tracking algorithm, whose aim is to locate the spectral peak corresponding to HR, formulating the problem of spectral peak tracking into a pattern classification problem. Experiments on the PPG datasets including 22 subjects used in the 2015 IEEE Signal Processing Cup showed that the proposed approach achieved the average absolute error of 1.65 beats per minute (BPM) on the 22 PPG datasets. Compared to state-of-the-art approaches, the proposed approach has better accuracy and robustness to intense motion artifacts, indicating its potential use in wearable sensors for health monitoring and fitness tracking.

Low-dimensional dynamical characterization of human performance of cancer patients using motion data.

PubMed

Hasnain, Zaki; Li, Ming; Dorff, Tanya; Quinn, David; Ueno, Naoto T; Yennu, Sriram; Kolatkar, Anand; Shahabi, Cyrus; Nocera, Luciano; Nieva, Jorge; Kuhn, Peter; Newton, Paul K

2018-05-18

Biomechanical characterization of human performance with respect to fatigue and fitness is relevant in many settings, however is usually limited to either fully qualitative assessments or invasive methods which require a significant experimental setup consisting of numerous sensors, force plates, and motion detectors. Qualitative assessments are difficult to standardize due to their intrinsic subjective nature, on the other hand, invasive methods provide reliable metrics but are not feasible for large scale applications. Presented here is a dynamical toolset for detecting performance groups using a non-invasive system based on the Microsoft Kinect motion capture sensor, and a case study of 37 cancer patients performing two clinically monitored tasks before and after therapy regimens. Dynamical features are extracted from the motion time series data and evaluated based on their ability to i) cluster patients into coherent fitness groups using unsupervised learning algorithms and to ii) predict Eastern Cooperative Oncology Group performance status via supervised learning. The unsupervised patient clustering is comparable to clustering based on physician assigned Eastern Cooperative Oncology Group status in that they both have similar concordance with change in weight before and after therapy as well as unexpected hospitalizations throughout the study. The extracted dynamical features can predict physician, coordinator, and patient Eastern Cooperative Oncology Group status with an accuracy of approximately 80%. The non-invasive Microsoft Kinect sensor and the proposed dynamical toolset comprised of data preprocessing, feature extraction, dimensionality reduction, and machine learning offers a low-cost and general method for performance segregation and can complement existing qualitative clinical assessments. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of a Waterproof Crack-Based Stretchable Strain Sensor Based on PDMS Shielding.

PubMed

Hong, Seong Kyung; Yang, Seongjin; Cho, Seong J; Jeon, Hyungkook; Lim, Geunbae

2018-04-12

This paper details the design of a poly(dimethylsiloxane) (PDMS)-shielded waterproof crack-based stretchable strain sensor, in which the electrical characteristics and sensing performance are not influenced by changes in humidity. This results in a higher number of potential applications for the sensor. A previously developed omni-purpose stretchable strain (OPSS) sensor was used as the basis for this work, which utilizes a metal cracking structure and provides a wide sensing range and high sensitivity. Changes in the conductivity of the OPSS sensor, based on humidity conditions, were investigated along with the potential possibility of using the design as a humidity sensor. However, to prevent conductivity variation, which can decrease the reliability and sensing ability of the OPSS sensor, PDMS was utilized as a shielding layer over the OPSS sensor. The PDMS-shielded OPSS sensor showed approximately the same electrical characteristics as previous designs, including in a high humidity environment, while maintaining its strain sensing capabilities. The developed sensor shows promise for use under high humidity conditions and in underwater applications. Therefore, considering its unique features and reliable sensing performance, the developed PDMS-shielded waterproof OPSS sensor has potential utility in a wide range of applications, such as motion monitoring, medical robotics and wearable healthcare devices.

Hand-writing motion tracking with vision-inertial sensor fusion: calibration and error correction.

PubMed

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J

2014-08-25

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model.

Telemonitoring of patients with Parkinson's disease using inertia sensors.

PubMed

Piro, N E; Baumann, L; Tengler, M; Piro, L; Blechschmidt-Trapp, R

2014-01-01

Medical treatment in patients suffering from Parkinson's disease is very difficult as dose-finding is mainly based on selective and subjective impressions by the physician. To allow for the objective evaluation of patients' symptoms required for optimal dosefinding, a telemonitoring system tracks the motion of patients in their surroundings. The system focuses on providing interoperability and usability in order to ensure high acceptance. Patients wear inertia sensors and perform standardized motor tasks. Data are recorded, processed and then presented to the physician in a 3D animated form. In addition, the same data is rated based on the UPDRS score. Interoperability is realized by developing the system in compliance with the recommendations of the Continua Health Alliance. Detailed requirements analysis and continuous collaboration with respective user groups help to achieve high usability. A sensor platform was developed that is capable of measuring acceleration and angular rate of motions as well as the absolute orientation of the device itself through an included compass sensor. The system architecture was designed and required infrastructure, and essential parts of the communication between the system components were implemented following Continua guidelines. Moreover, preliminary data analysis based on three-dimensional acceleration and angular rate data could be established. A prototype system for the telemonitoring of Parkinson's disease patients was successfully developed. The developed sensor platform fully satisfies the needs of monitoring patients of Parkinson's disease and is comparable to other sensor platforms, although these sensor platforms have yet to be tested rigorously against each other. Suitable approaches to provide interoperability and usability were identified and realized and remain to be tested in the field.

Triboelectrification based motion sensor for human-machine interfacing.

PubMed

Yang, Weiqing; Chen, Jun; Wen, Xiaonan; Jing, Qingshen; Yang, Jin; Su, Yuanjie; Zhu, Guang; Wu, Wenzuo; Wang, Zhong Lin

2014-05-28

We present triboelectrification based, flexible, reusable, and skin-friendly dry biopotential electrode arrays as motion sensors for tracking muscle motion and human-machine interfacing (HMI). The independently addressable, self-powered sensor arrays have been utilized to record the electric output signals as a mapping figure to accurately identify the degrees of freedom as well as directions and magnitude of muscle motions. A fast Fourier transform (FFT) technique was employed to analyse the frequency spectra of the obtained electric signals and thus to determine the motion angular velocities. Moreover, the motion sensor arrays produced a short-circuit current density up to 10.71 mA/m(2), and an open-circuit voltage as high as 42.6 V with a remarkable signal-to-noise ratio up to 1000, which enables the devices as sensors to accurately record and transform the motions of the human joints, such as elbow, knee, heel, and even fingers, and thus renders it a superior and unique invention in the field of HMI.

A novel sensor for two-degree-of-freedom motion measurement of linear nanopositioning stage using knife edge displacement sensing technique

NASA Astrophysics Data System (ADS)

Zolfaghari, Abolfazl; Jeon, Seongkyul; Stepanick, Christopher K.; Lee, ChaBum

2017-06-01

This paper presents a novel method for measuring two-degree-of-freedom (DOF) motion of flexure-based nanopositioning systems based on optical knife-edge sensing (OKES) technology, which utilizes the interference of two superimposed waves: a geometrical wave from the primary source of light and a boundary diffraction wave from the secondary source. This technique allows for two-DOF motion measurement of the linear and pitch motions of nanopositioning systems. Two capacitive sensors (CSs) are used for a baseline comparison with the proposed sensor by simultaneously measuring the motions of the nanopositioning system. The experimental results show that the proposed sensor closely agrees with the fundamental linear motion of the CS. However, the two-DOF OKES technology was shown to be approximately three times more sensitive to the pitch motion than the CS. The discrepancy in the two sensor outputs is discussed in terms of measuring principle, linearity, bandwidth, control effectiveness, and resolution.

Movement Behaviour of Traditionally Managed Cattle in the Eastern Province of Zambia Captured Using Two-Dimensional Motion Sensors.

PubMed

Lubaba, Caesar H; Hidano, Arata; Welburn, Susan C; Revie, Crawford W; Eisler, Mark C

2015-01-01

Two-dimensional motion sensors use electronic accelerometers to record the lying, standing and walking activity of cattle. Movement behaviour data collected automatically using these sensors over prolonged periods of time could be of use to stakeholders making management and disease control decisions in rural sub-Saharan Africa leading to potential improvements in animal health and production. Motion sensors were used in this study with the aim of monitoring and quantifying the movement behaviour of traditionally managed Angoni cattle in Petauke District in the Eastern Province of Zambia. This study was designed to assess whether motion sensors were suitable for use on traditionally managed cattle in two veterinary camps in Petauke District in the Eastern Province of Zambia. In each veterinary camp, twenty cattle were selected for study. Each animal had a motion sensor placed on its hind leg to continuously measure and record its movement behaviour over a two week period. Analysing the sensor data using principal components analysis (PCA) revealed that the majority of variability in behaviour among studied cattle could be attributed to their behaviour at night and in the morning. The behaviour at night was markedly different between veterinary camps; while differences in the morning appeared to reflect varying behaviour across all animals. The study results validate the use of such motion sensors in the chosen setting and highlight the importance of appropriate data summarisation techniques to adequately describe and compare animal movement behaviours if association to other factors, such as location, breed or health status are to be assessed.

Accelerometer-based on-body sensor localization for health and medical monitoring applications

PubMed Central

Vahdatpour, Alireza; Amini, Navid; Xu, Wenyao; Sarrafzadeh, Majid

2011-01-01

In this paper, we present a technique to recognize the position of sensors on the human body. Automatic on-body device localization ensures correctness and accuracy of measurements in health and medical monitoring systems. In addition, it provides opportunities to improve the performance and usability of ubiquitous devices. Our technique uses accelerometers to capture motion data to estimate the location of the device on the user’s body, using mixed supervised and unsupervised time series analysis methods. We have evaluated our technique with extensive experiments on 25 subjects. On average, our technique achieves 89% accuracy in estimating the location of devices on the body. In order to study the feasibility of classification of left limbs from right limbs (e.g., left arm vs. right arm), we performed analysis, based of which no meaningful classification was observed. Personalized ultraviolet monitoring and wireless transmission power control comprise two immediate applications of our on-body device localization approach. Such applications, along with their corresponding feasibility studies, are discussed. PMID:22347840

Open architecture CMM motion controller

NASA Astrophysics Data System (ADS)

Chang, David; Spence, Allan D.; Bigg, Steve; Heslip, Joe; Peterson, John

2001-12-01

Although initially the only Coordinate Measuring Machine (CMM) sensor available was a touch trigger probe, technological advances in sensors and computing have greatly increased the variety of available inspection sensors. Non-contact laser digitizers and analog scanning touch probes require very well tuned CMM motion control, as well as an extensible, open architecture interface. This paper describes the implementation of a retrofit CMM motion controller designed for open architecture interface to a variety of sensors. The controller is based on an Intel Pentium microcomputer and a Servo To Go motion interface electronics card. Motor amplifiers, safety, and additional interface electronics are housed in a separate enclosure. Host Signal Processing (HSP) is used for the motion control algorithm. Compared to the usual host plus DSP architecture, single CPU HSP simplifies integration with the various sensors, and implementation of software geometric error compensation. Motion control tuning is accomplished using a remote computer via 100BaseTX Ethernet. A Graphical User Interface (GUI) is used to enter geometric error compensation data, and to optimize the motion control tuning parameters. It is shown that this architecture achieves the required real time motion control response, yet is much easier to extend to additional sensors.

The effect of ego-motion on environmental monitoring.

PubMed

Lerner, Uri; Yacobi, Tamar; Levy, Ilan; Moltchanov, Sharon A; Cole-Hunter, Tom; Fishbain, Barak

2015-11-15

Air pollution has a proven impact on public health. Currently, pollutant levels are obtained by high-priced, sizeable, stationary Air Quality Monitoring (AQM) stations. Recent developments in sensory and communication technologies have made relatively low-cost, micro-sensing units (MSUs) feasible. Their lower power consumption and small size enable mobile sensing, deploying single or multiple units simultaneously. Recent studies have reported on measurements acquired by mobile MSUs, mounted on cars, bicycles and pedestrians. While these modes of transportation inherently present different velocity and acceleration regimes, the effect of the sensors' varying movement characteristics have not been previously accounted for. This research assesses the impact of sensor's motion on its functionality through laboratory measurements and a field campaign. The laboratory setup consists of a wind tunnel to assess the effect of air flow on the measurements of nitrogen dioxide and ozone at different velocities in a controlled environment, while the field campaign is based on three cars mounted with MSUs, measuring pollutants and environmental variables at different traveling speeds. In both experimental designs we can regard the MSUs as a moving object in the environment, i.e. having a distinct ego-motion. The results show that MSU's behavior is highly affected by variation in speed and sensor placement with respect to direction of movement, mainly due to the physical properties of installed sensors. This strongly suggests that any future design of MSU must account for the speed effect from the design stage all the way through deployment and results analysis. This is the first report examining the influence of airflow variations on MSU's ability to accurately measure pollutant levels. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative Assessment of Parkinsonian Tremor Based on an Inertial Measurement Unit

PubMed Central

Dai, Houde; Zhang, Pengyue; Lueth, Tim C.

2015-01-01

Quantitative assessment of parkinsonian tremor based on inertial sensors can provide reliable feedback on the effect of medication. In this regard, the features of parkinsonian tremor and its unique properties such as motor fluctuations and dyskinesia are taken into account. Least-square-estimation models are used to assess the severities of rest, postural, and action tremors. In addition, a time-frequency signal analysis algorithm for tremor state detection was also included in the tremor assessment method. This inertial sensor-based method was verified through comparison with an electromagnetic motion tracking system. Seven Parkinson’s disease (PD) patients were tested using this tremor assessment system. The measured tremor amplitudes correlated well with the judgments of a neurologist (r = 0.98). The systematic analysis of sensor-based tremor quantification and the corresponding experiments could be of great help in monitoring the severity of parkinsonian tremor. PMID:26426020

A highly shape-adaptive, stretchable design based on conductive liquid for energy harvesting and self-powered biomechanical monitoring

PubMed Central

Yi, Fang; Wang, Xiaofeng; Niu, Simiao; Li, Shengming; Yin, Yajiang; Dai, Keren; Zhang, Guangjie; Lin, Long; Wen, Zhen; Guo, Hengyu; Wang, Jie; Yeh, Min-Hsin; Zi, Yunlong; Liao, Qingliang; You, Zheng; Zhang, Yue; Wang, Zhong Lin

2016-01-01

The rapid growth of deformable and stretchable electronics calls for a deformable and stretchable power source. We report a scalable approach for energy harvesters and self-powered sensors that can be highly deformable and stretchable. With conductive liquid contained in a polymer cover, a shape-adaptive triboelectric nanogenerator (saTENG) unit can effectively harvest energy in various working modes. The saTENG can maintain its performance under a strain of as large as 300%. The saTENG is so flexible that it can be conformed to any three-dimensional and curvilinear surface. We demonstrate applications of the saTENG as a wearable power source and self-powered sensor to monitor biomechanical motion. A bracelet-like saTENG worn on the wrist can light up more than 80 light-emitting diodes. Owing to the highly scalable manufacturing process, the saTENG can be easily applied for large-area energy harvesting. In addition, the saTENG can be extended to extract energy from mechanical motion using flowing water as the electrode. This approach provides a new prospect for deformable and stretchable power sources, as well as self-powered sensors, and has potential applications in various areas such as robotics, biomechanics, physiology, kinesiology, and entertainment. PMID:27386560

A highly shape-adaptive, stretchable design based on conductive liquid for energy harvesting and self-powered biomechanical monitoring.

PubMed

Yi, Fang; Wang, Xiaofeng; Niu, Simiao; Li, Shengming; Yin, Yajiang; Dai, Keren; Zhang, Guangjie; Lin, Long; Wen, Zhen; Guo, Hengyu; Wang, Jie; Yeh, Min-Hsin; Zi, Yunlong; Liao, Qingliang; You, Zheng; Zhang, Yue; Wang, Zhong Lin

2016-06-01

The rapid growth of deformable and stretchable electronics calls for a deformable and stretchable power source. We report a scalable approach for energy harvesters and self-powered sensors that can be highly deformable and stretchable. With conductive liquid contained in a polymer cover, a shape-adaptive triboelectric nanogenerator (saTENG) unit can effectively harvest energy in various working modes. The saTENG can maintain its performance under a strain of as large as 300%. The saTENG is so flexible that it can be conformed to any three-dimensional and curvilinear surface. We demonstrate applications of the saTENG as a wearable power source and self-powered sensor to monitor biomechanical motion. A bracelet-like saTENG worn on the wrist can light up more than 80 light-emitting diodes. Owing to the highly scalable manufacturing process, the saTENG can be easily applied for large-area energy harvesting. In addition, the saTENG can be extended to extract energy from mechanical motion using flowing water as the electrode. This approach provides a new prospect for deformable and stretchable power sources, as well as self-powered sensors, and has potential applications in various areas such as robotics, biomechanics, physiology, kinesiology, and entertainment.

Development of Non-contact Respiratory Monitoring System for Newborn Using a FG Vision Sensor

NASA Astrophysics Data System (ADS)

Kurami, Yoshiyuki; Itoh, Yushi; Natori, Michiya; Ohzeki, Kazuo; Aoki, Yoshimitsu

In recent years, development of neonatal care is strongly hoped, with increase of the low-birth-weight baby birth rate. Especially respiration of low-birth-weight baby is incertitude because central nerve and respiratory function is immature. Therefore, a low-birth-weight baby often causes a disease of respiration. In a NICU (Neonatal Intensive Care Unit), neonatal respiration is monitored using cardio-respiratory monitor and pulse oximeter at all times. These contact-type sensors can measure respiratory rate and SpO2 (Saturation of Peripheral Oxygen). However, because a contact-type sensor might damage the newborn's skin, it is a real burden to monitor neonatal respiration. Therefore, we developed the respiratory monitoring system for newborn using a FG (Fiber Grating) vision sensor. FG vision sensor is an active stereo vision sensor, it is possible for non-contact 3D measurement. A respiratory waveform is calculated by detecting the vertical motion of the thoracic and abdominal region with respiration. We attempted clinical experiment in the NICU, and confirmed the accuracy of the obtained respiratory waveform was high. Non-contact respiratory monitoring of newborn using a FG vision sensor enabled the minimally invasive procedure.

OLAM: A wearable, non-contact sensor for continuous heart-rate and activity monitoring.

PubMed

Albright, Ryan K; Goska, Benjamin J; Hagen, Tory M; Chi, Mike Y; Cauwenberghs, G; Chiang, Patrick Y

2011-01-01

A wearable, multi-modal sensor is presented that can non-invasively monitor a patient's activity level and heart function concurrently for more than a week. The 4 in(2) sensor incorporates both a non-contact heartrate sensor and a 5-axis inertial measurement unit (IMU), allowing simultaneous heart, respiration, and movement monitoring without requiring physical contact with the skin [1]. Hence, this Oregon State University Life and Activity Monitor (OLAM) provides the unique opportunity to combine motion data with heart-rate information, enabling assessment of actual physical activity beyond conventional movement sensors. OLAM also provides a unique platform for non-contact sensing, enabling the filtering of movement artifacts generated by the non-contact capacitive interface, using the IMU data as a movement noise channel. Intended to be used in clinical trials for weeks at a time with no physician intervention, the OLAM allows continuous non-invasive monitoring of patients, providing the opportunity for long-term observation into a patient's physical activity and subtle longitudinal changes.

User-Independent Motion State Recognition Using Smartphone Sensors

PubMed Central

Gu, Fuqiang; Kealy, Allison; Khoshelham, Kourosh; Shang, Jianga

2015-01-01

The recognition of locomotion activities (e.g., walking, running, still) is important for a wide range of applications like indoor positioning, navigation, location-based services, and health monitoring. Recently, there has been a growing interest in activity recognition using accelerometer data. However, when utilizing only acceleration-based features, it is difficult to differentiate varying vertical motion states from horizontal motion states especially when conducting user-independent classification. In this paper, we also make use of the newly emerging barometer built in modern smartphones, and propose a novel feature called pressure derivative from the barometer readings for user motion state recognition, which is proven to be effective for distinguishing vertical motion states and does not depend on specific users’ data. Seven types of motion states are defined and six commonly-used classifiers are compared. In addition, we utilize the motion state history and the characteristics of people’s motion to improve the classification accuracies of those classifiers. Experimental results show that by using the historical information and human’s motion characteristics, we can achieve user-independent motion state classification with an accuracy of up to 90.7%. In addition, we analyze the influence of the window size and smartphone pose on the accuracy. PMID:26690163

User-Independent Motion State Recognition Using Smartphone Sensors.

PubMed

Gu, Fuqiang; Kealy, Allison; Khoshelham, Kourosh; Shang, Jianga

2015-12-04

The recognition of locomotion activities (e.g., walking, running, still) is important for a wide range of applications like indoor positioning, navigation, location-based services, and health monitoring. Recently, there has been a growing interest in activity recognition using accelerometer data. However, when utilizing only acceleration-based features, it is difficult to differentiate varying vertical motion states from horizontal motion states especially when conducting user-independent classification. In this paper, we also make use of the newly emerging barometer built in modern smartphones, and propose a novel feature called pressure derivative from the barometer readings for user motion state recognition, which is proven to be effective for distinguishing vertical motion states and does not depend on specific users' data. Seven types of motion states are defined and six commonly-used classifiers are compared. In addition, we utilize the motion state history and the characteristics of people's motion to improve the classification accuracies of those classifiers. Experimental results show that by using the historical information and human's motion characteristics, we can achieve user-independent motion state classification with an accuracy of up to 90.7%. In addition, we analyze the influence of the window size and smartphone pose on the accuracy.

Dynamic Metasurface Aperture as Smart Around-the-Corner Motion Detector.

PubMed

Del Hougne, Philipp; F Imani, Mohammadreza; Sleasman, Timothy; Gollub, Jonah N; Fink, Mathias; Lerosey, Geoffroy; Smith, David R

2018-04-25

Detecting and analysing motion is a key feature of Smart Homes and the connected sensor vision they embrace. At present, most motion sensors operate in line-of-sight Doppler shift schemes. Here, we propose an alternative approach suitable for indoor environments, which effectively constitute disordered cavities for radio frequency (RF) waves; we exploit the fundamental sensitivity of modes of such cavities to perturbations, caused here by moving objects. We establish experimentally three key features of our proposed system: (i) ability to capture the temporal variations of motion and discern information such as periodicity ("smart"), (ii) non line-of-sight motion detection, and (iii) single-frequency operation. Moreover, we explain theoretically and demonstrate experimentally that the use of dynamic metasurface apertures can substantially enhance the performance of RF motion detection. Potential applications include accurately detecting human presence and monitoring inhabitants' vital signs.

A Novel Sensor System for Measuring Wheel Loads of Vehicles on Highways

PubMed Central

Zhang, Wenbin; Suo, Chunguang; Wang, Qi

2008-01-01

With the development of the highway transportation and business trade, vehicle Weigh-In-Motion (WIM) technology has become a key technology for measuring traffic loads. In this paper a novel WIM system based on monitoring of pavement strain responses in rigid pavement was investigated. In this WIM system multiple low cost, light weight, small volume and high accuracy embedded concrete strain sensors were used as WIM sensors to measure rigid pavement strain responses. In order to verify the feasibility of the method, a system prototype based on multiple sensors was designed and deployed on a relatively busy freeway. Field calibration and tests were performed with known two-axle truck wheel loads and the measurement errors were calculated based on the static weights measured with a static weighbridge. This enables the weights of other vehicles to be calculated from the calibration constant. Calibration and test results for individual sensors or three-sensor fusions are both provided. Repeatability, sources of error, and weight accuracy are discussed. Successful results showed that the proposed method was feasible and proven to have a high accuracy. Furthermore, a sample mean approach using multiple fused individual sensors could provide better performance compared to individual sensors. PMID:27873952

Wearable PPG sensor based alertness scoring system.

PubMed

Dey, Jishnu; Bhowmik, Tanmoy; Sahoo, Saswata; Tiwari, Vijay Narayan

2017-07-01

Quantifying mental alertness in today's world is important as it enables the person to adopt lifestyle changes for better work efficiency. Miniaturized sensors in wearable devices have facilitated detection/monitoring of mental alertness. Photoplethysmography (PPG) sensors through Heart Rate Variability (HRV) offer one such opportunity by providing information about one's daily alertness levels without requiring any manual interference from the user. In this paper, a smartwatch based alertness estimation system is proposed. Data collected from PPG sensor of smartwatch is processed and fed to machine learning based model to get a continuous alertness score. Utility functions are designed based on statistical analysis to give a quality score on different stages of alertness such as awake, long sleep and short duration power nap. An intelligent data collection approach is proposed in collaboration with the motion sensor in the smartwatch to reduce battery drainage. Overall, our proposed wearable based system provides a detailed analysis of alertness over a period in a systematic and optimized manner. We were able to achieve an accuracy of 80.1% for sleep/awake classification along with alertness score. This opens up the possibility for quantifying alertness levels using a single PPG sensor for better management of health related activities including sleep.

Large-Area All-Textile Pressure Sensors for Monitoring Human Motion and Physiological Signals.

PubMed

Liu, Mengmeng; Pu, Xiong; Jiang, Chunyan; Liu, Ting; Huang, Xin; Chen, Libo; Du, Chunhua; Sun, Jiangman; Hu, Weiguo; Wang, Zhong Lin

2017-11-01

Wearable pressure sensors, which can perceive and respond to environmental stimuli, are essential components of smart textiles. Here, large-area all-textile-based pressure-sensor arrays are successfully realized on common fabric substrates. The textile sensor unit achieves high sensitivity (14.4 kPa -1 ), low detection limit (2 Pa), fast response (≈24 ms), low power consumption (<6 µW), and mechanical stability under harsh deformations. Thanks to these merits, the textile sensor is demonstrated to be able to recognize finger movement, hand gestures, acoustic vibrations, and real-time pulse wave. Furthermore, large-area sensor arrays are successfully fabricated on one textile substrate to spatially map tactile stimuli and can be directly incorporated into a fabric garment for stylish designs without sacrifice of comfort, suggesting great potential in smart textiles or wearable electronics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Development of Wireless Body Area Network for Motion Sensing Application

NASA Astrophysics Data System (ADS)

Puspitaningayu, P.; Widodo, A.; Yundra, E.; Ramadhany, F.; Arianto, L.; Habibie, D.

2018-04-01

The information era has driven the society into the digitally-controlled lifestyle. Wireless body area networks (WBAN) as the specific scope of wireless sensor networks (WSN) is consistently growing into bigger applications. Currently, people are able to monitor their medical parameters by simply using small electronics devices attached to their body and connected to the authorities. On top of that, this time, smart phones are typically equipped with sensors such as accelerometer, gyroscope, barometric pressure, heart rate monitor, etc. It means that the sensing yet the signal processing can be performed by a single device. Moreover, Android opens lot wider opportunities for new applications as the most popular open-sourced smart phone platform. This paper is intended to show the development of motion sensing application which focused on analysing data from accelerometer and gyroscope. Beside reads the sensors, this application also has the ability to convert the sensors’ numerical value into graphs.

The lucky image-motion prediction for simple scene observation based soft-sensor technology

NASA Astrophysics Data System (ADS)

Li, Yan; Su, Yun; Hu, Bin

2015-08-01

High resolution is important to earth remote sensors, while the vibration of the platforms of the remote sensors is a major factor restricting high resolution imaging. The image-motion prediction and real-time compensation are key technologies to solve this problem. For the reason that the traditional autocorrelation image algorithm cannot meet the demand for the simple scene image stabilization, this paper proposes to utilize soft-sensor technology in image-motion prediction, and focus on the research of algorithm optimization in imaging image-motion prediction. Simulations results indicate that the improving lucky image-motion stabilization algorithm combining the Back Propagation Network (BP NN) and support vector machine (SVM) is the most suitable for the simple scene image stabilization. The relative error of the image-motion prediction based the soft-sensor technology is below 5%, the training computing speed of the mathematical predication model is as fast as the real-time image stabilization in aerial photography.

Mobile Monitoring Data Processing & Analysis Strategies

EPA Science Inventory

The development of portable, high-time resolution instruments for measuring the concentrations of a variety of air pollutants has made it possible to collect data while in motion. This strategy, known as mobile monitoring, involves mounting air sensors on variety of different pla...

Highly Sensitive Flexible Human Motion Sensor Based on ZnSnO3/PVDF Composite

NASA Astrophysics Data System (ADS)

Yang, Young Jin; Aziz, Shahid; Mehdi, Syed Murtuza; Sajid, Memoon; Jagadeesan, Srikanth; Choi, Kyung Hyun

2017-07-01

A highly sensitive body motion sensor has been fabricated based on a composite active layer of zinc stannate (ZnSnO3) nano-cubes and poly(vinylidene fluoride) (PVDF) polymer. The thin film-based active layer was deposited on polyethylene terephthalate flexible substrate through D-bar coating technique. Electrical and morphological characterizations of the films and sensors were carried out to discover the physical characteristics and the output response of the devices. The synergistic effect between piezoelectric ZnSnO3 nanocubes and β phase PVDF provides the composite with a desirable electrical conductivity, remarkable bend sensitivity, and excellent stability, ideal for the fabrication of a motion sensor. The recorded resistance of the sensor towards the bending angles of -150° to 0° to 150° changed from 20 MΩ to 55 MΩ to 100 MΩ, respectively, showing the composite to be a very good candidate for motion sensing applications.

Sheath-Core Graphite/Silk Fiber Made by Dry-Meyer-Rod-Coating for Wearable Strain Sensors.

PubMed

Zhang, Mingchao; Wang, Chunya; Wang, Qi; Jian, Muqiang; Zhang, Yingying

2016-08-17

Recent years have witnessed the explosive development of flexible strain sensors. Nanomaterials have been widely utilized to fabricate flexible strain sensors, because of their high flexibility and electrical conductivity. However, the fabrication processes for nanomaterials and the subsequent strain sensors are generally complicated and are manufactured at high cost. In this work, we developed a facile dry-Meyer-rod-coating process to fabricate sheath-core-structured single-fiber strain sensors using ultrafine graphite flakes as the sheath and silk fibers as the core by virtue of their flexibility, high production, and low cost. The fabricated strain sensor exhibits a high sensitivity with a gauge factor of 14.5 within wide workable strain range up to 15%, and outstanding stability (up to 3000 cycles). The single-fiber-based strain sensors could be attached to a human body to detect joint motions or easily integrated into the multidirectional strain sensor for monitoring multiaxial strain, showing great potential applications as wearable strain sensors.

Mobile robotic sensors for perimeter detection and tracking.

PubMed

Clark, Justin; Fierro, Rafael

2007-02-01

Mobile robot/sensor networks have emerged as tools for environmental monitoring, search and rescue, exploration and mapping, evaluation of civil infrastructure, and military operations. These networks consist of many sensors each equipped with embedded processors, wireless communication, and motion capabilities. This paper describes a cooperative mobile robot network capable of detecting and tracking a perimeter defined by a certain substance (e.g., a chemical spill) in the environment. Specifically, the contributions of this paper are twofold: (i) a library of simple reactive motion control algorithms and (ii) a coordination mechanism for effectively carrying out perimeter-sensing missions. The decentralized nature of the methodology implemented could potentially allow the network to scale to many sensors and to reconfigure when adding/deleting sensors. Extensive simulation results and experiments verify the validity of the proposed cooperative control scheme.

Bandwidth management for mobile mode of mobile monitoring system for Indonesian Volcano

NASA Astrophysics Data System (ADS)

Evita, Maria; Djamal, Mitra; Zimanowski, Bernd; Schilling, Klaus

2017-01-01

Volcano monitoring requires the system which has high-fidelity operation and real-time acquisition. MONICA (Mobile Monitoring System for Indonesian Volcano), a system based on Wireless Sensor Network, mobile robot and satellite technology has been proposed to fulfill this requirement for volcano monitoring system in Indonesia. This system consists of fixed-mode for normal condition and mobile mode for emergency situation. The first and second modes have been simulated in slow motion earthquake cases of Merapi Volcano, Indonesia. In this research, we have investigated the application of our bandwidth management for high-fidelity operation and real time acquisition in mobile mode of a strong motion earthquake from this volcano. The simulation result showed that our system still could manage the bandwidth even when there were 2 died fixed node after had stroked by the lightning. This result (64% to 83% throughput in average) was still better than the bandwidth utilized by the existing equipment (0% throughput because of the broken seismometer).

Behavior analysis for elderly care using a network of low-resolution visual sensors

NASA Astrophysics Data System (ADS)

Eldib, Mohamed; Deboeverie, Francis; Philips, Wilfried; Aghajan, Hamid

2016-07-01

Recent advancements in visual sensor technologies have made behavior analysis practical for in-home monitoring systems. The current in-home monitoring systems face several challenges: (1) visual sensor calibration is a difficult task and not practical in real-life because of the need for recalibration when the visual sensors are moved accidentally by a caregiver or the senior citizen, (2) privacy concerns, and (3) the high hardware installation cost. We propose to use a network of cheap low-resolution visual sensors (30×30 pixels) for long-term behavior analysis. The behavior analysis starts by visual feature selection based on foreground/background detection to track the motion level in each visual sensor. Then a hidden Markov model (HMM) is used to estimate the user's locations without calibration. Finally, an activity discovery approach is proposed using spatial and temporal contexts. We performed experiments on 10 months of real-life data. We show that the HMM approach outperforms the k-nearest neighbor classifier against ground truth for 30 days. Our framework is able to discover 13 activities of daily livings (ADL parameters). More specifically, we analyze mobility patterns and some of the key ADL parameters to detect increasing or decreasing health conditions.

Hand-Writing Motion Tracking with Vision-Inertial Sensor Fusion: Calibration and Error Correction

PubMed Central

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J.

2014-01-01

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model. PMID:25157546

Resolving Single Molecule Lysozyme Dynamics with a Carbon Nanotube Electronic Circuit

NASA Astrophysics Data System (ADS)

Choi, Yongki; Moody, Issa S.; Perez, Israel; Sheps, Tatyana; Weiss, Gregory A.; Collins, Philip G.

2011-03-01

High resolution, real-time monitoring of a single lysozyme molecule is demonstrated by fabricating nanoscale electronic devices based on single-walled carbon nanotubes (SWCNT). In this sensor platform, a biomolecule of interest is attached to a single SWCNT device. The electrical conductance transduces chemical events with single molecule sensitivity and 10 microsecond resolution. In this work, enzymatic turnover by lysozyme is investigated, because the mechanistic details for its processivity and dynamics remain incompletely understood. Stochastically distributed binding events between a lysozyme and its binding substrate, peptidoglycan, are monitored via the sensor conductance. Furthermore, the magnitude and repetition rate of these events varies with pH and the presence of inhibitors or denaturation agents. Changes in the conductance signal are analyzed in terms of lysozyme's internal hinge motion, binding events, and enzymatic processing.

A novel nano-sensor based on optomechanical crystal cavity

NASA Astrophysics Data System (ADS)

Zhang, Yeping; Ai, Jie; Ma, Jingfang

2017-10-01

Optical devices based on new sensing principle are widely used in biochemical and medical area. Nowadays, mass sensing based on monitoring the frequency shifts induced by added mass in oscillators is a well-known and widely used technique. It is interesting to note that for nanoscience and nanotechnology applications there is a strong demand for very sensitive mass sensors, being the target a sensor for single molecule detection. The desired mass resolution for very few or even single molecule detection, has to be below the femtogram range. Considering the strong interaction between high co-localized optical mode and mechanical mode in optomechanical crystal (OMC) cavities, we investigate OMC splitnanobeam cavities in silicon operating near at the 1550nm to achieve high optomechanical coupling rate and ultra-small motion mass. Theoretical investigations of the optical and mechanical characteristic for the proposed cavity are carried out. By adjusting the structural parameters, the cavity's effective motion mass below 10fg and mechanical frequency exceed 10GHz. The transmission spectrum of the cavity is sensitive to the sample which located on the center of the cavity. We conducted the fabrication and the characterization of this cavity sensor on the silicon-on-insulator (SOI) chip. By using vertical coupling between the tapered fiber and the SOI chip, we measured the transmission spectrum of the cavity, and verify this cavity is promising for ultimate precision mass sensing and detection.

Wearable Stretch Sensors for Motion Measurement of the Wrist Joint Based on Dielectric Elastomers.

PubMed

Huang, Bo; Li, Mingyu; Mei, Tao; McCoul, David; Qin, Shihao; Zhao, Zhanfeng; Zhao, Jianwen

2017-11-23

Motion capture of the human body potentially holds great significance for exoskeleton robots, human-computer interaction, sports analysis, rehabilitation research, and many other areas. Dielectric elastomer sensors (DESs) are excellent candidates for wearable human motion capture systems because of their intrinsic characteristics of softness, light weight, and compliance. In this paper, DESs were applied to measure all component motions of the wrist joints. Five sensors were mounted to different positions on the wrist, and each one is for one component motion. To find the best position to mount the sensors, the distribution of the muscles is analyzed. Even so, the component motions and the deformation of the sensors are coupled; therefore, a decoupling method was developed. By the decoupling algorithm, all component motions can be measured with a precision of 5°, which meets the requirements of general motion capture systems.

Highly Stretchable Multifunctional Wearable Devices Based on Conductive Cotton and Wool Fabrics.

PubMed

Souri, Hamid; Bhattacharyya, Debes

2018-06-05

The demand for stretchable, flexible, and wearable multifunctional devices based on conductive nanomaterials is rapidly increasing considering their interesting applications including human motion detection, robotics, and human-machine interface. There still exists a great challenge to manufacture stretchable, flexible, and wearable devices through a scalable and cost-effective fabrication method. Herein, we report a simple method for the mass production of electrically conductive textiles, made of cotton and wool, by hybridization of graphene nanoplatelets and carbon black particles. Conductive textiles incorporated into a highly elastic elastomer are utilized as highly stretchable and wearable strain sensors and heaters. The electromechanical characterizations of our multifunctional devices establish their excellent performance as wearable strain sensors to monitor various human motions, such as finger, wrist, and knee joint movements, and to recognize sound with high durability. Furthermore, the electrothermal behavior of our devices shows their potential application as stretchable and wearable heaters working at a maximum temperature of 103 °C powered with 20 V.

Applications of fiber optics sensors in weigh-in-motion (WIM) systems for monitoring truck weights on pavements and structures.

DOT National Transportation Integrated Search

2003-04-01

The main objective of this project was to investigate emerging technologies and to establish criteria for evaluating fiber optic sensors used to measure actual dynamic loads on pavements and structures. The dynamic load of particular interest for thi...

Mobile Monitoring Data Processing and Analysis Strategies

EPA Science Inventory

The development of portable, high-time resolution instruments for measuring the concentrations of a variety of air pollutants has made it possible to collect data while in motion. This strategy, known as mobile monitoring, involves mounting air sensors on variety of different pla...

Ubiquitous-health (U-Health) monitoring systems for elders and caregivers

NASA Astrophysics Data System (ADS)

Moon, Gyu; Lim, Kyung-won; Yoo, Young-min; An, Hye-min; Lee, Ki Seop; Szu, Harold

2011-06-01

This paper presents two aordable low-tack system for household biomedical wellness monitoring. The rst system, JIKIMI (pronounced caregiver in Korean), is a remote monitoring system that analyzes the behavior patterns of elders that live alone. JIKIMI is composed of an in-house sensing system, a set of wireless sensor nodes containing a pyroelectric infrared sensor to detect the motion of elders, an emergency button and a magnetic sensor that detects the opening and closing of doors. The system is also equipped with a server system, which is comprised of a database and web server. The server provides the mechanism for web-based monitoring to caregivers. The second system, Reader of Bottle Information (ROBI), is an assistant system which advises the contents of bottles for elders. ROBI is composed of bottles that have connected RFID tags and an advice system, which is composed of a wireless RFID reader, a gateway and a remote database server. The RFID tags are connected to the caps of the bottles are used in conjunction with the advice system These systems have been in use for three years and have proven to be useful for caregivers to provide more ecient and eective care services.

Sampling optimization for high-speed weigh-in-motion measurements using in-pavement strain-based sensors

NASA Astrophysics Data System (ADS)

Zhang, Zhiming; Huang, Ying; Bridgelall, Raj; Palek, Leonard; Strommen, Robert

2015-06-01

Weigh-in-motion (WIM) measurement has been widely used for weight enforcement, pavement design, freight management, and intelligent transportation systems to monitor traffic in real-time. However, to use such sensors effectively, vehicles must exit the traffic stream and slow down to match their current capabilities. Hence, agencies need devices with higher vehicle passing speed capabilities to enable continuous weight measurements at mainline speeds. The current practices for data acquisition at such high speeds are fragmented. Deployment configurations and settings depend mainly on the experiences of operation engineers. To assure adequate data, most practitioners use very high frequency measurements that result in redundant samples, thereby diminishing the potential for real-time processing. The larger data memory requirements from higher sample rates also increase storage and processing costs. The field lacks a sampling design or standard to guide appropriate data acquisition of high-speed WIM measurements. This study develops the appropriate sample rate requirements as a function of the vehicle speed. Simulations and field experiments validate the methods developed. The results will serve as guidelines for future high-speed WIM measurements using in-pavement strain-based sensors.

A Universal Noninvasive Continuous Blood Pressure Measurement System for Remote Healthcare Monitoring.

PubMed

Mukherjee, Ramtanu; Ghosh, Sanchita; Gupta, Bharat; Chakravarty, Tapas

2018-01-22

The effectiveness of any remote healthcare monitoring system depends on how much accurate, patient-friendly, versatile, and cost-effective measurement it is delivering. There has always been a huge demand for such a long-term noninvasive remote blood pressure (BP) measurement system, which could be used worldwide in the remote healthcare industry. Thus, noninvasive continuous BP measurement and remote monitoring have become an emerging area in the remote healthcare industry. Photoplethysmography-based (PPG) BP measurement is a continuous, unobtrusive, patient-friendly, and cost-effective solution. However, BP measurements through PPG sensors are not much reliable and accurate due to some major limitations like pressure disturbance, motion artifacts, and variations in human skin tone. A novel reflective PPG sensor has been developed to eliminate the abovementioned pressure disturbance and motion artifacts during the BP measurement. Considering the variations of the human skin tone across demography, a novel algorithm has been developed to make the BP measurement accurate and reliable. The training dataset captured 186 subjects' data and the trial dataset captured another new 102 subjects' data. The overall accuracy achieved by using the proposed method is nearly 98%. Thus, demonstrating the efficacy of the proposed method. The developed BP monitoring system is quite accurate, reliable, cost-effective, handy, and user friendly. It is also expected that this system would be quite useful to monitor the BP of infants, elderly people, patients having wounds, burn injury, or in the intensive care unit environment.

Development of a real-time monitoring system for intra-fractional motion in intracranial treatment using pressure sensors.

PubMed

Inata, Hiroki; Araki, Fujio; Kuribayashi, Yuta; Hamamoto, Yasushi; Nakayama, Shigeki; Sodeoka, Noritaka; Kiriyama, Tetsukazu; Nishizaki, Osamu

2015-09-21

This study developed a dedicated real-time monitoring system to detect intra-fractional head motion in intracranial radiotherapy using pressure sensors. The dedicated real-time monitoring system consists of pressure sensors with a thickness of 0.6 mm and a radius of 9.1 mm, a thermoplastic mask, a vacuum pillow, and a baseplate. The four sensors were positioned at superior-inferior and right-left sides under the occipital area. The sampling rate of pressure sensors was set to 5 Hz. First, we confirmed that the relationship between the force and the displacement of the vacuum pillow follows Hook's law. Next, the spring constant for the vacuum pillow was determined from the relationship between the force given to the vacuum pillow and the displacement of the head, detected by Cyberknife target locating system (TLS) acquisitions in clinical application. Finally, the accuracy of our system was evaluated by using the 2  ×  2 confusion matrix. The regression lines between the force, y, and the displacement, x, of the vacuum pillow were given by y = 3.8x, y = 4.4x, and y = 5.0x when the degree of inner pressure was  -12 kPa,-20 kPa, and  -27 kPa, respectively. The spring constant of the vacuum pillow was 1.6 N mm(-1) from the 6D positioning data of a total of 2999 TLS acquisitions in 19 patients. Head motions of 1 mm, 1.5 mm, and 2 mm were detected in real-time with the accuracies of 67%, 84%, and 89%, respectively. Our system can detect displacement of the head continuously during every interval of TLS with a resolution of 1-2 mm without any radiation exposure.

Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Roberts, Barry; Bhanu, Bir

1992-01-01

Recent work on INS integrated motion analysis is described. Results were obtained with a maximally passive system of obstacle detection (OD) for ground-based vehicles and rotorcraft. The OD approach involves motion analysis of imagery acquired by a passive sensor in the course of vehicle travel to generate range measurements to world points within the sensor FOV. INS data and scene analysis results are used to enhance interest point selection, the matching of the interest points, and the subsequent motion-based computations, tracking, and OD. The most important lesson learned from the research described here is that the incorporation of inertial data into the motion analysis program greatly improves the analysis and makes the process more robust.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation.

PubMed

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-based sensor, the system is expected to be highly robust to sea weather conditions.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation

NASA Astrophysics Data System (ADS)

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-based sensor, the system is expected to be highly robust to sea weather conditions.

Motion camera based on a custom vision sensor and an FPGA architecture

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel

1998-09-01

A digital camera for custom focal plane arrays was developed. The camera allows the test and development of analog or mixed-mode arrays for focal plane processing. The camera is used with a custom sensor for motion detection to implement a motion computation system. The custom focal plane sensor detects moving edges at the pixel level using analog VLSI techniques. The sensor communicates motion events using the event-address protocol associated to a temporal reference. In a second stage, a coprocessing architecture based on a field programmable gate array (FPGA) computes the time-of-travel between adjacent pixels. The FPGA allows rapid prototyping and flexible architecture development. Furthermore, the FPGA interfaces the sensor to a compact PC computer which is used for high level control and data communication to the local network. The camera could be used in applications such as self-guided vehicles, mobile robotics and smart surveillance systems. The programmability of the FPGA allows the exploration of further signal processing like spatial edge detection or image segmentation tasks. The article details the motion algorithm, the sensor architecture, the use of the event- address protocol for velocity vector computation and the FPGA architecture used in the motion camera system.

Non-contact respiration monitoring for in-vivo murine micro computed tomography: characterization and imaging applications

NASA Astrophysics Data System (ADS)

Burk, Laurel M.; Lee, Yueh Z.; Wait, J. Matthew; Lu, Jianping; Zhou, Otto Z.

2012-09-01

A cone beam micro-CT has previously been utilized along with a pressure-tracking respiration sensor to acquire prospectively gated images of both wild-type mice and various adult murine disease models. While the pressure applied to the abdomen of the subject by this sensor is small and is generally without physiological effect, certain disease models of interest, as well as very young animals, are prone to atelectasis with added pressure, or they generate too weak a respiration signal with this method to achieve optimal prospective gating. In this work we present a new fibre-optic displacement sensor which monitors respiratory motion of a subject without requiring physical contact. The sensor outputs an analogue signal which can be used for prospective respiration gating in micro-CT imaging. The device was characterized and compared against a pneumatic air chamber pressure sensor for the imaging of adult wild-type mice. The resulting images were found to be of similar quality with respect to physiological motion blur; the quality of the respiration signal trace obtained using the non-contact sensor was comparable to that of the pressure sensor and was superior for gating purposes due to its better signal-to-noise ratio. The non-contact sensor was then used to acquire in-vivo micro-CT images of a murine model for congenital diaphragmatic hernia and of 11-day-old mouse pups. In both cases, quality CT images were successfully acquired using this new respiration sensor. Despite the presence of beam hardening artefacts arising from the presence of a fibre-optic cable in the imaging field, we believe this new technique for respiration monitoring and gating presents an opportunity for in-vivo imaging of disease models which were previously considered too delicate for established animal handling methods.

The Rendezvous Monitoring Display Capabilities of the Rendezvous and Proximity Operations Program

NASA Technical Reports Server (NTRS)

Brazzel, Jack; Spehar, Pete; Clark, Fred; Foster, Chris; Eldridge, Erin

2013-01-01

The Rendezvous and Proximity Operations Program (RPOP) is a laptop computer- based relative navigation tool and piloting aid that was developed during the Space Shuttle program. RPOP displays a graphical representation of the relative motion between the target and chaser vehicles in a rendezvous, proximity operations and capture scenario. After being used in over 60 Shuttle rendezvous missions, some of the RPOP display concepts have become recognized as a minimum standard for cockpit displays for monitoring the rendezvous task. To support International Space Station (ISS) based crews in monitoring incoming visiting vehicles, RPOP has been modified to allow crews to compare the Cygnus visiting vehicle s onboard navigated state to processed range measurements from an ISS-based, crew-operated Hand Held Lidar sensor. This paper will discuss the display concepts of RPOP that have proven useful in performing and monitoring rendezvous and proximity operations.

A smart composite patch for the repair of aircraft structures

NASA Astrophysics Data System (ADS)

Wakha, Kelah; Samuel, Paul; Pines, Darryll J.

2005-05-01

Recent interest in bonded composite patch repair technology for aerospace systems is because this method can be carried out at a reduced cost and time and can easily be applied to complex geometric structures. This paper details the development of a dual stiffness/energy sensor for monitoring the integrity of a composite patch used to repair an aluminum structural component. The smart sensor has the ability to predict the elastic field of a given host structure based on the strain state of two sub-sensors integrated into the structure. The present study shows the possibility of using the sensor to deduce the local instantaneous host stiffness. Damaged structures are characterized by a reduction in their elastic stiffness that evolve from microstructural defects. A local smart sensor can be developed to sense the local average properties on a host. In this paper, sensors are attached to a structure and a modified Eshelby's equivalent inclusion method is used to derive the elastic properties of the host. An analytical derivation and a sensitivity analysis for the quasistatic application is given in a papers by Majed, Dasgupta, Kelah and Pines. A summary of the derivation of the dynamic Eshelby tensor is presented. This is of importance because damage detection in structures undergoing vibratory and other motions present a greater challenge than those in quasistatic motion. An in-situ health monitoring active sensor system for a real structure (an aluminum plate with an attached repair patch) under close-to real lifecycle loading conditions is developed. The detection of the onset of any damage to the structure as well as the repair patch and the subsequent monitoring of the growth of this damage constitute important goals of the system. Both experimental and finite element methods were applied. Experimental results are presented for tests of the aluminum plate with the repair patch under monotonic quasi-static and dynamic loading vibratory conditions. In summary, the study shows that smart bonded composite repair patches are very effective in the repair of thin aluminum structures since they are able to determine the integrity of the repair structure as well as the repair patch.

Optical coherence tomography as a novel tool for in-line monitoring of a pharmaceutical film-coating process.

