A Printed Organic Amplification System for Wearable Potentiometric Electrochemical Sensors.

PubMed

Shiwaku, Rei; Matsui, Hiroyuki; Nagamine, Kuniaki; Uematsu, Mayu; Mano, Taisei; Maruyama, Yuki; Nomura, Ayako; Tsuchiya, Kazuhiko; Hayasaka, Kazuma; Takeda, Yasunori; Fukuda, Takashi; Kumaki, Daisuke; Tokito, Shizuo

2018-03-02

Electrochemical sensor systems with integrated amplifier circuits play an important role in measuring physiological signals via in situ human perspiration analysis. Signal processing circuitry based on organic thin-film transistors (OTFTs) have significant potential in realizing wearable sensor devices due to their superior mechanical flexibility and biocompatibility. Here, we demonstrate a novel potentiometric electrochemical sensing system comprised of a potassium ion (K + ) sensor and amplifier circuits employing OTFT-based pseudo-CMOS inverters, which have a highly controllable switching voltage and closed-loop gain. The ion concentration sensitivity of the fabricated K + sensor was 34 mV/dec, which was amplified to 160 mV/dec (by a factor of 4.6) with high linearity. The developed system is expected to help further the realization of ultra-thin and flexible wearable sensor devices for healthcare applications.

Identification of cigarette smoke inhalations from wearable sensor data using a Support Vector Machine classifier.

PubMed

Lopez-Meyer, Paulo; Tiffany, Stephen; Sazonov, Edward

2012-01-01

This study presents a subject-independent model for detection of smoke inhalations from wearable sensors capturing characteristic hand-to-mouth gestures and changes in breathing patterns during cigarette smoking. Wearable sensors were used to detect the proximity of the hand to the mouth and to acquire the respiratory patterns. The waveforms of sensor signals were used as features to build a Support Vector Machine classification model. Across a data set of 20 enrolled participants, precision of correct identification of smoke inhalations was found to be >87%, and a resulting recall >80%. These results suggest that it is possible to analyze smoking behavior by means of a wearable and non-invasive sensor system.

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.

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.

Sensitivity-Enhanced Wearable Active Voiceprint Sensor Based on Cellular Polypropylene Piezoelectret.

PubMed

Li, Wenbo; Zhao, Sheng; Wu, Nan; Zhong, Junwen; Wang, Bo; Lin, Shizhe; Chen, Shuwen; Yuan, Fang; Jiang, Hulin; Xiao, Yongjun; Hu, Bin; Zhou, Jun

2017-07-19

Wearable active sensors have extensive applications in mobile biosensing and human-machine interaction but require good flexibility, high sensitivity, excellent stability, and self-powered feature. In this work, cellular polypropylene (PP) piezoelectret was chosen as the core material of a sensitivity-enhanced wearable active voiceprint sensor (SWAVS) to realize voiceprint recognition. By virtue of the dipole orientation control method, the air layers in the piezoelectret were efficiently utilized, and the current sensitivity was enhanced (from 1.98 pA/Hz to 5.81 pA/Hz at 115 dB). The SWAVS exhibited the superiorities of high sensitivity, accurate frequency response, and excellent stability. The voiceprint recognition system could make correct reactions to human voices by judging both the password and speaker. This study presented a voiceprint sensor with potential applications in noncontact biometric recognition and safety guarantee systems, promoting the progress of wearable sensor networks.

A Wearable Context-Aware ECG Monitoring System Integrated with Built-in Kinematic Sensors of the Smartphone.

PubMed

Miao, Fen; Cheng, Yayu; He, Yi; He, Qingyun; Li, Ye

2015-05-19

Continuously monitoring the ECG signals over hours combined with activity status is very important for preventing cardiovascular diseases. A traditional ECG holter is often inconvenient to carry because it has many electrodes attached to the chest and because it is heavy. This work proposes a wearable, low power context-aware ECG monitoring system integrated built-in kinetic sensors of the smartphone with a self-designed ECG sensor. The wearable ECG sensor is comprised of a fully integrated analog front-end (AFE), a commercial micro control unit (MCU), a secure digital (SD) card, and a Bluetooth module. The whole sensor is very small with a size of only 58 × 50 × 10 mm for wearable monitoring application due to the AFE design, and the total power dissipation in a full round of ECG acquisition is only 12.5 mW. With the help of built-in kinetic sensors of the smartphone, the proposed system can compute and recognize user's physical activity, and thus provide context-aware information for the continuous ECG monitoring. The experimental results demonstrated the performance of proposed system in improving diagnosis accuracy for arrhythmias and identifying the most common abnormal ECG patterns in different activities. In conclusion, we provide a wearable, accurate and energy-efficient system for long-term and context-aware ECG monitoring without any extra cost on kinetic sensor design but with the help of the widespread smartphone.

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.

Wearable sensor glove based on conducting fabric using electrodermal activity and pulse-wave sensors for e-health application.

PubMed

Lee, Youngbum; Lee, Byungwoo; Lee, Myoungho

2010-03-01

Improvement of the quality and efficiency of health in medicine, both at home and the hospital, calls for improved sensors that might be included in a common carrier such as a wearable sensor device to measure various biosignals and provide healthcare services that use e-health technology. Designed to be user-friendly, smart clothes and gloves respond well to the end users for health monitoring. This study describes a wearable sensor glove that is equipped with an electrodermal activity (EDA) sensor, pulse-wave sensor, conducting fabric, and an embedded system. The EDA sensor utilizes the relationship between drowsiness and the EDA signal. The EDA sensors were made using a conducting fabric instead of silver chloride electrodes, as a more practical and practically wearable device. The pulse-wave sensor measurement system, which is widely applied in oriental medicinal practices, is also a strong element in e-health monitoring systems. The EDA and pulse-wave signal acquisition module was constructed by connecting the sensor to the glove via a conductive fabric. The signal acquisition module is then connected to a personal computer that displays the results of the EDA and pulse-wave signal processing analysis and gives accurate feedback to the user. This system is designed for a number of applications for the e-health services, including drowsiness detection and oriental medicine.

Interactive wearable systems for upper body rehabilitation: a systematic review.

PubMed

Wang, Qi; Markopoulos, Panos; Yu, Bin; Chen, Wei; Timmermans, Annick

2017-03-11

The development of interactive rehabilitation technologies which rely on wearable-sensing for upper body rehabilitation is attracting increasing research interest. This paper reviews related research with the aim: 1) To inventory and classify interactive wearable systems for movement and posture monitoring during upper body rehabilitation, regarding the sensing technology, system measurements and feedback conditions; 2) To gauge the wearability of the wearable systems; 3) To inventory the availability of clinical evidence supporting the effectiveness of related technologies. A systematic literature search was conducted in the following search engines: PubMed, ACM, Scopus and IEEE (January 2010-April 2016). Forty-five papers were included and discussed in a new cuboid taxonomy which consists of 3 dimensions: sensing technology, feedback modalities and system measurements. Wearable sensor systems were developed for persons in: 1) Neuro-rehabilitation: stroke (n = 21), spinal cord injury (n = 1), cerebral palsy (n = 2), Alzheimer (n = 1); 2) Musculoskeletal impairment: ligament rehabilitation (n = 1), arthritis (n = 1), frozen shoulder (n = 1), bones trauma (n = 1); 3) Others: chronic pulmonary obstructive disease (n = 1), chronic pain rehabilitation (n = 1) and other general rehabilitation (n = 14). Accelerometers and inertial measurement units (IMU) are the most frequently used technologies (84% of the papers). They are mostly used in multiple sensor configurations to measure upper limb kinematics and/or trunk posture. Sensors are placed mostly on the trunk, upper arm, the forearm, the wrist, and the finger. Typically sensors are attachable rather than embedded in wearable devices and garments; although studies that embed and integrate sensors are increasing in the last 4 years. 16 studies applied knowledge of result (KR) feedback, 14 studies applied knowledge of performance (KP) feedback and 15 studies applied both in various modalities. 16 studies have conducted their evaluation with patients and reported usability tests, while only three of them conducted clinical trials including one randomized clinical trial. This review has shown that wearable systems are used mostly for the monitoring and provision of feedback on posture and upper extremity movements in stroke rehabilitation. The results indicated that accelerometers and IMUs are the most frequently used sensors, in most cases attached to the body through ad hoc contraptions for the purpose of improving range of motion and movement performance during upper body rehabilitation. Systems featuring sensors embedded in wearable appliances or garments are only beginning to emerge. Similarly, clinical evaluations are scarce and are further needed to provide evidence on effectiveness and pave the path towards implementation in clinical settings.

Wearable Networked Sensing for Human Mobility and Activity Analytics: A Systems Study.

PubMed

Dong, Bo; Biswas, Subir

2012-01-01

This paper presents implementation details, system characterization, and the performance of a wearable sensor network that was designed for human activity analysis. Specific machine learning mechanisms are implemented for recognizing a target set of activities with both out-of-body and on-body processing arrangements. Impacts of energy consumption by the on-body sensors are analyzed in terms of activity detection accuracy for out-of-body processing. Impacts of limited processing abilities in the on-body scenario are also characterized in terms of detection accuracy, by varying the background processing load in the sensor units. Through a rigorous systems study, it is shown that an efficient human activity analytics system can be designed and operated even under energy and processing constraints of tiny on-body wearable sensors.

A Novel Wearable Electronic Nose for Healthcare Based on Flexible Printed Chemical Sensor Array

PubMed Central

Lorwongtragool, Panida; Sowade, Enrico; Watthanawisuth, Natthapol; Baumann, Reinhard R.; Kerdcharoen, Teerakiat

2014-01-01

A novel wearable electronic nose for armpit odor analysis is proposed by using a low-cost chemical sensor array integrated in a ZigBee wireless communication system. We report the development of a carbon nanotubes (CNTs)/polymer sensor array based on inkjet printing technology. With this technique both composite-like layer and actual composite film of CNTs/polymer were prepared as sensing layers for the chemical sensor array. The sensor array can response to a variety of complex odors and is installed in a prototype of wearable e-nose for monitoring the axillary odor released from human body. The wearable e-nose allows the classification of different armpit odors and the amount of the volatiles released as a function of level of skin hygiene upon different activities. PMID:25340447

A Wearable Respiratory Biofeedback System Based on Generalized Body Sensor Network

PubMed Central

Liu, Guan-Zheng; Huang, Bang-Yu

2011-01-01

Abstract Wearable medical devices have enabled unobtrusive monitoring of vital signs and emerging biofeedback services in a pervasive manner. This article describes a wearable respiratory biofeedback system based on a generalized body sensor network (BSN) platform. The compact BSN platform was tailored for the strong requirements of overall system optimizations. A waist-worn biofeedback device was designed using the BSN. Extensive bench tests have shown that the generalized BSN worked as intended. In-situ experiments with 22 subjects indicated that the biofeedback device was discreet, easy to wear, and capable of offering wearable respiratory trainings. Pilot studies on wearable training patterns and resultant heart rate variability suggested that paced respirations at abdominal level and with identical inhaling/exhaling ratio were more appropriate for decreasing sympathetic arousal and increasing parasympathetic activities. PMID:21545293

Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications

PubMed Central

Muro-de-la-Herran, Alvaro; Garcia-Zapirain, Begonya; Mendez-Zorrilla, Amaia

2014-01-01

This article presents a review of the methods used in recognition and analysis of the human gait from three different approaches: image processing, floor sensors and sensors placed on the body. Progress in new technologies has led the development of a series of devices and techniques which allow for objective evaluation, making measurements more efficient and effective and providing specialists with reliable information. Firstly, an introduction of the key gait parameters and semi-subjective methods is presented. Secondly, technologies and studies on the different objective methods are reviewed. Finally, based on the latest research, the characteristics of each method are discussed. 40% of the reviewed articles published in late 2012 and 2013 were related to non-wearable systems, 37.5% presented inertial sensor-based systems, and the remaining 22.5% corresponded to other wearable systems. An increasing number of research works demonstrate that various parameters such as precision, conformability, usability or transportability have indicated that the portable systems based on body sensors are promising methods for gait analysis. PMID:24556672

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.

Gait Partitioning Methods: A Systematic Review

PubMed Central

Taborri, Juri; Palermo, Eduardo; Rossi, Stefano; Cappa, Paolo

2016-01-01

In the last years, gait phase partitioning has come to be a challenging research topic due to its impact on several applications related to gait technologies. A variety of sensors can be used to feed algorithms for gait phase partitioning, mainly classifiable as wearable or non-wearable. Among wearable sensors, footswitches or foot pressure insoles are generally considered as the gold standard; however, to overcome some inherent limitations of the former, inertial measurement units have become popular in recent decades. Valuable results have been achieved also though electromyography, electroneurography, and ultrasonic sensors. Non-wearable sensors, such as opto-electronic systems along with force platforms, remain the most accurate system to perform gait analysis in an indoor environment. In the present paper we identify, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution. Finally, we comparatively examine the obtainable gait phase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments. PMID:26751449

Gait Partitioning Methods: A Systematic Review.

PubMed

Taborri, Juri; Palermo, Eduardo; Rossi, Stefano; Cappa, Paolo

2016-01-06

In the last years, gait phase partitioning has come to be a challenging research topic due to its impact on several applications related to gait technologies. A variety of sensors can be used to feed algorithms for gait phase partitioning, mainly classifiable as wearable or non-wearable. Among wearable sensors, footswitches or foot pressure insoles are generally considered as the gold standard; however, to overcome some inherent limitations of the former, inertial measurement units have become popular in recent decades. Valuable results have been achieved also though electromyography, electroneurography, and ultrasonic sensors. Non-wearable sensors, such as opto-electronic systems along with force platforms, remain the most accurate system to perform gait analysis in an indoor environment. In the present paper we identify, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution. Finally, we comparatively examine the obtainable gait phase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments.

Wearable and flexible electronics for continuous molecular monitoring.

PubMed

Yang, Yiran; Gao, Wei

2018-04-03

Wearable biosensors have received tremendous attention over the past decade owing to their great potential in predictive analytics and treatment toward personalized medicine. Flexible electronics could serve as an ideal platform for personalized wearable devices because of their unique properties such as light weight, low cost, high flexibility and great conformability. Unlike most reported flexible sensors that mainly track physical activities and vital signs, the new generation of wearable and flexible chemical sensors enables real-time, continuous and fast detection of accessible biomarkers from the human body, and allows for the collection of large-scale information about the individual's dynamic health status at the molecular level. In this article, we review and highlight recent advances in wearable and flexible sensors toward continuous and non-invasive molecular analysis in sweat, tears, saliva, interstitial fluid, blood, wound exudate as well as exhaled breath. The flexible platforms, sensing mechanisms, and device and system configurations employed for continuous monitoring are summarized. We also discuss the key challenges and opportunities of the wearable and flexible chemical sensors that lie ahead.

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.

Gait Analysis Using Wearable Sensors

PubMed Central

Tao, Weijun; Liu, Tao; Zheng, Rencheng; Feng, Hutian

2012-01-01

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications. PMID:22438763

Seamless Tracing of Human Behavior Using Complementary Wearable and House-Embedded Sensors

PubMed Central

Augustyniak, Piotr; Smoleń, Magdalena; Mikrut, Zbigniew; Kańtoch, Eliasz

2014-01-01

This paper presents a multimodal system for seamless surveillance of elderly people in their living environment. The system uses simultaneously a wearable sensor network for each individual and premise-embedded sensors specific for each environment. The paper demonstrates the benefits of using complementary information from two types of mobility sensors: visual flow-based image analysis and an accelerometer-based wearable network. The paper provides results for indoor recognition of several elementary poses and outdoor recognition of complex movements. Instead of complete system description, particular attention was drawn to a polar histogram-based method of visual pose recognition, complementary use and synchronization of the data from wearable and premise-embedded networks and an automatic danger detection algorithm driven by two premise- and subject-related databases. The novelty of our approach also consists in feeding the databases with real-life recordings from the subject, and in using the dynamic time-warping algorithm for measurements of distance between actions represented as elementary poses in behavioral records. The main results of testing our method include: 95.5% accuracy of elementary pose recognition by the video system, 96.7% accuracy of elementary pose recognition by the accelerometer-based system, 98.9% accuracy of elementary pose recognition by the combined accelerometer and video-based system, and 80% accuracy of complex outdoor activity recognition by the accelerometer-based wearable system. PMID:24787640

Detecting Vital Signs with Wearable Wireless Sensors

PubMed Central

Yilmaz, Tuba; Foster, Robert; Hao, Yang

2010-01-01

The emergence of wireless technologies and advancements in on-body sensor design can enable change in the conventional health-care system, replacing it with wearable health-care systems, centred on the individual. Wearable monitoring systems can provide continuous physiological data, as well as better information regarding the general health of individuals. Thus, such vital-sign monitoring systems will reduce health-care costs by disease prevention and enhance the quality of life with disease management. In this paper, recent progress in non-invasive monitoring technologies for chronic disease management is reviewed. In particular, devices and techniques for monitoring blood pressure, blood glucose levels, cardiac activity and respiratory activity are discussed; in addition, on-body propagation issues for multiple sensors are presented. PMID:22163501

Developing a Digital Medicine System in Psychiatry: Ingestion Detection Rate and Latency Period.

PubMed

Profit, Deborah; Rohatagi, Shashank; Zhao, Cathy; Hatch, Ainslie; Docherty, John P; Peters-Strickland, Timothy S

2016-09-01

A digital medicine system (DMS) has been developed to measure and report adherence to an atypical antipsychotic, aripiprazole, in psychiatric patients. The DMS consists of 3 components: ingestible sensor embedded in a medication tablet, wearable sensor, and secure mobile and cloud-based applications. An umbrella study protocol was designed to rapidly assess the technical performance and safety of the DMS in multiple substudies to guide the technology development. Two sequential substudies enrolled 30 and 29 healthy volunteers between March-April 2014 and February-March 2015, respectively, to assess detection accuracy of the ingestible sensor by the DMS and the latency period between ingestion and detection of the ingestion by the wearable sensor or the cloud-based server. The first substudy identified areas for improvement using early versions of the wearable sensor and the mobile application. The second substudy tested updated versions of the components and showed an overall ingestion detection rate of 96.6%. Mean latency times for the signal transmission were 1.1-1.3 minutes (from ingestion to the wearable sensor detection) and 6.2-10.3 minutes (from the wearable sensor detection to the server detection). Half of transmissions were completed in < 2 minutes, and ~90% of ingestions were registered by the smartphone within 30 minutes of ingestion. No serious adverse events, discontinuations, or clinically significant laboratory/vital signs findings were reported. The DMS implementing modified versions of the smartphone application and the wearable sensor has the technical capability to detect and report tablet ingestion with high accuracy and acceptable latency time. ClinicalTrials.gov identifier: NCT02091882. © Copyright 2016 Physicians Postgraduate Press, Inc.

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.

BIOTEX--biosensing textiles for personalised healthcare management.

PubMed

Coyle, Shirley; Lau, King-Tong; Moyna, Niall; O'Gorman, Donal; Diamond, Dermot; Di Francesco, Fabio; Costanzo, Daniele; Salvo, Pietro; Trivella, Maria Giovanna; De Rossi, Danilo Emilio; Taccini, Nicola; Paradiso, Rita; Porchet, Jacque-André; Ridolfi, Andrea; Luprano, Jean; Chuzel, Cyril; Lanier, Thierry; Revol-Cavalier, Frdéric; Schoumacker, Sébastien; Mourier, Véronique; Chartier, Isabelle; Convert, Reynald; De-Moncuit, Henri; Bini, Christina

2010-03-01

Textile-based sensors offer an unobtrusive method of continually monitoring physiological parameters during daily activities. Chemical analysis of body fluids, noninvasively, is a novel and exciting area of personalized wearable healthcare systems. BIOTEX was an EU-funded project that aimed to develop textile sensors to measure physiological parameters and the chemical composition of body fluids, with a particular interest in sweat. A wearable sensing system has been developed that integrates a textile-based fluid handling system for sample collection and transport with a number of sensors including sodium, conductivity, and pH sensors. Sensors for sweat rate, ECG, respiration, and blood oxygenation were also developed. For the first time, it has been possible to monitor a number of physiological parameters together with sweat composition in real time. This has been carried out via a network of wearable sensors distributed around the body of a subject user. This has huge implications for the field of sports and human performance and opens a whole new field of research in the clinical setting.

A compact perspiration meter system with capacitive humidity sensor for wearable health-care applications

NASA Astrophysics Data System (ADS)

Mitani, Yusuke; Miyaji, Kousuke; Kaneko, Satoshi; Uekura, Takaharu; Momose, Hideya; Johguchi, Koh

2018-04-01

This paper presents a compact wearable perspiration meter system using a 180-nm CMOS technology. With custom chip and board design, the proposed perspiration meter, which can measure a qualitative sweating rate, is integrated into 15 × 20 mm2. From the experimental results, the capacitances of the humidity sensors with analog-to-digital converter and band-gap reference circuits can operate accurately without hysteresis. In addition, a demonstration with simulated human skin is carried out to investigate the sensor’s performance under real environments. The proposed perspiration meter can output values equivalent to a conventional meter. As a result, it is verified that the proposed system can be used as a human sweat sensor for wearable application.

A Wearable Capacitive Sensor for Monitoring Human Respiratory Rate

NASA Astrophysics Data System (ADS)

Kundu, Subrata Kumar; Kumagai, Shinya; Sasaki, Minoru

2013-04-01

Realizing an untethered, low-cost, and comfortably wearable respiratory rate sensor for long-term breathing monitoring application still remains a challenge. In this paper, a conductive-textile-based wearable respiratory rate sensing technique based on the capacitive sensing approach is proposed. The sensing unit consists of two conductive textile electrodes that can be easily fabricated, laminated, and integrated in garments. Respiration cycle is detected by measuring the capacitance of two electrodes placed on the inner anterior and posterior sides of a T-shirt at either the abdomen or chest position. A convenient wearable respiratory sensor setup with a capacitance-to-voltage converter has been devised. Respiratory rate as well as breathing mode can be accurately identified using the designed sensor. The sensor output provides significant information on respiratory flow. The effectiveness of the proposed system for different breathing patterns has been evaluated by experiments.

Real Time Physiological Status Monitoring (RT-PSM): Accomplishments, Requirements, and Research Roadmap

DTIC Science & Technology

2016-03-01

Maneuver Center of Excellence (US Army - Ft. Benning) MINIMEN Minimalist Wearable Mesh Network Mloco Metabolic Costs of Locomotion MOUT Military...detect blast and ballistic wounding events Quantum Applied Science & Research, Inc. Army A05-163 SBIR 2005 Minimalist Short- Range Wearable for...STTR 2005 (Phase 1) 2005 Minimalist Wearable Mesh Network (MINIMEN) System Develop PSM system linking wearable sensors, mesh networking

Development and evaluation of an ambulatory stress monitor based on wearable sensors.

PubMed

Choi, Jongyoon; Ahmed, Beena; Gutierrez-Osuna, Ricardo

2012-03-01

Chronic stress is endemic to modern society. However, as it is unfeasible for physicians to continuously monitor stress levels, its diagnosis is nontrivial. Wireless body sensor networks offer opportunities to ubiquitously detect and monitor mental stress levels, enabling improved diagnosis, and early treatment. This article describes the development of a wearable sensor platform to monitor a number of physiological correlates of mental stress. We discuss tradeoffs in both system design and sensor selection to balance information content and wearability. Using experimental signals collected from the wearable sensor, we describe a selected number of physiological features that show good correlation with mental stress. In particular, we propose a new spectral feature that estimates the balance of the autonomic nervous system by combining information from the power spectral density of respiration and heart rate variability. We validate the effectiveness of our approach on a binary discrimination problem when subjects are placed under two psychophysiological conditions: mental stress and relaxation. When used in a logistic regression model, our feature set is able to discriminate between these two mental states with a success rate of 81% across subjects. © 2012 IEEE

System perspectives for mobile platform design in m-Health

NASA Astrophysics Data System (ADS)

Roveda, Janet M.; Fink, Wolfgang

2016-05-01

Advances in integrated circuit technologies have led to the integration of medical sensor front ends with data processing circuits, i.e., mobile platform design for wearable sensors. We discuss design methodologies for wearable sensor nodes and their applications in m-Health. From the user perspective, flexibility, comfort, appearance, fashion, ease-of-use, and visibility are key form factors. From the technology development point of view, high accuracy, low power consumption, and high signal to noise ratio are desirable features. From the embedded software design standpoint, real time data analysis algorithms, application and database interfaces are the critical components to create successful wearable sensor-based products.

Monitoring activities of daily living based on wearable wireless body sensor network.

PubMed

Kańtoch, E; Augustyniak, P; Markiewicz, M; Prusak, D

2014-01-01

With recent advances in microprocessor chip technology, wireless communication, and biomedical engineering it is possible to develop miniaturized ubiquitous health monitoring devices that are capable of recording physiological and movement signals during daily life activities. The aim of the research is to implement and test the prototype of health monitoring system. The system consists of the body central unit with Bluetooth module and wearable sensors: the custom-designed ECG sensor, the temperature sensor, the skin humidity sensor and accelerometers placed on the human body or integrated with clothes and a network gateway to forward data to a remote medical server. The system includes custom-designed transmission protocol and remote web-based graphical user interface for remote real time data analysis. Experimental results for a group of humans who performed various activities (eg. working, running, etc.) showed maximum 5% absolute error compared to certified medical devices. The results are promising and indicate that developed wireless wearable monitoring system faces challenges of multi-sensor human health monitoring during performing daily activities and opens new opportunities in developing novel healthcare services.

A Systematic Review of Wearable Systems for Cancer Detection: Current State and Challenges.

PubMed

Ray, Partha Pratim; Dash, Dinesh; De, Debashis

2017-10-02

Rapid growth of sensor and computing platforms have introduced the wearable systems. In recent years, wearable systems have led to new applications across all medical fields. The aim of this review is to present current state-of-the-art approach in the field of wearable system based cancer detection and identify key challenges that resist it from clinical adoption. A total of 472 records were screened and 11 were finally included in this study. Two types of records were studied in this context that includes 45% research articles and 55% manufactured products. The review was performed per PRISMA guidelines where considerations was given to records that were published or reported between 2009 and 2017. The identified records included 4 cancer detecting wearable systems such as breast cancer (36.3%), skin cancer (36.3%), prostate cancer (18.1%), and multi-type cancer (9%). Most works involved sensor based smart systems comprising of microcontroller, Bluetooth module, and smart phone. Few demonstrated Ultra-Wide Band (i.e. UWB) antenna based wearable systems. Skin cancer detecting wearable systems were most comprehensible ones. The current works are gradually progressing with seamless integration of sensory units along with smart networking. However, they lack in cloud computing and long-range communication paradigms. Artificial intelligence and machine learning are key ports that need to be attached with current wearable systems. Further, clinical inertia, lack of awareness, and high cost are altogether pulling back the actual growth of such system. It is well comprehended that upon sincere orientation of all identified challenges, wearable systems would emerge as vital alternative to futuristic cancer detection.

Rodent wearable ultrasound system for wireless neural recording.

PubMed

Piech, David K; Kay, Joshua E; Boser, Bernhard E; Maharbiz, Michel M

2017-07-01

Advances in minimally-invasive, distributed biological interface nodes enable possibilities for networks of sensors and actuators to connect the brain with external devices. The recent development of the neural dust sensor mote has shown that utilizing ultrasound backscatter communication enables untethered sub-mm neural recording devices. These implanted sensor motes require a wearable external ultrasound interrogation device to enable in-vivo, freely-behaving neural interface experiments. However, minimizing the complexity and size of the implanted sensors shifts the power and processing burden to the external interrogator. In this paper, we present an ultrasound backscatter interrogator that supports real-time backscatter processing in a rodent-wearable, completely wireless device. We demonstrate a generic digital encoding scheme which is intended for transmitting neural information. The system integrates a front-end ultrasonic interface ASIC with off-the-shelf components to enable a highly compact ultrasound interrogation device intended for rodent neural interface experiments but applicable to other model systems.

Fabric-based integrated energy devices for wearable activity monitors.

PubMed

Jung, Sungmook; Lee, Jongsu; Hyeon, Taeghwan; Lee, Minbaek; Kim, Dae-Hyeong

2014-09-01

A wearable fabric-based integrated power-supply system that generates energy triboelectrically using human activity and stores the generated energy in an integrated supercapacitor is developed. This system can be utilized as either a self-powered activity monitor or as a power supply for external wearable sensors. These demonstrations give new insights for the research of wearable electronics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

'Do-It-Yourself' Healthcare? Quality of Health and Healthcare Through Wearable Sensors.

PubMed

Vesnic-Alujevic, Lucia; Breitegger, Melina; Guimarães Pereira, Ângela

2018-06-01

Wearable sensors are an integral part of the new telemedicine concept supporting the idea that Information Technologies will improve the quality and efficiency of healthcare. The use of sensors in diagnosis, treatment and monitoring of patients not only potentially changes medical practice but also one's relationship with one's body and mind, as well as the role and responsibilities of patients and healthcare professionals. In this paper, we focus on knowledge assessment of the online communities of Fitbit (a commercial wearable device) and the Quantified Self movement. Through their online forums, we investigate how users' knowledge claims, shared experiences and imaginations about wearable sensors interrogate or confirm the narratives through which they are introduced to the publics. Citizen initiatives like the Quantified Self movement claim the right to 'own' the sensor generated data. But how these data can be used through traditional healthcare systems is an open question. More importantly, wearable sensors trigger a social function that is transformative of the current idea of care and healthcare, focused on sharing, socialising and collectively reflecting about individual problems. Whether this is aligned with current policy making about healthcare, whose central narrative is focused on efficiency and productivity, is to be seen.

Wireless wearable range-of-motion sensor system for upper and lower extremity joints: a validation study.

PubMed

Kumar, Yogaprakash; Yen, Shih-Cheng; Tay, Arthur; Lee, Wangwei; Gao, Fan; Zhao, Ziyi; Li, Jingze; Hon, Benjamin; Tian-Ma Xu, Tim; Cheong, Angela; Koh, Karen; Ng, Yee-Sien; Chew, Effie; Koh, Gerald

2015-02-01

Range-of-motion (ROM) assessment is a critical assessment tool during the rehabilitation process. The conventional approach uses the goniometer which remains the most reliable instrument but it is usually time-consuming and subject to both intra- and inter-therapist measurement errors. An automated wireless wearable sensor system for the measurement of ROM has previously been developed by the current authors. Presented is the correlation and accuracy of the automated wireless wearable sensor system against a goniometer in measuring ROM in the major joints of upper (UEs) and lower extremities (LEs) in 19 healthy subjects and 20 newly disabled inpatients through intra (same) subject comparison of ROM assessments between the sensor system against goniometer measurements by physical therapists. In healthy subjects, ROM measurements using the new sensor system were highly correlated with goniometry, with 95% of differences < 20° and 10° for most movements in major joints of UE and LE, respectively. Among inpatients undergoing rehabilitation, ROM measurements using the new sensor system were also highly correlated with goniometry, with 95% of the differences being < 20° and 25° for most movements in the major joints of UE and LE, respectively.

3D printing of wearable fractal-based sensor systems for neurocardiology and healthcare

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay K.

2017-04-01

Neurocardiology is the pathophysiological interplay of nervous and cardiovascular systems. The communication between the heart and brain has revealed various methodologies in healthcare that could be investigated to study the heart-brain interactions and other cardiovascular and neurological diseases. A textile based wearable nanosensor system in the form of e-bra, e-shirt, e-headband, e-brief, underwear etc, was presented in this SPIE conferences earlier for noninvasive recording of EEG and EKG, and showing the correlation between the brain and heart signals. In this paper, the technology is expanded further using fractal based geometries using 3D printing system for low cost and flexible wearable sensor system for healthcare.

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).

MEDIC: medical embedded device for individualized care.

PubMed

Wu, Winston H; Bui, Alex A T; Batalin, Maxim A; Au, Lawrence K; Binney, Jonathan D; Kaiser, William J

2008-02-01

Presented work highlights the development and initial validation of a medical embedded device for individualized care (MEDIC), which is based on a novel software architecture, enabling sensor management and disease prediction capabilities, and commercially available microelectronic components, sensors and conventional personal digital assistant (PDA) (or a cell phone). In this paper, we present a general architecture for a wearable sensor system that can be customized to an individual patient's needs. This architecture is based on embedded artificial intelligence that permits autonomous operation, sensor management and inference, and may be applied to a general purpose wearable medical diagnostics. A prototype of the system has been developed based on a standard PDA and wireless sensor nodes equipped with commercially available Bluetooth radio components, permitting real-time streaming of high-bandwidth data from various physiological and contextual sensors. We also present the results of abnormal gait diagnosis using the complete system from our evaluation, and illustrate how the wearable system and its operation can be remotely configured and managed by either enterprise systems or medical personnel at centralized locations. By using commercially available hardware components and software architecture presented in this paper, the MEDIC system can be rapidly configured, providing medical researchers with broadband sensor data from remote patients and platform access to best adapt operation for diagnostic operation objectives.

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.

Real Time Analysis of Bioanalytes in Healthcare, Food, Zoology and Botany

PubMed Central

Wang, Tianqi; Ramnarayanan, Ashwin

2017-01-01

The growing demand for real time analysis of bioanalytes has spurred development in the field of wearable technology to offer non-invasive data collection at a low cost. The manufacturing processes for creating these sensing systems vary significantly by the material used, the type of sensors needed and the subject of study as well. The methods predominantly involve stretchable electronic sensors to monitor targets and transmit data mainly through flexible wires or short-range wireless communication devices. Capable of conformal contact, the application of wearable technology goes beyond the healthcare to fields of food, zoology and botany. With a brief review of wearable technology and its applications to various fields, we believe this mini review would be of interest to the reader in broad fields of materials, sensor development and areas where wearable sensors can provide data that are not available elsewhere. PMID:29267256

Real Time Analysis of Bioanalytes in Healthcare, Food, Zoology and Botany.

PubMed

Wang, Tianqi; Ramnarayanan, Ashwin; Cheng, Huanyu

2017-12-21

The growing demand for real time analysis of bioanalytes has spurred development in the field of wearable technology to offer non-invasive data collection at a low cost. The manufacturing processes for creating these sensing systems vary significantly by the material used, the type of sensors needed and the subject of study as well. The methods predominantly involve stretchable electronic sensors to monitor targets and transmit data mainly through flexible wires or short-range wireless communication devices. Capable of conformal contact, the application of wearable technology goes beyond the healthcare to fields of food, zoology and botany. With a brief review of wearable technology and its applications to various fields, we believe this mini review would be of interest to the reader in broad fields of materials, sensor development and areas where wearable sensors can provide data that are not available elsewhere.

Estimation of Temporal Gait Parameters Using a Wearable Microphone-Sensor-Based System

PubMed Central

Wang, Cheng; Wang, Xiangdong; Long, Zhou; Yuan, Jing; Qian, Yueliang; Li, Jintao

2016-01-01

Most existing wearable gait analysis methods focus on the analysis of data obtained from inertial sensors. This paper proposes a novel, low-cost, wireless and wearable gait analysis system which uses microphone sensors to collect footstep sound signals during walking. This is the first time a microphone sensor is used as a wearable gait analysis device as far as we know. Based on this system, a gait analysis algorithm for estimating the temporal parameters of gait is presented. The algorithm fully uses the fusion of two feet footstep sound signals and includes three stages: footstep detection, heel-strike event and toe-on event detection, and calculation of gait temporal parameters. Experimental results show that with a total of 240 data sequences and 1732 steps collected using three different gait data collection strategies from 15 healthy subjects, the proposed system achieves an average 0.955 F1-measure for footstep detection, an average 94.52% accuracy rate for heel-strike detection and 94.25% accuracy rate for toe-on detection. Using these detection results, nine temporal related gait parameters are calculated and these parameters are consistent with their corresponding normal gait temporal parameters and labeled data calculation results. The results verify the effectiveness of our proposed system and algorithm for temporal gait parameter estimation. PMID:27999321

Smart Vest: wearable multi-parameter remote physiological monitoring system.