PubMed

Markl, Daniel; Hannesschläger, Günther; Sacher, Stephan; Leitner, Michael; Khinast, Johannes G

2014-05-13

Optical coherence tomography (OCT) is a contact-free non-destructive high-resolution imaging technique based on low-coherence interferometry. This study investigates the application of spectral-domain OCT as an in-line quality control tool for monitoring pharmaceutical film-coated tablets. OCT images of several commercially-available film-coated tablets of different shapes, formulations and coating thicknesses were captured off-line using two OCT systems with centre wavelengths of 830nm and 1325nm. Based on the off-line image evaluation, another OCT system operating at a shorter wavelength was selected to study the feasibility of OCT as an in-line monitoring method. Since in spectral-domain OCT motion artefacts can occur as a result of the tablet or sensor head movement, a basic understanding of the relationship between the tablet speed and the motion effects is essential for correct quantifying and qualifying of the tablet coating. Experimental data was acquired by moving the sensor head of the OCT system across a static tablet bed. Although examining the homogeneity of the coating turned more difficult with increasing transverse speed of the tablets, the determination of the coating thickness was still highly accurate at a speed up to 0.7m/s. The presented OCT setup enables the investigation of the intra- and inter-tablet coating uniformity in-line during the coating process. Copyright © 2014 Elsevier B.V. All rights reserved.

Methods for Expanding Rotary Wing Aircraft Health and Usage Monitoring Systems to the Rotating Frame through Real-time Rotor Blade Kinematics Estimation

NASA Astrophysics Data System (ADS)

Allred, Charles Jefferson

Since the advent of Health and Usage Monitoring Systems (HUMS) in the early 1990's, there has been a steady decrease in the number of component failure related helicopter accidents. Additionally, measurable cost benefits due to improved maintenance practices based on HUMS data has led to a desire to expand HUMS from its traditional area of helicopter drive train monitoring. One of the areas of greatest interest for this expansion of HUMS is monitoring of the helicopter rotor head loads. Studies of rotor head load and blade motions have primarily focused on wind tunnel testing with technology which would not be applicable for production helicopter HUMS deployment, or measuring bending along the blade, rather than where it is attached to the rotor head and the location through which all the helicopter loads pass. This dissertation details research into finding methods for real time methods of estimating rotor blade motion which could be applied across helicopter fleets as an expansion of current HUMS technology. First, there is a brief exploration of supporting technologies which will be crucial in enabling the expansion of HUMS from the fuselage of helicopters to the rotor head: wireless data transmission and energy harvesting. A brief overview of the commercially available low power wireless technology selected for this research is presented. The development of a relatively high-powered energy harvester specific to the motion of helicopter rotor blades is presented and two different prototypes of the device are shown. Following the overview of supporting technologies, two novel methods of monitoring rotor blade motion in real time are developed. The first method employs linear displacement sensors embedded in the elastomer layers of a high-capacity laminate bearing of the type commonly used in fully articulated rotors throughout the helicopter industry. The configuration of these displacement sensors allows modeling of the sensing system as a robotic parallel mechanism, similar to a Stewart Platform. A calibration method for this device is developed and the improved orientation estimation results are shown. The second method is not specific to the fully articulated rotor head mounting geometry of the first method. Rather, it utilizes micro-electromechanical (MEMS) accelerometers and gyroscopes configured to measure the centrifugal acceleration and rotation rate induced through rotor head rotation differentially. By measuring these quantities differentially, other accelerations from the fuselage reference frame are removed from the measurement, resulting in acceleration and rate quantities that are impacted only by the angle of the sensors relative to the plane of rotation. By mounting these sensors strategically and symmetrically about the rotor blade root center of rotation, the orientation of the rotor blade can be estimated in real time.

Infrared Thermography Sensor for Temperature and Speed Measurement of Moving Material.

PubMed

Usamentiaga, Rubén; García, Daniel Fernando

2017-05-18

Infrared thermography offers significant advantages in monitoring the temperature of objects over time, but crucial aspects need to be addressed. Movements between the infrared camera and the inspected material seriously affect the accuracy of the calculated temperature. These movements can be the consequence of solid objects that are moved, molten metal poured, material on a conveyor belt, or just vibrations. This work proposes a solution for monitoring the temperature of material in these scenarios. In this work both real movements and vibrations are treated equally, proposing a unified solution for both problems. The three key steps of the proposed procedure are image rectification, motion estimation and motion compensation. Image rectification calculates a front-parallel projection of the image that simplifies the estimation and compensation of the movement. Motion estimation describes the movement using a mathematical model, and estimates the coefficients using robust methods adapted to infrared images. Motion is finally compensated for in order to produce the correct temperature time history of the monitored material regardless of the movement. The result is a robust sensor for temperature of moving material that can also be used to measure the speed of the material. Different experiments are carried out to validate the proposed method in laboratory and real environments. Results show excellent performance.

Infrared Thermography Sensor for Temperature and Speed Measurement of Moving Material

PubMed Central

Usamentiaga, Rubén; García, Daniel Fernando

2017-01-01

Infrared thermography offers significant advantages in monitoring the temperature of objects over time, but crucial aspects need to be addressed. Movements between the infrared camera and the inspected material seriously affect the accuracy of the calculated temperature. These movements can be the consequence of solid objects that are moved, molten metal poured, material on a conveyor belt, or just vibrations. This work proposes a solution for monitoring the temperature of material in these scenarios. In this work both real movements and vibrations are treated equally, proposing a unified solution for both problems. The three key steps of the proposed procedure are image rectification, motion estimation and motion compensation. Image rectification calculates a front-parallel projection of the image that simplifies the estimation and compensation of the movement. Motion estimation describes the movement using a mathematical model, and estimates the coefficients using robust methods adapted to infrared images. Motion is finally compensated for in order to produce the correct temperature time history of the monitored material regardless of the movement. The result is a robust sensor for temperature of moving material that can also be used to measure the speed of the material. Different experiments are carried out to validate the proposed method in laboratory and real environments. Results show excellent performance. PMID:28524110

The Effects of Applying Game-Based Learning to Webcam Motion Sensor Games for Autistic Students' Sensory Integration Training

ERIC Educational Resources Information Center

Li, Kun-Hsien; Lou, Shi-Jer; Tsai, Huei-Yin; Shih, Ru-Chu

2012-01-01

This study aims to explore the effects of applying game-based learning to webcam motion sensor games for autistic students' sensory integration training for autistic students. The research participants were three autistic students aged from six to ten. Webcam camera as the research tool wad connected internet games to engage in motion sensor…

Understanding Smart Home Sensor Data for Ageing in Place Through Everyday Household Routines: A Mixed Method Case Study.

PubMed

van Kasteren, Yasmin; Bradford, Dana; Zhang, Qing; Karunanithi, Mohan; Ding, Hang

2017-06-13

An ongoing challenge for smart homes research for aging-in-place is how to make sense of the large amounts of data from in-home sensors to facilitate real-time monitoring and develop reliable alerts. The objective of our study was to explore the usefulness of a routine-based approach for making sense of smart home data for the elderly. Maximum variation sampling was used to select three cases for an in-depth mixed methods exploration of the daily routines of three elderly participants in a smart home trial using 180 days of power use and motion sensor data and longitudinal interview data. Sensor data accurately matched self-reported routines. By comparing daily movement data with personal routines, it was possible to identify changes in routine that signaled illness, recovery from bereavement, and gradual deterioration of sleep quality and daily movement. Interview and sensor data also identified changes in routine with variations in temperature and daylight hours. The findings demonstrated that a routine-based approach makes interpreting sensor data easy, intuitive, and transparent. They highlighted the importance of understanding and accounting for individual differences in preferences for routinization and the influence of the cyclical nature of daily routines, social or cultural rhythms, and seasonal changes in temperature and daylight hours when interpreting information based on sensor data. This research has demonstrated the usefulness of a routine-based approach for making sense of smart home data, which has furthered the understanding of the challenges that need to be addressed in order to make real-time monitoring and effective alerts a reality. ©Yasmin van Kasteren, Dana Bradford, Qing Zhang, Mohan Karunanithi, Hang Ding. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 13.06.2017.

Understanding Smart Home Sensor Data for Ageing in Place Through Everyday Household Routines: A Mixed Method Case Study

PubMed Central

van Kasteren, Yasmin; Bradford, Dana; Karunanithi, Mohan; Ding, Hang

2017-01-01

Background An ongoing challenge for smart homes research for aging-in-place is how to make sense of the large amounts of data from in-home sensors to facilitate real-time monitoring and develop reliable alerts. Objective The objective of our study was to explore the usefulness of a routine-based approach for making sense of smart home data for the elderly. Methods Maximum variation sampling was used to select three cases for an in-depth mixed methods exploration of the daily routines of three elderly participants in a smart home trial using 180 days of power use and motion sensor data and longitudinal interview data. Results Sensor data accurately matched self-reported routines. By comparing daily movement data with personal routines, it was possible to identify changes in routine that signaled illness, recovery from bereavement, and gradual deterioration of sleep quality and daily movement. Interview and sensor data also identified changes in routine with variations in temperature and daylight hours. Conclusions The findings demonstrated that a routine-based approach makes interpreting sensor data easy, intuitive, and transparent. They highlighted the importance of understanding and accounting for individual differences in preferences for routinization and the influence of the cyclical nature of daily routines, social or cultural rhythms, and seasonal changes in temperature and daylight hours when interpreting information based on sensor data. This research has demonstrated the usefulness of a routine-based approach for making sense of smart home data, which has furthered the understanding of the challenges that need to be addressed in order to make real-time monitoring and effective alerts a reality. PMID:28611014

Statistical data mining of streaming motion data for fall detection in assistive environments.

PubMed

Tasoulis, S K; Doukas, C N; Maglogiannis, I; Plagianakos, V P

2011-01-01

The analysis of human motion data is interesting for the purpose of activity recognition or emergency event detection, especially in the case of elderly or disabled people living independently in their homes. Several techniques have been proposed for identifying such distress situations using either motion, audio or video sensors on the monitored subject (wearable sensors) or the surrounding environment. The output of such sensors is data streams that require real time recognition, especially in emergency situations, thus traditional classification approaches may not be applicable for immediate alarm triggering or fall prevention. This paper presents a statistical mining methodology that may be used for the specific problem of real time fall detection. Visual data captured from the user's environment, using overhead cameras along with motion data are collected from accelerometers on the subject's body and are fed to the fall detection system. The paper includes the details of the stream data mining methodology incorporated in the system along with an initial evaluation of the achieved accuracy in detecting falls.

Oscillatory motion based measurement method and sensor for measuring wall shear stress due to fluid flow

DOEpatents

Armstrong, William D [Laramie, WY; Naughton, Jonathan [Laramie, WY; Lindberg, William R [Laramie, WY

2008-09-02

A shear stress sensor for measuring fluid wall shear stress on a test surface is provided. The wall shear stress sensor is comprised of an active sensing surface and a sensor body. An elastic mechanism mounted between the active sensing surface and the sensor body allows movement between the active sensing surface and the sensor body. A driving mechanism forces the shear stress sensor to oscillate. A measuring mechanism measures displacement of the active sensing surface relative to the sensor body. The sensor may be operated under periodic excitation where changes in the nature of the fluid properties or the fluid flow over the sensor measurably changes the amplitude or phase of the motion of the active sensing surface, or changes the force and power required from a control system in order to maintain constant motion. The device may be operated under non-periodic excitation where changes in the nature of the fluid properties or the fluid flow over the sensor change the transient motion of the active sensor surface or change the force and power required from a control system to maintain a specified transient motion of the active sensor surface.

A Shoe-Embedded Piezoelectric Energy Harvester for Wearable Sensors

PubMed Central

Zhao, Jingjing; You, Zheng

2014-01-01

Harvesting mechanical energy from human motion is an attractive approach for obtaining clean and sustainable electric energy to power wearable sensors, which are widely used for health monitoring, activity recognition, gait analysis and so on. This paper studies a piezoelectric energy harvester for the parasitic mechanical energy in shoes originated from human motion. The harvester is based on a specially designed sandwich structure with a thin thickness, which makes it readily compatible with a shoe. Besides, consideration is given to both high performance and excellent durability. The harvester provides an average output power of 1 mW during a walk at a frequency of roughly 1 Hz. Furthermore, a direct current (DC) power supply is built through integrating the harvester with a power management circuit. The DC power supply is tested by driving a simulated wireless transmitter, which can be activated once every 2–3 steps with an active period lasting 5 ms and a mean power of 50 mW. This work demonstrates the feasibility of applying piezoelectric energy harvesters to power wearable sensors. PMID:25019634

Drift-Free Position Estimation of Periodic or Quasi-Periodic Motion Using Inertial Sensors

PubMed Central

Latt, Win Tun; Veluvolu, Kalyana Chakravarthy; Ang, Wei Tech

2011-01-01

Position sensing with inertial sensors such as accelerometers and gyroscopes usually requires other aided sensors or prior knowledge of motion characteristics to remove position drift resulting from integration of acceleration or velocity so as to obtain accurate position estimation. A method based on analytical integration has previously been developed to obtain accurate position estimate of periodic or quasi-periodic motion from inertial sensors using prior knowledge of the motion but without using aided sensors. In this paper, a new method is proposed which employs linear filtering stage coupled with adaptive filtering stage to remove drift and attenuation. The prior knowledge of the motion the proposed method requires is only approximate band of frequencies of the motion. Existing adaptive filtering methods based on Fourier series such as weighted-frequency Fourier linear combiner (WFLC), and band-limited multiple Fourier linear combiner (BMFLC) are modified to combine with the proposed method. To validate and compare the performance of the proposed method with the method based on analytical integration, simulation study is performed using periodic signals as well as real physiological tremor data, and real-time experiments are conducted using an ADXL-203 accelerometer. Results demonstrate that the performance of the proposed method outperforms the existing analytical integration method. PMID:22163935

Multi-Sensor Methods for Mobile Radar Motion Capture and Compensation

NASA Astrophysics Data System (ADS)

Nakata, Robert

Remote sensing has many applications, including surveying and mapping, geophysics exploration, military surveillance, search and rescue and counter-terrorism operations. Remote sensor systems typically use visible image, infrared or radar sensors. Camera based image sensors can provide high spatial resolution but are limited to line-of-sight capture during daylight. Infrared sensors have lower resolution but can operate during darkness. Radar sensors can provide high resolution motion measurements, even when obscured by weather, clouds and smoke and can penetrate walls and collapsed structures constructed with non-metallic materials up to 1 m to 2 m in depth depending on the wavelength and transmitter power level. However, any platform motion will degrade the target signal of interest. In this dissertation, we investigate alternative methodologies to capture platform motion, including a Body Area Network (BAN) that doesn't require external fixed location sensors, allowing full mobility of the user. We also investigated platform stabilization and motion compensation techniques to reduce and remove the signal distortion introduced by the platform motion. We evaluated secondary ultrasonic and radar sensors to stabilize the platform resulting in an average 5 dB of Signal to Interference Ratio (SIR) improvement. We also implemented a Digital Signal Processing (DSP) motion compensation algorithm that improved the SIR by 18 dB on average. These techniques could be deployed on a quadcopter platform and enable the detection of respiratory motion using an onboard radar sensor.

A triboelectric motion sensor in wearable body sensor network for human activity recognition.

PubMed

Hui Huang; Xian Li; Ye Sun

2016-08-01

The goal of this study is to design a novel triboelectric motion sensor in wearable body sensor network for human activity recognition. Physical activity recognition is widely used in well-being management, medical diagnosis and rehabilitation. Other than traditional accelerometers, we design a novel wearable sensor system based on triboelectrification. The triboelectric motion sensor can be easily attached to human body and collect motion signals caused by physical activities. The experiments are conducted to collect five common activity data: sitting and standing, walking, climbing upstairs, downstairs, and running. The k-Nearest Neighbor (kNN) clustering algorithm is adopted to recognize these activities and validate the feasibility of this new approach. The results show that our system can perform physical activity recognition with a successful rate over 80% for walking, sitting and standing. The triboelectric structure can also be used as an energy harvester for motion harvesting due to its high output voltage in random low-frequency motion.

Miniature Biosensor with Health Risk Assessment Feedback

NASA Technical Reports Server (NTRS)

Hanson, Andrea; Downs, Meghan; Kalogera, Kent; Buxton, Roxanne; Cooper, Tommy; Cooper, Alan; Cooper, Ross

2016-01-01

Heart rate (HR) monitoring is a medical requirement during exercise on the International Space Station (ISS), fitness tests, and extravehicular activity (EVA); however, NASA does not currently have the technology to consistently and accurately monitor HR and other physiological data during these activities. Performance of currently available HR monitor technologies is dependent on uninterrupted contact with the torso and are prone to data drop-out and motion artifact. Here, we seek an alternative to the chest strap and electrode based sensors currently in use on ISS today. This project aims to develop a high performance, robust earbud based biosensor with focused efforts on improved HR data quality during exercise or EVA. A health risk assessment algorithm will further advance the goals of autonomous crew health care for exploration missions.

Kestrel: force protection and Intelligence, Surveillance, and Reconnaissance (ISR) persistent surveillance on aerostats

NASA Astrophysics Data System (ADS)

Luber, David R.; Marion, John E.; Fields, David

2012-05-01

Logos Technologies has developed and fielded the Kestrel system, an aerostat-based, wide area persistent surveillance system dedicated to force protection and ISR mission execution operating over forward operating bases. Its development included novel imaging and stabilization capability for day/night operations on military aerostat systems. The Kestrel system's contribution is a substantial enhancement to aerostat-based, force protection systems which to date have relied on narrow field of view ball gimbal sensors to identify targets of interest. This inefficient mechanism to conduct wide area field of view surveillance is greatly enhanced by Kestrel's ability to maintain a constant motion imagery stare of the entire forward operating base (FOB) area. The Kestrel airborne sensor enables 360° coverage out to extended ranges which covers a city sized area at moderate resolution, while cueing a narrow field of view sensor to provide high resolution imagery of targets of interest. The ground station exploitation system enables operators to autonomously monitor multiple regions of interest in real time, and allows for backtracking through the recorded imagery, while continuing to monitor ongoing activity. Backtracking capability allows operators to detect threat networks, their CONOPS, and locations of interest. Kestrel's unique advancement has already been utilized successfully in OEF operations.

Data Collection and Analysis Using Wearable Sensors for Monitoring Knee Range of Motion after Total Knee Arthroplasty

PubMed Central

Chiang, Chih-Yen; Chen, Kun-Hui; Liu, Kai-Chun; Hsu, Steen Jun-Ping; Chan, Chia-Tai

2017-01-01

Total knee arthroplasty (TKA) is the most common treatment for degenerative osteoarthritis of that articulation. However, either in rehabilitation clinics or in hospital wards, the knee range of motion (ROM) can currently only be assessed using a goniometer. In order to provide continuous and objective measurements of knee ROM, we propose the use of wearable inertial sensors to record the knee ROM during the recovery progress. Digitalized and objective data can assist the surgeons to control the recovery status and flexibly adjust rehabilitation programs during the early acute inpatient stage. The more knee flexion ROM regained during the early inpatient period, the better the long-term knee recovery will be and the sooner early discharge can be achieved. The results of this work show that the proposed wearable sensor approach can provide an alternative for continuous monitoring and objective assessment of knee ROM recovery progress for TKA patients compared to the traditional goniometer measurements. PMID:28241434

Development of esMOCA Biomechanic, Motion Capture Instrumentation for Biomechanics Analysis

NASA Astrophysics Data System (ADS)

Arendra, A.; Akhmad, S.

2018-01-01

This study aims to build motion capture instruments using inertial measurement unit sensors to assist in the analysis of biomechanics. Sensors used are accelerometer and gyroscope. Estimation of orientation sensors is done by digital motion processing in each sensor nodes. There are nine sensor nodes attached to the upper limbs. This sensor is connected to the pc via a wireless sensor network. The development of kinematics and inverse dynamamic models of the upper limb is done in simulink simmechanic. The kinematic model receives streaming data of sensor nodes mounted on the limbs. The output of the kinematic model is the pose of each limbs and visualized on display. The dynamic inverse model outputs the reaction force and reaction moment of each joint based on the limb motion input. Model validation in simulink with mathematical model of mechanical analysis showed results that did not differ significantly

Acoustic sensor array extracts physiology during movement

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.

2001-08-01

An acoustic sensor attached to a person's neck can extract heart and breath sounds, as well as voice and other physiology related to their health and performance. Soldiers, firefighters, law enforcement, and rescue personnel, as well as people at home or in health care facilities, can benefit form being remotely monitored. ARLs acoustic sensor, when worn around a person's neck, picks up the carotid artery and breath sounds very well by matching the sensor's acoustic impedance to that of the body via a gel pad, while airborne noise is minimized by an impedance mismatch. Although the physiological sounds have high SNR, the acoustic sensor also responds to motion-induced artifacts that obscure the meaningful physiology. To exacerbate signal extraction, these interfering signals are usually covariant with the heart sounds, in that as a person walks faster the heart tends to beat faster, and motion noises tend to contain low frequency component similar to the heart sounds. A noise-canceling configuration developed by ARL uses two acoustic sensor on the front sides of the neck as physiology sensors, and two additional acoustic sensor on the back sides of the neck as noise references. Breath and heart sounds, which occur with near symmetry and simultaneously at the two front sensor, will correlate well. The motion noise present on all four sensor will be used to cancel the noise on the two physiology sensors. This report will compare heart rate variability derived from both the acoustic array and from ECG data taken simultaneously on a treadmill test. Acoustically derived breath rate and volume approximations will be introduced as well. A miniature 3- axis accelerometer on the same neckband provides additional noise references to validate footfall and motion activity.

Waterway wide area tactical coverage and homing (WaterWATCH) program overview

NASA Astrophysics Data System (ADS)

Driggers, Gerald; Cleveland, Tammy; Araujo, Lisa; Spohr, Robert; Umansky, Mark

2008-04-01

The Congressional and Army sponsored WaterWATCH TM Program has developed and demonstrated a fully integrated shallow water port and facility monitoring system. It provides fully automated monitoring of domains above and below the surface of the water using primarily off-the-shelf sensors and software. The system is modular, open architecture and IP based, and elements can be mixed and matched to adapt to specific applications. The sensors integrated into the WaterWATCH TM system include cameras, radar, passive and active sonar, and various motion detectors. The sensors were chosen based on extensive requirements analyses and tradeoffs. Descriptions of the system and individual sensors are provided, along with data from modular and system level testing. Camera test results address capabilities and limitations associated with using "smart" image analysis software with stressing environmental issues such as bugs, darkness, rain and snow. Radar issues addressed include achieving range and resolution requirements. The passive sonar capability to provide near 100% true positives with zero false positives is demonstrated. Testing results are also presented to show that inexpensive active sonar can be effective against divers with or without SCUBA gear and that false alarms due to fish can be minimized. A simple operator interface has also been demonstrated.

Self-evaluation on Motion Adaptation for Service Robots

NASA Astrophysics Data System (ADS)

Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru

We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, T; Cho, M; Kang, S

Purpose: To improve the setup accuracy of thermoplastic mask, we developed a new monitoring method based on force sensing technology and evaluated its feasibility. Methods: The thermoplastic mask setup monitoring system consists of a force sensing resistor sensor unit, a signal transport device, a control PC and an in-house software. The system is designed to monitor pressure variation between the mask and patient in real time. It also provides a warning to the user when there is a possibility of movement. A preliminary study was performed to evaluate the reliability of the sensor unit and developed monitoring system with amore » head phantom. Then, a simulation study with volunteers was conducted to evaluate the feasibility of the monitoring system. Note that the sensor unit can have multiple end-sensors and every end-sensor was confirmed to be within 2% reliability in pressure reading through a screening test. Results: To evaluate the reproducibility of the proposed monitoring system in practice, we simulated a mask setup with the head phantom. FRS sensors were attached on the face of the head phantom and pressure was monitored. For 3 repeated mask setups on the phantom, the variation of the pressure was less than 3% (only 1% larger than 2% potential uncertainty confirmed in the screening test). In the volunteer study, we intended to verify that the system could detect patient movements within the mask. Thus, volunteers were asked to turn their head or lift their chin. The system was able to detect movements effectively, confirming the clinical feasibility of the monitoring system developed. Conclusion: Through the proposed setup monitoring method, it is possible to monitor patient motion inside a mask in real time, which has never been possible with most commonly used systems using non-radiographic technology such as infrared camera system and surface imaging system. This work was supported by the Radiation Technology R&D program (No. 2013M2A2A7043498) and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.« less

Development of a robust and cost-effective 3D respiratory motion monitoring system using the kinect device: Accuracy comparison with the conventional stereovision navigation system.

PubMed

Bae, Myungsoo; Lee, Sangmin; Kim, Namkug

2018-07-01

To develop and validate a robust and cost-effective 3D respiratory monitoring system based on a Kinect device with a custom-made simple marker. A 3D respiratory monitoring system comprising the simple marker and the Microsoft Kinect v2 device was developed. The marker was designed for simple and robust detection, and the tracking algorithm was developed using the depth, RGB, and infra-red images acquired from the Kinect sensor. A Kalman filter was used to suppress movement noises. The major movements of the marker attached to the four different locations of body surface were determined from the initially collected tracking points of the marker while breathing. The signal level of respiratory motion with the tracking point was estimated along the major direction vector. The accuracy of the results was evaluated through a comparison with those of the conventional stereovision navigation system (NDI Polaris Spectra). Sixteen normal volunteers were enrolled to evaluate the accuracy of this system. The correlation coefficients between the respiratory motion signal from the Kinect device and conventional navigation system ranged from 0.970 to 0.999 and from 0.837 to 0.995 at the abdominal and thoracic surfaces, respectively. The respiratory motion signal from this system was obtained at 27-30 frames/s. This system with the Kinect v2 device and simple marker could be used for cost-effective, robust and accurate 3D respiratory motion monitoring. In addition, this system is as reliable for respiratory motion signal generation and as practically useful as the conventional stereovision navigation system and is less sensitive to patient posture. Copyright © 2018 Elsevier B.V. All rights reserved.

Shape-based human detection for threat assessment

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Zhan, Pengcheng; Thomas, Aaron; Schoenberger, Robert B.

2004-07-01

Detection of intrusions for early threat assessment requires the capability of distinguishing whether the intrusion is a human, an animal, or other objects. Most low-cost security systems use simple electronic motion detection sensors to monitor motion or the location of objects within the perimeter. Although cost effective, these systems suffer from high rates of false alarm, especially when monitoring open environments. Any moving objects including animals can falsely trigger the security system. Other security systems that utilize video equipment require human interpretation of the scene in order to make real-time threat assessment. Shape-based human detection technique has been developed for accurate early threat assessments for open and remote environment. Potential threats are isolated from the static background scene using differential motion analysis and contours of the intruding objects are extracted for shape analysis. Contour points are simplified by removing redundant points connecting short and straight line segments and preserving only those with shape significance. Contours are represented in tangent space for comparison with shapes stored in database. Power cepstrum technique has been developed to search for the best matched contour in database and to distinguish a human from other objects from different viewing angles and distances.

SU-F-T-525: Monitordeep-Inspiratory Breathhold with a Laser Sensor for Radiation Therapy of Left Breast Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tai, A; Currey, A; Li, X Allen

2016-06-15

Purpose: Radiation therapy (RT) of left sided breast cancers with deep-inspiratory breathhold (DIBH) can reduce the dose to heart. The purpose of this study is to develop and test a new laser-based tool to improve ease of RT delivery using DIBH. Methods: A laser sensor together with breathing monitor device (Anzai Inc., Japan) was used to record the surface breathing motion of phantom/volunteers. The device projects a laser beam to the chestwall and the reflected light creates a focal spot on a light detecting element. The position change of the focal spot correlates with the patient’s breathing motion and ismore » measured through the change of current in the light detecting element. The signal is amplified and displayed on a computer screen, which is used to trigger radiation gating. The laser sensor can be easily mounted to the simulation/treatment couch with a fixing plate and a magnet base, and has a sensitivity range of 10 to 40 cm from the patient. The correlation of breathing signals detected by laser sensor and visionRT is also investigated. Results: It is found that the measured breathing signal from the laser sensor is stable and reproducible and has no noticeable delay. It correlates well with the VisionRT surface imaging system. The DIBH reference level does not change with movement of the couch because the laser sensor and couch move together. Conclusion: The Anzai laser sensor provides a cost-effective way to improve beam gating with DIBH for treating left breast cancer. It can be used alone or together with VisionRT to determine the correct DIBH level during the radiation treatment of left breast cancer with DIBH.« less

Real-time detection, classification, and quantification of apneic episodes using miniature surface motion sensors in rats.

PubMed

Waisman, Dan; Lev-Tov, Lior; Levy, Carmit; Faingersh, Anna; Colman Klotzman, Ifat; Bibi, Haim; Rotschild, Avi; Landesberg, Amir

2015-07-01

Real-time detection and classification of apneic episodes remain significant challenges. This study explores the applicability of a novel method of monitoring the respiratory effort and dynamics for rapid detection and classification of apneic episodes. Obstructive apnea (OA) and hypopnea/central apnea (CA) were induced in nine tracheostomized rats, by short-lived airway obstruction and administration of succinylcholine, respectively. Esophageal pressure (EP), EtCO2, arterial O2 saturation (SpO2), heart rate, and blood pressure were monitored. Respiratory dynamics were monitored utilizing three miniature motion sensors placed on the chest and epigastrium. Three indices were derived from these sensors: amplitude of the tidal chest wall displacement (TDi), breath time length (BTL), that included inspiration and rapid expiration phases, and amplitude time integral (ATI), the integral of breath amplitude over time. OA induced a progressive 6.42 ± 3.48-fold increase in EP from baseline, which paralleled a 3.04 ± 1.19-fold increase in TDi (P < 0.0012), a 1.39 ± 0.22-fold increase in BTL (P < 0.0002), and a 3.32 ± 1.40-fold rise in the ATI (P < 0.024). During central hypopneic/apneic episodes, each sensor revealed a gradual decrease in TDi, which culminated in absence of breathing attempts. Noninvasive monitoring of chest wall dynamics enables detection and classification of central and obstructive apneic episodes, which tightly correlates with the EP.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Young-Keun, E-mail: ykkim@handong.edu; Kim, Kyung-Soo

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-basedmore » sensor, the system is expected to be highly robust to sea weather conditions.« less

A High-Speed Vision-Based Sensor for Dynamic Vibration Analysis Using Fast Motion Extraction Algorithms.

PubMed

Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Changan

2016-04-22

The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features.

Inertial sensor-based smoother for gait analysis.

PubMed

Suh, Young Soo

2014-12-17

An off-line smoother algorithm is proposed to estimate foot motion using an inertial sensor unit (three-axis gyroscopes and accelerometers) attached to a shoe. The smoother gives more accurate foot motion estimation than filter-based algorithms by using all of the sensor data instead of using the current sensor data. The algorithm consists of two parts. In the first part, a Kalman filter is used to obtain initial foot motion estimation. In the second part, the error in the initial estimation is compensated using a smoother, where the problem is formulated in the quadratic optimization problem. An efficient solution of the quadratic optimization problem is given using the sparse structure. Through experiments, it is shown that the proposed algorithm can estimate foot motion more accurately than a filter-based algorithm with reasonable computation time. In particular, there is significant improvement in the foot motion estimation when the foot is moving off the floor: the z-axis position error squared sum (total time: 3.47 s) when the foot is in the air is 0.0807 m2 (Kalman filter) and 0.0020 m2 (the proposed smoother).

Ultra-wideband radar motion sensor

DOEpatents

McEwan, Thomas E.

1994-01-01

A motion sensor is based on ultra-wideband (UWB) radar. UWB radar range is determined by a pulse-echo interval. For motion detection, the sensors operate by staring at a fixed range and then sensing any change in the averaged radar reflectivity at that range. A sampling gate is opened at a fixed delay after the emission of a transmit pulse. The resultant sampling gate output is averaged over repeated pulses. Changes in the averaged sampling gate output represent changes in the radar reflectivity at a particular range, and thus motion.

Ultra-wideband radar motion sensor

DOEpatents

McEwan, T.E.

1994-11-01

A motion sensor is based on ultra-wideband (UWB) radar. UWB radar range is determined by a pulse-echo interval. For motion detection, the sensors operate by staring at a fixed range and then sensing any change in the averaged radar reflectivity at that range. A sampling gate is opened at a fixed delay after the emission of a transmit pulse. The resultant sampling gate output is averaged over repeated pulses. Changes in the averaged sampling gate output represent changes in the radar reflectivity at a particular range, and thus motion. 15 figs.

Piezoelectric power generation for sensor applications: design of a battery-less wireless tire pressure sensor

NASA Astrophysics Data System (ADS)

Makki, Noaman; Pop-Iliev, Remon

2011-06-01

An in-wheel wireless and battery-less piezo-powered tire pressure sensor is developed. Where conventional battery powered Tire Pressure Monitoring Systems (TPMS) are marred by the limited battery life, TPMS based on power harvesting modules provide virtually unlimited sensor life. Furthermore, the elimination of a permanent energy reservoir simplifies the overall sensor design through the exclusion of extra circuitry required to sense vehicle motion and conserve precious battery capacity during vehicle idling periods. In this paper, two design solutions are presented, 1) with very low cost highly flexible piezoceramic (PZT) bender elements bonded directly to the tire to generate power required to run the sensor and, 2) a novel rim mounted PZT harvesting unit that can be used to power pressure sensors incorporated into the valve stem requiring minimal change to the presently used sensors. While both the designs eliminate the use of environmentally unfriendly battery from the TPMS design, they offer advantages of being very low cost, service free and easily replaceable during tire repair and replacement.

Ductile cutting of silicon microstructures with surface inclination measurement and compensation by using a force sensor integrated single point diamond tool

NASA Astrophysics Data System (ADS)

Chen, Yuan-Liu; Cai, Yindi; Shimizu, Yuki; Ito, So; Gao, Wei; Ju, Bing-Feng

2016-02-01

This paper presents a measurement and compensation method of surface inclination for ductile cutting of silicon microstructures by using a diamond tool with a force sensor based on a four-axis ultra-precision lathe. The X- and Y-directional inclinations of a single crystal silicon workpiece with respect to the X- and Y-motion axes of the lathe slides were measured respectively by employing the diamond tool as a touch-trigger probe, in which the tool-workpiece contact is sensitively detected by monitoring the force sensor output. Based on the measurement results, fabrication of silicon microstructures can be thus carried out directly along the tilted silicon workpiece by compensating the cutting motion axis to be parallel to the silicon surface without time-consuming pre-adjustment of the surface inclination or turning of a flat surface. A diamond tool with a negative rake angle was used in the experiment for superior ductile cutting performance. The measurement precision by using the diamond tool as a touch-trigger probe was investigated. Experiments of surface inclination measurement and ultra-precision ductile cutting of a micro-pillar array and a micro-pyramid array with inclination compensation were carried out respectively to demonstrate the feasibility of the proposed method.

Autonomous Quality Control of Joint Orientation Measured with Inertial Sensors.

PubMed

Lebel, Karina; Boissy, Patrick; Nguyen, Hung; Duval, Christian

2016-07-05

Clinical mobility assessment is traditionally performed in laboratories using complex and expensive equipment. The low accessibility to such equipment, combined with the emerging trend to assess mobility in a free-living environment, creates a need for body-worn sensors (e.g., inertial measurement units-IMUs) that are capable of measuring the complexity in motor performance using meaningful measurements, such as joint orientation. However, accuracy of joint orientation estimates using IMUs may be affected by environment, the joint tracked, type of motion performed and velocity. This study investigates a quality control (QC) process to assess the quality of orientation data based on features extracted from the raw inertial sensors' signals. Joint orientation (trunk, hip, knee, ankle) of twenty participants was acquired by an optical motion capture system and IMUs during a variety of tasks (sit, sit-to-stand transition, walking, turning) performed under varying conditions (speed, environment). An artificial neural network was used to classify good and bad sequences of joint orientation with a sensitivity and a specificity above 83%. This study confirms the possibility to perform QC on IMU joint orientation data based on raw signal features. This innovative QC approach may be of particular interest in a big data context, such as for remote-monitoring of patients' mobility.

Uncertainty analysis of practical structural health monitoring systems currently employed for tall buildings consisting of small number of sensors

NASA Astrophysics Data System (ADS)

Hirai, Kenta; Mita, Akira

2016-04-01

Because of social background, such as repeated large earthquakes and cheating in design and construction, structural health monitoring (SHM) systems are getting strong attention. The SHM systems are in a practical phase. An SHM system consisting of small number of sensors has been introduced to 6 tall buildings in Shinjuku area. Including them, there are 2 major issues in the SHM systems consisting of small number of sensors. First, optimal system number of sensors and the location are not well-defined. In the practice, system placement is determined based on rough prediction and experience. Second, there are some uncertainties in estimation results by the SHM systems. Thus, the purpose of this research is to provide useful information for increasing reliability of SHM system and to improve estimation results based on uncertainty analysis of the SHM systems. The important damage index used here is the inter-story drift angle. The uncertainty considered here are number of sensors, earthquake motion characteristics, noise in data, error between numerical model and real building, nonlinearity of parameter. Then I have analyzed influence of each factor to estimation accuracy. The analysis conducted here will help to decide sensor system design considering valance of cost and accuracy. Because of constraint on the number of sensors, estimation results by the SHM system has tendency to provide smaller values. To overcome this problem, a compensation algorithm was discussed and presented. The usefulness of this compensation method was demonstrated for 40 story S and RC building models with nonlinear response.

Liquid-Embedded Elastomer Electronics

NASA Astrophysics Data System (ADS)

Kramer, Rebecca; Majidi, Carmel; Park, Yong-Lae; Paik, Jamie; Wood, Robert

2012-02-01

Hyperelastic sensors are fabricated by embedding a silicone rubber film with microchannels of conductive liquid. In the case of soft tactile sensors, pressing the surface of the elastomer will deform the cross-section of underlying channels and change their electrical resistance. Soft pressure sensors may be employed in a variety of applications. For example, a network of pressure sensors can serve as artificial skin by yielding detailed information about contact pressures. This concept was demonstrated in a hyperelastic keypad, where perpendicular conductive channels form a quasi-planar network within an elastomeric matrix that registers the location, intensity and duration of applied pressure. In a second demonstration, soft curvature sensors were used for joint angle proprioception. Because the sensors are soft and stretchable, they conform to the host without interfering with the natural mechanics of motion. This marked the first use of liquid-embedded elastomer electronics to monitor human or robotic motion. Finally, liquid-embedded elastomers may be implemented as conductors in applications that call for flexible or stretchable circuitry, such as robotic origami.

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study.

PubMed

Al-Naji, Ali; Gibson, Kim; Lee, Sang-Heon; Chahl, Javaan

2017-02-03

The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications.

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms.

PubMed

Hu, Qijun; He, Songsheng; Wang, Shilong; Liu, Yugang; Zhang, Zutao; He, Leping; Wang, Fubin; Cai, Qijie; Shi, Rendan; Yang, Yuan

2017-06-06

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable.

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms

PubMed Central

Hu, Qijun; He, Songsheng; Wang, Shilong; Liu, Yugang; Zhang, Zutao; He, Leping; Wang, Fubin; Cai, Qijie; Shi, Rendan; Yang, Yuan

2017-01-01

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable. PMID:28587275

Edge-filter technique and dominant frequency analysis for high-speed railway monitoring with fiber Bragg gratings

NASA Astrophysics Data System (ADS)

Kouroussis, Georges; Kinet, Damien; Mendoza, Edgar; Dupuy, Julien; Moeyaert, Véronique; Caucheteur, Christophe

2016-07-01

Structural health and operation monitoring are of growing interest in the development of railway networks. Conventional systems of infrastructure monitoring already exist (e.g. axle counters, track circuits) but present some drawbacks. Alternative solutions are therefore studied and developed. In this field, optical fiber sensors, and more particularly fiber Bragg grating (FBG) sensors, are particularly relevant due to their immunity to electromagnetic fields and simple wavelength-division-multiplexing capability. Field trials conducted up to now have demonstrated that FBG sensors provide useful information about train composition, positioning, speed, acceleration and weigh-in-motion estimations. Nevertheless, for practical deployment, cost-effectiveness should be ensured, specifically at the interrogator side that has also to be fast (>1 kHz repetition rate), accurate (∼1 pm wavelength shift) and reliable. To reach this objective, we propose in this paper to associate a low cost and high-speed interrogator coupled with an adequate signal-processing algorithm to dynamically monitor cascaded wavelength-multiplexed FBGs and to accurately capture the parameters of interest for railway traffic monitoring. This method has been field-tested with a Redondo Optics Inc. interrogator based on the well-known edge-filter demodulation technique. To determine the train speed from the raw data, a dominant frequency analysis has been implemented. Using this original method, we show that we can retrieve the speed of the trains, even when the time history strain signature is strongly affected by the measurement noise. The results are assessed by complimentary data obtained from a spectrometer-based FBG interrogator.

Civil infrastructure monitoring for IVHS using optical fiber sensors

NASA Astrophysics Data System (ADS)

de Vries, Marten J.; Arya, Vivek; Grinder, C. R.; Murphy, Kent A.; Claus, Richard O.

1995-01-01

8Early deployment of Intelligent Vehicle Highway Systems would necessitate the internal instrumentation of infrastructure for emergency preparedness. Existing quantitative analysis and visual analysis techniques are time consuming, cost prohibitive, and are often unreliable. Fiber optic sensors are rapidly replacing conventional instrumentation because of their small size, light weight, immunity to electromagnetic interference, and extremely high information carrying capability. In this paper research on novel optical fiber sensing techniques for health monitoring of civil infrastructure such as highways and bridges is reported. Design, fabrication, and implementation of fiber optic sensor configurations used for measurements of strain are discussed. Results from field tests conducted to demonstrate the effectiveness of fiber sensors at determining quantitative strain vector components near crack locations in bridges are presented. Emerging applications of fiber sensors for vehicle flow, vehicle speed, and weigh-in-motion measurements are also discussed.

Lumbar joint torque estimation based on simplified motion measurement using multiple inertial sensors.

PubMed

Miyajima, Saori; Tanaka, Takayuki; Imamura, Yumeko; Kusaka, Takashi

2015-01-01

We estimate lumbar torque based on motion measurement using only three inertial sensors. First, human motion is measured by a 6-axis motion tracking device that combines a 3-axis accelerometer and a 3-axis gyroscope placed on the shank, thigh, and back. Next, the lumbar joint torque during the motion is estimated by kinematic musculoskeletal simulation. The conventional method for estimating joint torque uses full body motion data measured by an optical motion capture system. However, in this research, joint torque is estimated by using only three link angles of the body, thigh, and shank. The utility of our method was verified by experiments. We measured motion of bendung knee and waist simultaneously. As the result, we were able to estimate the lumbar joint torque from measured motion.

In-motion optical sensing for assessment of animal well-being

NASA Astrophysics Data System (ADS)

Atkins, Colton A.; Pond, Kevin R.; Madsen, Christi K.

2017-05-01

The application of in-motion optical sensor measurements was investigated for inspecting livestock soundness as a means of animal well-being. An optical sensor-based platform was used to collect in-motion, weight-related information. Eight steers, weighing between 680 and 1134 kg, were evaluated twice. Six of the 8 steers were used for further evaluation and analysis. Hoof impacts caused plate flexion that was optically sensed. Observed kinetic differences between animals' strides at a walking or running/trotting gait with significant force distributions of animals' hoof impacts allowed for observation of real-time, biometric patterns. Overall, optical sensor-based measurements identified hoof differences between and within animals in motion that may allow for diagnosis of musculoskeletal unsoundness without visual evaluation.

Computer-Guided Deep Brain Stimulation Programming for Parkinson's Disease.

PubMed

Heldman, Dustin A; Pulliam, Christopher L; Urrea Mendoza, Enrique; Gartner, Maureen; Giuffrida, Joseph P; Montgomery, Erwin B; Espay, Alberto J; Revilla, Fredy J

2016-02-01

Pilot study to evaluate computer-guided deep brain stimulation (DBS) programming designed to optimize stimulation settings using objective motion sensor-based motor assessments. Seven subjects (five males; 54-71 years) with Parkinson's disease (PD) and recently implanted DBS systems participated in this pilot study. Within two months of lead implantation, the subject returned to the clinic to undergo computer-guided programming and parameter selection. A motion sensor was placed on the index finger of the more affected hand. Software guided a monopolar survey during which monopolar stimulation on each contact was iteratively increased followed by an automated assessment of tremor and bradykinesia. After completing assessments at each setting, a software algorithm determined stimulation settings designed to minimize symptom severities, side effects, and battery usage. Optimal DBS settings were chosen based on average severity of motor symptoms measured by the motion sensor. Settings chosen by the software algorithm identified a therapeutic window and improved tremor and bradykinesia by an average of 35.7% compared with baseline in the "off" state (p < 0.01). Motion sensor-based computer-guided DBS programming identified stimulation parameters that significantly improved tremor and bradykinesia with minimal clinician involvement. Automated motion sensor-based mapping is worthy of further investigation and may one day serve to extend programming to populations without access to specialized DBS centers. © 2015 International Neuromodulation Society.

A WBAN System for Ambulatory Monitoring of Physical Activity and Health Status: Applications and Challenges.

PubMed

Jovanov, E; Milenkovic, A; Otto, C; De Groen, P; Johnson, B; Warren, S; Taibi, G

2005-01-01

Recent technological advances in sensors, low-power integrated circuits, and wireless communications have enabled the design of low-cost, miniature, lightweight, intelligent physiological sensor platforms that can be seamlessly integrated into a body area network for health monitoring. Wireless body area networks (WBANs) promise unobtrusive ambulatory health monitoring for extended periods of time and near real-time updates of patients' medical records through the Internet. A number of innovative systems for health monitoring have recently been proposed. However, they typically rely on custom communication protocols and hardware designs, lacking generality and flexibility. The lack of standard platforms, system software support, and standards makes these systems expensive. Bulky sensors, high price, and frequent battery changes are all likely to limit user compliance. To address some of these challenges, we prototyped a WBAN utilizing a common off-the-shelf wireless sensor platform with a ZigBee-compliant radio interface and an ultra low-power microcontroller. The standard platform interfaces to custom sensor boards that are equipped with accelerometers for motion monitoring and a bioamplifier for electrocardiogram or electromyogram monitoring. Software modules for on-board processing, communication, and network synchronization have been developed using the TinyOS operating system. Although the initial WBAN prototype targets ambulatory monitoring of user activity, the developed sensors can easily be adapted to monitor other physiological parameters. In this paper, we discuss initial results, implementation challenges, and the need for standardization in this dynamic and promising research field.

Polyvinylidene fluoride sensor-based method for unconstrained snoring detection.

PubMed

Hwang, Su Hwan; Han, Chung Min; Yoon, Hee Nam; Jung, Da Woon; Lee, Yu Jin; Jeong, Do-Un; Park, Kwang Suk

2015-07-01

We established and tested a snoring detection method using a polyvinylidene fluoride (PVDF) sensor for accurate, fast, and motion-artifact-robust monitoring of snoring events during sleep. Twenty patients with obstructive sleep apnea participated in this study. The PVDF sensor was located between a mattress cover and mattress, and the patients' snoring signals were unconstrainedly measured with the sensor during polysomnography. The power ratio and peak frequency from the short-time Fourier transform were used to extract spectral features from the PVDF data. A support vector machine was applied to the spectral features to classify the data into either the snore or non-snore class. The performance of the method was assessed using manual labelling by three human observers as a reference. For event-by-event snoring detection, PVDF data that contained 'snoring' (SN), 'snoring with movement' (SM), and 'normal breathing' epochs were selected for each subject. As a result, the overall sensitivity and the positive predictive values were 94.6% and 97.5%, respectively, and there was no significant difference between the SN and SM results. The proposed method can be applied in both residential and ambulatory snoring monitoring systems.

Wireless Sensor Network Deployment for Monitoring Wildlife Passages

PubMed Central

Garcia-Sanchez, Antonio-Javier; Garcia-Sanchez, Felipe; Losilla, Fernando; Kulakowski, Pawel; Garcia-Haro, Joan; Rodríguez, Alejandro; López-Bao, José-Vicente; Palomares, Francisco

2010-01-01

Wireless Sensor Networks (WSNs) are being deployed in very diverse application scenarios, including rural and forest environments. In these particular contexts, specimen protection and conservation is a challenge, especially in natural reserves, dangerous locations or hot spots of these reserves (i.e., roads, railways, and other civil infrastructures). This paper proposes and studies a WSN based system for generic target (animal) tracking in the surrounding area of wildlife passages built to establish safe ways for animals to cross transportation infrastructures. In addition, it allows target identification through the use of video sensors connected to strategically deployed nodes. This deployment is designed on the basis of the IEEE 802.15.4 standard, but it increases the lifetime of the nodes through an appropriate scheduling. The system has been evaluated for the particular scenario of wildlife monitoring in passages across roads. For this purpose, different schemes have been simulated in order to find the most appropriate network operational parameters. Moreover, a novel prototype, provided with motion detector sensors, has also been developed and its design feasibility demonstrated. Original software modules providing new functionalities have been implemented and included in this prototype. Finally, main performance evaluation results of the whole system are presented and discussed in depth. PMID:22163601

In-line quality control of moving objects by means of spectral-domain OCT

NASA Astrophysics Data System (ADS)

Markl, Daniel; Hannesschläger, Günther; Buchsbaum, Andreas; Sacher, Stephan; Khinast, Johannes G.; Leitner, Michael

2014-08-01

In-line quality control of intermediate and final products is essential in various industries. This may imply determining the thickness of a foil or evaluating the homogeneity of coating applied to a pharmaceutical tablet. Such a qualitative and quantitative monitoring in a depth-resolved manner can be accomplished using optical coherence tomography (OCT). In-line quality control based on OCT requires additional consideration of motion effects for the system design as well as for data interpretation. This study focuses on transverse motion effects that can arise in spectral-domain (SD-) OCT systems. The impact of a transverse movement is analyzed for a constant relative speed difference up to 0.7 m/s between sample and sensor head. In particular, transverse motion is affecting OCT system properties such as the beam displacement (distance between adjacent A-scans) and transverse resolution. These properties were evaluated theoretically and experimentally for OCT images of a resolution target and pharmaceutical film-coated tablets. Both theoretical and experimental analyses highlight the shift of the transverse resolution limiting factor from the optics to the beam displacement above a relative speed difference between sensor head and sample of 0.42 m/s (for the presented SD-OCT setup). Speeds above 0.4 m/s are often demanded when monitoring industrial processes, such as a coating process when producing film-coated tablets. This emphasizes the importance of a fast data acquisition when using OCT as in-line quality control tool.

On-Line Detection and Segmentation of Sports Motions Using a Wearable Sensor.

PubMed

Kim, Woosuk; Kim, Myunggyu

2018-03-19

In sports motion analysis, observation is a prerequisite for understanding the quality of motions. This paper introduces a novel approach to detect and segment sports motions using a wearable sensor for supporting systematic observation. The main goal is, for convenient analysis, to automatically provide motion data, which are temporally classified according to the phase definition. For explicit segmentation, a motion model is defined as a sequence of sub-motions with boundary states. A sequence classifier based on deep neural networks is designed to detect sports motions from continuous sensor inputs. The evaluation on two types of motions (soccer kicking and two-handed ball throwing) verifies that the proposed method is successful for the accurate detection and segmentation of sports motions. By developing a sports motion analysis system using the motion model and the sequence classifier, we show that the proposed method is useful for observation of sports motions by automatically providing relevant motion data for analysis.

Technical and clinical view on ambulatory assessment in Parkinson's disease.

PubMed

Hobert, M A; Maetzler, W; Aminian, K; Chiari, L

2014-09-01

With the progress of technologies of recent years, methods have become available that use wearable sensors and ambulatory systems to measure aspects of--particular axial--motor function. As Parkinson's disease (PD) can be considered a model disorder for motor impairment, a significant number of studies have already been performed with these patients using such techniques. In general, motion sensors such as accelerometers and gyroscopes are used, in combination with lightweight electronics that do not interfere with normal human motion. A fundamental advantage in comparison with usual clinical assessment is that these sensors allow a more quantitative, objective, and reliable evaluation of symptoms; they have also significant advantages compared to in-lab technologies (e.g., optoelectronic motion capture) as they allow long-term monitoring under real-life conditions. In addition, based on recent findings particularly from studies using functional imaging, we learned that non-motor symptoms, specifically cognitive aspects, may be at least indirectly assessable. It is hypothesized that ambulatory quantitative assessment strategies will allow users, clinicians, and scientists in the future to gain more quantitative, unobtrusive, and everyday relevant data out of their clinical evaluation and can also be designed as pervasive (everywhere) and intensive (anytime) tools for ambulatory assessment and even rehabilitation of motor and (partly) non-motor symptoms in PD. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Citizen sensors for SHM: use of accelerometer data from smartphones.

PubMed

Feng, Maria; Fukuda, Yoshio; Mizuta, Masato; Ozer, Ekin

2015-01-29

Ubiquitous smartphones have created a significant opportunity to form a low-cost wireless Citizen Sensor network and produce big data for monitoring structural integrity and safety under operational and extreme loads. Such data are particularly useful for rapid assessment of structural damage in a large urban setting after a major event such as an earthquake. This study explores the utilization of smartphone accelerometers for measuring structural vibration, from which structural health and post-event damage can be diagnosed. Widely available smartphones are tested under sinusoidal wave excitations with frequencies in the range relevant to civil engineering structures. Large-scale seismic shaking table tests, observing input ground motion and response of a structural model, are carried out to evaluate the accuracy of smartphone accelerometers under operational, white-noise and earthquake excitations of different intensity. Finally, the smartphone accelerometers are tested on a dynamically loaded bridge. The extensive experiments show satisfactory agreements between the reference and smartphone sensor measurements in both time and frequency domains, demonstrating the capability of the smartphone sensors to measure structural responses ranging from low-amplitude ambient vibration to high-amplitude seismic response. Encouraged by the results of this study, the authors are developing a citizen-engaging and data-analytics crowdsourcing platform towards a smartphone-based Citizen Sensor network for structural health monitoring and post-event damage assessment applications.

Sensor Network Infrastructure for a Home Care Monitoring System

PubMed Central

Palumbo, Filippo; Ullberg, Jonas; Štimec, Ales; Furfari, Francesco; Karlsson, Lars; Coradeschi, Silvia

2014-01-01

This paper presents the sensor network infrastructure for a home care system that allows long-term monitoring of physiological data and everyday activities. The aim of the proposed system is to allow the elderly to live longer in their home without compromising safety and ensuring the detection of health problems. The system offers the possibility of a virtual visit via a teleoperated robot. During the visit, physiological data and activities occurring during a period of time can be discussed. These data are collected from physiological sensors (e.g., temperature, blood pressure, glucose) and environmental sensors (e.g., motion, bed/chair occupancy, electrical usage). The system can also give alarms if sudden problems occur, like a fall, and warnings based on more long-term trends, such as the deterioration of health being detected. It has been implemented and tested in a test environment and has been deployed in six real homes for a year-long evaluation. The key contribution of the paper is the presentation of an implemented system for ambient assisted living (AAL) tested in a real environment, combining the acquisition of sensor data, a flexible and adaptable middleware compliant with the OSGistandard and a context recognition application. The system has been developed in a European project called GiraffPlus. PMID:24573309

Sensor network infrastructure for a home care monitoring system.

PubMed

Palumbo, Filippo; Ullberg, Jonas; Stimec, Ales; Furfari, Francesco; Karlsson, Lars; Coradeschi, Silvia

2014-02-25

This paper presents the sensor network infrastructure for a home care system that allows long-term monitoring of physiological data and everyday activities. The aim of the proposed system is to allow the elderly to live longer in their home without compromising safety and ensuring the detection of health problems. The system offers the possibility of a virtual visit via a teleoperated robot. During the visit, physiological data and activities occurring during a period of time can be discussed. These data are collected from physiological sensors (e.g., temperature, blood pressure, glucose) and environmental sensors (e.g., motion, bed/chair occupancy, electrical usage). The system can also give alarms if sudden problems occur, like a fall, and warnings based on more long-term trends, such as the deterioration of health being detected. It has been implemented and tested in a test environment and has been deployed in six real homes for a year-long evaluation. The key contribution of the paper is the presentation of an implemented system for ambient assisted living (AAL) tested in a real environment, combining the acquisition of sensor data, a flexible and adaptable middleware compliant with the OSGistandard and a context recognition application. The system has been developed in a European project called GiraffPlus.

Segmentation and Characterization of Chewing Bouts by Monitoring Temporalis Muscle Using Smart Glasses With Piezoelectric Sensor.

PubMed

Farooq, Muhammad; Sazonov, Edward

2017-11-01

Several methods have been proposed for automatic and objective monitoring of food intake, but their performance suffers in the presence of speech and motion artifacts. This paper presents a novel sensor system and algorithms for detection and characterization of chewing bouts from a piezoelectric strain sensor placed on the temporalis muscle. The proposed data acquisition device was incorporated into the temple of eyeglasses. The system was tested by ten participants in two part experiments, one under controlled laboratory conditions and the other in unrestricted free-living. The proposed food intake recognition method first performed an energy-based segmentation to isolate candidate chewing segments (instead of using epochs of fixed duration commonly reported in research literature), with the subsequent classification of the segments by linear support vector machine models. On participant level (combining data from both laboratory and free-living experiments), with ten-fold leave-one-out cross-validation, chewing were recognized with average F-score of 96.28% and the resultant area under the curve was 0.97, which are higher than any of the previously reported results. A multivariate regression model was used to estimate chew counts from segments classified as chewing with an average mean absolute error of 3.83% on participant level. These results suggest that the proposed system is able to identify chewing segments in the presence of speech and motion artifacts, as well as automatically and accurately quantify chewing behavior, both under controlled laboratory conditions and unrestricted free-living.

A Mobile Sensor Network System for Monitoring of Unfriendly Environments.

PubMed

Song, Guangming; Zhou, Yaoxin; Ding, Fei; Song, Aiguo

2008-11-14

Observing microclimate changes is one of the most popular applications of wireless sensor networks. However, some target environments are often too dangerous or inaccessible to humans or large robots and there are many challenges for deploying and maintaining wireless sensor networks in those unfriendly environments. This paper presents a mobile sensor network system for solving this problem. The system architecture, the mobile node design, the basic behaviors and advanced network capabilities have been investigated respectively. A wheel-based robotic node architecture is proposed here that can add controlled mobility to wireless sensor networks. A testbed including some prototype nodes has also been created for validating the basic functions of the proposed mobile sensor network system. Motion performance tests have been done to get the positioning errors and power consumption model of the mobile nodes. Results of the autonomous deployment experiment show that the mobile nodes can be distributed evenly into the previously unknown environments. It provides powerful support for network deployment and maintenance and can ensure that the sensor network will work properly in unfriendly environments.

Unconstrained pulse pressure monitoring for health management using hetero-core fiber optic sensor.

PubMed

Nishiyama, Michiko; Sonobe, Masako; Watanabe, Kazuhiro

2016-09-01

In this paper, we present a pulse pressure waveform sensor that does not constrain a wearer's daily activity; the sensor uses hetero-core fiber optics. Hetero-core fiber sensors have been found to be sensitive to moderate bending. To detect minute pulse pressure changes from the radial artery at the wrist, we devised a fiber sensor arrangement using three-point bending supports. We analyzed and evaluated the measurement validity using wavelet transformation, which is well-suited for biological signal processing. It was confirmed that the detected pulse waveform had a fundamental mode frequency of around 1.25 Hz over the time-varying waveform. A band-pass filter with a range of frequencies from 0.85 to 1.7 Hz was used to pick up the fundamental mode. In addition, a high-pass filter with 0.85 Hz frequency eliminated arm motion artifacts; consequently, we achieved high signal-to-noise ratio. For unrestricted daily health management, it is desirable that pulse pressure monitoring can be achieved by simply placing a device on the hand without the sensor being noticed. Two types of arrangements were developed and demonstrated in which the pulse sensors were either embedded in a base, such as an armrest, or in a wearable device. A wearable device without cuff pressure using a sensitivity-enhanced fiber sensor was successfully achieved with a sensitivity of 0.07-0.3 dB with a noise floor lower than 0.01 dB for multiple subjects.

Daily life activity routine discovery in hemiparetic rehabilitation patients using topic models.

PubMed

Seiter, J; Derungs, A; Schuster-Amft, C; Amft, O; Tröster, G

2015-01-01

Monitoring natural behavior and activity routines of hemiparetic rehabilitation patients across the day can provide valuable progress information for therapists and patients and contribute to an optimized rehabilitation process. In particular, continuous patient monitoring could add type, frequency and duration of daily life activity routines and hence complement standard clinical scores that are assessed for particular tasks only. Machine learning methods have been applied to infer activity routines from sensor data. However, supervised methods require activity annotations to build recognition models and thus require extensive patient supervision. Discovery methods, including topic models could provide patient routine information and deal with variability in activity and movement performance across patients. Topic models have been used to discover characteristic activity routine patterns of healthy individuals using activity primitives recognized from supervised sensor data. Yet, the applicability of topic models for hemiparetic rehabilitation patients and techniques to derive activity primitives without supervision needs to be addressed. We investigate, 1) whether a topic model-based activity routine discovery framework can infer activity routines of rehabilitation patients from wearable motion sensor data. 2) We compare the performance of our topic model-based activity routine discovery using rule-based and clustering-based activity vocabulary. We analyze the activity routine discovery in a dataset recorded with 11 hemiparetic rehabilitation patients during up to ten full recording days per individual in an ambulatory daycare rehabilitation center using wearable motion sensors attached to both wrists and the non-affected thigh. We introduce and compare rule-based and clustering-based activity vocabulary to process statistical and frequency acceleration features to activity words. Activity words were used for activity routine pattern discovery using topic models based on Latent Dirichlet Allocation. Discovered activity routine patterns were then mapped to six categorized activity routines. Using the rule-based approach, activity routines could be discovered with an average accuracy of 76% across all patients. The rule-based approach outperformed clustering by 10% and showed less confusions for predicted activity routines. Topic models are suitable to discover daily life activity routines in hemiparetic rehabilitation patients without trained classifiers and activity annotations. Activity routines show characteristic patterns regarding activity primitives including body and extremity postures and movement. A patient-independent rule set can be derived. Including expert knowledge supports successful activity routine discovery over completely data-driven clustering.

A wearable strain sensor based on a carbonized nano-sponge/silicone composite for human motion detection.

PubMed

Yu, Xiao-Guang; Li, Yuan-Qing; Zhu, Wei-Bin; Huang, Pei; Wang, Tong-Tong; Hu, Ning; Fu, Shao-Yun

2017-05-25

Melamine sponge, also known as nano-sponge, is widely used as an abrasive cleaner in our daily life. In this work, the fabrication of a wearable strain sensor for human motion detection is first demonstrated with a commercially available nano-sponge as a starting material. The key resistance sensitive material in the wearable strain sensor is obtained by the encapsulation of a carbonized nano-sponge (CNS) with silicone resin. The as-fabricated CNS/silicone sensor is highly sensitive to strain with a maximum gauge factor of 18.42. In addition, the CNS/silicone sensor exhibits a fast and reliable response to various cyclic loading within a strain range of 0-15% and a loading frequency range of 0.01-1 Hz. Finally, the CNS/silicone sensor as a wearable device for human motion detection including joint motion, eye blinking, blood pulse and breathing is demonstrated by attaching the sensor to the corresponding parts of the human body. In consideration of the simple fabrication technique, low material cost and excellent strain sensing performance, the CNS/silicone sensor is believed to have great potential in the next-generation of wearable devices for human motion detection.

Study on the multi-sensors monitoring and information fusion technology of dangerous cargo container

NASA Astrophysics Data System (ADS)

Xu, Shibo; Zhang, Shuhui; Cao, Wensheng

2017-10-01

In this paper, monitoring system of dangerous cargo container based on multi-sensors is presented. In order to improve monitoring accuracy, multi-sensors will be applied inside of dangerous cargo container. Multi-sensors information fusion solution of monitoring dangerous cargo container is put forward, and information pre-processing, the fusion algorithm of homogenous sensors and information fusion based on BP neural network are illustrated, applying multi-sensors in the field of container monitoring has some novelty.

Smart Braid Feedback for the Closed-Loop Control of Soft Robotic Systems.

PubMed

Felt, Wyatt; Chin, Khai Yi; Remy, C David

2017-09-01

This article experimentally investigates the potential of using flexible, inductance-based contraction sensors in the closed-loop motion control of soft robots. Accurate motion control remains a highly challenging task for soft robotic systems. Precise models of the actuation dynamics and environmental interactions are often unavailable. This renders open-loop control impossible, while closed-loop control suffers from a lack of suitable feedback. Conventional motion sensors, such as linear or rotary encoders, are difficult to adapt to robots that lack discrete mechanical joints. The rigid nature of these sensors runs contrary to the aspirational benefits of soft systems. As truly soft sensor solutions are still in their infancy, motion control of soft robots has so far relied on laboratory-based sensing systems such as motion capture, electromagnetic (EM) tracking, or Fiber Bragg Gratings. In this article, we used embedded flexible sensors known as Smart Braids to sense the contraction of McKibben muscles through changes in inductance. We evaluated closed-loop control on two systems: a revolute joint and a planar, one degree of freedom continuum manipulator. In the revolute joint, our proposed controller compensated for elasticity in the actuator connections. The Smart Braid feedback allowed motion control with a steady-state root-mean-square (RMS) error of [1.5]°. In the continuum manipulator, Smart Braid feedback enabled tracking of the desired tip angle with a steady-state RMS error of [1.25]°. This work demonstrates that Smart Braid sensors can provide accurate position feedback in closed-loop motion control suitable for field applications of soft robotic systems.

Secured network sensor-based defense system

NASA Astrophysics Data System (ADS)

Wei, Sixiao; Shen, Dan; Ge, Linqiang; Yu, Wei; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe

2015-05-01

Network sensor-based defense (NSD) systems have been widely used to defend against cyber threats. Nonetheless, if the adversary finds ways to identify the location of monitor sensors, the effectiveness of NSD systems can be reduced. In this paper, we propose both temporal and spatial perturbation based defense mechanisms to secure NSD systems and make the monitor sensor invisible to the adversary. The temporal-perturbation based defense manipulates the timing information of published data so that the probability of successfully recognizing monitor sensors can be reduced. The spatial-perturbation based defense dynamically redeploys monitor sensors in the network so that the adversary cannot obtain the complete information to recognize all of the monitor sensors. We carried out experiments using real-world traffic traces to evaluate the effectiveness of our proposed defense mechanisms. Our data shows that our proposed defense mechanisms can reduce the attack accuracy of recognizing detection sensors.

Effects of transients in LIGO suspensions on searches for gravitational waves

NASA Astrophysics Data System (ADS)

Walker, M.; Abbott, T. D.; Aston, S. M.; González, G.; Macleod, D. M.; McIver, J.; Abbott, B. P.; Abbott, R.; Adams, C.; Adhikari, R. X.; Anderson, S. B.; Ananyeva, A.; Appert, S.; Arai, K.; Ballmer, S. W.; Barker, D.; Barr, B.; Barsotti, L.; Bartlett, J.; Bartos, I.; Batch, J. C.; Bell, A. S.; Betzwieser, J.; Billingsley, G.; Birch, J.; Biscans, S.; Biwer, C.; Blair, C. D.; Bork, R.; Brooks, A. F.; Ciani, G.; Clara, F.; Countryman, S. T.; Cowart, M. J.; Coyne, D. C.; Cumming, A.; Cunningham, L.; Danzmann, K.; Da Silva Costa, C. F.; Daw, E. J.; DeBra, D.; DeRosa, R. T.; DeSalvo, R.; Dooley, K. L.; Doravari, S.; Driggers, J. C.; Dwyer, S. E.; Effler, A.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fair, H.; Fernández Galiana, A.; Fisher, R. P.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Giaime, J. A.; Giardina, K. D.; Goetz, E.; Goetz, R.; Gras, S.; Gray, C.; Grote, H.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, E. D.; Hammond, G.; Hanks, J.; Hanson, J.; Hardwick, T.; Harry, G. M.; Heintze, M. C.; Heptonstall, A. W.; Hough, J.; Izumi, K.; Jones, R.; Kandhasamy, S.; Karki, S.; Kasprzack, M.; Kaufer, S.; Kawabe, K.; Kijbunchoo, N.; King, E. J.; King, P. J.; Kissel, J. S.; Korth, W. Z.; Kuehn, G.; Landry, M.; Lantz, B.; Lockerbie, N. A.; Lormand, M.; Lundgren, A. P.; MacInnis, M.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martin, I. W.; Martynov, D. V.; Mason, K.; Massinger, T. J.; Matichard, F.; Mavalvala, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McIntyre, G.; Mendell, G.; Merilh, E. L.; Meyers, P. M.; Miller, J.; Mittleman, R.; Moreno, G.; Mueller, G.; Mullavey, A.; Munch, J.; Nuttall, L. K.; Oberling, J.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ottaway, D. J.; Overmier, H.; Palamos, J. R.; Paris, H. R.; Parker, W.; Pele, A.; Penn, S.; Phelps, M.; Pierro, V.; Pinto, I.; Principe, M.; Prokhorov, L. G.; Puncken, O.; Quetschke, V.; Quintero, E. A.; Raab, F. J.; Radkins, H.; Raffai, P.; Reid, S.; Reitze, D. H.; Robertson, N. A.; Rollins, J. G.; Roma, V. J.; Romie, J. H.; Rowan, S.; Ryan, K.; Sadecki, T.; Sanchez, E. J.; Sandberg, V.; Savage, R. L.; Schofield, R. M. S.; Sellers, D.; Shaddock, D. A.; Shaffer, T. J.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sigg, D.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Sorazu, B.; Staley, A.; Strain, K. A.; Tanner, D. B.; Taylor, R.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Torrie, C. I.; Traylor, G.; Tuyenbayev, D.; Vajente, G.; Valdes, G.; van Veggel, A. A.; Vecchio, A.; Veitch, P. J.; Venkateswara, K.; Vo, T.; Vorvick, C.; Ward, R. L.; Warner, J.; Weaver, B.; Weiss, R.; Weßels, P.; Willke, B.; Wipf, C. C.; Worden, J.; Wu, G.; Yamamoto, H.; Yancey, C. C.; Yu, Hang; Yu, Haocun; Zhang, L.; Zucker, M. E.; Zweizig, J.

2017-12-01

This paper presents an analysis of the transient behavior of the Advanced LIGO (Laser Interferometer Gravitational-wave Observatory) suspensions used to seismically isolate the optics. We have characterized the transients in the longitudinal motion of the quadruple suspensions during Advanced LIGO's first observing run. Propagation of transients between stages is consistent with modeled transfer functions, such that transient motion originating at the top of the suspension chain is significantly reduced in amplitude at the test mass. We find that there are transients seen by the longitudinal motion monitors of quadruple suspensions, but they are not significantly correlated with transient motion above the noise floor in the gravitational wave strain data, and therefore do not present a dominant source of background noise in the searches for transient gravitational wave signals. Using the suspension transfer functions, we compared the transients in a week of gravitational wave strain data with transients from a quadruple suspension. Of the strain transients between 10 and 60 Hz, 84% are loud enough that they would have appeared above the sensor noise in the top stage quadruple suspension monitors if they had originated at that stage at the same frequencies. We find no significant temporal correlation with the suspension transients in that stage, so we can rule out suspension motion originating at the top stage as the cause of those transients. However, only 3.2% of the gravitational wave strain transients are loud enough that they would have been seen by the second stage suspension sensors, and none of them are above the sensor noise levels of the penultimate stage. Therefore, we cannot eliminate the possibility of transient noise in the detectors originating in the intermediate stages of the suspension below the sensing noise.

Significant Change Spotting for Periodic Human Motion Segmentation of Cleaning Tasks Using Wearable Sensors

PubMed Central

Liu, Kai-Chun; Chan, Chia-Tai

2017-01-01

The proportion of the aging population is rapidly increasing around the world, which will cause stress on society and healthcare systems. In recent years, advances in technology have created new opportunities for automatic activities of daily living (ADL) monitoring to improve the quality of life and provide adequate medical service for the elderly. Such automatic ADL monitoring requires reliable ADL information on a fine-grained level, especially for the status of interaction between body gestures and the environment in the real-world. In this work, we propose a significant change spotting mechanism for periodic human motion segmentation during cleaning task performance. A novel approach is proposed based on the search for a significant change of gestures, which can manage critical technical issues in activity recognition, such as continuous data segmentation, individual variance, and category ambiguity. Three typical machine learning classification algorithms are utilized for the identification of the significant change candidate, including a Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Naive Bayesian (NB) algorithm. Overall, the proposed approach achieves 96.41% in the F1-score by using the SVM classifier. The results show that the proposed approach can fulfill the requirement of fine-grained human motion segmentation for automatic ADL monitoring. PMID:28106853

Pyroelectric IR sensor arrays for fall detection in the older population

NASA Astrophysics Data System (ADS)

Sixsmith, A.; Johnson, N.; Whatmore, R.

2005-09-01

Uncooled pyroelectric sensor arrays have been studied over many years for their uses in thermal imaging applications. These arrays will only detect changes in IR flux and so systems based upon them are very good at detecting movements of people in the scene without sensing the background, if they are used in staring mode. Relatively-low element count arrays (16 x 16) can be used for a variety of people sensing applications, including people counting (for safety applications), queue monitoring etc. With appropriate signal processing such systems can be also be used for the detection of particular events such as a person falling over. There is a considerable need for automatic fall detection amongst older people, but there are important limitations to some of the current and emerging technologies available for this. Simple sensors, such as 1 or 2 element pyroelectric infra-red sensors provide crude data that is difficult to interpret; the use of devices worn on the person, such as wrist communicator and motion detectors have potential, but are reliant on the person being able and willing to wear the device; video cameras may be seen as intrusive and require considerable human resources to monitor activity while machine-interpretation of camera images is complex and may be difficult in this application area. The use of a pyroelectric thermal array sensor was seen to have a number of potential benefits. The sensor is wall-mounted and does not require the user to wear a device. It enables detailed analysis of a subject's motion to be achieved locally, within the detector, using only a modest processor. This is possible due to the relative ease with which data from the sensor can be interpreted relative to the data generated by alternative sensors such as video devices. In addition to the cost-effectiveness of this solution, it was felt that the lack of detail in the low-level data, together with the elimination of the need to transmit data outside the detector, would help to avert feelings intrusiveness on the part of the end-user.The main benefits of this type of technology would be for older people who spend time alone in unsupervised environments. This would include people living alone in ordinary housing or in sheltered accommodation (apartment complexes for older people with local warden) and non-communal areas in residential/nursing home environments (e.g. bedrooms and ensuite bathrooms and toilets). This paper will review the development of the array, the pyroelectric ceramic material upon which it is based and the system capabilities. It will present results from the Framework 5 SIMBAD project, which used the system to monitor the movements of elderly people over a considerable period of time.

A model-based reasoning approach to sensor placement for monitorability

NASA Technical Reports Server (NTRS)

Chien, Steve; Doyle, Richard; Homemdemello, Luiz

1992-01-01

An approach is presented to evaluating sensor placements to maximize monitorability of the target system while minimizing the number of sensors. The approach uses a model of the monitored system to score potential sensor placements on the basis of four monitorability criteria. The scores can then be analyzed to produce a recommended sensor set. An example from our NASA application domain is used to illustrate our model-based approach to sensor placement.

The Design of The Monitoring Tools Of Clean Air Condition And Dangerous Gas CO, CO2 CH4 In Chemical Laboratory By Using Fuzzy Logic Based On Microcontroller

NASA Astrophysics Data System (ADS)

Widodo, Slamet; Miftakul, Amin M.; Sutrisman, Adi

2018-02-01

There are many phenomena that human are exposed to toxins from certain types such as of CO2, CO2 and CH4 gases. The device used to detect large amounts of CO, CO2, and CH4 gas in air in enclosed spaces using MQ 135 gas sensors of different types based on the three sensitivity of the Gas. The results of testing the use of sensors MQ 135 on the gas content of CO, CO2 and CH4 received by the sensor is still in the form of ppm based on the maximum ppm detection range of each sensor. Active sensor detects CO 120 ppm gas, CO2 1600 ppm and CH4 1ppm "standby 1" air condition with intermediate rotary fan. Active sensor detects CO 30 ppm gas, CO2 490 ppm and CH4 7 ppm "Standby 2" with low rotating fan output. Fuzzy rulebase logic for motor speed when gas detection sensor CO, CO2, and CH4 output controls the motion speed of the fan blower. Active sensors detect CO 15 ppm, CO2 320 ppm and CH4 45 ppm "Danger" air condition with high fan spin fan. At the gas level of CO 15 ppm, CO2 390 ppm and CH4 3 ppm detect "normal" AC sensor with fan output stop spinning.

Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades.

PubMed

Orchard, Garrick; Jayawant, Ajinkya; Cohen, Gregory K; Thakor, Nitish

2015-01-01

Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset creation rather than collecting and labeling existing data. The task is further complicated by a desire to simultaneously provide traditional frame-based recordings to allow for direct comparison with traditional Computer Vision algorithms. Here we propose a method for converting existing Computer Vision static image datasets into Neuromorphic Vision datasets using an actuated pan-tilt camera platform. Moving the sensor rather than the scene or image is a more biologically realistic approach to sensing and eliminates timing artifacts introduced by monitor updates when simulating motion on a computer monitor. We present conversion of two popular image datasets (MNIST and Caltech101) which have played important roles in the development of Computer Vision, and we provide performance metrics on these datasets using spike-based recognition algorithms. This work contributes datasets for future use in the field, as well as results from spike-based algorithms against which future works can compare. Furthermore, by converting datasets already popular in Computer Vision, we enable more direct comparison with frame-based approaches.

Deep-brain stimulator and control of Parkinson's disease

NASA Astrophysics Data System (ADS)

Varadan, Vijay K.; Harbaugh, Robert; Abraham, Jose K.

2004-07-01

The design of a novel feedback sensor system with wireless implantable polymer MEMS sensors for detecting and wirelessly transmitting physiological data that can be used for the diagnosis and treatment of various neurological disorders, such as Parkinson's disease, epilepsy, head injury, stroke, hydrocephalus, changes in pressure, patient movements, and tremors is presented in this paper. The sensor system includes MEMS gyroscopes, accelerometers, and pressure sensors. This feedback sensor system focuses on the development and integration of implantable systems with various wireless sensors for medical applications, particularly for the Parkinson's disease. It is easy to integrate and modify the sensor network feed back system for other neurological disorders mentioned above. The monitoring and control of tremor in Parkinson's disease can be simulated on a skeleton via wireless telemetry system communicating with electroactive polymer actuator, and microsensors attached to the skeleton hand and legs. Upon sensing any abnormal motor activity which represent the characteristic rhythmic motion of a typical Parkinson's (PD) patient, these sensors will generate necessary control pulses which will be transmitted to a hat sensor system on the skeleton head. Tiny inductively coupled antennas attached to the hat sensor system can receive these control pulses, demodulate and deliver it to actuate the parts of the skeleton to control the abnormal motor activity. This feedback sensor system can further monitor and control depending on the amplitude of the abnormal motor activity. This microsystem offers cost effective means of monitoring and controlling of neurological disorders in real PD patients. Also, this network system offers a remote monitoring of the patients conditions without visiting doctors office or hospitals. The data can be monitored using PDA and can be accessed using internet (or cell phone). Cellular phone technology will allow a health care worker to be automatically notified if monitoring indicates an emergency situation. The main advantage of such system is that it can effectively monitor large number of patients at the same time, which helps to compensate the present shortage of health care workers.

The instantaneous linear motion information measurement method based on inertial sensors for ships

NASA Astrophysics Data System (ADS)

Yang, Xu; Huang, Jing; Gao, Chen; Quan, Wei; Li, Ming; Zhang, Yanshun

2018-05-01

Ship instantaneous line motion information is the important foundation for ship control, which needs to be measured accurately. For this purpose, an instantaneous line motion measurement method based on inertial sensors is put forward for ships. By introducing a half-fixed coordinate system to realize the separation between instantaneous line motion and ship master movement, the instantaneous line motion acceleration of ships can be obtained with higher accuracy. Then, the digital high-pass filter is applied to suppress the velocity error caused by the low frequency signal such as schuler period. Finally, the instantaneous linear motion displacement of ships can be measured accurately. Simulation experimental results show that the method is reliable and effective, and can realize the precise measurement of velocity and displacement of instantaneous line motion for ships.

Flexible Strain Sensors Fabricated by Meniscus-Guided Printing of Carbon Nanotube-Polymer Composites.

PubMed

Wajahat, Muhammad; Lee, Sanghyeon; Kim, Jung Hyun; Chang, Won Suk; Pyo, Jaeyeon; Cho, Sung Ho; Seol, Seung Kwon

2018-06-13

Printed strain sensors have promising potential as a human-machine interface (HMI) for health-monitoring systems, human-friendly wearable interactive systems, and smart robotics. Herein, flexible strain sensors based on carbon nanotube (CNT)-polymer composites were fabricated by meniscus-guided printing using a CNT ink formulated from multiwall nanotubes (MWNTs) and polyvinylpyrrolidone (PVP); the ink was suitable for micropatterning on nonflat (or curved) substrates and even three-dimensional structures. The printed strain sensors exhibit a reproducible response to applied tensile and compressive strains, having gauge factors of 13.07 under tensile strain and 12.87 under compressive strain; they also exhibit high stability during ∼1500 bending cycles. Applied strains induce a contact rearrangement of the MWNTs and a change in the tunneling distance between them, resulting in a change in the resistance (Δ R/ R 0 ) of the sensor. Printed MWNT-PVP sensors were used in gloves for finger movement detection; these can be applied to human motion detection and remote control of robotic equipment. Our results demonstrate that meniscus-guided printing using CNT inks can produce highly flexible, sensitive, and inexpensive HMI devices.

A simple integrative method for presenting head-contingent motion parallax and disparity cues on intel x86 processor-based machines.

PubMed

Szatmary, J; Hadani, I; Julesz, B

1997-01-01

Rogers and Graham (1979) developed a system to show that head-movement-contingent motion parallax produces monocular depth perception in random dot patterns. Their display system comprised an oscilloscope driven by function generators or a special graphics board that triggered the X and Y deflection of the raster scan signal. Replication of this system required costly hardware that is no longer on the market. In this paper the Rogers-Graham method is reproduced with an Intel processor based IBM PC compatible machine with no additional hardware cost. An adapted joystick sampled through the standard game-port can serve as a provisional head-movement sensor. Monitor resolution for displaying motion is effectively enhanced 16 times by the use of anti-aliasing, enabling the display of thousands of random dots in real-time with a refresh rate of 60 Hz or above. A color monitor enables the use of the anaglyph method, thus combining stereoscopic and monocular parallax on a single display without the loss of speed. The power of this system is demonstrated by a psychophysical measurement in which subjects nulled head-movement-contingent illusory parallax, evoked by a static stereogram, with real parallax. The amount of real parallax required to null the illusory stereoscopic parallax monotonically increased with disparity.

Modeling perceived stress via HRV and accelerometer sensor streams.

PubMed

Wu, Min; Cao, Hong; Nguyen, Hai-Long; Surmacz, Karl; Hargrove, Caroline

2015-08-01

Discovering and modeling of stress patterns of human beings is a key step towards achieving automatic stress monitoring, stress management and healthy lifestyle. As various wearable sensors become popular, it becomes possible for individuals to acquire their own relevant sensory data and to automatically assess their stress level on the go. Previous studies for stress analysis were conducted in the controlled laboratory and clinic settings. These studies are not suitable for stress monitoring in one's daily life as various physical activities may affect the physiological signals. In this paper, we address such issue by integrating two modalities of sensors, i.e., HRV sensors and accelerometers, to monitor the perceived stress levels in daily life. We gathered both the heart and the motion data from 8 participants continuously for about 2 weeks. We then extracted features from both sensory data and compared the existing machine learning methods for learning personalized models to interpret the perceived stress levels. Experimental results showed that Bagging classifier with feature selection is able to achieve a prediction accuracy 85.7%, indicating our stress monitoring on daily basis is fairly practical.

Smart Sensor-Based Motion Detection System for Hand Movement Training in Open Surgery.

PubMed

Sun, Xinyao; Byrns, Simon; Cheng, Irene; Zheng, Bin; Basu, Anup

2017-02-01

We introduce a smart sensor-based motion detection technique for objective measurement and assessment of surgical dexterity among users at different experience levels. The goal is to allow trainees to evaluate their performance based on a reference model shared through communication technology, e.g., the Internet, without the physical presence of an evaluating surgeon. While in the current implementation we used a Leap Motion Controller to obtain motion data for analysis, our technique can be applied to motion data captured by other smart sensors, e.g., OptiTrack. To differentiate motions captured from different participants, measurement and assessment in our approach are achieved using two strategies: (1) low level descriptive statistical analysis, and (2) Hidden Markov Model (HMM) classification. Based on our surgical knot tying task experiment, we can conclude that finger motions generated from users with different surgical dexterity, e.g., expert and novice performers, display differences in path length, number of movements and task completion time. In order to validate the discriminatory ability of HMM for classifying different movement patterns, a non-surgical task was included in our analysis. Experimental results demonstrate that our approach had 100 % accuracy in discriminating between expert and novice performances. Our proposed motion analysis technique applied to open surgical procedures is a promising step towards the development of objective computer-assisted assessment and training systems.

Strong Motion Seismograph Based On MEMS Accelerometer

NASA Astrophysics Data System (ADS)

Teng, Y.; Hu, X.

2013-12-01

The MEMS strong motion seismograph we developed used the modularization method to design its software and hardware.It can fit various needs in different application situation.The hardware of the instrument is composed of a MEMS accelerometer,a control processor system,a data-storage system,a wired real-time data transmission system by IP network,a wireless data transmission module by 3G broadband,a GPS calibration module and power supply system with a large-volumn lithium battery in it. Among it,the seismograph's sensor adopted a three-axis with 14-bit high resolution and digital output MEMS accelerometer.Its noise level just reach about 99μg/√Hz and ×2g to ×8g dynamically selectable full-scale.Its output data rates from 1.56Hz to 800Hz. Its maximum current consumption is merely 165μA,and the device is so small that it is available in a 3mm×3mm×1mm QFN package. Furthermore,there is access to both low pass filtered data as well as high pass filtered data,which minimizes the data analysis required for earthquake signal detection. So,the data post-processing can be simplified. Controlling process system adopts a 32-bit low power consumption embedded ARM9 processor-S3C2440 and is based on the Linux operation system.The processor's operating clock at 400MHz.The controlling system's main memory is a 64MB SDRAM with a 256MB flash-memory.Besides,an external high-capacity SD card data memory can be easily added.So the system can meet the requirements for data acquisition,data processing,data transmission,data storage,and so on. Both wired and wireless network can satisfy remote real-time monitoring, data transmission,system maintenance,status monitoring or updating software.Linux was embedded and multi-layer designed conception was used.The code, including sensor hardware driver,the data acquisition,earthquake setting out and so on,was written on medium layer.The hardware driver consist of IIC-Bus interface driver, IO driver and asynchronous notification driver. The application program layer mainly concludes: earthquake parameter module, local database managing module, data transmission module, remote monitoring, FTP service and so on. The application layer adopted multi-thread process. The whole strong motion seismograph was encapsulated in a small aluminum box, which size is 80mm×120mm×55mm. The inner battery can work continuesly more than 24 hours. The MEMS accelerograph uses modular design for its software part and hardware part. It has remote software update function and can meet the following needs: a) Auto picking up the earthquake event; saving the data on wave-event files and hours files; It may be used for monitoring strong earthquake, explosion, bridge and house health. b) Auto calculate the earthquake parameters, and transferring those parameters by 3G wireless broadband network. This kind of seismograph has characteristics of low cost, easy installation. They can be concentrated in the urban region or areas need to specially care. We can set up a ground motion parameters quick report sensor network while large earthquake break out. Then high-resolution-fine shake-map can be easily produced for the need of emergency rescue. c) By loading P-wave detection program modules, it can be used for earthquake early warning for large earthquakes; d) Can easily construct a high-density layout seismic monitoring network owning remote control and modern intelligent earthquake sensor.

Avoiding space robot collisions utilizing the NASA/GSFC tri-mode skin sensor

NASA Technical Reports Server (NTRS)

Prinz, F. B. S.; Mahalingam, S.

1992-01-01

A capacitance based proximity sensor, the 'Capaciflector' (Vranish 92), has been developed at the Goddard Space Flight Center of NASA. We had investigated the use of this sensor for avoiding and maneuvering around unexpected objects (Mahalingam 92). The approach developed there would help in executing collision-free gross motions. Another important aspect of robot motion planning is fine motion planning. Let us classify manipulator robot motion planning into two groups at the task level: gross motion planning and fine motion planning. We use the term 'gross planning' where the major degrees of freedom of the robot execute large motions, for example, the motion of a robot in a pick and place type operation. We use the term 'fine motion' to indicate motions of the robot where the large dofs do not move much, and move far less than the mirror dofs, such as in inserting a peg in a hole. In this report we describe our experiments and experiences in this area.

Commercial Motion Sensor Based Low-Cost and Convenient Interactive Treadmill.

PubMed

Kim, Jonghyun; Gravunder, Andrew; Park, Hyung-Soon

2015-09-17

Interactive treadmills were developed to improve the simulation of overground walking when compared to conventional treadmills. However, currently available interactive treadmills are expensive and inconvenient, which limits their use. We propose a low-cost and convenient version of the interactive treadmill that does not require expensive equipment and a complicated setup. As a substitute for high-cost sensors, such as motion capture systems, a low-cost motion sensor was used to recognize the subject's intention for speed changing. Moreover, the sensor enables the subject to make a convenient and safe stop using gesture recognition. For further cost reduction, the novel interactive treadmill was based on an inexpensive treadmill platform and a novel high-level speed control scheme was applied to maximize performance for simulating overground walking. Pilot tests with ten healthy subjects were conducted and results demonstrated that the proposed treadmill achieves similar performance to a typical, costly, interactive treadmill that contains a motion capture system and an instrumented treadmill, while providing a convenient and safe method for stopping.

A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors

PubMed Central

Mishra, Abhishek; Ghosh, Rohan; Principe, Jose C.; Thakor, Nitish V.; Kukreja, Sunil L.

2017-01-01

Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available. To address these limitations, in this paper we develop a technique for generalized motion segmentation based on spatial statistics across time frames. First, we create micromotion on the platform to facilitate the separation of static and dynamic elements of a scene, inspired by human saccadic eye movements. Second, we introduce the concept of spike-groups as a methodology to partition spatio-temporal event groups, which facilitates computation of scene statistics and characterize objects in it. Experimental results show that our algorithm is able to classify dynamic objects with a moving camera with maximum accuracy of 92%. PMID:28316563

Validation of enhanced kinect sensor based motion capturing for gait assessment

PubMed Central

Müller, Björn; Ilg, Winfried; Giese, Martin A.

2017-01-01

Optical motion capturing systems are expensive and require substantial dedicated space to be set up. On the other hand, they provide unsurpassed accuracy and reliability. In many situations however flexibility is required and the motion capturing system can only temporarily be placed. The Microsoft Kinect v2 sensor is comparatively cheap and with respect to gait analysis promising results have been published. We here present a motion capturing system that is easy to set up, flexible with respect to the sensor locations and delivers high accuracy in gait parameters comparable to a gold standard motion capturing system (VICON). Further, we demonstrate that sensor setups which track the person only from one-side are less accurate and should be replaced by two-sided setups. With respect to commonly analyzed gait parameters, especially step width, our system shows higher agreement with the VICON system than previous reports. PMID:28410413

Energy Optimization on the Battlefield: How Integrating Energy Efficient Technologies at the Tactical Level Can Reduce Fuel Consumption and Lessen the Burden of Fuel Logistics

DTIC Science & Technology

2014-06-13

a kill zone. This also created maintenance issues including diesel soot buildup in the vehicles exhaust systems. Since it took three to four days to...cost savings when summed over the thousands of light fixtures used on bases and FOBs. Changing to LEDs in tents and installing motion sensors could...CFL systems. Motion sensors also aided in turning lights off when the tents 78 are not occupied. Both LEDs and motion sensors produced significant

Miniature Biometric Sensor Project

NASA Technical Reports Server (NTRS)

Falker, John; Terrier, Douglas; Clayton, Ronald; Hanson, Andrea; Cooper, Tommy; Downs, Meghan; Flint, Stephanie; Reyna, Baraquiel; Simon, Cory; Wilt, Grier

2015-01-01

Heart rate monitoring (HRM) is a critical need during exploration missions. Unlike the four separate systems used on ISS today, the single HRM system should perform as a diagnostic tool, perform well during exercise or high level activity, and be suitable for use during EVA. Currently available HRM technologies are dependent on uninterrupted contact with the skin and are prone to data drop-out and motion artifact when worn in the spacesuit or during exercise. Here, we seek an alternative to the chest strap and electrode based sensors currently in use on ISS today. This project aims to develop a single, high performance, robust biosensor with focused efforts on improved heart rate data quality collection during high intensity activity such as exercise or EVA.

A robust vision-based sensor fusion approach for real-time pose estimation.

PubMed

Assa, Akbar; Janabi-Sharifi, Farrokh

2014-02-01

Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.

Model-Based Reinforcement of Kinect Depth Data for Human Motion Capture Applications

PubMed Central

Calderita, Luis Vicente; Bandera, Juan Pedro; Bustos, Pablo; Skiadopoulos, Andreas

2013-01-01

Motion capture systems have recently experienced a strong evolution. New cheap depth sensors and open source frameworks, such as OpenNI, allow for perceiving human motion on-line without using invasive systems. However, these proposals do not evaluate the validity of the obtained poses. This paper addresses this issue using a model-based pose generator to complement the OpenNI human tracker. The proposed system enforces kinematics constraints, eliminates odd poses and filters sensor noise, while learning the real dimensions of the performer's body. The system is composed by a PrimeSense sensor, an OpenNI tracker and a kinematics-based filter and has been extensively tested. Experiments show that the proposed system improves pure OpenNI results at a very low computational cost. PMID:23845933

EDITORIAL: Sensors and sensing systems

NASA Astrophysics Data System (ADS)

Dewhurst, Richard; Tian, Gui Yun

2008-02-01

Sensors are very important for measurement science and technology. They serve as a vital component in new measurement techniques and instrumentation systems. Key qualities of a good sensor system are high resolution, high reliability, low cost, appropriate output for a given input (good sensitivity), rapid response time, small random error in results, and small systematic error. Linearity is also useful, but with the advent of lookup tables and software, it is not as important as it used to be. In the last several years, considerable effort around the world has been devoted to a wide range of sensors from nanoscale sensors to sensor networks. Collectively, these vast and multidisciplinary efforts are developing important technological roadmaps to futuristic sensors with new modalities, significantly enhanced effectiveness and integrated functionality (data processing, computation, decision making and communications). When properly organized, they will have important relevance to life science and security applications, e.g. the sensing and monitoring of chemical, biological, radiological and explosive threats. A special feature in this issue takes a snapshot of some recent developments that were first presented at an international conference, the 2007 IEEE International Conference on Networking, Sensing and Control (ICNSC). The conference discussed recent developments, from which a few papers have since been brought together in this special feature. Gas sensing for environmental monitoring remains a topical subject, and two papers deal with this issue. One is concerned with the exploitation of nanostructured Au-doped cobalt oxyhydroxide-based carbon monoxide sensors for fire detection at its earlier stages (Zhuiykov and Dowling), whilst another examines the role of oxygen in high temperature hydrogen sulfide detection using MISiC sensors (Weng et al). Again for environmental monitoring, another paper deals with accurate sound source localization in a reverberant environment using multiple acoustic sensors (Atmoko et al). Not only is gaseous monitoring important, there are particular difficulties when it comes to the continuous monitoring of solids by non-destructive evaluation techniques. Examples of potential solutions for specialist applications are sensors for the detection and measurement of thin dielectric layers using reflection of frequency-scanned millimetre electromagnetic waves (Bowring et al), and an electrostatic sensor for velocity measurements of pneumatically conveyed solid particles (Xu et al). For potential medical applications, position measurement of internal organs is an on-going challenge. Tracking of internal organ motion with a six degree-of-freedom MEMS sensor is discussed by Bandala and Joyce. We hope that these papers provide an insight into exciting developments that continue to take place in the field of sensors and control.

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

PubMed Central

Al-Naji, Ali; Gibson, Kim; Lee, Sang-Heon; Chahl, Javaan

2017-01-01

The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications. PMID:28165382

The Multi-Parameter Wireless Sensing System (MPwise): Its Description and Application to Earthquake Risk Mitigation.

PubMed

Boxberger, Tobias; Fleming, Kevin; Pittore, Massimiliano; Parolai, Stefano; Pilz, Marco; Mikulla, Stefan

2017-10-20

The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the recorded ground motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation.

The Multi-Parameter Wireless Sensing System (MPwise): Its Description and Application to Earthquake Risk Mitigation

PubMed Central

Boxberger, Tobias; Fleming, Kevin; Pittore, Massimiliano; Parolai, Stefano; Pilz, Marco; Mikulla, Stefan

2017-01-01

The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the recorded ground motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation. PMID:29053608

Design and Implementation of Foot-Mounted Inertial Sensor Based Wearable Electronic Device for Game Play Application.

PubMed

Zhou, Qifan; Zhang, Hai; Lari, Zahra; Liu, Zhenbo; El-Sheimy, Naser

2016-10-21

Wearable electronic devices have experienced increasing development with the advances in the semiconductor industry and have received more attention during the last decades. This paper presents the development and implementation of a novel inertial sensor-based foot-mounted wearable electronic device for a brand new application: game playing. The main objective of the introduced system is to monitor and identify the human foot stepping direction in real time, and coordinate these motions to control the player operation in games. This proposed system extends the utilized field of currently available wearable devices and introduces a convenient and portable medium to perform exercise in a more compelling way in the near future. This paper provides an overview of the previously-developed system platforms, introduces the main idea behind this novel application, and describes the implemented human foot moving direction identification algorithm. Practical experiment results demonstrate that the proposed system is capable of recognizing five foot motions, jump, step left, step right, step forward, and step backward, and has achieved an over 97% accuracy performance for different users. The functionality of the system for real-time application has also been verified through the practical experiments.

Design and Implementation of Foot-Mounted Inertial Sensor Based Wearable Electronic Device for Game Play Application

PubMed Central

Zhou, Qifan; Zhang, Hai; Lari, Zahra; Liu, Zhenbo; El-Sheimy, Naser

2016-01-01

Wearable electronic devices have experienced increasing development with the advances in the semiconductor industry and have received more attention during the last decades. This paper presents the development and implementation of a novel inertial sensor-based foot-mounted wearable electronic device for a brand new application: game playing. The main objective of the introduced system is to monitor and identify the human foot stepping direction in real time, and coordinate these motions to control the player operation in games. This proposed system extends the utilized field of currently available wearable devices and introduces a convenient and portable medium to perform exercise in a more compelling way in the near future. This paper provides an overview of the previously-developed system platforms, introduces the main idea behind this novel application, and describes the implemented human foot moving direction identification algorithm. Practical experiment results demonstrate that the proposed system is capable of recognizing five foot motions, jump, step left, step right, step forward, and step backward, and has achieved an over 97% accuracy performance for different users. The functionality of the system for real-time application has also been verified through the practical experiments. PMID:27775673

The Large Ring Laser G for Continuous Earth Rotation Monitoring

NASA Astrophysics Data System (ADS)

Schreiber, K. U.; Klügel, T.; Velikoseltsev, A.; Schlüter, W.; Stedman, G. E.; Wells, J.-P. R.

2009-09-01

Ring Laser gyroscopes exploit the Sagnac effect and measure rotations absolute. They do not require an external reference frame and therefore provide an independent method to monitor Earth rotation. Large-scale versions of these gyroscopes promise to eventually provide a similar high resolution for the measurement of the variations in the Earth rotation rate as the established methods based on VLBI and GNSS. This would open the door to a continuous monitoring of LOD (Length of Day) and polar motion, which is not yet available today. Another advantage is the access to the sub-daily frequency regime of Earth rotation. The ring laser “G” (Grossring), located at the Geodetic Observatory Wettzell (Germany) is the most advanced realization of such a large gyroscope. This paper outlines the current sensor design and properties.

Disbonding effects on elastic wave generation and reception by bonded piezoelectric sensor systems

NASA Astrophysics Data System (ADS)

Blackshire, James L.; Martin, Steven A.; Na, Jeong K.

2007-04-01

Durable integrated sensor systems are needed for long-term health monitoring evaluations of aerospace systems. For legacy aircraft the primary means of implementing a sensor system will be through surface mounting or bonding of the sensors to the structure. Previous work has shown that the performance of surface-bonded piezo sensors can degrade due to environmental effects such as vibrations, temperature fluctuations, and substrate flexure motions. This performance degradation included sensor cracking, disbonding, and general loss of efficiency over time. In this research effort, the bonding state of a piezo sensor system was systematically studied to understand and improve the long-term durability and survivability of the sensor system. Analytic and computational models were developed and used to understand elastic wave generation and reception performance for various states of sensor disbond. Experimental studies were also conducted using scanning laser vibrometry, pitch-catch ultrasound, and pulse-echo ultrasound methods to understand elastic wave propagation effects in thin plate materials. Significant performance loss was observed for increasing levels of sensor disbond as well as characteristic frequency signatures which may be useful in understanding sensor performance levels for future structural health monitoring systems.

Use of the shape memory polymer polystyrene in the creation of thin film stretchable sensors for wearable applications

NASA Astrophysics Data System (ADS)

Van Volkinburg, Kyle R.; Nguyen, Thao; Pegan, Jonathan D.; Khine, Michelle; Washington, Gregory N.