PubMed

Pandian, P S; Mohanavelu, K; Safeer, K P; Kotresh, T M; Shakunthala, D T; Gopal, Parvati; Padaki, V C

2008-05-01

The wearable physiological monitoring system is a washable shirt, which uses an array of sensors connected to a central processing unit with firmware for continuously monitoring physiological signals. The data collected can be correlated to produce an overall picture of the wearer's health. In this paper, we discuss the wearable physiological monitoring system called 'Smart Vest'. The Smart Vest consists of a comfortable to wear vest with sensors integrated for monitoring physiological parameters, wearable data acquisition and processing hardware and remote monitoring station. The wearable data acquisition system is designed using microcontroller and interfaced with wireless communication and global positioning system (GPS) modules. The physiological signals monitored are electrocardiogram (ECG), photoplethysmogram (PPG), body temperature, blood pressure, galvanic skin response (GSR) and heart rate. The acquired physiological signals are sampled at 250samples/s, digitized at 12-bit resolution and transmitted wireless to a remote physiological monitoring station along with the geo-location of the wearer. The paper describes a prototype Smart Vest system used for remote monitoring of physiological parameters and the clinical validation of the data are also presented.

Anatomical calibration for wearable motion capture systems: Video calibrated anatomical system technique.

PubMed

Bisi, Maria Cristina; Stagni, Rita; Caroselli, Alessio; Cappello, Angelo

2015-08-01

Inertial sensors are becoming widely used for the assessment of human movement in both clinical and research applications, thanks to their usability out of the laboratory. This work aims to propose a method for calibrating anatomical landmark position in the wearable sensor reference frame with an ease to use, portable and low cost device. An off-the-shelf camera, a stick and a pattern, attached to the inertial sensor, compose the device. The proposed technique is referred to as video Calibrated Anatomical System Technique (vCAST). The absolute orientation of a synthetic femur was tracked both using the vCAST together with an inertial sensor and using stereo-photogrammetry as reference. Anatomical landmark calibration showed mean absolute error of 0.6±0.5 mm: these errors are smaller than those affecting the in-vivo identification of anatomical landmarks. The roll, pitch and yaw anatomical frame orientations showed root mean square errors close to the accuracy limit of the wearable sensor used (1°), highlighting the reliability of the proposed technique. In conclusion, the present paper proposes and preliminarily verifies the performance of a method (vCAST) for calibrating anatomical landmark position in the wearable sensor reference frame: the technique is low time consuming, highly portable, easy to implement and usable outside laboratory. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Flexible piezoelectric nanogenerator in wearable self-powered active sensor for respiration and healthcare monitoring

NASA Astrophysics Data System (ADS)

Liu, Z.; Zhang, S.; Jin, Y. M.; Ouyang, H.; Zou, Y.; Wang, X. X.; Xie, L. X.; Li, Z.

2017-06-01

A wearable self-powered active sensor for respiration and healthcare monitoring was fabricated based on a flexible piezoelectric nanogenerator. An electrospinning poly(vinylidene fluoride) thin film on silicone substrate was polarized to fabricate the flexible nanogenerator and its electrical property was measured. When periodically stretched by a linear motor, the flexible piezoelectric nanogenerator generated an output open-circuit voltage and short-circuit current of up to 1.5 V and 400 nA, respectively. Through integration with an elastic bandage, a wearable self-powered sensor was fabricated and used to monitor human respiration, subtle muscle movement, and voice recognition. As respiration proceeded, the electrical output signals of the sensor corresponded to the signals measured by a physiological signal recording system with good reliability and feasibility. This self-powered, wearable active sensor has significant potential for applications in pulmonary function evaluation, respiratory monitoring, and detection of gesture and vocal cord vibration for the personal healthcare monitoring of disabled or paralyzed patients.

Smart wearable systems: current status and future challenges.

PubMed

Chan, Marie; Estève, Daniel; Fourniols, Jean-Yves; Escriba, Christophe; Campo, Eric

2012-11-01

Extensive efforts have been made in both academia and industry in the research and development of smart wearable systems (SWS) for health monitoring (HM). Primarily influenced by skyrocketing healthcare costs and supported by recent technological advances in micro- and nanotechnologies, miniaturisation of sensors, and smart fabrics, the continuous advances in SWS will progressively change the landscape of healthcare by allowing individual management and continuous monitoring of a patient's health status. Consisting of various components and devices, ranging from sensors and actuators to multimedia devices, these systems support complex healthcare applications and enable low-cost wearable, non-invasive alternatives for continuous 24-h monitoring of health, activity, mobility, and mental status, both indoors and outdoors. Our objective has been to examine the current research in wearable to serve as references for researchers and provide perspectives for future research. Herein, we review the current research and development of and the challenges facing SWS for HM, focusing on multi-parameter physiological sensor systems and activity and mobility measurement system designs that reliably measure mobility or vital signs and integrate real-time decision support processing for disease prevention, symptom detection, and diagnosis. For this literature review, we have chosen specific selection criteria to include papers in which wearable systems or devices are covered. We describe the state of the art in SWS and provide a survey of recent implementations of wearable health-care systems. We describe current issues, challenges, and prospects of SWS. We conclude by identifying the future challenges facing SWS for HM. Copyright © 2012 Elsevier B.V. All rights reserved.

Inkjet-/3D-/4D-printed autonomous wearable RF modules for biomonitoring, positioning and sensing applications

NASA Astrophysics Data System (ADS)

Bito, Jo; Bahr, Ryan; Hester, Jimmy; Kimionis, John; Nauroze, Abdullah; Su, Wenjing; Tehrani, Bijan; Tentzeris, Manos M.

2017-05-01

In this paper, numerous inkjet-/3D-/4D-printed wearable flexible antennas, RF electronics, modules and sensors fabricated on paper and other polymer (e.g. LCP) substrates are introduced as a system-level solution for ultra-low-cost mass production of autonomous Biomonitoring, Positioning and Sensing applications. This paper briefly discusses the state-of-the-art area of fully-integrated wearable wireless sensor modules on paper or flexible LCP and show the first ever 4D sensor module integration on paper, as well as numerous 3D and 4D multilayer paper-based and LCP-based RF/microwave, flexible and wearable structures, that could potentially set the foundation for the truly convergent wireless sensor ad-hoc "on-body networks of the future with enhanced cognitive intelligence and "rugged" packaging. Also, some challenges concerning the power sources of "nearperpetual" wearable RF modules, including flexible miniaturized batteries as well as power-scavenging approaches involving electromagnetic and solar energy forms are discuessed. The final step of the paper will involve examples from mmW wearable (e.g. biomonitoring) antennas and RF modules, as well as the first examples of the integration of inkjet-printed nanotechnology-based (e.g.CNT) sensors on paper and organic substrates for Internet of Things (IoT) applications. It has to be noted that the paper will review and present challenges for inkjetprinted organic active and nonlinear devices as well as future directions in the area of environmentally-friendly "green") wearable RF electronics and "smart-skin conformal sensors.

A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications

PubMed Central

Antolín, Diego; Medrano, Nicolás; Calvo, Belén; Pérez, Francisco

2017-01-01

This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO2 concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers. PMID:28216556

A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications.

PubMed

Antolín, Diego; Medrano, Nicolás; Calvo, Belén; Pérez, Francisco

2017-02-14

This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO₂ concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers.

Tattoolike Polyaniline Microparticle-Doped Gold Nanowire Patches as Highly Durable Wearable Sensors.

PubMed

Gong, Shu; Lai, Daniel T H; Wang, Yan; Yap, Lim Wei; Si, Kae Jye; Shi, Qianqian; Jason, Naveen Noah; Sridhar, Tam; Uddin, Hemayet; Cheng, Wenlong

2015-09-09

Wearable and highly sensitive strain sensors are essential components of electronic skin for future biomonitoring and human machine interfaces. Here we report a low-cost yet efficient strategy to dope polyaniline microparticles into gold nanowire (AuNW) films, leading to 10 times enhancement in conductivity and ∼8 times improvement in sensitivity. Simultaneously, tattoolike wearable sensors could be fabricated simply by a direct "draw-on" strategy with a Chinese penbrush. The stretchability of the sensors could be enhanced from 99.7% to 149.6% by designing curved tattoo with different radius of curvatures. We also demonstrated roller coating method to encapusulate AuNWs sensors, exhibiting excellent water resistibility and durability. Because of improved conductivity of our sensors, they can directly interface with existing wireless circuitry, allowing for fabrication of wireless flexion sensors for a human finger-controlled robotic arm system.

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.

Quaternion-Based Unscented Kalman Filter for Accurate Indoor Heading Estimation Using Wearable Multi-Sensor System

PubMed Central

Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng

2015-01-01

Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384

Location verification algorithm of wearable sensors for wireless body area networks.

PubMed

Wang, Hua; Wen, Yingyou; Zhao, Dazhe

2018-01-01

Knowledge of the location of sensor devices is crucial for many medical applications of wireless body area networks, as wearable sensors are designed to monitor vital signs of a patient while the wearer still has the freedom of movement. However, clinicians or patients can misplace the wearable sensors, thereby causing a mismatch between their physical locations and their correct target positions. An error of more than a few centimeters raises the risk of mistreating patients. The present study aims to develop a scheme to calculate and detect the position of wearable sensors without beacon nodes. A new scheme was proposed to verify the location of wearable sensors mounted on the patient's body by inferring differences in atmospheric air pressure and received signal strength indication measurements from wearable sensors. Extensive two-sample t tests were performed to validate the proposed scheme. The proposed scheme could easily recognize a 30-cm horizontal body range and a 65-cm vertical body range to correctly perform sensor localization and limb identification. All experiments indicate that the scheme is suitable for identifying wearable sensor positions in an indoor environment.

Wearable Fall Detector using Integrated Sensors and Energy Devices

NASA Astrophysics Data System (ADS)

Jung, Sungmook; Hong, Seungki; Kim, Jaemin; Lee, Sangkyu; Hyeon, Taeghwan; Lee, Minbaek; Kim, Dae-Hyeong

2015-11-01

Wearable devices have attracted great attentions as next-generation electronic devices. For the comfortable, portable, and easy-to-use system platform in wearable electronics, a key requirement is to replace conventional bulky and rigid energy devices into thin and deformable ones accompanying the capability of long-term energy supply. Here, we demonstrate a wearable fall detection system composed of a wristband-type deformable triboelectric generator and lithium ion battery in conjunction with integrated sensors, controllers, and wireless units. A stretchable conductive nylon is used as electrodes of the triboelectric generator and the interconnection between battery cells. Ethoxylated polyethylenimine, coated on the surface of the conductive nylon electrode, tunes the work function of a triboelectric generator and maximizes its performance. The electrical energy harvested from the triboelectric generator through human body motions continuously recharges the stretchable battery and prolongs hours of its use. The integrated energy supply system runs the 3-axis accelerometer and related electronics that record human body motions and send the data wirelessly. Upon the unexpected fall occurring, a custom-made software discriminates the fall signal and an emergency alert is immediately sent to an external mobile device. This wearable fall detection system would provide new opportunities in the mobile electronics and wearable healthcare.

Wearable Fall Detector using Integrated Sensors and Energy Devices.

PubMed

Jung, Sungmook; Hong, Seungki; Kim, Jaemin; Lee, Sangkyu; Hyeon, Taeghwan; Lee, Minbaek; Kim, Dae-Hyeong

2015-11-24

Wearable devices have attracted great attentions as next-generation electronic devices. For the comfortable, portable, and easy-to-use system platform in wearable electronics, a key requirement is to replace conventional bulky and rigid energy devices into thin and deformable ones accompanying the capability of long-term energy supply. Here, we demonstrate a wearable fall detection system composed of a wristband-type deformable triboelectric generator and lithium ion battery in conjunction with integrated sensors, controllers, and wireless units. A stretchable conductive nylon is used as electrodes of the triboelectric generator and the interconnection between battery cells. Ethoxylated polyethylenimine, coated on the surface of the conductive nylon electrode, tunes the work function of a triboelectric generator and maximizes its performance. The electrical energy harvested from the triboelectric generator through human body motions continuously recharges the stretchable battery and prolongs hours of its use. The integrated energy supply system runs the 3-axis accelerometer and related electronics that record human body motions and send the data wirelessly. Upon the unexpected fall occurring, a custom-made software discriminates the fall signal and an emergency alert is immediately sent to an external mobile device. This wearable fall detection system would provide new opportunities in the mobile electronics and wearable healthcare.

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

Carbon nanotubes (CNTs) based strain sensors for a wearable monitoring and biofeedback system for pressure ulcer prevention and rehabilitation.

PubMed

Boissy, Patrick; Genest, Jonathan; Patenaude, Johanne; Poirier, Marie-Sol; Chenel, Vanessa; Béland, Jean-Pierre; Legault, Georges-Auguste; Bernier, Louise; Tapin, Danielle; Beauvais, Jacques

2011-01-01

This paper presents an overview of the functioning principles of CNTs and their electrical and mechanical properties when used as strain sensors and describes a system embodiment for a wearable monitoring and biofeedback platform for use in pressure ulcer prevention and rehabilitation. Two type of CNTs films (multi-layered CNTs film vs purified film) were characterized electrically and mechanically for potential use as source material. The loosely woven CNTs film (multi-layered) showed substantial less sensitivity than the purified CNTs film but had an almost linear response to stress and better mechanical properties. CNTs have the potential to achieve a much higher sensitivity to strain than other piezoresistors based on regular of conductive particles such as commercially available resistive inks and could become an innovative source material for wearable strain sensors. We are currently continuing the characterization of CNTs based strain sensors and exploring their use in a design for 3-axis strain sensors.

Wearable knee health rehabilitation assessment using acoustical emissions

NASA Astrophysics Data System (ADS)

Teague, Caitlin N.; Hersek, Sinan; Conant, Jordan L.; Gilliland, Scott M.; Inan, Omer T.

2017-02-01

We have developed a novel, wearable sensing system based on miniature piezoelectric contact microphones for measuring the acoustical emissions from the knee during movement. The system consists of two contact microphones, positioned on the medial and lateral sides of the patella, connected to custom, analog pre-amplifier circuits and a microcontroller for digitization and data storage on a secure digital card. Tn addition to the acoustical sensing, the system includes two integrated inertial measurement sensors including accelerometer and gyroscope modalities to enable joint angle calculations; these sensors, with digital outputs, are connected directly to the same microcontroller. The system provides low noise, accurate joint acoustical emission and angle measurements in a wearable form factor and has several hours of battery life.

Home monitoring of patients with Parkinson's disease via wearable technology and a web-based application.

PubMed

Patel, Shyamal; Chen, Bor-Rong; Buckley, Thomas; Rednic, Ramona; McClure, Doug; Tarsy, Daniel; Shih, Ludy; Dy, Jennifer; Welsh, Matt; Bonato, Paolo

2010-01-01

Objective long-term health monitoring can improve the clinical management of several medical conditions ranging from cardiopulmonary diseases to motor disorders. In this paper, we present our work toward the development of a home-monitoring system. The system is currently used to monitor patients with Parkinson's disease who experience severe motor fluctuations. Monitoring is achieved using wireless wearable sensors whose data are relayed to a remote clinical site via a web-based application. The work herein presented shows that wearable sensors combined with a web-based application provide reliable quantitative information that can be used for clinical decision making.

Development of a wearable wireless body area network for health monitoring of the elderly and disabled

NASA Astrophysics Data System (ADS)

Rushambwa, Munyaradzi C.; Gezimati, Mavis; Jeeva, J. B.

2017-11-01

Novel advancements in systems miniaturization, electronics in health care and communication technologies are enabling the integration of both patients and doctors involvement in health care system. A Wearable Wireless Body Area Network (WWBAN) provides continuous, unobtrusive ambulatory, ubiquitous health monitoring, and provide real time patient’s status to the physician without any constraint on their normal daily life activities. In this project we developed a wearable wireless body area network system that continuously monitor the health of the elderly and the disabled and provide them with independent, safe and secure living. The WWBAN system monitors the following parameters; blood oxygen saturation using a pulse oximeter sensor (SpO2), heart rate (HR) pulse sensor, Temperature, hydration, glucose level and fall detection. When the wearable system is put on, the sensor values are processed and analysed. If any of the monitored parameter values falls below or exceeds the normal range, there is trigger of remote alert by which an SMS is send to a doctor or physician via GSM module and network. The developed system offers flexibility and mobility to the user; it is a real time system and has significance in revolutionizing health care system by enabling non-invasive, inexpensive, continuous health monitoring.

A remote assessment system with a vision robot and wearable sensors.

PubMed

Zhang, Tong; Wang, Jue; Ren, Yumiao; Li, Jianjun

2004-01-01

This paper describes an ongoing researched remote rehabilitation assessment system that has a 6-freedom double-eyes vision robot to catch vision information, and a group of wearable sensors to acquire biomechanical signals. A server computer is fixed on the robot, to provide services to the robot's controller and all the sensors. The robot is connected to Internet by wireless channel, and so do the sensors to the robot. Rehabilitation professionals can semi-automatically practise an assessment program via Internet. The preliminary results show that the smart device, including the robot and the sensors, can improve the quality of remote assessment, and reduce the complexity of operation at a distance.

Radio-frequency energy harvesting for wearable sensors.

PubMed

Borges, Luís M; Chávez-Santiago, Raul; Barroca, Norberto; Velez, Fernando José; Balasingham, Ilangko

2015-02-01

The use of wearable biomedical sensors for the continuous monitoring of physiological signals will facilitate the involvement of the patients in the prevention and management of chronic diseases. The fabrication of small biomedical sensors transmitting physiological data wirelessly is possible as a result of the tremendous advances in ultra-low power electronics and radio communications. However, the widespread adoption of these devices depends very much on their ability to operate for long periods of time without the need to frequently change, recharge or even use batteries. In this context, energy harvesting (EH) is the disruptive technology that can pave the road towards the massive utilisation of wireless wearable sensors for patient self-monitoring and daily healthcare. Radio-frequency (RF) transmissions from commercial telecommunication networks represent reliable ambient energy that can be harvested as they are ubiquitous in urban and suburban areas. The state-of-the-art in RF EH for wearable biomedical sensors specifically targeting the global system of mobile 900/1800 cellular and 700 MHz digital terrestrial television networks as ambient RF energy sources are showcased. Furthermore, guidelines for the choice of the number of stages for the RF energy harvester are presented, depending on the requirements from the embedded system to power supply, which is useful for other researchers that work in the same area. The present authors' recent advances towards the development of an efficient RF energy harvester and storing system are presented and thoroughly discussed too.

Wearable health monitoring using capacitive voltage-mode Human Body Communication.

PubMed

Maity, Shovan; Das, Debayan; Sen, Shreyas

2017-07-01

Rapid miniaturization and cost reduction of computing, along with the availability of wearable and implantable physiological sensors have led to the growth of human Body Area Network (BAN) formed by a network of such sensors and computing devices. One promising application of such a network is wearable health monitoring where the collected data from the sensors would be transmitted and analyzed to assess the health of a person. Typically, the devices in a BAN are connected through wireless (WBAN), which suffers from energy inefficiency due to the high-energy consumption of wireless transmission. Human Body Communication (HBC) uses the relatively low loss human body as the communication medium to connect these devices, promising order(s) of magnitude better energy-efficiency and built-in security compared to WBAN. In this paper, we demonstrate a health monitoring device and system built using Commercial-Off-The-Shelf (COTS) sensors and components, that can collect data from physiological sensors and transmit it through a) intra-body HBC to another device (hub) worn on the body or b) upload health data through HBC-based human-machine interaction to an HBC capable machine. The system design constraints and signal transfer characteristics for the implemented HBC-based wearable health monitoring system are measured and analyzed, showing reliable connectivity with >8× power savings compared to Bluetooth low-energy (BTLE).

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.

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.

Advancing from offline to online activity recognition with wearable sensors.

PubMed

Ermes, Miikka; Parkka, Juha; Cluitmans, Luc

2008-01-01

Activity recognition with wearable sensors could motivate people to perform a variety of different sports and other physical exercises. We have earlier developed algorithms for offline analysis of activity data collected with wearable sensors. In this paper, we present our current progress in advancing the platform for the existing algorithms to an online version, onto a PDA. Acceleration data are obtained from wireless motion bands which send the 3D raw acceleration signals via a Bluetooth link to the PDA which then performs the data collection, feature extraction and activity classification. As a proof-of-concept, the online activity system was tested with three subjects. All of them performed at least 5 minutes of each of the following activities: lying, sitting, standing, walking, running and cycling with an exercise bike. The average second-by-second classification accuracies for the subjects were 99%, 97%, and 82 %. These results suggest that earlier developed offline analysis methods for the acceleration data obtained from wearable sensors can be successfully implemented in an online activity recognition application.

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

Highly Stretchable Core-Sheath Fibers via Wet-Spinning for Wearable Strain Sensors.

PubMed

Tang, Zhenhua; Jia, Shuhai; Wang, Fei; Bian, Changsheng; Chen, Yuyu; Wang, Yonglin; Li, Bo

2018-02-21

Lightweight, stretchable, and wearable strain sensors have recently been widely studied for the development of health monitoring systems, human-machine interfaces, and wearable devices. Herein, highly stretchable polymer elastomer-wrapped carbon nanocomposite piezoresistive core-sheath fibers are successfully prepared using a facile and scalable one-step coaxial wet-spinning assembly approach. The carbon nanotube-polymeric composite core of the stretchable fiber is surrounded by an insulating sheath, similar to conventional cables, and shows excellent electrical conductivity with a low percolation threshold (0.74 vol %). The core-sheath elastic fibers are used as wearable strain sensors, exhibiting ultra-high stretchability (above 300%), excellent stability (>10 000 cycles), fast response, low hysteresis, and good washability. Furthermore, the piezoresistive core-sheath fiber possesses bending-insensitiveness and negligible torsion-sensitive properties, and the strain sensing performance of piezoresistive fibers maintains a high degree of stability under harsh conditions. On the basis of this high level of performance, the fiber-shaped strain sensor can accurately detect both subtle and large-scale human movements by embedding it in gloves and garments or by directly attaching it to the skin. The current results indicate that the proposed stretchable strain sensor has many potential applications in health monitoring, human-machine interfaces, soft robotics, and wearable electronics.

Smart wearable body sensors for patient self-assessment and monitoring.

PubMed

Appelboom, Geoff; Camacho, Elvis; Abraham, Mickey E; Bruce, Samuel S; Dumont, Emmanuel Lp; Zacharia, Brad E; D'Amico, Randy; Slomian, Justin; Reginster, Jean Yves; Bruyère, Olivier; Connolly, E Sander

2014-01-01

Innovations in mobile and electronic healthcare are revolutionizing the involvement of both doctors and patients in the modern healthcare system by extending the capabilities of physiological monitoring devices. Despite significant progress within the monitoring device industry, the widespread integration of this technology into medical practice remains limited. The purpose of this review is to summarize the developments and clinical utility of smart wearable body sensors. We reviewed the literature for connected device, sensor, trackers, telemonitoring, wireless technology and real time home tracking devices and their application for clinicians. Smart wearable sensors are effective and reliable for preventative methods in many different facets of medicine such as, cardiopulmonary, vascular, endocrine, neurological function and rehabilitation medicine. These sensors have also been shown to be accurate and useful for perioperative monitoring and rehabilitation medicine. Although these devices have been shown to be accurate and have clinical utility, they continue to be underutilized in the healthcare industry. Incorporating smart wearable sensors into routine care of patients could augment physician-patient relationships, increase the autonomy and involvement of patients in regards to their healthcare and will provide for novel remote monitoring techniques which will revolutionize healthcare management and spending.

Manufacturing of Wearable Sensors for Human Health and Performance Monitoring

NASA Astrophysics Data System (ADS)

Alizadeh, Azar

2015-03-01

Continuous monitoring of physiological and biological parameters is expected to improve performance and medical outcomes by assessing overall health status and alerting for life-saving interventions. Continuous monitoring of these parameters requires wearable devices with an appropriate form factor (lightweight, comfortable, low energy consuming and even single-use) to avoid disrupting daily activities thus ensuring operation relevance and user acceptance. Many previous efforts to implement remote and wearable sensors have suffered from high cost and poor performance, as well as low clinical and end-use acceptance. New manufacturing and system level design approaches are needed to make the performance and clinical benefits of these sensors possible while satisfying challenging economic, regulatory, clinical, and user-acceptance criteria. In this talk we will review several recent design and manufacturing efforts aimed at designing and building prototype wearable sensors. We will discuss unique opportunities and challenges provided by additive manufacturing, including 3D printing, to drive innovation through new designs, faster prototyping and manufacturing, distributed networks, and new ecosystems. We will also show alternative hybrid self-assembly based integration techniques for low cost large scale manufacturing of single use wearable devices. Coauthors: Prabhjot Singh and Jeffrey Ashe.

Wearable Fall Detector using Integrated Sensors and Energy Devices

PubMed Central

Jung, Sungmook; Hong, Seungki; Kim, Jaemin; Lee, Sangkyu; Hyeon, Taeghwan; Lee, Minbaek; Kim, Dae-Hyeong

2015-01-01

Wearable devices have attracted great attentions as next-generation electronic devices. For the comfortable, portable, and easy-to-use system platform in wearable electronics, a key requirement is to replace conventional bulky and rigid energy devices into thin and deformable ones accompanying the capability of long-term energy supply. Here, we demonstrate a wearable fall detection system composed of a wristband-type deformable triboelectric generator and lithium ion battery in conjunction with integrated sensors, controllers, and wireless units. A stretchable conductive nylon is used as electrodes of the triboelectric generator and the interconnection between battery cells. Ethoxylated polyethylenimine, coated on the surface of the conductive nylon electrode, tunes the work function of a triboelectric generator and maximizes its performance. The electrical energy harvested from the triboelectric generator through human body motions continuously recharges the stretchable battery and prolongs hours of its use. The integrated energy supply system runs the 3-axis accelerometer and related electronics that record human body motions and send the data wirelessly. Upon the unexpected fall occurring, a custom-made software discriminates the fall signal and an emergency alert is immediately sent to an external mobile device. This wearable fall detection system would provide new opportunities in the mobile electronics and wearable healthcare. PMID:26597423

Extracting aerobic system dynamics during unsupervised activities of daily living using wearable sensor machine learning models.

PubMed

Beltrame, Thomas; Amelard, Robert; Wong, Alexander; Hughson, Richard L

2018-02-01

Physical activity levels are related through algorithms to the energetic demand, with no information regarding the integrity of the multiple physiological systems involved in the energetic supply. Longitudinal analysis of the oxygen uptake (V̇o 2 ) by wearable sensors in realistic settings might permit development of a practical tool for the study of the longitudinal aerobic system dynamics (i.e., V̇o 2 kinetics). This study evaluated aerobic system dynamics based on predicted V̇o 2 data obtained from wearable sensors during unsupervised activities of daily living (μADL). Thirteen healthy men performed a laboratory-controlled moderate exercise protocol and were monitored for ≈6 h/day for 4 days (μADL data). Variables derived from hip accelerometer (ACC HIP ), heart rate monitor, and respiratory bands during μADL were extracted and processed by a validated random forest regression model to predict V̇o 2 . The aerobic system analysis was based on the frequency-domain analysis of ACC HIP and predicted V̇o 2 data obtained during μADL. Optimal samples for frequency domain analysis (constrained to ≤0.01 Hz) were selected when ACC HIP was higher than 0.05 g at a given frequency (i.e., participants were active). The temporal characteristics of predicted V̇o 2 data during μADL correlated with the temporal characteristics of measured V̇o 2 data during laboratory-controlled protocol ([Formula: see text] = 0.82, P < 0.001, n = 13). In conclusion, aerobic system dynamics can be investigated during unsupervised activities of daily living by wearable sensors. Although speculative, these algorithms have the potential to be incorporated into wearable systems for early detection of changes in health status in realistic environments by detecting changes in aerobic response dynamics. NEW & NOTEWORTHY The early detection of subclinical aerobic system impairments might be indicative of impaired physiological reserves that impact the capacity for physical activity. This study is the first to use wearable sensors in unsupervised activities of daily living in combination with novel machine learning algorithms to investigate the aerobic system dynamics with the potential to contribute to models of functional health status and guide future individualized health care in the normal population.

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.

Identifying balance impairments in people with Parkinson's disease using video and wearable sensors.

PubMed

Stack, Emma; Agarwal, Veena; King, Rachel; Burnett, Malcolm; Tahavori, Fatemeh; Janko, Balazs; Harwin, William; Ashburn, Ann; Kunkel, Dorit

2018-05-01

Falls and near falls are common among people with Parkinson's (PwP). To date, most wearable sensor research focussed on fall detection, few studies explored if wearable sensors can detect instability. Can instability (caution or near-falls) be detected using wearable sensors in comparison to video analysis? Twenty-four people (aged 60-86) with and without Parkinson's were recruited from community groups. Movements (e.g. walking, turning, transfers and reaching) were observed in the gait laboratory and/or at home; recorded using clinical measures, video and five wearable sensors (attached on the waist, ankles and wrists). After defining 'caution' and 'instability', two researchers evaluated video data and a third the raw wearable sensor data; blinded to each other's evaluations. Agreement between video and sensor data was calculated on stability, timing, step count and strategy. Data was available for 117 performances: 82 (70%) appeared stable on video. Ratings agreed in 86/117 cases (74%). Highest agreement was noted for chair transfer, timed up and go test and 3 m walks. Video analysts noted caution (slow, contained movements, safety-enhancing postures and concentration) and/or instability (saving reactions, stopping after stumbling or veering) in 40/134 performances (30%): raw wearable sensor data identified 16/35 performances rated cautious or unstable (sensitivity 46%) and 70/82 rated stable (specificity 85%). There was a 54% chance that a performance identified from wearable sensors as cautious/unstable was so; rising to 80% for stable movements. Agreement between wearable sensor and video data suggested that wearable sensors can detect subtle instability and near-falls. Caution and instability were observed in nearly a third of performances, suggesting that simple, mildly challenging actions, with clearly defined start- and end-points, may be most amenable to monitoring during free-living at home. Using the genuine near-falls recorded, work continues to automatically detect subtle instability using algorithms. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

SmartStuff: A case study of a smart water bottle.

PubMed

Jovanov, Emil; Nallathimmareddygari, Vindhya R; Pryor, Jonathan E

2016-08-01

The rapid growth of Internet of Things (IoT) and miniature wearable biosensors have generated new opportunities for personalized eHealth and mHealth services. Smart objects equipped with physiological sensors can provide robust monitoring of activities of daily living and context for wearable physiological sensors. We present a case study of an intelligent water bottle that can precisely measure the amount of liquid in the bottle, monitor activity using inertial sensors, and physiological parameters using a touch and photoplethysmographic sensor. We evaluate two system configurations: a smart water bottle integrated into a personal body sensor network and a cloud based device. This paper presents system organization and the results from preliminary field testing of the prototype device.

Wearable and Implantable Wireless Sensor Network Solutions for Healthcare Monitoring

PubMed Central

Darwish, Ashraf; Hassanien, Aboul Ella

2011-01-01

Wireless sensor network (WSN) technologies are considered one of the key research areas in computer science and the healthcare application industries for improving the quality of life. The purpose of this paper is to provide a snapshot of current developments and future direction of research on wearable and implantable body area network systems for continuous monitoring of patients. This paper explains the important role of body sensor networks in medicine to minimize the need for caregivers and help the chronically ill and elderly people live an independent life, besides providing people with quality care. The paper provides several examples of state of the art technology together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provides a comprehensive analysis of the various benefits and drawbacks of these systems. Although offering significant benefits, the field of wearable and implantable body sensor networks still faces major challenges and open research problems which are investigated and covered, along with some proposed solutions, in this paper. PMID:22163914

Wearable and implantable wireless sensor network solutions for healthcare monitoring.

PubMed

Darwish, Ashraf; Hassanien, Aboul Ella

2011-01-01

Wireless sensor network (WSN) technologies are considered one of the key research areas in computer science and the healthcare application industries for improving the quality of life. The purpose of this paper is to provide a snapshot of current developments and future direction of research on wearable and implantable body area network systems for continuous monitoring of patients. This paper explains the important role of body sensor networks in medicine to minimize the need for caregivers and help the chronically ill and elderly people live an independent life, besides providing people with quality care. The paper provides several examples of state of the art technology together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provides a comprehensive analysis of the various benefits and drawbacks of these systems. Although offering significant benefits, the field of wearable and implantable body sensor networks still faces major challenges and open research problems which are investigated and covered, along with some proposed solutions, in this paper.

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 Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients

PubMed Central

Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

2016-01-01

Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1) they are susceptible to subjective factors; (2) they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information. PMID:26861337

A Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients.

PubMed

Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

2016-02-05

Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1) they are susceptible to subjective factors; (2) they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information.

Low-Cost Embedded Oximeter

NASA Astrophysics Data System (ADS)

Laghrouche, M.; Haddab, S.; Lotmani, S.; Mekdoud, K.; Ameur, S.

2010-01-01

Nowadays, many medical devices have been developed for the purposes of diagnosing and treatment. Wearable sensors and systems have evolved to the point that they can be considered ready for clinical application. The use of wearable monitoring devices that allow continuous or intermittent monitoring of physiological signals is critical for the advancement of both the diagnosis as well as treatment of diseases. Patient vital sign monitoring within hospitals requires the use of noninvasive sensors that are hardwired to bedside monitors. This paper describes the initial bench testing of a wireless wearable pulse oximeter. Arterial oxygen saturation in the patient's blood signal was measured with an optical sensor, and then converted to digital data using a microcontroller system. The digital data were then sent to a receiver where it is in 433 MHz FM/FSK transmitter. At the receiver, the digital data were reconverted to analog signal to be monitored and recorded on the PC.

A Wearable Hydration Sensor with Conformal Nanowire Electrodes.

PubMed

Yao, Shanshan; Myers, Amanda; Malhotra, Abhishek; Lin, Feiyan; Bozkurt, Alper; Muth, John F; Zhu, Yong

2017-03-01

A wearable skin hydration sensor in the form of a capacitor is demonstrated based on skin impedance measurement. The capacitor consists of two interdigitated or parallel electrodes that are made of silver nanowires (AgNWs) in a polydimethylsiloxane (PDMS) matrix. The flexible and stretchable nature of the AgNW/PDMS electrode allows conformal contact to the skin. The hydration sensor is insensitive to the external humidity change and is calibrated against a commercial skin hydration system on an artificial skin over a wide hydration range. The hydration sensor is packaged into a flexible wristband, together with a network analyzer chip, a button cell battery, and an ultralow power microprocessor with Bluetooth. In addition, a chest patch consisting of a strain sensor, three electrocardiography electrodes, and a skin hydration sensor is developed for multimodal sensing. The wearable wristband and chest patch may be used for low-cost, wireless, and continuous monitoring of skin hydration and other health parameters. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Estimation of Center of Mass Trajectory using Wearable Sensors during Golf Swing.

PubMed

Najafi, Bijan; Lee-Eng, Jacqueline; Wrobel, James S; Goebel, Ruben

2015-06-01

This study suggests a wearable sensor technology to estimate center of mass (CoM) trajectory during a golf swing. Groups of 3, 4, and 18 participants were recruited, respectively, for the purpose of three validation studies. Study 1 examined the accuracy of the system to estimate a 3D body segment angle compared to a camera-based motion analyzer (Vicon®). Study 2 assessed the accuracy of three simplified CoM trajectory models. Finally, Study 3 assessed the accuracy of the proposed CoM model during multiple golf swings. A relatively high agreement was observed between wearable sensors and the reference (Vicon®) for angle measurement (r > 0.99, random error <1.2° (1.5%) for anterior-posterior; <0.9° (2%) for medial-lateral; and <3.6° (2.5%) for internal-external direction). The two-link model yielded a better agreement with the reference system compared to one-link model (r > 0.93 v. r = 0.52, respectively). On the same note, the proposed two-link model estimated CoM trajectory during golf swing with relatively good accuracy (r > 0.9, A-P random error <1cm (7.7%) and <2cm (10.4%) for M-L). The proposed system appears to accurately quantify the kinematics of CoM trajectory as a surrogate of dynamic postural control during an athlete's movement and its portability, makes it feasible to fit the competitive environment without restricting surface type. Key pointsThis study demonstrates that wearable technology based on inertial sensors are accurate to estimate center of mass trajectory in complex athletic task (e.g., golf swing)This study suggests that two-link model of human body provides optimum tradeoff between accuracy and minimum number of sensor module for estimation of center of mass trajectory in particular during fast movements.Wearable technologies based on inertial sensors are viable option for assessing dynamic postural control in complex task outside of gait laboratory and constraints of cameras, surface, and base of support.