2016-04-01

The shape memory polymer polystyrene (PS) has been used to create complex hierarchical wrinkling in the fabrication of stretchable thin film bimetallic sensors ideal for wearable based gesture monitoring applications. The film has been bonded to the elastomer polydimethylsiloxane (PDMS) and operates as a strain gauge under the general notion of geometric piezoresistivity. The film was subject to tensile, cyclic, and step loading conditions in order to characterize its dynamic behavior. To measure the joint angle of the metacarpophalangeal (MCP) joint on the right index finger, the sensor was adhered to a fitted golf glove above said joint and a motion study was conducted. At maximum joint angle the sensor experienced roughly 23.5% strain. From the study it was found that two simple curves, one while the finger was in flexion and the other while the finger was in extension, were able to predict the joint angle from measured voltage with an average error of 2.99 degrees.

Gait Recognition Using Wearable Motion Recording Sensors

NASA Astrophysics Data System (ADS)

Gafurov, Davrondzhon; Snekkenes, Einar

2009-12-01

This paper presents an alternative approach, where gait is collected by the sensors attached to the person's body. Such wearable sensors record motion (e.g. acceleration) of the body parts during walking. The recorded motion signals are then investigated for person recognition purposes. We analyzed acceleration signals from the foot, hip, pocket and arm. Applying various methods, the best EER obtained for foot-, pocket-, arm- and hip- based user authentication were 5%, 7%, 10% and 13%, respectively. Furthermore, we present the results of our analysis on security assessment of gait. Studying gait-based user authentication (in case of hip motion) under three attack scenarios, we revealed that a minimal effort mimicking does not help to improve the acceptance chances of impostors. However, impostors who know their closest person in the database or the genders of the users can be a threat to gait-based authentication. We also provide some new insights toward the uniqueness of gait in case of foot motion. In particular, we revealed the following: a sideway motion of the foot provides the most discrimination, compared to an up-down or forward-backward directions; and different segments of the gait cycle provide different level of discrimination.

Wearable Resistive Pressure Sensor Based on Highly Flexible Carbon Composite Conductors with Irregular Surface Morphology.

PubMed

Kim, Kang-Hyun; Hong, Soon Kyu; Jang, Nam-Su; Ha, Sung-Hun; Lee, Hyung Woo; Kim, Jong-Man

2017-05-24

Wearable pressure sensors are crucial building blocks for potential applications in real-time health monitoring, artificial electronic skins, and human-to-machine interfaces. Here we present a highly sensitive, simple-architectured wearable resistive pressure sensor based on highly compliant yet robust carbon composite conductors made of a vertically aligned carbon nanotube (VACNT) forest embedded in a polydimethylsiloxane (PDMS) matrix with irregular surface morphology. A roughened surface of the VACNT/PDMS composite conductor is simply formed using a sandblasted silicon master in a low-cost and potentially scalable manner and plays an important role in improving the sensitivity of resistive pressure sensor. After assembling two of the roughened composite conductors, our sensor shows considerable pressure sensitivity of ∼0.3 kPa -1 up to 0.7 kPa as well as stable steady-state responses under various pressures, a wide detectable range of up to 5 kPa before saturation, a relatively fast response time of ∼162 ms, and good reproducibility over 5000 cycles of pressure loading/unloading. The fabricated pressure sensor can be used to detect a wide range of human motions ranging from subtle blood pulses to dynamic joint movements, and it can also be used to map spatial pressure distribution in a multipixel platform (in a 4 × 4 pixel array).

Citizen Sensors for SHM: Use of Accelerometer Data from Smartphones

PubMed Central

Feng, Maria; Fukuda, Yoshio; Mizuta, Masato; Ozer, Ekin

2015-01-01

Ubiquitous smartphones have created a significant opportunity to form a low-cost wireless Citizen Sensor network and produce big data for monitoring structural integrity and safety under operational and extreme loads. Such data are particularly useful for rapid assessment of structural damage in a large urban setting after a major event such as an earthquake. This study explores the utilization of smartphone accelerometers for measuring structural vibration, from which structural health and post-event damage can be diagnosed. Widely available smartphones are tested under sinusoidal wave excitations with frequencies in the range relevant to civil engineering structures. Large-scale seismic shaking table tests, observing input ground motion and response of a structural model, are carried out to evaluate the accuracy of smartphone accelerometers under operational, white-noise and earthquake excitations of different intensity. Finally, the smartphone accelerometers are tested on a dynamically loaded bridge. The extensive experiments show satisfactory agreements between the reference and smartphone sensor measurements in both time and frequency domains, demonstrating the capability of the smartphone sensors to measure structural responses ranging from low-amplitude ambient vibration to high-amplitude seismic response. Encouraged by the results of this study, the authors are developing a citizen-engaging and data-analytics crowdsourcing platform towards a smartphone-based Citizen Sensor network for structural health monitoring and post-event damage assessment applications. PMID:25643056

Contrast based band selection for optimized weathered oil detection in hyperspectral images

NASA Astrophysics Data System (ADS)

Levaux, Florian; Bostater, Charles R., Jr.; Neyt, Xavier

2012-09-01

Hyperspectral imagery offers unique benefits for detection of land and water features due to the information contained in reflectance signatures such as the bi-directional reflectance distribution function or BRDF. The reflectance signature directly shows the relative absorption and backscattering features of targets. These features can be very useful in shoreline monitoring or surveillance applications, for example to detect weathered oil. In real-time detection applications, processing of hyperspectral data can be an important tool and Optimal band selection is thus important in real time applications in order to select the essential bands using the absorption and backscatter information. In the present paper, band selection is based upon the optimization of target detection using contrast algorithms. The common definition of the contrast (using only one band out of all possible combinations available within a hyperspectral image) is generalized in order to consider all the possible combinations of wavelength dependent contrasts using hyperspectral images. The inflection (defined here as an approximation of the second derivative) is also used in order to enhance the variations in the reflectance spectra as well as in the contrast spectrua in order to assist in optimal band selection. The results of the selection in term of target detection (false alarms and missed detection) are also compared with a previous method to perform feature detection, namely the matched filter. In this paper, imagery is acquired using a pushbroom hyperspectral sensor mounted at the bow of a small vessel. The sensor is mechanically rotated using an optical rotation stage. This opto-mechanical scanning system produces hyperspectral images with pixel sizes on the order of mm to cm scales, depending upon the distance between the sensor and the shoreline being monitored. The motion of the platform during the acquisition induces distortions in the collected HSI imagery. It is therefore necessary to apply a motion correction to the imagery. In this paper, imagery is corrected for the pitching motion of a vessel, which causes most of the deformation when the vessel is anchored at 2 points (bow and stern) during the acquisition of the hyperspectral imagry.

Novel approach to ambulatory assessment of human segmental orientation on a wearable sensor system.

PubMed

Liu, Kun; Liu, Tao; Shibata, Kyoko; Inoue, Yoshio; Zheng, Rencheng

2009-12-11

A new method using a double-sensor difference based algorithm for analyzing human segment rotational angles in two directions for segmental orientation analysis in the three-dimensional (3D) space was presented. A wearable sensor system based only on triaxial accelerometers was developed to obtain the pitch and yaw angles of thigh segment with an accelerometer approximating translational acceleration of the hip joint and two accelerometers measuring the actual accelerations on the thigh. To evaluate the method, the system was first tested on a 2 degrees of freedom mechanical arm assembled out of rigid segments and encoders. Then, to estimate the human segmental orientation, the wearable sensor system was tested on the thighs of eight volunteer subjects, who walked in a straight forward line in the work space of an optical motion analysis system at three self-selected speeds: slow, normal and fast. In the experiment, the subject was assumed to walk in a straight forward way with very little trunk sway, skin artifacts and no significant internal/external rotation of the leg. The root mean square (RMS) errors of the thigh segment orientation measurement were between 2.4 degrees and 4.9 degrees during normal gait that had a 45 degrees flexion/extension range of motion. Measurement error was observed to increase with increasing walking speed probably because of the result of increased trunk sway, axial rotation and skin artifacts. The results show that, without integration and switching between different sensors, using only one kind of sensor, the wearable sensor system is suitable for ambulatory analysis of normal gait orientation of thigh and shank in two directions of the segment-fixed local coordinate system in 3D space. It can then be applied to assess spatio-temporal gait parameters and monitoring the gait function of patients in clinical settings.

An Earthquake Shake Map Routine with Low Cost Accelerometers: Preliminary Results

NASA Astrophysics Data System (ADS)

Alcik, H. A.; Tanircan, G.; Kaya, Y.

2015-12-01

Vast amounts of high quality strong motion data are indispensable inputs of the analyses in the field of geotechnical and earthquake engineering however, high cost of installation of the strong motion systems constitutes the biggest obstacle for worldwide dissemination. In recent years, MEMS based (micro-electro-mechanical systems) accelerometers have been used in seismological research-oriented studies as well as earthquake engineering oriented projects basically due to precision obtained in downsized instruments. In this research our primary goal is to ensure the usage of these low-cost instruments in the creation of shake-maps immediately after a strong earthquake. Second goal is to develop software that will automatically process the real-time data coming from the rapid response network and create shake-map. For those purposes, four MEMS sensors have been set up to deliver real-time data. Data transmission is done through 3G modems. A subroutine was coded in assembler language and embedded into the operating system of each instrument to create MiniSEED files with packages of 1-second instead of 512-byte packages.The Matlab-based software calculates the strong motion (SM) parameters at every second, and they are compared with the user-defined thresholds. A voting system embedded in the software captures the event if the total vote exceeds the threshold. The user interface of the software enables users to monitor the calculated SM parameters either in a table or in a graph (Figure 1). A small scale and affordable rapid response network is created using four MEMS sensors, and the functionality of the software has been tested and validated using shake table tests. The entire system is tested together with a reference sensor under real strong ground motion recordings as well as series of sine waves with varying amplitude and frequency. The successful realization of this software allowed us to set up a test network at Tekirdağ Province, the closest coastal point to the moderate size earthquake activities in the Marmara Sea, Turkey.

Use of Finite Elements Analysis for a Weigh-in-Motion Sensor Design

PubMed Central

Opitz, Rigobert; Goanta, Viorel; Carlescu, Petru; Barsanescu, Paul-Doru; Taranu, Nicolae; Banu, Oana

2012-01-01

High speed weigh-in-motion (WIM) sensors are utilized as components of complex traffic monitoring and measurement systems. They should be able to determine the weights on wheels, axles and vehicle gross weights, and to help the classification of vehicles (depending on the number of axles). WIM sensors must meet the following main requirements: good accuracy, high endurance, low price and easy installation in the road structure. It is not advisable to use cheap materials in constructing these devices for lower prices, since the sensors are normally working in harsh environmental conditions such as temperatures between −40 °C and +70 °C, dust, temporary water immersion, shocks and vibrations. Consequently, less expensive manufacturing technologies are recommended. Because the installation cost in the road structure is high and proportional to the WIM sensor cross section (especially with its thickness), the device needs to be made as flat as possible. The WIM sensor model presented and analyzed in this paper uses a spring element equipped with strain gages. Using Finite Element Analysis (FEA), the authors have attempted to obtain a more sensitive, reliable, lower profile and overall cheaper elastic element for a new WIM sensor. PMID:22969332

The network of photodetectors and diode lasers of the CMS Link alignment system

NASA Astrophysics Data System (ADS)

Arce, P.; Barcala, J. M.; Calvo, E.; Ferrando, A.; Josa, M. I.; Molinero, A.; Navarrete, J.; Oller, J. C.; Brochero, J.; Calderón, A.; Fernández, M. G.; Gómez, G.; González-Sánchez, F. J.; Martínez-Rivero, C.; Matorras, F.; Rodrigo, T.; Ruiz-Árbol, P.; Scodellaro, L.; Sobrón, M.; Vila, I.; Virto, A. L.; Fernández, J.; Raics, P.; Szabó, Zs.; Trócsnyi, Z.; Ujvári, B.; Zilizi, Gy.; Béni, N.; Christian, G.; Imrek, J.; Molnar, J.; Novak, D.; Pálinkás, J.; Székely, G.; Szillási, Z.; Bencze, G. L.; Vestergombi, G.; Benettoni, M.; Gasparini, F.; Montecassiano, F.; Rampazzo, M.; Zago, M.; Benvenuti, A.; Reithler, H.; Jiang, C.

2018-07-01

The central feature of the CMS Link alignment system is a network of Amorphous Silicon Position Detectors distributed throughout the muon spectrometer that are connected by multiple laser lines. The data collected during the years from 2008 to 2015 is presented confirming an outstanding performance of the photo sensors during more than seven years of operation. Details of the photo sensor readout of the laser signals are presented. The mechanical motions of the CMS detector are monitored using these photosensors and good agreement with distance sensors is obtained.

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements.

PubMed

Tannous, Halim; Istrate, Dan; Benlarbi-Delai, Aziz; Sarrazin, Julien; Gamet, Didier; Ho Ba Tho, Marie Christine; Dao, Tien Tuan

2016-11-15

Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject's movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

Validation of cardiac accelerometer sensor measurements.

PubMed

Remme, Espen W; Hoff, Lars; Halvorsen, Per Steinar; Naerum, Edvard; Skulstad, Helge; Fleischer, Lars A; Elle, Ole Jakob; Fosse, Erik

2009-12-01

In this study we have investigated the accuracy of an accelerometer sensor designed for the measurement of cardiac motion and automatic detection of motion abnormalities caused by myocardial ischaemia. The accelerometer, attached to the left ventricular wall, changed its orientation relative to the direction of gravity during the cardiac cycle. This caused a varying gravity component in the measured acceleration signal that introduced an error in the calculation of myocardial motion. Circumferential displacement, velocity and rotation of the left ventricular apical region were calculated from the measured acceleration signal. We developed a mathematical method to separate translational and gravitational acceleration components based on a priori assumptions of myocardial motion. The accuracy of the measured motion was investigated by comparison with known motion of a robot arm programmed to move like the heart wall. The accuracy was also investigated in an animal study. The sensor measurements were compared with simultaneously recorded motion from a robot arm attached next to the sensor on the heart and with measured motion by echocardiography and a video camera. The developed compensation method for the varying gravity component improved the accuracy of the calculated velocity and displacement traces, giving very good agreement with the reference methods.

A strong and flexible electronic vessel for real-time monitoring of temperature, motions and flow.

PubMed

Zhang, Wei; Hou, Chengyi; Li, Yaogang; Zhang, Qinghong; Wang, Hongzhi

2017-11-23

Flexible and multifunctional sensors that continuously detect physical information are urgently required to fabricate wearable materials for health monitoring. This study describes the fabrication and performance of a strong and flexible vessel-like sensor. This electronic vessel consists of a self-supported braided cotton hose substrate, single-walled carbon nanotubes (SWCNTs)/ZnO@polyvinylidene fluoride (PVDF) function arrays and a flexible PVDF function fibrous membrane, and it possesses high mechanical property and accurate physical sensing. The rationally designed tubular structure facilities the detection of the applied temperature and strain and the frequency, pressure, and temperature of pulsed fluids. Therefore, the flexible electronic vessel holds promising potential for applications in wearable or implantable materials for the monitoring of health.

An ultra-low power (ULP) bandage-type ECG sensor for efficient cardiac disease management.

PubMed

Shin, Kunsoo; Park, G G; Kim, J P; Lee, T H; Ko, B H; Kim, Y H

2013-01-01

This paper proposed an ultra-low power bandage-type ECG sensor (the size: 76 × 34 × 3 (mm(3)) and the power consumption: 1 mW) which allows for a continuous and real-time monitoring of a user's ECG signals over 24h during daily activities. For its compact size and lower power consumption, we designed the analog front-end, the SRP (Samsung Reconfigurable Processor) based DSP of 30 uW/MHz, and the ULP wireless RF of 1 nJ/bit. Also, to tackle motion artifacts(MA), a MA monitoring technique based on the HCP (Half-cell Potential) is proposed which resulted in the high correlation between the MA and the HCP, the correlation coefficient of 0.75 ± 0.18. To assess its feasibility and validity as a wearable health monitor, we performed the comparison of two ECG signals recorded form it and a conventional Holter device. As a result, the performance of the former is a little lower as compared with the latter, although showing no statistical significant difference (the quality of the signal: 94.3% vs 99.4%; the accuracy of arrhythmia detection: 93.7% vs 98.7%). With those results, it has been confirmed that it can be used as a wearable health monitor due to its comfortability, its long operation lifetime and the good quality of the measured ECG signal.

Development of Gravity Acceleration Measurement Using Simple Harmonic Motion Pendulum Method Based on Digital Technology and Photogate Sensor

NASA Astrophysics Data System (ADS)

Yulkifli; Afandi, Zurian; Yohandri

2018-04-01

Development of gravitation acceleration measurement using simple harmonic motion pendulum method, digital technology and photogate sensor has been done. Digital technology is more practical and optimizes the time of experimentation. The pendulum method is a method of calculating the acceleration of gravity using a solid ball that connected to a rope attached to a stative pole. The pendulum is swung at a small angle resulted a simple harmonic motion. The measurement system consists of a power supply, Photogate sensors, Arduino pro mini and seven segments. The Arduino pro mini receives digital data from the photogate sensor and processes the digital data into the timing data of the pendulum oscillation. The calculation result of the pendulum oscillation time is displayed on seven segments. Based on measured data, the accuracy and precision of the experiment system are 98.76% and 99.81%, respectively. Based on experiment data, the system can be operated in physics experiment especially in determination of the gravity acceleration.

A Self-Alignment Algorithm for SINS Based on Gravitational Apparent Motion and Sensor Data Denoising

PubMed Central

Liu, Yiting; Xu, Xiaosu; Liu, Xixiang; Yao, Yiqing; Wu, Liang; Sun, Jin

2015-01-01

Initial alignment is always a key topic and difficult to achieve in an inertial navigation system (INS). In this paper a novel self-initial alignment algorithm is proposed using gravitational apparent motion vectors at three different moments and vector-operation. Simulation and analysis showed that this method easily suffers from the random noise contained in accelerometer measurements which are used to construct apparent motion directly. Aiming to resolve this problem, an online sensor data denoising method based on a Kalman filter is proposed and a novel reconstruction method for apparent motion is designed to avoid the collinearity among vectors participating in the alignment solution. Simulation, turntable tests and vehicle tests indicate that the proposed alignment algorithm can fulfill initial alignment of strapdown INS (SINS) under both static and swinging conditions. The accuracy can either reach or approach the theoretical values determined by sensor precision under static or swinging conditions. PMID:25923932

Senior residents' perceived need of and preferences for "smart home" sensor technologies.

PubMed

Demiris, George; Hensel, Brian K; Skubic, Marjorie; Rantz, Marilyn

2008-01-01

The goal of meeting the desire of older adults to remain independent in their home setting while controlling healthcare costs has led to the conceptualization of "smart homes." A smart home is a residence equipped with technology that enhances safety of residents and monitors their health conditions. The study aim is to assess older adults' perceptions of specific smart home technologies (i.e., a bed sensor, gait monitor, stove sensor, motion sensor, and video sensor). The study setting is TigerPlace, a retirement community designed according to the Aging in Place model. Focus group sessions with fourteen residents were conducted to assess perceived advantages and concerns associated with specific applications, and preferences for recipients of sensor-generated information pertaining to residents' activity levels, sleep patterns and potential emergencies. Sessions were audio-taped; tapes were transcribed, and a content analysis was performed. A total of fourteen older adults over the age of 65 participated in three focus group sessions Most applications were perceived as useful, and participants would agree to their installation in their own home. Preference for specific sensors related to sensors' appearance and residents' own level of frailty and perceived need. Specific concerns about privacy were raised. The findings indicate an overall positive attitude toward sensor technologies for nonobtrusive monitoring. Researchers and practitioners are called upon to address ethical and technical challenges in this emerging domain.

Virtual Sensors for Advanced Controllers in Rehabilitation Robotics.

PubMed

Mancisidor, Aitziber; Zubizarreta, Asier; Cabanes, Itziar; Portillo, Eva; Jung, Je Hyung

2018-03-05

In order to properly control rehabilitation robotic devices, the measurement of interaction force and motion between patient and robot is an essential part. Usually, however, this is a complex task that requires the use of accurate sensors which increase the cost and the complexity of the robotic device. In this work, we address the development of virtual sensors that can be used as an alternative of actual force and motion sensors for the Universal Haptic Pantograph (UHP) rehabilitation robot for upper limbs training. These virtual sensors estimate the force and motion at the contact point where the patient interacts with the robot using the mathematical model of the robotic device and measurement through low cost position sensors. To demonstrate the performance of the proposed virtual sensors, they have been implemented in an advanced position/force controller of the UHP rehabilitation robot and experimentally evaluated. The experimental results reveal that the controller based on the virtual sensors has similar performance to the one using direct measurement (less than 0.005 m and 1.5 N difference in mean error). Hence, the developed virtual sensors to estimate interaction force and motion can be adopted to replace actual precise but normally high-priced sensors which are fundamental components for advanced control of rehabilitation robotic devices.

Feasibility testing of a home-based sensor system to monitor mobility and daily activities in Korean American older adults.

PubMed

Chung, Jane; Demiris, George; Thompson, Hilaire J; Chen, Ke-Yu; Burr, Robert; Patel, Shwetak; Fogarty, James

2017-03-01

This study aimed to test feasibility of a home-based sensor system that is designed to assess mobility and daily activity patterns among Korean American older adults (KAOAs; n = 6) and explore sensor technology acceptance among participants. Home-based sensors have the potential to support older adults' desire to remain at home as long as possible. Despite a growing interest in using home-based sensors for older adults, there have been no documented attempts to apply this type of technology to a group of ethnic minority older adults. The study employed descriptive, quantitative and qualitative approaches. The system was deployed for 2 months in four homes of KAOAs. Study procedures included (i) sensor-based data collection, (ii) self-report mobility instruments, (iii) activity logs and (iv) interviews. To explore changes in activity patterns, line graphs and sequence plots were applied to data obtained from a set of sensors. General linear models (GLMs) were used for motion in each space of the home to examine how much variability of activities is explained by several time variables. Sensor data had natural fluctuation over time. Different 24-hr patterns were observed across homes. The GLM estimates showed that effect sizes of the time variables vary across individuals. A hydro sensor deployed in one participant's bathroom inferred various water usage activities. Overall, sensors were acceptable for all participants, despite some privacy concerns. Study findings demonstrate that sensor technology applications could be successfully used longitudinally in a minority population of older adults that is not often targeted as an end-user group for the use of innovative technologies. The use of home-based sensors provides nurses with a useful tool to detect deviations from normal patterns and to achieve proactive care for some groups of older adults. © 2016 John Wiley & Sons Ltd.

FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision

PubMed Central

Botella, Guillermo; Martín H., José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms. PMID:22164069

FPGA-based multimodal embedded sensor system integrating low- and mid-level vision.

PubMed

Botella, Guillermo; Martín H, José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms.

Study on robot motion control for intelligent welding processes based on the laser tracking sensor

NASA Astrophysics Data System (ADS)

Zhang, Bin; Wang, Qian; Tang, Chen; Wang, Ju

2017-06-01

A robot motion control method is presented for intelligent welding processes of complex spatial free-form curve seams based on the laser tracking sensor. First, calculate the tip position of the welding torch according to the velocity of the torch and the seam trajectory detected by the sensor. Then, search the optimal pose of the torch under constraints using genetic algorithms. As a result, the intersection point of the weld seam and the laser plane of the sensor is within the detectable range of the sensor. Meanwhile, the angle between the axis of the welding torch and the tangent of the weld seam meets the requirements. The feasibility of the control method is proved by simulation.

Intelligent artifact classification for ambulatory physiological signals.

PubMed

Sweeney, Kevin T; Leamy, Darren J; Ward, Tomas E; McLoone, Sean

2010-01-01

Connected health represents an increasingly important model for health-care delivery. The concept is heavily reliant on technology and in particular remote physiological monitoring. One of the principal challenges is the maintenance of high quality data streams which must be collected with minimally intrusive, inexpensive sensor systems operating in difficult conditions. Ambulatory monitoring represents one of the most challenging signal acquisition challenges of all in that data is collected as the patient engages in normal activities of everyday living. Data thus collected suffers from considerable corruption as a result of artifact, much of it induced by motion and this has a bearing on its utility for diagnostic purposes. We propose a model for ambulatory signal recording in which the data collected is accompanied by labeling indicating the quality of the collected signal. As motion is such an important source of artifact we demonstrate the concept in this case with a quality of signal measure derived from motion sensing technology viz. accelerometers. We further demonstrate how different types of artifact might be tagged to inform artifact reduction signal processing elements during subsequent signal analysis. This is demonstrated through the use of multiple accelerometers which allow the algorithm to distinguish between disturbance of the sensor relative to the underlying tissue and movement of this tissue. A brain monitoring experiment utilizing EEG and fNIRS is used to illustrate the concept.

The Vestibular System and Human Dynamic Space Orientation

NASA Technical Reports Server (NTRS)

Meiry, J. L.

1966-01-01

The motion sensors of the vestibular system are studied to determine their role in human dynamic space orientation and manual vehicle control. The investigation yielded control models for the sensors, descriptions of the subsystems for eye stabilization, and demonstrations of the effects of motion cues on closed loop manual control. Experiments on the abilities of subjects to perceive a variety of linear motions provided data on the dynamic characteristics of the otoliths, the linear motion sensors. Angular acceleration threshold measurements supplemented knowledge of the semicircular canals, the angular motion sensors. Mathematical models are presented to describe the known control characteristics of the vestibular sensors, relating subjective perception of motion to objective motion of a vehicle. The vestibular system, the neck rotation proprioceptors and the visual system form part of the control system which maintains the eye stationary relative to a target or a reference. The contribution of each of these systems was identified through experiments involving head and body rotations about a vertical axis. Compensatory eye movements in response to neck rotation were demonstrated and their dynamic characteristics described by a lag-lead model. The eye motions attributable to neck rotations and vestibular stimulation obey superposition when both systems are active. Human operator compensatory tracking is investigated in simple vehicle orientation control system with stable and unstable controlled elements. Control of vehicle orientation to a reference is simulated in three modes: visual, motion and combined. Motion cues sensed by the vestibular system through tactile sensation enable the operator to generate more lead compensation than in fixed base simulation with only visual input. The tracking performance of the human in an unstable control system near the limits of controllability is shown to depend heavily upon the rate information provided by the vestibular sensors.

Wearable multifunctional sensors using printed stretchable conductors made of silver nanowires

NASA Astrophysics Data System (ADS)

Yao, Shanshan; Zhu, Yong

2014-01-01

Considerable efforts have been made to achieve highly sensitive and wearable sensors that can simultaneously detect multiple stimuli such as stretch, pressure, temperature or touch. Here we develop highly stretchable multifunctional sensors that can detect strain (up to 50%), pressure (up to ~1.2 MPa) and finger touch with high sensitivity, fast response time (~40 ms) and good pressure mapping function. The reported sensors utilize the capacitive sensing mechanism, where silver nanowires are used as electrodes (conductors) and Ecoflex is used as a dielectric. The silver nanowire electrodes are screen printed. Our sensors have been demonstrated for several wearable applications including monitoring thumb movement, sensing the strain of the knee joint in patellar reflex (knee-jerk) and other human motions such as walking, running and jumping from squatting, illustrating the potential utilities of such sensors in robotic systems, prosthetics, healthcare and flexible touch panels.Considerable efforts have been made to achieve highly sensitive and wearable sensors that can simultaneously detect multiple stimuli such as stretch, pressure, temperature or touch. Here we develop highly stretchable multifunctional sensors that can detect strain (up to 50%), pressure (up to ~1.2 MPa) and finger touch with high sensitivity, fast response time (~40 ms) and good pressure mapping function. The reported sensors utilize the capacitive sensing mechanism, where silver nanowires are used as electrodes (conductors) and Ecoflex is used as a dielectric. The silver nanowire electrodes are screen printed. Our sensors have been demonstrated for several wearable applications including monitoring thumb movement, sensing the strain of the knee joint in patellar reflex (knee-jerk) and other human motions such as walking, running and jumping from squatting, illustrating the potential utilities of such sensors in robotic systems, prosthetics, healthcare and flexible touch panels. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr05496a

Two terminal micropower radar sensor

DOEpatents

McEwan, Thomas E.

1995-01-01

A simple, low power ultra-wideband radar motion sensor/switch configuration connects a power source and load to ground. The switch is connected to and controlled by the signal output of a radar motion sensor. The power input of the motion sensor is connected to the load through a diode which conducts power to the motion sensor when the switch is open. A storage capacitor or rechargeable battery is connected to the power input of the motion sensor. The storage capacitor or battery is charged when the switch is open and powers the motion sensor when the switch is closed. The motion sensor and switch are connected between the same two terminals between the source/load and ground.

Two terminal micropower radar sensor

DOEpatents

McEwan, T.E.

1995-11-07

A simple, low power ultra-wideband radar motion sensor/switch configuration connects a power source and load to ground. The switch is connected to and controlled by the signal output of a radar motion sensor. The power input of the motion sensor is connected to the load through a diode which conducts power to the motion sensor when the switch is open. A storage capacitor or rechargeable battery is connected to the power input of the motion sensor. The storage capacitor or battery is charged when the switch is open and powers the motion sensor when the switch is closed. The motion sensor and switch are connected between the same two terminals between the source/load and ground. 3 figs.

An error-based micro-sensor capture system for real-time motion estimation

NASA Astrophysics Data System (ADS)

Yang, Lin; Ye, Shiwei; Wang, Zhibo; Huang, Zhipei; Wu, Jiankang; Kong, Yongmei; Zhang, Li

2017-10-01

A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities. In the proposed filter algorithm, the gyroscope bias error, orientation error and magnetic disturbance error are estimated and compensated, significantly reducing the orientation estimation error due to sensor noise and drift. Displacement estimation, especially for activities such as jumping, has been the challenge in micro-sensor motion capture. An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities. The performance of this system is benchmarked with respect to the results of VICON optical capture system. The experimental results have demonstrated effectiveness of the system in daily activities tracking, with estimation error 0.16 ± 0.06 m for normal walking and 0.13 ± 0.11 m for jumping motions. Research supported by the National Natural Science Foundation of China (Nos. 61431017, 81272166).

Literature review on monitoring technologies and their outcomes in independently living elderly people.

PubMed

Peetoom, Kirsten K B; Lexis, Monique A S; Joore, Manuela; Dirksen, Carmen D; De Witte, Luc P

2015-07-01

To obtain insight into what kind of monitoring technologies exist to monitor activity in-home, what the characteristics and aims of applying these technologies are, what kind of research has been conducted on their effects and what kind of outcomes are reported. A systematic document search was conducted within the scientific databases Pubmed, Embase, Cochrane, PsycINFO and Cinahl, complemented by Google Scholar. Documents were included in this review if they reported on monitoring technologies that detect activities of daily living (ADL) or significant events, e.g. falls, of elderly people in-home, with the aim of prolonging independent living. Five main types of monitoring technologies were identified: PIR motion sensors, body-worn sensors, pressure sensors, video monitoring and sound recognition. In addition, multicomponent technologies and smart home technologies were identified. Research into the use of monitoring technologies is widespread, but in its infancy, consisting mainly of small-scale studies and including few longitudinal studies. Monitoring technology is a promising field, with applications to the long-term care of elderly persons. However, monitoring technologies have to be brought to the next level, with longitudinal studies that evaluate their (cost-) effectiveness to demonstrate the potential to prolong independent living of elderly persons. [Box: see text].

Monitoring Human Performance During Suited Operations: A Technology Feasibility Study Using EMU Gloves

NASA Technical Reports Server (NTRS)

Bekdash, Omar; Norcross, Jason; McFarland, Shane

2015-01-01

Mobility tracking of human subjects while conducting suited operations still remains focused on the external movement of the suit and little is known about the human movement within it. For this study, accelerometers and bend sensitive resistors were integrated into a custom carrier glove to quantify range of motion and dexterity from within the pressurized glove environment as a first stage feasibility study of sensor hardware, integration, and reporting capabilities. Sensors were also placed on the exterior of the pressurized glove to determine if it was possible to compare a glove joint angle to the anatomical joint angle of the subject during tasks. Quantifying human movement within the suit was feasible, with accelerometers clearly detecting movements in the wrist and reporting expected joint angles at maximum flexion or extension postures with repeatability of plus or minus 5 degrees between trials. Bend sensors placed on the proximal interphalangeal and distal interphalangeal joints performed less well. It was not possible to accurately determine the actual joint angle using these bend sensors, but these sensors could be used to determine when the joint was flexed to its maximum and provide a general range of mobility needed to complete a task. Further work includes additional testing with accelerometers and the possible inclusion of hardware such as magnetometers or gyroscopes to more precisely locate the joint in 3D space. We hope to eventually expand beyond the hand and glove and develop a more comprehensive suit sensor suite to characterize motion across more joints (knee, elbow, shoulder, etc.) and fully monitor the human body operating within the suit environment.

Sensing of minute airflow motions near walls using pappus-type nature-inspired sensors

PubMed Central

Mikulich, Vladimir

2017-01-01

This work describes the development and use of pappus-like structures as sensitive sensors to detect minute air-flow motions. We made such sensors from pappi taken from nature-grown seed, whose filiform hairs’ length-scale is suitable for the study of large-scale turbulent convection flows. The stem with the pappus on top is fixated on an elastic membrane on the wall and tilts under wind-load proportional to the velocity magnitude in direction of the wind, similar as the biological sensory hairs found in spiders, however herein the sensory hair has multiple filiform protrusions at the tip. As the sensor response is proportional to the drag on the tip and a low mass ensures a larger bandwidth, lightweight pappus structures similar as those found in nature with documented large drag are useful to improve the response of artificial sensors. The pappus of a Dandelion represents such a structure which has evolved to maximize wind-driven dispersion, therefore it is used herein as the head of our sensor. Because of its multiple hairs arranged radially around the stem it generates uniform drag for all wind directions. While still being permeable to the flow, the hundreds of individual hairs on the tip of the sensor head maximize the drag and minimize influence of pressure gradients or shear-induced lift forces on the sensor response as they occur in non-permeable protrusions. In addition, the flow disturbance by the sensor itself is limited. The optical recording of the head-motion allows continuously remote-distance monitoring of the flow fluctuations in direction and magnitude. Application is shown for the measurement of a reference flow under isothermal conditions to detect the early occurrence of instabilities. PMID:28658272

Clinically acceptable agreement between the ViMove wireless motion sensor system and the Vicon motion capture system when measuring lumbar region inclination motion in the sagittal and coronal planes.

PubMed

Mjøsund, Hanne Leirbekk; Boyle, Eleanor; Kjaer, Per; Mieritz, Rune Mygind; Skallgård, Tue; Kent, Peter

2017-03-21

Wireless, wearable, inertial motion sensor technology introduces new possibilities for monitoring spinal motion and pain in people during their daily activities of work, rest and play. There are many types of these wireless devices currently available but the precision in measurement and the magnitude of measurement error from such devices is often unknown. This study investigated the concurrent validity of one inertial motion sensor system (ViMove) for its ability to measure lumbar inclination motion, compared with the Vicon motion capture system. To mimic the variability of movement patterns in a clinical population, a sample of 34 people were included - 18 with low back pain and 16 without low back pain. ViMove sensors were attached to each participant's skin at spinal levels T12 and S2, and Vicon surface markers were attached to the ViMove sensors. Three repetitions of end-range flexion inclination, extension inclination and lateral flexion inclination to both sides while standing were measured by both systems concurrently with short rest periods in between. Measurement agreement through the whole movement range was analysed using a multilevel mixed-effects regression model to calculate the root mean squared errors and the limits of agreement were calculated using the Bland Altman method. We calculated root mean squared errors (standard deviation) of 1.82° (±1.00°) in flexion inclination, 0.71° (±0.34°) in extension inclination, 0.77° (±0.24°) in right lateral flexion inclination and 0.98° (±0.69°) in left lateral flexion inclination. 95% limits of agreement ranged between -3.86° and 4.69° in flexion inclination, -2.15° and 1.91° in extension inclination, -2.37° and 2.05° in right lateral flexion inclination and -3.11° and 2.96° in left lateral flexion inclination. We found a clinically acceptable level of agreement between these two methods for measuring standing lumbar inclination motion in these two cardinal movement planes. Further research should investigate the ViMove system's ability to measure lumbar motion in more complex 3D functional movements and to measure changes of movement patterns related to treatment effects.

Improvements of Real Time First Motion Focal Mechanism and Noise Characteristics of New Sites at the Puerto Rico Seismic Network

NASA Astrophysics Data System (ADS)

Williams, D. M.; Lopez, A. M.; Huerfano, V.; Lugo, J.; Cancel, J.

2011-12-01

Seismic networks need quick and efficient ways to obtain information related to seismic events for the purposes of seismic activity monitoring, risk assessment, and scientific knowledge among others. As part of an IRIS summer internship program, two projects were performed to provide a tool for quick faulting mechanism and improve seismic data at the Puerto Rico Seismic Network (PRSN). First, a simple routine to obtain a focal mechanisms, the geometry of the fault, based on first motions was developed and implemented for data analysts routine operations at PRSN. The new tool provides the analyst a quick way to assess the probable faulting mechanism that occurred while performing the interactive earthquake location procedure. The focal mechanism is generated on-the-fly when data analysts pick P wave arrivals onsets and motions. Once first motions have been identified, an in-house PRSN utility is employed to obtain the double couple representation and later plotted using GMT's psmeca utility. Second, we addressed the issue of seismic noise related to thermal fluctuations inside seismic vaults. Seismic sites can be extremely noisy due to proximity to cultural activities and unattended thermal fluctuations inside sensor housings, thus resulting in skewed readings. In the past, seismologists have used different insulation techniques to reduce the amount of unwanted noise that a seismometers experience due to these thermal changes with items such as Styrofoam, and fiber glass among others. PRSN traditionally uses Styrofoam boxes to cover their seismic sensors, however, a proper procedure to test how these method compare to other new techniques has never been approached. The deficiency of properly testing these techniques in the Caribbean and especially Puerto Rico is that these thermal fluctuations still happen because of the intense sun and humidity. We conducted a test based on the methods employed by the IRIS Transportable Array, based on insulation by sand burial of the sensor. Two Guralps CMG-3T's connected to RefTek's 150 digitizers were used at PRSN's MPR site seismic vault to compare the two types of insulation. Two temperature loggers were placed along each seismic sensor for a period of one week to observe how much thermal fluctuations occur in each insulation method and then compared its capability for noise reduction due to thermal fluctuations. With only a single degree Celsius fluctuation inside the sand (compared to almost twice that value for the foam) the sensor buried in sand provided the best insulation for the seismic vault. In addition, the quality of the data was analyzed by comparing both sensors using PQLX. We show results of this analysis and also provide a site characteristic of new stations to be included in the daily earthquake location operations at the PRSN.

Multisensory visual servoing by a neural network.

PubMed

Wei, G Q; Hirzinger, G

1999-01-01

Conventional computer vision methods for determining a robot's end-effector motion based on sensory data needs sensor calibration (e.g., camera calibration) and sensor-to-hand calibration (e.g., hand-eye calibration). This involves many computations and even some difficulties, especially when different kinds of sensors are involved. In this correspondence, we present a neural network approach to the motion determination problem without any calibration. Two kinds of sensory data, namely, camera images and laser range data, are used as the input to a multilayer feedforward network to associate the direct transformation from the sensory data to the required motions. This provides a practical sensor fusion method. Using a recursive motion strategy and in terms of a network correction, we relax the requirement for the exactness of the learned transformation. Another important feature of our work is that the goal position can be changed without having to do network retraining. Experimental results show the effectiveness of our method.

PhysioDroid: Combining Wearable Health Sensors and Mobile Devices for a Ubiquitous, Continuous, and Personal Monitoring

PubMed Central

Villalonga, Claudia; Damas, Miguel

2014-01-01

Technological advances on the development of mobile devices, medical sensors, and wireless communication systems support a new generation of unobtrusive, portable, and ubiquitous health monitoring systems for continuous patient assessment and more personalized health care. There exist a growing number of mobile apps in the health domain; however, little contribution has been specifically provided, so far, to operate this kind of apps with wearable physiological sensors. The PhysioDroid, presented in this paper, provides a personalized means to remotely monitor and evaluate users' conditions. The PhysioDroid system provides ubiquitous and continuous vital signs analysis, such as electrocardiogram, heart rate, respiration rate, skin temperature, and body motion, intended to help empower patients and improve clinical understanding. The PhysioDroid is composed of a wearable monitoring device and an Android app providing gathering, storage, and processing features for the physiological sensor data. The versatility of the developed app allows its use for both average users and specialists, and the reduced cost of the PhysioDroid puts it at the reach of most people. Two exemplary use cases for health assessment and sports training are presented to illustrate the capabilities of the PhysioDroid. Next technical steps include generalization to other mobile platforms and health monitoring devices. PMID:25295301

PhysioDroid: combining wearable health sensors and mobile devices for a ubiquitous, continuous, and personal monitoring.

PubMed

Banos, Oresti; Villalonga, Claudia; Damas, Miguel; Gloesekoetter, Peter; Pomares, Hector; Rojas, Ignacio

2014-01-01

Technological advances on the development of mobile devices, medical sensors, and wireless communication systems support a new generation of unobtrusive, portable, and ubiquitous health monitoring systems for continuous patient assessment and more personalized health care. There exist a growing number of mobile apps in the health domain; however, little contribution has been specifically provided, so far, to operate this kind of apps with wearable physiological sensors. The PhysioDroid, presented in this paper, provides a personalized means to remotely monitor and evaluate users' conditions. The PhysioDroid system provides ubiquitous and continuous vital signs analysis, such as electrocardiogram, heart rate, respiration rate, skin temperature, and body motion, intended to help empower patients and improve clinical understanding. The PhysioDroid is composed of a wearable monitoring device and an Android app providing gathering, storage, and processing features for the physiological sensor data. The versatility of the developed app allows its use for both average users and specialists, and the reduced cost of the PhysioDroid puts it at the reach of most people. Two exemplary use cases for health assessment and sports training are presented to illustrate the capabilities of the PhysioDroid. Next technical steps include generalization to other mobile platforms and health monitoring devices.

Fatigue crack monitoring with coupled piezoelectric film acoustic emission sensors

NASA Astrophysics Data System (ADS)

Zhou, Changjiang

Fatigue-induced cracking is a commonly seen problem in civil infrastructures reaching their original design life. A number of high-profile accidents have been reported in the past that involved fatigue damage in structures. Such incidences often happen without prior warnings due to lack of proper crack monitoring technique. In order to detect and monitor the fatigue crack, acoustic emission (AE) technique, has been receiving growing interests recently. AE can provide continuous and real-time monitoring data on damage progression in structures. Piezoelectric film AE sensor measures stress-wave induced strain in ultrasonic frequency range and its feasibility for AE signal monitoring has been demonstrated recently. However, extensive work in AE monitoring system development based on piezoelectric film AE sensor and sensor characterization on full-scale structures with fatigue cracks, have not been done. A lack of theoretical formulations for understanding the AE signals also hinders the use of piezoelectric film AE sensors. Additionally, crack detection and source localization with AE signals is a very important area yet to be explored for this new type of AE sensor. This dissertation presents the results of both analytical and experimental study on the signal characteristics of surface stress-wave induced AE strain signals measured by piezoelectric film AE sensors in near-field and an AE source localization method based on sensor couple theory. Based on moment tensor theory, generalized expression for AE strain signal is formulated. A special case involving the response of piezoelectric film AE sensor to surface load is also studied, which could potentially be used for sensor calibration of this type of sensor. A new concept of sensor couple theory based AE source localization technique is proposed and validated with both simulated and experimental data from fatigue test and field monitoring. Two series of fatigue tests were conducted to perform fatigue crack monitoring on large-scale steel test specimens using piezoelectric film AE sensors. Continuous monitoring of fatigue crack growth in steel structures is demonstrated in these fatigue test specimens. The use of piezoelectric film AE sensor for field monitoring of existing fatigue crack is also demonstrated in a real steel I-girder bridge located in Maryland. The sensor couple theory based AE source localization is validated using a limited number of piezoelectric film AE sensor data from both fatigue test specimens and field monitoring bridge. Through both laboratory fatigue test and field monitoring of steel structures with active fatigue cracks, the signal characteristics of piezoelectric film AE sensor have been studied in real-world environment.

Optical and Acoustic Sensor-Based 3D Ball Motion Estimation for Ball Sport Simulators †.

PubMed

Seo, Sang-Woo; Kim, Myunggyu; Kim, Yejin

2018-04-25

Estimation of the motion of ball-shaped objects is essential for the operation of ball sport simulators. In this paper, we propose an estimation system for 3D ball motion, including speed and angle of projection, by using acoustic vector and infrared (IR) scanning sensors. Our system is comprised of three steps to estimate a ball motion: sound-based ball firing detection, sound source localization, and IR scanning for motion analysis. First, an impulsive sound classification based on the mel-frequency cepstrum and feed-forward neural network is introduced to detect the ball launch sound. An impulsive sound source localization using a 2D microelectromechanical system (MEMS) microphones and delay-and-sum beamforming is presented to estimate the firing position. The time and position of a ball in 3D space is determined from a high-speed infrared scanning method. Our experimental results demonstrate that the estimation of ball motion based on sound allows a wider activity area than similar camera-based methods. Thus, it can be practically applied to various simulations in sports such as soccer and baseball.

Monitoring Method of Cutting Force by Using Additional Spindle Sensors

NASA Astrophysics Data System (ADS)

Sarhan, Ahmed Aly Diaa; Matsubara, Atsushi; Sugihara, Motoyuki; Saraie, Hidenori; Ibaraki, Soichi; Kakino, Yoshiaki

This paper describes a monitoring method of cutting forces for end milling process by using displacement sensors. Four eddy-current displacement sensors are installed on the spindle housing of a machining center so that they can detect the radial motion of the rotating spindle. Thermocouples are also attached to the spindle structure in order to examine the thermal effect in the displacement sensing. The change in the spindle stiffness due to the spindle temperature and the speed is investigated as well. Finally, the estimation performance of cutting forces using the spindle displacement sensors is experimentally investigated by machining tests on carbon steel in end milling operations under different cutting conditions. It is found that the monitoring errors are attributable to the thermal displacement of the spindle, the time lag of the sensing system, and the modeling error of the spindle stiffness. It is also shown that the root mean square errors between estimated and measured amplitudes of cutting forces are reduced to be less than 20N with proper selection of the linear stiffness.

Sequence Learning with Passive RFID Sensors for Real-Time Bed-Egress Recognition in Older People.

PubMed

Wickramasinghe, Asanga; Ranasinghe, Damith C; Fumeaux, Christophe; Hill, Keith D; Visvanathan, Renuka

2017-07-01

Getting out of bed and ambulating without supervision is identified as one of the major causes of patient falls in hospitals and nursing homes. Therefore, increased supervision is proposed as a key strategy toward falls prevention. An emerging generation of batteryless, lightweight, and wearable sensors are creating new possibilities for ambulatory monitoring, where the unobtrusive nature of such sensors makes them particularly adapted for monitoring older people. In this study, we investigate the use of a batteryless radio-frequency identification (RFID) tag response to analyze bed-egress movements. We propose a bed-egress movement detection framework that includes a novel sequence learning classifier with a set of features derived from bed-egress motion analysis. We analyzed data from 14 healthy older people (66-86 years old) who wore a wearable embodiment of a batteryless accelerometer integrated RFID sensor platform loosely attached over their clothes at sternum level, and undertook a series of activities including bed-egress in two clinical room settings. The promising results indicate the efficacy of our batteryless bed-egress monitoring framework.

Application and Evaluation of ALOS PALSAR Data for Monitoring of Mining Induced Surface Deformations Using Interferometric Techniques

NASA Astrophysics Data System (ADS)

Walter, Diana; Wegmuller, Urs; Spreckels, Volker; Busch, Wolfgang

2008-11-01

The main objective of the projects "Determination of ground motions in mining areas by interferometric analyses of ALOS data" (ALOS ADEN 3576, ESA) and "Monitoring of mining induced surface deformation" (ALOS-RA-094, JAXA) is to evaluate PALSAR data for surface deformation monitoring, using interferometric techniques. We present monitoring results of surface movements for an active hard coal colliery of the German hard coal mining company RAG Deutsche Steinkohle (RAG). Underground mining activities lead to ground movements at the surface with maximum subsidence rates of about 10cm per month for the test site. In these projects the L-band sensor clearly demonstrates the good potential for deformation monitoring in active mining areas, especially in rural areas. In comparison to C-band sensors we clearly observe advantages in resolving the high deformation gradients that are present in this area and we achieve a more complete spatial coverage than with C-band. Extensive validation data based on levelling data and GPS measurements are available within RAǴs GIS based database "GeoMon" and thus enable an adequate analysis of the quality of the interferometric results. Previous analyses confirm the good accuracy of PALSAR data for deformation monitoring in mining areas. Furthermore, we present results of special investigations like precision geocoding of PALSAR data and corner reflector analysis. At present only DInSAR results are obtained due to the currently available number of PALSAR scenes. For the future we plan to also apply Persistent Scatterer Interferometry (PSI) using longer series of PALSAR data.

A novel camera localization system for extending three-dimensional digital image correlation

NASA Astrophysics Data System (ADS)

Sabato, Alessandro; Reddy, Narasimha; Khan, Sameer; Niezrecki, Christopher

2018-03-01

The monitoring of civil, mechanical, and aerospace structures is important especially as these systems approach or surpass their design life. Often, Structural Health Monitoring (SHM) relies on sensing techniques for condition assessment. Advancements achieved in camera technology and optical sensors have made three-dimensional (3D) Digital Image Correlation (DIC) a valid technique for extracting structural deformations and geometry profiles. Prior to making stereophotogrammetry measurements, a calibration has to be performed to obtain the vision systems' extrinsic and intrinsic parameters. It means that the position of the cameras relative to each other (i.e. separation distance, cameras angle, etc.) must be determined. Typically, cameras are placed on a rigid bar to prevent any relative motion between the cameras. This constraint limits the utility of the 3D-DIC technique, especially as it is applied to monitor large-sized structures and from various fields of view. In this preliminary study, the design of a multi-sensor system is proposed to extend 3D-DIC's capability and allow for easier calibration and measurement. The suggested system relies on a MEMS-based Inertial Measurement Unit (IMU) and a 77 GHz radar sensor for measuring the orientation and relative distance of the stereo cameras. The feasibility of the proposed combined IMU-radar system is evaluated through laboratory tests, demonstrating its ability in determining the cameras position in space for performing accurate 3D-DIC calibration and measurements.

The Red Atrapa Sismos (Quake Catcher Network in Mexico): assessing performance during large and damaging earthquakes.

USGS Publications Warehouse

Dominguez, Luis A.; Yildirim, Battalgazi; Husker, Allen L.; Cochran, Elizabeth S.; Christensen, Carl; Cruz-Atienza, Victor M.

2015-01-01

Each volunteer computer monitors ground motion and communicates using the Berkeley Open Infrastructure for Network Computing (BOINC, Anderson, 2004). Using a standard short‐term average, long‐term average (STLA) algorithm (Earle and Shearer, 1994; Cochran, Lawrence, Christensen, Chung, 2009; Cochran, Lawrence, Christensen, and Jakka, 2009), volunteer computer and sensor systems detect abrupt changes in the acceleration recordings. Each time a possible trigger signal is declared, a small package of information containing sensor and ground‐motion information is streamed to one of the QCN servers (Chung et al., 2011). Trigger signals, correlated in space and time, are then processed by the QCN server to look for potential earthquakes.

Verification of real sensor motion for a high-dynamic 3D measurement inspection system

NASA Astrophysics Data System (ADS)

Breitbarth, Andreas; Correns, Martin; Zimmermann, Manuel; Zhang, Chen; Rosenberger, Maik; Schambach, Jörg; Notni, Gunther

2017-06-01

Inline three-dimensional measurements are a growing part of optical inspection. Considering increasing production capacities and economic aspects, dynamic measurements under motion are inescapable. Using a sequence of different pattern, like it is generally done in fringe projection systems, relative movements of the measurement object with respect to the 3d sensor between the images of one pattern sequence have to be compensated. Based on the application of fully automated optical inspection of circuit boards at an assembly line, the knowledge of the relative speed of movement between the measurement object and the 3d sensor system should be used inside the algorithms of motion compensation. Optimally, this relative speed is constant over the whole measurement process and consists of only one motion direction to avoid sensor vibrations. The quantified evaluation of this two assumptions and the error impact on the 3d accuracy are content of the research project described by this paper. For our experiments we use a glass etalon with non-transparent circles and transmitted light. Focused on the circle borders, this is one of the most reliable methods to determine subpixel positions using a couple of searching rays. The intersection point of all rays characterize the center of each circle. Based on these circle centers determined with a precision of approximately 1=50 pixel, the motion vector between two images could be calculated and compared with the input motion vector. Overall, the results are used to optimize the weight distribution of the 3d sensor head and reduce non-uniformly vibrations. Finally, there exists a dynamic 3d measurement system with an error of motion vectors about 4 micrometer. Based on this outcome, simulations result in a 3d standard deviation at planar object regions of 6 micrometers. The same system yields a 3d standard deviation of 9 µm without the optimization of weight distribution.

Trunk posture monitoring with inertial sensors

PubMed Central

Wong, Man Sang

2008-01-01

Measurement of human posture and movement is an important area of research in the bioengineering and rehabilitation fields. Various attempts have been initiated for different clinical application goals, such as diagnosis of pathological posture and movements, assessment of pre- and post-treatment efficacy and comparison of different treatment protocols. Image-based methods for measurements of human posture and movements have been developed, such as the radiography, photogrammetry, optoelectric technique and video analysis. However, it is found that these methods are complicated to set up, time-consuming to operate and could only be applied in laboratory environments. This study introduced a method of using a posture monitoring system in estimating the spinal curvature changes during trunk movements on the sagittal and coronal planes and providing trunk posture monitoring during daily activities. The system consisted of three sensor modules, each with one tri-axial accelerometer and three uni-axial gyroscopes orthogonally aligned, and a digital data acquisition and feedback system. The accuracy of this system was tested with a motion analysis system (Vicon 370) in calibration with experimental setup and in trunk posture measurement with nine human subjects, and the performance of the posture monitoring system during daily activities with two human subjects was reported. The averaged root mean squared differences between the measurements of the system and motion analysis system were found to be <1.5° in dynamic calibration, and <3.1° for the sagittal plane and ≤2.1° for the coronal plane in estimation of the trunk posture change during trunk movements. The measurements of the system and the motion analysis system was highly correlated (>0.999 for dynamic calibration and >0.829 for estimation of spinal curvature change in domain planes of movement during flexion and lateral bending). With the sensing modules located on the upper trunk, mid-trunk and the pelvic levels, the inclination of trunk segment and the change of spinal curvature in trunk movements could be estimated. The posture information of five subjects was recorded at 30 s intervals during daily activity over a period of 3 days and 2 h a day. The preliminary results demonstrated that the subjects could improve their posture when feedback signals were provided. The posture monitoring system could be used for the purpose of posture monitoring during daily activity. PMID:18196296

Trunk posture monitoring with inertial sensors.

PubMed

Wong, Wai Yin; Wong, Man Sang

2008-05-01

Measurement of human posture and movement is an important area of research in the bioengineering and rehabilitation fields. Various attempts have been initiated for different clinical application goals, such as diagnosis of pathological posture and movements, assessment of pre- and post-treatment efficacy and comparison of different treatment protocols. Image-based methods for measurements of human posture and movements have been developed, such as the radiography, photogrammetry, optoelectric technique and video analysis. However, it is found that these methods are complicated to set up, time-consuming to operate and could only be applied in laboratory environments. This study introduced a method of using a posture monitoring system in estimating the spinal curvature changes during trunk movements on the sagittal and coronal planes and providing trunk posture monitoring during daily activities. The system consisted of three sensor modules, each with one tri-axial accelerometer and three uni-axial gyroscopes orthogonally aligned, and a digital data acquisition and feedback system. The accuracy of this system was tested with a motion analysis system (Vicon 370) in calibration with experimental setup and in trunk posture measurement with nine human subjects, and the performance of the posture monitoring system during daily activities with two human subjects was reported. The averaged root mean squared differences between the measurements of the system and motion analysis system were found to be < 1.5 degrees in dynamic calibration, and < 3.1 degrees for the sagittal plane and < or = 2.1 degrees for the coronal plane in estimation of the trunk posture change during trunk movements. The measurements of the system and the motion analysis system was highly correlated (> 0.999 for dynamic calibration and > 0.829 for estimation of spinal curvature change in domain planes of movement during flexion and lateral bending). With the sensing modules located on the upper trunk, mid-trunk and the pelvic levels, the inclination of trunk segment and the change of spinal curvature in trunk movements could be estimated. The posture information of five subjects was recorded at 30 s intervals during daily activity over a period of 3 days and 2 h a day. The preliminary results demonstrated that the subjects could improve their posture when feedback signals were provided. The posture monitoring system could be used for the purpose of posture monitoring during daily activity.

Wearable Inertial Sensors Allow for Quantitative Assessment of Shoulder and Elbow Kinematics in a Cadaveric Knee Arthroscopy Model.

PubMed

Rose, Michael; Curtze, Carolin; O'Sullivan, Joseph; El-Gohary, Mahmoud; Crawford, Dennis; Friess, Darin; Brady, Jacqueline M

2017-12-01

To develop a model using wearable inertial sensors to assess the performance of orthopaedic residents while performing a diagnostic knee arthroscopy. Fourteen subjects performed a diagnostic arthroscopy on a cadaveric right knee. Participants were divided into novices (5 postgraduate year 3 residents), intermediates (5 postgraduate year 4 residents), and experts (4 faculty) based on experience. Arm movement data were collected by inertial measurement units (Opal sensors) by securing 2 sensors to each upper extremity (dorsal forearm and lateral arm) and 2 sensors to the trunk (sternum and lumbar spine). Kinematics of the elbow and shoulder joints were calculated from the inertial data by biomechanical modeling based on a sequence of links connected by joints. Range of motion required to complete the procedure was calculated for each group. Histograms were used to compare the distribution of joint positions for an expert, intermediate, and novice. For both the right and left upper extremities, skill level corresponded well with shoulder abduction-adduction and elbow prono-supination. Novices required on average 17.2° more motion in the right shoulder abduction-adduction plane than experts to complete the diagnostic arthroscopy (P = .03). For right elbow prono-supination (probe hand), novices required on average 23.7° more motion than experts to complete the procedure (P = .03). Histogram data showed novices had markedly more variability in shoulder abduction-adduction and elbow prono-supination compared with the other groups. Our data show wearable inertial sensors can measure joint kinematics during diagnostic knee arthroscopy. Range-of-motion data in the shoulder and elbow correlated inversely with arthroscopic experience. Motion pattern-based analysis shows promise as a metric of resident skill acquisition and development in arthroscopy. Wearable inertial sensors show promise as metrics of arthroscopic skill acquisition among residents. Copyright © 2017 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Large Scale Triboelectric Nanogenerator and Self-Powered Pressure Sensor Array Using Low Cost Roll-to-Roll UV Embossing

PubMed Central

Dhakar, Lokesh; Gudla, Sudeep; Shan, Xuechuan; Wang, Zhiping; Tay, Francis Eng Hock; Heng, Chun-Huat; Lee, Chengkuo

2016-01-01

Triboelectric nanogenerators (TENGs) have emerged as a potential solution for mechanical energy harvesting over conventional mechanisms such as piezoelectric and electromagnetic, due to easy fabrication, high efficiency and wider choice of materials. Traditional fabrication techniques used to realize TENGs involve plasma etching, soft lithography and nanoparticle deposition for higher performance. But lack of truly scalable fabrication processes still remains a critical challenge and bottleneck in the path of bringing TENGs to commercial production. In this paper, we demonstrate fabrication of large scale triboelectric nanogenerator (LS-TENG) using roll-to-roll ultraviolet embossing to pattern polyethylene terephthalate sheets. These LS-TENGs can be used to harvest energy from human motion and vehicle motion from embedded devices in floors and roads, respectively. LS-TENG generated a power density of 62.5 mW m−2. Using roll-to-roll processing technique, we also demonstrate a large scale triboelectric pressure sensor array with pressure detection sensitivity of 1.33 V kPa−1. The large scale pressure sensor array has applications in self-powered motion tracking, posture monitoring and electronic skin applications. This work demonstrates scalable fabrication of TENGs and self-powered pressure sensor arrays, which will lead to extremely low cost and bring them closer to commercial production. PMID:26905285

An activity recognition model using inertial sensor nodes in a wireless sensor network for frozen shoulder rehabilitation exercises.

PubMed

Lin, Hsueh-Chun; Chiang, Shu-Yin; Lee, Kai; Kan, Yao-Chiang

2015-01-19

This paper proposes a model for recognizing motions performed during rehabilitation exercises for frozen shoulder conditions. The model consists of wearable wireless sensor network (WSN) inertial sensor nodes, which were developed for this study, and enables the ubiquitous measurement of bodily motions. The model employs the back propagation neural network (BPNN) algorithm to compute motion data that are formed in the WSN packets; herein, six types of rehabilitation exercises were recognized. The packets sent by each node are converted into six components of acceleration and angular velocity according to three axes. Motor features such as basic acceleration, angular velocity, and derivative tilt angle were input into the training procedure of the BPNN algorithm. In measurements of thirteen volunteers, the accelerations and included angles of nodes were adopted from possible features to demonstrate the procedure. Five exercises involving simple swinging and stretching movements were recognized with an accuracy of 85%-95%; however, the accuracy with which exercises entailing spiral rotations were recognized approximately 60%. Thus, a characteristic space and enveloped spectrum improving derivative features were suggested to enable identifying customized parameters. Finally, a real-time monitoring interface was developed for practical implementation. The proposed model can be applied in ubiquitous healthcare self-management to recognize rehabilitation exercises.

Artifact Noise Removal Techniques on Seismocardiogram Using Two Tri-Axial Accelerometers

PubMed Central

Luu, Loc; Dinh, Anh

2018-01-01

The aim of this study is on the investigation of motion noise removal techniques using two-accelerometer sensor system and various placements of the sensors on gentle movement and walking of the patients. A Wi-Fi based data acquisition system and a framework on Matlab are developed to collect and process data while the subjects are in motion. The tests include eight volunteers who have no record of heart disease. The walking and running data on the subjects are analyzed to find the minimal-noise bandwidth of the SCG signal. This bandwidth is used to design filters in the motion noise removal techniques and peak signal detection. There are two main techniques of combining signals from the two sensors to mitigate the motion artifact: analog processing and digital processing. The analog processing comprises analog circuits performing adding or subtracting functions and bandpass filter to remove artifact noises before entering the data acquisition system. The digital processing processes all the data using combinations of total acceleration and z-axis only acceleration. The two techniques are tested on three placements of accelerometer sensors including horizontal, vertical, and diagonal on gentle motion and walking. In general, the total acceleration and z-axis acceleration are the best techniques to deal with gentle motion on all sensor placements which improve average systolic signal-noise-ratio (SNR) around 2 times and average diastolic SNR around 3 times comparing to traditional methods using only one accelerometer. With walking motion, ADDER and z-axis acceleration are the best techniques on all placements of the sensors on the body which enhance about 7 times of average systolic SNR and about 11 times of average diastolic SNR comparing to only one accelerometer method. Among the sensor placements, the performance of horizontal placement of the sensors is outstanding comparing with other positions on all motions. PMID:29614821

A civil structural monitoring system based on fiber grating sensors

NASA Astrophysics Data System (ADS)

Zhang, Yan; Cai, Haiwen; Pastore, Robert; Ju, Jing; Zeng, Debing; Yin, Zhifan; Cui, Hong-Liang

2003-08-01

Optical fiber sensors based on Fiber Bragg Grating (FBG) technology have found many applications in the area of civil structural monitoring systems, such as in bridge monitoring and maintenance. FBG sensors can measure the deformation, overload and cracks on bridge with a high sensitivity. In this paper we report on our recent work a structural monitoring system using FBG sensors. Basic theoretical background and design of the system is described here, including the light source, FBG sensors, demodulator sensors, signal detection and processing schemes. The system will be installed on a major arch bridge currently under construction in Shanghai, China for long-term in situ health monitoring. The system schematic arrangement on the bridge is introduced in brief. Simulation experiments in the laboratory were carried out to test the performance of FBG strain sensors. The sensor response shows excellent linearity against the strain imposed on it. Traffic and overload monitoring on bridge using FBG sensors is also discussed and planned for the near future.

Inertial Motion Capture Costume Design Study

PubMed Central

Szczęsna, Agnieszka; Skurowski, Przemysław; Lach, Ewa; Pruszowski, Przemysław; Pęszor, Damian; Paszkuta, Marcin; Słupik, Janusz; Lebek, Kamil; Janiak, Mateusz; Polański, Andrzej; Wojciechowski, Konrad

2017-01-01

The paper describes a scalable, wearable multi-sensor system for motion capture based on inertial measurement units (IMUs). Such a unit is composed of accelerometer, gyroscope and magnetometer. The final quality of an obtained motion arises from all the individual parts of the described system. The proposed system is a sequence of the following stages: sensor data acquisition, sensor orientation estimation, system calibration, pose estimation and data visualisation. The construction of the system’s architecture with the dataflow programming paradigm makes it easy to add, remove and replace the data processing steps. The modular architecture of the system allows an effortless introduction of a new sensor orientation estimation algorithms. The original contribution of the paper is the design study of the individual components used in the motion capture system. The two key steps of the system design are explored in this paper: the evaluation of sensors and algorithms for the orientation estimation. The three chosen algorithms have been implemented and investigated as part of the experiment. Due to the fact that the selection of the sensor has a significant impact on the final result, the sensor evaluation process is also explained and tested. The experimental results confirmed that the choice of sensor and orientation estimation algorithm affect the quality of the final results. PMID:28304337

Motion perception: behavior and neural substrate.

PubMed

Mather, George

2011-05-01

Visual motion perception is vital for survival. Single-unit recordings in primate primary visual cortex (V1) have revealed the existence of specialized motion sensing neurons; perceptual effects such as the motion after-effect demonstrate their importance for motion perception. Human psychophysical data on motion detection can be explained by a computational model of cortical motion sensors. Both psychophysical and physiological data reveal at least two classes of motion sensor capable of sensing motion in luminance-defined and texture-defined patterns, respectively. Psychophysical experiments also reveal that motion can be seen independently of motion sensor output, based on attentive tracking of visual features. Sensor outputs are inherently ambiguous, due to the problem of univariance in neural responses. In order to compute stimulus direction and speed, the visual system must compare the responses of many different sensors sensitive to different directions and speeds. Physiological data show that this computation occurs in the visual middle temporal (MT) area. Recent psychophysical studies indicate that information about spatial form may also play a role in motion computations. Adaptation studies show that the human visual system is selectively sensitive to large-scale optic flow patterns, and physiological studies indicate that cells in the middle superior temporal (MST) area derive this sensitivity from the combined responses of many MT cells. Extraretinal signals used to control eye movements are an important source of signals to cancel out the retinal motion responses generated by eye movements, though visual information also plays a role. A number of issues remain to be resolved at all levels of the motion-processing hierarchy. WIREs Cogni Sci 2011 2 305-314 DOI: 10.1002/wcs.110 For further resources related to this article, please visit the WIREs website Additional Supporting Information may be found in http://www.lifesci.sussex.ac.uk/home/George_Mather/Motion/index.html. Copyright © 2010 John Wiley & Sons, Ltd.

Economy of scale: a motion sensor with variable speed tuning.

PubMed

Perrone, John A

2005-01-26

We have previously presented a model of how neurons in the primate middle temporal (MT/V5) area can develop selectivity for image speed by using common properties of the V1 neurons that precede them in the visual motion pathway (J. A. Perrone & A. Thiele, 2002). The motion sensor developed in this model is based on two broad classes of V1 complex neurons (sustained and transient). The S-type neuron has low-pass temporal frequency tuning, p(omega), and the T-type has band-pass temporal frequency tuning, m(omega). The outputs from the S and T neurons are combined in a special way (weighted intersection mechanism [WIM]) to generate a sensor tuned to a particular speed, v. Here I go on to show that if the S and T temporal frequency tuning functions have a particular form (i.e., p(omega)/(m(omega) = k/omega), then a motion sensor with variable speed tuning can be generated from just two V1 neurons. A simple scaling of the S- or T-type neuron output before it is incorporated into the WIM model produces a motion sensor that can be tuned to a wide continuous range of optimal speeds.

Gyroscope-reduced inertial navigation system for flight vehicle motion estimation

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiao, Lu

2017-01-01

In this paper, a novel configuration of strategically distributed accelerometer sensors with the aid of one gyro to infer a flight vehicle's angular motion is presented. The MEMS accelerometer and gyro sensors are integrated to form a gyroscope-reduced inertial measurement unit (GR-IMU). The motivation for gyro aided accelerometers array is to have direct measurements of angular rates, which is an improvement to the traditional gyroscope-free inertial system that employs only direct measurements of specific force. Some technical issues regarding error calibration in accelerometers and gyro in GR-IMU are put forward. The GR-IMU based inertial navigation system can be used to find a complete attitude solution for flight vehicle motion estimation. Results of numerical simulation are given to illustrate the effectiveness of the proposed configuration. The gyroscope-reduced inertial navigation system based on distributed accelerometer sensors can be developed into a cost effective solution for a fast reaction, MEMS based motion capture system. Future work will include the aid from external navigation references (e.g. GPS) to improve long time mission performance.

Developments in real-time monitoring for geologic hazard warnings (Invited)

NASA Astrophysics Data System (ADS)

Leith, W. S.; Mandeville, C. W.; Earle, P. S.

2013-12-01

Real-time data from global, national and local sensor networks enable prompt alerts and warnings of earthquakes, tsunami, volcanic eruptions, geomagnetic storms , broad-scale crustal deformation and landslides. State-of-the-art seismic systems can locate and evaluate earthquake sources in seconds, enabling 'earthquake early warnings' to be broadcast ahead of the damaging surface waves so that protective actions can be taken. Strong motion monitoring systems in buildings now support near-real-time structural damage detection systems, and in quiet times can be used for state-of-health monitoring. High-rate GPS data are being integrated with seismic strong motion data, allowing accurate determination of earthquake displacements in near-real time. GPS data, combined with rainfall, groundwater and geophone data, are now used for near-real-time landslide monitoring and warnings. Real-time sea-floor water pressure data are key for assessing tsunami generation by large earthquakes. For monitoring remote volcanoes that lack local ground-based instrumentation, the USGS uses new technologies such as infrasound arrays and the worldwide lightning detection array to detect eruptions in progress. A new real-time UV-camera system for measuring the two dimensional SO2 flux from volcanic plumes will allow correlations with other volcano monitoring data streams to yield fundamental data on changes in gas flux as an eruption precursor, and how magmas de-gas prior to and during eruptions. Precision magnetic field data support the generation of real-time indices of geomagnetic disturbances (Dst, K and others), and can be used to model electrical currents in the crust and bulk power system. Ground-induced electrical current monitors are used to track those currents so that power grids can be effectively managed during geomagnetic storms. Beyond geophysical sensor data, USGS is using social media to rapidly detect possible earthquakes and to collect firsthand accounts of the impacts of natural disasters useful for social science studies. Monitoring of tweets in real-time, when analyzed statistically and geographically, can give a prompt indication of an earthquake, well before seismic networks in sparsely instrumented regions can locate an event and determine its magnitude. With more and more real-time data becoming available, new applications and products are inevitable.

An Integrated Processing Strategy for Mountain Glacier Motion Monitoring Based on SAR Images

NASA Astrophysics Data System (ADS)

Ruan, Z.; Yan, S.; Liu, G.; LV, M.

2017-12-01

Mountain glacier dynamic variables are important parameters in studies of environment and climate change in High Mountain Asia. Due to the increasing events of abnormal glacier-related hazards, research of monitoring glacier movements has attracted more interest during these years. Glacier velocities are sensitive and changing fast under complex conditions of high mountain regions, which implies that analysis of glacier dynamic changes requires comprehensive and frequent observations with relatively high accuracy. Synthetic aperture radar (SAR) has been successfully exploited to detect glacier motion in a number of previous studies, usually with pixel-tracking and interferometry methods. However, the traditional algorithms applied to mountain glacier regions are constrained by the complex terrain and diverse glacial motion types. Interferometry techniques are prone to fail in mountain glaciers because of their narrow size and the steep terrain, while pixel-tracking algorithm, which is more robust in high mountain areas, is subject to accuracy loss. In order to derive glacier velocities continually and efficiently, we propose a modified strategy to exploit SAR data information for mountain glaciers. In our approach, we integrate a set of algorithms for compensating non-glacial-motion-related signals which exist in the offset values retrieved by sub-pixel cross-correlation of SAR image pairs. We exploit modified elastic deformation model to remove the offsets associated with orbit and sensor attitude, and for the topographic residual offset we utilize a set of operations including DEM-assisted compensation algorithm and wavelet-based algorithm. At the last step of the flow, an integrated algorithm combining phase and intensity information of SAR images will be used to improve regional motion results failed in cross-correlation related processing. The proposed strategy is applied to the West Kunlun Mountain and Muztagh Ata region in western China using ALOS/PALSAR data. The results show that the strategy can effectively improve the accuracy of velocity estimation by reducing the mean and standard deviation values from 0.32 m and 0.4 m to 0.16 m. It is proved to be highly appropriate for monitoring glacier motion over a widely varying range of ice velocities with a relatively high accuracy.

Adherence to and effectiveness of an individually tailored home-based exercise program for frail older adults, driven by mobility monitoring: design of a prospective cohort study.

PubMed

Geraedts, Hilde A E; Zijlstra, Wiebren; Zhang, Wei; Bulstra, Sjoerd; Stevens, Martin

2014-06-07

With the number of older adults in society rising, frailty becomes an increasingly prevalent health condition. Regular physical activity can prevent functional decline and reduce frailty symptoms. In particular, home-based exercise programs can be beneficial in reducing frailty of older adults and fall risk, and in improving associated physiological parameters. However, adherence to home-based exercise programs is generally low among older adults. Current developments in technology can assist in enlarging adherence to home-based exercise programs. This paper presents the rationale and design of a study evaluating the adherence to and effectiveness of an individually tailored, home-based physical activity program for frail older adults driven by mobility monitoring through a necklace-worn physical activity sensor and remote feedback using a tablet PC. Fifty transitionally frail community-dwelling older adults will join a 6-month home-based physical activity program in which exercises are provided in the form of exercise videos on a tablet PC and daily activity is monitored by means of a necklace-worn motion sensor. Participants exercise 5 times a week. Exercises are built up in levels and are individually tailored in consultation with a coach through weekly telephone contact. The physical activity program driven by mobility monitoring through a necklace-worn sensor and remote feedback using a tablet PC is an innovative method for physical activity stimulation in frail older adults. We hypothesize that, if participants are sufficiently adherent, the program will result in higher daily physical activity and higher strength and balance assessed by physical tests compared to baseline. If adherence to and effectiveness of the program is considered sufficient, the next step would be to evaluate the effectiveness with a randomised controlled trial. The knowledge gained in this study can be used to develop and fine-tune the application of innovative technology in home-based exercise programs. Nederlands Trial Register (NTR); trial number 4265. The study was prospectively registered (registration date 14/11/2013).

FOSREM - Fibre-Optic System for Rotational Events&Phenomena Monitoring

NASA Astrophysics Data System (ADS)

Jaroszewicz, Leszek; Krajewski, Zbigniew; Kurzych, Anna; Kowalski, Jerzy; Teisseyre, Krzysztof

2016-04-01

We present the construction and tests of fiber-optic rotational seismometer named FOSREM (Fibre-Optic System for Rotational Events&Phenomena Monitoring). This presented device is designed for detection and monitoring the one-axis rotational motions, brought about to ground or human-made structures both by seismic events and the creep processes. The presented system works by measuring Sagnac effect and generally consists of two basic elements: optical sensor and electronic part. The optical sensor is based on so-called the minimum configuration of FOG (Fibre-Optic Gyroscope) where the Sagnac effect produces a phase shift between two counter-propagating light beams proportional to the measured rotation speed. The main advantage of the sensor of this type is its complete insensitivity to linear motions and a direct measurement of rotational speed. It may work even when tilted, moreover, used in continuous mode it may record the tilt. The electronic system, involving specific electronic solutions, calculates and records rotational events data by realizing synchronous in a digital form by using 32 bit DSP (Digital Signal Processing). Storage data and system control are realised over the internet by using connection between FOSREM and GSM/GPS. The most significant attribute of our system is possibility to measure rotation in wide range both amplitude up to 10 rad/s and frequency up to 328.12 Hz. Application of the wideband, low coherence and high power superluminescent diode with long fibre loop and suitable low losses optical elements assures the theoretical sensitivity of the system equal to 2·10-8 rad/s/Sqrt(Hz). Moreover, the FOSREM is fully remote controlled as well as is suited for continuous, autonomous work in very long period of time (weeks, months, even years), so it is useful for systematic seismological investigation at any place. Possible applications of this system include seismic monitoring in observatories, buildings, mines and even on glaciers and in their vicinity. In geodetic, geomorphological and glaciological survey, joint measurement of tilt and seismic phenomena using a set of three FOSREM devices oriented in perpendicular planes would enable to collect very important information.

Player Monitoring in Indoor Team Sports: Concurrent Validity of Inertial Measurement Units to Quantify Average and Peak Acceleration Values

PubMed Central

Roell, Mareike; Roecker, Kai; Gehring, Dominic; Mahler, Hubert; Gollhofer, Albert

2018-01-01

The increasing interest in assessing physical demands in team sports has led to the development of multiple sports related monitoring systems. Due to technical limitations, these systems primarily could be applied to outdoor sports, whereas an equivalent indoor locomotion analysis is not established yet. Technological development of inertial measurement units (IMU) broadens the possibilities for player monitoring and enables the quantification of locomotor movements in indoor environments. The aim of the current study was to validate an IMU measuring by determining average and peak human acceleration under indoor conditions in team sport specific movements. Data of a single wearable tracking device including an IMU (Optimeye S5, Catapult Sports, Melbourne, Australia) were compared to the results of a 3D motion analysis (MA) system (Vicon Motion Systems, Oxford, UK) during selected standardized movement simulations in an indoor laboratory (n = 56). A low-pass filtering method for gravity correction (LF) and two sensor fusion algorithms for orientation estimation [Complementary Filter (CF), Kalman-Filter (KF)] were implemented and compared with MA system data. Significant differences (p < 0.05) were found between LF and MA data but not between sensor fusion algorithms and MA. Higher precision and lower relative errors were found for CF (RMSE = 0.05; CV = 2.6%) and KF (RMSE = 0.15; CV = 3.8%) both compared to the LF method (RMSE = 1.14; CV = 47.6%) regarding the magnitude of the resulting vector and strongly emphasize the implementation of orientation estimation to accurately describe human acceleration. Comparing both sensor fusion algorithms, CF revealed slightly lower errors than KF and additionally provided valuable information about positive and negative acceleration values in all three movement planes with moderate to good validity (CV = 3.9 – 17.8%). Compared to x- and y-axis superior results were found for the z-axis. These findings demonstrate that IMU-based wearable tracking devices can successfully be applied for athlete monitoring in indoor team sports and provide potential to accurately quantify accelerations and decelerations in all three orthogonal axes with acceptable validity. An increase in accuracy taking magnetometers in account should be specifically pursued by future research. PMID:29535641

High resolution tiltmeters and strainmeters based on extrinsic fiber Fabbry-Perot interferometry: the LINES project

NASA Astrophysics Data System (ADS)

chery, J.; Boudin, F.; Cattoen, M.; Seat, H.; Suleiman, M.; Chawah, P.; Plantier, G.; Sourice, A.; Bernard, P.; Brunet, C.; Gaffet, S.; Boyer, D.

2011-12-01

Measurements of strain and vibrations due to seismic and volcanic processes are mandatory for the understanding and the monitoring of the behavior of these systems. In the future, risk mitigation will depend on our capability to detect in a reliable way small precursors of large seismic and volcanic events and to assess the seismic/aseismic spatial and temporal distribution and evolution of crustal strain in these unstable systems.The robustness of strain and motion detection is primary linked to measurement accuracy, but also to the number and repartition of instrument. This implies that instrument cost and maintenance are essential for the development of networks. To date, only GPS sensors are robust enough to be deployed for long periods of time with limited problems of maintenance. Tiltmeters and strainmeters capabilities are often plagued by numerous technical problems limiting their usefulness. On the basis of existing or prototype sensors, we develop new instruments (seismometers, tiltmeters, strainmeters) using an interferometric motion measurement. Both Laser source and fringe analysis are connected to the mechanical sensor with long optic fiber (100 m - 10 km) depending on applications (volcanoes, sea bottom, boreholes) The fiber signal transmission is a major improvement by comparison with usual electric wires (cost, data channels, lightning, weight). Also, the absence of embedded electronic on the sensor is a guarantee for reliability and toughness. The proposed optical cell is an extrinsic all-fiber Fabry-Perot type interferometer (EFFPI). While being intrinsically insensitive to external perturbations to the sensing arm such as from stress/strain and temperature variations, the EFFPI is, however, extremely sensitive to changes in its sensing cavity length caused by parameters such as displacement, strain, and mechanical deformation along the optical axis. Coupled to well-advanced associated technologies in terms of laser sources (stability, output power), optical fiber (quality, low losses, couplers, connectics), photodetection (bandwidth, gain, low-noise) and real-time interferometric signal demodulation, this interferometer is today a mature device whose performance potential can be exploited in in-situ environmental monitoring of seismic activities (earthquakes and volcanoes) and in predicting the related risks. In the framework of the LINES project, we develop three types of mechanical sensors: a long baseline tiltmeter based on hydrostatic levelling, a borehole tiltmeter based on a simple pendulum and a seismometer for detecting vibrations at frequencies higher than 1 Hz. A common building principle is an external laser source and phase detector: as this part of the tool is remotely connected through an optic fiber to the underground sensor, this overcomes most of electric, power and maintenance problem occurring with non-optical devices. Moreover, this allows simple analog data transmission for a real-time network monitoring. We will show preliminary results suggesting that a rapid transition between laboratory prototypes and field instruments is likely.

Miniaturized optical wavelength sensors

NASA Astrophysics Data System (ADS)

Kung, Helen Ling-Ning

Recently semiconductor processing technology has been applied to the miniaturization of optical wavelength sensors. Compact sensors enable new applications such as integrated diode-laser wavelength monitors and frequency lockers, portable chemical and biological detection, and portable and adaptive hyperspectral imaging arrays. Small sensing systems have trade-offs between resolution, operating range, throughput, multiplexing and complexity. We have developed a new wavelength sensing architecture that balances these parameters for applications involving hyperspectral imaging spectrometer arrays. In this thesis we discuss and demonstrate two new wavelength-sensing architectures whose single-pixel designs can easily be extended into spectrometer arrays. The first class of devices is based on sampling a standing wave. These devices are based on measuring the wavelength-dependent period of optical standing waves formed by the interference of forward and reflected waves at a mirror. We fabricated two different devices based on this principle. The first device is a wavelength monitor, which measures the wavelength and power of a monochromatic source. The second device is a spectrometer that can also act as a selective spectral coherence sensor. The spectrometer contains a large displacement piston-motion MEMS mirror and a thin GaAs photodiode flip-chip bonded to a quartz substrate. The performance of this spectrometer is similar to that of a Michelson in resolution, operating range, throughput and multiplexing but with the added advantages of fewer components and one-dimensional architecture. The second class of devices is based on the Talbot self-imaging effect. The Talbot effect occurs when a periodic object is illuminated with a spatially coherent wave. Periodically spaced self-images are formed behind the object. The spacing of the self-images is proportional to wavelength of the incident light. We discuss and demonstrate how this effect can be used for spectroscopy. In the conclusion we compare these two new miniaturized spectrometer architectures to existing miniaturized spectrometers. We believe that the combination of miniaturized wavelength sensors and smart processing should facilitate the development real-time, adaptive and portable sensing systems.

A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-07-24

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04-0.24 m/s; height RMSE was in the range 5-68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions.

A configurable sensor network applied to ambient assisted living.

PubMed

Villacorta, Juan J; Jiménez, María I; Del Val, Lara; Izquierdo, Alberto

2011-01-01

The rising older people population has increased the interest in ambient assisted living systems. This article presents a system for monitoring the disabled or older persons developed from an existing surveillance system. The modularity and adaptability characteristics of the system allow an easy adaptation for a different purpose. The proposed system uses a network of sensors capable of motion detection that includes fall warning, identification of persons and a configurable control system which allows its use in different scenarios.

Massachusetts Institute of Technology Consortium Agreement. Phase II

DTIC Science & Technology

1999-03-01

Portable VOR Testing Apparatusthe visual target. Head movements are monitored with magneto-hydrodynamic rotational velocity sensors , and eye motions are...Zhang 4. Miniaturization of the Ring Sensor B-H Yang, H. Asada, K-W. Chang , S. Rhee, Y. Zhang 5. SIMSUIT and Biochair Projects L. Jones, J. Tangorra...No change along 0 a•0a = (2) Neglect Vr = Vr = 0 (Wall velocity of r direction is very small compared with v.’.) a ax ax= (3) As r << x, Dr• >> axx

Development of Acceleration Sensor and Acceleration Evaluation System for Super-Low-Range Frequencies

NASA Astrophysics Data System (ADS)

Asano, Shogo; Matsumoto, Hideki

2001-05-01

This paper describes the development process for acceleration sensors used on automobiles and an acceleration evaluation system designed specifically for acceleration at super-low-range frequencies. The features of the newly developed sensor are as follows. 1) Original piezo-bimorph design based on a disc-center-fixed structure achieves pyroeffect cancelling and stabilization of sensor characteristics and enables the detection of the acceleration of 0.0009 G at the super-low-range-frequency of 0.03 Hz. 2) The addition of a self-diagnostic function utilizing the characteristics of piezoceramics enables constant monitoring of sensor failure. The frequency range of acceleration for accurate vehicle motion control is considered to be from DC to about 50 Hz. However, the measurement of acceleration in the super-low-range frequency near DC has been difficult because of mechanical and electrical noise interruption. This has delayed the development of the acceleration sensor for automotive use. We have succeeded in the development of an acceleration evaluation system for super-low-range frequencies from 0.015 Hz to 2 Hz with detection of the acceleration range from 0.0002 G (0.2 gal) to 1 G, as well as the development of a piezoelectric-type acceleration sensor for automotive use.

Toward seamless wearable sensing: Automatic on-body sensor localization for physical activity monitoring.

PubMed

Saeedi, Ramyar; Purath, Janet; Venkatasubramanian, Krishna; Ghasemzadeh, Hassan

2014-01-01

Mobile wearable sensors have demonstrated great potential in a broad range of applications in healthcare and wellness. These technologies are known for their potential to revolutionize the way next generation medical services are supplied and consumed by providing more effective interventions, improving health outcomes, and substantially reducing healthcare costs. Despite these potentials, utilization of these sensor devices is currently limited to lab settings and in highly controlled clinical trials. A major obstacle in widespread utilization of these systems is that the sensors need to be used in predefined locations on the body in order to provide accurate outcomes such as type of physical activity performed by the user. This has reduced users' willingness to utilize such technologies. In this paper, we propose a novel signal processing approach that leverages feature selection algorithms for accurate and automatic localization of wearable sensors. Our results based on real data collected using wearable motion sensors demonstrate that the proposed approach can perform sensor localization with 98.4% accuracy which is 30.7% more accurate than an approach without a feature selection mechanism. Furthermore, utilizing our node localization algorithm aids the activity recognition algorithm to achieve 98.8% accuracy (an increase from 33.6% for the system without node localization).

Radio Frequency Identification (RFID) Based Corrosion Monitoring Sensors. Part 2: Application and Testing of the Coating Materials

DTIC Science & Technology

2014-12-22

Radio frequency identification ( RFID ) based corrosion monitoring sensors: Part II Application and testing of the coating materials Youliang He1...email: yohe@nrcan.gc.ca Keywords: Corrosion monitoring; Wireless sensor; RFID ; Electromagnetic interference; Coating. Abstract Cost-effective...Radio Frequency Identification ( RFID ) transponders (tags) were investigated for wireless corrosion monitoring by applying a metal-filled conductive

Monitoring industrial facilities using principles of integration of fiber classifier and local sensor networks

NASA Astrophysics Data System (ADS)

Korotaev, Valery V.; Denisov, Victor M.; Rodrigues, Joel J. P. C.; Serikova, Mariya G.; Timofeev, Andrey V.

2015-05-01

The paper deals with the creation of integrated monitoring systems. They combine fiber-optic classifiers and local sensor networks. These systems allow for the monitoring of complex industrial objects. Together with adjacent natural objects, they form the so-called geotechnical systems. An integrated monitoring system may include one or more spatially continuous fiber-optic classifiers based on optic fiber and one or more arrays of discrete measurement sensors, which are usually combined in sensor networks. Fiber-optic classifiers are already widely used for the control of hazardous extended objects (oil and gas pipelines, railways, high-rise buildings, etc.). To monitor local objects, discrete measurement sensors are generally used (temperature, pressure, inclinometers, strain gauges, accelerometers, sensors measuring the composition of impurities in the air, and many others). However, monitoring complex geotechnical systems require a simultaneous use of continuous spatially distributed sensors based on fiber-optic cable and connected local discrete sensors networks. In fact, we are talking about integration of the two monitoring methods. This combination provides an additional way to create intelligent monitoring systems. Modes of operation of intelligent systems can automatically adapt to changing environmental conditions. For this purpose, context data received from one sensor (e.g., optical channel) may be used to change modes of work of other sensors within the same monitoring system. This work also presents experimental results of the prototype of the integrated monitoring system.

Analysis and Visualization of 3D Motion Data for UPDRS Rating of Patients with Parkinson's Disease.

PubMed

Piro, Neltje E; Piro, Lennart K; Kassubek, Jan; Blechschmidt-Trapp, Ronald A

2016-06-21

Remote monitoring of Parkinson's Disease (PD) patients with inertia sensors is a relevant method for a better assessment of symptoms. We present a new approach for symptom quantification based on motion data: the automatic Unified Parkinson Disease Rating Scale (UPDRS) classification in combination with an animated 3D avatar giving the neurologist the impression of having the patient live in front of him. In this study we compared the UPDRS ratings of the pronation-supination task derived from: (a) an examination based on video recordings as a clinical reference; (b) an automatically classified UPDRS; and (c) a UPDRS rating from the assessment of the animated 3D avatar. Data were recorded using Magnetic, Angular Rate, Gravity (MARG) sensors with 15 subjects performing a pronation-supination movement of the hand. After preprocessing, the data were classified with a J48 classifier and animated as a 3D avatar. Video recording of the movements, as well as the 3D avatar, were examined by movement disorder specialists and rated by UPDRS. The mean agreement between the ratings based on video and (b) the automatically classified UPDRS is 0.48 and with (c) the 3D avatar it is 0.47. The 3D avatar is similarly suitable for assessing the UPDRS as video recordings for the examined task and will be further developed by the research team.

A smart home application to eldercare: current status and lessons learned.

PubMed

Skubic, Marjorie; Alexander, Gregory; Popescu, Mihail; Rantz, Marilyn; Keller, James

2009-01-01

To address an aging population, we have been investigating sensor networks for monitoring older adults in their homes. In this paper, we report ongoing work in which passive sensor networks have been installed in 17 apartments in an aging in place eldercare facility. The network under development includes simple motion sensors, video sensors, and a bed sensor that captures sleep restlessness and pulse and respiration levels. Data collection has been ongoing for over two years in some apartments. This longevity in sensor data collection is allowing us to study the data and develop algorithms for identifying alert conditions such as falls, as well as extracting typical daily activity patterns for an individual. The goal is to capture patterns representing physical and cognitive health conditions and then recognize when activity patterns begin to deviate from the norm. In doing so, we strive to provide early detection of potential problems which may lead to serious health events if left unattended. We describe the components of the network and show examples of logged sensor data with correlated references to health events. A summary is also included on the challenges encountered and the lessons learned as a result of our experiences in monitoring aging adults in their homes.

The ESO astronomical site monitor upgrade

NASA Astrophysics Data System (ADS)

Chiozzi, Gianluca; Sommer, Heiko; Sarazin, Marc; Bierwirth, Thomas; Dorigo, Dario; Vera Sequeiros, Ignacio; Navarrete, Julio; Del Valle, Diego

2016-08-01

Monitoring and prediction of astronomical observing conditions are essential for planning and optimizing observations. For this purpose, ESO, in the 90s, developed the concept of an Astronomical Site Monitor (ASM), as a facility fully integrated in the operations of the VLT observatory[1]. Identical systems were installed at Paranal and La Silla, providing comprehensive local weather information. By now, we had very good reasons for a major upgrade: • The need of introducing new features to satisfy the requirements of observing with the Adaptive Optics Facility and to benefit other Adaptive Optics systems. • Managing hardware and software obsolescence. • Making the system more maintainable and expandable by integrating off-the-shelf hardware solutions. The new ASM integrates: • A new Differential Image Motion Monitor (DIMM) paired with a Multi Aperture Scintillation Sensor (MASS) to measure the vertical distribution of turbulence in the high atmosphere and its characteristic velocity. • A new SLOpe Detection And Ranging (SLODAR) telescope, for measuring the altitude and intensity of turbulent layers in the low atmosphere. • A water vapour radiometer to monitor the water vapour content of the atmosphere. • The old weather tower, which is being refurbished with new sensors. The telescopes and the devices integrated are commercial products and we have used as much as possible the control system from the vendors. The existing external interfaces, based on the VLT standards, have been maintained for full backward compatibility. All data produced by the system are directly fed in real time into a relational database. A completely new web-based display replaces the obsolete plots based on HP-UX RTAP. We analyse here the architectural and technological choices and discuss the motivations and trade-offs.

Classifying prosthetic use via accelerometry in persons with transtibial amputations.

PubMed

Redfield, Morgan T; Cagle, John C; Hafner, Brian J; Sanders, Joan E

2013-01-01

Knowledge of how persons with amputation use their prostheses and how this use changes over time may facilitate effective rehabilitation practices and enhance understanding of prosthesis functionality. Perpetual monitoring and classification of prosthesis use may also increase the health and quality of life for prosthetic users. Existing monitoring and classification systems are often limited in that they require the subject to manipulate the sensor (e.g., attach, remove, or reset a sensor), record data over relatively short time periods, and/or classify a limited number of activities and body postures of interest. In this study, a commercially available three-axis accelerometer (ActiLife ActiGraph GT3X+) was used to characterize the activities and body postures of individuals with transtibial amputation. Accelerometers were mounted on prosthetic pylons of 10 persons with transtibial amputation as they performed a preset routine of actions. Accelerometer data was postprocessed using a binary decision tree to identify when the prosthesis was being worn and to classify periods of use as movement (i.e., leg motion such as walking or stair climbing), standing (i.e., standing upright with limited leg motion), or sitting (i.e., seated with limited leg motion). Classifications were compared to visual observation by study researchers. The classifier achieved a mean +/- standard deviation accuracy of 96.6% +/- 3.0%.

Classifying Prosthetic Use via Accelerometry in Persons with Trans-Tibial Amputations

PubMed Central

Redfield, Morgan T.; Cagle, John C.; Hafner, Brian J.; Sanders, Joan E.

2014-01-01

Knowledge of how persons with amputation use their prostheses and how this use changes over time may facilitate effective rehabilitation practices and enhance understanding of prosthesis functionality. Perpetual monitoring and classification of prosthesis use may also increase the health and quality of life for prosthetic users. Existing monitoring and classification systems are often limited in that they require the subject to manipulate the sensor (e.g., attach, remove, or reset a sensor), record data over relatively short time periods, and/or classify a limited number of activities and body postures of interest. In this study, a commercially-available three-axis accelerometer (ActiLife ActiGraph GT3X+) was used to characterize the activities and body postures of individuals with trans-tibial amputation. Accelerometers were mounted on prosthetic pylons of ten persons with trans-tibial amputation as they performed a preset routine of actions. Accelerometer data was post-processed using a Binary Decision Tree to identify when the prosthesis was being worn and to classify periods of use as movement (i.e., leg motion like walking or stair climbing), standing (i.e., standing upright with limited leg motion), or sitting (i.e., seated with limited leg motion). Classifications were compared to visual observation by study researchers. The classifier achieved a mean accuracy of 96.6% (SD=3.0%). PMID:24458961

3DUI assisted lower and upper member therapy.

PubMed

Uribe-Quevedo, Alvaro; Perez-Gutierrez, Byron

2012-01-01

3DUIs are becoming very popular among researchers, developers and users as they allow more immersive and interactive experiences by taking advantage of the human dexterity. The features offered by these interfaces outside the gaming environment, have allowed the development of applications in the medical area by enhancing the user experience and aiding the therapy process in controlled and monitored environments. Using mainstream videogame 3DUIs based on inertial and image sensors available in the market, this work presents the development of a virtual environment and its navigation through lower member captured gestures for assisting motion during therapy.

Monitoring Method and Apparatus Using Asynchronous, One-Way Transmission from Sensor to Base Station

NASA Technical Reports Server (NTRS)

Drouant, George J. (Inventor); Jensen, Scott L. (Inventor)

2013-01-01

A monitoring system is disclosed, which includes a base station and at least one sensor unit that is separate from the base station. The at least one sensor unit resides in a dormant state until it is awakened by the triggering of a vibration-sensitive switch. Once awakened, the sensor may take a measurement, and then transmit to the base station the measurement. Once data is transmitted from the sensor to the base station, the sensor may return to its dormant state. There may be various sensors for each base station and the various sensors may optionally measure different quantities, such as current, voltage, single-axis and/or three-axis magnetic fields.

A new calibration methodology for thorax and upper limbs motion capture in children using magneto and inertial sensors.

PubMed

Ricci, Luca; Formica, Domenico; Sparaci, Laura; Lasorsa, Francesca Romana; Taffoni, Fabrizio; Tamilia, Eleonora; Guglielmelli, Eugenio

2014-01-09

Recent advances in wearable sensor technologies for motion capture have produced devices, mainly based on magneto and inertial measurement units (M-IMU), that are now suitable for out-of-the-lab use with children. In fact, the reduced size, weight and the wireless connectivity meet the requirement of minimum obtrusivity and give scientists the possibility to analyze children's motion in daily life contexts. Typical use of magneto and inertial measurement units (M-IMU) motion capture systems is based on attaching a sensing unit to each body segment of interest. The correct use of this setup requires a specific calibration methodology that allows mapping measurements from the sensors' frames of reference into useful kinematic information in the human limbs' frames of reference. The present work addresses this specific issue, presenting a calibration protocol to capture the kinematics of the upper limbs and thorax in typically developing (TD) children. The proposed method allows the construction, on each body segment, of a meaningful system of coordinates that are representative of real physiological motions and that are referred to as functional frames (FFs). We will also present a novel cost function for the Levenberg-Marquardt algorithm, to retrieve the rotation matrices between each sensor frame (SF) and the corresponding FF. Reported results on a group of 40 children suggest that the method is repeatable and reliable, opening the way to the extensive use of this technology for out-of-the-lab motion capture in children.

Characterization of cement-based materials using a reusable piezoelectric impedance-based sensor

NASA Astrophysics Data System (ADS)

Tawie, R.; Lee, H. K.

2011-08-01

This paper proposes a reusable sensor, which employs a piezoceramic (PZT) plate as an active sensing transducer, for non-destructive monitoring of cement-based materials based on the electromechanical impedance (EMI) sensing technique. The advantage of the sensor design is that the PZT can be easily removed from the set-up and re-used for repetitive tests. The applicability of the sensor was demonstrated for monitoring of the setting of cement mortar. EMI measurements were performed using an impedance analyzer and the transformation of the specimen from the plastic to solid state was monitored by automatically measuring the changes in the PZT conductance spectra with respect to curing time using the root mean square deviation (RMSD) algorithm. In another experiment, drying-induced moisture loss of a hardened mortar specimen at saturated surface dry (SSD) condition was measured, and monitored using the reusable sensor to establish a correlation between the RMSD values and moisture loss rate. The reusable sensor was also demonstrated for detecting progressive damages imparted on a mortar specimen attached with the sensor under several loading levels before allowing it to load to failure. Overall, the reusable sensor is an effective and efficient monitoring device that could possibly be used for field application in characterization of cement-based materials.

Laboratory and field testing of commercial rotational seismometers

USGS Publications Warehouse

Nigbor, R.L.; Evans, J.R.; Hutt, C.R.

2009-01-01

There are a small number of commercially available sensors to measure rotational motion in the frequency and amplitude ranges appropriate for earthquake motions on the ground and in structures. However, the performance of these rotational seismometers has not been rigorously and independently tested and characterized for earthquake monitoring purposes as is done for translational strong- and weak-motion seismometers. Quantities such as sensitivity, frequency response, resolution, and linearity are needed for the understanding of recorded rotational data. To address this need, we, with assistance from colleagues in the United States and Taiwan, have been developing performance test methodologies and equipment for rotational seismometers. In this article the performance testing methodologies are applied to samples of a commonly used commercial rotational seismometer, the eentec model R-1. Several examples were obtained for various test sequences in 2006, 2007, and 2008. Performance testing of these sensors consisted of measuring: (1) sensitivity and frequency response; (2) clip level; (3) self noise and resolution; and (4) cross-axis sensitivity, both rotational and translational. These sensor-specific results will assist in understanding the performance envelope of the R-1 rotational seismometer, and the test methodologies can be applied to other rotational seismometers.