Low Power Wearable Systems for Continuous Monitoring of Environment and Health for Chronic Respiratory Disease

PubMed Central

Dieffenderfer, James; Goodell, Henry; Mills, Steven; McKnight, Michael; Yao, Shanshan; Lin, Feiyan; Beppler, Eric; Bent, Brinnae; Lee, Bongmook; Misra, Veena; Zhu, Yong; Oralkan, Omer; Strohmaier, Jason; Muth, John; Peden, David; Bozkurt, Alper

2016-01-01

We present our efforts towards enabling a wearable sensor system that allows for the correlation of individual environmental exposures to physiologic and subsequent adverse health responses. This system will permit a better understanding of the impact of increased ozone levels and other pollutants on chronic asthma conditions. We discuss the inefficiency of existing commercial off-the-shelf components to achieve continuous monitoring and our system-level and nano-enabled efforts towards improving the wearability and power consumption. Our system consists of a wristband, a chest patch, and a handheld spirometer. We describe our preliminary efforts to achieve a sub-milliwatt system ultimately powered by the energy harvested from thermal radiation and motion of the body with the primary contributions being an ultra-low power ozone sensor, an volatile organic compounds sensor, spirometer, and the integration of these and other sensors in a multimodal sensing platform. The measured environmental parameters include ambient ozone concentration, temperature, and relative humidity. Our array of sensors also assesses heart rate via photoplethysmography and electrocardiography, respiratory rate via photoplethysmography, skin impedance, three-axis acceleration, wheezing via a microphone, and expiratory airflow. The sensors on the wristband, chest patch, and spirometer consume 0.83, 0.96, and 0.01 milliwatts respectively. The data from each sensor is continually streamed to a peripheral data aggregation device and is subsequently transferred to a dedicated server for cloud storage. Future work includes reducing the power consumption of the system-on-chip including radio to reduce the entirety of each described system in the sub-milliwatt range. PMID:27249840

Low-Power Wearable Systems for Continuous Monitoring of Environment and Health for Chronic Respiratory Disease.

PubMed

Dieffenderfer, James; Goodell, Henry; Mills, Steven; McKnight, Michael; Yao, Shanshan; Lin, Feiyan; Beppler, Eric; Bent, Brinnae; Lee, Bongmook; Misra, Veena; Zhu, Yong; Oralkan, Omer; Strohmaier, Jason; Muth, John; Peden, David; Bozkurt, Alper

2016-09-01

We present our efforts toward enabling a wearable sensor system that allows for the correlation of individual environmental exposures with physiologic and subsequent adverse health responses. This system will permit a better understanding of the impact of increased ozone levels and other pollutants on chronic asthma conditions. We discuss the inefficiency of existing commercial off-the-shelf components to achieve continuous monitoring and our system-level and nano-enabled efforts toward improving the wearability and power consumption. Our system consists of a wristband, a chest patch, and a handheld spirometer. We describe our preliminary efforts to achieve a submilliwatt system ultimately powered by the energy harvested from thermal radiation and motion of the body with the primary contributions being an ultralow-power ozone sensor, an volatile organic compounds sensor, spirometer, and the integration of these and other sensors in a multimodal sensing platform. The measured environmental parameters include ambient ozone concentration, temperature, and relative humidity. Our array of sensors also assesses heart rate via photoplethysmography and electrocardiography, respiratory rate via photoplethysmography, skin impedance, three-axis acceleration, wheezing via a microphone, and expiratory airflow. The sensors on the wristband, chest patch, and spirometer consume 0.83, 0.96, and 0.01 mW, respectively. The data from each sensor are continually streamed to a peripheral data aggregation device and are subsequently transferred to a dedicated server for cloud storage. Future work includes reducing the power consumption of the system-on-chip including radio to reduce the entirety of each described system in the submilliwatt range.

Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition

PubMed Central

Banos, Oresti; Toth, Mate Attila; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

2014-01-01

Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements. In this work, we innovatively explore the effects of sensor displacement induced by both the intentional misplacement of sensors and self-placement by the user. The effects of sensor displacement are analyzed for standard activity recognition techniques, as well as for an alternate robust sensor fusion method proposed in a previous work. While classical recognition models show little tolerance to sensor displacement, the proposed method is proven to have notable capabilities to assimilate the changes introduced in the sensor position due to self-placement and provides considerable improvements for large misplacements. PMID:24915181

Light-controlling, flexible and transparent ethanol gas sensor based on ZnO nanoparticles for wearable devices

PubMed Central

Zheng, Z. Q.; Yao, J. D.; Wang, B.; Yang, G. W.

2015-01-01

In recent years, owing to the significant applications of health monitoring, wearable electronic devices such as smart watches, smart glass and wearable cameras have been growing rapidly. Gas sensor is an important part of wearable electronic devices for detecting pollutant, toxic, and combustible gases. However, in order to apply to wearable electronic devices, the gas sensor needs flexible, transparent, and working at room temperature, which are not available for traditional gas sensors. Here, we for the first time fabricate a light-controlling, flexible, transparentand working at room-temperature ethanol gas sensor by using commercial ZnO nanoparticles. The fabricated sensor not only exhibits fast and excellent photoresponse, but also shows high sensing response to ethanol under UV irradiation. Meanwhile, its transmittance exceeds 62% in the visible spectral range, and the sensing performance keeps the same even bent it at a curvature angle of 90o. Additionally, using commercial ZnO nanoparticles provides a facile and low-cost route to fabricate wearable electronic devices. PMID:26076705

Light-controlling, flexible and transparent ethanol gas sensor based on ZnO nanoparticles for wearable devices.

PubMed

Zheng, Z Q; Yao, J D; Wang, B; Yang, G W

2015-06-16

In recent years, owing to the significant applications of health monitoring, wearable electronic devices such as smart watches, smart glass and wearable cameras have been growing rapidly. Gas sensor is an important part of wearable electronic devices for detecting pollutant, toxic, and combustible gases. However, in order to apply to wearable electronic devices, the gas sensor needs flexible, transparent, and working at room temperature, which are not available for traditional gas sensors. Here, we for the first time fabricate a light-controlling, flexible, transparent, and working at room-temperature ethanol gas sensor by using commercial ZnO nanoparticles. The fabricated sensor not only exhibits fast and excellent photoresponse, but also shows high sensing response to ethanol under UV irradiation. Meanwhile, its transmittance exceeds 62% in the visible spectral range, and the sensing performance keeps the same even bent it at a curvature angle of 90(o). Additionally, using commercial ZnO nanoparticles provides a facile and low-cost route to fabricate wearable electronic devices.

Recognition physical activities with optimal number of wearable sensors using data mining algorithms and deep belief network.

PubMed

Al-Fatlawi, Ali H; Fatlawi, Hayder K; Sai Ho Ling

2017-07-01

Daily physical activities monitoring is benefiting the health care field in several ways, in particular with the development of the wearable sensors. This paper adopts effective ways to calculate the optimal number of the necessary sensors and to build a reliable and a high accuracy monitoring system. Three data mining algorithms, namely Decision Tree, Random Forest and PART Algorithm, have been applied for the sensors selection process. Furthermore, the deep belief network (DBN) has been investigated to recognise 33 physical activities effectively. The results indicated that the proposed method is reliable with an overall accuracy of 96.52% and the number of sensors is minimised from nine to six sensors.

Wearable Wireless Telemetry System for Implantable Bio-MEMS Sensors

NASA Technical Reports Server (NTRS)

Simons, Rainee N.; Miranda, Felix A.; Wilson, Jeffrey D.; Simons, Renita E.

2006-01-01

In this paper, a telemetry and contact-less powering system consisting of an implantable bio-MEMS sensor with a miniature printed square spiral chip antenna and an external wearable garment with printed loop antenna is investigated. The wearable garment pick-up antenna and the implantable chip antenna are in close proximity to each other and hence couple inductively through their near-fields and behave as the primary and the secondary circuits of a transformer, respectively. The numerical and experimental results are graphically presented, and include the design parameter values as a function of the geometry, the relative RF magnetic near-field intensity as a function of the distance and angle, and the current density on the strip conductors, for the implantable chip antenna.

Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges

PubMed Central

Banaee, Hadi; Ahmed, Mobyen Uddin; Loutfi, Amy

2013-01-01

The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems. PMID:24351646

Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges.

PubMed

Banaee, Hadi; Ahmed, Mobyen Uddin; Loutfi, Amy

2013-12-17

The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems.

Wearable Wireless Tyrosinase Bandage and Microneedle Sensors: Toward Melanoma Screening.

PubMed

Ciui, Bianca; Martin, Aida; Mishra, Rupesh K; Brunetti, Barbara; Nakagawa, Tatsuo; Dawkins, Thomas J; Lyu, Mengjia; Cristea, Cecilia; Sandulescu, Robert; Wang, Joseph

2018-04-01

Wearable bendable bandage-based sensor and a minimally invasive microneedle biosensor are described toward rapid screening of skin melanoma. These wearable electrochemical sensors are capable of detecting the presence of the tyrosinase (TYR) enzyme cancer biomarker in the presence of its catechol substrate, immobilized on the transducer surface. In the presence of the surface TYR biomarker, the immobilized catechol is rapidly converted to benzoquinone that is detected amperometrically, with a current signal proportional to the TYR level. The flexible epidermal bandage sensor relies on printing stress-enduring inks which display good resiliency against mechanical deformations, whereas the hollow microneedle device is filled with catechol-coated carbon paste for assessing tissue TYR levels. The bandage sensor can thus be used directly on the skin whereas microneedle device can reach melanoma tissues under the skin. Both wearable sensors are interfaced to an ultralight flexible electronic board, which transmits data wirelessly to a mobile device. The analytical performance of the resulting bandage and microneedle sensing systems are evaluated using TYR-containing agarose phantom gel and porcine skin. The new integrated conformal portable sensing platforms hold considerable promise for decentralized melanoma screening, and can be extended to the screening of other key biomarkers in skin moles. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Real-Time Health Monitoring System for Remote Cardiac Patients Using Smartphone and Wearable Sensors.

PubMed

Kakria, Priyanka; Tripathi, N K; Kitipawang, Peerapong

2015-01-01

Online telemedicine systems are useful due to the possibility of timely and efficient healthcare services. These systems are based on advanced wireless and wearable sensor technologies. The rapid growth in technology has remarkably enhanced the scope of remote health monitoring systems. In this paper, a real-time heart monitoring system is developed considering the cost, ease of application, accuracy, and data security. The system is conceptualized to provide an interface between the doctor and the patients for two-way communication. The main purpose of this study is to facilitate the remote cardiac patients in getting latest healthcare services which might not be possible otherwise due to low doctor-to-patient ratio. The developed monitoring system is then evaluated for 40 individuals (aged between 18 and 66 years) using wearable sensors while holding an Android device (i.e., smartphone under supervision of the experts). The performance analysis shows that the proposed system is reliable and helpful due to high speed. The analyses showed that the proposed system is convenient and reliable and ensures data security at low cost. In addition, the developed system is equipped to generate warning messages to the doctor and patient under critical circumstances.

A Real-Time Health Monitoring System for Remote Cardiac Patients Using Smartphone and Wearable Sensors

PubMed Central

Kakria, Priyanka; Tripathi, N. K.; Kitipawang, Peerapong

2015-01-01

Online telemedicine systems are useful due to the possibility of timely and efficient healthcare services. These systems are based on advanced wireless and wearable sensor technologies. The rapid growth in technology has remarkably enhanced the scope of remote health monitoring systems. In this paper, a real-time heart monitoring system is developed considering the cost, ease of application, accuracy, and data security. The system is conceptualized to provide an interface between the doctor and the patients for two-way communication. The main purpose of this study is to facilitate the remote cardiac patients in getting latest healthcare services which might not be possible otherwise due to low doctor-to-patient ratio. The developed monitoring system is then evaluated for 40 individuals (aged between 18 and 66 years) using wearable sensors while holding an Android device (i.e., smartphone under supervision of the experts). The performance analysis shows that the proposed system is reliable and helpful due to high speed. The analyses showed that the proposed system is convenient and reliable and ensures data security at low cost. In addition, the developed system is equipped to generate warning messages to the doctor and patient under critical circumstances. PMID:26788055

Multifunctional wearable devices for diagnosis and therapy of movement disorders.

PubMed

Son, Donghee; Lee, Jongha; Qiao, Shutao; Ghaffari, Roozbeh; Kim, Jaemin; Lee, Ji Eun; Song, Changyeong; Kim, Seok Joo; Lee, Dong Jun; Jun, Samuel Woojoo; Yang, Shixuan; Park, Minjoon; Shin, Jiho; Do, Kyungsik; Lee, Mincheol; Kang, Kwanghun; Hwang, Cheol Seong; Lu, Nanshu; Hyeon, Taeghwan; Kim, Dae-Hyeong

2014-05-01

Wearable systems that monitor muscle activity, store data and deliver feedback therapy are the next frontier in personalized medicine and healthcare. However, technical challenges, such as the fabrication of high-performance, energy-efficient sensors and memory modules that are in intimate mechanical contact with soft tissues, in conjunction with controlled delivery of therapeutic agents, limit the wide-scale adoption of such systems. Here, we describe materials, mechanics and designs for multifunctional, wearable-on-the-skin systems that address these challenges via monolithic integration of nanomembranes fabricated with a top-down approach, nanoparticles assembled by bottom-up methods, and stretchable electronics on a tissue-like polymeric substrate. Representative examples of such systems include physiological sensors, non-volatile memory and drug-release actuators. Quantitative analyses of the electronics, mechanics, heat-transfer and drug-diffusion characteristics validate the operation of individual components, thereby enabling system-level multifunctionalities.

Wearable Devices in Medical Internet of Things: Scientific Research and Commercially Available Devices

PubMed Central

Thurow, Kerstin; Stoll, Regina

2017-01-01

Objectives Wearable devices are currently at the heart of just about every discussion related to the Internet of Things. The requirement for self-health monitoring and preventive medicine is increasing due to the projected dramatic increase in the number of elderly people until 2020. Developed technologies are truly able to reduce the overall costs for prevention and monitoring. This is possible by constantly monitoring health indicators in various areas, and in particular, wearable devices are considered to carry this task out. These wearable devices and mobile apps now have been integrated with telemedicine and telehealth efficiently, to structure the medical Internet of Things. This paper reviews wearable health care devices both in scientific papers and commercial efforts. Methods MIoT is demonstrated through a defined architecture design, including hardware and software dealing with wearable devices, sensors, smart phones, medical application, and medical station analyzers for further diagnosis and data storage. Results Wearables, with the help of improved technology have been developed greatly and are considered reliable tools for long-term health monitoring systems. These are applied in the observation of a large variety of health monitoring indicators in the environment, vital signs, and fitness. Conclusions Wearable devices are now used for a wide range of healthcare observation. One of the most important elements essential in data collection is the sensor. During recent years with improvement in semiconductor technology, sensors have made investigation of a full range of parameters closer to realization. PMID:28261526

Wearable Devices in Medical Internet of Things: Scientific Research and Commercially Available Devices.

PubMed

Haghi, Mostafa; Thurow, Kerstin; Stoll, Regina

2017-01-01

Wearable devices are currently at the heart of just about every discussion related to the Internet of Things. The requirement for self-health monitoring and preventive medicine is increasing due to the projected dramatic increase in the number of elderly people until 2020. Developed technologies are truly able to reduce the overall costs for prevention and monitoring. This is possible by constantly monitoring health indicators in various areas, and in particular, wearable devices are considered to carry this task out. These wearable devices and mobile apps now have been integrated with telemedicine and telehealth efficiently, to structure the medical Internet of Things. This paper reviews wearable health care devices both in scientific papers and commercial efforts. MIoT is demonstrated through a defined architecture design, including hardware and software dealing with wearable devices, sensors, smart phones, medical application, and medical station analyzers for further diagnosis and data storage. Wearables, with the help of improved technology have been developed greatly and are considered reliable tools for long-term health monitoring systems. These are applied in the observation of a large variety of health monitoring indicators in the environment, vital signs, and fitness. Wearable devices are now used for a wide range of healthcare observation. One of the most important elements essential in data collection is the sensor. During recent years with improvement in semiconductor technology, sensors have made investigation of a full range of parameters closer to realization.

A wearable device for emotional recognition using facial expression and physiological response.

PubMed

Jangho Kwon; Da-Hye Kim; Wanjoo Park; Laehyun Kim

2016-08-01

This paper introduces a glasses-typed wearable system to detect user's emotions using facial expression and physiological responses. The system is designed to acquire facial expression through a built-in camera and physiological responses such as photoplethysmogram (PPG) and electrodermal activity (EDA) in unobtrusive way. We used video clips for induced emotions to test the system suitability in the experiment. The results showed a few meaningful properties that associate emotions with facial expressions and physiological responses captured by the developed wearable device. We expect that this wearable system with a built-in camera and physiological sensors may be a good solution to monitor user's emotional state in daily life.

Unintended Consequences of Wearable Sensor Use in Healthcare. Contribution of the IMIA Wearable Sensors in Healthcare WG.

PubMed

Schukat, M; McCaldin, D; Wang, K; Schreier, G; Lovell, N H; Marschollek, M; Redmond, S J

2016-11-10

As wearable sensors take the consumer market by storm, and medical device manufacturers move to make their devices wireless and appropriate for ambulatory use, this revolution brings with it some unintended consequences, which we aim to discuss in this paper. We discuss some important unintended consequences, both beneficial and unwanted, which relate to: modifications of behavior; creation and use of big data sets; new security vulnerabilities; and unforeseen challenges faced by regulatory authorities, struggling to keep pace with recent innovations. Where possible, we proposed potential solutions to unwanted consequences. Intelligent and inclusive design processes may mitigate unintended modifications in behavior. For big data, legislating access to and use of these data will be a legal and political challenge in the years ahead, as we trade the health benefits of wearable sensors against the risk to our privacy. The wireless and personal nature of wearable sensors also exposes them to a number of unique security vulnerabilities. Regulation plays an important role in managing these security risks, but also has the dual responsibility of ensuring that wearable devices are fit for purpose. However, the burden of validating the function and security of medical devices is becoming infeasible for regulators, given the many software apps and wearable sensors entering the market each year, which are only a subset of an even larger 'internet of things'. Wearable sensors may serve to improve wellbeing, but we must be vigilant against the occurrence of unintended consequences. With collaboration between device manufacturers, regulators, and end-users, we balance the risk of unintended consequences occurring against the incredible benefit that wearable sensors promise to bring to the world.

Wearable carbon nanotube-based fabric sensors for monitoring human physiological performance

NASA Astrophysics Data System (ADS)

Wang, Long; Loh, Kenneth J.

2017-05-01

A target application of wearable sensors is to detect human motion and to monitor physical activity for improving athletic performance and for delivering better physical therapy. In addition, measuring human vital signals (e.g., respiration rate and body temperature) provides rich information that can be used to assess a subject’s physiological or psychological condition. This study aims to design a multifunctional, wearable, fabric-based sensing system. First, carbon nanotube (CNT)-based thin films were fabricated by spraying. Second, the thin films were integrated with stretchable fabrics to form the fabric sensors. Third, the strain and temperature sensing properties of sensors fabricated using different CNT concentrations were characterized. Furthermore, the sensors were demonstrated to detect human finger bending motions, so as to validate their practical strain sensing performance. Finally, to monitor human respiration, the fabric sensors were integrated with a chest band, which was directly worn by a human subject. Quantification of respiration rates were successfully achieved. Overall, the fabric sensors were characterized by advantages such as flexibility, ease of fabrication, lightweight, low-cost, noninvasiveness, and user comfort.

Wearable technology for spine movement assessment: A systematic review.

PubMed

Papi, Enrica; Koh, Woon Senn; McGregor, Alison H

2017-11-07

Continuous monitoring of spine movement function could enhance our understanding of low back pain development. Wearable technologies have gained popularity as promising alternative to laboratory systems in allowing ambulatory movement analysis. This paper aims to review the state of art of current use of wearable technology to assess spine kinematics and kinetics. Four electronic databases and reference lists of relevant articles were searched to find studies employing wearable technologies to assess the spine in adults performing dynamic movements. Two reviewers independently identified relevant papers. Customised data extraction and quality appraisal form were developed to extrapolate key details and identify risk of biases of each study. Twenty-two articles were retrieved that met the inclusion criteria: 12 were deemed of medium quality (score 33.4-66.7%), and 10 of high quality (score >66.8%). The majority of articles (19/22) reported validation type studies. Only 6 reported data collection in real-life environments. Multiple sensors type were used: electrogoniometers (3/22), strain gauges based sensors (3/22), textile piezoresistive sensor (1/22) and accelerometers often used with gyroscopes and magnetometers (15/22). Two sensors units were mainly used and placing was commonly reported on the spine lumbar and sacral regions. The sensors were often wired to data transmitter/logger resulting in cumbersome systems. Outcomes were mostly reported relative to the lumbar segment and in the sagittal plane, including angles, range of motion, angular velocity, joint moments and forces. This review demonstrates the applicability of wearable technology to assess the spine, although this technique is still at an early stage of development. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Gas sensors boosted by two-dimensional h-BN enabled transfer on thin substrate foils: towards wearable and portable applications.

PubMed

Ayari, Taha; Bishop, Chris; Jordan, Matthew B; Sundaram, Suresh; Li, Xin; Alam, Saiful; ElGmili, Youssef; Patriarche, Gilles; Voss, Paul L; Salvestrini, Jean Paul; Ougazzaden, Abdallah

2017-11-09

The transfer of GaN based gas sensors to foreign substrates provides a pathway to enhance sensor performance, lower the cost and extend the applications to wearable, mobile or disposable systems. The main keys to unlocking this pathway is to grow and fabricate the sensors on large h-BN surface and to transfer them to the flexible substrate without any degradation of the performances. In this work, we develop a new generation of AlGaN/GaN gas sensors with boosted performances on a low cost flexible substrate. We fabricate 2-inch wafer scale AlGaN/GaN gas sensors on sacrificial two-dimensional (2D) nano-layered h-BN without any delamination or cracks and subsequently transfer sensors to an acrylic surface on metallic foil. This technique results in a modification of relevant device properties, leading to a doubling of the sensitivity to NO 2 gas and a response time that is more than 6 times faster than before transfer. This new approach for GaN-based sensor design opens new avenues for sensor improvement via transfer to more suitable substrates, and is promising for next-generation wearable and portable opto-electronic devices.

Barriers to the Adoption of Wearable Sensors in the Workplace: A Survey of Occupational Safety and Health Professionals.

PubMed

Schall, Mark C; Sesek, Richard F; Cavuoto, Lora A

2018-05-01

To gather information on the (a) types of wearable sensors, particularly personal activity monitors, currently used by occupational safety and health (OSH) professionals; (b) potential benefits of using such technologies in the workplace; and (c) perceived barriers preventing the widespread adoption of wearable sensors in industry. Wearable sensors are increasingly being promoted as a means to improve employee health and well-being, and there is mounting evidence supporting their use as exposure assessment and personal health tools. Despite this, many workplaces have been hesitant to adopt these technologies. An electronic survey was emailed to 28,428 registered members of the American Society of Safety Engineers (ASSE) and 1,302 professionals certified by the Board of Certification in Professional Ergonomics (BCPE). A total of 952 valid responses were returned. Over half of respondents described being in favor of using wearable sensors to track OSH-related risk factors and relevant exposure metrics at their respective workplaces. However, barriers including concerns regarding employee privacy/confidentiality of collected data, employee compliance, sensor durability, the cost/benefit ratio of using wearables, and good manufacturing practice requirements were described as challenges precluding adoption. The broad adoption of wearable technologies appears to depend largely on the scientific community's ability to successfully address the identified barriers. Investigators may use the information provided to develop research studies that better address OSH practitioner concerns and help technology developers operationalize wearable sensors to improve employee health and well-being.

Implementation study of wearable sensors for activity recognition systems.

PubMed

Rezaie, Hamed; Ghassemian, Mona

2015-08-01

This Letter investigates and reports on a number of activity recognition methods for a wearable sensor system. The authors apply three methods for data transmission, namely 'stream-based', 'feature-based' and 'threshold-based' scenarios to study the accuracy against energy efficiency of transmission and processing power that affects the mote's battery lifetime. They also report on the impact of variation of sampling frequency and data transmission rate on energy consumption of motes for each method. This study leads us to propose a cross-layer optimisation of an activity recognition system for provisioning acceptable levels of accuracy and energy efficiency.

An Embedded, Eight Channel, Noise Canceling, Wireless, Wearable sEMG Data Acquisition System With Adaptive Muscle Contraction Detection.

PubMed

Ergeneci, Mert; Gokcesu, Kaan; Ertan, Erhan; Kosmas, Panagiotis

2018-02-01

Wearable technology has gained increasing popularity in the applications of healthcare, sports science, and biomedical engineering in recent years. Because of its convenient nature, the wearable technology is particularly useful in the acquisition of the physiological signals. Specifically, the (surface electromyography) sEMG systems, which measure the muscle activation potentials, greatly benefit from this technology in both clinical and industrial applications. However, the current wearable sEMG systems have several drawbacks including inefficient noise cancellation, insufficient measurement quality, and difficult integration to customized applications. Additionally, none of these sEMG data acquisition systems can detect sEMG signals (i.e., contractions), which provides a valuable environment for further studies such as human machine interaction, gesture recognition, and fatigue tracking. To this end, we introduce an embedded, eight channel, noise canceling, wireless, wearable sEMG data acquisition system with adaptive muscle contraction detection. Our design consists of two stages, which are the sEMG sensors and the multichannel data acquisition unit. For the first stage, we propose a low cost, dry, and active sEMG sensor that captures the muscle activation potentials, a data acquisition unit that evaluates these captured multichannel sEMG signals and transmits them to a user interface. In the data acquisition unit, the sEMG signals are processed through embedded, adaptive methods in order to reject the power line noise and detect the muscle contractions. Through extensive experiments, we demonstrate that our sEMG sensor outperforms a widely used commercially available product and our data acquisition system achieves 4.583 dB SNR gain with accuracy in the detection of the contractions.

Collecting and distributing wearable sensor data: an embedded personal area network to local area network gateway server.

PubMed

Neuhaeuser, Jakob; D'Angelo, Lorenzo T

2013-01-01

The goal of the concept and of the device presented in this contribution is to be able to collect sensor data from wearable sensors directly, automatically and wirelessly and to make them available over a wired local area network. Several concepts in e-health and telemedicine make use of portable and wearable sensors to collect movement or activity data. Usually these data are either collected via a wireless personal area network or using a connection to the user's smartphone. However, users might not carry smartphones on them while inside a residential building such as a nursing home or a hospital, but also within their home. Also, in such areas the use of other wireless communication technologies might be limited. The presented system is an embedded server which can be deployed in several rooms in order to ensure live data collection in bigger buildings. Also, the collection of data batches recorded out of range, as soon as a connection is established, is also possible. Both, the system concept and the realization are presented.

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.

Sensorized Garments and Textrode-Enabled Measurement Instrumentation for Ambulatory Assessment of the Autonomic Nervous System Response in the ATREC Project

PubMed Central

Seoane, Fernando; Ferreira, Javier; Alvarez, Lorena; Buendia, Ruben; Ayllón, David; Llerena, Cosme; Gil-Pita, Roberto

2013-01-01

Advances in textile materials, technology and miniaturization of electronics for measurement instrumentation has boosted the development of wearable measurement systems. In several projects sensorized garments and non-invasive instrumentation have been integrated to assess on emotional, cognitive responses as well as physical arousal and status of mental stress through the study of the autonomous nervous system. Assessing the mental state of workers under stressful conditions is critical to identify which workers are in the proper state of mind and which are not ready to undertake a mission, which might consequently risk their own life and the lives of others. The project Assessment in Real Time of the Stress in Combatants (ATREC) aims to enable real time assessment of mental stress of the Spanish Armed Forces during military activities using a wearable measurement system containing sensorized garments and textile-enabled non-invasive instrumentation. This work describes the multiparametric sensorized garments and measurement instrumentation implemented in the first phase of the project required to evaluate physiological indicators and recording candidates that can be useful for detection of mental stress. For such purpose different sensorized garments have been constructed: a textrode chest-strap system with six repositionable textrodes, a sensorized glove and an upper-arm strap. The implemented textile-enabled instrumentation contains one skin galvanometer, two temperature sensors for skin and environmental temperature and an impedance pneumographer containing a 1-channel ECG amplifier to record cardiogenic biopotentials. With such combinations of garments and non-invasive measurement devices, a multiparametric wearable measurement system has been implemented able to record the following physiological parameters: heart and respiration rate, skin galvanic response, environmental and peripheral temperature. To ensure the proper functioning of the implemented garments and devices the full series of 12 sets have been functionally tested recording cardiogenic biopotential, thoracic impedance, galvanic skin response and temperature values. The experimental results indicate that the implemented wearable measurement systems operate according to the specifications and are ready to be used for mental stress experiments, which will be executed in the coming phases of the project with dozens of healthy volunteers. PMID:23857264

Sensorized garments and textrode-enabled measurement instrumentation for ambulatory assessment of the autonomic nervous system response in the ATREC project.

PubMed

Seoane, Fernando; Ferreira, Javier; Alvarez, Lorena; Buendia, Ruben; Ayllón, David; Llerena, Cosme; Gil-Pita, Roberto

2013-07-12

Advances in textile materials, technology and miniaturization of electronics for measurement instrumentation has boosted the development of wearable measurement systems. In several projects sensorized garments and non-invasive instrumentation have been integrated to assess on emotional, cognitive responses as well as physical arousal and status of mental stress through the study of the autonomous nervous system. Assessing the mental state of workers under stressful conditions is critical to identify which workers are in the proper state of mind and which are not ready to undertake a mission, which might consequently risk their own life and the lives of others. The project Assessment in Real Time of the Stress in Combatants (ATREC) aims to enable real time assessment of mental stress of the Spanish Armed Forces during military activities using a wearable measurement system containing sensorized garments and textile-enabled non-invasive instrumentation. This work describes the multiparametric sensorized garments and measurement instrumentation implemented in the first phase of the project required to evaluate physiological indicators and recording candidates that can be useful for detection of mental stress. For such purpose different sensorized garments have been constructed: a textrode chest-strap system with six repositionable textrodes, a sensorized glove and an upper-arm strap. The implemented textile-enabled instrumentation contains one skin galvanometer, two temperature sensors for skin and environmental temperature and an impedance pneumographer containing a 1-channel ECG amplifier to record cardiogenic biopotentials. With such combinations of garments and non-invasive measurement devices, a multiparametric wearable measurement system has been implemented able to record the following physiological parameters: heart and respiration rate, skin galvanic response, environmental and peripheral temperature. To ensure the proper functioning of the implemented garments and devices the full series of 12 sets have been functionally tested recording cardiogenic biopotential, thoracic impedance, galvanic skin response and temperature values. The experimental results indicate that the implemented wearable measurement systems operate according to the specifications and are ready to be used for mental stress experiments, which will be executed in the coming phases of the project with dozens of healthy volunteers.

Optimization and evaluation of the human fall detection system

NASA Astrophysics Data System (ADS)

Alzoubi, Hadeel; Ramzan, Naeem; Shahriar, Hasan; Alzubi, Raid; Gibson, Ryan; Amira, Abbes

2016-10-01

Falls are the most critical health problem for elderly people, which are often, cause significant injuries. To tackle a serious risk that made by the fall, we develop an automatic wearable fall detection system utilizing two devices (mobile phone and wireless sensor) based on three axes accelerometer signals. The goal of this study is to find an effective machine learning method that distinguish falls from activities of daily living (ADL) using only a single triaxial accelerometer. In addition, comparing the performance results for wearable sensor and mobile device data .The proposed model detects the fall by using seven different classifiers and the significant performance is demonstrated using accuracy, recall, precision and F-measure. Our model obtained accuracy over 99% on wearable device data and over 97% on mobile phone data.

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis.

PubMed

Gao, Wei; Emaminejad, Sam; Nyein, Hnin Yin Yin; Challa, Samyuktha; Chen, Kevin; Peck, Austin; Fahad, Hossain M; Ota, Hiroki; Shiraki, Hiroshi; Kiriya, Daisuke; Lien, Der-Hsien; Brooks, George A; Davis, Ronald W; Javey, Ali

2016-01-28

Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual's state of health. Sampling human sweat, which is rich in physiological information, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications.

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

NASA Astrophysics Data System (ADS)

Gao, Wei; Emaminejad, Sam; Nyein, Hnin Yin Yin; Challa, Samyuktha; Chen, Kevin; Peck, Austin; Fahad, Hossain M.; Ota, Hiroki; Shiraki, Hiroshi; Kiriya, Daisuke; Lien, Der-Hsien; Brooks, George A.; Davis, Ronald W.; Javey, Ali

2016-01-01

Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health. Sampling human sweat, which is rich in physiological information, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications.

A wireless potentiostat for mobile chemical sensing and biosensing.

PubMed

Steinberg, Matthew D; Kassal, Petar; Kereković, Irena; Steinberg, Ivana Murković

2015-10-01

Wireless chemical sensors are used as analytical devices in homeland defence, home-based healthcare, food logistics and more generally for the Sensor Internet of Things (SIoT). Presented here is a battery-powered and highly portable credit-card size potentiostat that is suitable for performing mobile and wearable amperometric electrochemical measurements with seamless wireless data transfer to mobile computing devices. The mobile electrochemical analytical system has been evaluated in the laboratory with a model redox system - the reduction of hexacyanoferrate(III) - and also with commercially available enzymatic blood-glucose test-strips. The potentiostat communicates wirelessly with mobile devices such as tablets or Smartphones by near-field communication (NFC) or with personal computers by radio-frequency identification (RFID), and thus provides a solution to the 'missing link' in connectivity that often exists between low-cost mobile and wearable chemical sensors and ubiquitous mobile computing products. The mobile potentiostat has been evaluated in the laboratory with a set of proof-of-concept experiments, and its analytical performance compared with a commercial laboratory potentiostat (R(2)=0.9999). These first experimental results demonstrate the functionality of the wireless potentiostat and suggest that the device could be suitable for wearable and point-of-sample analytical measurements. We conclude that the wireless potentiostat could contribute significantly to the advancement of mobile chemical sensor research and adoption, in particular for wearable sensors in healthcare and sport physiology, for wound monitoring and in mobile point-of-sample diagnostics as well as more generally as a part of the Sensor Internet of Things. Copyright © 2015 Elsevier B.V. All rights reserved.

Wearable Performance Devices in Sports Medicine.

PubMed

Li, Ryan T; Kling, Scott R; Salata, Michael J; Cupp, Sean A; Sheehan, Joseph; Voos, James E

2016-01-01

Wearable performance devices and sensors are becoming more readily available to the general population and athletic teams. Advances in technology have allowed individual endurance athletes, sports teams, and physicians to monitor functional movements, workloads, and biometric markers to maximize performance and minimize injury. Movement sensors include pedometers, accelerometers/gyroscopes, and global positioning satellite (GPS) devices. Physiologic sensors include heart rate monitors, sleep monitors, temperature sensors, and integrated sensors. The purpose of this review is to familiarize health care professionals and team physicians with the various available types of wearable sensors, discuss their current utilization, and present future applications in sports medicine. Data were obtained from peer-reviewed literature through a search of the PubMed database. Included studies searched development, outcomes, and validation of wearable performance devices such as GPS, accelerometers, and physiologic monitors in sports. Clinical review. Level 4. Wearable sensors provide a method of monitoring real-time physiologic and movement parameters during training and competitive sports. These parameters can be used to detect position-specific patterns in movement, design more efficient sports-specific training programs for performance optimization, and screen for potential causes of injury. More recent advances in movement sensors have improved accuracy in detecting high-acceleration movements during competitive sports. Wearable devices are valuable instruments for the improvement of sports performance. Evidence for use of these devices in professional sports is still limited. Future developments are needed to establish training protocols using data from wearable devices. © 2015 The Author(s).

Wearable Performance Devices in Sports Medicine

PubMed Central

Li, Ryan T.; Kling, Scott R.; Salata, Michael J.; Cupp, Sean A.; Sheehan, Joseph; Voos, James E.

2016-01-01

Context: Wearable performance devices and sensors are becoming more readily available to the general population and athletic teams. Advances in technology have allowed individual endurance athletes, sports teams, and physicians to monitor functional movements, workloads, and biometric markers to maximize performance and minimize injury. Movement sensors include pedometers, accelerometers/gyroscopes, and global positioning satellite (GPS) devices. Physiologic sensors include heart rate monitors, sleep monitors, temperature sensors, and integrated sensors. The purpose of this review is to familiarize health care professionals and team physicians with the various available types of wearable sensors, discuss their current utilization, and present future applications in sports medicine. Evidence Acquisition: Data were obtained from peer-reviewed literature through a search of the PubMed database. Included studies searched development, outcomes, and validation of wearable performance devices such as GPS, accelerometers, and physiologic monitors in sports. Study Design: Clinical review. Level of Evidence: Level 4. Results: Wearable sensors provide a method of monitoring real-time physiologic and movement parameters during training and competitive sports. These parameters can be used to detect position-specific patterns in movement, design more efficient sports-specific training programs for performance optimization, and screen for potential causes of injury. More recent advances in movement sensors have improved accuracy in detecting high-acceleration movements during competitive sports. Conclusion: Wearable devices are valuable instruments for the improvement of sports performance. Evidence for use of these devices in professional sports is still limited. Future developments are needed to establish training protocols using data from wearable devices. PMID:26733594

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.