Autonomous Landmark Calibration Method for Indoor Localization

PubMed Central

Kim, Jae-Hoon; Kim, Byoung-Seop

2017-01-01

Machine-generated data expansion is a global phenomenon in recent Internet services. The proliferation of mobile communication and smart devices has increased the utilization of machine-generated data significantly. One of the most promising applications of machine-generated data is the estimation of the location of smart devices. The motion sensors integrated into smart devices generate continuous data that can be used to estimate the location of pedestrians in an indoor environment. We focus on the estimation of the accurate location of smart devices by determining the landmarks appropriately for location error calibration. In the motion sensor-based location estimation, the proposed threshold control method determines valid landmarks in real time to avoid the accumulation of errors. A statistical method analyzes the acquired motion sensor data and proposes a valid landmark for every movement of the smart devices. Motion sensor data used in the testbed are collected from the actual measurements taken throughout a commercial building to demonstrate the practical usefulness of the proposed method. PMID:28837071

3D Orthogonal Woven Triboelectric Nanogenerator for Effective Biomechanical Energy Harvesting and as Self-Powered Active Motion Sensors.

PubMed

Dong, Kai; Deng, Jianan; Zi, Yunlong; Wang, Yi-Cheng; Xu, Cheng; Zou, Haiyang; Ding, Wenbo; Dai, Yejing; Gu, Bohong; Sun, Baozhong; Wang, Zhong Lin

2017-10-01

The development of wearable and large-area energy-harvesting textiles has received intensive attention due to their promising applications in next-generation wearable functional electronics. However, the limited power outputs of conventional textiles have largely hindered their development. Here, in combination with the stainless steel/polyester fiber blended yarn, the polydimethylsiloxane-coated energy-harvesting yarn, and nonconductive binding yarn, a high-power-output textile triboelectric nanogenerator (TENG) with 3D orthogonal woven structure is developed for effective biomechanical energy harvesting and active motion signal tracking. Based on the advanced 3D structural design, the maximum peak power density of 3D textile can reach 263.36 mW m -2 under the tapping frequency of 3 Hz, which is several times more than that of conventional 2D textile TENGs. Besides, its collected power is capable of lighting up a warning indicator, sustainably charging a commercial capacitor, and powering a smart watch. The 3D textile TENG can also be used as a self-powered active motion sensor to constantly monitor the movement signals of human body. Furthermore, a smart dancing blanket is designed to simultaneously convert biomechanical energy and perceive body movement. This work provides a new direction for multifunctional self-powered textiles with potential applications in wearable electronics, home security, and personalized healthcare. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A knitted glove sensing system with compression strain for finger movements

NASA Astrophysics Data System (ADS)

Ryu, Hochung; Park, Sangki; Park, Jong-Jin; Bae, Jihyun

2018-05-01

Development of a fabric structure strain sensor has received considerable attention due to its broad application in healthcare monitoring and human–machine interfaces. In the knitted textile structure, it is critical to understand the surface structural deformation from a different body motion, inducing the electrical signal characteristics. Here, we report the electromechanical properties of the knitted glove sensing system focusing on the compressive strain behavior. Compared with the electrical response of the tensile strain, the compressive strain shows much higher sensitivity, stability, and linearity via different finger motions. Additionally, the sensor exhibits constant electrical properties after repeated cyclic tests and washing processes. The proposed knitted glove sensing system can be readily extended to a scalable and cost-effective production due to the use of a commercialized manufacturing system.

Novel Flexible Wearable Sensor Materials and Signal Processing for Vital Sign and Human Activity Monitoring.

PubMed

Servati, Amir; Zou, Liang; Wang, Z Jane; Ko, Frank; Servati, Peyman

2017-07-13

Advances in flexible electronic materials and smart textile, along with broad availability of smart phones, cloud and wireless systems have empowered the wearable technologies for significant impact on future of digital and personalized healthcare as well as consumer electronics. However, challenges related to lack of accuracy, reliability, high power consumption, rigid or bulky form factor and difficulty in interpretation of data have limited their wide-scale application in these potential areas. As an important solution to these challenges, we present latest advances in novel flexible electronic materials and sensors that enable comfortable and conformable body interaction and potential for invisible integration within daily apparel. Advances in novel flexible materials and sensors are described for wearable monitoring of human vital signs including, body temperature, respiratory rate and heart rate, muscle movements and activity. We then present advances in signal processing focusing on motion and noise artifact removal, data mining and aspects of sensor fusion relevant to future clinical applications of wearable technology.

Novel Flexible Wearable Sensor Materials and Signal Processing for Vital Sign and Human Activity Monitoring

PubMed Central

Servati, Amir; Wang, Z. Jane; Ko, Frank; Servati, Peyman

2017-01-01

Advances in flexible electronic materials and smart textile, along with broad availability of smart phones, cloud and wireless systems have empowered the wearable technologies for significant impact on future of digital and personalized healthcare as well as consumer electronics. However, challenges related to lack of accuracy, reliability, high power consumption, rigid or bulky form factor and difficulty in interpretation of data have limited their wide-scale application in these potential areas. As an important solution to these challenges, we present latest advances in novel flexible electronic materials and sensors that enable comfortable and conformable body interaction and potential for invisible integration within daily apparel. Advances in novel flexible materials and sensors are described for wearable monitoring of human vital signs including, body temperature, respiratory rate and heart rate, muscle movements and activity. We then present advances in signal processing focusing on motion and noise artifact removal, data mining and aspects of sensor fusion relevant to future clinical applications of wearable technology. PMID:28703744

Eye motion triggered self-powered mechnosensational communication system using triboelectric nanogenerator.

PubMed

Pu, Xianjie; Guo, Hengyu; Chen, Jie; Wang, Xue; Xi, Yi; Hu, Chenguo; Wang, Zhong Lin

2017-07-01

Mechnosensational human-machine interfaces (HMIs) can greatly extend communication channels between human and external devices in a natural way. The mechnosensational HMIs based on biopotential signals have been developing slowly owing to the low signal-to-noise ratio and poor stability. In eye motions, the corneal-retinal potential caused by hyperpolarization and depolarization is very weak. However, the mechanical micromotion of the skin around the corners of eyes has never been considered as a good trigger signal source. We report a novel triboelectric nanogenerator (TENG)-based micromotion sensor enabled by the coupling of triboelectricity and electrostatic induction. By using an indium tin oxide electrode and two opposite tribomaterials, the proposed flexible and transparent sensor is capable of effectively capturing eye blink motion with a super-high signal level (~750 mV) compared with the traditional electrooculogram approach (~1 mV). The sensor is fixed on a pair of glasses and applied in two real-time mechnosensational HMIs-the smart home control system and the wireless hands-free typing system with advantages of super-high sensitivity, stability, easy operation, and low cost. This TENG-based micromotion sensor is distinct and unique in its fundamental mechanism, which provides a novel design concept for intelligent sensor technique and shows great potential application in mechnosensational HMIs.

Eye motion triggered self-powered mechnosensational communication system using triboelectric nanogenerator

PubMed Central

Pu, Xianjie; Guo, Hengyu; Chen, Jie; Wang, Xue; Xi, Yi; Hu, Chenguo; Wang, Zhong Lin

2017-01-01

Mechnosensational human-machine interfaces (HMIs) can greatly extend communication channels between human and external devices in a natural way. The mechnosensational HMIs based on biopotential signals have been developing slowly owing to the low signal-to-noise ratio and poor stability. In eye motions, the corneal-retinal potential caused by hyperpolarization and depolarization is very weak. However, the mechanical micromotion of the skin around the corners of eyes has never been considered as a good trigger signal source. We report a novel triboelectric nanogenerator (TENG)–based micromotion sensor enabled by the coupling of triboelectricity and electrostatic induction. By using an indium tin oxide electrode and two opposite tribomaterials, the proposed flexible and transparent sensor is capable of effectively capturing eye blink motion with a super-high signal level (~750 mV) compared with the traditional electrooculogram approach (~1 mV). The sensor is fixed on a pair of glasses and applied in two real-time mechnosensational HMIs—the smart home control system and the wireless hands-free typing system with advantages of super-high sensitivity, stability, easy operation, and low cost. This TENG-based micromotion sensor is distinct and unique in its fundamental mechanism, which provides a novel design concept for intelligent sensor technique and shows great potential application in mechnosensational HMIs. PMID:28782029

Using Internet of Things inspired wireless sensor networks to monitor cryospheric processes

NASA Astrophysics Data System (ADS)

Hart, J. K.; Martinez, K.

2017-12-01

In order to understand how modern climate change is effecting cryospheric environments we need to monitor these remote environments. There are few measurements of current day conditions because of the logistical difficulties. In particular, the whole year needs to be monitored, as well as accessing challenging environments (such as beneath the glacier). We demonstrate from Norway, Iceland and Scotland how embedded sensors along with geophysical (GPR)and surveying data (dGPS, TLS, UAV and time-lapse photography) can be used to investigate recent dramatic environmental changes associated with climate change. This includes: i) a comparison between stable and unstable glacier retreat (the subglacial hydrology, glacier motion, englacial structure and till behaviour of a rapid subaqueous glacier break-up compared with slower terrestrial retreat); and iii) an investigation of future ground stability and greenhouse gas release associated with periglacial conditions.

Decoupled tracking and thermal monitoring of non-stationary targets.

PubMed

Tan, Kok Kiong; Zhang, Yi; Huang, Sunan; Wong, Yoke San; Lee, Tong Heng

2009-10-01

Fault diagnosis and predictive maintenance address pertinent economic issues relating to production systems as an efficient technique can continuously monitor key health parameters and trigger alerts when critical changes in these variables are detected, before they lead to system failures and production shutdowns. In this paper, we present a decoupled tracking and thermal monitoring system which can be used on non-stationary targets of closed systems such as machine tools. There are three main contributions from the paper. First, a vision component is developed to track moving targets under a monitor. Image processing techniques are used to resolve the target location to be tracked. Thus, the system is decoupled and applicable to closed systems without the need for a physical integration. Second, an infrared temperature sensor with a built-in laser for locating the measurement spot is deployed for non-contact temperature measurement of the moving target. Third, a predictive motion control system holds the thermal sensor and follows the moving target efficiently to enable continuous temperature measurement and monitoring.

Estimation of ground reaction forces and joint moments on the basis on plantar pressure insoles and wearable sensors for joint angle measurement.

PubMed

Ostaszewski, Michal; Pauk, Jolanta

2018-05-16

Gait analysis is a useful tool medical staff use to support clinical decision making. There is still an urgent need to develop low-cost and unobtrusive mobile health monitoring systems. The goal of this study was twofold. Firstly, a wearable sensor system composed of plantar pressure insoles and wearable sensors for joint angle measurement was developed. Secondly, the accuracy of the system in the measurement of ground reaction forces and joint moments was examined. The measurements included joint angles and plantar pressure distribution. To validate the wearable sensor system and examine the effectiveness of the proposed method for gait analysis, an experimental study on ten volunteer subjects was conducted. The accuracy of measurement of ground reaction forces and joint moments was validated against the results obtained from a reference motion capture system. Ground reaction forces and joint moments measured by the wearable sensor system showed a root mean square error of 1% for min. GRF and 27.3% for knee extension moment. The correlation coefficient was over 0.9, in comparison with the stationary motion capture system. The study suggests that the wearable sensor system could be recommended both for research and clinical applications outside a typical gait laboratory.

Sensor for In-Motion Continuous 3D Shape Measurement Based on Dual Line-Scan Cameras

PubMed Central

Sun, Bo; Zhu, Jigui; Yang, Linghui; Yang, Shourui; Guo, Yin

2016-01-01

The acquisition of three-dimensional surface data plays an increasingly important role in the industrial sector. Numerous 3D shape measurement techniques have been developed. However, there are still limitations and challenges in fast measurement of large-scale objects or high-speed moving objects. The innovative line scan technology opens up new potentialities owing to the ultra-high resolution and line rate. To this end, a sensor for in-motion continuous 3D shape measurement based on dual line-scan cameras is presented. In this paper, the principle and structure of the sensor are investigated. The image matching strategy is addressed and the matching error is analyzed. The sensor has been verified by experiments and high-quality results are obtained. PMID:27869731

A flexible wearable sensor for knee flexion assessment during gait.

PubMed

Papi, Enrica; Bo, Yen Nee; McGregor, Alison H

2018-05-01

Gait analysis plays an important role in the diagnosis and management of patients with movement disorders but it is usually performed within a laboratory. Recently interest has shifted towards the possibility of conducting gait assessments in everyday environments thus facilitating long-term monitoring. This is possible by using wearable technologies rather than laboratory based equipment. This study aims to validate a novel wearable sensor system's ability to measure peak knee sagittal angles during gait. The proposed system comprises a flexible conductive polymer unit interfaced with a wireless acquisition node attached over the knee on a pair of leggings. Sixteen healthy volunteers participated to two gait assessments on separate occasions. Data was simultaneously collected from the novel sensor and a gold standard 10 camera motion capture system. The relationship between sensor signal and reference knee flexion angles was defined for each subject to allow the transformation of sensor voltage outputs to angular measures (degrees). The knee peak flexion angle from the sensor and reference system were compared by means of root mean square error (RMSE), absolute error, Bland-Altman plots and intra-class correlation coefficients (ICCs) to assess test-retest reliability. Comparisons of knee peak flexion angles calculated from the sensor and gold standard yielded an absolute error of 0.35(±2.9°) and RMSE of 1.2(±0.4)°. Good agreement was found between the two systems with the majority of data lying within the limits of agreement. The sensor demonstrated high test-retest reliability (ICCs>0.8). These results show the ability of the sensor to monitor knee peak sagittal angles with small margins of error and in agreement with the gold standard system. The sensor has potential to be used in clinical settings as a discreet, unobtrusive wearable device allowing for long-term gait analysis. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Wideband Motion Control by Position and Acceleration Input Based Disturbance Observer

NASA Astrophysics Data System (ADS)

Irie, Kouhei; Katsura, Seiichiro; Ohishi, Kiyoshi

The disturbance observer can observe and suppress the disturbance torque within its bandwidth. Recent motion systems begin to spread in the society and they are required to have ability to contact with unknown environment. Such a haptic motion requires much wider bandwidth. However, since the conventional disturbance observer attains the acceleration response by the second order derivative of position response, the bandwidth is limited due to the derivative noise. This paper proposes a novel structure of a disturbance observer. The proposed disturbance observer uses an acceleration sensor for enlargement of bandwidth. Generally, the bandwidth of an acceleration sensor is from 1Hz to more than 1kHz. To cover DC range, the conventional position sensor based disturbance observer is integrated. Thus, the performance of the proposed Position and Acceleration input based disturbance observer (PADO) is superior to the conventional one. The PADO is applied to position control (infinity stiffness) and force control (zero stiffness). The numerical and experimental results show viability of the proposed method.

Cascade and parallel combination (CPC) of adaptive filters for estimating heart rate during intensive physical exercise from photoplethysmographic signal

PubMed Central

Islam, Mohammad Tariqul; Tanvir Ahmed, Sk.; Zabir, Ishmam; Shahnaz, Celia

2018-01-01

Photoplethysmographic (PPG) signal is getting popularity for monitoring heart rate in wearable devices because of simplicity of construction and low cost of the sensor. The task becomes very difficult due to the presence of various motion artefacts. In this study, an algorithm based on cascade and parallel combination (CPC) of adaptive filters is proposed in order to reduce the effect of motion artefacts. First, preliminary noise reduction is performed by averaging two channel PPG signals. Next in order to reduce the effect of motion artefacts, a cascaded filter structure consisting of three cascaded adaptive filter blocks is developed where three-channel accelerometer signals are used as references to motion artefacts. To further reduce the affect of noise, a scheme based on convex combination of two such cascaded adaptive noise cancelers is introduced, where two widely used adaptive filters namely recursive least squares and least mean squares filters are employed. Heart rates are estimated from the noise reduced PPG signal in spectral domain. Finally, an efficient heart rate tracking algorithm is designed based on the nature of the heart rate variability. The performance of the proposed CPC method is tested on a widely used public database. It is found that the proposed method offers very low estimation error and a smooth heart rate tracking with simple algorithmic approach. PMID:29515812

Modeling and Implementation of PID Control for Autonomous Robots

DTIC Science & Technology

2007-06-01

2 Figure 2. Bigfoot ...guidance, 802.11 wireless communications, and a motion triggered camera to monitor an area for IED placement. LT John Herkamp’s Bigfoot (Figure 2) is...designed to disable IED’s. Bigfoot includes the same obstacle avoidance software and sensors, but has a controllable arm to carry a counter charge

Practical Approaches to Prescribing Physical Activity and Monitoring Exercise Intensity.

PubMed

Reed, Jennifer L; Pipe, Andrew L

2016-04-01

Regular physical activity helps to prevent heart disease, and reduces the risk of first or subsequent cardiovascular events. It is recommended that Canadian adults accumulate at least 150 minutes of moderate- to vigorous-intensity aerobic exercise per week, in bouts of 10 minutes or more, and perform muscle- and bone-strengthening activities at least 2 days per week. Individual exercise prescriptions can be developed using the frequency, intensity, time, and type principles. Increasing evidence suggests that high-intensity interval training is efficacious for a broad spectrum of heart health outcomes. Several practical approaches to prescribing and monitoring exercise intensity exist including: heart rate monitoring, the Borg rating of perceived exertion scale, the Talk Test, and, motion sensors. The Borg rating of perceived exertion scale matches a numerical value to an individual's perception of effort, and can also be used to estimate heart rate. The Talk Test, the level at which simple conversation is possible, can be used to monitor desired levels of moderate- to vigorous-intensity exercise. Motion sensors can provide users with practical and useful exercise training information to aid in meeting current exercise recommendations. These approaches can be used by the public, exercise scientists, and clinicians to easily and effectively guide physical activity in a variety of settings. Copyright © 2016 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.

A multi-channel opto-electronic sensor to accurately monitor heart rate against motion artefact during exercise.

PubMed

Alzahrani, Abdullah; Hu, Sijung; Azorin-Peris, Vicente; Barrett, Laura; Esliger, Dale; Hayes, Matthew; Akbare, Shafique; Achart, Jérôme; Kuoch, Sylvain

2015-10-12

This study presents the use of a multi-channel opto-electronic sensor (OEPS) to effectively monitor critical physiological parameters whilst preventing motion artefact as increasingly demanded by personal healthcare. The aim of this work was to study how to capture the heart rate (HR) efficiently through a well-constructed OEPS and a 3-axis accelerometer with wireless communication. A protocol was designed to incorporate sitting, standing, walking, running and cycling. The datasets collected from these activities were processed to elaborate sport physiological effects. t-test, Bland-Altman Agreement (BAA), and correlation to evaluate the performance of the OEPS were used against Polar and Mio-Alpha HR monitors. No differences in the HR were found between OEPS, and either Polar or Mio-Alpha (both p > 0.05); a strong correlation was found between Polar and OEPS (r: 0.96, p < 0.001); the bias of BAA 0.85 bpm, the standard deviation (SD) 9.20 bpm, and the limits of agreement (LOA) from -17.18 bpm to +18.88 bpm. For the Mio-Alpha and OEPS, a strong correlation was found (r: 0.96, p < 0.001); the bias of BAA 1.63 bpm, SD 8.62 bpm, LOA from -15.27 bpm to +18.58 bpm. These results demonstrate the OEPS to be capable of carrying out real time and remote monitoring of heart rate.

Inertial Sensor-Based Motion Analysis of Lower Limbs for Rehabilitation Treatments

PubMed Central

Sun, Tongyang; Duan, Lihong; Wang, Yulong

2017-01-01

The hemiplegic rehabilitation state diagnosing performed by therapists can be biased due to their subjective experience, which may deteriorate the rehabilitation effect. In order to improve this situation, a quantitative evaluation is proposed. Though many motion analysis systems are available, they are too complicated for practical application by therapists. In this paper, a method for detecting the motion of human lower limbs including all degrees of freedom (DOFs) via the inertial sensors is proposed, which permits analyzing the patient's motion ability. This method is applicable to arbitrary walking directions and tracks of persons under study, and its results are unbiased, as compared to therapist qualitative estimations. Using the simplified mathematical model of a human body, the rotation angles for each lower limb joint are calculated from the input signals acquired by the inertial sensors. Finally, the rotation angle versus joint displacement curves are constructed, and the estimated values of joint motion angle and motion ability are obtained. The experimental verification of the proposed motion detection and analysis method was performed, which proved that it can efficiently detect the differences between motion behaviors of disabled and healthy persons and provide a reliable quantitative evaluation of the rehabilitation state. PMID:29065575

Structural health monitoring system of soccer arena based on optical sensors

NASA Astrophysics Data System (ADS)

Shishkin, Victor V.; Churin, Alexey E.; Kharenko, Denis S.; Zheleznova, Maria A.; Shelemba, Ivan S.

2014-05-01

A structural health monitoring system based on optical sensors has been developed and installed on the indoor soccer arena "Zarya" in Novosibirsk. The system integrates 119 fiber optic sensors: 85 strain, 32 temperature and 2 displacement sensors. In addition, total station is used for measuring displacement in 45 control points. All of the constituents of the supporting structure are subjects for monitoring: long-span frames with under floor ties, connections, purlins and foundation.

Screen printing of a capacitive cantilever-based motion sensor on fabric using a novel sacrificial layer process for smart fabric applications

NASA Astrophysics Data System (ADS)

Wei, Yang; Torah, Russel; Yang, Kai; Beeby, Steve; Tudor, John

2013-07-01

Free-standing cantilevers have been fabricated by screen printing sacrificial and structural layers onto a standard polyester cotton fabric. By printing additional conductive layers, a complete capacitive motion sensor on fabric using only screen printing has been fabricated. This type of free-standing structure cannot currently be fabricated using conventional fabric manufacturing processes. In addition, compared to conventional smart fabric fabrication processes (e.g. weaving and knitting), screen printing offers the advantages of geometric design flexibility and the ability to simultaneously print multiple devices of the same or different designs. Furthermore, a range of active inks exists from the printed electronics industry which can potentially be applied to create many types of smart fabric. Four cantilevers with different lengths have been printed on fabric using a five-layer structure with a sacrificial material underneath the cantilever. The sacrificial layer is subsequently removed at 160 °C for 30 min to achieve a freestanding cantilever above the fabric. Two silver electrodes, one on top of the cantilever and the other on top of the fabric, are used to capacitively detect the movement of the cantilever. In this way, an entirely printed motion sensor is produced on a standard fabric. The motion sensor was initially tested on an electromechanical shaker rig at a low frequency range to examine the linearity and the sensitivity of each design. Then, these sensors were individually attached to a moving human forearm to evaluate more representative results. A commercial accelerometer (Microstrain G-link) was mounted alongside for comparison. The printed sensors have a similar motion response to the commercial accelerometer, demonstrating the potential of a printed smart fabric motion sensor for use in intelligent clothing applications.

A Sensor Fusion Method for Tracking Vertical Velocity and Height Based on Inertial and Barometric Altimeter Measurements

PubMed Central

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-01-01

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04–0.24 m/s; height RMSE was in the range 5–68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions. PMID:25061835

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

PubMed Central

Filippeschi, Alessandro; Schmitz, Norbert; Miezal, Markus; Bleser, Gabriele; Ruffaldi, Emanuele; Stricker, Didier

2017-01-01

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error). PMID:28587178

Early-age monitoring of cement structures using FBG sensors

NASA Astrophysics Data System (ADS)

Wang, Chuan; Zhou, Zhi; Zhang, Zhichun; Ou, Jinping

2006-03-01

With more and more broad applications of the cement-based structures such as neat cement paste, cement mortar and concrete in civil engineering, people hope to find out what their performances should like. The in-service performances of cement-based structures are highly affected by their hardening process during the early-age. But it is still a big problem for traditional sensors to be used to monitor the early curing of cement-based structures due to such disadvantages as difficulties to install sensors inside the concrete, limited measuring points, poor durability and interference of electromagnetic wave and so on. In this paper, according to the sensing properties of the Fiber Bragg Grating sensors and self-characters of the cement-based structures, we have successfully finished measuring and monitoring the early-age inner-strain and temperature changes of the neat cement paste, concrete with and without restrictions, mass concrete structures and negative concrete, respectively. Three types of FBG-based sensors have been developed to monitor the cement-based structures. Besides, the installation techniques and the embedding requirements of FBG sensors in cement-based structures are also discussed. Moreover, such kind of technique has been used in practical structure, 3rd Nanjing Yangtze Bridge, and the results show that FBG sensors are well proper for measuring and monitoring the temperature and strain changes including self-shrinkage, dry shrinkage, plastic shrinkage, temperature expansion, frost heaving and so on inside different cement-based structures. This technique provides us a new useful measuring method on early curing monitoring of cement-based structures and greater understanding of details of their hardening process.

Samba: a real-time motion capture system using wireless camera sensor networks.

PubMed

Oh, Hyeongseok; Cha, Geonho; Oh, Songhwai

2014-03-20

There is a growing interest in 3D content following the recent developments in 3D movies, 3D TVs and 3D smartphones. However, 3D content creation is still dominated by professionals, due to the high cost of 3D motion capture instruments. The availability of a low-cost motion capture system will promote 3D content generation by general users and accelerate the growth of the 3D market. In this paper, we describe the design and implementation of a real-time motion capture system based on a portable low-cost wireless camera sensor network. The proposed system performs motion capture based on the data-driven 3D human pose reconstruction method to reduce the computation time and to improve the 3D reconstruction accuracy. The system can reconstruct accurate 3D full-body poses at 16 frames per second using only eight markers on the subject's body. The performance of the motion capture system is evaluated extensively in experiments.

Samba: A Real-Time Motion Capture System Using Wireless Camera Sensor Networks

PubMed Central

Oh, Hyeongseok; Cha, Geonho; Oh, Songhwai

2014-01-01

There is a growing interest in 3D content following the recent developments in 3D movies, 3D TVs and 3D smartphones. However, 3D content creation is still dominated by professionals, due to the high cost of 3D motion capture instruments. The availability of a low-cost motion capture system will promote 3D content generation by general users and accelerate the growth of the 3D market. In this paper, we describe the design and implementation of a real-time motion capture system based on a portable low-cost wireless camera sensor network. The proposed system performs motion capture based on the data-driven 3D human pose reconstruction method to reduce the computation time and to improve the 3D reconstruction accuracy. The system can reconstruct accurate 3D full-body poses at 16 frames per second using only eight markers on the subject's body. The performance of the motion capture system is evaluated extensively in experiments. PMID:24658618

Fiber Bragg grating sensors for real-time monitoring of evacuation process

NASA Astrophysics Data System (ADS)

Guru Prasad, A. S.; Hegde, Gopalkrishna M.; Asokan, S.

2010-03-01

Fiber bragg grating (FBG) sensors have been widely used for number of sensing applications like temperature, pressure, acousto-ultrasonic, static and dynamic strain, refractive index change measurements and so on. Present work demonstrates the use of FBG sensors in in-situ measurement of vacuum process with simultaneous leak detection capability. Experiments were conducted in a bell jar vacuum chamber facilitated with conventional Pirani gauge for vacuum measurement. Three different experiments have been conducted to validate the performance of FBG sensor in monitoring vacuum creating process and air bleeding. The preliminary results of FBG sensors in vacuum monitoring have been compared with that of commercial Pirani gauge sensor. This novel technique offers a simple alternative to conventional method for real time monitoring of evacuation process. Proposed FBG based vacuum sensor has potential applications in vacuum systems involving hazardous environment such as chemical and gas plants, automobile industries, aeronautical establishments and leak monitoring in process industries, where the electrical or MEMS based sensors are prone to explosion and corrosion.

Wireless Sensor Network Based Subsurface Contaminant Plume Monitoring

DTIC Science & Technology

2012-04-16

Sensor Network (WSN) to monitor contaminant plume movement in naturally heterogeneous subsurface formations to advance the sensor networking based...time to assess the source and predict future plume behavior. This proof-of-concept research aimed at demonstrating the use of an intelligent Wireless

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Kohler, M. D.; Heaton, T. H.; Massari, A.; Guy, R.; Bunn, J.; Chandy, M.

2015-12-01

The CSN now has approximately 600 stations in the northern Los Angeles region. The sensors are class-C MEMs accelerometers that are packaged with backup power and data memory and are connected to a cloud-based processing system through the Internet. Most of the sensors are located in an xy-spatial network with an average minimum station spacing of 800 m. This density allows the lateral variations in ground motion to be determined, which will lead to detailed microzonation maps of the region. Approximately 100 of the sensors are located on campuses of the Los Angeles Unified School District (LAUSD), and this is part of a plan to provide schools with critical earthquake information immediately following an earthquake using the ShakeCast system. The software system in the sensors is being upgraded to allow on site measurements of PGA and PVA to be sent directly to the ShakeMap and earthquake early warning systems. More than 160 of the sensor packages are located on multiple floors of buildings with typically one or two 3-component sensors per floor. With these data we can identify traveling waves in the building, as well as determine the eigenfrequencies and mode shapes. By monitoring these quantities with high spatial density before, during, and after a major shaking event, we hope to determine the state of health of the structure.

IMU-Based Gait Recognition Using Convolutional Neural Networks and Multi-Sensor Fusion.

PubMed

Dehzangi, Omid; Taherisadr, Mojtaba; ChangalVala, Raghvendar

2017-11-27

The wide spread usage of wearable sensors such as in smart watches has provided continuous access to valuable user generated data such as human motion that could be used to identify an individual based on his/her motion patterns such as, gait. Several methods have been suggested to extract various heuristic and high-level features from gait motion data to identify discriminative gait signatures and distinguish the target individual from others. However, the manual and hand crafted feature extraction is error prone and subjective. Furthermore, the motion data collected from inertial sensors have complex structure and the detachment between manual feature extraction module and the predictive learning models might limit the generalization capabilities. In this paper, we propose a novel approach for human gait identification using time-frequency (TF) expansion of human gait cycles in order to capture joint 2 dimensional (2D) spectral and temporal patterns of gait cycles. Then, we design a deep convolutional neural network (DCNN) learning to extract discriminative features from the 2D expanded gait cycles and jointly optimize the identification model and the spectro-temporal features in a discriminative fashion. We collect raw motion data from five inertial sensors placed at the chest, lower-back, right hand wrist, right knee, and right ankle of each human subject synchronously in order to investigate the impact of sensor location on the gait identification performance. We then present two methods for early (input level) and late (decision score level) multi-sensor fusion to improve the gait identification generalization performance. We specifically propose the minimum error score fusion (MESF) method that discriminatively learns the linear fusion weights of individual DCNN scores at the decision level by minimizing the error rate on the training data in an iterative manner. 10 subjects participated in this study and hence, the problem is a 10-class identification task. Based on our experimental results, 91% subject identification accuracy was achieved using the best individual IMU and 2DTF-DCNN. We then investigated our proposed early and late sensor fusion approaches, which improved the gait identification accuracy of the system to 93.36% and 97.06%, respectively.

Motion estimation accuracy for visible-light/gamma-ray imaging fusion for portable portal monitoring

NASA Astrophysics Data System (ADS)

Karnowski, Thomas P.; Cunningham, Mark F.; Goddard, James S.; Cheriyadat, Anil M.; Hornback, Donald E.; Fabris, Lorenzo; Kerekes, Ryan A.; Ziock, Klaus-Peter; Gee, Timothy F.

2010-01-01

The use of radiation sensors as portal monitors is increasing due to heightened concerns over the smuggling of fissile material. Portable systems that can detect significant quantities of fissile material that might be present in vehicular traffic are of particular interest. We have constructed a prototype, rapid-deployment portal gamma-ray imaging portal monitor that uses machine vision and gamma-ray imaging to monitor multiple lanes of traffic. Vehicles are detected and tracked by using point detection and optical flow methods as implemented in the OpenCV software library. Points are clustered together but imperfections in the detected points and tracks cause errors in the accuracy of the vehicle position estimates. The resulting errors cause a "blurring" effect in the gamma image of the vehicle. To minimize these errors, we have compared a variety of motion estimation techniques including an estimate using the median of the clustered points, a "best-track" filtering algorithm, and a constant velocity motion estimation model. The accuracy of these methods are contrasted and compared to a manually verified ground-truth measurement by quantifying the rootmean- square differences in the times the vehicles cross the gamma-ray image pixel boundaries compared with a groundtruth manual measurement.

Feasibility study of patient motion monitoring by using tactile array sensors

NASA Astrophysics Data System (ADS)

Kim, Tae-Ho; Kang, Seong-Hee; Kim, Dong-Su; Cho, Min-Seok; Kim, Kyeong-Hyeon; Suh, Tae-Suk; Kim, Siyong

2015-07-01

An ideal alignment method based on the external anatomical surface of the patient should consider the entire region of interest. However, optical-camera-based systems cannot blindly monitor such areas as the patient's back, for example. Furthermore, collecting enough information to correct the associated deformation error is impossible. The study aim is to propose a new patient alignment method using tactile array sensors that can measure the distributed pressure profiles along the contact surface. The TactArray system includes one sensor, a signal-conditioning device (USB drive/interface electronics, power supply, and cables), and a PC. The tactile array sensor was placed between the patient's back and the treatment couch, and the deformations at different location on the patient's back were evaluated. Three healthy male volunteers were enrolled in this study, and pressure profile distributions (PPDs) were obtained with and without immobilization. After the initial pretreatment setup using the laser alignment system, the PPD of the patient's back was acquired. The results were obtained at four different times and included a reference PPD dataset. The contact area and the center-of-pressure value were also acquired based on the PPD data for a more elaborate quantitative data analysis. To evaluate the clinical feasibility of using the proposed alignment method for reducing the deformation error, we implemented a real-time self-correction procedure. Despite the initial alignment, we confirmed that PPD variations existed in both cases of the volunteer studies (with and without the use of the immobilization tool). Additionally, we confirmed that the contact area and the center of pressure varied in both cases, and those variations were observed in all three volunteers. With the proposed alignment method and the real-time selfcorrection procedure, the deformation error was significantly reduced. The proposed alignment method can be used to account for the limitation of the camera-based system and to improve the accuracy of the external surface-based patient setup.

A wireless smart sensor network for automated monitoring of cable tension

NASA Astrophysics Data System (ADS)

Sim, Sung-Han; Li, Jian; Jo, Hongki; Park, Jong-Woong; Cho, Soojin; Spencer, Billie F., Jr.; Jung, Hyung-Jo

2014-02-01

As cables are primary load carrying members in cable-stayed bridges, monitoring the tension forces of the cables provides valuable information regarding structural soundness. Incorporating wireless smart sensors with vibration-based tension estimation methods provides an efficient means of autonomous long-term monitoring of cable tensions. This study develops a wireless cable tension monitoring system using MEMSIC’s Imote2 smart sensors. The monitoring system features autonomous operation, sustainable energy harvesting and power consumption, and remote access using the internet. To obtain the tension force, an in-network data processing strategy associated with the vibration-based tension estimation method is implemented on the Imote2-based sensor network, significantly reducing the wireless data transmission and the power consumption. The proposed monitoring system has been deployed and validated on the Jindo Bridge, a cable-stayed bridge located in South Korea.

Wearable sensors for health monitoring

NASA Astrophysics Data System (ADS)

Suciu, George; Butca, Cristina; Ochian, Adelina; Halunga, Simona

2015-02-01

In this paper we describe several wearable sensors, designed for monitoring the health condition of the patients, based on an experimental model. Wearable sensors enable long-term continuous physiological monitoring, which is important for the treatment and management of many chronic illnesses, neurological disorders, and mental health issues. The system is based on a wearable sensors network, which is connected to a computer or smartphone. The wearable sensor network integrates several wearable sensors that can measure different parameters such as body temperature, heart rate and carbon monoxide quantity from the air. After the portable sensors measuring parameter values, they are transmitted by microprocessor through the Bluetooth to the application developed on computer or smartphone, to be interpreted.

Advanced Networks in Motion Mobile Sensorweb

NASA Technical Reports Server (NTRS)

Ivancic, William D.; Stewart, David H.

2011-01-01

Advanced mobile networking technology applicable to mobile sensor platforms was developed, deployed and demonstrated. A two-tier sensorweb design was developed. The first tier utilized mobile network technology to provide mobility. The second tier, which sits above the first tier, utilizes 6LowPAN (Internet Protocol version 6 Low Power Wireless Personal Area Networks) sensors. The entire network was IPv6 enabled. Successful mobile sensorweb system field tests took place in late August and early September of 2009. The entire network utilized IPv6 and was monitored and controlled using a remote Web browser via IPv6 technology. This paper describes the mobile networking and 6LowPAN sensorweb design, implementation, deployment and testing as well as wireless systems and network monitoring software developed to support testing and validation.

Tattoo-based potentiometric ion-selective sensors for epidermal pH monitoring.

PubMed

Bandodkar, Amay J; Hung, Vinci W S; Jia, Wenzhao; Valdés-Ramírez, Gabriela; Windmiller, Joshua R; Martinez, Alexandra G; Ramírez, Julian; Chan, Garrett; Kerman, Kagan; Wang, Joseph

2013-01-07

This article presents the fabrication and characterization of novel tattoo-based solid-contact ion-selective electrodes (ISEs) for non-invasive potentiometric monitoring of epidermal pH levels. The new fabrication approach combines commercially available temporary transfer tattoo paper with conventional screen printing and solid-contact polymer ISE methodologies. The resulting tattoo-based potentiometric sensors exhibit rapid and sensitive response to a wide range of pH changes with no carry-over effects. Furthermore, the tattoo ISE sensors endure repetitive mechanical deformation, which is a key requirement of wearable and epidermal sensors. The flexible and conformal nature of the tattoo sensors enable them to be mounted on nearly any exposed skin surface for real-time pH monitoring of the human perspiration, as illustrated from the response during a strenuous physical activity. The resulting tattoo-based ISE sensors offer considerable promise as wearable potentiometric sensors suitable for diverse applications.

An experimental protocol for the definition of upper limb anatomical frames on children using magneto-inertial sensors.

PubMed

Ricci, L; Formica, D; Tamilia, E; Taffoni, F; Sparaci, L; Capirci, O; Guglielmelli, E

2013-01-01

Motion capture based on magneto-inertial sensors is a technology enabling data collection in unstructured environments, allowing "out of the lab" motion analysis. This technology is a good candidate for motion analysis of children thanks to the reduced weight and size as well as the use of wireless communication that has improved its wearability and reduced its obtrusivity. A key issue in the application of such technology for motion analysis is its calibration, i.e. a process that allows mapping orientation information from each sensor to a physiological reference frame. To date, even if there are several calibration procedures available for adults, no specific calibration procedures have been developed for children. This work addresses this specific issue presenting a calibration procedure for motion capture of thorax and upper limbs on healthy children. Reported results suggest comparable performance with similar studies on adults and emphasize some critical issues, opening the way to further improvements.

Gravity Compensation Method for Combined Accelerometer and Gyro Sensors Used in Cardiac Motion Measurements.

PubMed

Krogh, Magnus Reinsfelt; Nghiem, Giang M; Halvorsen, Per Steinar; Elle, Ole Jakob; Grymyr, Ole-Johannes; Hoff, Lars; Remme, Espen W

2017-05-01

A miniaturized accelerometer fixed to the heart can be used for monitoring of cardiac function. However, an accelerometer cannot differentiate between acceleration caused by motion and acceleration due to gravity. The accuracy of motion measurements is therefore dependent on how well the gravity component can be estimated and filtered from the measured signal. In this study we propose a new method for estimating the gravity, based on strapdown inertial navigation, using a combined accelerometer and gyro. The gyro was used to estimate the orientation of the gravity field and thereby remove it. We compared this method with two previously proposed gravity filtering methods in three experimental models using: (1) in silico computer simulated heart motion; (2) robot mimicked heart motion; and (3) in vivo measured motion on the heart in an animal model. The new method correlated excellently with the reference (r 2  > 0.93) and had a deviation from reference peak systolic displacement (6.3 ± 3.9 mm) below 0.2 ± 0.5 mm for the robot experiment model. The new method performed significantly better than the two previously proposed methods (p < 0.001). The results show that the proposed method using gyro can measure cardiac motion with high accuracy and performs better than existing methods for filtering the gravity component from the accelerometer signal.

Adaptive Environmental Source Localization and Tracking with Unknown Permittivity and Path Loss Coefficients †

PubMed Central

Fidan, Barış; Umay, Ilknur

2015-01-01

Accurate signal-source and signal-reflector target localization tasks via mobile sensory units and wireless sensor networks (WSNs), including those for environmental monitoring via sensory UAVs, require precise knowledge of specific signal propagation properties of the environment, which are permittivity and path loss coefficients for the electromagnetic signal case. Thus, accurate estimation of these coefficients has significant importance for the accuracy of location estimates. In this paper, we propose a geometric cooperative technique to instantaneously estimate such coefficients, with details provided for received signal strength (RSS) and time-of-flight (TOF)-based range sensors. The proposed technique is integrated to a recursive least squares (RLS)-based adaptive localization scheme and an adaptive motion control law, to construct adaptive target localization and adaptive target tracking algorithms, respectively, that are robust to uncertainties in aforementioned environmental signal propagation coefficients. The efficiency of the proposed adaptive localization and tracking techniques are both mathematically analysed and verified via simulation experiments. PMID:26690441

Biosensors based on cantilevers.

PubMed

Alvarez, Mar; Carrascosa, Laura G; Zinoviev, Kiril; Plaza, Jose A; Lechuga, Laura M

2009-01-01

Microcantilevers based-biosensors are a new label-free technique that allows the direct detection of biomolecular interactions in a label-less way and with great accuracy by translating the biointeraction into a nanomechanical motion. Low cost and reliable standard silicon technologies are widely used for the fabrication of cantilevers with well-controlled mechanical properties. Over the last years, the number of applications of these sensors has shown a fast growth in diverse fields, such as genomic or proteomic, because of the biosensor flexibility, the low sample consumption, and the non-pretreated samples required. In this chapter, we report a dedicated design and a fabrication process of highly sensitive microcantilever silicon sensors. We will describe as well an application of the device in the environmental field showing the immunodetection of an organic toxic pesticide as an example. The cantilever biofunctionalization process and the subsequent pesticide determination are detected in real time by monitoring the nanometer-scale bending of the microcantilever due to a differential surface stress generated between both surfaces of the device.

Monitoring system of hydraulic lifting device based on the fiber optic sensors

NASA Astrophysics Data System (ADS)

Fajkus, Marcel; Nedoma, Jan; Novak, Martin; Martinek, Radek; Vanus, Jan; Mec, Pavel; Vasinek, Vladimir

2017-10-01

This article deals with the description of the monitoring system of hydraulic lifting device based on the fiber-optic sensors. For minimize the financial costs of the proposed monitoring system, the power evaluation of measured signal has been chosen. The solution is based on an evaluation of the signal obtained using the single point optic fiber sensors with overlapping reflective spectra. For encapsulation of the sensors was used polydimethylsiloxane (PDMS) polymer. To obtain a information of loading is uses the action of deformation of the lifting device on the pair single point optic fiber sensors mounted on the lifting device of the tested car. According to the proposed algorithm is determined information of pressure with an accuracy of +/- 5 %. Verification of the proposed system was realized on the various types of the tested car with different loading. The original contribution of the paper is to verify the new low-cost system for monitoring the hydraulic lifting device based on the fiber-optic sensors.

Hybrid wireless sensor network for rescue site monitoring after earthquake

NASA Astrophysics Data System (ADS)

Wang, Rui; Wang, Shuo; Tang, Chong; Zhao, Xiaoguang; Hu, Weijian; Tan, Min; Gao, Bowei

2016-07-01

This paper addresses the design of a low-cost, low-complexity, and rapidly deployable wireless sensor network (WSN) for rescue site monitoring after earthquakes. The system structure of the hybrid WSN is described. Specifically, the proposed hybrid WSN consists of two kinds of wireless nodes, i.e., the monitor node and the sensor node. Then the mechanism and the system configuration of the wireless nodes are detailed. A transmission control protocol (TCP)-based request-response scheme is proposed to allow several monitor nodes to communicate with the monitoring center. UDP-based image transmission algorithms with fast recovery have been developed to meet the requirements of in-time delivery of on-site monitor images. In addition, the monitor node contains a ZigBee module that used to communicate with the sensor nodes, which are designed with small dimensions to monitor the environment by sensing different physical properties in narrow spaces. By building a WSN using these wireless nodes, the monitoring center can display real-time monitor images of the monitoring area and visualize all collected sensor data on geographic information systems. In the end, field experiments were performed at the Training Base of Emergency Seismic Rescue Troops of China and the experimental results demonstrate the feasibility and effectiveness of the monitor system.

A stretchable strain sensor based on a metal nanoparticle thin film for human motion detection

NASA Astrophysics Data System (ADS)

Lee, Jaehwan; Kim, Sanghyeok; Lee, Jinjae; Yang, Daejong; Park, Byong Chon; Ryu, Seunghwa; Park, Inkyu

2014-09-01

Wearable strain sensors for human motion detection are being highlighted in various fields such as medical, entertainment and sports industry. In this paper, we propose a new type of stretchable strain sensor that can detect both tensile and compressive strains and can be fabricated by a very simple process. A silver nanoparticle (Ag NP) thin film patterned on the polydimethylsiloxane (PDMS) stamp by a single-step direct transfer process is used as the strain sensing material. The working principle is the change in the electrical resistance caused by the opening/closure of micro-cracks under mechanical deformation. The fabricated stretchable strain sensor shows highly sensitive and durable sensing performances in various tensile/compressive strains, long-term cyclic loading and relaxation tests. We demonstrate the applications of our stretchable strain sensors such as flexible pressure sensors and wearable human motion detection devices with high sensitivity, response speed and mechanical robustness.Wearable strain sensors for human motion detection are being highlighted in various fields such as medical, entertainment and sports industry. In this paper, we propose a new type of stretchable strain sensor that can detect both tensile and compressive strains and can be fabricated by a very simple process. A silver nanoparticle (Ag NP) thin film patterned on the polydimethylsiloxane (PDMS) stamp by a single-step direct transfer process is used as the strain sensing material. The working principle is the change in the electrical resistance caused by the opening/closure of micro-cracks under mechanical deformation. The fabricated stretchable strain sensor shows highly sensitive and durable sensing performances in various tensile/compressive strains, long-term cyclic loading and relaxation tests. We demonstrate the applications of our stretchable strain sensors such as flexible pressure sensors and wearable human motion detection devices with high sensitivity, response speed and mechanical robustness. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr03295k

DNA Encoding Training Using 3D Gesture Interaction.

PubMed

Nicola, Stelian; Handrea, Flavia-Laura; Crişan-Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara

2017-01-01

The work described in this paper summarizes the development process and presents the results of a human genetics training application, studying the 20 amino acids formed by the combination of the 3 nucleotides of DNA targeting mainly medical and bioinformatics students. Currently, the domain applications using recognized human gestures of the Leap Motion sensor are used in molecules controlling and learning from Mendeleev table or in visualizing the animated reactions of specific molecules with water. The novelty in the current application consists in using the Leap Motion sensor creating new gestures for the application control and creating a tag based algorithm corresponding to each amino acid, depending on the position in the 3D virtual space of the 4 nucleotides of DNA and their type. The team proposes a 3D application based on Unity editor and on Leap Motion sensor where the user has the liberty of forming different combinations of the 20 amino acids. The results confirm that this new type of study of medicine/biochemistry using the Leap Motion sensor for handling amino acids is suitable for students. The application is original and interactive and the users can create their own amino acid structures in a 3D-like environment which they could not do otherwise using traditional pen-and-paper.

Design and development of LED-based irregular leather area measuring machine

NASA Astrophysics Data System (ADS)

Adil, Rehan; Khan, Sarah Jamal

2012-01-01

Using optical sensor array, a precision motion control system in a conveyer follows the irregular shaped leather sheet to measure its surface area. In operation, irregular shaped leather sheet passes on conveyer belt and optical sensor array detects the leather sheet edge. In this way outside curvature of the leather sheet is detected and is then feed to the controller to measure its approximate area. Such system can measure irregular shapes, by neglecting rounded corners, ellipses etc. To minimize the error in calculating surface area of irregular curve to the above mentioned system, the motion control system only requires the footprint of the optical sensor to be small and the distance between the sensors is to be minimized. In the proposed technique surface area measurement of irregular shaped leather sheet is done by defining velocity and detecting position of the move. The motion controller takes the information and creates the necessary edge profile on point-to-point bases. As a result irregular shape of leather sheet is mapped and is then feed to the controller to calculate surface area.

Motorized CPM/CAM physiotherapy device with sliding-mode Fuzzy Neural Network control loop.

PubMed

Ho, Hung-Jung; Chen, Tien-Chi

2009-11-01

Continuous passive motion (CPM) and controllable active motion (CAM) physiotherapy devices promote rehabilitation of damaged joints. This paper presents a computerized CPM/CAM system that obviates the need for mechanical resistance devices such as springs. The system is controlled by a computer which performs sliding-mode Fuzzy Neural Network (FNN) calculations online. CAM-type resistance force is generated by the active performance of an electric motor which is controlled so as to oppose the motion of the patient's leg. A force sensor under the patient's foot on the device pedal provides data for feedback in a sliding-mode FNN control loop built around the motor. Via an active impedance control feedback system, the controller drives the motor to behave similarly to a damped spring by generating and controlling the amplitude and direction of the pedal force in relation to the patient's leg. Experiments demonstrate the high sensitivity and speed of the device. The PC-based feedback nature of the control loop means that sophisticated auto-adaptable CPM/CAM custom-designed physiotherapy becomes possible. The computer base also allows extensive data recording, data analysis and network-connected remote patient monitoring.

Turbulence Measurements from Compliant Moorings. Part II: Motion Correction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kilcher, Levi F.; Thomson, Jim; Harding, Samuel

2017-06-01

Acoustic Doppler velocimeters (ADVs) are a valuable tool for making highprecision measurements of turbulence, and moorings are a convenient and ubiquitous platform for making many kinds of measurements in the ocean. However—because of concerns that mooring motion can contaminate turbulence measurements and acoustic Doppler profilers are relatively easy to deploy—ADVs are not frequently deployed from moorings. This work details a method for measuring turbulence using moored ADVs that corrects for mooring motion using measurements from inertial motion sensors. Three distinct mooring platforms were deployed in a tidal channel with inertial motion-sensor-equipped ADVs. In each case, the motion correction based onmore » the inertial measurements dramatically reduced contamination from mooring motion. The spectra from these measurements have a shape that is consistent with other measurements in tidal channels, and have a f^(5/3) slope at high frequencies—consistent with Kolmogorov’s theory of isotropic turbulence. Motion correction also improves estimates of cross-spectra and Reynold’s stresses. Comparison of turbulence dissipation with flow speed and turbulence production indicates a bottom boundary layer production-dissipation balance during ebb and flood that is consistent with the strong tidal forcing at the site. These results indicate that inertial-motion-sensor-equipped ADVs are a valuable new tool for measuring turbulence from moorings.« less

Can energy expenditure be accurately assessed using accelerometry-based wearable motion detectors for physical activity monitoring in post-stroke patients in the subacute phase?