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

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 Application of Wearable Technology in Surgery: Ensuring the Positive Impact of the Wearable Revolution on Surgical Patients

PubMed Central

Slade Shantz, Jesse Alan; Veillette, Christian J. H.

2014-01-01

Wearable technology has become an important trend in consumer electronics in the past year. The miniaturization and mass production of myriad sensors have made possible the integration of sensors and output devices in wearable platforms. Despite the consumer focus of the wearable revolution some surgical applications are being developed. These fall into augmentative, assistive, and assessment functions and primarily layer onto current surgical workflows. Some challenges to the adoption of wearable technologies are discussed and a conceptual framework for understanding the potential of wearable technology to revolutionize surgical practice are presented. PMID:25593963

Online Phase Detection Using Wearable Sensors for Walking with a Robotic Prosthesis

PubMed Central

Goršič, Maja; Kamnik, Roman; Ambrožič, Luka; Vitiello, Nicola; Lefeber, Dirk; Pasquini, Guido; Munih, Marko

2014-01-01

This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle of detecting transitions between gait phases is based on heuristic threshold rules, dividing a steady-state walking stride into four phases. For the evaluation of the algorithm, experiments with three amputees, walking with the robotic prosthesis and wearable sensors, were performed. Results show a high rate of successful detection for all four phases (the average success rate across all subjects >90%). A comparison of the proposed method to an off-line trained algorithm using hidden Markov models reveals a similar performance achieved without the need for learning dataset acquisition and previous model training. PMID:24521944

Wearable sensor platform and mobile application for use in cognitive behavioral therapy for drug addiction and PTSD.

PubMed

Fletcher, Richard Ribón; Tam, Sharon; Omojola, Olufemi; Redemske, Richard; Kwan, Joyce

2011-01-01

We present a wearable sensor platform designed for monitoring and studying autonomic nervous system (ANS) activity for the purpose of mental health treatment and interventions. The mobile sensor system consists of a sensor band worn on the ankle that continuously monitors electrodermal activity (EDA), 3-axis acceleration, and temperature. A custom-designed ECG heart monitor worn on the chest is also used as an optional part of the system. The EDA signal from the ankle bands provides a measure sympathetic nervous system activity and used to detect arousal events. The optional ECG data can be used to improve the sensor classification algorithm and provide a measure of emotional "valence." Both types of sensor bands contain a Bluetooth radio that enables communication with the patient's mobile phone. When a specific arousal event is detected, the phone automatically presents therapeutic and empathetic messages to the patient in the tradition of Cognitive Behavioral Therapy (CBT). As an example of clinical use, we describe how the system is currently being used in an ongoing study for patients with drug-addiction and post-traumatic stress disorder (PTSD).

Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations

PubMed Central

Kim, Dong Hyun; Lee, Sang Wook; Park, Hyung-Soon

2016-01-01

Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices. PMID:27240364

Personalized biomedical devices & systems for healthcare applications

NASA Astrophysics Data System (ADS)

Chen, I.-Ming; Phee, Soo Jay; Luo, Zhiqiang; Lim, Chee Kian

2011-03-01

With the advancement in micro- and nanotechnology, electromechanical components and systems are getting smaller and smaller and gradually can be applied to the human as portable, mobile and even wearable devices. Healthcare industry have started to benefit from this technology trend by providing more and more miniature biomedical devices for personalized medical treatments in order to obtain better and more accurate outcome. This article introduces some recent development in non-intrusive and intrusive biomedical devices resulted from the advancement of niche miniature sensors and actuators, namely, wearable biomedical sensors, wearable haptic devices, and ingestible medical capsules. The development of these devices requires carful integration of knowledge and people from many different disciplines like medicine, electronics, mechanics, and design. Furthermore, designing affordable devices and systems to benefit all mankind is a great challenge ahead. The multi-disciplinary nature of the R&D effort in this area provides a new perspective for the future mechanical engineers.

Bioimpedance-Based Wearable Measurement Instrumentation for Studying the Autonomic Nerve System Response to Stressful Working Conditions

NASA Astrophysics Data System (ADS)

Ferreira, J.; Álvarez, L.; Buendía, R.; Ayllón, D.; Llerena, C.; Gil-Pita, R.; Seoane, F.

2013-04-01

The assessment of mental stress on workers under hard and stressful conditions is critical to identify which workers are not ready to undertake a mission that might put in risk their own life and the life of others. The ATREC project aims to enable Real Time Assessment of Mental Stress of the Spanish Armed Forces during military activities. Integrating sensors with garments and using wearable measurement devices, the following physiological measurements were recorded: heart and respiration rate, skin galvanic response as well as peripheral temperature. The measuring garments are the following: a sensorized glove, an upper-arm strap and a repositionable textrode chest strap system with 6 textrodes. The implemented textile-enabled instrumentation contains: one skin galvanometer, two temperature sensors, for skin and environmental, and an Impedance Cardiographer/Pneumographer containing a 1 channel ECG amplifier to record cardiogenic biopotentials. The implemented wearable systems operated accordingly to the specifications and are ready to be used for the mental stress experiments that will be executed in the coming phases of the project in healthy volunteers.

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.

The challenges facing wearable sensor systems.

PubMed

McAdams, Eric; Gehin, Claudine; Massot, Bertrand; McLaughlin, James

2012-01-01

It has been pointed out that, in spite of significant national and international funding programmes, there is a dearth of successfully commercialised wearable monitoring systems. Although problems such as financial reimbursement, device interoperability and the present lack of the required connected healthcare infrastructure are major hurdles to the provision of remote clinical monitoring of home-based patients, the "Mount Everest" of monitoring applications, why are wearable systems not already commercialised and used in less demanding applications? The numerous wearable systems which appear on the Web and even in the literature are, for the most part, basic prototypes unsuited to the demands of real-life applications. SMEs which do seek to commercialise clinically promising systems are unfortunately faced with many challenges and few as yet have survived long enough to successfully commercialise their innovations.

Estimation of Center of Mass Trajectory using Wearable Sensors during Golf Swing

PubMed Central

Najafi, Bijan; Lee-Eng, Jacqueline; Wrobel, James S.; Goebel, Ruben

2015-01-01

This study suggests a wearable sensor technology to estimate center of mass (CoM) trajectory during a golf swing. Groups of 3, 4, and 18 participants were recruited, respectively, for the purpose of three validation studies. Study 1 examined the accuracy of the system to estimate a 3D body segment angle compared to a camera-based motion analyzer (Vicon®). Study 2 assessed the accuracy of three simplified CoM trajectory models. Finally, Study 3 assessed the accuracy of the proposed CoM model during multiple golf swings. A relatively high agreement was observed between wearable sensors and the reference (Vicon®) for angle measurement (r > 0.99, random error <1.2° (1.5%) for anterior-posterior; <0.9° (2%) for medial-lateral; and <3.6° (2.5%) for internal-external direction). The two-link model yielded a better agreement with the reference system compared to one-link model (r > 0.93 v. r = 0.52, respectively). On the same note, the proposed two-link model estimated CoM trajectory during golf swing with relatively good accuracy (r > 0.9, A-P random error <1cm (7.7%) and <2cm (10.4%) for M-L). The proposed system appears to accurately quantify the kinematics of CoM trajectory as a surrogate of dynamic postural control during an athlete’s movement and its portability, makes it feasible to fit the competitive environment without restricting surface type. Key points This study demonstrates that wearable technology based on inertial sensors are accurate to estimate center of mass trajectory in complex athletic task (e.g., golf swing) This study suggests that two-link model of human body provides optimum tradeoff between accuracy and minimum number of sensor module for estimation of center of mass trajectory in particular during fast movements. Wearable technologies based on inertial sensors are viable option for assessing dynamic postural control in complex task outside of gait laboratory and constraints of cameras, surface, and base of support. PMID:25983585

Wearable Wireless Sensor for Multi-Scale Physiological Monitoring

DTIC Science & Technology

2013-10-01

AD_________________ Award Number: W81XWH-12-1-0541 TITLE: Wearable Wireless Sensor for Multi-Scale...TYPE Annual 3. DATES COVERED 25 12- 13 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Wearable Wireless Sensor for Multi-Scale Physiological...peripheral management • Procedures for low power mode activation and wake - up • Routines for start- up state detection • Flash memory management

Implementation study of wearable sensors for activity recognition systems

PubMed Central

Ghassemian, Mona

2015-01-01

This Letter investigates and reports on a number of activity recognition methods for a wearable sensor system. The authors apply three methods for data transmission, namely ‘stream-based’, ‘feature-based’ and ‘threshold-based’ scenarios to study the accuracy against energy efficiency of transmission and processing power that affects the mote's battery lifetime. They also report on the impact of variation of sampling frequency and data transmission rate on energy consumption of motes for each method. This study leads us to propose a cross-layer optimisation of an activity recognition system for provisioning acceptable levels of accuracy and energy efficiency. PMID:26609413

A Systematic Review of Wearable Patient Monitoring Systems - Current Challenges and Opportunities for Clinical Adoption.

PubMed

Baig, Mirza Mansoor; GholamHosseini, Hamid; Moqeem, Aasia A; Mirza, Farhaan; Lindén, Maria

2017-07-01

The aim of this review is to investigate barriers and challenges of wearable patient monitoring (WPM) solutions adopted by clinicians in acute, as well as in community, care settings. Currently, healthcare providers are coping with ever-growing healthcare challenges including an ageing population, chronic diseases, the cost of hospitalization, and the risk of medical errors. WPM systems are a potential solution for addressing some of these challenges by enabling advanced sensors, wearable technology, and secure and effective communication platforms between the clinicians and patients. A total of 791 articles were screened and 20 were selected for this review. The most common publication venue was conference proceedings (13, 54%). This review only considered recent studies published between 2015 and 2017. The identified studies involved chronic conditions (6, 30%), rehabilitation (7, 35%), cardiovascular diseases (4, 20%), falls (2, 10%) and mental health (1, 5%). Most studies focussed on the system aspects of WPM solutions including advanced sensors, wireless data collection, communication platform and clinical usability based on a specific area or disease. The current studies are progressing with localized sensor-software integration to solve a specific use-case/health area using non-scalable and 'silo' solutions. There is further work required regarding interoperability and clinical acceptance challenges. The advancement of wearable technology and possibilities of using machine learning and artificial intelligence in healthcare is a concept that has been investigated by many studies. We believe future patient monitoring and medical treatments will build upon efficient and affordable solutions of wearable technology.

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.

A low-power multi-modal body sensor network with application to epileptic seizure monitoring.

PubMed

Altini, Marco; Del Din, Silvia; Patel, Shyamal; Schachter, Steven; Penders, Julien; Bonato, Paolo

2011-01-01

Monitoring patients' physiological signals during their daily activities in the home environment is one of the challenge of the health care. New ultra-low-power wireless technologies could help to achieve this goal. In this paper we present a low-power, multi-modal, wearable sensor platform for the simultaneous recording of activity and physiological data. First we provide a description of the wearable sensor platform, and its characteristics with respect to power consumption. Second we present the preliminary results of the comparison between our sensors and a reference system, on healthy subjects, to test the reliability of the detected physiological (electrocardiogram and respiration) and electromyography signals.

3D Printed Stretchable Tactile Sensors.

PubMed

Guo, Shuang-Zhuang; Qiu, Kaiyan; Meng, Fanben; Park, Sung Hyun; McAlpine, Michael C

2017-07-01

The development of methods for the 3D printing of multifunctional devices could impact areas ranging from wearable electronics and energy harvesting devices to smart prosthetics and human-machine interfaces. Recently, the development of stretchable electronic devices has accelerated, concomitant with advances in functional materials and fabrication processes. In particular, novel strategies have been developed to enable the intimate biointegration of wearable electronic devices with human skin in ways that bypass the mechanical and thermal restrictions of traditional microfabrication technologies. Here, a multimaterial, multiscale, and multifunctional 3D printing approach is employed to fabricate 3D tactile sensors under ambient conditions conformally onto freeform surfaces. The customized sensor is demonstrated with the capabilities of detecting and differentiating human movements, including pulse monitoring and finger motions. The custom 3D printing of functional materials and devices opens new routes for the biointegration of various sensors in wearable electronics systems, and toward advanced bionic skin applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Development of a belt-type wearable sensor system with multi-function for home health care

NASA Astrophysics Data System (ADS)

Ban, Yunho; Choi, Samjin; Jiang, Zhongwei; Park, Chanwon

2005-12-01

Some reports show that the physiological information measured in hospital is not enough without the one measured in home. The physiological information monitored in home, therefore, is strongly required recently. The goal of this research is to develop a wearable and tractable sensor system for detecting biomedical signals such as cardiac rhythm, respiration, body movement, and percentage of body fat (%BF) and for home health care. A belt type sensor for this purpose is developed, which consists of sensing materials of PVDF film and conductive fabrics. Also several data processing techniques, such as the discrete wavelet transform, cross correlation and adaptive filtering method, were introduced to eliminate noises and base wandering and to extract the specified components. The ECG and respiration signals obtained by the proposed belt type sensor system gave good agreements with commercial medical system. Furthermore, the body fat (%BF) measurement based on the four-electrode BIA was also built in the belt sensor. The body fat was calculated by measuring the body impedance from the belt type sensor and compared with the predicted %BF measured by the commercial adipometer (TBF-607). The results validated also the efficiency of the belt type sensor system.

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.

Unintended Consequences of Wearable Sensor Use in Healthcare

PubMed Central

McCaldin, D.; Wang, K.; Schreier, G.; Lovell, N. H.; Marschollek, M.; Redmond, S. J.

2016-01-01

Summary Objectives As wearable sensors take the consumer market by storm, and medical device manufacturers move to make their devices wireless and appropriate for ambulatory use, this revolution brings with it some unintended consequences, which we aim to discuss in this paper. Methods We discuss some important unintended consequences, both beneficial and unwanted, which relate to: modifications of behavior; creation and use of big data sets; new security vulnerabilities; and unforeseen challenges faced by regulatory authorities, struggling to keep pace with recent innovations. Where possible, we proposed potential solutions to unwanted consequences. Results Intelligent and inclusive design processes may mitigate unintended modifications in behavior. For big data, legislating access to and use of these data will be a legal and political challenge in the years ahead, as we trade the health benefits of wearable sensors against the risk to our privacy. The wireless and personal nature of wearable sensors also exposes them to a number of unique security vulnerabilities. Regulation plays an important role in managing these security risks, but also has the dual responsibility of ensuring that wearable devices are fit for purpose. However, the burden of validating the function and security of medical devices is becoming infeasible for regulators, given the many software apps and wearable sensors entering the market each year, which are only a subset of an even larger ‘internet of things’. Conclusion Wearable sensors may serve to improve wellbeing, but we must be vigilant against the occurrence of unintended consequences. With collaboration between device manufacturers, regulators, and end-users, we balance the risk of unintended consequences occurring against the incredible benefit that wearable sensors promise to bring to the world. PMID:27830234

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

PubMed Central

Nyein, Hnin Yin Yin; Challa, Samyuktha; Chen, Kevin; Peck, Austin; Fahad, Hossain M.; Ota, Hiroki; Shiraki, Hiroshi; Kiriya, Daisuke; Lien, Der-Hsien; Brooks, George A.; Davis, Ronald W.; Javey, Ali

2016-01-01

Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual's state of health1–12. Sampling human sweat, which is rich in physiological information13, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state14–18. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications. PMID:26819044

A web-based system for home monitoring of patients with Parkinson's disease using wearable sensors.

PubMed

Chen, Bor-Rong; Patel, Shyamal; Buckley, Thomas; Rednic, Ramona; McClure, Douglas J; Shih, Ludy; Tarsy, Daniel; Welsh, Matt; Bonato, Paolo

2011-03-01

This letter introduces MercuryLive, a platform to enable home monitoring of patients with Parkinson's disease (PD) using wearable sensors. MercuryLive contains three tiers: a resource-aware data collection engine that relies upon wearable sensors, web services for live streaming and storage of sensor data, and a web-based graphical user interface client with video conferencing capability. Besides, the platform has the capability of analyzing sensor (i.e., accelerometer) data to reliably estimate clinical scores capturing the severity of tremor, bradykinesia, and dyskinesia. Testing results showed an average data latency of less than 400 ms and video latency of about 200 ms with video frame rate of about 13 frames/s when 800 kb/s of bandwidth were available and we used a 40% video compression, and data feature upload requiring 1 min of extra time following a 10 min interactive session. These results indicate that the proposed platform is suitable to monitor patients with PD to facilitate the titration of medications in the late stages of the disease.

A battery-less and wireless wearable sensor system for identifying bed and chair exits in a pilot trial in hospitalized older people.

PubMed

Shinmoto Torres, Roberto L; Visvanathan, Renuka; Abbott, Derek; Hill, Keith D; Ranasinghe, Damith C

2017-01-01

Falls in hospitals are common, therefore strategies to minimize the impact of these events in older patients and needs to be examined. In this pilot study, we investigate a movement monitoring sensor system for identifying bed and chair exits using a wireless wearable sensor worn by hospitalized older patients. We developed a movement monitoring sensor system that recognizes bed and chair exits. The system consists of a machine learning based activity classifier and a bed and chair exit recognition process based on an activity score function. Twenty-six patients, aged 71 to 93 years old, hospitalized in the Geriatric Evaluation and Management Unit participated in the supervised trials. They wore over their attire a battery-less, lightweight and wireless sensor and performed scripted activities such as getting off the bed and chair. We investigated the system performance in recognizing bed and chair exits in hospital rooms where RFID antennas and readers were in place. The system's acceptability was measured using two surveys with 0-10 likert scales. The first survey measured the change in user perception of the system before and after a trial; the second survey, conducted only at the end of each trial, measured user acceptance of the system based on a multifactor sensor acceptance model. The performance of the system indicated an overall recall of 81.4%, precision of 66.8% and F-score of 72.4% for joint bed and chair exit recognition. Patients demonstrated improved perception of the system after use with overall score change from 7.8 to 9.0 and high acceptance of the system with score ≥ 6.7 for all acceptance factors. The present pilot study suggests the use of wireless wearable sensors is feasible for detecting bed and chair exits in a hospital environment.

A Triple-Mode Flexible E-Skin Sensor Interface for Multi-Purpose Wearable Applications

PubMed Central

Kim, Sung-Woo; Lee, Youngoh; Park, Jonghwa; Kim, Seungmok; Chae, Heeyoung; Ko, Hyunhyub

2017-01-01

This study presents a flexible wireless electronic skin (e-skin) sensor system that includes a multi-functional sensor device, a triple-mode reconfigurable readout integrated circuit (ROIC), and a mobile monitoring interface. The e-skin device’s multi-functionality is achieved by an interlocked micro-dome array structure that uses a polyvinylidene fluoride and reduced graphene oxide (PVDF/RGO) composite material that is inspired by the structure and functions of the human fingertip. For multi-functional implementation, the proposed triple-mode ROIC is reconfigured to support piezoelectric, piezoresistance, and pyroelectric interfaces through single-type e-skin sensor devices. A flexible system prototype was developed and experimentally verified to provide various wireless wearable sensing functions—including pulse wave, voice, chewing/swallowing, breathing, knee movements, and temperature—while their real-time sensed data are displayed on a smartphone. PMID:29286312

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.

Wearable system-on-a-chip UWB radar for health care and its application to the safety improvement of emergency operators.

PubMed

Zito, Domenico; Pepe, Domenico; Neri, Bruno; De Rossi, Danilo; Lanatà, Antonio; Tognetti, Alessandro; Scilingo, Enzo Pasquale

2007-01-01

A new wearable system-on-a-chip UWB radar for health care systems is presented. The idea and its applications to the safety improvement of emergency operators are discussed. The system consists of a wearable wireless interface including a fully integrated UWB radar for the detection of the heart beat and breath rates, and a IEEE 802.15.4 ZigBee radio interface. The principle of operation of the UWB radar for the monitoring of the heart wall is explained hereinafter. The results obtained by the feasibility study regarding its implementation on a modern standard silicon technology (CMOS 90 nm) are reported, demonstrating (at simulation level) the effectiveness of such an approach and enabling the standard silicon technology for new generations of wireless sensors for heath care and safeguard wearable systems.

A battery-less and wireless wearable sensor system for identifying bed and chair exits in a pilot trial in hospitalized older people

PubMed Central

Visvanathan, Renuka; Abbott, Derek; Hill, Keith D.; Ranasinghe, Damith C.

2017-01-01

Falls in hospitals are common, therefore strategies to minimize the impact of these events in older patients and needs to be examined. In this pilot study, we investigate a movement monitoring sensor system for identifying bed and chair exits using a wireless wearable sensor worn by hospitalized older patients. We developed a movement monitoring sensor system that recognizes bed and chair exits. The system consists of a machine learning based activity classifier and a bed and chair exit recognition process based on an activity score function. Twenty-six patients, aged 71 to 93 years old, hospitalized in the Geriatric Evaluation and Management Unit participated in the supervised trials. They wore over their attire a battery-less, lightweight and wireless sensor and performed scripted activities such as getting off the bed and chair. We investigated the system performance in recognizing bed and chair exits in hospital rooms where RFID antennas and readers were in place. The system’s acceptability was measured using two surveys with 0–10 likert scales. The first survey measured the change in user perception of the system before and after a trial; the second survey, conducted only at the end of each trial, measured user acceptance of the system based on a multifactor sensor acceptance model. The performance of the system indicated an overall recall of 81.4%, precision of 66.8% and F-score of 72.4% for joint bed and chair exit recognition. Patients demonstrated improved perception of the system after use with overall score change from 7.8 to 9.0 and high acceptance of the system with score ≥ 6.7 for all acceptance factors. The present pilot study suggests the use of wireless wearable sensors is feasible for detecting bed and chair exits in a hospital environment. PMID:29016696

Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems

PubMed Central

Wan, Liangtian; Han, Guangjie; Wang, Hao; Shu, Lei; Feng, Nanxing; Peng, Bao

2016-01-01

In health monitoring systems, the base station (BS) and the wearable sensors communicate with each other to construct a virtual multiple input and multiple output (VMIMO) system. In real applications, the signal that the BS received is a distributed source because of the scattering, reflection, diffraction and refraction in the propagation path. In this paper, a 2D direction-of-arrival (DOA) estimation algorithm for incoherently-distributed (ID) and coherently-distributed (CD) sources is proposed based on multiple VMIMO systems. ID and CD sources are separated through the second-order blind identification (SOBI) algorithm. The traditional estimating signal parameters via the rotational invariance technique (ESPRIT)-based algorithm is valid only for one-dimensional (1D) DOA estimation for the ID source. By constructing the signal subspace, two rotational invariant relationships are constructed. Then, we extend the ESPRIT to estimate 2D DOAs for ID sources. For DOA estimation of CD sources, two rational invariance relationships are constructed based on the application of generalized steering vectors (GSVs). Then, the ESPRIT-based algorithm is used for estimating the eigenvalues of two rational invariance matrices, which contain the angular parameters. The expressions of azimuth and elevation for ID and CD sources have closed forms, which means that the spectrum peak searching is avoided. Therefore, compared to the traditional 2D DOA estimation algorithms, the proposed algorithm imposes significantly low computational complexity. The intersecting point of two rays, which come from two different directions measured by two uniform rectangle arrays (URA), can be regarded as the location of the biosensor (wearable sensor). Three BSs adopting the smart antenna (SA) technique cooperate with each other to locate the wearable sensors using the angulation positioning method. Simulation results demonstrate the effectiveness of the proposed algorithm. PMID:26985896

Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems.

PubMed

Wan, Liangtian; Han, Guangjie; Wang, Hao; Shu, Lei; Feng, Nanxing; Peng, Bao

2016-03-12

In health monitoring systems, the base station (BS) and the wearable sensors communicate with each other to construct a virtual multiple input and multiple output (VMIMO) system. In real applications, the signal that the BS received is a distributed source because of the scattering, reflection, diffraction and refraction in the propagation path. In this paper, a 2D direction-of-arrival (DOA) estimation algorithm for incoherently-distributed (ID) and coherently-distributed (CD) sources is proposed based on multiple VMIMO systems. ID and CD sources are separated through the second-order blind identification (SOBI) algorithm. The traditional estimating signal parameters via the rotational invariance technique (ESPRIT)-based algorithm is valid only for one-dimensional (1D) DOA estimation for the ID source. By constructing the signal subspace, two rotational invariant relationships are constructed. Then, we extend the ESPRIT to estimate 2D DOAs for ID sources. For DOA estimation of CD sources, two rational invariance relationships are constructed based on the application of generalized steering vectors (GSVs). Then, the ESPRIT-based algorithm is used for estimating the eigenvalues of two rational invariance matrices, which contain the angular parameters. The expressions of azimuth and elevation for ID and CD sources have closed forms, which means that the spectrum peak searching is avoided. Therefore, compared to the traditional 2D DOA estimation algorithms, the proposed algorithm imposes significantly low computational complexity. The intersecting point of two rays, which come from two different directions measured by two uniform rectangle arrays (URA), can be regarded as the location of the biosensor (wearable sensor). Three BSs adopting the smart antenna (SA) technique cooperate with each other to locate the wearable sensors using the angulation positioning method. Simulation results demonstrate the effectiveness of the proposed algorithm.

Assessing physical activity using wearable monitors: measures of physical activity.

PubMed

Butte, Nancy F; Ekelund, Ulf; Westerterp, Klaas R

2012-01-01

Physical activity may be defined broadly as "all bodily actions produced by the contraction of skeletal muscle that increase energy expenditure above basal level." Physical activity is a complex construct that can be classified into major categories qualitatively, quantitatively, or contextually. The quantitative assessment of physical activity using wearable monitors is grounded in the measurement of energy expenditure. Six main categories of wearable monitors are currently available to investigators: pedometers, load transducers/foot-contact monitors, accelerometers, HR monitors, combined accelerometer and HR monitors, and multiple sensor systems. Currently available monitors are capable of measuring total physical activity as well as components of physical activity that play important roles in human health. The selection of wearable monitors for measuring physical activity will depend on the physical activity component of interest, study objectives, characteristics of the target population, and study feasibility in terms of cost and logistics. Future development of sensors and analytical techniques for assessing physical activity should focus on the dynamic ranges of sensors, comparability for sensor output across manufacturers, and the application of advanced modeling techniques to predict energy expenditure and classify physical activities. New approaches for qualitatively classifying physical activity should be validated using direct observation or recording. New sensors and methods for quantitatively assessing physical activity should be validated in laboratory and free-living populations using criterion methods of calorimetry or doubly labeled water.

Wearable sensors: modalities, challenges, and prospects.

PubMed

Heikenfeld, J; Jajack, A; Rogers, J; Gutruf, P; Tian, L; Pan, T; Li, R; Khine, M; Kim, J; Wang, J; Kim, J

2018-01-16

Wearable sensors have recently seen a large increase in both research and commercialization. However, success in wearable sensors has been a mix of both progress and setbacks. Most of commercial progress has been in smart adaptation of existing mechanical, electrical and optical methods of measuring the body. This adaptation has involved innovations in how to miniaturize sensing technologies, how to make them conformal and flexible, and in the development of companion software that increases the value of the measured data. However, chemical sensing modalities have experienced greater challenges in commercial adoption, especially for non-invasive chemical sensors. There have also been significant challenges in making significant fundamental improvements to existing mechanical, electrical, and optical sensing modalities, especially in improving their specificity of detection. Many of these challenges can be understood by appreciating the body's surface (skin) as more of an information barrier than as an information source. With a deeper understanding of the fundamental challenges faced for wearable sensors and of the state-of-the-art for wearable sensor technology, the roadmap becomes clearer for creating the next generation of innovations and breakthroughs.

Predicting Functional Independence Measure Scores During Rehabilitation with Wearable Inertial Sensors

PubMed Central

Sprint, Gina; Cook, Diane J.; Weeks, Douglas L.; Borisov, Vladimir

2016-01-01

Evaluating patient progress and making discharge decisions regarding inpatient medical rehabilitation rely upon standard clinical assessments administered by trained clinicians. Wearable inertial sensors can offer more objective measures of patient movement and progress. We undertook a study to investigate the contribution of wearable sensor data to predict discharge functional independence measure (FIM) scores for 20 patients at an inpatient rehabilitation facility. The FIM utilizes a 7-point ordinal scale to measure patient independence while performing several activities of daily living, such as walking, grooming, and bathing. Wearable inertial sensor data were collected from ecological ambulatory tasks at two time points mid-stay during inpatient rehabilitation. Machine learning algorithms were trained with sensor-derived features and clinical information obtained from medical records at admission to the inpatient facility. While models trained only with clinical features predicted discharge scores well, we were able to achieve an even higher level of prediction accuracy when also including the wearable sensor-derived features. Correlations as high as 0.97 for leave-one-out cross validation predicting discharge FIM motor scores are reported. PMID:27054054

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

Development of a Wearable Cardiac Monitoring System for Behavioral Neurocardiac Training: A Usability Study.

PubMed

Uddin, Akib A; Morita, Plinio P; Tallevi, Kevin; Armour, Kevin; Li, John; Nolan, Robert P; Cafazzo, Joseph A

2016-04-22

Elevated blood pressure is one of the main risk factors for death globally. Behavioral neurocardiac training (BNT) is a complementary approach to blood pressure and stress management that is intended to exercise the autonomic reflexes, improve stress recovery, and lower blood pressure. BNT involves cognitive-behavioral therapy with a paced breathing technique and heart rate variability biofeedback. BNT is limited to in-clinic delivery and faces an accessibility barrier because of the need for clinical oversight and the use of complex monitoring tools. The objective of this project was to design, develop, and evaluate a wearable electrocardiographic (ECG) sensor system for the delivery of BNT in a home setting. The wearable sensor system, Beat, consists of an ECG sensor and a mobile app. It was developed iteratively using the principles of test-driven Agile development and user-centered design. A usability study was conducted at Toronto General Hospital to evaluate feasibility and user experience and identify areas of improvement. The Beat sensor was designed as a modular patch to be worn on the user's chest and uses standard ECG electrodes. It streams a single-lead ECG wirelessly to a mobile phone using Bluetooth Low Energy. The use of small, low-power electronics, a low device profile, and a tapered enclosure allowed for a device that can be unobtrusively worn under clothing. The sensor was designed to operate with a mobile app that guides users through the BNT exercises to train them to a slow-paced breathing technique for stress recovery. The BNT app uses the ECG captured by the sensor to provide heart rate variability biofeedback in the form of a real-time heart rate waveform to complement and reinforce the impact of the training. Usability testing (n=6) indicated that the overall response to the design and user experience of the system was perceived positively. All participants indicated that the system had a positive effect on stress management and that they would use it at home. Areas of improvement were identified, which focused primarily on the delivery of training and education on BNT through the app. The outcome of this project was a wearable sensor system to deliver BNT at home. The system has the potential to offer a complementary approach to blood pressure and stress management at home and reduce current accessibility barriers.

Wearable physiological sensors and real-time algorithms for detection of acute mountain sickness.

PubMed

Muza, Stephen R

2018-03-01

This is a minireview of potential wearable physiological sensors and algorithms (process and equations) for detection of acute mountain sickness (AMS). Given the emerging status of this effort, the focus of the review is on the current clinical assessment of AMS, known risk factors (environmental, demographic, and physiological), and current understanding of AMS pathophysiology. Studies that have examined a range of physiological variables to develop AMS prediction and/or detection algorithms are reviewed to provide insight and potential technological roadmaps for future development of real-time physiological sensors and algorithms to detect AMS. Given the lack of signs and nonspecific symptoms associated with AMS, development of wearable physiological sensors and embedded algorithms to predict in the near term or detect established AMS will be challenging. Prior work using [Formula: see text], HR, or HRv has not provided the sensitivity and specificity for useful application to predict or detect AMS. Rather than using spot checks as most prior studies have, wearable systems that continuously measure SpO 2 and HR are commercially available. Employing other statistical modeling approaches such as general linear and logistic mixed models or time series analysis to these continuously measured variables is the most promising approach for developing algorithms that are sensitive and specific for physiological prediction or detection of AMS.

Business model design for a wearable biofeedback system.

PubMed

Hidefjäll, Patrik; Titkova, Dina

2015-01-01

Wearable sensor technologies used to track daily activities have become successful in the consumer market. In order for wearable sensor technology to offer added value in the more challenging areas of stress-rehab care and occupational health stress-related biofeedback parameters need to be monitored and more elaborate business models are needed. To identify probable success factors for a wearable biofeedback system (Affective Health) in the two mentioned market segments in a Swedish setting, we conducted literature studies and interviews with relevant representatives. Data were collected and used first to describe the two market segments and then to define likely feasible business model designs, according to the Business Model Canvas framework. Needs of stakeholders were identified as inputs to business model design. Value propositions, a key building block of a business model, were defined for each segment. The value proposition for occupational health was defined as "A tool that can both identify employees at risk of stress-related disorders and reinforce healthy sustainable behavior" and for healthcare as: "Providing therapists with objective data about the patient's emotional state and motivating patients to better engage in the treatment process".

Wearable flex sensor system for multiple badminton player grip identification

NASA Astrophysics Data System (ADS)

Jacob, Alvin; Zakaria, Wan Nurshazwani Wan; Tomari, Mohd Razali Bin Md; Sek, Tee Kian; Suberi, Anis Azwani Muhd

2017-09-01

This paper focuses on the development of a wearable sensor system to identify the different types of badminton grip that is used by a player during training. Badminton movements and strokes are fast and dynamic, where most of the involved movement are difficult to identify with the naked eye. Also, the usage of high processing optometric motion capture system is expensive and causes computational burden. Therefore, this paper suggests the development of a sensorized glove using flex sensor to measure a badminton player's finger flexion angle. The proposed Hand Monitoring Module (HMM) is connected to a personal computer through Bluetooth to enable wireless data transmission. The usability and feasibility of the HMM to identify different grip types were examined through a series of experiments, where the system exhibited 70% detection ability for the five different grip type. The outcome plays a major role in training players to use the proper grips for a badminton stroke to achieve a more powerful and accurate stroke execution.

An arm wearable haptic interface for impact sensing on unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Choi, Yunshil; Hong, Seung-Chan; Lee, Jung-Ryul

2017-04-01

In this paper, an impact monitoring system using fiber Bragg grating (FBG) sensors and vibro-haptic actuators has been introduced. The system is suggested for structural health monitoring (SHM) for unmanned aerial vehicles (UAVs), by making a decision with human-robot interaction. The system is composed with two major subsystems; an on-board system equipped on UAV and an arm-wearable interface for ground pilot. The on-board system acquires impact-induced wavelength changes and performs localization process, which was developed based on arrival time calculation. The arm-wearable interface helps ground pilots to make decision about impact location themselves by stimulating their tactile-sense with motor vibration.

A Printed Organic Circuit System for Wearable Amperometric Electrochemical Sensors.

PubMed

Shiwaku, Rei; Matsui, Hiroyuki; Nagamine, Kuniaki; Uematsu, Mayu; Mano, Taisei; Maruyama, Yuki; Nomura, Ayako; Tsuchiya, Kazuhiko; Hayasaka, Kazuma; Takeda, Yasunori; Fukuda, Takashi; Kumaki, Daisuke; Tokito, Shizuo

2018-04-23

Wearable sensor device technologies, which enable continuous monitoring of biological information from the human body, are promising in the fields of sports, healthcare, and medical applications. Further thinness, light weight, flexibility and low-cost are significant requirements for making the devices attachable onto human tissues or clothes like a patch. Here we demonstrate a flexible and printed circuit system consisting of an enzyme-based amperometric sensor, feedback control and amplification circuits based on organic thin-film transistors. The feedback control and amplification circuits based on pseudo-CMOS inverters were successfuly integrated by printing methods on a plastic film. This simple system worked very well like a potentiostat for electrochemical measurements, and enabled the quantitative and real-time measurement of lactate concentration with high sensitivity of 1 V/mM and a short response time of a hundred seconds.

Wearable Sensors for Remote Health Monitoring.