PubMed

Mandigout, Stéphane; Lacroix, Justine; Ferry, Béatrice; Vuillerme, Nicolas; Compagnat, Maxence; Daviet, Jean-Christophe

2017-12-01

Background In the subacute stroke phase, the monitoring of ambulatory activity and activities of daily life with wearable sensors may have relevant clinical applications. Do current commercially available wearable activity trackers allow us to objectively assess the energy expenditure of these activities? The objective of the present study was to compare the energy expenditure evaluated by indirect calorimetry during the course of a scenario consisting of everyday activities while estimating the energy expenditure using several commercialised wearable sensors in post-stroke patients (less than six months since stroke). Method Twenty-four patients (age 68.2 ± 13.9; post-stroke delay 34 ± 25 days) voluntarily participated in this study. Each patient underwent a scenario of various everyday tasks (transfer, walking, etc.). During the implementation, patients wore 14 wearable sensors (Armband, Actigraph GT3X, Actical, pedometer) to obtain an estimate of the energy expenditure. The actual energy expenditure was concurrently determined by indirect calorimetry. Results Except for the Armband worn on the non-plegic side, the results of our study show a significant difference between the energy expenditure values estimated by the various sensors and the actual energy expenditure when the scenario is considered as a whole. Conclusion The present results suggest that, for a series of everyday tasks, the wearable sensors underestimate the actual energy expenditure values in post-stroke patients in the subacute phase and are therefore not accurate. Several factors are likely to confound the results: types of activity, prediction equations, the position of the sensor and the hemiplegia side.

Polyurethane nanofiber strain sensors via in situ polymerization of polypyrrole and application to monitoring joint flexion

NASA Astrophysics Data System (ADS)

Kim, Inhwan; Cho, Gilsoo

2018-07-01

Strain sensors made of intrinsically conductive polymers (ICPs) and nanofibers were fabricated and tested for suitability for use in wearable technology. The sensors were fabricated and evaluated based on their surface appearances, and electrical, tensile, and chemical/thermal properties. Polypyrrole (PPy) was in situ polymerized onto polyurethane (PU) nanofiber substrates by exposing pyrrole monomers to ammonium persulfate as oxidant and 2,6-naphthalenedisulfonic acid disodium salt as doping agents in an aqueous bath. The PPy treated PU nanofibers were then coated with polydimethylsiloxane (PDMS). Both pyrrole concentrations and layer numbers were significantly related to change in electrical conductivity. Specimen treated with 0.1 M of PPy and having three layered structure showed the best electrical conductivity. Regarding tensile strength, the in situ polymerization process decreased tensile strength because the oxidant chemically degraded the PU fibers. Adding layers and PDMS treatment generally improved tensile properties while adding layers created fracture parts in the stress–strain curves. The treatment condition of 0.1 M of PPy, two layered, and PDMS treated specimen showed the best tensile properties as a strain sensor. The chemical property evaluation with Fourier transform infrared and x-ray photoelectron spectroscopy tests showed successful PPy polymerization and PDMS treatments. The functional groups and chemical bonds in polyol, urethane linkage, backbone ring structure in PPy, silicon-based functional groups in PDMS, and elemental content changes by treatment at each stage were characterized. The real-time data acquired from the dummy and five human subjects with repetition of motion at three different speeds of 0.16, 0.25 and 0.5 Hz generated similar trends and tendencies. The PU nanofiber sensors based on PPy and PDMS treatments in this study point to the possibility of developing textiles based wearable strain sensors developed using ICPs.

Self-Powered Multiparameter Health Sensor.

PubMed

Tobola, Andreas; Leutheuser, Heike; Pollak, Markus; Spies, Peter; Hofmann, Christian; Weigand, Christian; Eskofier, Bjoern M; Fischer, Georg

2018-01-01

Wearable health sensors are about to change our health system. While several technological improvements have been presented to enhance performance and energy-efficiency, battery runtime is still a critical concern for practical use of wearable biomedical sensor systems. The runtime limitation is directly related to the battery size, which is another concern regarding practicality and customer acceptance. We introduced ULPSEK-Ultra-Low-Power Sensor Evaluation Kit-for evaluation of biomedical sensors and monitoring applications (http://ulpsek.com). ULPSEK includes a multiparameter sensor measuring and processing electrocardiogram, respiration, motion, body temperature, and photoplethysmography. Instead of a battery, ULPSEK is powered using an efficient body heat harvester. The harvester produced 171 W on average, which was sufficient to power the sensor below 25 C ambient temperature. We present design issues regarding the power supply and the power distribution network of the ULPSEK sensor platform. Due to the security aspect of self-powered health sensors, we suggest a hybrid solution consisting of a battery charged by a harvester.

Tracking the harmonic response of magnetically-soft sensors for wireless temperature, stress, and corrosive monitoring.

PubMed

Ong, Keat G; Grimes, Craig A

2002-09-30

This paper describes the application of magnetically-soft ribbon-like sensors for measurement of temperature and stress, as well as corrosive monitoring, based upon changes in the amplitudes of the higher-order harmonics generated by the sensors in response to a magnetic interrogation signal. The sensors operate independently of mass loading, and so can be placed or rigidly embedded inside nonmetallic, opaque structures such as concrete or plastic. The passive harmonic-based sensor is remotely monitored through a single coplanar interrogation and detection coil. Effects due to the relative location of the sensor are eliminated by tracking harmonic amplitude ratios, thereby, enabling wide area monitoring. The wireless, passive, mass loading independent nature of the described sensor platform makes it ideally suited for long-term structural monitoring applications, such as measurement of temperature and stress inside concrete structures. A theoretical model is presented to explain the origin and behavior of the higher-order harmonics in response to temperature and stress. c2002 Elsevier Science B.V. All rights reserved.

Tracking the harmonic response of magnetically-soft sensors for wireless temperature, stress, and corrosive monitoring

NASA Technical Reports Server (NTRS)

Ong, Keat G.; Grimes, Craig A.

2002-01-01

This paper describes the application of magnetically-soft ribbon-like sensors for measurement of temperature and stress, as well as corrosive monitoring, based upon changes in the amplitudes of the higher-order harmonics generated by the sensors in response to a magnetic interrogation signal. The sensors operate independently of mass loading, and so can be placed or rigidly embedded inside nonmetallic, opaque structures such as concrete or plastic. The passive harmonic-based sensor is remotely monitored through a single coplanar interrogation and detection coil. Effects due to the relative location of the sensor are eliminated by tracking harmonic amplitude ratios, thereby, enabling wide area monitoring. The wireless, passive, mass loading independent nature of the described sensor platform makes it ideally suited for long-term structural monitoring applications, such as measurement of temperature and stress inside concrete structures. A theoretical model is presented to explain the origin and behavior of the higher-order harmonics in response to temperature and stress. c2002 Elsevier Science B.V. All rights reserved.

77 FR 74513 - Certain CMOS Image Sensors and Products Containing Same; Investigations: Terminations...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-14

.... International Trade Commission. ACTION: Notice. SUMMARY: Notice is hereby given that the U.S. International... unopposed motions to terminate the above-captioned investigation based on a settlement agreement. The..., ``Nokia''); and Research In Motion Ltd., of Ontario, Canada, and Research In Motion Corp., of Irving...

SU-E-J-211: Design and Study of In-House Software Based Respiratory Motion Monitoring, Controlling and Breath-Hold Device for Gated Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shanmugam, Senthilkumar

Purpose: The purpose of this present work was to fabricate an in-house software based respiratory monitoring, controlling and breath-hold device using computer software programme which guides the patient to have uniform breath hold in response to request during the gated radiotherapy. Methods: The respiratory controlling device consists of a computer, inhouse software, video goggles, a highly sensitive sensor for measurement of distance, mounting systems, a camera, a respiratory signal device, a speaker and a visual indicator. The computer is used to display the respiratory movements of the patient with digital as well as analogue respiration indicators during the respiration cycle,more » to control, breath-hold and analyze the respiratory movement using indigenously developed software. Results: Studies were conducted with anthropomophic phantoms by simulating the respiratory motion on phantoms and recording the respective movements using the respiratory monitoring device. The results show good agreement between the simulated and measured movements. Further studies were conducted for 60 cancer patients with several types of cancers in the thoracic region. The respiratory movement cycles for each fraction of radiotherapy treatment were recorded and compared. Alarm indications are provided in the system to indicate when the patient breathing movement exceeds the threshold level. This will help the patient to maintain uniform breath hold during the radiotherapy treatment. Our preliminary clinical test results indicate that our device is highly reliable and able to maintain the uniform respiratory motion and breathe hold during the entire course of gated radiotherapy treatment. Conclusion: An indigenous respiratory monitoring device to guide the patient to have uniform breath hold device was fabricated. The alarm feature and the visual waveform indicator in the system guide the patient to have normal respiration. The signal from the device can be connected to the radiation unit in near future to carry out the gated radiotherapy treatment.« less

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

PubMed

Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

2017-03-03

Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

Chemical, biochemical, and environmental fiber sensors III; Proceedings of the Meeting, Boston, MA, Sept. 4, 5, 1991

NASA Astrophysics Data System (ADS)

Lieberman, Robert A.

Various papers on chemical, biochemical, and environmental fiber sensors are presented. Individual topics addressed include: fiber optic pressure sensor for combustion monitoring and control, viologen-based fiber optic oxygen sensors, renewable-reagent fiber optic sensor for ocean pCO2, transition metal complexes as indicators for a fiber optic oxygen sensor, fiber optic pH measurements using azo indicators, simple reversible fiber optic chemical sensors using solvatochromic dyes, totally integrated optical measuring sensors, integrated optic biosensor for environmental monitoring, radiation dosimetry using planar waveguide sensors, optical and piezoelectric analysis of polymer films for chemical sensor characterization, source polarization effects in an optical fiber fluorosensor, lens-type refractometer for on-line chemical analysis, fiber optic hydrocarbon sensor system, chemical sensors for environmental monitoring, optical fibers for liquid-crystal sensing and logic devices, suitability of single-mode fluoride fibers for evanescent-wave sensing, integrated modules for fiber optic sensors, optoelectronic sensors based on narrowband A3B5 alloys, fiber Bragg grating chemical sensor.

SoM: a smart sensor for human activity monitoring and assisted healthy ageing.

PubMed

Naranjo-Hernández, David; Roa, Laura M; Reina-Tosina, Javier; Estudillo-Valderrama, Miguel Ángel

2012-11-01

This paper presents the hardware and software design and implementation of a low-cost, wearable, and unobstructive intelligent accelerometer sensor for the monitoring of human physical activities. In order to promote healthy lifestyles to elders for an active, independent, and healthy ageing, as well as for the early detection of psychomotor abnormalities, the activity monitoring is performed in a holistic manner in the same device through different approaches: 1) a classification of the level of activity that allows to establish patterns of behavior; 2) a daily activity living classifier that is able to distinguish activities such as climbing or descending stairs using a simple method to decouple the gravitational acceleration components of the motion components; and 3) an estimation of metabolic expenditure independent of the activity performed and the anthropometric characteristics of the user. Experimental results have demonstrated the feasibility of the prototype and the proposed algorithms.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

PubMed

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-07-07

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition

PubMed Central

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-01-01

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method. PMID:26198231

Laser-Assisted Reduction of Highly Conductive Circuits Based on Copper Nitrate for Flexible Printed Sensors

NASA Astrophysics Data System (ADS)

Bai, Shi; Zhang, Shigang; Zhou, Weiping; Ma, Delong; Ma, Ying; Joshi, Pooran; Hu, Anming

2017-10-01

Stretchable electronic sensing devices are defining the path toward wearable electronics. High-performance flexible strain sensors attached on clothing or human skin are required for potential applications in the entertainment, health monitoring, and medical care sectors. In this work, conducting copper electrodes were fabricated on polydimethylsiloxane as sensitive stretchable microsensors by integrating laser direct writing and transfer printing approaches. The copper electrode was reduced from copper salt using laser writing rather than the general approach of printing with pre-synthesized copper or copper oxide nanoparticles. An electrical resistivity of 96 μΩ cm was achieved on 40-μm-thick Cu electrodes on flexible substrates. The motion sensing functionality successfully demonstrated a high sensitivity and mechanical robustness. This in situ fabrication method leads to a path toward electronic devices on flexible substrates.[Figure not available: see fulltext.

Accelerometry-based classification of human activities using Markov modeling.

PubMed

Mannini, Andrea; Sabatini, Angelo Maria

2011-01-01

Accelerometers are a popular choice as body-motion sensors: the reason is partly in their capability of extracting information that is useful for automatically inferring the physical activity in which the human subject is involved, beside their role in feeding biomechanical parameters estimators. Automatic classification of human physical activities is highly attractive for pervasive computing systems, whereas contextual awareness may ease the human-machine interaction, and in biomedicine, whereas wearable sensor systems are proposed for long-term monitoring. This paper is concerned with the machine learning algorithms needed to perform the classification task. Hidden Markov Model (HMM) classifiers are studied by contrasting them with Gaussian Mixture Model (GMM) classifiers. HMMs incorporate the statistical information available on movement dynamics into the classification process, without discarding the time history of previous outcomes as GMMs do. An example of the benefits of the obtained statistical leverage is illustrated and discussed by analyzing two datasets of accelerometer time series.

Mobile quantum gravity sensor with unprecedented stability

NASA Astrophysics Data System (ADS)

Freier, C.; Hauth, M.; Schkolnik, V.; Leykauf, B.; Schilling, M.; Wziontek, H.; Scherneck, H.-G.; Müller, J.; Peters, A.

2016-06-01

Changes of surface gravity on Earth are of great interest in geodesy, earth sciences and natural resource exploration. They are indicative of Earth system's mass redistributions and vertical surface motion, and are usually measured with falling corner-cube- and superconducting gravimeters (FCCG and SCG). Here we report on absolute gravity measurements with a mobile quantum gravimeter based on atom interferometry. The measurements were conducted in Germany and Sweden over periods of several days with simultaneous SCG and FCCG comparisons. They show the best-reported performance of mobile atomic gravimeters to date with an accuracy of 39nm/s2, long-term stability of 0.5nm/s2 and short-term noise of 96nm/s2/√Hz. These measurements highlight the unique properties of atomic sensors. The achieved level of performance in a transportable instrument enables new applications in geodesy and related fields, such as continuous absolute gravity monitoring with a single instrument under rough environmental conditions.

Activity recognition with wearable sensors on loose clothing

PubMed Central

Howard, Matthew

2017-01-01

Observing human motion in natural everyday environments (such as the home), has evoked a growing interest in the development of on-body wearable sensing technology. However, wearable sensors suffer from motion artefacts introduced by the non-rigid attachment of sensors to the body, and the prevailing view is that it is necessary to eliminate these artefacts. This paper presents findings that suggest that these artefacts can, in fact, be used to distinguish between similar motions, by exploiting additional information provided by the fabric motion. An experimental study is presented whereby factors of both the motion and the properties of the fabric are analysed in the context of motion similarity. It is seen that while standard rigidly attached sensors have difficultly in distinguishing between similar motions, sensors mounted onto fabric exhibit significant differences (p < 0.01). An evaluation of the physical properties of the fabric shows that the stiffness of the material plays a role in this, with a trade-off between additional information and extraneous motion. This effect is evaluated in an online motion classification task, and the use of fabric-mounted sensors demonstrates an increase in prediction accuracy over rigidly attached sensors. PMID:28976978

Activity recognition with wearable sensors on loose clothing.

PubMed

Michael, Brendan; Howard, Matthew

2017-01-01

Observing human motion in natural everyday environments (such as the home), has evoked a growing interest in the development of on-body wearable sensing technology. However, wearable sensors suffer from motion artefacts introduced by the non-rigid attachment of sensors to the body, and the prevailing view is that it is necessary to eliminate these artefacts. This paper presents findings that suggest that these artefacts can, in fact, be used to distinguish between similar motions, by exploiting additional information provided by the fabric motion. An experimental study is presented whereby factors of both the motion and the properties of the fabric are analysed in the context of motion similarity. It is seen that while standard rigidly attached sensors have difficultly in distinguishing between similar motions, sensors mounted onto fabric exhibit significant differences (p < 0.01). An evaluation of the physical properties of the fabric shows that the stiffness of the material plays a role in this, with a trade-off between additional information and extraneous motion. This effect is evaluated in an online motion classification task, and the use of fabric-mounted sensors demonstrates an increase in prediction accuracy over rigidly attached sensors.

Combine harvester monitor system based on wireless sensor network

USDA-ARS?s Scientific Manuscript database

A measurement method based on Wireless Sensor Network (WSN) was developed to monitor the working condition of combine harvester for remote application. Three JN5139 modules were chosen for sensor data acquisition and another two as a router and a coordinator, which could create a tree topology netwo...

Development of a wireless MEMS multifunction sensor system and field demonstration of embedded sensors for monitoring concrete pavements : tech transfer summary.

DOT National Transportation Integrated Search

2016-08-01

Micro-electromechanical sensors and systems- (MEMS)-based and : wireless-based smart-sensing technologies have, until now, rarely : been used for monitoring pavement response in the field, and the : requirements for using such smart sensing technolog...

Technical Note: A respiratory monitoring and processing system based on computer vision: prototype and proof of principle

PubMed Central

Atallah, Vincent; Escarmant, Patrick; Vinh‐Hung, Vincent

2016-01-01

Monitoring and controlling respiratory motion is a challenge for the accuracy and safety of therapeutic irradiation of thoracic tumors. Various commercial systems based on the monitoring of internal or external surrogates have been developed but remain costly. In this article we describe and validate Madibreast, an in‐house‐made respiratory monitoring and processing device based on optical tracking of external markers. We designed an optical apparatus to ensure real‐time submillimetric image resolution at 4 m. Using OpenCv libraries, we optically tracked high‐contrast markers set on patients' breasts. Validation of spatial and time accuracy was performed on a mechanical phantom and on human breast. Madibreast was able to track motion of markers up to a 5 cm/s speed, at a frame rate of 30 fps, with submillimetric accuracy on mechanical phantom and human breasts. Latency was below 100 ms. Concomitant monitoring of three different locations on the breast showed discrepancies in axial motion up to 4 mm for deep‐breathing patterns. This low‐cost, computer‐vision system for real‐time motion monitoring of the irradiation of breast cancer patients showed submillimetric accuracy and acceptable latency. It allowed the authors to highlight differences in surface motion that may be correlated to tumor motion. PACS number(s): 87.55.km PMID:27685116

Technical Note: A respiratory monitoring and processing system based on computer vision: prototype and proof of principle.

PubMed

Leduc, Nicolas; Atallah, Vincent; Escarmant, Patrick; Vinh-Hung, Vincent

2016-09-08

Monitoring and controlling respiratory motion is a challenge for the accuracy and safety of therapeutic irradiation of thoracic tumors. Various commercial systems based on the monitoring of internal or external surrogates have been developed but remain costly. In this article we describe and validate Madibreast, an in-house-made respiratory monitoring and processing device based on optical tracking of external markers. We designed an optical apparatus to ensure real-time submillimetric image resolution at 4 m. Using OpenCv libraries, we optically tracked high-contrast markers set on patients' breasts. Validation of spatial and time accuracy was performed on a mechanical phantom and on human breast. Madibreast was able to track motion of markers up to a 5 cm/s speed, at a frame rate of 30 fps, with submillimetric accuracy on mechanical phantom and human breasts. Latency was below 100 ms. Concomitant monitoring of three different locations on the breast showed discrepancies in axial motion up to 4 mm for deep-breathing patterns. This low-cost, computer-vision system for real-time motion monitoring of the irradiation of breast cancer patients showed submillimetric accuracy and acceptable latency. It allowed the authors to highlight differences in surface motion that may be correlated to tumor motion.v. © 2016 The Authors.

Avoiding space robot collisions utilizing the NASA/GSFC tri-mode skin sensor

NASA Technical Reports Server (NTRS)

Prinz, F. B.

1991-01-01

Sensor based robot motion planning research has primarily focused on mobile robots. Consider, however, the case of a robot manipulator expected to operate autonomously in a dynamic environment where unexpected collisions can occur with many parts of the robot. Only a sensor based system capable of generating collision free paths would be acceptable in such situations. Recently, work in this area has been reported in which a deterministic solution for 2DOF systems has been generated. The arm was sensitized with 'skin' of infra-red sensors. We have proposed a heuristic (potential field based) methodology for redundant robots with large DOF's. The key concepts are solving the path planning problem by cooperating global and local planning modules, the use of complete information from the sensors and partial (but appropriate) information from a world model, representation of objects with hyper-ellipsoids in the world model, and the use of variational planning. We intend to sensitize the robot arm with a 'skin' of capacitive proximity sensors. These sensors were developed at NASA, and are exceptionally suited for the space application. In the first part of the report, we discuss the development and modeling of the capacitive proximity sensor. In the second part we discuss the motion planning algorithm.

A conductive grating sensor for online quantitative monitoring of fatigue crack.

PubMed

Li, Peiyuan; Cheng, Li; Yan, Xiaojun; Jiao, Shengbo; Li, Yakun

2018-05-01

Online quantitative monitoring of crack damage due to fatigue is a critical challenge for structural health monitoring systems assessing structural safety. To achieve online quantitative monitoring of fatigue crack, a novel conductive grating sensor based on the principle of electrical potential difference is proposed. The sensor consists of equidistant grating channels to monitor the fatigue crack length and conductive bars to provide the circuit path. An online crack monitoring system is established to verify the sensor's capability. The experimental results prove that the sensor is suitable for online quantitative monitoring of fatigue crack. A finite element model for the sensor is also developed to optimize the sensitivity of crack monitoring, which is defined by the rate of sensor resistance change caused by the break of the first grating channel. Analysis of the model shows that the sensor sensitivity can be enhanced by reducing the number of grating channels and increasing their resistance and reducing the resistance of the conductive bar.

A conductive grating sensor for online quantitative monitoring of fatigue crack

NASA Astrophysics Data System (ADS)

Li, Peiyuan; Cheng, Li; Yan, Xiaojun; Jiao, Shengbo; Li, Yakun

2018-05-01

Online quantitative monitoring of crack damage due to fatigue is a critical challenge for structural health monitoring systems assessing structural safety. To achieve online quantitative monitoring of fatigue crack, a novel conductive grating sensor based on the principle of electrical potential difference is proposed. The sensor consists of equidistant grating channels to monitor the fatigue crack length and conductive bars to provide the circuit path. An online crack monitoring system is established to verify the sensor's capability. The experimental results prove that the sensor is suitable for online quantitative monitoring of fatigue crack. A finite element model for the sensor is also developed to optimize the sensitivity of crack monitoring, which is defined by the rate of sensor resistance change caused by the break of the first grating channel. Analysis of the model shows that the sensor sensitivity can be enhanced by reducing the number of grating channels and increasing their resistance and reducing the resistance of the conductive bar.

Image deblurring in smartphone devices using built-in inertial measurement sensors

NASA Astrophysics Data System (ADS)

Šindelář, Ondřej; Šroubek, Filip

2013-01-01

Long-exposure handheld photography is degraded with blur, which is difficult to remove without prior information about the camera motion. In this work, we utilize inertial sensors (accelerometers and gyroscopes) in modern smartphones to detect exact motion trajectory of the smartphone camera during exposure and remove blur from the resulting photography based on the recorded motion data. The whole system is implemented on the Android platform and embedded in the smartphone device, resulting in a close-to-real-time deblurring algorithm. The performance of the proposed system is demonstrated in real-life scenarios.

Machine learning methods for classifying human physical activity from on-body accelerometers.

PubMed

Mannini, Andrea; Sabatini, Angelo Maria

2010-01-01

The use of on-body wearable sensors is widespread in several academic and industrial domains. Of great interest are their applications in ambulatory monitoring and pervasive computing systems; here, some quantitative analysis of human motion and its automatic classification are the main computational tasks to be pursued. In this paper, we discuss how human physical activity can be classified using on-body accelerometers, with a major emphasis devoted to the computational algorithms employed for this purpose. In particular, we motivate our current interest for classifiers based on Hidden Markov Models (HMMs). An example is illustrated and discussed by analysing a dataset of accelerometer time series.

PSD Camera Based Position and Posture Control of Redundant Robot Considering Contact Motion

NASA Astrophysics Data System (ADS)

Oda, Naoki; Kotani, Kentaro

The paper describes a position and posture controller design based on the absolute position by external PSD vision sensor for redundant robot manipulator. The redundancy enables a potential capability to avoid obstacle while continuing given end-effector jobs under contact with middle link of manipulator. Under contact motion, the deformation due to joint torsion obtained by comparing internal and external position sensor, is actively suppressed by internal/external position hybrid controller. The selection matrix of hybrid loop is given by the function of the deformation. And the detected deformation is also utilized in the compliant motion controller for passive obstacle avoidance. The validity of the proposed method is verified by several experimental results of 3link planar redundant manipulator.

Motion artifact removal in FNIR spectroscopy for real-world applications

NASA Astrophysics Data System (ADS)

Devaraj, Ajit; Izzetoglu, Meltem; Izzetoglu, Kurtulus; Bunce, Scott C.; Li, Connie Y.; Onaral, Banu

2004-12-01

Near infrared spectroscopy as a neuroimaging modality is a recent development. Near infrared neuroimagers are typically safe, portable, relatively affordable and non-invasive. The ease of sensor setup and non-intrusiveness make functional near infrared (fNIR) imaging an ideal candidate for monitoring human cortical function in a wide range of real world situations. However optical signals are susceptible to motion-artifacts, hindering the application of fNIR in studies where subject mobility cannot be controlled. In this paper, we present a filtering framework for motion-artifact cancellation to facilitate the deployment of fNIR imaging in real-world scenarios. We simulate a generic field environment by having subjects walk on a treadmill while performing a cognitive task and demonstrate that measurements can be effectively cleaned of motion-artifacts.

Chemical Sensor Platform for Non-Invasive Monitoring of Activity and Dehydration

PubMed Central

Solovei, Dmitry; Žák, Jaromír; Majzlíková, Petra; Sedláček, Jiří; Hubálek, Jaromír

2015-01-01

A non-invasive solution for monitoring of the activity and dehydration of organisms is proposed in the work. For this purpose, a wireless standalone chemical sensor platform using two separate measurement techniques has been developed. The first approach for activity monitoring is based on humidity measurement. Our solution uses new humidity sensor based on a nanostructured TiO2 surface for sweat rate monitoring. The second technique is based on monitoring of potassium concentration in urine. High level of potassium concentration denotes clear occurrence of dehydration. Furthermore, a Wireless Body Area Network (WBAN) was developed for this sensor platform to manage data transfer among devices and the internet. The WBAN coordinator controls the sensor devices and collects and stores the measured data. The collected data is particular to individuals and can be shared with physicians, emergency systems or athletes' coaches. Long-time monitoring of activity and potassium concentration in urine can help maintain the appropriate water intake of elderly people or athletes and to send warning signals in the case of near dehydration. The created sensor system was calibrated and tested in laboratory and real conditions as well. The measurement results are discussed. PMID:25594591

Compliant finger sensor for sensorimotor studies in MEG and MR environment

NASA Astrophysics Data System (ADS)

Li, Y.; Yong, X.; Cheung, T. P. L.; Menon, C.

2016-07-01

Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) are widely used for functional brain imaging. The correlations between the sensorimotor functions of the hand and brain activities have been investigated in MEG/fMRI studies. Currently, limited information can be drawn from these studies due to the limitations of existing motion sensors that are used to detect hand movements. One major challenge in designing these motion sensors is to limit the signal interference between the motion sensors and the MEG/fMRI. In this work, a novel finger motion sensor, which contains low-ferromagnetic and non-conductive materials, is introduced. The finger sensor consists of four air-filled chambers. When compressed by finger(s), the pressure change in the chambers can be detected by the electronics of the finger sensor. Our study has validated that the interference between the finger sensor and an MEG is negligible. Also, by applying a support vector machine algorithm to the data obtained from the finger sensor, at least 11 finger patterns can be discriminated. Comparing to the use of traditional electromyography (EMG) in detecting finger motion, our proposed finger motion sensor is not only MEG/fMRI compatible, it is also easy to use. As the signals acquired from the sensor have a higher SNR than that of the EMG, no complex algorithms are required to detect different finger movement patterns. Future studies can utilize this motion sensor to investigate brain activations during different finger motions and correlate the activations with the sensory and motor functions respectively.

Real-time motion artifacts compensation of ToF sensors data on GPU

NASA Astrophysics Data System (ADS)

Lefloch, Damien; Hoegg, Thomas; Kolb, Andreas

2013-05-01

Over the last decade, ToF sensors attracted many computer vision and graphics researchers. Nevertheless, ToF devices suffer from severe motion artifacts for dynamic scenes as well as low-resolution depth data which strongly justifies the importance of a valid correction. To counterbalance this effect, a pre-processing approach is introduced to greatly improve range image data on dynamic scenes. We first demonstrate the robustness of our approach using simulated data to finally validate our method using sensor range data. Our GPU-based processing pipeline enhances range data reliability in real-time.

Design and implementation of modular home security system with short messaging system

NASA Astrophysics Data System (ADS)

Budijono, Santoso; Andrianto, Jeffri; Axis Novradin Noor, Muhammad

2014-03-01

Today we are living in 21st century where crime become increasing and everyone wants to secure they asset at their home. In that situation user must have system with advance technology so person do not worry when getting away from his home. It is therefore the purpose of this design to provide home security device, which send fast information to user GSM (Global System for Mobile) mobile device using SMS (Short Messaging System) and also activate - deactivate system by SMS. The Modular design of this Home Security System make expandable their capability by add more sensors on that system. Hardware of this system has been designed using microcontroller AT Mega 328, PIR (Passive Infra Red) motion sensor as the primary sensor for motion detection, camera for capturing images, GSM module for sending and receiving SMS and buzzer for alarm. For software this system using Arduino IDE for Arduino and Putty for testing connection programming in GSM module. This Home Security System can monitor home area that surrounding by PIR sensor and sending SMS, save images capture by camera, and make people panic by turn on the buzzer when trespassing surrounding area that detected by PIR sensor. The Modular Home Security System has been tested and succeed detect human movement.

Acoustic Emission Behavior of Early Age Concrete Monitored by Embedded Sensors.

PubMed

Qin, Lei; Ren, Hong-Wei; Dong, Bi-Qin; Xing, Feng

2014-10-02

Acoustic emission (AE) is capable of monitoring the cracking activities inside materials. In this study, embedded sensors were employed to monitor the AE behavior of early age concrete. Type 1-3 cement-based piezoelectric composites, which had lower mechanical quality factor and acoustic impedance, were fabricated and used to make sensors. Sensors made of the composites illustrated broadband frequency response. In a laboratory, the cracking of early age concrete was monitored to recognize different hydration stages. The sensors were also embedded in a mass concrete foundation to localize the temperature gradient cracks.

IoT based Growth Monitoring System of Guava (Psidium guajava L.) Fruits

NASA Astrophysics Data System (ADS)

Slamet, W.; Irham, N. M.; Sutan, M. S. A.

2018-05-01

Growth monitoring of plant is important especially to evaluate the influence of environment or growing condition on its productivity. One way to monitor the plant growth is by measuring the radial growth (i.e., the change of circumference) of certain part of plant such as trunk, branch, and fruit. In this study we develop an internet of things (IoT) based monitoring system of radial growth of plant using a low-cost optoelectronic sensor. The system was applied to monitor radial growth of guava fruits (Psidium guajava L.). The principle of the developed sensor is based on the optoelectronic sensor which detects alternating white and black narrow bar printed on reflective tapes. Reflective tape was installed encircling the fruit. The movement of reflective tapes will follow the radial growth of the fruit so that the infrared sensor on the optoelectronic would response reflective tapes movement. This device is designed to measure object continuously and long-term monitor with minimum maintenance. The data collected by the sensors are then sent to the server and also can be monitored in real-time. Based on field test, at current stage, the developed sensor could measure the radial growth of the fruits with a maximum error 2 mm. In term of data transfer, the success rate of the developed system was 97.54%. The result indicated that the developed system can be used as an effective tool for growth monitoring of plant.

In-Line Capacitance Sensor for Real-Time Water Absorption Measurements

NASA Technical Reports Server (NTRS)

Nurge, Mark A.; Perusich, Stephen A.

2010-01-01

A capacitance/dielectric sensor was designed, constructed, and used to measure in real time the in-situ water concentration in a desiccant water bed. Measurements were carried out with two experimental setups: (1) passing nitrogen through a humidity generator and allowing the gas stream to become saturated at a measured temperature and pressure, and (2) injecting water via a syringe pump into a nitrogen stream. Both water vapor generating devices were attached to a downstream vertically-mounted water capture bed filled with 19.5 g of Moisture Gone desiccant. The sensor consisted of two electrodes: (1) a 1/8" dia stainless steel rod placed in the middle of the bed and (2) the outer shell of the stainless steel bed concentric with the rod. All phases of the water capture process (background, heating, absorption, desorption, and cooling) were monitored with capacitance. The measured capacitance was found to vary linearly with the water content in the bed at frequencies above 100 kHz indicating dipolar motion dominated the signal; below this frequency, ionic motion caused nonlinearities in the water concentration/capacitance relationship. The desiccant exhibited a dielectric relaxation whose activation energy was lowered upon addition of water indicating either a less hindered rotational motion or crystal reorientation.

Micro sensor node for air pollutant monitoring: hardware and software issues.

PubMed

Choi, Sukwon; Kim, Nakyoung; Cha, Hojung; Ha, Rhan

2009-01-01

Wireless sensor networks equipped with various gas sensors have been actively used for air quality monitoring. Previous studies have typically explored system issues that include middleware or networking performance, but most research has barely considered the details of the hardware and software of the sensor node itself. In this paper, we focus on the design and implementation of a sensor board for air pollutant monitoring applications. Several hardware and software issues are discussed to explore the possibilities of a practical WSN-based air pollution monitoring system. Through extensive experiments and evaluation, we have determined the various characteristics of the gas sensors and their practical implications for air pollutant monitoring systems.

Interaction force and motion estimators facilitating impedance control of the upper limb rehabilitation robot.

PubMed

Mancisidor, Aitziber; Zubizarreta, Asier; Cabanes, Itziar; Bengoa, Pablo; Jung, Je Hyung

2017-07-01

In order to enhance the performance of rehabilitation robots, it is imperative to know both force and motion caused by the interaction between user and robot. However, common direct measurement of both signals through force and motion sensors not only increases the complexity of the system but also impedes affordability of the system. As an alternative of the direct measurement, in this work, we present new force and motion estimators for the proper control of the upper-limb rehabilitation Universal Haptic Pantograph (UHP) robot. The estimators are based on the kinematic and dynamic model of the UHP and the use of signals measured by means of common low-cost sensors. In order to demonstrate the effectiveness of the estimators, several experimental tests were carried out. The force and impedance control of the UHP was implemented first by directly measuring the interaction force using accurate extra sensors and the robot performance was compared to the case where the proposed estimators replace the direct measured values. The experimental results reveal that the controller based on the estimators has similar performance to that using direct measurement (less than 1 N difference in root mean square error between two cases), indicating that the proposed force and motion estimators can facilitate implementation of interactive controller for the UHP in robotmediated rehabilitation trainings.

Evaluating physical function and activity in the elderly patient using wearable motion sensors.

PubMed

Grimm, Bernd; Bolink, Stijn

2016-05-01

Wearable sensors, in particular inertial measurement units (IMUs) allow the objective, valid, discriminative and responsive assessment of physical function during functional tests such as gait, stair climbing or sit-to-stand.Applied to various body segments, precise capture of time-to-task achievement, spatiotemporal gait and kinematic parameters of demanding tests or specific to an affected limb are the most used measures.In activity monitoring (AM), accelerometry has mainly been used to derive energy expenditure or general health related parameters such as total step counts.In orthopaedics and the elderly, counting specific events such as stairs or high intensity activities were clinimetrically most powerful; as were qualitative parameters at the 'micro-level' of activity such as step frequency or sit-stand duration.Low cost and ease of use allow routine clinical application but with many options for sensors, algorithms, test and parameter definitions, choice and comparability remain difficult, calling for consensus or standardisation. Cite this article: Grimm B, Bolink S. Evaluating physical function and activity in the elderly patient using wearable motion sensors. EFORT Open Rev 2016;1:112-120. DOI: 10.1302/2058-5241.1.160022.

Evaluating physical function and activity in the elderly patient using wearable motion sensors

PubMed Central

Grimm, Bernd; Bolink, Stijn

2016-01-01

Wearable sensors, in particular inertial measurement units (IMUs) allow the objective, valid, discriminative and responsive assessment of physical function during functional tests such as gait, stair climbing or sit-to-stand. Applied to various body segments, precise capture of time-to-task achievement, spatiotemporal gait and kinematic parameters of demanding tests or specific to an affected limb are the most used measures. In activity monitoring (AM), accelerometry has mainly been used to derive energy expenditure or general health related parameters such as total step counts. In orthopaedics and the elderly, counting specific events such as stairs or high intensity activities were clinimetrically most powerful; as were qualitative parameters at the ‘micro-level’ of activity such as step frequency or sit-stand duration. Low cost and ease of use allow routine clinical application but with many options for sensors, algorithms, test and parameter definitions, choice and comparability remain difficult, calling for consensus or standardisation. Cite this article: Grimm B, Bolink S. Evaluating physical function and activity in the elderly patient using wearable motion sensors. EFORT Open Rev 2016;1:112–120. DOI: 10.1302/2058-5241.1.160022. PMID:28461937

Data Fusion Based on Optical Technology for Observation of Human Manipulation

NASA Astrophysics Data System (ADS)

Falco, Pietro; De Maria, Giuseppe; Natale, Ciro; Pirozzi, Salvatore

2012-01-01

The adoption of human observation is becoming more and more frequent within imitation learning and programming by demonstration approaches (PbD) to robot programming. For robotic systems equipped with anthropomorphic hands, the observation phase is very challenging and no ultimate solution exists. This work proposes a novel mechatronic approach to the observation of human hand motion during manipulation tasks. The strategy is based on the combined use of an optical motion capture system and a low-cost data glove equipped with novel joint angle sensors, based on optoelectronic technology. The combination of the two information sources is obtained through a sensor fusion algorithm based on the extended Kalman filter (EKF) suitably modified to tackle the problem of marker occlusions, typical of optical motion capture systems. This approach requires a kinematic model of the human hand. Another key contribution of this work is a new method to calibrate this model.

Optical fiber sensors for the non-destructive evaluation of materials

NASA Technical Reports Server (NTRS)

1986-01-01

The operation of the modal domain vibration sensor was demonstrated in several simple vibrational systems. Two apparent advantages are the sensors bandwidth and sensitivity. An inherent drawback of standard vibration detection devices is their rapid cost increase with high frequency bandwidth. This sensor showed consistent response in the freqency range of 1.5 to 400 Hz. By imparting very small but measurable excitations in the structures, the sensors ability to respond to very low order vibration induced strain was established. Dynamic ranges on the order of 18 to 22 dB for the CF beam and string systems respectively were observed. The sensor itself represents a very simple system: a coherent source, a single fiber and a low bandwidth detector. The inherent advantages of ruggedness and immunity to external radiation can also be added. Finally, the sensor minimally impairs structural motion through loading, an advantage in monitoring small vibrations or lightweight structures. Some drawbacks of the sensor are also noted.

Recommendations for standardizing validation procedures assessing physical activity of older persons by monitoring body postures and movements.

PubMed

Lindemann, Ulrich; Zijlstra, Wiebren; Aminian, Kamiar; Chastin, Sebastien F M; de Bruin, Eling D; Helbostad, Jorunn L; Bussmann, Johannes B J

2014-01-10

Physical activity is an important determinant of health and well-being in older persons and contributes to their social participation and quality of life. Hence, assessment tools are needed to study this physical activity in free-living conditions. Wearable motion sensing technology is used to assess physical activity. However, there is a lack of harmonisation of validation protocols and applied statistics, which make it hard to compare available and future studies. Therefore, the aim of this paper is to formulate recommendations for assessing the validity of sensor-based activity monitoring in older persons with focus on the measurement of body postures and movements. Validation studies of body-worn devices providing parameters on body postures and movements were identified and summarized and an extensive inter-active process between authors resulted in recommendations about: information on the assessed persons, the technical system, and the analysis of relevant parameters of physical activity, based on a standardized and semi-structured protocol. The recommended protocols can be regarded as a first attempt to standardize validity studies in the area of monitoring physical activity.

Load monitoring using a calibrated piezo diaphragm based impedance strain sensor and wireless sensor network in real time

NASA Astrophysics Data System (ADS)

Gopal Madhav Annamdas, Venu; Kiong Soh, Chee

2017-04-01

The last decade has seen the use of various wired-wireless and contact-contactless sensors in several structural health monitoring (SHM) techniques. Most SHM sensors that are predominantly used for strain measurements may be ineffective for damage detection and vice versa, indicating the uniapplicability of these sensors. However, piezoelectric (PE)-based macro fiber composite (MFC) and lead zirconium titanate (PZT) sensors have been on the rise in SHM, vibration and damping control, etc, due to their superior actuation and sensing abilities. These PE sensors have created much interest for their multi-applicability in various technologies such as electromechanical impedance (EMI)-based SHM. This research employs piezo diaphragms, a cheaper alternative to several expensive types of PZT/MFC sensors for the EMI technique. These piezo diaphragms were validated last year for their applicability in damage detection using the frequency domain. Here we further validate their applicability in strain monitoring using the real time domain. Hence, these piezo diaphragms can now be classified as PE sensors and used with PZT and MFC sensors in the EMI technique for monitoring damage and loading. However, no single technique or single type of sensor will be sufficient for large SHM, thus requiring the necessary deployment of more than one technique with different types of sensors such as a piezoresistive strain gauge based wireless sensor network for strain measurements to complement the EMI technique. Furthermore, we present a novel procedure of converting a regular PE sensor in the ‘frequency domain’ to ‘real time domain’ for strain applications.

A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications

PubMed Central

Costa, Daniel G.; Collotta, Mario; Pau, Giovanni; Duran-Faundez, Cristian

2017-01-01

The advance of technologies in several areas has allowed the development of smart city applications, which can improve the way of life in modern cities. When employing visual sensors in that scenario, still images and video streams may be retrieved from monitored areas, potentially providing valuable data for many applications. Actually, visual sensor networks may need to be highly dynamic, reflecting the changing of parameters in smart cities. In this context, characteristics of visual sensors and conditions of the monitored environment, as well as the status of other concurrent monitoring systems, may affect how visual sensors collect, encode and transmit information. This paper proposes a fuzzy-based approach to dynamically configure the way visual sensors will operate concerning sensing, coding and transmission patterns, exploiting different types of reference parameters. This innovative approach can be considered as the basis for multi-systems smart city applications based on visual monitoring, potentially bringing significant results for this research field. PMID:28067777

A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications.

PubMed

Costa, Daniel G; Collotta, Mario; Pau, Giovanni; Duran-Faundez, Cristian

2017-01-05

The advance of technologies in several areas has allowed the development of smart city applications, which can improve the way of life in modern cities. When employing visual sensors in that scenario, still images and video streams may be retrieved from monitored areas, potentially providing valuable data for many applications. Actually, visual sensor networks may need to be highly dynamic, reflecting the changing of parameters in smart cities. In this context, characteristics of visual sensors and conditions of the monitored environment, as well as the status of other concurrent monitoring systems, may affect how visual sensors collect, encode and transmit information. This paper proposes a fuzzy-based approach to dynamically configure the way visual sensors will operate concerning sensing, coding and transmission patterns, exploiting different types of reference parameters. This innovative approach can be considered as the basis for multi-systems smart city applications based on visual monitoring, potentially bringing significant results for this research field.

Nano-enabled paper humidity sensor for mobile based point-of-care lung function monitoring.

PubMed

Bhattacharjee, Mitradip; Nemade, Harshal B; Bandyopadhyay, Dipankar

2017-08-15

The frequency of breathing and peak flow rate of exhaled air are necessary parameters to detect chronic obstructive pulmonary diseases (COPDs) such as asthma, bronchitis, or pneumonia. We developed a lung function monitoring point-of-care-testing device (LFM-POCT) consisting of mouthpiece, paper-based humidity sensor, micro-heater, and real-time monitoring unit. Fabrication of a mouthpiece of optimal length ensured that the exhaled air was focused on the humidity-sensor. The resistive relative humidity sensor was developed using a filter paper coated with nanoparticles, which could easily follow the frequency and peak flow rate of the human breathing. Adsorption followed by condensation of the water molecules of the humid air on the paper-sensor during the forced exhalation reduced the electrical resistance of the sensor, which was converted to an electrical signal for sensing. A micro-heater composed of a copper-coil embedded in a polymer matrix helped in maintaining an optimal temperature on the sensor surface. Thus, water condensed on the sensor surface only during forcible breathing and the sensor recovered rapidly after the exhalation was complete by rapid desorption of water molecules from the sensor surface. Two types of real-time monitoring units were integrated into the device based on light emitting diodes (LEDs) and smart phones. The LED based unit displayed the diseased, critical, and fit conditions of the lungs by flashing LEDs of different colors. In comparison, for the mobile based monitoring unit, an application was developed employing an open source software, which established a wireless connectivity with the LFM-POCT device to perform the tests. Copyright © 2017 Elsevier B.V. All rights reserved.

An Optical Interferometric Triaxial Displacement Sensor for Structural Health Monitoring: Characterization of Sliding and Debonding for a Delamination Process

PubMed Central

Chen, Yizheng; Zhuang, Yiyang; Du, Yang; Gerald, Rex E.; Tang, Yan

2017-01-01

This paper presents an extrinsic Fabry–Perot interferometer-based optical fiber sensor (EFPI) for measuring three-dimensional (3D) displacements, including interfacial sliding and debonding during delamination. The idea employs three spatially arranged EFPIs as the sensing elements. In our sensor, the three EFPIs are formed by three endfaces of three optical fibers and their corresponding inclined mirrors. Two coincident roof-like metallic structures are used to support the three fibers and the three mirrors, respectively. Our sensor was calibrated and then used to monitor interfacial sliding and debonding between a long square brick of mortar and its support structure (i.e., a steel base plate) during the drying/curing process. This robust and easy-to-manufacture triaxial EFPI-based 3D displacement sensor has great potential in structural health monitoring, the construction industry, oil well monitoring, and geotechnology. PMID:29165351

An Optical Interferometric Triaxial Displacement Sensor for Structural Health Monitoring: Characterization of Sliding and Debonding for a Delamination Process.

PubMed

Zhu, Chen; Chen, Yizheng; Zhuang, Yiyang; Du, Yang; Gerald, Rex E; Tang, Yan; Huang, Jie

2017-11-22

This paper presents an extrinsic Fabry-Perot interferometer-based optical fiber sensor (EFPI) for measuring three-dimensional (3D) displacements, including interfacial sliding and debonding during delamination. The idea employs three spatially arranged EFPIs as the sensing elements. In our sensor, the three EFPIs are formed by three endfaces of three optical fibers and their corresponding inclined mirrors. Two coincident roof-like metallic structures are used to support the three fibers and the three mirrors, respectively. Our sensor was calibrated and then used to monitor interfacial sliding and debonding between a long square brick of mortar and its support structure (i.e., a steel base plate) during the drying/curing process. This robust and easy-to-manufacture triaxial EFPI-based 3D displacement sensor has great potential in structural health monitoring, the construction industry, oil well monitoring, and geotechnology.

Standards for efficient employment of wide-area motion imagery (WAMI) sensors

NASA Astrophysics Data System (ADS)

Randall, L. Scott; Maenner, Paul F.

2013-05-01

Airborne Wide Area Motion Imagery (WAMI) sensors provide the opportunity for continuous high-resolution surveillance of geographic areas covering tens of square kilometers. This is both a blessing and a curse. Data volumes from "gigapixel-class" WAMI sensors are orders of magnitude greater than for traditional "megapixel-class" video sensors. The amount of data greatly exceeds the capacities of downlinks to ground stations, and even if this were not true, the geographic coverage is too large for effective human monitoring. Although collected motion imagery is recorded on the platform, typically only small "windows" of the full field of view are transmitted to the ground; the full set of collected data can be retrieved from the recording device only after the mission has concluded. Thus, the WAMI environment presents several difficulties: (1) data is too massive for downlink; (2) human operator selection and control of the video windows may not be effective; (3) post-mission storage and dissemination may be limited by inefficient file formats; and (4) unique system implementation characteristics may thwart exploitation by available analysis tools. To address these issues, the National Geospatial-Intelligence Agency's Motion Imagery Standards Board (MISB) is developing relevant standard data exchange formats: (1) moving target indicator (MTI) and tracking metadata to support tipping and cueing of WAMI windows using "watch boxes" and "trip wires"; (2) control channel commands for positioning the windows within the full WAMI field of view; and (3) a full-field-of-view spatiotemporal tiled file format for efficient storage, retrieval, and dissemination. The authors previously provided an overview of this suite of standards. This paper describes the latest progress, with specific concentration on a detailed description of the spatiotemporal tiled file format.

Validation of Freezing-of-Gait Monitoring Using Smartphone.

PubMed

Kim, Han Byul; Lee, Hong Ji; Lee, Woong Woo; Kim, Sang Kyong; Jeon, Hyo Seon; Park, Hye Young; Shin, Chae Won; Yi, Won Jin; Jeon, Beomseok; Park, Kwang S

2018-04-30

Freezing of gait (FOG) is a commonly observed motor symptom for patients with Parkinson's disease (PD). The symptoms of FOG include reduced step lengths or motor blocks, even with an evident intention of walking. FOG should be monitored carefully because it not only lowers the patient's quality of life, but also significantly increases the risk of injury. In previous studies, patients had to wear several sensors on the body and another computing device was needed to run the FOG detection algorithm. Moreover, the features used in the algorithm were based on low-level and hand-crafted features. In this study, we propose a FOG detection system based on a smartphone, which can be placed in the patient's daily wear, with a novel convolutional neural network (CNN). The walking data of 32 PD patients were collected from the accelerometer and gyroscope embedded in the smartphone, located in the trouser pocket. The motion signals measured by the sensors were converted into the frequency domain and stacked into a 2D image for the CNN input. A specialized CNN model for FOG detection was determined through a validation process. We compared our performances with the results acquired by the previously reported settings. The proposed architecture discriminated the freezing events from the normal activities with an average sensitivity of 93.8% and a specificity of 90.1%. Using our methodology, the precise and continuous monitoring of freezing events with unconstrained sensing can assist patients in managing their chronic disease in daily life effectively.

iCalm: wearable sensor and network architecture for wirelessly communicating and logging autonomic activity.

PubMed

Fletcher, Richard Ribon; Dobson, Kelly; Goodwin, Matthew S; Eydgahi, Hoda; Wilder-Smith, Oliver; Fernholz, David; Kuboyama, Yuta; Hedman, Elliott Bruce; Poh, Ming-Zher; Picard, Rosalind W

2010-03-01

Widespread use of affective sensing in healthcare applications has been limited due to several practical factors, such as lack of comfortable wearable sensors, lack of wireless standards, and lack of low-power affordable hardware. In this paper, we present a new low-cost, low-power wireless sensor platform implemented using the IEEE 802.15.4 wireless standard, and describe the design of compact wearable sensors for long-term measurement of electrodermal activity, temperature, motor activity, and photoplethysmography. We also illustrate the use of this new technology for continuous long-term monitoring of autonomic nervous system and motion data from active infants, children, and adults. We describe several new applications enabled by this system, discuss two specific wearable designs for the wrist and foot, and present sample data.