PubMed

Majumder, Sumit; Mondal, Tapas; Deen, M Jamal

2017-01-12

Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

Wearable Sensors for Remote Health Monitoring

PubMed Central

Majumder, Sumit; Mondal, Tapas; Deen, M. Jamal

2017-01-01

Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed. PMID:28085085

A Framework for Learning Analytics Using Commodity Wearable Devices

PubMed Central

Lu, Yu; Zhang, Sen; Zhang, Zhiqiang; Xiao, Wendong; Yu, Shengquan

2017-01-01

We advocate for and introduce LEARNSense, a framework for learning analytics using commodity wearable devices to capture learner’s physical actions and accordingly infer learner context (e.g., student activities and engagement status in class). Our work is motivated by the observations that: (a) the fine-grained individual-specific learner actions are crucial to understand learners and their context information; (b) sensor data available on the latest wearable devices (e.g., wrist-worn and eye wear devices) can effectively recognize learner actions and help to infer learner context information; (c) the commodity wearable devices that are widely available on the market can provide a hassle-free and non-intrusive solution. Following the above observations and under the proposed framework, we design and implement a sensor-based learner context collector running on the wearable devices. The latest data mining and sensor data processing techniques are employed to detect different types of learner actions and context information. Furthermore, we detail all of the above efforts by offering a novel and exemplary use case: it successfully provides the accurate detection of student actions and infers the student engagement states in class. The specifically designed learner context collector has been implemented on the commodity wrist-worn device. Based on the collected and inferred learner information, the novel intervention and incentivizing feedback are introduced into the system service. Finally, a comprehensive evaluation with the real-world experiments, surveys and interviews demonstrates the effectiveness and impact of the proposed framework and this use case. The F1 score for the student action classification tasks achieve 0.9, and the system can effectively differentiate the defined three learner states. Finally, the survey results show that the learners are satisfied with the use of our system (mean score of 3.7 with a standard deviation of 0.55). PMID:28613236

A Framework for Learning Analytics Using Commodity Wearable Devices.

PubMed

Lu, Yu; Zhang, Sen; Zhang, Zhiqiang; Xiao, Wendong; Yu, Shengquan

2017-06-14

We advocate for and introduce LEARNSense, a framework for learning analytics using commodity wearable devices to capture learner's physical actions and accordingly infer learner context (e.g., student activities and engagement status in class). Our work is motivated by the observations that: (a) the fine-grained individual-specific learner actions are crucial to understand learners and their context information; (b) sensor data available on the latest wearable devices (e.g., wrist-worn and eye wear devices) can effectively recognize learner actions and help to infer learner context information; (c) the commodity wearable devices that are widely available on the market can provide a hassle-free and non-intrusive solution. Following the above observations and under the proposed framework, we design and implement a sensor-based learner context collector running on the wearable devices. The latest data mining and sensor data processing techniques are employed to detect different types of learner actions and context information. Furthermore, we detail all of the above efforts by offering a novel and exemplary use case: it successfully provides the accurate detection of student actions and infers the student engagement states in class. The specifically designed learner context collector has been implemented on the commodity wrist-worn device. Based on the collected and inferred learner information, the novel intervention and incentivizing feedback are introduced into the system service. Finally, a comprehensive evaluation with the real-world experiments, surveys and interviews demonstrates the effectiveness and impact of the proposed framework and this use case. The F1 score for the student action classification tasks achieve 0.9, and the system can effectively differentiate the defined three learner states. Finally, the survey results show that the learners are satisfied with the use of our system (mean score of 3.7 with a standard deviation of 0.55).

Respiratory rate detection using a wearable electromagnetic generator.

PubMed

Padasdao, Bryson; Boric-Lubecke, Olga

2011-01-01

Wearable health and fitness monitoring systems are a promising new way of collecting physiological data without inconveniencing patients. Human energy harvesting may be used to power wearable sensors. In this paper, we explore this zero-net energy biosensor concept through sensing and harvesting of respiratory effort. An off the shelf servo motor operation in reverse was used to successfully obtain respiratory rate, while also demonstrating significant harvested power. These are the first reported respiratory rate sensing results using electromagnetic generators.

Indoor localization using pedestrian dead reckoning updated with RFID-based fiducials.

PubMed

House, Samuel; Connell, Sean; Milligan, Ian; Austin, Daniel; Hayes, Tamara L; Chiang, Patrick

2011-01-01

We describe a low-cost wearable system that tracks the location of individuals indoors using commonly available inertial navigation sensors fused with radio frequency identification (RFID) tags placed around the smart environment. While conventional pedestrian dead reckoning (PDR) calculated with an inertial measurement unit (IMU) is susceptible to sensor drift inaccuracies, the proposed wearable prototype fuses the drift-sensitive IMU with a RFID tag reader. Passive RFID tags placed throughout the smart-building then act as fiducial markers that update the physical locations of each user, thereby correcting positional errors and sensor inaccuracy. Experimental measurements taken for a 55 m × 20 m 2D floor space indicate an over 1200% improvement in average error rate of the proposed RFID-fused system over dead reckoning alone.

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.

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

Reduction of Energy Intake using Just-In-Time Feedback from a Wearable Sensor System

PubMed Central

Farooq, Muhammad; McCrory, Megan A.; Sazonov, Edward

2017-01-01

Objective This work explored the potential use of a wearable sensor system for providing just-in-time (JIT) feedback on the progression of a meal and tested its ability to reduce the total food mass intake. Methods Eighteen participants each consumed three meals in a lab while monitored by a wearable sensor system capable of accurately tracking chew counts. The baseline visit was used to establish the self-determined ingested mass and the associated chew counts. Real-time feedback on chew counts was provided in the next two visits during which the target chew counts was either the same as that at baseline or the baseline chew counts reduced by 25%, in randomized order. The target was concealed from the participant and from the experimenter. Nonparametric repeated-measures ANOVA were performed to compare mass of intake, meal duration, and ratings of hunger, appetite, and thirst across 3 meals. Results JIT feedback targeting a 25% reduction in chew counts resulted in a reduction in mass and energy intake without affecting perceived hunger or fullness. Conclusion JIT feedback on chewing behavior may reduce intake within a meal. This system can be further used to help develop individualized strategies to provide just-in-time adaptive interventions for reducing energy intake. PMID:28233942

Reduction of energy intake using just-in-time feedback from a wearable sensor system.

PubMed

Farooq, Muhammad; McCrory, Megan A; Sazonov, Edward

2017-04-01

This work explored the potential use of a wearable sensor system for providing just-in-time (JIT) feedback on the progression of a meal and tested its ability to reduce the total food mass intake. Eighteen participants consumed three meals each in a lab while monitored by a wearable sensor system capable of accurately tracking chew counts. The baseline visit was used to establish the self-determined ingested mass and the associated chew counts. Real-time feedback on chew counts was provided in the next two visits, during which the target chew count was either the same as that at baseline or the baseline chew count reduced by 25% (in randomized order). The target was concealed from the participant and from the experimenter. Nonparametric repeated-measures ANOVAs were performed to compare mass of intake, meal duration, and ratings of hunger, appetite, and thirst across three meals. JIT feedback targeting a 25% reduction in chew counts resulted in a reduction in mass and energy intake without affecting perceived hunger or fullness. JIT feedback on chewing behavior may reduce intake within a meal. This system can be further used to help develop individualized strategies to provide JIT adaptive interventions for reducing energy intake. © 2017 The Obesity Society.

Modular Bayesian Networks with Low-Power Wearable Sensors for Recognizing Eating Activities.

PubMed

Kim, Kee-Hoon; Cho, Sung-Bae

2017-12-11

Recently, recognizing a user's daily activity using a smartphone and wearable sensors has become a popular issue. However, in contrast with the ideal definition of an experiment, there could be numerous complex activities in real life with respect to its various background and contexts: time, space, age, culture, and so on. Recognizing these complex activities with limited low-power sensors, considering the power and memory constraints of the wearable environment and the user's obtrusiveness at once is not an easy problem, although it is very crucial for the activity recognizer to be practically useful. In this paper, we recognize activity of eating, which is one of the most typical examples of a complex activity, using only daily low-power mobile and wearable sensors. To organize the related contexts systemically, we have constructed the context model based on activity theory and the "Five W's", and propose a Bayesian network with 88 nodes to predict uncertain contexts probabilistically. The structure of the proposed Bayesian network is designed by a modular and tree-structured approach to reduce the time complexity and increase the scalability. To evaluate the proposed method, we collected the data with 10 different activities from 25 volunteers of various ages, occupations, and jobs, and have obtained 79.71% accuracy, which outperforms other conventional classifiers by 7.54-14.4%. Analyses of the results showed that our probabilistic approach could also give approximate results even when one of contexts or sensor values has a very heterogeneous pattern or is missing.

Gaussian processes for personalized e-health monitoring with wearable sensors.

PubMed

Clifton, Lei; Clifton, David A; Pimentel, Marco A F; Watkinson, Peter J; Tarassenko, Lionel

2013-01-01

Advances in wearable sensing and communications infrastructure have allowed the widespread development of prototype medical devices for patient monitoring. However, such devices have not penetrated into clinical practice, primarily due to a lack of research into "intelligent" analysis methods that are sufficiently robust to support large-scale deployment. Existing systems are typically plagued by large false-alarm rates, and an inability to cope with sensor artifact in a principled manner. This paper has two aims: 1) proposal of a novel, patient-personalized system for analysis and inference in the presence of data uncertainty, typically caused by sensor artifact and data incompleteness; 2) demonstration of the method using a large-scale clinical study in which 200 patients have been monitored using the proposed system. This latter provides much-needed evidence that personalized e-health monitoring is feasible within an actual clinical environment, at scale, and that the method is capable of improving patient outcomes via personalized healthcare.

Development of a Wearable Cardiac Monitoring System for Behavioral Neurocardiac Training: A Usability Study

PubMed Central

Morita, Plinio P; Tallevi, Kevin; Armour, Kevin; Li, John; Nolan, Robert P; Cafazzo, Joseph A

2016-01-01

Background Elevated blood pressure is one of the main risk factors for death globally. Behavioral neurocardiac training (BNT) is a complementary approach to blood pressure and stress management that is intended to exercise the autonomic reflexes, improve stress recovery, and lower blood pressure. BNT involves cognitive-behavioral therapy with a paced breathing technique and heart rate variability biofeedback. BNT is limited to in-clinic delivery and faces an accessibility barrier because of the need for clinical oversight and the use of complex monitoring tools. Objective The objective of this project was to design, develop, and evaluate a wearable electrocardiographic (ECG) sensor system for the delivery of BNT in a home setting. Methods The wearable sensor system, Beat, consists of an ECG sensor and a mobile app. It was developed iteratively using the principles of test-driven Agile development and user-centered design. A usability study was conducted at Toronto General Hospital to evaluate feasibility and user experience and identify areas of improvement. Results The Beatsensor was designed as a modular patch to be worn on the user’s chest and uses standard ECG electrodes. It streams a single-lead ECG wirelessly to a mobile phone using Bluetooth Low Energy. The use of small, low-power electronics, a low device profile, and a tapered enclosure allowed for a device that can be unobtrusively worn under clothing. The sensor was designed to operate with a mobile app that guides users through the BNT exercises to train them to a slow-paced breathing technique for stress recovery. The BNT app uses the ECG captured by the sensor to provide heart rate variability biofeedback in the form of a real-time heart rate waveform to complement and reinforce the impact of the training. Usability testing (n=6) indicated that the overall response to the design and user experience of the system was perceived positively. All participants indicated that the system had a positive effect on stress management and that they would use it at home. Areas of improvement were identified, which focused primarily on the delivery of training and education on BNT through the app. Conclusions The outcome of this project was a wearable sensor system to deliver BNT at home. The system has the potential to offer a complementary approach to blood pressure and stress management at home and reduce current accessibility barriers. PMID:27106171

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.

Detection-gap-independent optical sensor design using divergence-beam-controlled slit lasers for wearable devices

NASA Astrophysics Data System (ADS)

Yoon, Young Zoon; Kim, Hyochul; Park, Yeonsang; Kim, Jineun; Lee, Min Kyung; Kim, Un Jeong; Roh, Young-Geun; Hwang, Sung Woo

2016-09-01

Wearable devices often employ optical sensors, such as photoplethysmography sensors, for detecting heart rates or other biochemical factors. Pulse waveforms, rather than simply detecting heartbeats, can clarify arterial conditions. However, most optical sensor designs require close skin contact to reduce power consumption while obtaining good quality signals without distortion. We have designed a detection-gap-independent optical sensor array using divergence-beam-controlled slit lasers and distributed photodiodes in a pulse-detection device wearable over the wrist's radial artery. It achieves high biosignal quality and low power consumption. The top surface of a vertical-cavity surface-emitting laser of 850 nm wavelength was covered by Au film with an open slit of width between 500 nm and 1500 nm, which generated laser emissions across a large divergence angle along an axis orthogonal to the slit direction. The sensing coverage of the slit laser diode (LD) marks a 50% improvement over nonslit LD sensor coverage. The slit LD sensor consumes 100% more input power than the nonslit LD sensor to obtain similar optical output power. The slit laser sensor showed intermediate performance between LD and light-emitting diode sensors. Thus, designing sensors with multiple-slit LD arrays can provide useful and convenient ways for incorporating optical sensors in wrist-wearable devices.

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

DOE PAGES

Gao, Wei; Emaminejad, Sam; Nyein, Hnin Yin Yin; ...

2016-01-27

We report that wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health. Sampling human sweat, which is rich in physiological information13, could enable non-invasive monitoring. Previously reported sweat-based and other noninvasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state14–18. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanicallymore » flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Lastly, our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plasticbased sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing.« less

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

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

Gao, Wei; Emaminejad, Sam; Nyein, Hnin Yin Yin

We report that wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health. Sampling human sweat, which is rich in physiological information13, could enable non-invasive monitoring. Previously reported sweat-based and other noninvasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state14–18. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanicallymore » flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Lastly, our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plasticbased sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing.« less

Integration of biochemical sensors into wearable biomaterial platforms

NASA Astrophysics Data System (ADS)

Jandhyala, Sidhartha; Walper, Scott A.; Cargill, Allison A.; Ozual, Abigail; Daniele, Michael A.

2016-05-01

With rapidly inflating healthcare costs, a limited supply of physicians and an alarming surge in lifestyle diseases, radical changes must be made to improve preventative medicine and ensure a sustainable healthcare system. A compelling solution is to equip the population with wearable health monitors to continuously record representative and actionable physiological data. Herein, we present a preliminary design and evaluation of a biochemical sensor node enabled by a substrate comprised of a nanocellulose thin-film that conforms to the skin and carries a printed sensor element. The nanocellulose layer ensures conformal and biocompatible contact with the skin, while a printed layer provides a high surface-area electrode. While the recognition/transduction element can be exchanged for many different sensing motifs, we utilize the general structure of an electrochemical glucose sensor.

Feature Extraction and Selection for Myoelectric Control Based on Wearable EMG Sensors.

PubMed

Phinyomark, Angkoon; N Khushaba, Rami; Scheme, Erik

2018-05-18

Specialized myoelectric sensors have been used in prosthetics for decades, but, with recent advancements in wearable sensors, wireless communication and embedded technologies, wearable electromyographic (EMG) armbands are now commercially available for the general public. Due to physical, processing, and cost constraints, however, these armbands typically sample EMG signals at a lower frequency (e.g., 200 Hz for the Myo armband) than their clinical counterparts. It remains unclear whether existing EMG feature extraction methods, which largely evolved based on EMG signals sampled at 1000 Hz or above, are still effective for use with these emerging lower-bandwidth systems. In this study, the effects of sampling rate (low: 200 Hz vs. high: 1000 Hz) on the classification of hand and finger movements were evaluated for twenty-six different individual features and eight sets of multiple features using a variety of datasets comprised of both able-bodied and amputee subjects. The results show that, on average, classification accuracies drop significantly ( p.

Wearable System for Acquisition and Monitoring of Biological Signals

NASA Astrophysics Data System (ADS)

Piccinini, D. J.; Andino, N. B.; Ponce, S. D.; Roberti, MA; López, y. N.

2016-04-01

This paper presents a modular, wearable system for acquisition and wireless transmission of biological signals. Configurable slaves for different signals (such as ECG, EMG, inertial sensors, and temperature) based in the ADS1294 Medical Analog Front End are connected to a Master, based in the CC3200 microcontroller, both from Texas Instruments. The slaves are configurable according to the specific application, providing versatility to the wearable system. The battery consumption is reduced, through a couple of Li-ion batteries and the circuit has also a battery charger. A custom made box was designed and fabricated in a 3D printer, preserving the requirements of low cost, low weight and safety recommendations.

An Alternative Wearable Tracking System Based on a Low-Power Wide-Area Network.

PubMed

Fernández-Garcia, Raul; Gil, Ignacio

2017-03-14

This work presents an alternative wearable tracking system based on a low-power wide area network. A complete GPS receiver was integrated with a textile substrate, and the latitude and longitude coordinates were sent to the cloud by means of the SIM-less SIGFOX network. To send the coordinates over SIGFOX protocol, a specific codification algorithm was used and a customized UHF antenna on jeans fabric was designed, simulated and tested. Moreover, to guarantee the compliance to international regulations for human body exposure to electromagnetic radiation, the electromagnetic specific absorption rate of this antenna was analyzed. A specific remote server was developed to decode the latitude and longitude coordinates. Once the coordinates have been decoded, the remote server sends this information to the open source data viewer SENTILO to show the location of the sensor node in a map. The functionality of this system has been demonstrated experimentally. The results guarantee the utility and wearability of the proposed tracking system for the development of sensor nodes and point out that it can be a low cost alternative to other commercial products based on GSM networks.

Ultra-low-power wearable biopotential sensor nodes.

PubMed

Yazicioglu, R F; Torfs, T; Penders, J; Romero, I; Kim, H; Merken, P; Gyselinckx, B; Yoo, H J; Van Hoof, C

2009-01-01

This paper discusses ultra-low-power wireless sensor nodes intended for wearable biopotential monitoring. Specific attention is given to mixed-signal design approaches and their impact on the overall system power dissipation. Examples of trade-offs in power dissipation between analog front-ends and digital signal processing are also given. It is shown how signal filtering can further reduce the internal power consumption of a node. Such power saving approaches are indispensable as real-life tests of custom wireless ECG patches reveal the need for artifact detection and correction. The power consumption of such additional features has to come from power savings elsewhere in the system as the overall power budget cannot increase.

Feasibility Study and Design of a Wearable System-on-a-Chip Pulse Radar for Contactless Cardiopulmonary Monitoring

PubMed Central

Zito, Domenico; Pepe, Domenico; Neri, Bruno; Zito, Fabio; De Rossi, Danilo; Lanatà, Antonio

2008-01-01

A new system-on-a-chip radar sensor for next-generation wearable wireless interface applied to the human health care and safeguard is presented. The system overview is provided and the feasibility study of the radar sensor is presented. In detail, the overall system consists of a radar sensor for detecting the heart and breath rates and a low-power IEEE 802.15.4 ZigBee radio interface, which provides a wireless data link with remote data acquisition and control units. In particular, the pulse radar exploits 3.1–10.6 GHz ultra-wideband signals which allow a significant reduction of the transceiver complexity and then of its power consumption. The operating principle of the radar for the cardiopulmonary monitoring is highlighted and the results of the system analysis are reported. Moreover, the results obtained from the building-blocks design, the channel measurement, and the ultra-wideband antenna realization are reported. PMID:18389068

Advances in wearable technology for rehabilitation.

PubMed

Bonato, Paolo

2009-01-01

Assessing the impact of rehabilitation interventions on the real life of individuals is a key element of the decision-making process required to choose a rehabilitation strategy. In the past, therapists and physicians inferred the effectiveness of a given rehabilitation approach from observations performed in a clinical setting and self-reports by patients. Recent developments in wearable technology have provided tools to complement the information gathered by rehabilitation personnel via patient's direct observation and via interviews and questionnaires. A new generation of wearable sensors and systems has emerged that allows clinicians to gather measures in the home and community settings that capture patients' activity level and exercise compliance, the effectiveness of pharmacological interventions, and the ability of patients to perform efficiently specific motor tasks. Available unobtrusive sensors allow clinical personnel to monitor patients' movement and physiological data such as heart rate, respiratory rate, and oxygen saturation. Cell phone technology and the widespread access to the Internet provide means to implement systems designed to remotely monitor patients' status and optimize interventions based on individual responses to different rehabilitation approaches. This chapter summarizes recent advances in the field of wearable technology and presents examples of application of this technology in rehabilitation.

User-Wearable Devices that Monitor Exposure to Blue Light and Recommend Adjustments Thereto

NASA Technical Reports Server (NTRS)

Lee, Yong Jin (Inventor)

2017-01-01

Described herein are user-wearable devices that include an optical sensor, and methods for use therewith. In certain embodiments, an optical sensor of a user-wearable device (e.g., a wrist-worn device) is used to detect blue light that is incident on the optical sensor and to produce a blue light detection signal indicative thereof, and thus, indicative of the response of the user's intrinsically photosensitive Retinal Ganglion Cells (ipRGCs). In dependence on the blue light detection signal, there is a determination of a metric indicative of an amount of blue light detected by the optical sensor. The metric is compared to a corresponding threshold, and a user notification is triggered in dependence on results of the comparing, wherein the user notification informs a person wearing the user-wearable device to adjust their exposure to light.

Recommendations for Assessment of the Reliability, Sensitivity, and Validity of Data Provided by Wearable Sensors Designed for Monitoring Physical Activity

PubMed Central

2018-01-01

Although it is becoming increasingly popular to monitor parameters related to training, recovery, and health with wearable sensor technology (wearables), scientific evaluation of the reliability, sensitivity, and validity of such data is limited and, where available, has involved a wide variety of approaches. To improve the trustworthiness of data collected by wearables and facilitate comparisons, we have outlined recommendations for standardized evaluation. We discuss the wearable devices themselves, as well as experimental and statistical considerations. Adherence to these recommendations should be beneficial not only for the individual, but also for regulatory organizations and insurance companies. PMID:29712629

A Smart Wearable Sensor System for Counter-Fighting Overweight in Teenagers.

PubMed

Standoli, Carlo Emilio; Guarneri, Maria Renata; Perego, Paolo; Mazzola, Marco; Mazzola, Alessandra; Andreoni, Giuseppe

2016-08-10

PEGASO is a FP7-funded project whose goal is to develop an ICT and mobile-based platform together with an appropriate strategy to tackle the diffusion of obesity and other lifestyle-related illnesses among teenagers. Indeed, the design of an engaging strategy, leveraging a complementary set of technologies, is the approach proposed by the project to promote the adoption of healthy habits such as active lifestyle and balanced nutrition and to effectively counter-fight the emergence of overweight and obesity in the younger population. A technological key element of such a strategy sees the adoption of wearable sensors to monitor teenagers' activities, which is at the basis of developing awareness about the current lifestyle. This paper describes the experience carried out in the framework of the PEGASO project in developing and evaluating wearable monitoring systems addressed to adolescents. The paper describes the methodological approach based on the co-designing of such a wearable system and the main results that, in the first phase, involved a total of 407 adolescents across Europe in a series of focus groups conducted in three countries for the requirements definition phase. Moreover, it describes an evaluation process of signal reliability during the usage of the wearable system. The main results described here are: (a) a prototype of the standardized experimental protocol that has been developed and applied to test signal reliability in smart garments; (b) the requirements definition methodology through a co-design activity and approach to address user requirements and preferences and not only technological specifications. Such co-design approach is able to support a higher system acceptance and usability together with a sustained adoption of the solution with respect to the traditional technology push system development strategy.

A Smart Wearable Sensor System for Counter-Fighting Overweight in Teenagers

PubMed Central

Standoli, Carlo Emilio; Guarneri, Maria Renata; Perego, Paolo; Mazzola, Marco; Mazzola, Alessandra; Andreoni, Giuseppe

2016-01-01

PEGASO is a FP7-funded project whose goal is to develop an ICT and mobile-based platform together with an appropriate strategy to tackle the diffusion of obesity and other lifestyle-related illnesses among teenagers. Indeed, the design of an engaging strategy, leveraging a complementary set of technologies, is the approach proposed by the project to promote the adoption of healthy habits such as active lifestyle and balanced nutrition and to effectively counter-fight the emergence of overweight and obesity in the younger population. A technological key element of such a strategy sees the adoption of wearable sensors to monitor teenagers’ activities, which is at the basis of developing awareness about the current lifestyle. This paper describes the experience carried out in the framework of the PEGASO project in developing and evaluating wearable monitoring systems addressed to adolescents. The paper describes the methodological approach based on the co-designing of such a wearable system and the main results that, in the first phase, involved a total of 407 adolescents across Europe in a series of focus groups conducted in three countries for the requirements definition phase. Moreover, it describes an evaluation process of signal reliability during the usage of the wearable system. The main results described here are: (a) a prototype of the standardized experimental protocol that has been developed and applied to test signal reliability in smart garments; (b) the requirements definition methodology through a co-design activity and approach to address user requirements and preferences and not only technological specifications. Such co-design approach is able to support a higher system acceptance and usability together with a sustained adoption of the solution with respect to the traditional technology push system development strategy. PMID:27517929

Design a Wearable Device for Blood Oxygen Concentration and Temporal Heart Beat Rate

NASA Astrophysics Data System (ADS)

Myint, Cho Zin; Barsoum, Nader; Ing, Wong Kiing

2010-06-01

The wireless network technology is increasingly important in healthcare as a result of the aging population and the tendency to acquire chronic disease such as heart attack, high blood pressure amongst the elderly. A wireless sensor network system that has the capability to monitor physiological sign such as SpO2 (Saturation of Arterial Oxygen) and heart beat rate in real-time from the human's body is highlighted in this study. This research is to design a prototype sensor network hardware, which consists of microcontroller PIC18F series and transceiver unit. The sensor is corporate into a wearable body sensor network which is small in size and easy to use. The sensor allows a non invasive, real time method to provide information regarding the health of the body. This enables a more efficient and economical means for managing the health care of the population.

A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks

PubMed Central

Hu, Sheng; Wei, Hongxing; Chen, Youdong; Tan, Jindong

2012-01-01

Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. This paper presents the design of a real-time wearable ECG monitoring system with associated cardiac arrhythmia classification algorithms. One of the striking advantages is that ECG analog front-end and on-node digital processing are designed to remove most of the noise and bias. In addition, the wearable sensor node is able to monitor the patient's ECG and motion signal in an unobstructive way. To realize the real-time medical analysis, the ECG is digitalized and transmitted to a smart phone via Bluetooth. On the smart phone, the ECG waveform is visualized and a novel layered hidden Markov model is seamlessly integrated to classify multiple cardiac arrhythmias in real time. Experimental results demonstrate that the clean and reliable ECG waveform can be captured in multiple stressed conditions and the real-time classification on cardiac arrhythmia is competent to other workbenches. PMID:23112746

RGO-coated elastic fibres as wearable strain sensors for full-scale detection of human motions

NASA Astrophysics Data System (ADS)

Mi, Qing; Wang, Qi; Zang, Siyao; Mao, Guoming; Zhang, Jinnan; Ren, Xiaomin

2018-01-01

In this study, we chose highly-elastic fabric fibres as the functional carrier and then simply coated the fibres with reduced graphene oxide (rGO) using plasma treatment, dip coating and hydrothermal reduction steps, finally making a wearable strain sensor. As a result, the full-scale detection of human motions, ranging from bending joints to the pulse beat, has been achieved by these sensors. Moreover, high sensitivity, good stability and excellent repeatability were realized. The good sensing performances and economical fabrication process of this wearable strain sensor have strengthened our confidence in practical applications in smart clothing, smart fabrics, healthcare, and entertainment fields.

Highly stretchable and wearable graphene strain sensors with controllable sensitivity for human motion monitoring.

PubMed

Park, Jung Jin; Hyun, Woo Jin; Mun, Sung Cik; Park, Yong Tae; Park, O Ok

2015-03-25

Because of their outstanding electrical and mechanical properties, graphene strain sensors have attracted extensive attention for electronic applications in virtual reality, robotics, medical diagnostics, and healthcare. Although several strain sensors based on graphene have been reported, the stretchability and sensitivity of these sensors remain limited, and also there is a pressing need to develop a practical fabrication process. This paper reports the fabrication and characterization of new types of graphene strain sensors based on stretchable yarns. Highly stretchable, sensitive, and wearable sensors are realized by a layer-by-layer assembly method that is simple, low-cost, scalable, and solution-processable. Because of the yarn structures, these sensors exhibit high stretchability (up to 150%) and versatility, and can detect both large- and small-scale human motions. For this study, wearable electronics are fabricated with implanted sensors that can monitor diverse human motions, including joint movement, phonation, swallowing, and breathing.

A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring

PubMed Central

Yang, Che-Chang; Hsu, Yeh-Liang

2010-01-01

Characteristics of physical activity are indicative of one’s mobility level, latent chronic diseases and aging process. Accelerometers have been widely accepted as useful and practical sensors for wearable devices to measure and assess physical activity. This paper reviews the development of wearable accelerometry-based motion detectors. The principle of accelerometry measurement, sensor properties and sensor placements are first introduced. Various research using accelerometry-based wearable motion detectors for physical activity monitoring and assessment, including posture and movement classification, estimation of energy expenditure, fall detection and balance control evaluation, are also reviewed. Finally this paper reviews and compares existing commercial products to provide a comprehensive outlook of current development status and possible emerging technologies. PMID:22163626

Carbon Nanotube-Based Ion Selective Sensors for Wearable Applications.

PubMed

Roy, Soumyendu; David-Pur, Moshe; Hanein, Yael

2017-10-11

Wearable electronics offer new opportunities in a wide range of applications, especially sweat analysis using skin sensors. A fundamental challenge in these applications is the formation of sensitive and stable electrodes. In this article we report the development of a wearable sensor based on carbon nanotube (CNT) electrode arrays for sweat sensing. Solid-state ion selective electrodes (ISEs), sensitive to Na + ions, were prepared by drop coating plasticized poly(vinyl chloride) (PVC) doped with ionophore and ion exchanger on CNT electrodes. The ion selective membrane (ISM) filled the intertubular spaces of the highly porous CNT film and formed an attachment that was stronger than that achieved with flat Au, Pt, or carbon electrodes. Concentration of the ISM solution used influenced the attachment to the CNT film, the ISM surface morphology, and the overall performance of the sensor. Sensitivity of 56 ± 3 mV/decade to Na + ions was achieved. Optimized solid-state reference electrodes (REs), suitable for wearable applications, were prepared by coating CNT electrodes with colloidal dispersion of Ag/AgCl, agarose hydrogel with 0.5 M NaCl, and a passivation layer of PVC doped with NaCl. The CNT-based REs had low sensitivity (-1.7 ± 1.2 mV/decade) toward the NaCl solution and high repeatability and were superior to bare Ag/AgCl, metals, carbon, and CNT films, reported previously as REs. CNT-based ISEs were calibrated against CNT-based REs, and the short-term stability of the system was tested. We demonstrate that CNT-based devices implemented on a flexible support are a very attractive platform for future wearable technology devices.

Temperature measurement systems in wearable electronics

NASA Astrophysics Data System (ADS)

Walczak, S.; Gołebiowski, J.

2014-08-01

The aim of this paper is to present the concept of temperature measurement system, adapted to wearable electronics applications. Temperature is one of the most commonly monitored factor in smart textiles, especially in sportswear, medical and rescue products. Depending on the application, measured temperature could be used as an initial value of alert, heating, lifesaving or analysis system. The concept of the temperature measurement multi-point system, which consists of flexible screen-printed resistive sensors, placed on the T-shirt connected with the central unit and the power supply is elaborated in the paper.

Wearable Sensors in Transportation - Exploratory Advanced Research Program Initial Stage Investigation

DOT National Transportation Integrated Search

2016-03-01

This report summarizes an initial stage investigation into wearable sensors for transportation research : applications. The Federal Highway Administration (FHWA) has observed significant activity in this area and : seeks to obtain an understanding of...

Physiological Informatics: Collection and Analyses of Data from Wearable Sensors and Smartphone for Healthcare.

PubMed

Bai, Jinwei; Shen, Li; Sun, Huimin; Shen, Bairong

2017-01-01

Physiological data from wearable sensors and smartphone are accumulating rapidly, and this provides us the chance to collect dynamic and personalized information as phenotype to be integrated to genotype for the holistic understanding of complex diseases. This integration can be applied to early prediction and prevention of disease, therefore promoting the shifting of disease care tradition to the healthcare paradigm. In this chapter, we summarize the physiological signals which can be detected by wearable sensors, the sharing of the physiological big data, and the mining methods for the discovery of disease-associated patterns for personalized diagnosis and treatment. We discuss the challenges of physiological informatics about the storage, the standardization, the analyses, and the applications of the physiological data from the wearable sensors and smartphone. At last, we present our perspectives on the models for disentangling the complex relationship between early disease prediction and the mining of physiological phenotype data.

Bioinspired Composite Microfibers for Skin Adhesion and Signal Amplification of Wearable Sensors.

PubMed

Drotlef, Dirk-M; Amjadi, Morteza; Yunusa, Muhammad; Sitti, Metin

2017-07-01

A facile approach is proposed for superior conformation and adhesion of wearable sensors to dry and wet skin. Bioinspired skin-adhesive films are composed of elastomeric microfibers decorated with conformal and mushroom-shaped vinylsiloxane tips. Strong skin adhesion is achieved by crosslinking the viscous vinylsiloxane tips directly on the skin surface. Furthermore, composite microfibrillar adhesive films possess a high adhesion strength of 18 kPa due to the excellent shape adaptation of the vinylsiloxane tips to the multiscale roughness of the skin. As a utility of the skin-adhesive films in wearable-device applications, they are integrated with wearable strain sensors for respiratory and heart-rate monitoring. The signal-to-noise ratio of the strain sensor is significantly improved to 59.7 because of the considerable signal amplification of microfibrillar skin-adhesive films. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modular Bayesian Networks with Low-Power Wearable Sensors for Recognizing Eating Activities

PubMed Central

Kim, Kee-Hoon

2017-01-01

Recently, recognizing a user’s daily activity using a smartphone and wearable sensors has become a popular issue. However, in contrast with the ideal definition of an experiment, there could be numerous complex activities in real life with respect to its various background and contexts: time, space, age, culture, and so on. Recognizing these complex activities with limited low-power sensors, considering the power and memory constraints of the wearable environment and the user’s obtrusiveness at once is not an easy problem, although it is very crucial for the activity recognizer to be practically useful. In this paper, we recognize activity of eating, which is one of the most typical examples of a complex activity, using only daily low-power mobile and wearable sensors. To organize the related contexts systemically, we have constructed the context model based on activity theory and the “Five W’s”, and propose a Bayesian network with 88 nodes to predict uncertain contexts probabilistically. The structure of the proposed Bayesian network is designed by a modular and tree-structured approach to reduce the time complexity and increase the scalability. To evaluate the proposed method, we collected the data with 10 different activities from 25 volunteers of various ages, occupations, and jobs, and have obtained 79.71% accuracy, which outperforms other conventional classifiers by 7.54–14.4%. Analyses of the results showed that our probabilistic approach could also give approximate results even when one of contexts or sensor values has a very heterogeneous pattern or is missing. PMID:29232937

A Novel Wearable Sensor-Based Human Activity Recognition Approach Using Artificial Hydrocarbon Networks.

PubMed

Ponce, Hiram; Martínez-Villaseñor, María de Lourdes; Miralles-Pechuán, Luis

2016-07-05

Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services. There are many examples of health systems improved by human activity recognition. Nevertheless, the human activity recognition classification process is not an easy task. Different types of noise in wearable sensors data frequently hamper the human activity recognition classification process. In order to develop a successful activity recognition system, it is necessary to use stable and robust machine learning techniques capable of dealing with noisy data. In this paper, we presented the artificial hydrocarbon networks (AHN) technique to the human activity recognition community. Our artificial hydrocarbon networks novel approach is suitable for physical activity recognition, noise tolerance of corrupted data sensors and robust in terms of different issues on data sensors. We proved that the AHN classifier is very competitive for physical activity recognition and is very robust in comparison with other well-known machine learning methods.

CCS_WHMS: A Congestion Control Scheme for Wearable Health Management System.