CardioGuard: A Brassiere-Based Reliable ECG Monitoring Sensor System for Supporting Daily Smartphone Healthcare Applications

PubMed Central

Kwon, Sungjun; Kim, Jeehoon; Kang, Seungwoo; Lee, Youngki; Baek, Hyunjae

2014-01-01

Abstract We propose CardioGuard, a brassiere-based reliable electrocardiogram (ECG) monitoring sensor system, for supporting daily smartphone healthcare applications. It is designed to satisfy two key requirements for user-unobtrusive daily ECG monitoring: reliability of ECG sensing and usability of the sensor. The system is validated through extensive evaluations. The evaluation results showed that the CardioGuard sensor reliably measure the ECG during 12 representative daily activities including diverse movement levels; 89.53% of QRS peaks were detected on average. The questionnaire-based user study with 15 participants showed that the CardioGuard sensor was comfortable and unobtrusive. Additionally, the signal-to-noise ratio test and the washing durability test were conducted to show the high-quality sensing of the proposed sensor and its physical durability in practical use, respectively. PMID:25405527

Response of Seismometer with Symmetric Triaxial Sensor Configuration to Complex Ground Motion

NASA Astrophysics Data System (ADS)

Graizer, V.

2007-12-01

Most instruments used in seismological practice to record ground motion in all directions use three sensors oriented toward North, East and upward. In this standard configuration horizontal and vertical sensors differ in their construction because of gravity acceleration always applied to a vertical sensor. An alternative way of symmetric sensor configuration was first introduced by Galperin (1955) for petroleum exploration. In this arrangement three identical sensors are also positioned orthogonally to each other but are tilted at the same angle of 54.7 degrees to the vertical axis (triaxial system of coordinate balanced on its corner). Records obtained using symmetric configuration must be rotated into an earth referenced X, Y, Z coordinate system. A number of recent seismological instruments (e.g., broadband seismometers Streckeisen STS-2, Trillium of Nanometrics and Cronos of Kinemetrics) are using symmetric sensor configuration. In most of seismological studies it is assumed that rotational (rocking and torsion) components of earthquake ground motion are small enough to be neglected. However, recently examples were shown when rotational components are significant relative to translational components of motions. Response of pendulums installed in standard configuration (vertical and two horizontals) to complex input motion that includes rotations has been studied in a number of publications. We consider the response of pendulums in a symmetric sensor configuration to complex input motions including rotations, and the resultant triaxial system response. Possible implications of using symmetric sensor configuration in strong motion studies are discussed. Considering benefits of equal design of all three sensors in symmetric configuration, and as a result potentially lower cost of the three-component accelerograph, it may be useful for strong motion measurements not requiring high resolution post signal processing. The disadvantage of this configuration is that if one of the sensors is not working properly or there is a misalignment of sensors, it results in degradation of all three components. Symmetric sensor configuration requires identical processing of each channel putting a number of limitations on further processing of strong motion records.

Simultaneous Detection of Displacement, Rotation Angle, and Contact Pressure Using Sandpaper Molded Elastomer Based Triple Electrode Sensor

PubMed Central

Sul, Onejae; Lee, Seung-Beck

2017-01-01

In this article, we report on a flexible sensor based on a sandpaper molded elastomer that simultaneously detects planar displacement, rotation angle, and vertical contact pressure. When displacement, rotation, and contact pressure are applied, the contact area between the translating top elastomer electrode and the stationary three bottom electrodes change characteristically depending on the movement, making it possible to distinguish between them. The sandpaper molded undulating surface of the elastomer reduces friction at the contact allowing the sensor not to affect the movement during measurement. The sensor showed a 0.25 mm−1 displacement sensitivity with a ±33 μm accuracy, a 0.027 degree−1 of rotation sensitivity with ~0.95 degree accuracy, and a 4.96 kP−1 of pressure sensitivity. For possible application to joint movement detection, we demonstrated that our sensor effectively detected the up-and-down motion of a human forefinger and the bending and straightening motion of a human arm. PMID:28878166

Simultaneous Detection of Displacement, Rotation Angle, and Contact Pressure Using Sandpaper Molded Elastomer Based Triple Electrode Sensor.

PubMed

Choi, Eunsuk; Sul, Onejae; Lee, Seung-Beck

2017-09-06

In this article, we report on a flexible sensor based on a sandpaper molded elastomer that simultaneously detects planar displacement, rotation angle, and vertical contact pressure. When displacement, rotation, and contact pressure are applied, the contact area between the translating top elastomer electrode and the stationary three bottom electrodes change characteristically depending on the movement, making it possible to distinguish between them. The sandpaper molded undulating surface of the elastomer reduces friction at the contact allowing the sensor not to affect the movement during measurement. The sensor showed a 0.25 mm −1 displacement sensitivity with a ±33 μm accuracy, a 0.027 degree −1 of rotation sensitivity with ~0.95 degree accuracy, and a 4.96 kP −1 of pressure sensitivity. For possible application to joint movement detection, we demonstrated that our sensor effectively detected the up-and-down motion of a human forefinger and the bending and straightening motion of a human arm.

Geopositioning with a quadcopter: Extracted feature locations and predicted accuracy without a priori sensor attitude information

NASA Astrophysics Data System (ADS)

Dolloff, John; Hottel, Bryant; Edwards, David; Theiss, Henry; Braun, Aaron

2017-05-01

This paper presents an overview of the Full Motion Video-Geopositioning Test Bed (FMV-GTB) developed to investigate algorithm performance and issues related to the registration of motion imagery and subsequent extraction of feature locations along with predicted accuracy. A case study is included corresponding to a video taken from a quadcopter. Registration of the corresponding video frames is performed without the benefit of a priori sensor attitude (pointing) information. In particular, tie points are automatically measured between adjacent frames using standard optical flow matching techniques from computer vision, an a priori estimate of sensor attitude is then computed based on supplied GPS sensor positions contained in the video metadata and a photogrammetric/search-based structure from motion algorithm, and then a Weighted Least Squares adjustment of all a priori metadata across the frames is performed. Extraction of absolute 3D feature locations, including their predicted accuracy based on the principles of rigorous error propagation, is then performed using a subset of the registered frames. Results are compared to known locations (check points) over a test site. Throughout this entire process, no external control information (e.g. surveyed points) is used other than for evaluation of solution errors and corresponding accuracy.

Mobile user identity sensing using the motion sensor

NASA Astrophysics Data System (ADS)

Zhao, Xi; Feng, Tao; Xu, Lei; Shi, Weidong

2014-05-01

Employing mobile sensor data to recognize user behavioral activities has been well studied in recent years. However, to adopt the data as a biometric modality has rarely been explored. Existing methods either used the data to recognize gait, which is considered as a distinguished identity feature; or segmented a specific kind of motion for user recognition, such as phone picking-up motion. Since the identity and the motion gesture jointly affect motion data, to fix the gesture (walking or phone picking-up) definitively simplifies the identity sensing problem. However, it meanwhile introduces the complexity from gesture detection or requirement on a higher sample rate from motion sensor readings, which may draw the battery fast and affect the usability of the phone. In general, it is still under investigation that motion based user authentication in a large scale satisfies the accuracy requirement as a stand-alone biometrics modality. In this paper, we propose a novel approach to use the motion sensor readings for user identity sensing. Instead of decoupling the user identity from a gesture, we reasonably assume users have their own distinguishing phone usage habits and extract the identity from fuzzy activity patterns, represented by a combination of body movements whose signals in chains span in relative low frequency spectrum and hand movements whose signals span in relative high frequency spectrum. Then Bayesian Rules are applied to analyze the dependency of different frequency components in the signals. During testing, a posterior probability of user identity given the observed chains can be computed for authentication. Tested on an accelerometer dataset with 347 users, our approach has demonstrated the promising results.

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

PubMed Central

Cho, Youngjun; Julier, Simon J.; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-01-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area. PMID:29082079

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging.

PubMed

Cho, Youngjun; Julier, Simon J; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-10-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.

Application of ion-sensitive sensors in water quality monitoring.

PubMed

Winkler, S; Rieger, L; Saracevic, E; Pressl, A; Gruber, G

2004-01-01

Within the last years a trend towards in-situ monitoring can be observed, i.e. most new sensors for water quality monitoring are designed for direct installation in the medium, compact in size and use measurement principles which minimise maintenance demand. Ion-sensitive sensors (Ion-Sensitive-Electrode--ISE) are based on a well known measurement principle and recently some manufacturers have released probe types which are specially adapted for application in water quality monitoring. The function principle of ISE-sensors, their advantages, limitations and the different methods for sensor calibration are described. Experiences with ISE-sensors from applications in sewer networks, at different sampling points within wastewater treatment plants and for surface water monitoring are reported. An estimation of investment and operation costs in comparison to other sensor types is given.

The application of a low-cost 3D depth camera for patient set-up and respiratory motion management in radiotherapy

NASA Astrophysics Data System (ADS)

Tahavori, Fatemeh

Respiratory motion induces uncertainty in External Beam Radiotherapy (EBRT), which can result in sub-optimal dose delivery to the target tissue and unwanted dose to normal tissue. The conventional approach to managing patient respiratory motion for EBRT within the area of abdominal-thoracic cancer is through the use of internal radiological imaging methods (e.g. Megavoltage imaging or Cone-Beam Computed Tomography) or via surrogate estimates of tumour position using external markers placed on the patient chest. This latter method uses tracking with video-based techniques, and relies on an assumed correlation or mathematical model, between the external surrogate signal and the internal target position. The marker's trajectory can be used in both respiratory gating techniques and real-time tracking methods. Internal radiological imaging methods bring with them limited temporal resolution, and additional radiation burden, which can be addressed by external marker-based methods that carry no such issues. Moreover, by including multiple external markers and placing them closer to the internal target organs, the effciency of correlation algorithms can be increased. However, the quality of such external monitoring methods is underpinned by the performance of the associated correlation model. Therefore, several new approaches to correlation modelling have been developed as part of this thesis and compared using publicly-available datasets. Highly competitive results have been obtained when compared against state-of-the-art methods. Marker-based methods also have the disadvantages of requiring manual set-up time for marker placement and patient positioning and potential issues with reproducibility of marker placement. This motivates the investigation of non-contact marker-free methods for use in EBRT, which is the main topic of this thesis. The Microsoft Kinect is used as an example of a low-cost consumer grade 3D depth camera for capturing and analysing external respiratory motion. This thesis makes the first presentation of detailed studies of external respiratory motion captured using such low-cost technology and demonstrates its potential in a healthcare environment. Firstly, the fundamental performance of a range of Microsoft Kinect sensors is assessed for use in radiotherapy (and potentially other healthcare applications), in terms of static and dynamic performance using both phantoms and volunteers. Then external respiratory motion is captured using the above technology from a group of 32 healthy volunteers and Principal Component Analysis (PCA) is applied to a region of interest encompassing the complete anterior surface to demonstrate breathing style. This work demonstrates that this surface motion can be compactly described by the first two PCA eigenvectors. The reproducibility of subject-specific EBRT set-up using conventional laser-based alignment and marker-based Deep Inspiration Breath Hold (DIBH) methods are also studied using the Microsoft Kinect sensor. A cohort of five healthy female volunteers is repeatedly set-up for left-sided breast cancer EBRT and multiple DIBH episodes captured over five separate sessions representing multiple fractionated radiotherapy treatment sessions, but without dose delivery. This provided an independent assessment that subjects were set-up and generally achieved variations within currently accepted margins of clinical practice. Moreover, this work demonstrated the potential role of consumer-grade 3D depth camera technology as a possible replacement for marker based set-up and DIBH management procedures. This brings with it the additional benefits of low cost, and potential through-put benefits, as patient set-up could ultimately be fully automated with this technology, and DIBH could be independently monitored without requiring preparatory manual intervention.

Mobile patient monitoring based on impedance-loaded SAW-sensors.

PubMed

Karilainen, Anna; Finnberg, Thomas; Uelzen, Thorsten; Dembowski, Klaus; Müller, Jörg

2004-11-01

A remotely requestable, passive, short-range sensor network for measuring small voltages is presented. The sensor system is able to simultaneously monitor six small voltages in millivolt-range, and it can be used for Holter-electrocardiogram (ECG) and other biopotential monitoring, or in industrial applications. The sensors are based on a surface acoustic wave (SAW) delay line with voltage-dependent, impedance loading on a reflector interdigital transducer (IDT). The load circuit impedance is varied by the capacitance of the voltage-controlled varactor. High resolution is achieved by developing a MOS-capacitor with a thin oxide, low flat-band voltage, and zero-voltage capacitance in the space-charge region, as well as a high-Q-microcoil by thick metal electroplating. Simultaneous monitoring of multiple potentials is realized by time-division-multiplexing of different sensor signals.

Continued Development of Compact Multi-Gas Monitor for Life Support Systems Control in Space

NASA Technical Reports Server (NTRS)

Delgado-Alonso, Jesus; Phillips, Straun; Berry, David; DiCarmine, Paul; Chullen, Cinda; Quinn, Gregory

2016-01-01

Miniature optical gas sensors based on luminescent materials have shown great potential as alternatives to NIR-based gas sensor systems for the Portable Life Support System (PLSS). The unique capability of luminescent sensors for carbon dioxide and oxygen monitoring under wet conditions has been reported, as has the fast recovery of humidity sensors after long periods of being wet. Lower volume and power requirements are also potential advantages over both traditional and advanced non-dispersive infrared (NDIR) gas sensors, which have so far shown longer life than luminescent sensors. In this paper we present the most recent results in the development and analytical validation of a compact multi-gas sensor unit based on luminescent sensors for the PLSS. Results of extensive testing are presented, including studies conducted in Intelligent Optical Systems laboratories, a United Technologies Corporation Aerospace Systems (UTC) laboratory, and a Johnson Space Center laboratory. The potential of this sensor technology for gas monitoring in PLSSs and other life support systems, and the advantages and limitations found through detailed sensor validation are discussed.

Motion analysis report

NASA Technical Reports Server (NTRS)

Badler, N. I.

1985-01-01

Human motion analysis is the task of converting actual human movements into computer readable data. Such movement information may be obtained though active or passive sensing methods. Active methods include physical measuring devices such as goniometers on joints of the body, force plates, and manually operated sensors such as a Cybex dynamometer. Passive sensing de-couples the position measuring device from actual human contact. Passive sensors include Selspot scanning systems (since there is no mechanical connection between the subject's attached LEDs and the infrared sensing cameras), sonic (spark-based) three-dimensional digitizers, Polhemus six-dimensional tracking systems, and image processing systems based on multiple views and photogrammetric calculations.

Sensor-based balance training with motion feedback in people with mild cognitive impairment.

PubMed

Schwenk, Michael; Sabbagh, Marwan; Lin, Ivy; Morgan, Pharah; Grewal, Gurtej S; Mohler, Jane; Coon, David W; Najafi, Bijan

2016-01-01

Some individuals with mild cognitive impairment (MCI) experience not only cognitive deficits but also a decline in motor function, including postural balance. This pilot study sought to estimate the feasibility, user experience, and effects of a novel sensor-based balance training program. Patients with amnestic MCI (mean age 78.2 yr) were randomized to an intervention group (IG, n = 12) or control group (CG, n = 10). The IG underwent balance training (4 wk, twice a week) that included weight shifting and virtual obstacle crossing. Real-time visual/audio lower-limb motion feedback was provided from wearable sensors. The CG received no training. User experience was measured by a questionnaire. Postintervention effects on balance (center of mass sway during standing with eyes open [EO] and eyes closed), gait (speed, variability), cognition, and fear of falling were measured. Eleven participants (92%) completed the training and expressed fun, safety, and helpfulness of sensor feedback. Sway (EO, p = 0.04) and fear of falling (p = 0.02) were reduced in the IG compared to the CG. Changes in other measures were nonsignificant. Results suggest that the sensor-based training paradigm is well accepted in the target population and beneficial for improving postural control. Future studies should evaluate the added value of the sensor-based training compared to traditional training.

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles.

PubMed

Lu, Xiaodong; Xie, Yuting; Zhou, Jun

2018-05-27

Inspired by the problem that the current spatial registration methods are unsuitable for three-dimensional (3-D) sensor on high-dynamic platform, this paper focuses on the estimation for the registration errors of cooperative missiles and motion states of maneuvering target. There are two types of errors being discussed: sensor measurement biases and attitude biases. Firstly, an improved Kalman Filter on Earth-Centered Earth-Fixed (ECEF-KF) coordinate algorithm is proposed to estimate the deviations mentioned above, from which the outcomes are furtherly compensated to the error terms. Secondly, the Pseudo Linear Kalman Filter (PLKF) and the nonlinear scheme the Unscented Kalman Filter (UKF) with modified inputs are employed for target tracking. The convergence of filtering results are monitored by a position-judgement logic, and a low-pass first order filter is selectively introduced before compensation to inhibit the jitter of estimations. In the simulation, the ECEF-KF enhancement is proven to improve the accuracy and robustness of the space alignment, while the conditional-compensation-based PLKF method is demonstrated to be the optimal performance in target tracking.

Energy scavenging sources for biomedical sensors.

PubMed

Romero, E; Warrington, R O; Neuman, M R

2009-09-01

Energy scavenging has increasingly become an interesting option for powering electronic devices because of the almost infinite lifetime and the non-dependence on fuels for energy generation. Moreover, the rise of wireless technologies promises new applications in medical monitoring systems, but these still face limitations due to battery lifetime and size. A trade-off of these two factors has typically governed the size, useful life and capabilities of an autonomous system. Energy generation from sources such as motion, light and temperature gradients has been established as commercially viable alternatives to batteries for human-powered flashlights, solar calculators, radio receivers and thermal-powered wristwatches, among others. Research on energy harvesting from human activities has also addressed the feasibility of powering wearable or implantable systems. Biomedical sensors can take advantage of human-based activities as the energy source for energy scavengers. This review describes the state of the art of energy scavenging technologies for powering sensors and instrumentation of physiological variables. After a short description of the human power and the energy generation limits, the different transduction mechanisms, recent developments and challenges faced are reviewed and discussed.

Determining the 3-D structure and motion of objects using a scanning laser range sensor

NASA Technical Reports Server (NTRS)

Nandhakumar, N.; Smith, Philip W.

1993-01-01

In order for the EVAHR robot to autonomously track and grasp objects, its vision system must be able to determine the 3-D structure and motion of an object from a sequence of sensory images. This task is accomplished by the use of a laser radar range sensor which provides dense range maps of the scene. Unfortunately, the currently available laser radar range cameras use a sequential scanning approach which complicates image analysis. Although many algorithms have been developed for recognizing objects from range images, none are suited for use with single beam, scanning, time-of-flight sensors because all previous algorithms assume instantaneous acquisition of the entire image. This assumption is invalid since the EVAHR robot is equipped with a sequential scanning laser range sensor. If an object is moving while being imaged by the device, the apparent structure of the object can be significantly distorted due to the significant non-zero delay time between sampling each image pixel. If an estimate of the motion of the object can be determined, this distortion can be eliminated; but, this leads to the motion-structure paradox - most existing algorithms for 3-D motion estimation use the structure of objects to parameterize their motions. The goal of this research is to design a rigid-body motion recovery technique which overcomes this limitation. The method being developed is an iterative, linear, feature-based approach which uses the non-zero image acquisition time constraint to accurately recover the motion parameters from the distorted structure of the 3-D range maps. Once the motion parameters are determined, the structural distortion in the range images is corrected.

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments.

PubMed

Roy, Nirmalya; Misra, Archan; Cook, Diane

2016-02-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional 'hidden' context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions.

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments

PubMed Central

Misra, Archan; Cook, Diane

2016-01-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional ‘hidden’ context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions. PMID:27042240

Web-Based Interface for Command and Control of Network Sensors

NASA Technical Reports Server (NTRS)

Wallick, Michael N.; Doubleday, Joshua R.; Shams, Khawaja S.

2010-01-01

This software allows for the visualization and control of a network of sensors through a Web browser interface. It is currently being deployed for a network of sensors monitoring Mt. Saint Helen s volcano; however, this innovation is generic enough that it can be deployed for any type of sensor Web. From this interface, the user is able to fully control and monitor the sensor Web. This includes, but is not limited to, sending "test" commands to individual sensors in the network, monitoring for real-world events, and reacting to those events

Using Custom Fiber Bragg Grating-Based Sensors to Monitor Artificial Landslides.

PubMed

Zhang, Qinghua; Wang, Yuan; Sun, Yangyang; Gao, Lei; Zhang, Zhenglin; Zhang, Wenyuan; Zhao, Pengchong; Yue, Yin

2016-09-02

Four custom fiber Bragg grating (FBG)-based sensors are developed to monitor an artificial landslide located in Nanjing, China. The sensors are composed of a rod and two FBGs. Based on the strength of the rods, two sensors are referred to as "hard sensors" (Sensor 1 and Sensor 2), the other two are referred to as "soft sensors" (Sensor 3 and Sensor 4). The two FBGs are fixed on each sensor rod at distances of 50 cm and 100 cm from the top of the rod (an upper FBG and a lower FBG). In the experiment presented in this paper, the sensors are installed on a slope on which an artificial landslide is generated through both machine-based and manual excavation. The fiber sensing system consists of the four custom FBG-based sensors, optical fiber, a static fiber grating demodulation instrument (SM125), and a PC with the necessary software. Experimental data was collected in the presence of an artificial landslide, and the results show that the lower FBGs are more sensitive than the upper FBGs for all four of the custom sensors. It was also found that Sensor 2 and Sensor 4 are more capable of monitoring small-scale landslides than Sensor 1 and Sensor 3, and this is mainly due to their placement location with respect to the landslide. The stronger rods used in the hard sensors make them more adaptable to the harsh environments of large landslides. Thus, hard sensors should be fixed near the landslide, while soft sensors should be placed farther away from the landslide. In addition, a clear tendency of strain variation can be detected by the soft sensors, which can be used to predict landslides and raise a hazard alarm.

Multi-Wavelength Based Optical Density Sensor for Autonomous Monitoring of Microalgae

PubMed Central

Jia, Fei; Kacira, Murat; Ogden, Kimberly L.

2015-01-01

A multi-wavelength based optical density sensor unit was designed, developed, and evaluated to monitor microalgae growth in real time. The system consisted of five main components including: (1) laser diode modules as light sources; (2) photodiodes as detectors; (3) driver circuit; (4) flow cell; and (5) sensor housing temperature controller. The sensor unit was designed to be integrated into any microalgae culture system for both real time and non-real time optical density measurements and algae growth monitoring applications. It was shown that the sensor unit was capable of monitoring the dynamics and physiological changes of the microalgae culture in real-time. Algae biomass concentration was accurately estimated with optical density measurements at 650, 685 and 780 nm wavelengths used by the sensor unit. The sensor unit was able to monitor cell concentration as high as 1.05 g·L−1 (1.51 × 108 cells·mL−1) during the culture growth without any sample preparation for the measurements. Since high cell concentrations do not need to be diluted using the sensor unit, the system has the potential to be used in industrial microalgae cultivation systems for real time monitoring and control applications that can lead to improved resource use efficiency. PMID:26364640

Flexible and Compressible PEDOT:PSS@Melamine Conductive Sponge Prepared via One-Step Dip Coating as Piezoresistive Pressure Sensor for Human Motion Detection.

PubMed

Ding, Yichun; Yang, Jack; Tolle, Charles R; Zhu, Zhengtao

2018-05-09

Flexible and wearable pressure sensor may offer convenient, timely, and portable solutions to human motion detection, yet it is a challenge to develop cost-effective materials for pressure sensor with high compressibility and sensitivity. Herein, a cost-efficient and scalable approach is reported to prepare a highly flexible and compressible conductive sponge for piezoresistive pressure sensor. The conductive sponge, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)@melamine sponge (MS), is prepared by one-step dip coating the commercial melamine sponge (MS) in an aqueous dispersion of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). Due to the interconnected porous structure of MS, the conductive PEDOT:PSS@MS has a high compressibility and a stable piezoresistive response at the compressive strain up to 80%, as well as good reproducibility over 1000 cycles. Thereafter, versatile pressure sensors fabricated using the conductive PEDOT:PSS@MS sponges are attached to the different parts of human body; the capabilities of these devices to detect a variety of human motions including speaking, finger bending, elbow bending, and walking are evaluated. Furthermore, prototype tactile sensory array based on these pressure sensors is demonstrated.

A Personal Navigation System Based on Inertial and Magnetic Field Measurements

DTIC Science & Technology

2010-09-01

MATLAB IMPLEMENTATION.................................................................74 G. A MODEL FOR PENDULUM MOTION SENSOR DATA...76 1. Pendulum Model for MATLAB Simulation....................................76 2. Sensor Data Generated with the Pendulum Model... PENDULUM ..................................................................................................88 I. FILTER PERFORMANCE WITH REAL PENDULUM DATA

Skyhook gravitational-wave detector

NASA Astrophysics Data System (ADS)

Braginskii, V. B.; Thorne, K. S.

1985-08-01

A new and more sensitive type of earth-orbiting gravitational wave detector, called a 'skyhook', which would operate in the 10-100 mHz band, is proposed. The skyhook would consist of two masses, one on each end of a long thin cable with a spring at its center. As it orbits the earth, the cable wold be stretched radially by the earth's tidal gravitational field. Gravitational waves would pull the masses apart and push them together in an oscillatory fashion. Their motion would be transmitted to the spring by the cable, and a sensor would monitor the spring's resulting motion.

Freestanding, Fiber-Based, Wearable Temperature Sensor with Tunable Thermal Index for Healthcare Monitoring.

PubMed

Trung, Tran Quang; Le, Hoang Sinh; Dang, Thi My Linh; Ju, Sanghyun; Park, Sang Yoon; Lee, Nae-Eung

2018-06-01

Fiber-based sensors integrated on textiles or clothing systems are required for the next generation of wearable electronic platforms. Fiber-based physical sensors are developed, but the development of fiber-based temperature sensors is still limited. Herein, a new approach to develop wearable temperature sensors that use freestanding single reduction graphene oxide (rGO) fiber is proposed. A freestanding and wearable temperature-responsive rGO fiber with tunable thermal index is obtained using simple wet spinning and a controlled graphene oxide reduction time. The freestanding fiber-based temperature sensor shows high responsivity, fast response time (7 s), and good recovery time (20 s) to temperature. It also maintains its response under an applied mechanical deformation. The fiber device fabricated by means of a simple process is easily integrated into fabric such as socks or undershirts and can be worn by a person to monitor the temperature of the environment and skin temperature without interference during movement and various activities. These results demonstrate that the freestanding fiber-based temperature sensor has great potential for fiber-based wearable electronic platforms. It is also promising for applications in healthcare and biomedical monitoring. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

New generation of wearable goniometers for motion capture systems

PubMed Central

2014-01-01

Background Monitoring joint angles through wearable systems enables human posture and gesture to be reconstructed as a support for physical rehabilitation both in clinics and at the patient’s home. A new generation of wearable goniometers based on knitted piezoresistive fabric (KPF) technology is presented. Methods KPF single-and double-layer devices were designed and characterized under stretching and bending to work as strain sensors and goniometers. The theoretical working principle and the derived electromechanical model, previously proved for carbon elastomer sensors, were generalized to KPF. The devices were used to correlate angles and piezoresistive fabric behaviour, to highlight the differences in terms of performance between the single layer and the double layer sensors. A fast calibration procedure is also proposed. Results The proposed device was tested both in static and dynamic conditions in comparison with standard electrogoniometers and inertial measurement units respectively. KPF goniometer capabilities in angle detection were experimentally proved and a discussion of the device measurement errors of is provided. The paper concludes with an analysis of sensor accuracy and hysteresis reduction in particular configurations. Conclusions Double layer KPF goniometers showed a promising performance in terms of angle measurements both in quasi-static and dynamic working mode for velocities typical of human movement. A further approach consisting of a combination of multiple sensors to increase accuracy via sensor fusion technique has been presented. PMID:24725669

Motion-compensated detection of heart rate based on the time registration adaptive filter

NASA Astrophysics Data System (ADS)

Yang, Lei; Zhou, Jinsong; Jing, Juanjuan; Li, Yacan; Wei, Lidong; Feng, Lei; He, Xiaoying; Bu, Meixia; Fu, Xilu

2018-01-01

A non-contact heart rate detection method based on the dual-wavelength technique is proposed and demonstrated experimentally. The heart rate is obtained based on the PhotoPlethysmoGraphy (PPG). Each detection module uses the reflection detection probe which is composed of the LED and the photodiode. It is a well-known fact that the differences in the circuits of two detection modules result in different responses of two modules for motion artifacts. It will cause a time delay between the two signals. This poses a great challenge to compensate the motion artifacts during measurements. In order to solve this problem, we have firstly used the time registration and translated the signals to ensure that the two signals are consistent in time domain. Then the adaptive filter is used to compensate the motion artifacts. Moreover, the data obtained by using this non-contact detection system is compared with those of the conventional finger blood volume pulse (BVP) sensor by simultaneously measuring the heart rate of the subject. During the experiment, the left hand remains stationary and is detected by a conventional finger BVP sensor. Meanwhile, the moving palm of right hand is detected by the proposed system. The data obtained from the proposed non-contact system are consistent and comparable with that of the BVP sensor. This method can effectively suppress the interference caused by the two circuit differences and successfully compensate the motion artifacts. This technology can be used in medical and daily heart rate measurement.

Respiratory monitoring by inductive plethysmography in unrestrained subjects using position sensor-adjusted calibration.

PubMed

Brüllmann, Gregor; Fritsch, Karsten; Thurnheer, Robert; Bloch, Konrad E

2010-01-01

Portable respiratory inductive plethysmography (RIP) is promising for noninvasive monitoring of breathing patterns in unrestrained subjects. However, its use has been hampered by requiring recalibration after changes in body position. To facilitate RIP application in unrestrained subjects, we developed a technique for adjustment of RIP calibration using position sensor feedback. Five healthy subjects and 12 patients with lung disease were monitored by portable RIP with sensors incorporated within a body garment. Unrestrained individuals were studied during 40-60 min while supine, sitting and upright/walking. Position was changed repeatedly every 5-10 min. Initial qualitative diagnostic calibration followed by volume scaling in absolute units during 20 breaths in different positions by flow meter provided position-specific volume-motion coefficients for RIP. These were applied during subsequent monitoring in corresponding positions according to feedback from 4 accelerometers placed at the chest and thigh. Accuracy of RIP was evaluated by face mask pneumotachography. Position sensor feedback allowed accurate adjustment of RIP calibration during repeated position changes in subjects and patients as reflected in a minor mean difference (bias) in breath-by-breath tidal volumes estimated by RIP and flow meter of 0.02 liters (not significant) and limits of agreement (+/-2 SD) of +/-19% (2,917 comparisons). An average of 10 breaths improved precision of RIP (limits of agreement +/-14%). RIP calibration incorporating position sensor feedback greatly enhances the application of RIP as a valuable, unobtrusive tool to investigate respiratory physiology and ventilatory limitation in unrestrained healthy subjects and patients with lung disease during everyday activities including position changes. Copyright 2009 S. Karger AG, Basel.

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Rajeeva; Kumar, Aditya; Dai, Dan

2012-12-31

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developedmore » will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.« less

Orientation-independent measures of ground motion

USGS Publications Warehouse

Boore, D.M.; Watson-Lamprey, Jennie; Abrahamson, N.A.

2006-01-01

The geometric mean of the response spectra for two orthogonal horizontal components of motion, commonly used as the response variable in predictions of strong ground motion, depends on the orientation of the sensors as installed in the field. This means that the measure of ground-motion intensity could differ for the same actual ground motion. This dependence on sensor orientation is most pronounced for strongly correlated motion (the extreme example being linearly polarized motion), such as often occurs at periods of 1 sec or longer. We propose two new measures of the geometric mean, GMRotDpp, and GMRotIpp, that are independent of the sensor orientations. Both are based on a set of geometric means computed from the as-recorded orthogonal horizontal motions rotated through all possible non-redundant rotation angles. GMRotDpp is determined as the ppth percentile of the set of geometric means for a given oscillator period. For example, GMRotDOO, GMRotD50, and GMRotD100 correspond to the minimum, median, and maximum values, respectively. The rotations that lead to GMRotDpp depend on period, whereas a single-period-independent rotation is used for GMRotIpp, the angle being chosen to minimize the spread of the rotation-dependent geometric mean (normalized by GMRotDpp) over the usable range of oscillator periods. GMRotI50 is the ground-motion intensity measure being used in the development of new ground-motion prediction equations by the Pacific Earthquake Engineering Center Next Generation Attenuation project. Comparisons with as-recorded geometric means for a large dataset show that the new measures are systematically larger than the geometric-mean response spectra using the as-recorded values of ground acceleration, but only by a small amount (less than 3%). The theoretical advantage of the new measures is that they remove sensor orientation as a contributor to aleatory uncertainty. Whether the reduction is of practical significance awaits detailed studies of large datasets. A preliminary analysis contained in a companion article by Beyer and Bommer finds that the reduction is small-to-nonexistent for equations based on a wide range of magnitudes and distances. The results of Beyer and Bommer do suggest, however, that there is an increasing reduction as period increases. Whether the reduction increases with other subdivisions of the dataset for which strongly correlated motions might be expected (e.g., pulselike motions close to faults) awaits further analysis.

Low-cost and disposable pressure sensor mat for non-invasive sleep and movement monitoring applications.

PubMed

Abraham, Jose K; Sullivan, Shawn; Ranganathan, Sridhar

2011-01-01

Sleep has profound effects on the physical and mental well-being of an individual. The National Institutes of Health (NIH) Sleep Disorder Research Plan gives particular emphasis to non-invasive sleep monitoring methods. Older adults experience sleep fragmentation due to sleep disorders. Unobtrusive non-contact monitoring can be the only realistic solution for long term home-based sleep monitoring. The demand for a low-cost and non-invasive sleep monitoring system for in-home use is more than before due to an increasingly stressful life style. Cost and complexity of current sensor elements hinder the development of low-cost sleep monitoring devices for in-home use. This paper presents the design, development and implementation of a low-cost and disposable pressure sensor mat that could be useful for in-home sleep and movement monitoring applications. The sensor mat design is based on a compressible foam sandwiched between two orthogonal arrays of cPaper capacitance sensors. A low-cost conducting paper has been developed for use as the capacitance sensor electrode. Typical mat design uses a 3 mm thick foam with 5 mm row/column grid array shows that it has a measurement resolution of 0.1 PSI pressure. The resolution can be controlled by both modifying properties of the conducting paper and the foam. Since this pressure mat design is based on low-cost paper, the sensor electrodes are disposable or semi-durable and hence it is ideal for the use in point-of-care physiological monitoring, pervasive healthcare and consumer electronic devices.

A zero power harmonic transponder sensor for ubiquitous wireless μL liquid-volume monitoring

NASA Astrophysics Data System (ADS)

Huang, Haiyu; Chen, Pai-Yen; Hung, Cheng-Hsien; Gharpurey, Ranjit; Akinwande, Deji

2016-01-01

Autonomous liquid-volume monitoring is crucial in ubiquitous healthcare. However, conventional approach is based on either human visual observation or expensive detectors, which are costly for future pervasive monitoring. Here we introduce a novel approach based on passive harmonic transponder antenna sensor and frequency hopping spread spectrum (FHSS) pattern analysis, to provide a very low cost wireless μL-resolution liquid-volume monitoring without battery or digital circuits. In our conceptual demonstration, the harmonic transponder comprises of a passive nonlinear frequency multiplier connected to a metamaterial-inspired 3-D antenna designed to be highly sensitive to the liquid-volume within a confined region. The transponder first receives some FHSS signal from an interrogator, then converts such signal to its harmonic band and re-radiates through the antenna sensor. The harmonic signal is picked up by a sniffer receiver and decoded through pattern analysis of the high dimensional FHSS signal strength data. A robust, zero power, absolute accuracy wireless liquid-volume monitoring is realized in the presence of strong direct coupling, background scatters, distance variance as well as near-field human-body interference. The concepts of passive harmonic transponder sensor, metamaterial-inspired antenna sensor, and FHSS pattern analysis based sensor decoding may help establishing cost-effective, energy-efficient and intelligent wireless pervasive healthcare monitoring platforms.

A zero power harmonic transponder sensor for ubiquitous wireless μL liquid-volume monitoring.

PubMed

Huang, Haiyu; Chen, Pai-Yen; Hung, Cheng-Hsien; Gharpurey, Ranjit; Akinwande, Deji

2016-01-06

Autonomous liquid-volume monitoring is crucial in ubiquitous healthcare. However, conventional approach is based on either human visual observation or expensive detectors, which are costly for future pervasive monitoring. Here we introduce a novel approach based on passive harmonic transponder antenna sensor and frequency hopping spread spectrum (FHSS) pattern analysis, to provide a very low cost wireless μL-resolution liquid-volume monitoring without battery or digital circuits. In our conceptual demonstration, the harmonic transponder comprises of a passive nonlinear frequency multiplier connected to a metamaterial-inspired 3-D antenna designed to be highly sensitive to the liquid-volume within a confined region. The transponder first receives some FHSS signal from an interrogator, then converts such signal to its harmonic band and re-radiates through the antenna sensor. The harmonic signal is picked up by a sniffer receiver and decoded through pattern analysis of the high dimensional FHSS signal strength data. A robust, zero power, absolute accuracy wireless liquid-volume monitoring is realized in the presence of strong direct coupling, background scatters, distance variance as well as near-field human-body interference. The concepts of passive harmonic transponder sensor, metamaterial-inspired antenna sensor, and FHSS pattern analysis based sensor decoding may help establishing cost-effective, energy-efficient and intelligent wireless pervasive healthcare monitoring platforms.

A zero power harmonic transponder sensor for ubiquitous wireless μL liquid-volume monitoring

PubMed Central

Huang, Haiyu; Chen, Pai-Yen; Hung, Cheng-Hsien; Gharpurey, Ranjit; Akinwande, Deji

2016-01-01

Autonomous liquid-volume monitoring is crucial in ubiquitous healthcare. However, conventional approach is based on either human visual observation or expensive detectors, which are costly for future pervasive monitoring. Here we introduce a novel approach based on passive harmonic transponder antenna sensor and frequency hopping spread spectrum (FHSS) pattern analysis, to provide a very low cost wireless μL-resolution liquid-volume monitoring without battery or digital circuits. In our conceptual demonstration, the harmonic transponder comprises of a passive nonlinear frequency multiplier connected to a metamaterial-inspired 3-D antenna designed to be highly sensitive to the liquid-volume within a confined region. The transponder first receives some FHSS signal from an interrogator, then converts such signal to its harmonic band and re-radiates through the antenna sensor. The harmonic signal is picked up by a sniffer receiver and decoded through pattern analysis of the high dimensional FHSS signal strength data. A robust, zero power, absolute accuracy wireless liquid-volume monitoring is realized in the presence of strong direct coupling, background scatters, distance variance as well as near-field human-body interference. The concepts of passive harmonic transponder sensor, metamaterial-inspired antenna sensor, and FHSS pattern analysis based sensor decoding may help establishing cost-effective, energy-efficient and intelligent wireless pervasive healthcare monitoring platforms. PMID:26732251

Design and Evaluation of Novel Textile Wearable Systems for the Surveillance of Vital Signals.

PubMed

Trindade, Isabel G; Machado da Silva, José; Miguel, Rui; Pereira, Madalena; Lucas, José; Oliveira, Luís; Valentim, Bruno; Barreto, Jorge; Santos Silva, Manuel

2016-09-24

This article addresses the design, development, and evaluation of T-shirt prototypes that embed novel textile sensors for the capture of cardio and respiratory signals. The sensors are connected through textile interconnects to either an embedded custom-designed data acquisition and transmission unit or to snap fastener terminals for connection to external monitoring devices. The performance of the T-shirt prototype is evaluated in terms of signal-to-noise ratio amplitude and signal interference caused by baseline wander and motion artefacts, through laboratory tests with subjects in standing and walking conditions. Performance tests were also conducted in a hospital environment using a T-shirt prototype connected to a commercial three-channel Holter monitoring device. The textile sensors and interconnects were realized with the assistance of an industrial six-needle digital embroidery tool and their resistance to wear addressed with normalized tests of laundering and abrasion. The performance of these wearable systems is discussed, and pathways and methods for their optimization are highlighted.

Design and Evaluation of Novel Textile Wearable Systems for the Surveillance of Vital Signals

PubMed Central

Trindade, Isabel G.; Machado da Silva, José; Miguel, Rui; Pereira, Madalena; Lucas, José; Oliveira, Luís; Valentim, Bruno; Barreto, Jorge; Santos Silva, Manuel

2016-01-01

This article addresses the design, development, and evaluation of T-shirt prototypes that embed novel textile sensors for the capture of cardio and respiratory signals. The sensors are connected through textile interconnects to either an embedded custom-designed data acquisition and transmission unit or to snap fastener terminals for connection to external monitoring devices. The performance of the T-shirt prototype is evaluated in terms of signal-to-noise ratio amplitude and signal interference caused by baseline wander and motion artefacts, through laboratory tests with subjects in standing and walking conditions. Performance tests were also conducted in a hospital environment using a T-shirt prototype connected to a commercial three-channel Holter monitoring device. The textile sensors and interconnects were realized with the assistance of an industrial six-needle digital embroidery tool and their resistance to wear addressed with normalized tests of laundering and abrasion. The performance of these wearable systems is discussed, and pathways and methods for their optimization are highlighted. PMID:27669263

Monitoring of Vital Signs with Flexible and Wearable Medical Devices.

PubMed

Khan, Yasser; Ostfeld, Aminy E; Lochner, Claire M; Pierre, Adrien; Arias, Ana C

2016-06-01

Advances in wireless technologies, low-power electronics, the internet of things, and in the domain of connected health are driving innovations in wearable medical devices at a tremendous pace. Wearable sensor systems composed of flexible and stretchable materials have the potential to better interface to the human skin, whereas silicon-based electronics are extremely efficient in sensor data processing and transmission. Therefore, flexible and stretchable sensors combined with low-power silicon-based electronics are a viable and efficient approach for medical monitoring. Flexible medical devices designed for monitoring human vital signs, such as body temperature, heart rate, respiration rate, blood pressure, pulse oxygenation, and blood glucose have applications in both fitness monitoring and medical diagnostics. As a review of the latest development in flexible and wearable human vitals sensors, the essential components required for vitals sensors are outlined and discussed here, including the reported sensor systems, sensing mechanisms, sensor fabrication, power, and data processing requirements. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A New Corrosion Sensor to Determine the Start and Development of Embedded Rebar Corrosion Process at Coastal Concrete

PubMed Central

Xu, Chen; Li, Zhiyuan; Jin, Weiliang

2013-01-01

The corrosion of reinforcements induced by chloride has resulted to be one of the most frequent causes of their premature damage. Most corrosion sensors were designed to monitor corrosion state in concrete, such as Anode-Ladder-System and Corrowatch System, which are widely used to monitor chloride ingress in marine concrete. However, the monitoring principle of these corrosion sensors is based on the macro-cell test method, so erroneous information may be obtained, especially from concrete under drying or saturated conditions due to concrete resistance taking control in macro-cell corrosion. In this paper, a fast weak polarization method to test corrosion state of reinforcements based on electrochemical polarization dynamics was proposed. Furthermore, a new corrosion sensor for monitoring the corrosion state of concrete cover was developed based on the proposed test method. The sensor was tested in cement mortar, with dry-wet cycle tests to accelerate the chloride ingress rate. The results show that the corrosion sensor can effectively monitor chloride penetration into concrete with little influence of the relative humidity in the concrete. With a reasonable corrosion sensor electrode arrangement, it seems the Ohm-drop effect measured by EIS can be ignored, which makes the tested electrochemical parameters more accurate. PMID:24084117

A new corrosion sensor to determine the start and development of embedded rebar corrosion process at coastal concrete.

PubMed

Xu, Chen; Li, Zhiyuan; Jin, Weiliang

2013-09-30

The corrosion of reinforcements induced by chloride has resulted to be one of the most frequent causes of their premature damage. Most corrosion sensors were designed to monitor corrosion state in concrete, such as Anode-Ladder-System and Corrowatch System, which are widely used to monitor chloride ingress in marine concrete. However, the monitoring principle of these corrosion sensors is based on the macro-cell test method, so erroneous information may be obtained, especially from concrete under drying or saturated conditions due to concrete resistance taking control in macro-cell corrosion. In this paper, a fast weak polarization method to test corrosion state of reinforcements based on electrochemical polarization dynamics was proposed. Furthermore, a new corrosion sensor for monitoring the corrosion state of concrete cover was developed based on the proposed test method. The sensor was tested in cement mortar, with dry-wet cycle tests to accelerate the chloride ingress rate. The results show that the corrosion sensor can effectively monitor chloride penetration into concrete with little influence of the relative humidity in the concrete. With a reasonable corrosion sensor electrode arrangement, it seems the Ohm-drop effect measured by EIS can be ignored, which makes the tested electrochemical parameters more accurate.

A theoretical model to predict both horizontal displacement and vertical displacement for electromagnetic induction-based deep displacement sensors.

PubMed

Shentu, Nanying; Zhang, Hongjian; Li, Qing; Zhou, Hongliang; Tong, Renyuan; Li, Xiong

2012-01-01

Deep displacement observation is one basic means of landslide dynamic study and early warning monitoring and a key part of engineering geological investigation. In our previous work, we proposed a novel electromagnetic induction-based deep displacement sensor (I-type) to predict deep horizontal displacement and a theoretical model called equation-based equivalent loop approach (EELA) to describe its sensing characters. However in many landslide and related geological engineering cases, both horizontal displacement and vertical displacement vary apparently and dynamically so both may require monitoring. In this study, a II-type deep displacement sensor is designed by revising our I-type sensor to simultaneously monitor the deep horizontal displacement and vertical displacement variations at different depths within a sliding mass. Meanwhile, a new theoretical modeling called the numerical integration-based equivalent loop approach (NIELA) has been proposed to quantitatively depict II-type sensors' mutual inductance properties with respect to predicted horizontal displacements and vertical displacements. After detailed examinations and comparative studies between measured mutual inductance voltage, NIELA-based mutual inductance and EELA-based mutual inductance, NIELA has verified to be an effective and quite accurate analytic model for characterization of II-type sensors. The NIELA model is widely applicable for II-type sensors' monitoring on all kinds of landslides and other related geohazards with satisfactory estimation accuracy and calculation efficiency.

Optical fiber grating vibration sensor for vibration monitoring of hydraulic pump

NASA Astrophysics Data System (ADS)

Zhang, Zhengyi; Liu, Chuntong; Li, Hongcai; He, Zhenxin; Zhao, Xiaofeng

2017-06-01

In view of the existing electrical vibration monitoring traditional hydraulic pump vibration sensor, the high false alarm rate is susceptible to electromagnetic interference and is not easy to achieve long-term reliable monitoring, based on the design of a beam of the uniform strength structure of the fiber Bragg grating (FBG) vibration sensor. In this paper, based on the analysis of the vibration theory of the equal strength beam, the principle of FBG vibration tuning based on the equal intensity beam is derived. According to the practical application of the project, the structural dimensions of the equal strength beam are determined, and the optimization design of the vibrator is carried out. The finite element analysis of the sensor is carried out by ANSYS, and the first order resonant frequency is 94.739 Hz. The vibration test of the sensor is carried out by using the vibration frequency of 35 Hz and the vibration source of 50 Hz. The time domain and frequency domain analysis results of test data show that the sensor has good dynamic response characteristics, which can realize the accurate monitoring of the vibration frequency and meet the special requirements of vibration monitoring of hydraulic pump under specific environment.

Distinguishing the causes of falls in humans using an array of wearable tri-axial accelerometers.

PubMed

Aziz, Omar; Park, Edward J; Mori, Greg; Robinovitch, Stephen N

2014-01-01

Falls are the number one cause of injury in older adults. Lack of objective evidence on the cause and circumstances of falls is often a barrier to effective prevention strategies. Previous studies have established the ability of wearable miniature inertial sensors (accelerometers and gyroscopes) to automatically detect falls, for the purpose of delivering medical assistance. In the current study, we extend the applications of this technology, by developing and evaluating the accuracy of wearable sensor systems for determining the cause of falls. Twelve young adults participated in experimental trials involving falls due to seven causes: slips, trips, fainting, and incorrect shifting/transfer of body weight while sitting down, standing up from sitting, reaching and turning. Features (means and variances) of acceleration data acquired from four tri-axial accelerometers during the falling trials were input to a linear discriminant analysis technique. Data from an array of three sensors (left ankle+right ankle+sternum) provided at least 83% sensitivity and 89% specificity in classifying falls due to slips, trips, and incorrect shift of body weight during sitting, reaching and turning. Classification of falls due to fainting and incorrect shift during rising was less successful across all sensor combinations. Furthermore, similar classification accuracy was observed with data from wearable sensors and a video-based motion analysis system. These results establish a basis for the development of sensor-based fall monitoring systems that provide information on the cause and circumstances of falls, to direct fall prevention strategies at a patient or population level. Copyright © 2013 Elsevier B.V. All rights reserved.

A fabric wrist patch sensor for continuous and comprehensive monitoring of the cardiovascular system.

PubMed

Kwonjoon Lee; Kiseok Song; Taehwan Roh; Hoi-Jun Yoo

2016-08-01

The wrist patch-type ECG/APW sensor system is proposed for continuous and comprehensive monitoring of the patient's cardiovascular system. The wrist patch-type ECG/APW sensor system is consists of ECG/APW sensor, ECG/APW electrodes, and base station for real-time monitoring of the patient's status. The ECG/APW sensor and electrodes are composed of wrist patch, bandage-type ECG electrode and fabric APW electrode, respectively so that the patient's cardiovascular system can be continuously monitored in daily life with free hand-movement. Since the proposed wrist patchtype ECG/APW sensor simultaneously measures ECG/APW, the cardiac indicators, such as HR and PAT, can be extracted for comprehensive and accurate monitoring of the patient's cardiovascular system. The proposed wrist patch-type ECG/APW sensor system is successfully verified using the commercial PPG sensor (RP520) and demonstrated with the customized Android application on the smart phone.

A novel wearable smart button system for fall detection

NASA Astrophysics Data System (ADS)

Zhuang, Wei; Sun, Xiang; Zhi, Yueyan; Han, Yue; Mao, Hande

2017-05-01

Fall has been the second most cause of accidental injury to death in the world. It has been a serious threat to the physical and mental health of the elders. Therefore, developing wearable node system with fall detecting ability has become increasingly pressing at present. A novel smart button for long-term fall detection is proposed in this paper, which is able to accurately monitor the falling behavior, and sending warning message online as well. The smart button is based on the tri-axis acceleration sensor which is used to collect the body motion signals. By using the statistical metrics of acceleration characteristics, a new SVM classification algorithm with high positive accuracy and stability is proposed so as to classify the falls and activities of daily living, and the results can be real-time displayed on Android based mobile phone. The experiments show that our wearable node system can continuously monitor the falling behavior with positive rate 94.8%.