PubMed

Kafi, Mohamed Amine; Ben Othman, Jalel; Bagaa, Miloud; Badache, Nadjib

2015-12-01

Wearable computing is becoming a more and more attracting field in the last years thanks to the miniaturisation of electronic devices. Wearable healthcare monitoring systems (WHMS) as an important client of wearable computing technology has gained a lot. Indeed, the wearable sensors and their surrounding healthcare applications bring a lot of benefits to patients, elderly people and medical staff, so facilitating their daily life quality. But from a research point of view, there is still work to accomplish in order to overcome the gap between hardware and software parts. In this paper, we target the problem of congestion control when all these healthcare sensed data have to reach the destination in a reliable manner that avoids repetitive transmission which wastes precious energy or leads to loss of important information in emergency cases, too. We propose a congestion control scheme CCS_WHMS that ensures efficient and fair data delivery while used in the body wearable system part or in the multi-hop inter bodies wearable ones to get the destination. As the congestion detection paradigm is very important in the control process, we do experimental tests to compare between state of the art congestion detection methods, using MICAz motes, in order to choose the appropriate one for our scheme.

Flexible and Stretchable Physical Sensor Integrated Platforms for Wearable Human-Activity Monitoringand Personal Healthcare.

PubMed

Trung, Tran Quang; Lee, Nae-Eung

2016-06-01

Flexible and stretchable physical sensors that can measure and quantify electrical signals generated by human activities are attracting a great deal of attention as they have unique characteristics, such as ultrathinness, low modulus, light weight, high flexibility, and stretchability. These flexible and stretchable physical sensors conformally attached on the surface of organs or skin can provide a new opportunity for human-activity monitoring and personal healthcare. Consequently, in recent years there has been considerable research effort devoted to the development of flexible and stretchable physical sensors to fulfill the requirements of future technology, and much progress has been achieved. Here, the most recent developments of flexible and stretchable physical sensors are described, including temperature, pressure, and strain sensors, and flexible and stretchable sensor-integrated platforms. The latest successful examples of flexible and stretchable physical sensors for the detection of temperature, pressure, and strain, as well as their novel structures, technological innovations, and challenges, are reviewed first. In the next section, recent progress regarding sensor-integrated wearable platforms is overviewed in detail. Some of the latest achievements regarding self-powered sensor-integrated wearable platform technologies are also reviewed. Further research direction and challenges are also proposed to develop a fully sensor-integrated wearable platform for monitoring human activity and personal healthcare in the near future. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Human Activity Recognition from Body Sensor Data using Deep Learning.

PubMed

Hassan, Mohammad Mehedi; Huda, Shamsul; Uddin, Md Zia; Almogren, Ahmad; Alrubaian, Majed

2018-04-16

In recent years, human activity recognition from body sensor data or wearable sensor data has become a considerable research attention from academia and health industry. This research can be useful for various e-health applications such as monitoring elderly and physical impaired people at Smart home to improve their rehabilitation processes. However, it is not easy to accurately and automatically recognize physical human activity through wearable sensors due to the complexity and variety of body activities. In this paper, we address the human activity recognition problem as a classification problem using wearable body sensor data. In particular, we propose to utilize a Deep Belief Network (DBN) model for successful human activity recognition. First, we extract the important initial features from the raw body sensor data. Then, a kernel principal component analysis (KPCA) and linear discriminant analysis (LDA) are performed to further process the features and make them more robust to be useful for fast activity recognition. Finally, the DBN is trained by these features. Various experiments were performed on a real-world wearable sensor dataset to verify the effectiveness of the deep learning algorithm. The results show that the proposed DBN outperformed other algorithms and achieves satisfactory activity recognition performance.

Fusion solution for soldier wearable gunfire detection systems

NASA Astrophysics Data System (ADS)

Cakiades, George; Desai, Sachi; Deligeorges, Socrates; Buckland, Bruce E.; George, Jemin

2012-06-01

Currently existing acoustic based Gunfire Detection Systems (GDS) such as soldier wearable, vehicle mounted, and fixed site devices provide enemy detection and localization capabilities to the user. However, the solution to the problem of portability versus performance tradeoff remains elusive. The Data Fusion Module (DFM), described herein, is a sensor/platform agnostic software supplemental tool that addresses this tradeoff problem by leveraging existing soldier networks to enhance GDS performance across a Tactical Combat Unit (TCU). The DFM software enhances performance by leveraging all available acoustic GDS information across the TCU synergistically to calculate highly accurate solutions more consistently than any individual GDS in the TCU. The networked sensor architecture provides additional capabilities addressing the multiple shooter/fire-fight problems in addition to sniper detection/localization. The addition of the fusion solution to the overall Size, Weight and Power & Cost (SWaP&C) is zero to negligible. At the end of the first-year effort, the DFM integrated sensor network's performance was impressive showing improvements upwards of 50% in comparison to a single sensor solution. Further improvements are expected when the networked sensor architecture created in this effort is fully exploited.

An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.

PubMed

He, Jian; Bai, Shuang; Wang, Xiaoyi

2017-06-16

Falls are one of the main health risks among the elderly. A fall detection system based on inertial sensors can automatically detect fall event and alert a caregiver for immediate assistance, so as to reduce injuries causing by falls. Nevertheless, most inertial sensor-based fall detection technologies have focused on the accuracy of detection while neglecting quantization noise caused by inertial sensor. In this paper, an activity model based on tri-axial acceleration and gyroscope is proposed, and the difference between activities of daily living (ADLs) and falls is analyzed. Meanwhile, a Kalman filter is proposed to preprocess the raw data so as to reduce noise. A sliding window and Bayes network classifier are introduced to develop a wearable fall detection system, which is composed of a wearable motion sensor and a smart phone. The experiment shows that the proposed system distinguishes simulated falls from ADLs with a high accuracy of 95.67%, while sensitivity and specificity are 99.0% and 95.0%, respectively. Furthermore, the smart phone can issue an alarm to caregivers so as to provide timely and accurate help for the elderly, as soon as the system detects a fall.

Graphene-Based Three-Dimensional Capacitive Touch Sensor for Wearable Electronics.

PubMed

Kang, Minpyo; Kim, Jejung; Jang, Bongkyun; Chae, Youngcheol; Kim, Jae-Hyun; Ahn, Jong-Hyun

2017-08-22

The development of input device technology in a conformal and stretchable format is important for the advancement of various wearable electronics. Herein, we report a capacitive touch sensor with good sensing capabilities in both contact and noncontact modes, enabled by the use of graphene and a thin device geometry. This device can be integrated with highly deformable areas of the human body, such as the forearms and palms. This touch sensor detects multiple touch signals in acute recordings and recognizes the distance and shape of the approaching objects before direct contact is made. This technology offers a convenient and immersive human-machine interface and additional potential utility as a multifunctional sensor for emerging wearable electronics and robotics.

Wearable Sensors; Applications, design and implementation

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Subhas Chandra; Islam, Tarikul

2017-12-01

With the ability to monitor a vast range of physiological parameters, combined with wireless technology, wireless sensor networks and the Internet of Things, wearable sensors are revolutionising the field of digital health monitoring. In addition to applications in health monitoring, such technology is being used to monitor the state of our living environment and even the quality of our foods and the wellbeing of livestock. Written for scientists, engineers and practitioners by an international collection of authors, this book reviews the fundamentals of wearable sensors, their function, design, fabrication and implementation. Their application and advanced aspects including interface electronics and signal processing for easy interpretation of data, data transmission, data networking, data security, and privacy are also included.

Flexible Sensing Electronics for Wearable/Attachable Health Monitoring.

PubMed

Wang, Xuewen; Liu, Zheng; Zhang, Ting

2017-07-01

Wearable or attachable health monitoring smart systems are considered to be the next generation of personal portable devices for remote medicine practices. Smart flexible sensing electronics are components crucial in endowing health monitoring systems with the capability of real-time tracking of physiological signals. These signals are closely associated with body conditions, such as heart rate, wrist pulse, body temperature, blood/intraocular pressure and blood/sweat bio-information. Monitoring such physiological signals provides a convenient and non-invasive way for disease diagnoses and health assessments. This Review summarizes the recent progress of flexible sensing electronics for their use in wearable/attachable health monitoring systems. Meanwhile, we present an overview of different materials and configurations for flexible sensors, including piezo-resistive, piezo-electrical, capacitive, and field effect transistor based devices, and analyze the working principles in monitoring physiological signals. In addition, the future perspectives of wearable healthcare systems and the technical demands on their commercialization are briefly discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Wearable sensors objectively measure gait parameters in Parkinson’s disease

PubMed Central

Marxreiter, Franz; Gossler, Julia; Kohl, Zacharias; Reinfelder, Samuel; Gassner, Heiko; Aminian, Kamiar; Eskofier, Bjoern M.; Winkler, Jürgen; Klucken, Jochen

2017-01-01

Distinct gait characteristics like short steps and shuffling gait are prototypical signs commonly observed in Parkinson’s disease. Routinely assessed by observation through clinicians, gait is rated as part of categorical clinical scores. There is an increasing need to provide quantitative measurements of gait, e.g. to provide detailed information about disease progression. Recently, we developed a wearable sensor-based gait analysis system as diagnostic tool that objectively assesses gait parameter in Parkinson’s disease without the need of having a specialized gait laboratory. This system consists of inertial sensor units attached laterally to both shoes. The computed target of measures are spatiotemporal gait parameters including stride length and time, stance phase time, heel-strike and toe-off angle, toe clearance, and inter-stride variation from gait sequences. To translate this prototype into medical care, we conducted a cross-sectional study including 190 Parkinson’s disease patients and 101 age-matched controls and measured gait characteristics during a 4x10 meter walk at the subjects’ preferred speed. To determine intraindividual changes in gait, we monitored the gait characteristics of 63 patients longitudinally. Cross-sectional analysis revealed distinct spatiotemporal gait parameter differences reflecting typical Parkinson’s disease gait characteristics including short steps, shuffling gait, and postural instability specific for different disease stages and levels of motor impairment. The longitudinal analysis revealed that gait parameters were sensitive to changes by mirroring the progressive nature of Parkinson’s disease and corresponded to physician ratings. Taken together, we successfully show that wearable sensor-based gait analysis reaches clinical applicability providing a high biomechanical resolution for gait impairment in Parkinson’s disease. These data demonstrate the feasibility and applicability of objective wearable sensor-based gait measurement in Parkinson’s disease reaching high technological readiness levels for both, large scale clinical studies and individual patient care. PMID:29020012

Conceptual design of wearpack with physiology detector feature based on wearable instrumentation

NASA Astrophysics Data System (ADS)

Sukirman, Melani; Laksono, Pringgo Widyo; Priadythama, Ilham; Susmartini, Susy; Suhardi, Bambang

2017-11-01

Every company in Indonesia is responsible for their worker health and safety condition as mentioned in UU No I year 1970. In manufacturing industries, there are many manual tasks dealing with high work load and risk, so that they require excellent concentration and physical condition. There is no ideal way to guarantee worker safety without a real time physiological monitoring. This paper reports our ongoing study in conceptual design development of worker's clothing which is equipped with a wearable instrumentation system. The system is designed to detect and measure body temperature and pulse in real time. Some electrical components such as, LCD (liquid crystal display), LEDs (light emitting diode), batteries, and physiological sensors were assembled. All components are controlled by a wearable on board controller. LEDs is used as alert which can indicate abnormal physical conditions. The LCD was added to provide more detail information. TMP 36 and XD-58C were selected as the physiological sensors. Finally, an Arduino Lilypad was chosen for the controller. This instrumentation system was verified by accurately detected and inform physiological condition of 3 subjects. Further we are going to attach the system to a worker's clothing which was specifically designed to simplify and comfortable usage.

An Alternative Wearable Tracking System Based on a Low-Power Wide-Area Network

PubMed Central

Fernández-Garcia, Raul; Gil, Ignacio

2017-01-01

This work presents an alternative wearable tracking system based on a low-power wide area network. A complete GPS receiver was integrated with a textile substrate, and the latitude and longitude coordinates were sent to the cloud by means of the SIM-less SIGFOX network. To send the coordinates over SIGFOX protocol, a specific codification algorithm was used and a customized UHF antenna on jeans fabric was designed, simulated and tested. Moreover, to guarantee the compliance to international regulations for human body exposure to electromagnetic radiation, the electromagnetic specific absorption rate of this antenna was analyzed. A specific remote server was developed to decode the latitude and longitude coordinates. Once the coordinates have been decoded, the remote server sends this information to the open source data viewer SENTILO to show the location of the sensor node in a map. The functionality of this system has been demonstrated experimentally. The results guarantee the utility and wearability of the proposed tracking system for the development of sensor nodes and point out that it can be a low cost alternative to other commercial products based on GSM networks. PMID:28335424

WearETE: A Scalable Wearable E-Textile Triboelectric Energy Harvesting System for Human Motion Scavenging

PubMed Central

Li, Xian

2017-01-01

In this paper, we report the design, experimental validation and application of a scalable, wearable e-textile triboelectric energy harvesting (WearETE) system for scavenging energy from activities of daily living. The WearETE system features ultra-low-cost material and manufacturing methods, high accessibility, and high feasibility for powering wearable sensors and electronics. The foam and e-textile are used as the two active tribomaterials for energy harvester design with the consideration of flexibility and wearability. A calibration platform is also developed to quantify the input mechanical power and power efficiency. The performance of the WearETE system for human motion scavenging is validated and calibrated through experiments. The results show that the wearable triboelectric energy harvester can generate over 70 V output voltage which is capable of powering over 52 LEDs simultaneously with a 9 × 9 cm2 area. A larger version is able to lighten 190 LEDs during contact-separation process. The WearETE system can generate a maximum power of 4.8113 mW from hand clapping movements under the frequency of 4 Hz. The average power efficiency can be up to 24.94%. The output power harvested by the WearETE system during slow walking is 7.5248 µW. The results show the possibility of powering wearable electronics during human motion. PMID:29149035

Posture and activity recognition and energy expenditure prediction in a wearable platform.

PubMed

Sazonova, Nadezhda; Browning, Raymond; Melanson, Edward; Sazonov, Edward

2014-01-01

The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here we describe use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time prediction and display of time spent in various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we introduce new algorithms that require substantially less computational power. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a four-hour stay in a room calorimeter. Use of Multinomial Logistic Discrimination (MLD) for posture and activity classification resulted in an accuracy comparable to that of Support Vector Machines (SVM) (90% vs. 95%-98%) while reducing the running time by a factor of 190 and reducing the memory requirement by a factor of 104. Per minute EE estimation using activity-specific models resulted in an accurate EE prediction (RMSE of 0.53 METs vs. RMSE of 0.69 METs using previously reported SVM-branched models). These results demonstrate successful implementation of real-time physical activity monitoring and EE prediction system on a wearable platform.

Towards the development of a wearable Electrical Impedance Tomography system: A study about the suitability of a low power bioimpedance front-end.

PubMed

Menolotto, Matteo; Rossi, Stefano; Dario, Paolo; Della Torre, Luigi

2015-01-01

Wearable systems for remote monitoring of physiological parameter are ready to evolve towards wearable imaging systems. The Electrical Impedance Tomography (EIT) allows the non-invasive investigation of the internal body structure. The characteristics of this low-resolution and low-cost technique match perfectly with the concept of a wearable imaging device. On the other hand low power consumption, which is a mandatory requirement for wearable systems, is not usually discussed for standard EIT applications. In this work a previously developed low power architecture for a wearable bioimpedance sensor is applied to EIT acquisition and reconstruction, to evaluate the impact on the image of the limited signal to noise ratio (SNR), caused by low power design. Some anatomical models of the chest, with increasing geometric complexity, were developed, in order to evaluate and calibrate, through simulations, the parameters of the reconstruction algorithms provided by Electrical Impedance Diffuse Optical Reconstruction Software (EIDORS) project. The simulation results were compared with experimental measurements taken with our bioimpedance device on a phantom reproducing chest tissues properties. The comparison was both qualitative and quantitative through the application of suitable figures of merit; in this way the impact of the noise of the low power front-end on the image quality was assessed. The comparison between simulation and measurement results demonstrated that, despite the limited SNR, the device is accurate enough to be used for the development of an EIT based imaging wearable system.

Wearable smart sensor systems integrated on soft contact lenses for wireless ocular diagnostics

PubMed Central

Kim, Joohee; Kim, Minji; Lee, Mi-Sun; Kim, Kukjoo; Ji, Sangyoon; Kim, Yun-Tae; Park, Jihun; Na, Kyungmin; Bae, Kwi-Hyun; Kyun Kim, Hong; Bien, Franklin; Young Lee, Chang; Park, Jang-Ung

2017-01-01

Wearable contact lenses which can monitor physiological parameters have attracted substantial interests due to the capability of direct detection of biomarkers contained in body fluids. However, previously reported contact lens sensors can only monitor a single analyte at a time. Furthermore, such ocular contact lenses generally obstruct the field of vision of the subject. Here, we developed a multifunctional contact lens sensor that alleviates some of these limitations since it was developed on an actual ocular contact lens. It was also designed to monitor glucose within tears, as well as intraocular pressure using the resistance and capacitance of the electronic device. Furthermore, in-vivo and in-vitro tests using a live rabbit and bovine eyeball demonstrated its reliable operation. Our developed contact lens sensor can measure the glucose level in tear fluid and intraocular pressure simultaneously but yet independently based on different electrical responses. PMID:28447604

Wearable smart sensor systems integrated on soft contact lenses for wireless ocular diagnostics.

PubMed

Kim, Joohee; Kim, Minji; Lee, Mi-Sun; Kim, Kukjoo; Ji, Sangyoon; Kim, Yun-Tae; Park, Jihun; Na, Kyungmin; Bae, Kwi-Hyun; Kyun Kim, Hong; Bien, Franklin; Young Lee, Chang; Park, Jang-Ung

2017-04-27

Wearable contact lenses which can monitor physiological parameters have attracted substantial interests due to the capability of direct detection of biomarkers contained in body fluids. However, previously reported contact lens sensors can only monitor a single analyte at a time. Furthermore, such ocular contact lenses generally obstruct the field of vision of the subject. Here, we developed a multifunctional contact lens sensor that alleviates some of these limitations since it was developed on an actual ocular contact lens. It was also designed to monitor glucose within tears, as well as intraocular pressure using the resistance and capacitance of the electronic device. Furthermore, in-vivo and in-vitro tests using a live rabbit and bovine eyeball demonstrated its reliable operation. Our developed contact lens sensor can measure the glucose level in tear fluid and intraocular pressure simultaneously but yet independently based on different electrical responses.

Wearable smart sensor systems integrated on soft contact lenses for wireless ocular diagnostics

NASA Astrophysics Data System (ADS)

Kim, Joohee; Kim, Minji; Lee, Mi-Sun; Kim, Kukjoo; Ji, Sangyoon; Kim, Yun-Tae; Park, Jihun; Na, Kyungmin; Bae, Kwi-Hyun; Kyun Kim, Hong; Bien, Franklin; Young Lee, Chang; Park, Jang-Ung

2017-04-01

Wearable contact lenses which can monitor physiological parameters have attracted substantial interests due to the capability of direct detection of biomarkers contained in body fluids. However, previously reported contact lens sensors can only monitor a single analyte at a time. Furthermore, such ocular contact lenses generally obstruct the field of vision of the subject. Here, we developed a multifunctional contact lens sensor that alleviates some of these limitations since it was developed on an actual ocular contact lens. It was also designed to monitor glucose within tears, as well as intraocular pressure using the resistance and capacitance of the electronic device. Furthermore, in-vivo and in-vitro tests using a live rabbit and bovine eyeball demonstrated its reliable operation. Our developed contact lens sensor can measure the glucose level in tear fluid and intraocular pressure simultaneously but yet independently based on different electrical responses.

Recent progress of flexible and wearable strain sensors for human-motion monitoring

NASA Astrophysics Data System (ADS)

Ge, Gang; Huang, Wei; Shao, Jinjun; Dong, Xiaochen

2018-01-01

With the rapid development of human artificial intelligence and the inevitably expanding markets, the past two decades have witnessed an urgent demand for the flexible and wearable devices, especially the flexible strain sensors. Flexible strain sensors, incorporated the merits of stretchability, high sensitivity and skin-mountable, are emerging as an extremely charming domain in virtue of their promising applications in artificial intelligent realms, human-machine systems and health-care devices. In this review, we concentrate on the transduction mechanisms, building blocks of flexible physical sensors, subsequently property optimization in terms of device structures and sensing materials in the direction of practical applications. Perspectives on the existing challenges are also highlighted in the end. Project supported by the NNSF of China (Nos. 61525402, 61604071), the Key University Science Research Project of Jiangsu Province (No. 15KJA430006), and the Natural Science Foundation of Jiangsu Province (No. BK20161012).

On the Comparison of Wearable Sensor Data Fusion to a Single Sensor Machine Learning Technique in Fall Detection.

PubMed

Tsinganos, Panagiotis; Skodras, Athanassios

2018-02-14

In the context of the ageing global population, researchers and scientists have tried to find solutions to many challenges faced by older people. Falls, the leading cause of injury among elderly, are usually severe enough to require immediate medical attention; thus, their detection is of primary importance. To this effect, many fall detection systems that utilize wearable and ambient sensors have been proposed. In this study, we compare three newly proposed data fusion schemes that have been applied in human activity recognition and fall detection. Furthermore, these algorithms are compared to our recent work regarding fall detection in which only one type of sensor is used. The results show that fusion algorithms differ in their performance, whereas a machine learning strategy should be preferred. In conclusion, the methods presented and the comparison of their performance provide useful insights into the problem of fall detection.

Soft bio-integrated systems for continuous health monitoring

NASA Astrophysics Data System (ADS)

Raj, M.; Wei, P. H.; Morey, B.; Wang, X.; Keen, B.; DePetrillo, P.; Hsu, Y. Y.; Ghaffari, R.

2014-06-01

Electronically-enabled wearable systems that monitor physiological activity and electrophysiological activity hold the key to truly personalized medical care outside of the hospital setting. However, fundamental technical challenges exist in achieving medical systems that are comfortable, unobtrusive and fully integrated without external connections to bench top instruments. In particular, there is a fundamental mismatch in mechanical coupling between existing classes of rigid electronics and soft biological substrates, like the skin. Here we describe new mechanical and electrical design strategies for wearable devices with mechanical properties that approach that of biological tissue. These systems exploit stretchable networks of conformal sensors (i.e. electrodes, temperature sensors, and accelerometers) and associated circuitry (i.e. microcontroller, memory, voltage regulators, rechargeable battery, wireless communication modules) embedded in ultrathin, elastomeric substrates. Quantitative analyses of sensor performance and mechanics under tensile and torsional stresses illustrate the ability to mechanically couple with soft tissues in a way that is mechanically invisible to the user. Representative examples of these soft biointegrated systems can be applied for continuous sensing of muscle and movement activity in the home and ambulatory settings.

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.

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

Design, fabrication and metrological evaluation of wearable pressure sensors.

PubMed

Goy, C B; Menichetti, V; Yanicelli, L M; Lucero, J B; López, M A Gómez; Parodi, N F; Herrera, M C

2015-04-01

Pressure sensors are valuable transducers that are necessary in a huge number of medical application. However, the state of the art of compact and lightweight pressure sensors with the capability of measuring the contact pressure between two surfaces (contact pressure sensors) is very poor. In this work, several types of wearable contact pressure sensors are fabricated using different conductive textile materials and piezo-resistive films. The fabricated sensors differ in size, the textile conductor used and/or the number of layers of the sandwiched piezo-resistive film. The intention is to study, through the obtaining of their calibration curves, their metrological properties (repeatability, sensitivity and range) and determine which physical characteristics improve their ability for measuring contact pressures. It has been found that it is possible to obtain wearable contact pressure sensors through the proposed fabrication process with satisfactory repeatability, range and sensitivity; and that some of these properties can be improved by the physical characteristics of the sensors.

Detection of vapor-phase organophosphate threats using wearable conformable integrated epidermal and textile wireless biosensor systems.

PubMed

Mishra, Rupesh K; Martín, Aida; Nakagawa, Tatsuo; Barfidokht, Abbas; Lu, Xialong; Sempionatto, Juliane R; Lyu, Kay Mengjia; Karajic, Aleksandar; Musameh, Mustafa M; Kyratzis, Ilias L; Wang, Joseph

2018-03-15

Flexible epidermal tattoo and textile-based electrochemical biosensors have been developed for vapor-phase detection of organophosphorus (OP) nerve agents. These new wearable sensors, based on stretchable organophosphorus hydrolase (OPH) enzyme electrodes, are coupled with a fully integrated conformal flexible electronic interface that offers rapid and selective square-wave voltammetric detection of OP vapor threats and wireless data transmission to a mobile device. The epidermal tattoo and textile sensors display a good reproducibility (with RSD of 2.5% and 4.2%, respectively), along with good discrimination against potential interferences and linearity over the 90-300mg/L range, with a sensitivity of 10.7µA∙cm 3 ∙mg -1 (R 2 = 0.983) and detection limit of 12mg/L in terms of OP air density. Stress-enduring inks, used for printing the electrode transducers, ensure resilience against mechanical deformations associated with textile and skin-based on-body sensing operations. Theoretical simulations are used to estimate the OP air density over the sensor surface. These fully integrated wearable wireless tattoo and textile-based nerve-agent vapor biosensor systems offer considerable promise for rapid warning regarding personal exposure to OP nerve-agent vapors in variety of decentralized security applications. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

A wearable 12-lead ECG acquisition system with fabric electrodes.

PubMed

Haoshi Zhang; Lan Tian; Huiyang Lu; Ming Zhou; Haiqing Zou; Peng Fang; Fuan Yao; Guanglin Li

2017-07-01

Continuous electrocardiogram (ECG) monitoring is significant for prevention of heart disease and is becoming an important part of personal and family health care. In most of the existing wearable solutions, conventional metal sensors and corresponding chips are simply integrated into clothes and usually could only collect few leads of ECG signals that could not provide enough information for diagnosis of cardiac diseases such as arrhythmia and myocardial ischemia. In this study, a wearable 12-lead ECG acquisition system with fabric electrodes was developed and could simultaneously process 12 leads of ECG signals. By integrating the fabric electrodes into a T-shirt, the wearable system would provide a comfortable and convenient user interface for ECG recording. For comparison, the proposed fabric electrode and the gelled traditional metal electrodes were used to collect ECG signals on a subject, respectively. The approximate entropy (ApEn) of ECG signals from both types of electrodes were calculated. The experimental results show that the fabric electrodes could achieve similar performance as the gelled metal electrodes. This preliminary work has demonstrated that the developed ECG system with fabric electrodes could be utilized for wearable health management and telemedicine applications.

Position Tracking During Human Walking Using an Integrated Wearable Sensing System.

PubMed

Zizzo, Giulio; Ren, Lei

2017-12-10

Progress has been made enabling expensive, high-end inertial measurement units (IMUs) to be used as tracking sensors. However, the cost of these IMUs is prohibitive to their widespread use, and hence the potential of low-cost IMUs is investigated in this study. A wearable low-cost sensing system consisting of IMUs and ultrasound sensors was developed. Core to this system is an extended Kalman filter (EKF), which provides both zero-velocity updates (ZUPTs) and Heuristic Drift Reduction (HDR). The IMU data was combined with ultrasound range measurements to improve accuracy. When a map of the environment was available, a particle filter was used to impose constraints on the possible user motions. The system was therefore composed of three subsystems: IMUs, ultrasound sensors, and a particle filter. A Vicon motion capture system was used to provide ground truth information, enabling validation of the sensing system. Using only the IMU, the system showed loop misclosure errors of 1% with a maximum error of 4-5% during walking. The addition of the ultrasound sensors resulted in a 15% reduction in the total accumulated error. Lastly, the particle filter was capable of providing noticeable corrections, which could keep the tracking error below 2% after the first few steps.

Toward wearable sensors: optical sensor for detection of ammonium nitrate-based explosives, ANFO and ANNM.

PubMed

Sheykhi, Sara; Mosca, Lorenzo; Anzenbacher, Pavel

2017-05-04

Increasing security needs require compact and portable detection tools for the rapid and reliable identification of explosives used in improvised explosive devices (IEDs). We report of an easy-to-use optical sensor for both vapour-phase and solution-phase identification of explosive mixtures that uses a cross-reactive fluorimetric sensor array comprising chemically responsive fluorimetric indicators composed of aromatic aldehydes and polyethyleneimine. Ammonium nitrate-nitromethane (ANNM) was analyzed by paper microzone arrays and nanofiber sensor mats. Progress toward wearable sensors based on electrospun nanofiber mats is outlined.

Analysis of Public Datasets for Wearable Fall Detection Systems.

PubMed

Casilari, Eduardo; Santoyo-Ramón, José-Antonio; Cano-García, José-Manuel

2017-06-27

Due to the boom of wireless handheld devices such as smartwatches and smartphones, wearable Fall Detection Systems (FDSs) have become a major focus of attention among the research community during the last years. The effectiveness of a wearable FDS must be contrasted against a wide variety of measurements obtained from inertial sensors during the occurrence of falls and Activities of Daily Living (ADLs). In this regard, the access to public databases constitutes the basis for an open and systematic assessment of fall detection techniques. This paper reviews and appraises twelve existing available data repositories containing measurements of ADLs and emulated falls envisaged for the evaluation of fall detection algorithms in wearable FDSs. The analysis of the found datasets is performed in a comprehensive way, taking into account the multiple factors involved in the definition of the testbeds deployed for the generation of the mobility samples. The study of the traces brings to light the lack of a common experimental benchmarking procedure and, consequently, the large heterogeneity of the datasets from a number of perspectives (length and number of samples, typology of the emulated falls and ADLs, characteristics of the test subjects, features and positions of the sensors, etc.). Concerning this, the statistical analysis of the samples reveals the impact of the sensor range on the reliability of the traces. In addition, the study evidences the importance of the selection of the ADLs and the need of categorizing the ADLs depending on the intensity of the movements in order to evaluate the capability of a certain detection algorithm to discriminate falls from ADLs.

Analysis of Public Datasets for Wearable Fall Detection Systems

PubMed Central

Santoyo-Ramón, José-Antonio; Cano-García, José-Manuel

2017-01-01

Due to the boom of wireless handheld devices such as smartwatches and smartphones, wearable Fall Detection Systems (FDSs) have become a major focus of attention among the research community during the last years. The effectiveness of a wearable FDS must be contrasted against a wide variety of measurements obtained from inertial sensors during the occurrence of falls and Activities of Daily Living (ADLs). In this regard, the access to public databases constitutes the basis for an open and systematic assessment of fall detection techniques. This paper reviews and appraises twelve existing available data repositories containing measurements of ADLs and emulated falls envisaged for the evaluation of fall detection algorithms in wearable FDSs. The analysis of the found datasets is performed in a comprehensive way, taking into account the multiple factors involved in the definition of the testbeds deployed for the generation of the mobility samples. The study of the traces brings to light the lack of a common experimental benchmarking procedure and, consequently, the large heterogeneity of the datasets from a number of perspectives (length and number of samples, typology of the emulated falls and ADLs, characteristics of the test subjects, features and positions of the sensors, etc.). Concerning this, the statistical analysis of the samples reveals the impact of the sensor range on the reliability of the traces. In addition, the study evidences the importance of the selection of the ADLs and the need of categorizing the ADLs depending on the intensity of the movements in order to evaluate the capability of a certain detection algorithm to discriminate falls from ADLs. PMID:28653991

A Study on Secure Medical-Contents Strategies with DRM Based on Cloud Computing

PubMed Central

Měsíček, Libor; Choi, Jongsun

2018-01-01

Many hospitals and medical clinics have been using a wearable sensor in its health care system because the wearable sensor, which is able to measure the patients' biometric information, has been developed to analyze their patients remotely. The measured information is saved to a server in a medical center, and the server keeps the medical information, which also involves personal information, on a cloud system. The server and network devices are used by connecting each other, and sensitive medical records are dealt with remotely. However, these days, the attackers, who try to attack the server or the network systems, are increasing. In addition, the server and the network system have a weak protection and security policy against the attackers. In this paper, it is suggested that security compliance of medical contents should be followed to improve the level of security. As a result, the medical contents are kept safely. PMID:29796233

A Study on Secure Medical-Contents Strategies with DRM Based on Cloud Computing.

PubMed

Ko, Hoon; Měsíček, Libor; Choi, Jongsun; Hwang, Seogchan

2018-01-01

Many hospitals and medical clinics have been using a wearable sensor in its health care system because the wearable sensor, which is able to measure the patients' biometric information, has been developed to analyze their patients remotely. The measured information is saved to a server in a medical center, and the server keeps the medical information, which also involves personal information, on a cloud system. The server and network devices are used by connecting each other, and sensitive medical records are dealt with remotely. However, these days, the attackers, who try to attack the server or the network systems, are increasing. In addition, the server and the network system have a weak protection and security policy against the attackers. In this paper, it is suggested that security compliance of medical contents should be followed to improve the level of security. As a result, the medical contents are kept safely.

Wireless Power Transfer for Autonomous Wearable Neurotransmitter Sensors.

PubMed

Nguyen, Cuong M; Kota, Pavan Kumar; Nguyen, Minh Q; Dubey, Souvik; Rao, Smitha; Mays, Jeffrey; Chiao, J-C

2015-09-23

In this paper, we report a power management system for autonomous and real-time monitoring of the neurotransmitter L-glutamate (L-Glu). A low-power, low-noise, and high-gain recording module was designed to acquire signal from an implantable flexible L-Glu sensor fabricated by micro-electro-mechanical system (MEMS)-based processes. The wearable recording module was wirelessly powered through inductive coupling transmitter antennas. Lateral and angular misalignments of the receiver antennas were resolved by using a multi-transmitter antenna configuration. The effective coverage, over which the recording module functioned properly, was improved with the use of in-phase transmitter antennas. Experimental results showed that the recording system was capable of operating continuously at distances of 4 cm, 7 cm and 10 cm. The wireless power management system reduced the weight of the recording module, eliminated human intervention and enabled animal experimentation for extended durations.

Wireless Power Transfer for Autonomous Wearable Neurotransmitter Sensors

PubMed Central

Nguyen, Cuong M.; Kota, Pavan Kumar; Nguyen, Minh Q.; Dubey, Souvik; Rao, Smitha; Mays, Jeffrey; Chiao, J.-C.

2015-01-01

In this paper, we report a power management system for autonomous and real-time monitoring of the neurotransmitter L-glutamate (L-Glu). A low-power, low-noise, and high-gain recording module was designed to acquire signal from an implantable flexible L-Glu sensor fabricated by micro-electro-mechanical system (MEMS)-based processes. The wearable recording module was wirelessly powered through inductive coupling transmitter antennas. Lateral and angular misalignments of the receiver antennas were resolved by using a multi-transmitter antenna configuration. The effective coverage, over which the recording module functioned properly, was improved with the use of in-phase transmitter antennas. Experimental results showed that the recording system was capable of operating continuously at distances of 4 cm, 7 cm and 10 cm. The wireless power management system reduced the weight of the recording module, eliminated human intervention and enabled animal experimentation for extended durations. PMID:26404311

The Baetylus Theorem—the central disconnect driving consumer behavior and investment returns in Wearable Technologies

PubMed Central

Levine, James A.

2016-01-01

The Wearable Technology market may increase fivefold by the end of the decade. There is almost no academic investigation as to what drives the investment hypothesis in wearable technologies. This paper seeks to examine this issue from an evidence-based perspective. There is a fundamental disconnect in how consumers view wearable sensors and how companies market them; this is called The Baetylus Theorem where people believe (falsely) that by buying a wearable sensor they will receive health benefit; data suggest that this is not the case. This idea is grounded social constructs, psychological theories and marketing approaches. A marketing proposal that fails to recognize The Baetylus Theorem and how it can be integrated into a business offering has not optimized its competitive advantage. More importantly, consumers should not falsely believe that purchasing a wearable technology, improves health. PMID:27617162

The Baetylus Theorem-the central disconnect driving consumer behavior and investment returns in Wearable Technologies.

PubMed

Levine, James A

2016-08-01

The Wearable Technology market may increase fivefold by the end of the decade. There is almost no academic investigation as to what drives the investment hypothesis in wearable technologies. This paper seeks to examine this issue from an evidence-based perspective. There is a fundamental disconnect in how consumers view wearable sensors and how companies market them; this is called The Baetylus Theorem where people believe (falsely) that by buying a wearable sensor they will receive health benefit; data suggest that this is not the case. This idea is grounded social constructs, psychological theories and marketing approaches. A marketing proposal that fails to recognize The Baetylus Theorem and how it can be integrated into a business offering has not optimized its competitive advantage. More importantly, consumers should not falsely believe that purchasing a wearable technology, improves health.

Highly ordered nanowire arrays on plastic substrates for ultrasensitive flexible chemical sensors.

PubMed

McAlpine, Michael C; Ahmad, Habib; Wang, Dunwei; Heath, James R

2007-05-01

The development of a robust method for integrating high-performance semiconductors on flexible plastics could enable exciting avenues in fundamental research and novel applications. One area of vital relevance is chemical and biological sensing, which if implemented on biocompatible substrates, could yield breakthroughs in implantable or wearable monitoring systems. Semiconducting nanowires (and nanotubes) are particularly sensitive chemical sensors because of their high surface-to-volume ratios. Here, we present a scalable and parallel process for transferring hundreds of pre-aligned silicon nanowires onto plastic to yield highly ordered films for low-power sensor chips. The nanowires are excellent field-effect transistors, and, as sensors, exhibit parts-per-billion sensitivity to NO2, a hazardous pollutant. We also use SiO2 surface chemistries to construct a 'nano-electronic nose' library, which can distinguish acetone and hexane vapours via distributed responses. The excellent sensing performance coupled with bendable plastic could open up opportunities in portable, wearable or even implantable sensors.

Highly ordered nanowire arrays on plastic substrates for ultrasensitive flexible chemical sensors

NASA Astrophysics Data System (ADS)

McAlpine, Michael C.; Ahmad, Habib; Wang, Dunwei; Heath, James R.

2007-05-01

The development of a robust method for integrating high-performance semiconductors on flexible plastics could enable exciting avenues in fundamental research and novel applications. One area of vital relevance is chemical and biological sensing, which if implemented on biocompatible substrates, could yield breakthroughs in implantable or wearable monitoring systems. Semiconducting nanowires (and nanotubes) are particularly sensitive chemical sensors because of their high surface-to-volume ratios. Here, we present a scalable and parallel process for transferring hundreds of pre-aligned silicon nanowires onto plastic to yield highly ordered films for low-power sensor chips. The nanowires are excellent field-effect transistors, and, as sensors, exhibit parts-per-billion sensitivity to NO2, a hazardous pollutant. We also use SiO2 surface chemistries to construct a `nano-electronic nose' library, which can distinguish acetone and hexane vapours via distributed responses. The excellent sensing performance coupled with bendable plastic could open up opportunities in portable, wearable or even implantable sensors.

Highly ordered nanowire arrays on plastic substrates for ultrasensitive flexible chemical sensors

PubMed Central

McAlpine, Michael C.; Ahmad, Habib; Wang, Dunwei; Heath, James R.

2013-01-01

The development of a robust method for integrating high-performance semiconductors on flexible plastics could enable exciting avenues in fundamental research and novel applications. One area of vital relevance is chemical and biological sensing, which if implemented on biocompatible substrates, could yield breakthroughs in implantable or wearable monitoring systems. Semiconducting nanowires (and nanotubes) are particularly sensitive chemical sensors because of their high surface-to-volume ratios. Here, we present a scalable and parallel process for transferring hundreds of pre-aligned silicon nanowires onto plastic to yield highly ordered films for low-power sensor chips. The nanowires are excellent field-effect transistors, and, as sensors, exhibit parts-per-billion sensitivity to NO2, a hazardous pollutant. We also use SiO2 surface chemistries to construct a ‘nano-electronic nose’ library, which can distinguish acetone and hexane vapours via distributed responses. The excellent sensing performance coupled with bendable plastic could open up opportunities in portable, wearable or even implantable sensors. PMID:17450146

Assessment of Lower Limb Prosthesis through Wearable Sensors and Thermography

PubMed Central

Cutti, Andrea Giovanni; Perego, Paolo; Fusca, Marcello C.; Sacchetti, Rinaldo; Andreoni, Giuseppe

2014-01-01

This study aimed to explore the application of infrared thermography in combination with ambulatory wearable monitoring of temperature and relative humidity, to assess the residual limb-to-liner interface in lower-limb prosthesis users. Five male traumatic transtibial amputees were involved, who reported no problems or discomfort while wearing the prosthesis. A thermal imaging camera was used to measure superficial thermal distribution maps of the stump. A wearable system for recording the temperature and relative humidity in up to four anatomical points was developed, tested in vitro and integrated with the measurement set. The parallel application of an infrared camera and wearable sensors provided complementary information. Four main Regions of Interest were identified on the stump (inferior patella, lateral/medial epicondyles, tibial tuberosity), with good inter-subject repeatability. An average increase of 20% in hot areas (P < 0.05) is shown after walking compared to resting conditions. The sensors inside the cuff did not provoke any discomfort during recordings and provide an inside of the thermal exchanges while walking and recording the temperature increase (a regime value is ∼+1.1 ± 0.7 °C) and a more significant one (∼+4.1 ± 2.3%) in humidity because of the sweat produced. This study has also begun the development of a reference data set for optimal socket/liner-stump construction. PMID:24618782

Nano-enabled sensors, electronics and energy source on polymer, paper and thread substrates

NASA Astrophysics Data System (ADS)

Mostafalu, Pooria

Over the past decades, design and development of portable devices for monitoring of biomarkers especially for at risk patients is receiving considerable attention. These devices are either single use diagnostic platforms, wearable on body or on fabric, or they are implanted close to the tissue and organ that it monitors and cures. Sensors, energy sources, and data acquisition devices are the main components of a such monitoring platform. Sensors collect the information using bio-recognition tools such as enzymes and antibodies. Then, the transducers (electrodes, fluorophore, etc) convert it to the appropriate format, for instance electrical and optical signals. After that, data acquisition system amplifies and digitizes the signal and transfers the data to the recording instruments for further processing. Moreover, energy sources are necessary for powering the sensors and electronics. In wearable and implantable applications, these devices need to be flexible, light weight and biocompatible, and their performance should be similar to their rigid counterparts. In this dissertation we address these requirement for wearable and implantable devices. We showed integrated sensors, electronics, and energy sources on flexible polymers, paper, and thread. These devices provide many advantages for monitoring of the physiological condition of a patient and treatment accordingly. Real-time capability of the platform was enabled using wireless telemetry. One of the major innovations of this dissertation is the use of thread as a substrate for making medical diagnostic devices. While conventional substrates (glass, silicon, polyimide, PDMS etc) hold great promise for making wearable and implantable devices, their overall structure and form has remained essentially two dimensional, limiting their function to tissue surfaces such as skin. However, the ability to integrate functional components such as sensors, actuators, and electronics in a way that they penetrate multiple layers of tissues in a 3D topology would be a significant surgical advance. We have devised an integrated thread-based diagnostic (TDD) system with the ability to measure physical (strain and temperature) and chemical (pH and glucose) markers in the body in vivo. Such device was made from threads, which have been widely used in the apparel industry and is readily available as a low-cost biocompatible material.

Unraveling fabrication and calibration of wearable gas monitor for use under free-living conditions.

PubMed

Yue Deng; Cheng Chen; Tsow, Francis; Xiaojun Xian; Forzani, Erica

2016-08-01

Volatile organic compounds (VOC) are organic chemicals that have high vapor pressure at regular conditions. Some VOC could be dangerous to human health, therefore it is important to determine real-time indoor and outdoor personal exposures to VOC. To achieve this goal, our group has developed a wearable gas monitor with a complete sensor fabrication and calibration protocol for free-living conditions. Correction factors for calibrating the sensors, including sensitivity, aging effect, and temperature effect are implemented into a Quick Response Code (QR code), so that the pre-calibrated quartz tuning fork (QTF) sensor can be used with the wearable monitor under free-living conditions.

Physiological parameters monitoring of fire-fighters by means of a wearable wireless sensor system

NASA Astrophysics Data System (ADS)

Stelios, M.; Mitilineos, Stelios A.; Chatzistamatis, Panagiotis; Vassiliadis, Savvas; Primentas, Antonios; Kogias, Dimitris; Michailidis, Emmanouel T.; Rangoussi, Maria; Kurşun Bahadir, Senem; Atalay, Özgür; Kalaoğlu, Fatma; Sağlam, Yusuf

2016-03-01

Physiological parameter monitoring may be useful in many different groups of the population, such as infants, elderly people, athletes, soldiers, drivers, fire-fighters, police etc. This can provide a variety of information ranging from health status to operational readiness. In this article, we focus on the case of first responders and specifically fire-fighters. Firefighters can benefit from a physiological monitoring system that is used to extract multiple indications such as the present position, the possible life risk level, the stress level etc. This work presents a wearable wireless sensor network node, based on low cost, commercial-off- the-self (COTS) electronic modules, which can be easily attached on a standard fire-fighters’ uniform. Due to the low frequency wired interface between the selected electronic components, the proposed solution can be used as a basis for a textile system where all wired connections will be implemented by means of conductive yarn routing in the textile structure, while some of the standard sensors can be replaced by textile ones. System architecture is described in detail, while indicative samples of acquired signals are also presented.

Recommendations for Assessment of the Reliability, Sensitivity, and Validity of Data Provided by Wearable Sensors Designed for Monitoring Physical Activity.

PubMed

Düking, Peter; Fuss, Franz Konstantin; Holmberg, Hans-Christer; Sperlich, Billy

2018-04-30

Although it is becoming increasingly popular to monitor parameters related to training, recovery, and health with wearable sensor technology (wearables), scientific evaluation of the reliability, sensitivity, and validity of such data is limited and, where available, has involved a wide variety of approaches. To improve the trustworthiness of data collected by wearables and facilitate comparisons, we have outlined recommendations for standardized evaluation. We discuss the wearable devices themselves, as well as experimental and statistical considerations. Adherence to these recommendations should be beneficial not only for the individual, but also for regulatory organizations and insurance companies. ©Peter Düking, Franz Konstantin Fuss, Hans-Christer Holmberg, Billy Sperlich. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 30.04.2018.

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.

Unmanned Ground Vehicles for Integrated Force Protection

DTIC Science & Technology

2004-04-01

employed. 2 Force Protection 18 MAR 02 Security Posts Squad Laptop Fire Tm Ldr Wearable Computers OP/LP Def Fight Psn SRT Sensors USA, USMC, Allied...visual systems. Attaching sensors and response devices on a monorail proved to be much more technically challenging than expected. Film producers and...facilitate experimentation with weapon aiming and firing techniques from the MRHA. grated Marsupial Delivery System was developed to transport smaller

Performance of a wearable acoustic system for fetal movement discrimination

PubMed Central

Lai, Jonathan; Woodward, Richard; Alexandrov, Yuriy; ain Munnee, Qurratul; Lees, Christoph C.

2018-01-01

Fetal movements (FM) are a key factor in clinical management of high-risk pregnancies such as fetal growth restriction. While maternal perception of reduced FM can trigger self-referral to obstetric services, maternal sensation is highly subjective. Objective, reliable monitoring of fetal movement patterns outside clinical environs is not currently possible. A wearable and non-transmitting system capable of sensing fetal movements over extended periods of time would be extremely valuable, not only for monitoring individual fetal health, but also for establishing normal levels of movement in the population at large. Wearable monitors based on accelerometers have previously been proposed as a means of tracking FM, but such systems have difficulty separating maternal and fetal activity and have not matured to the level of clinical use. We introduce a new wearable system based on a novel combination of accelerometers and bespoke acoustic sensors as well as an advanced signal processing architecture to identify and discriminate between types of fetal movements. We validate the system with concurrent ultrasound tests on a cohort of 44 pregnant women and demonstrate that the garment is capable of both detecting and discriminating the vigorous, whole-body ‘startle’ movements of a fetus. These results demonstrate the promise of multimodal sensing for the development of a low-cost, non-transmitting wearable monitor for fetal movements. PMID:29734344

Performance of a wearable acoustic system for fetal movement discrimination.

PubMed

Lai, Jonathan; Woodward, Richard; Alexandrov, Yuriy; Ain Munnee, Qurratul; Lees, Christoph C; Vaidyanathan, Ravi; Nowlan, Niamh C

2018-01-01

Fetal movements (FM) are a key factor in clinical management of high-risk pregnancies such as fetal growth restriction. While maternal perception of reduced FM can trigger self-referral to obstetric services, maternal sensation is highly subjective. Objective, reliable monitoring of fetal movement patterns outside clinical environs is not currently possible. A wearable and non-transmitting system capable of sensing fetal movements over extended periods of time would be extremely valuable, not only for monitoring individual fetal health, but also for establishing normal levels of movement in the population at large. Wearable monitors based on accelerometers have previously been proposed as a means of tracking FM, but such systems have difficulty separating maternal and fetal activity and have not matured to the level of clinical use. We introduce a new wearable system based on a novel combination of accelerometers and bespoke acoustic sensors as well as an advanced signal processing architecture to identify and discriminate between types of fetal movements. We validate the system with concurrent ultrasound tests on a cohort of 44 pregnant women and demonstrate that the garment is capable of both detecting and discriminating the vigorous, whole-body 'startle' movements of a fetus. These results demonstrate the promise of multimodal sensing for the development of a low-cost, non-transmitting wearable monitor for fetal movements.

Wearable Environmental and Physiological Sensing Unit

NASA Technical Reports Server (NTRS)

Spremo, Stevan; Ahlman, Jim; Stricker, Ed; Santos, Elmer

2007-01-01

The wearable environmental and physiological sensing unit (WEPS) is a prototype of systems to be worn by emergency workers (e.g., firefighters and members of hazardous-material response teams) to increase their level of safety. The WEPS includes sensors that measure a few key physiological and environmental parameters, a microcontroller unit that processes the digitized outputs of the sensors, and a radio transmitter that sends the processed sensor signals to a computer in a mobile command center for monitoring by a supervisor. The monitored parameters serve as real-time indications of the wearer s physical condition and level of activity, and of the degree and type of danger posed by the wearer s environment. The supervisor could use these indications to determine, for example, whether the wearer should withdraw in the face of an increasing hazard or whether the wearer should be rescued.

Study of Wearable Knee Assistive Instruments for Walk Rehabilitation

NASA Astrophysics Data System (ADS)

Zhu, Yong; Nakamura, Masahiro; Ito, Noritaka; Fujimoto, Hiroshi; Horikuchi, Kenichi; Wakabayashi, Shojiro; Takahashi, Rei; Terada, Hidetsugu; Haro, Hirotaka

A wearable Knee Assistive Instrument for the walk rehabilitation was newly developed. Especially, this system aimed at supporting the rehabilitation for the post-TKA (Total Knee Arthroplasty) which is a popular surgery for aging people. This system consisted of an assisting mechanism for the knee joint, a hip joint support system and a foot pressure sensor system. The driving system of this robot consisted of a CPU board which generated the walking pattern, a Li-ion battery, DC motors with motor drivers, contact sensors to detect the state of foot and potentiometers to detect the hip joint angle. The control method was proposed to reproduce complex motion of knee joint as much as possible, and to increase hip or knee flexion angle. Especially, this method used the timing that heel left from the floor. This method included that the lower limb was raised to prevent a subject's fall. Also, the prototype of knee assisting system was tested. It was confirmed that the assisting system is useful.

Toward a Fault Tolerant Architecture for Vital Medical-Based Wearable Computing.

PubMed

Abdali-Mohammadi, Fardin; Bajalan, Vahid; Fathi, Abdolhossein

2015-12-01

Advancements in computers and electronic technologies have led to the emergence of a new generation of efficient small intelligent systems. The products of such technologies might include Smartphones and wearable devices, which have attracted the attention of medical applications. These products are used less in critical medical applications because of their resource constraint and failure sensitivity. This is due to the fact that without safety considerations, small-integrated hardware will endanger patients' lives. Therefore, proposing some principals is required to construct wearable systems in healthcare so that the existing concerns are dealt with. Accordingly, this paper proposes an architecture for constructing wearable systems in critical medical applications. The proposed architecture is a three-tier one, supporting data flow from body sensors to cloud. The tiers of this architecture include wearable computers, mobile computing, and mobile cloud computing. One of the features of this architecture is its high possible fault tolerance due to the nature of its components. Moreover, the required protocols are presented to coordinate the components of this architecture. Finally, the reliability of this architecture is assessed by simulating the architecture and its components, and other aspects of the proposed architecture are discussed.

UHF wearable battery free sensor module for activity and falling detection.

PubMed

Nam Trung Dang; Thang Viet Tran; Wan-Young Chung

2016-08-01

Falling is one of the most serious medical and social problems in aging population. Therefore taking care of the elderly by detecting activity and falling for preventing and mitigating the injuries caused by falls needs to be concerned. This study proposes a wearable, wireless, battery free ultra-high frequency (UHF) smart sensor tag module for falling and activity detection. The proposed tag is powered by UHF RF wave from reader and read by a standard UHF Electronic Product Code (EPC) Class-1 Generation-2 reader. The battery free sensor module could improve the wearability of the wireless device. The combination of accelerometer signal and received signal strength indication (RSSI) from a reader in the passive smart sensor tag detect the activity and falling of the elderly very successfully. The fabricated smart sensor tag module has an operating range of up to 2.5m and conducting in real-time activity and falling detection.

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

Assessment of Haptic Interaction for Home-Based Physical Tele-Therapy using Wearable Devices and Depth Sensors.

PubMed

Barmpoutis, Angelos; Alzate, Jose; Beekhuizen, Samantha; Delgado, Horacio; Donaldson, Preston; Hall, Andrew; Lago, Charlie; Vidal, Kevin; Fox, Emily J

2016-01-01

In this paper a prototype system is presented for home-based physical tele-therapy using a wearable device for haptic feedback. The haptic feedback is generated as a sequence of vibratory cues from 8 vibrator motors equally spaced along an elastic wearable band. The motors guide the patients' movement as they perform a prescribed exercise routine in a way that replaces the physical therapists' haptic guidance in an unsupervised or remotely supervised home-based therapy session. A pilot study of 25 human subjects was performed that focused on: a) testing the capability of the system to guide the users in arbitrary motion paths in the space and b) comparing the motion of the users during typical physical therapy exercises with and without haptic-based guidance. The results demonstrate the efficacy of the proposed system.

Wearable Health Monitoring Systems

NASA Technical Reports Server (NTRS)

Bell, John

2015-01-01

The shrinking size and weight of electronic circuitry has given rise to a new generation of smart clothing that enables biological data to be measured and transmitted. As the variation in the number and type of deployable devices and sensors increases, technology must allow their seamless integration so they can be electrically powered, operated, and recharged over a digital pathway. Nyx Illuminated Clothing Company has developed a lightweight health monitoring system that integrates medical sensors, electrodes, electrical connections, circuits, and a power supply into a single wearable assembly. The system is comfortable, bendable in three dimensions, durable, waterproof, and washable. The innovation will allow astronaut health monitoring in a variety of real-time scenarios, with data stored in digital memory for later use in a medical database. Potential commercial uses are numerous, as the technology enables medical personnel to noninvasively monitor patient vital signs in a multitude of health care settings and applications.

A review of wearable technology in medicine.

PubMed

Iqbal, Mohammed H; Aydin, Abdullatif; Brunckhorst, Oliver; Dasgupta, Prokar; Ahmed, Kamran

2016-10-01

With rapid advances in technology, wearable devices have evolved and been adopted for various uses, ranging from simple devices used in aiding fitness to more complex devices used in assisting surgery. Wearable technology is broadly divided into head-mounted displays and body sensors. A broad search of the current literature revealed a total of 13 different body sensors and 11 head-mounted display devices. The latter have been reported for use in surgery (n = 7), imaging (n = 3), simulation and education (n = 2) and as navigation tools (n = 1). Body sensors have been used as vital signs monitors (n = 9) and for posture-related devices for posture and fitness (n = 4). Body sensors were found to have excellent functionality in aiding patient posture and rehabilitation while head-mounted displays can provide information to surgeons to while maintaining sterility during operative procedures. There is a potential role for head-mounted wearable technology and body sensors in medicine and patient care. However, there is little scientific evidence available proving that the application of such technologies improves patient satisfaction or care. Further studies need to be conducted prior to a clear conclusion. © The Royal Society of Medicine.

An RF-based wearable sensor system for indoor tracking to facilitate efficient healthcare management.

PubMed

Yuzhe Ouyang; Shan, Kai; Bui, Francis Minhthang

2016-08-01

To understand the utilization of clinical resources and improve the efficiency of healthcare, it is often necessary to accurately locate patients and doctors in a healthcare facility. However, existing tracking methods, such as GPS, Wi-Fi and RFID, have technological drawbacks or impose significant costs, thus limiting their applications in many clinical environments, especially those with indoor enclosures. This paper proposes a low-cost and flexible tracking system that is well suited for operating in an indoor environment. Based on readily available RF transceivers and microcontrollers, our wearable sensor system can facilitate locating users (e.g., patients or doctors) or objects (e.g., medical devices) in a building. The strategic construction of the sensor system, along with a suitably designed tracking algorithm, together provide for reliability and dispatch in localization performance. For demonstration purposes, several simplified experiments, with different configurations of the system, are implemented in two testing rooms to assess the baseline performance. From the obtained results, our system exhibits immense promise in acquiring a user location and corresponding time-stamp, with high accuracy and rapid response. This capability is conducive to both short- and long-term data analytics, which are crucial for improving healthcare management.

Highly Sensitive Multifilament Fiber Strain Sensors with Ultrabroad Sensing Range for Textile Electronics.

PubMed

Lee, Jaehong; Shin, Sera; Lee, Sanggeun; Song, Jaekang; Kang, Subin; Han, Heetak; Kim, SeulGee; Kim, Seunghoe; Seo, Jungmok; Kim, DaeEun; Lee, Taeyoon

2018-05-22

Highly stretchable fiber strain sensors are one of the most important components for various applications in wearable electronics, electronic textiles, and biomedical electronics. Herein, we present a facile approach for fabricating highly stretchable and sensitive fiber strain sensors by embedding Ag nanoparticles into a stretchable fiber with a multifilament structure. The multifilament structure and Ag-rich shells of the fiber strain sensor enable the sensor to simultaneously achieve both a high sensitivity and largely wide sensing range despite its simple fabrication process and components. The fiber strain sensor simultaneously exhibits ultrahigh gauge factors (∼9.3 × 10 5 and ∼659 in the first stretching and subsequent stretching, respectively), a very broad strain-sensing range (450 and 200% for the first and subsequent stretching, respectively), and high durability for more than 10 000 stretching cycles. The fiber strain sensors can also be readily integrated into a glove to control a hand robot and effectively applied to monitor the large volume expansion of a balloon and a pig bladder for an artificial bladder system, thereby demonstrating the potential of the fiber strain sensors as candidates for electronic textiles, wearable electronics, and biomedical engineering.

Towards a wearable sensor system for continuous occupational cold stress assessment

PubMed Central

AUSTAD, Hanne; WIGGEN, Øystein; FÆREVIK, Hilde; SEEBERG, Trine M.

2018-01-01

This study investigated the usefulness of continuous sensor data for improving occupational cold stress assessment. Eleven volunteer male subjects completed a 90–120-min protocol in cold environments, consisting of rest, moderate and hard work. Biomedical data were measured using a smart jacket with integrated temperature, humidity and activity sensors, in addition to a custom-made sensor belt worn around the chest. Other relevant sensor data were measured using commercially available sensors. The study aimed to improve decision support for workers in cold climates, by taking advantage of the information provided by data from the rapidly growing market of wearable sensors. Important findings were that the subjective thermal sensation did not correspond to the measured absolute skin temperature and that large differences were observed in both metabolic energy production and skin temperatures under identical exposure conditions. Temperature, humidity, activity and heart rate were found to be relevant parameters for cold stress assessment, and the locations of the sensors in the prototype jacket were adequate. The study reveals the need for cold stress assessment and indicates that a generalised approached is not sufficient to assess the stress on an individual level. PMID:29353859

Flexible Graphene-Based Wearable Gas and Chemical Sensors.

PubMed

Singh, Eric; Meyyappan, M; Nalwa, Hari Singh

2017-10-11

Wearable electronics is expected to be one of the most active research areas in the next decade; therefore, nanomaterials possessing high carrier mobility, optical transparency, mechanical robustness and flexibility, lightweight, and environmental stability will be in immense demand. Graphene is one of the nanomaterials that fulfill all these requirements, along with other inherently unique properties and convenience to fabricate into different morphological nanostructures, from atomically thin single layers to nanoribbons. Graphene-based materials have also been investigated in sensor technologies, from chemical sensing to detection of cancer biomarkers. The progress of graphene-based flexible gas and chemical sensors in terms of material preparation, sensor fabrication, and their performance are reviewed here. The article provides a brief introduction to graphene-based materials and their potential applications in flexible and stretchable wearable electronic devices. The role of graphene in fabricating flexible gas sensors for the detection of various hazardous gases, including nitrogen dioxide (NO 2 ), ammonia (NH 3 ), hydrogen (H 2 ), hydrogen sulfide (H 2 S), carbon dioxide (CO 2 ), sulfur dioxide (SO 2 ), and humidity in wearable technology, is discussed. In addition, applications of graphene-based materials are also summarized in detecting toxic heavy metal ions (Cd, Hg, Pb, Cr, Fe, Ni, Co, Cu, Ag), and volatile organic compounds (VOCs) including nitrobenzene, toluene, acetone, formaldehyde, amines, phenols, bisphenol A (BPA), explosives, chemical warfare agents, and environmental pollutants. The sensitivity, selectivity and strategies for excluding interferents are also discussed for graphene-based gas and chemical sensors. The challenges for developing future generation of flexible and stretchable sensors for wearable technology that would be usable for the Internet of Things (IoT) are also highlighted.

Tissue viability monitoring: a multi-sensor wearable platform approach

NASA Astrophysics Data System (ADS)

Mathur, Neha; Davidson, Alan; Buis, Arjan; Glesk, Ivan

2016-12-01

Health services worldwide are seeking ways to improve patient care for amputees suffering from diabetes, and at the same time reduce costs. The monitoring of residual limb temperature, interface pressure and gait can be a useful indicator of tissue viability in lower limb amputees especially to predict the occurrence of pressure ulcers. This is further exacerbated by elevated temperatures and humid micro environment within the prosthesis which encourages the growth of bacteria and skin breakdown. Wearable systems for prosthetic users have to be designed such that the sensors are minimally obtrusive and reliable enough to faithfully record movement and physiological signals. A mobile sensor platform has been developed for use with the lower limb prosthetic users. This system uses an Arduino board that includes sensors for temperature, gait, orientation and pressure measurements. The platform transmits sensor data to a central health authority database server infrastructure through the Bluetooth protocol at a suitable sampling rate. The data-sets recorded using these systems are then processed using machine learning algorithms to extract clinically relevant information from the data. Where a sensor threshold is reached a warning signal can be sent wirelessly together with the relevant data to the patient and appropriate medical personnel. This knowledge is also useful in establishing biomarkers related to a possible deterioration in a patient's health or for assessing the impact of clinical interventions.

What is the Best Configuration of Wearable Sensors to Measure Spatiotemporal Gait Parameters in Children with Cerebral Palsy?

PubMed Central

Carcreff, Lena; Paraschiv-Ionescu, Anisoara; De Coulon, Geraldo; Armand, Stéphane; Aminian, Kamiar

2018-01-01

Wearable inertial devices have recently been used to evaluate spatiotemporal parameters of gait in daily life situations. Given the heterogeneity of gait patterns in children with cerebral palsy (CP), the sensor placement and analysis algorithm may influence the validity of the results. This study aimed at comparing the spatiotemporal measurement performances of three wearable configurations defined by different sensor positioning on the lower limbs: (1) shanks and thighs, (2) shanks, and (3) feet. The three configurations were selected based on their potential to be used in daily life for children with CP and typically developing (TD) controls. For each configuration, dedicated gait analysis algorithms were used to detect gait events and compute spatiotemporal parameters. Fifteen children with CP and 11 TD controls were included. Accuracy, precision, and agreement of the three configurations were determined in comparison with an optoelectronic system as a reference. The three configurations were comparable for the evaluation of TD children and children with a low level of disability (CP-GMFCS I) whereas the shank-and-thigh-based configuration was more robust regarding children with a higher level of disability (CP-GMFCS II–III). PMID:29385700

Video Analysis Verification of Head Impact Events Measured by Wearable Sensors.

PubMed

Cortes, Nelson; Lincoln, Andrew E; Myer, Gregory D; Hepburn, Lisa; Higgins, Michael; Putukian, Margot; Caswell, Shane V

2017-08-01

Wearable sensors are increasingly used to quantify the frequency and magnitude of head impact events in multiple sports. There is a paucity of evidence that verifies head impact events recorded by wearable sensors. To utilize video analysis to verify head impact events recorded by wearable sensors and describe the respective frequency and magnitude. Cohort study (diagnosis); Level of evidence, 2. Thirty male (mean age, 16.6 ± 1.2 years; mean height, 1.77 ± 0.06 m; mean weight, 73.4 ± 12.2 kg) and 35 female (mean age, 16.2 ± 1.3 years; mean height, 1.66 ± 0.05 m; mean weight, 61.2 ± 6.4 kg) players volunteered to participate in this study during the 2014 and 2015 lacrosse seasons. Participants were instrumented with GForceTracker (GFT; boys) and X-Patch sensors (girls). Simultaneous game video was recorded by a trained videographer using a single camera located at the highest midfield location. One-third of the field was framed and panned to follow the ball during games. Videographic and accelerometer data were time synchronized. Head impact counts were compared with video recordings and were deemed valid if (1) the linear acceleration was ≥20 g, (2) the player was identified on the field, (3) the player was in camera view, and (4) the head impact mechanism could be clearly identified. Descriptive statistics of peak linear acceleration (PLA) and peak rotational velocity (PRV) for all verified head impacts ≥20 g were calculated. For the boys, a total recorded 1063 impacts (2014: n = 545; 2015: n = 518) were logged by the GFT between game start and end times (mean PLA, 46 ± 31 g; mean PRV, 1093 ± 661 deg/s) during 368 player-games. Of these impacts, 690 were verified via video analysis (65%; mean PLA, 48 ± 34 g; mean PRV, 1242 ± 617 deg/s). The X-Patch sensors, worn by the girls, recorded a total 180 impacts during the course of the games, and 58 (2014: n = 33; 2015: n = 25) were verified via video analysis (32%; mean PLA, 39 ± 21 g; mean PRV, 1664 ± 619 rad/s). The current data indicate that existing wearable sensor technologies may substantially overestimate head impact events. Further, while the wearable sensors always estimated a head impact location, only 48% of the impacts were a result of direct contact to the head as characterized on video. Using wearable sensors and video to verify head impacts may decrease the inclusion of false-positive impacts during game activity in the analysis.

Detecting Gunshots Using Wearable Accelerometers

PubMed Central

Loeffler, Charles E.

2014-01-01

Gun violence continues to be a staggering and seemingly intractable issue in many communities. The prevalence of gun violence among the sub-population of individuals under court-ordered community supervision provides an opportunity for intervention using remote monitoring technology. Existing monitoring systems rely heavily on location-based monitoring methods, which have incomplete geographic coverage and do not provide information on illegal firearm use. This paper presents the first results demonstrating the feasibility of using wearable inertial sensors to recognize wrist movements and other signals corresponding to firearm usage. Data were collected from accelerometers worn on the wrists of subjects shooting a number of different firearms, conducting routine daily activities, and participating in activities and tasks that could be potentially confused with firearm discharges. A training sample was used to construct a combined detector and classifier for individual gunshots, which achieved a classification accuracy of 99.4 percent when tested against a hold-out sample of observations. These results suggest the feasibility of using inexpensive wearable sensors to detect firearm discharges. PMID:25184416

Detecting gunshots using wearable accelerometers.

PubMed

Loeffler, Charles E

2014-01-01

Gun violence continues to be a staggering and seemingly intractable issue in many communities. The prevalence of gun violence among the sub-population of individuals under court-ordered community supervision provides an opportunity for intervention using remote monitoring technology. Existing monitoring systems rely heavily on location-based monitoring methods, which have incomplete geographic coverage and do not provide information on illegal firearm use. This paper presents the first results demonstrating the feasibility of using wearable inertial sensors to recognize wrist movements and other signals corresponding to firearm usage. Data were collected from accelerometers worn on the wrists of subjects shooting a number of different firearms, conducting routine daily activities, and participating in activities and tasks that could be potentially confused with firearm discharges. A training sample was used to construct a combined detector and classifier for individual gunshots, which achieved a classification accuracy of 99.4 percent when tested against a hold-out sample of observations. These results suggest the feasibility of using inexpensive wearable sensors to detect firearm discharges.

An adaptive Hidden Markov Model for activity recognition based on a wearable multi-sensor device

USDA-ARS?s Scientific Manuscript database

Human activity recognition is important in the study of personal health, wellness and lifestyle. In order to acquire human activity information from the personal space, many wearable multi-sensor devices have been developed. In this paper, a novel technique for automatic activity recognition based o...

Multimodal Teaching Analytics: Automated Extraction of Orchestration Graphs from Wearable Sensor Data

ERIC Educational Resources Information Center

Prieto, L. P.; Sharma, K.; Kidzinski, L.; Rodríguez-Triana, M. J.; Dillenbourg, P.

2018-01-01

The pedagogical modelling of everyday classroom practice is an interesting kind of evidence, both for educational research and teachers' own professional development. This paper explores the usage of wearable sensors and machine learning techniques to automatically extract orchestration graphs (teaching activities and their social plane over time)…

[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.

How honest are the signals? A protocol for validating wearable sensors.

PubMed

Kayhan, Varol Onur; Chen, Zheng Chris; French, Kimberly A; Allen, Tammy D; Salomon, Kristen; Watkins, Alison

2018-02-01

There is growing interest among organizational researchers in tapping into alternative sources of data beyond self-reports to provide a new avenue for measuring behavioral constructs. Use of alternative data sources such as wearable sensors is necessary for developing theory and enhancing organizational practice. Although wearable sensors are now commercially available, the veracity of the data they capture is largely unknown and mostly based on manufacturers' claims. The goal of this research is to test the validity and reliability of data captured by one such wearable badge (by Humanyze) in the context of structured meetings where all individuals wear a badge for the duration of the encounter. We developed a series of studies, each targeting a specific sensor of this badge that is relevant for structured meetings, and we make specific recommendations for badge data usage based on our validation results. We have incorporated the insights from our studies on a website that researchers can use to conduct validation tests for their badges, upload their data, and assess the validity of the data. We discuss this website in the corresponding studies.

Recognizing Academic Performance, Sleep Quality, Stress Level, and Mental Health using Personality Traits, Wearable Sensors and Mobile Phones

PubMed Central

Sano, Akane; Phillips, Andrew J.; Yu, Amy Z.; McHill, Andrew W.; Taylor, Sara; Jaques, Natasha; Czeisler, Charles A.; Klerman, Elizabeth B.; Picard, Rosalind W.

2017-01-01

What can wearable sensors and usage of smart phones tell us about academic performance, self-reported sleep quality, stress and mental health condition? To answer this question, we collected extensive subjective and objective data using mobile phones, surveys, and wearable sensors worn day and night from 66 participants, for 30 days each, totaling 1,980 days of data. We analyzed daily and monthly behavioral and physiological patterns and identified factors that affect academic performance (GPA), Pittsburg Sleep Quality Index (PSQI) score, perceived stress scale (PSS), and mental health composite score (MCS) from SF-12, using these month-long data. We also examined how accurately the collected data classified the participants into groups of high/low GPA, good/poor sleep quality, high/low self-reported stress, high/low MCS using feature selection and machine learning techniques. We found associations among PSQI, PSS, MCS, and GPA and personality types. Classification accuracies using the objective data from wearable sensors and mobile phones ranged from 67–92%. PMID:28516162

A Human-Centered Smart Home System with Wearable-Sensor Behavior Analysis

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

Ji, Jianting; Liu, Ting; Shen, Chao

Smart home has recently attracted much research interest owing to its potential in improving the quality of human life. How to obtain user's demand is the most important and challenging task for appliance optimal scheduling in smart home, since it is highly related to user's unpredictable behavior. In this paper, a human-centered smart home system is proposed to identify user behavior, predict their demand and schedule the household appliances. Firstly, the sensor data from user's wearable devices are monitored to profile user's full-day behavior. Then, the appliance-demand matrix is constructed to predict user's demand on home environment, which is extractedmore » from the history of appliance load data and user behavior. Two simulations are designed to demonstrate user behavior identification, appliance-demand matrix construction and strategy of appliance optimal scheduling generation.« less

The Museum Wearable: Real-Time Sensor-Driven Understanding of Visitors' Interests for Personalized Visually-Augmented Museum Experiences.

ERIC Educational Resources Information Center

Sparacino, Flavia

This paper describes the museum wearable: a wearable computer that orchestrates an audiovisual narration as a function of the visitors' interests gathered from their physical path in the museum and length of stops. The wearable consists of a lightweight and small computer that people carry inside a shoulder pack. It offers an audiovisual…

Variables influencing wearable sensor outcome estimates in individuals with stroke and incomplete spinal cord injury: a pilot investigation validating two research grade sensors.

PubMed

Jayaraman, Chandrasekaran; Mummidisetty, Chaithanya Krishna; Mannix-Slobig, Alannah; McGee Koch, Lori; Jayaraman, Arun

2018-03-13

Monitoring physical activity and leveraging wearable sensor technologies to facilitate active living in individuals with neurological impairment has been shown to yield benefits in terms of health and quality of living. In this context, accurate measurement of physical activity estimates from these sensors are vital. However, wearable sensor manufacturers generally only provide standard proprietary algorithms based off of healthy individuals to estimate physical activity metrics which may lead to inaccurate estimates in population with neurological impairment like stroke and incomplete spinal cord injury (iSCI). The main objective of this cross-sectional investigation was to evaluate the validity of physical activity estimates provided by standard proprietary algorithms for individuals with stroke and iSCI. Two research grade wearable sensors used in clinical settings were chosen and the outcome metrics estimated using standard proprietary algorithms were validated against designated golden standard measures (Cosmed K4B2 for energy expenditure and metabolic equivalent and manual tallying for step counts). The influence of sensor location, sensor type and activity characteristics were also studied. 28 participants (Healthy (n = 10); incomplete SCI (n = 8); stroke (n = 10)) performed a spectrum of activities in a laboratory setting using two wearable sensors (ActiGraph and Metria-IH1) at different body locations. Manufacturer provided standard proprietary algorithms estimated the step count, energy expenditure (EE) and metabolic equivalent (MET). These estimates were compared with the estimates from gold standard measures. For verifying validity, a series of Kruskal Wallis ANOVA tests (Games-Howell multiple comparison for post-hoc analyses) were conducted to compare the mean rank and absolute agreement of outcome metrics estimated by each of the devices in comparison with the designated gold standard measurements. The sensor type, sensor location, activity characteristics and the population specific condition influences the validity of estimation of physical activity metrics using standard proprietary algorithms. Implementing population specific customized algorithms accounting for the influences of sensor location, type and activity characteristics for estimating physical activity metrics in individuals with stroke and iSCI could be beneficial.

HuMOVE: a low-invasive wearable monitoring platform in sexual medicine.

PubMed

Ciuti, Gastone; Nardi, Matteo; Valdastri, Pietro; Menciassi, Arianna; Basile Fasolo, Ciro; Dario, Paolo

2014-10-01

To investigate an accelerometer-based wearable system, named Human Movement (HuMOVE) platform, designed to enable quantitative and continuous measurement of sexual performance with minimal invasiveness and inconvenience for users. Design, implementation, and development of HuMOVE, a wearable platform equipped with an accelerometer sensor for monitoring inertial parameters for sexual performance assessment and diagnosis, were performed. The system enables quantitative measurement of movement parameters during sexual intercourse, meeting the requirements of wearability, data storage, sampling rate, and interfacing methods, which are fundamental for human sexual intercourse performance analysis. HuMOVE was validated through characterization using a controlled experimental test bench and evaluated in a human model during simulated sexual intercourse conditions. HuMOVE demonstrated to be a robust and quantitative monitoring platform and a reliable candidate for sexual performance evaluation and diagnosis. Characterization analysis on the controlled experimental test bench demonstrated an accurate correlation between the HuMOVE system and data from a reference displacement sensor. Experimental tests in the human model during simulated intercourse conditions confirmed the accuracy of the sexual performance evaluation platform and the effectiveness of the selected and derived parameters. The obtained outcomes also established the project expectations in terms of usability and comfort, evidenced by the questionnaires that highlighted the low invasiveness and acceptance of the device. To the best of our knowledge, HuMOVE platform is the first device for human sexual performance analysis compatible with sexual intercourse; the system has the potential to be a helpful tool for physicians to accurately classify sexual disorders, such as premature or delayed ejaculation. Copyright © 2014 Elsevier Inc. All rights reserved.

Usability of a novel digital medicine system in adults with schizophrenia treated with sensor-embedded tablets of aripiprazole.

PubMed

Peters-Strickland, Timothy; Pestreich, Linda; Hatch, Ainslie; Rohatagi, Shashank; Baker, Ross A; Docherty, John P; Markovtsova, Lada; Raja, Praveen; Weiden, Peter J; Walling, David P

2016-01-01

Digital medicine system (DMS) is a novel drug-device combination that objectively measures and reports medication ingestion. The DMS consists of medication embedded with an ingestible sensor (digital medicine), a wearable sensor, and software applications. This study evaluated usability of the DMS in adults with schizophrenia rated by both patients and their health care providers (HCPs) during 8-week treatment with prescribed doses of digital aripiprazole. Six US sites enrolled outpatients into this Phase IIa, open-label study (NCT02219009). The study comprised a screening phase, a training phase (three weekly site visits), and a 5-week independent phase. Patients and HCPs independently rated usability of and satisfaction with the DMS. Sixty-seven patients were enrolled, and 49 (73.1%) patients completed the study. The mean age (SD) of the patients was 46.6 years (9.7 years); the majority of them were male (74.6%), black (76.1%), and rated mildly ill on the Clinical Global Impression - Severity scale (70.1%). By the end of week 8 or early termination, 82.1% (55/67) of patients had replaced the wearable sensor independently or with minimal assistance, based on HCP rating. The patients used the wearable sensor for a mean (SD) of 70.7% (24.7%) and a median of 77.8% of their time in the trial. The patients contacted a call center most frequently at week 1. At the last visit, 78% (47/60) of patients were somewhat satisfied/satisfied/extremely satisfied with the DMS. A high proportion of patients with schizophrenia were able to use the DMS and reported satisfaction with the DMS. These data support the potential utility of the DMS in clinical practice.

Fall risks assessment among community dwelling elderly using wearable wireless sensors

NASA Astrophysics Data System (ADS)

Lockhart, Thurmon E.; Soangra, Rahul; Frames, Chris

2014-06-01

Postural stability characteristics are considered to be important in maintaining functional independence free of falls and healthy life style especially for the growing elderly population. This study focuses on developing tools of clinical value in fall prevention: 1) Implementation of sensors that are minimally obtrusive and reliably record movement data. 2) Unobtrusively gather data from wearable sensors from four community centers 3) developed and implemented linear and non-linear signal analysis algorithms to extract clinically relevant information using wearable technology. In all a total of 100 community dwelling elderly individuals (66 non-fallers and 34 fallers) participated in the experiment. All participants were asked to stand-still in eyes open (EO) and eyes closed (EC) condition on forceplate with one wireless inertial sensor affixed at sternum level. Participants' history of falls had been recorded for last 2 years, with emphasis on frequency and characteristics of falls. Any participant with at least one fall in the prior year were classified as faller and the others as non-faller. The results indicated several key factors/features of postural characteristics relevant to balance control and stability during quite stance and, showed good predictive capability of fall risks among older adults. Wearable technology allowed us to gather data where it matters the most to answer fall related questions, i.e. the community setting environments. This study opens new prospects of clinical testing using postural variables with a wearable sensor that may be relevant for assessing fall risks at home and patient environment in near future.

Effectiveness of a Batteryless and Wireless Wearable Sensor System for Identifying Bed and Chair Exits in Healthy Older People

PubMed Central

Shinmoto Torres, Roberto Luis; Visvanathan, Renuka; Hoskins, Stephen; van den Hengel, Anton; Ranasinghe, Damith C.

2016-01-01

Aging populations are increasing worldwide and strategies to minimize the impact of falls on older people need to be examined. Falls in hospitals are common and current hospital technological implementations use localized sensors on beds and chairs to alert caregivers of unsupervised patient ambulations; however, such systems have high false alarm rates. We investigate the recognition of bed and chair exits in real-time using a wireless wearable sensor worn by healthy older volunteers. Fourteen healthy older participants joined in supervised trials. They wore a batteryless, lightweight and wireless sensor over their attire and performed a set of broadly scripted activities. We developed a movement monitoring approach for the recognition of bed and chair exits based on a machine learning activity predictor. We investigated the effectiveness of our approach in generating bed and chair exit alerts in two possible clinical deployments (Room 1 and Room 2). The system obtained recall results above 93% (Room 2) and 94% (Room 1) for bed and chair exits, respectively. Precision was >78% and 67%, respectively, while F-score was >84% and 77% for bed and chair exits, respectively. This system has potential for real-time monitoring but further research in the final target population of older people is necessary. PMID:27092506

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.

A wearable, mobile phone-based respiration monitoring system for sleep apnea syndrome detection.

PubMed

Ishida, Ryoichi; Yonezawa, Yoshiharu; Maki, Hiromichi; Ogawa, Hidekuni; Ninomiya, Ishio; Sada, Kouji; Hamada, Shingo; Hahn, Allen W; Caldwell, W Morton

2005-01-01

A new wearable respiration monitoring system has been developed for non-invasive detection of sleep apnea syndrome. The system, which is attached to a shirt, consists of a piezoelectric sensor, a low-power 8-bit single chip microcontroller, EEPROM and a 2.4 GHz low-power transmitting mobile phone (PHS). The piezoelectric sensor, whose electrical polarization voltage is produced by body movements, is installed inside the shirt and closely contacts the patient's chest. The low frequency components of body movements recorded by the sensor are mainly generated by respiration. The microcontroller sequentially stores the movement signal to the EEPROM for 5 minutes and detects, by time-frequency analysis, whether the patient has breathed during that time. When the patient is apneic for 10 sseconds, the microcontroller sends the recorded respiration waveform during and one minute before and after the apnea directly to the hospital server computer via the mobile phone. The server computer then creates apnea "filings" automatically for every patient. The system can be used at home and be self-applied by patients. Moreover, the system does not require any extra equipment such as a personal computer, PDA, or Internet connection.

An Inflatable and Wearable Wireless System for Making 32-Channel Electroencephalogram Measurements.

PubMed

Yu, Yi-Hsin; Lu, Shao-Wei; Chuang, Chun-Hsiang; King, Jung-Tai; Chang, Che-Lun; Chen, Shi-An; Chen, Sheng-Fu; Lin, Chin-Teng

2016-07-01

Potable electroencephalography (EEG) devices have become critical for important research. They have various applications, such as in brain-computer interfaces (BCI). Numerous recent investigations have focused on the development of dry sensors, but few concern the simultaneous attachment of high-density dry sensors to different regions of the scalp to receive qualified EEG signals from hairy sites. An inflatable and wearable wireless 32-channel EEG device was designed, prototyped, and experimentally validated for making EEG signal measurements; it incorporates spring-loaded dry sensors and a novel gasbag design to solve the problem of interference by hair. The cap is ventilated and incorporates a circuit board and battery with a high-tolerance wireless (Bluetooth) protocol and low power consumption characteristics. The proposed system provides a 500/250 Hz sampling rate, and 24 bit EEG data to meet the BCI system data requirement. Experimental results prove that the proposed EEG system is effective in measuring audio event-related potential, measuring visual event-related potential, and rapid serial visual presentation. Results of this work demonstrate that the proposed EEG cap system performs well in making EEG measurements and is feasible for practical applications.

Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care.

PubMed

Bayo-Monton, Jose-Luis; Martinez-Millana, Antonio; Han, Weisi; Fernandez-Llatas, Carlos; Sun, Yan; Traver, Vicente

2018-06-06

Health and sociological indicators alert that life expectancy is increasing, hence so are the years that patients have to live with chronic diseases and co-morbidities. With the advancement in ICT, new tools and paradigms are been explored to provide effective and efficient health care. Telemedicine and health sensors stand as indispensable tools for promoting patient engagement, self-management of diseases and assist doctors to remotely follow up patients. In this paper, we evaluate a rapid prototyping solution for information merging based on five health sensors and two low-cost ubiquitous computing components: Arduino and Raspberry Pi. Our study, which is entirely described with the purpose of reproducibility, aimed to evaluate the extent to which portable technologies are capable of integrating wearable sensors by comparing two deployment scenarios: Raspberry Pi 3 and Personal Computer. The integration is implemented using a choreography engine to transmit data from sensors to a display unit using web services and a simple communication protocol with two modes of data retrieval. Performance of the two set-ups is compared by means of the latency in the wearable data transmission and data loss. PC has a delay of 0.051 ± 0.0035 s (max = 0.2504 s), whereas the Raspberry Pi yields a delay of 0.0175 ± 0.149 s (max = 0.294 s) for N = 300. Our analysis confirms that portable devices ( p < < 0 . 01 ) are suitable to support the transmission and analysis of biometric signals into scalable telemedicine systems.

Lunar Health Monitor (LHM)

NASA Technical Reports Server (NTRS)

Lisy, Frederick J.

2015-01-01

Orbital Research, Inc., has developed a low-profile, wearable sensor suite for monitoring astronaut health in both intravehicular and extravehicular activities. The Lunar Health Monitor measures respiration, body temperature, electrocardiogram (EKG) heart rate, and other cardiac functions. Orbital Research's dry recording electrode is central to the innovation and can be incorporated into garments, eliminating the need for conductive pastes, adhesives, or gels. The patented dry recording electrode has been approved by the U.S. Food and Drug Administration. The LHM is easily worn under flight gear or with civilian clothing, making the system completely versatile for applications where continuous physiological monitoring is needed. During Phase II, Orbital Research developed a second-generation LHM that allows sensor customization for specific monitoring applications and anatomical constraints. Evaluations included graded exercise tests, lunar mission task simulations, functional battery tests, and resting measures. The LHM represents the successful integration of sensors into a wearable platform to capture long-duration and ambulatory physiological markers.

Smart garments for safety improvement of emergency/disaster operators.

PubMed

Curone, Davide; Dudnik, Gabriela; Loriga, Giannicola; Luprano, Jean; Magenes, Giovanni; Paradiso, Rita; Tognetti, Alessandro; Bonfiglio, Annalisa

2007-01-01

The main purpose of the European project ProeTEX is to develop equipment to improve safety, coordination and efficiency of emergency disaster intervention personnel like fire-fighters or civil protection rescuers. The equipment consists of a new generation of "smart" garments, integrating wearable sensors which will allow monitoring physiological parameters, position and activity of the user, as like as environmental variables of the operating field in which rescuers are working: both commercial and newly developed textile and fibre based sensors will be included. The garments will also contain an electronic box to process data collected by the sensors and a communication system enabling the transmission of data to the other rescuers and to a monitoring station. Also a "smart" victim patch will be developed: a wearable garment which will allow monitoring physiological parameters of injured civilians involved in disasters, with the aim of optimizing their survival management.

A Wearable Real-Time and Non-Invasive Thoracic Cavity Monitoring System

NASA Astrophysics Data System (ADS)

Salman, Safa

A surgery-free on-body monitoring system is proposed to evaluate the dielectric constant of internal body tissues (especially lung and heart) and effectively determine irregularities in real-time. The proposed surgery-free on-body monitoring system includes a sensor, a post-processing technique, and an automated data collection circuit. Data are automatically collected from the sensor electrodes and then post processed to extract the electrical properties of the underlying biological tissue(s). To demonstrate the imaging concept, planar and wrap-around sensors are devised. These sensors are designed to detect changes in the dielectric constant of inner tissues (lung and heart). The planar sensor focuses on a single organ while the wrap-around sensors allows for imaging of the thoracic cavity's cross section. Moreover, post-processing techniques are proposed to complement sensors for a more complete on-body monitoring system. The idea behind the post-processing technique is to suppress interference from the outer layers (skin, fat, muscle, and bone). The sensors and post-processing techniques yield high signal (from the inner layers) to noise (from the outer layers) ratio. Additionally, data collection circuits are proposed for a more robust and stand-alone system. The circuit design aims to sequentially activate each port of the sensor and portions of the propagating signal are to be received at all passive ports in the form of a voltage at the probes. The voltages are converted to scattering parameters which are then used in the post-processing technique to obtain epsilonr. The concept of wearability is also considered through the use of electrically conductive fibers (E-fibers). These fibers show matching performance to that of copper, especially at low frequencies making them a viable substitute. For the cases considered, the proposed sensors show promising results in recovering the permittivity of deep tissues with a maximum error of 13.5%. These sensors provide a way for a new class of medical sensors through accuracy improvements and avoidance of inverse scattering techniques.

A wearable biofeedback control system based body area network for freestyle swimming.

PubMed

Rui Li; Zibo Cai; WeeSit Lee; Lai, Daniel T H

2016-08-01

Wearable posture measurement units are capable of enabling real-time performance evaluation and providing feedback to end users. This paper presents a wearable feedback prototype designed for freestyle swimming with focus on trunk rotation measurement. The system consists of a nine-degree-of-freedom inertial sensor, which is built in a central data collection and processing unit, and two vibration motors for delivering real-time feedback. Theses devices form a fundamental body area network (BAN). In the experiment setup, four recreational swimmers were asked to do two sets of 4 x 25m freestyle swimming without and with feedback provided respectively. Results showed that real-time biofeedback mechanism improves swimmers kinematic performance by an average of 4.5% reduction in session time. Swimmers can gradually adapt to feedback signals, and the biofeedback control system can be employed in swimmers daily training for fitness maintenance.

A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments

PubMed Central

Ghamari, Mohammad; Janko, Balazs; Sherratt, R. Simon; Harwin, William; Piechockic, Robert; Soltanpur, Cinna

2016-01-01

Current progress in wearable and implanted health monitoring technologies has strong potential to alter the future of healthcare services by enabling ubiquitous monitoring of patients. A typical health monitoring system consists of a network of wearable or implanted sensors that constantly monitor physiological parameters. Collected data are relayed using existing wireless communication protocols to a base station for additional processing. This article provides researchers with information to compare the existing low-power communication technologies that can potentially support the rapid development and deployment of WBAN systems, and mainly focuses on remote monitoring of elderly or chronically ill patients in residential environments. PMID:27338377

A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments.

PubMed

Ghamari, Mohammad; Janko, Balazs; Sherratt, R Simon; Harwin, William; Piechockic, Robert; Soltanpur, Cinna

2016-06-07

Current progress in wearable and implanted health monitoring technologies has strong potential to alter the future of healthcare services by enabling ubiquitous monitoring of patients. A typical health monitoring system consists of a network of wearable or implanted sensors that constantly monitor physiological parameters. Collected data are relayed using existing wireless communication protocols to a base station for additional processing. This article provides researchers with information to compare the existing low-power communication technologies that can potentially support the rapid development and deployment of WBAN systems, and mainly focuses on remote monitoring of elderly or chronically ill patients in residential environments.

Protection against impact with the ground using wearable airbags.

PubMed

Fukaya, Kiyoshi; Uchida, Mitsuya

2008-01-01

Incidental falls from heights, falls on the same level caused by slipping or tripping, and falls from wheelchair overturns are commonplace phenomena, associated with serious injuries from impact with the ground. A wearable airbag device is a countermeasure applicable to all these types of incidents. Three types of wearable airbag systems were developed and evaluated: for protection against falls from heights (Type-1), against wheelchair overturns (Type-2), and against falls on the same level (Type-3). The systems consist of an airbag, sensor, inflator, and jacket. The sensor detects the fall and the airbag inflates to protect the user. Fall tests using dummies with/without the airbags demonstrated the effectiveness of these devices. In the experiments with system Type-1, for fall heights of less than 2m, the airbags reduced the impact acceleration, and the Head Injury Criterion (HIC) values were under 1,000, the auto-crash test requirement. However, there are limits to the amount of protection afforded: in Type-1, the airbag can protect only the back of the head.; in Types-2 and 3, the fall height of the center of gravity is lower than 2m, and there is some margin of extra protective resource, which can be used to extend the protected area.

Energy Autonomous Wireless Sensing System Enabled by Energy Generated during Human Walking

NASA Astrophysics Data System (ADS)

Kuang, Yang; Ruan, Tingwen; Chew, Zheng Jun; Zhu, Meiling

2016-11-01

Recently, there has been a huge amount of work devoted to wearable energy harvesting (WEH) in a bid to establish energy autonomous wireless sensing systems for a range of health monitoring applications. However, limited work has been performed to implement and test such systems in real-world settings. This paper reports the development and real-world characterisation of a magnetically plucked wearable knee-joint energy harvester (Mag-WKEH) powered wireless sensing system, which integrates our latest research progresses in WEH, power conditioning and wireless sensing to achieve high energy efficiency. Experimental results demonstrate that with walking speeds of 3∼7 km/h, the Mag-WKEH generates average power of 1.9∼4.5 mW with unnoticeable impact on the wearer and is able to power the wireless sensor node (WSN) with three sensors to work at duty cycles of 6.6%∼13%. In each active period of 2 s, the WSN is able to measure and transmit 482 readings to the base station.

Textile Organic Electrochemical Transistors as a Platform for Wearable Biosensors

NASA Astrophysics Data System (ADS)

Gualandi, I.; Marzocchi, M.; Achilli, A.; Cavedale, D.; Bonfiglio, A.; Fraboni, B.

2016-09-01

The development of wearable chemical sensors is receiving a great deal of attention in view of non-invasive and continuous monitoring of physiological parameters in healthcare applications. This paper describes the development of a fully textile, wearable chemical sensor based on an organic electrochemical transistor (OECT) entirely made of conductive polymer (PEDOT:PSS). The active polymer patterns are deposited into the fabric by screen printing processes, thus allowing the device to actually “disappear” into it. We demonstrate the reliability of the proposed textile OECTs as a platform for developing chemical sensors capable to detect in real-time various redox active molecules (adrenaline, dopamine and ascorbic acid), by assessing their performance in two different experimental contexts: i) ideal operation conditions (i.e. totally dipped in an electrolyte solution); ii) real-life operation conditions (i.e. by sequentially adding few drops of electrolyte solution onto only one side of the textile sensor). The OECTs response has also been measured in artificial sweat, assessing how these sensors can be reliably used for the detection of biomarkers in body fluids. Finally, the very low operating potentials (<1 V) and absorbed power (~10-4 W) make the here described textile OECTs very appealing for portable and wearable applications.

Textile Organic Electrochemical Transistors as a Platform for Wearable Biosensors

PubMed Central

Gualandi, I.; Marzocchi, M.; Achilli, A.; Cavedale, D.; Bonfiglio, A.; Fraboni, B.

2016-01-01

The development of wearable chemical sensors is receiving a great deal of attention in view of non-invasive and continuous monitoring of physiological parameters in healthcare applications. This paper describes the development of a fully textile, wearable chemical sensor based on an organic electrochemical transistor (OECT) entirely made of conductive polymer (PEDOT:PSS). The active polymer patterns are deposited into the fabric by screen printing processes, thus allowing the device to actually “disappear” into it. We demonstrate the reliability of the proposed textile OECTs as a platform for developing chemical sensors capable to detect in real-time various redox active molecules (adrenaline, dopamine and ascorbic acid), by assessing their performance in two different experimental contexts: i) ideal operation conditions (i.e. totally dipped in an electrolyte solution); ii) real-life operation conditions (i.e. by sequentially adding few drops of electrolyte solution onto only one side of the textile sensor). The OECTs response has also been measured in artificial sweat, assessing how these sensors can be reliably used for the detection of biomarkers in body fluids. Finally, the very low operating potentials (<1 V) and absorbed power (~10−4 W) make the here described textile OECTs very appealing for portable and wearable applications. PMID:27667396

Efficient Skin Temperature Sensor and Stable Gel-Less Sticky ECG Sensor for a Wearable Flexible Healthcare Patch.

PubMed

Yamamoto, Yuki; Yamamoto, Daisuke; Takada, Makoto; Naito, Hiroyoshi; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2017-09-01

Wearable, flexible healthcare devices, which can monitor health data to predict and diagnose disease in advance, benefit society. Toward this future, various flexible and stretchable sensors as well as other components are demonstrated by arranging materials, structures, and processes. Although there are many sensor demonstrations, the fundamental characteristics such as the dependence of a temperature sensor on film thickness and the impact of adhesive for an electrocardiogram (ECG) sensor are yet to be explored in detail. In this study, the effect of film thickness for skin temperature measurements, adhesive force, and reliability of gel-less ECG sensors as well as an integrated real-time demonstration is reported. Depending on the ambient conditions, film thickness strongly affects the precision of skin temperature measurements, resulting in a thin flexible film suitable for a temperature sensor in wearable device applications. Furthermore, by arranging the material composition, stable gel-less sticky ECG electrodes are realized. Finally, real-time simultaneous skin temperature and ECG signal recordings are demonstrated by attaching an optimized device onto a volunteer's chest. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A wearable, low-power, health-monitoring instrumentation based on a Programmable System-on-Chip.

PubMed

Massot, Bertrand; Gehin, Claudine; Nocua, Ronald; Dittmar, Andre; McAdams, Eric

2009-01-01

Improvement in quality and efficiency of health and medicine, at home and in hospital, has become of paramount importance. The solution of this problem would require the continuous monitoring of several key patient parameters, including the assessment of autonomic nervous system (ANS) activity using non-invasive sensors, providing information for emotional, sensorial, cognitive and physiological analysis of the patient. Recent advances in embedded systems, microelectronics, sensors and wireless networking enable the design of wearable systems capable of such advanced health monitoring. The subject of this article is an ambulatory system comprising a small wrist device connected to several sensors for the detection of the autonomic nervous system activity. It affords monitoring of skin resistance, skin temperature and heart activity. It is also capable of recording the data on a removable media or sending it to computer via a wireless communication. The wrist device is based on a Programmable System-on-Chip (PSoC) from Cypress: PSoCs are mixed-signal arrays, with dynamic, configurable digital and analogical blocks and an 8-bit Microcontroller unit (MCU) core on a single chip. In this paper we present first of all the hardware and software architecture of the device, and then results obtained from initial experiments.

Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables

PubMed Central

Haugen Mikalsen, Martin; Woldaregay, Ashenafi Zebene; Muzny, Miroslav; Hartvigsen, Gunnar; Hopstock, Laila Arnesdatter; Grimsgaard, Sameline

2018-01-01

Background New fitness trackers and smartwatches are released to the consumer market every year. These devices are equipped with different sensors, algorithms, and accompanying mobile apps. With recent advances in mobile sensor technology, privately collected physical activity data can be used as an addition to existing methods for health data collection in research. Furthermore, data collected from these devices have possible applications in patient diagnostics and treatment. With an increasing number of diverse brands, there is a need for an overview of device sensor support, as well as device applicability in research projects. Objective The objective of this study was to examine the availability of wrist-worn fitness wearables and analyze availability of relevant fitness sensors from 2011 to 2017. Furthermore, the study was designed to assess brand usage in research projects, compare common brands in terms of developer access to collected health data, and features to consider when deciding which brand to use in future research. Methods We searched for devices and brand names in six wearable device databases. For each brand, we identified additional devices on official brand websites. The search was limited to wrist-worn fitness wearables with accelerometers, for which we mapped brand, release year, and supported sensors relevant for fitness tracking. In addition, we conducted a Medical Literature Analysis and Retrieval System Online (MEDLINE) and ClinicalTrials search to determine brand usage in research projects. Finally, we investigated developer accessibility to the health data collected by identified brands. Results We identified 423 unique devices from 132 different brands. Forty-seven percent of brands released only one device. Introduction of new brands peaked in 2014, and the highest number of new devices was introduced in 2015. Sensor support increased every year, and in addition to the accelerometer, a photoplethysmograph, for estimating heart rate, was the most common sensor. Out of the brands currently available, the five most often used in research projects are Fitbit, Garmin, Misfit, Apple, and Polar. Fitbit is used in twice as many validation studies as any other brands and is registered in ClinicalTrials studies 10 times as often as other brands. Conclusions The wearable landscape is in constant change. New devices and brands are released every year, promising improved measurements and user experience. At the same time, other brands disappear from the consumer market for various reasons. Advances in device quality offer new opportunities for research. However, only a few well-established brands are frequently used in research projects, and even less are thoroughly validated. PMID:29567635

Wearable sensor use for assessing standing balance and walking stability in people with Parkinson's disease: a systematic review.

PubMed

Hubble, Ryan P; Naughton, Geraldine A; Silburn, Peter A; Cole, Michael H

2015-01-01

Postural instability and gait disability threaten the independence and well-being of people with Parkinson's disease and increase the risk of falls and fall-related injuries. Prospective research has shown that commonly-used clinical assessments of balance and walking lack the sensitivity to accurately and consistently identify those people with Parkinson's disease who are at a higher risk of falling. Wearable sensors provide a portable and affordable alternative for researchers and clinicians who are seeking to objectively assess movements and falls risk in the clinical setting. However, no consensus currently exists on the optimal placements for sensors and the best outcome measures to use for assessing standing balance and walking stability in Parkinson's disease patients. Hence, this systematic review aimed to examine the available literature to establish the best sensor types, locations and outcomes to assess standing balance and walking stability in this population. Papers listed in three electronic databases were searched by title and abstract to identify articles measuring standing balance or walking stability with any kind of wearable sensor among adults diagnosed with PD. To be eligible for inclusion, papers were required to be full-text articles published in English between January 1994 and December 2014 that assessed measures of standing balance or walking stability with wearable sensors in people with PD. Articles were excluded if they; i) did not use any form of wearable sensor to measure variables associated with standing balance or walking stability; ii) did not include a control group or control condition; iii) were an abstract and/or included in the proceedings of a conference; or iv) were a review article or case study. The targeted search of the three electronic databases identified 340 articles that were potentially eligible for inclusion, but following title, abstract and full-text review only 26 articles were deemed to meet the inclusion criteria. Included articles were assessed for methodological quality and relevant data from the papers were extracted and synthesized. Quality assessment of these included articles indicated that 31% were of low methodological quality, while 58% were of moderate methodological quality and 11% were of high methodological quality. All studies adopted a cross-sectional design and used a variety of sensor types and outcome measures to assess standing balance or walking stability in people with Parkinson's disease. Despite the typically low to moderate methodological quality, 81% of the studies reported differences in sensor-based measures of standing balance or walking stability between different groups of Parkinson's disease patients and/or healthy controls. These data support the use of wearable sensors for detecting differences in standing balance and walking stability between people with PD and controls. Further high-quality research is needed to better understand the utility of wearable sensors for the early identification of Parkinson's disease symptoms and for assessing falls risk in this population. CRD42014010838.

Wearable Sensor Use for Assessing Standing Balance and Walking Stability in People with Parkinson’s Disease: A Systematic Review

PubMed Central

Hubble, Ryan P.; Naughton, Geraldine A.; Silburn, Peter A.; Cole, Michael H.

2015-01-01

Background Postural instability and gait disability threaten the independence and well-being of people with Parkinson’s disease and increase the risk of falls and fall-related injuries. Prospective research has shown that commonly-used clinical assessments of balance and walking lack the sensitivity to accurately and consistently identify those people with Parkinson’s disease who are at a higher risk of falling. Wearable sensors provide a portable and affordable alternative for researchers and clinicians who are seeking to objectively assess movements and falls risk in the clinical setting. However, no consensus currently exists on the optimal placements for sensors and the best outcome measures to use for assessing standing balance and walking stability in Parkinson’s disease patients. Hence, this systematic review aimed to examine the available literature to establish the best sensor types, locations and outcomes to assess standing balance and walking stability in this population. Methods Papers listed in three electronic databases were searched by title and abstract to identify articles measuring standing balance or walking stability with any kind of wearable sensor among adults diagnosed with PD. To be eligible for inclusion, papers were required to be full-text articles published in English between January 1994 and December 2014 that assessed measures of standing balance or walking stability with wearable sensors in people with PD. Articles were excluded if they; i) did not use any form of wearable sensor to measure variables associated with standing balance or walking stability; ii) did not include a control group or control condition; iii) were an abstract and/or included in the proceedings of a conference; or iv) were a review article or case study. The targeted search of the three electronic databases identified 340 articles that were potentially eligible for inclusion, but following title, abstract and full-text review only 26 articles were deemed to meet the inclusion criteria. Included articles were assessed for methodological quality and relevant data from the papers were extracted and synthesized. Results Quality assessment of these included articles indicated that 31% were of low methodological quality, while 58% were of moderate methodological quality and 11% were of high methodological quality. All studies adopted a cross-sectional design and used a variety of sensor types and outcome measures to assess standing balance or walking stability in people with Parkinson’s disease. Despite the typically low to moderate methodological quality, 81% of the studies reported differences in sensor-based measures of standing balance or walking stability between different groups of Parkinson’s disease patients and/or healthy controls. Conclusion These data support the use of wearable sensors for detecting differences in standing balance and walking stability between people with PD and controls. Further high-quality research is needed to better understand the utility of wearable sensors for the early identification of Parkinson’s disease symptoms and for assessing falls risk in this population. PROSPERO Registration CRD42014010838 PMID:25894561

Detection of Site-Specific Blood Flow Variation in Humans during Running by a Wearable Laser Doppler Flowmeter.

PubMed

Iwasaki, Wataru; Nogami, Hirofumi; Takeuchi, Satoshi; Furue, Masutaka; Higurashi, Eiji; Sawada, Renshi

2015-10-05

Wearable wireless physiological sensors are helpful for monitoring and maintaining human health. Blood flow contains abundant physiological information but it is hard to measure blood flow during exercise using conventional blood flowmeters because of their size, weight, and use of optic fibers. To resolve these disadvantages, we previously developed a micro integrated laser Doppler blood flowmeter using microelectromechanical systems technology. This micro blood flowmeter is wearable and capable of stable measurement signals even during movement. Therefore, we attempted to measure skin blood flow at the forehead, fingertip, and earlobe of seven young men while running as a pilot experiment to extend the utility of the micro blood flowmeter. We measured blood flow in each subject at velocities of 6, 8, and 10 km/h. We succeeded in obtaining stable measurements of blood flow, with few motion artifacts, using the micro blood flowmeter, and the pulse wave signal and motion artifacts were clearly separated by conducting frequency analysis. Furthermore, the results showed that the extent of the changes in blood flow depended on the intensity of exercise as well as previous work with an ergometer. Thus, we demonstrated the capability of this wearable blood flow sensor for measurement during exercise.

Mechanically Compliant Electronic Materials for Wearable Photovoltaics and Human-Machine Interfaces

NASA Astrophysics Data System (ADS)

O'Connor, Timothy Francis, III

Applications of stretchable electronic materials for human-machine interfaces are described herein. Intrinsically stretchable organic conjugated polymers and stretchable electronic composites were used to develop stretchable organic photovoltaics (OPVs), mechanically robust wearable OPVs, and human-machine interfaces for gesture recognition, American Sign Language Translation, haptic control of robots, and touch emulation for virtual reality, augmented reality, and the transmission of touch. The stretchable and wearable OPVs comprise active layers of poly-3-alkylthiophene:phenyl-C61-butyric acid methyl ester (P3AT:PCBM) and transparent conductive electrodes of poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) and devices could only be fabricated through a deep understanding of the connection between molecular structure and the co-engineering of electronic performance with mechanical resilience. The talk concludes with the use of composite piezoresistive sensors two smart glove prototypes. The first integrates stretchable strain sensors comprising a carbon-elastomer composite, a wearable microcontroller, low energy Bluetooth, and a 6-axis accelerometer/gyroscope to construct a fully functional gesture recognition glove capable of wirelessly translating American Sign Language to text on a cell phone screen. The second creates a system for the haptic control of a 3D printed robot arm, as well as the transmission of touch and temperature information.

Wearable wireless photoplethysmography sensors

NASA Astrophysics Data System (ADS)

Spigulis, Janis; Erts, Renars; Nikiforovs, Vladimirs; Kviesis-Kipge, Edgars

2008-04-01

Wearable health monitoring sensors may support early detection of abnormal conditions and prevention of their consequences. Recent designs of three wireless photoplethysmography monitoring devices embedded in hat, glove and sock, and connected to PC or mobile phone by means of the Bluetooth technology, are described. First results of distant monitoring of heart rate and pulse wave transit time using the newly developed devices are presented.

Three Dimensional Gait Analysis Using Wearable Acceleration and Gyro Sensors Based on Quaternion Calculations

PubMed Central

Tadano, Shigeru; Takeda, Ryo; Miyagawa, Hiroaki

2013-01-01

This paper proposes a method for three dimensional gait analysis using wearable sensors and quaternion calculations. Seven sensor units consisting of a tri-axial acceleration and gyro sensors, were fixed to the lower limbs. The acceleration and angular velocity data of each sensor unit were measured during level walking. The initial orientations of the sensor units were estimated using acceleration data during upright standing position and the angular displacements were estimated afterwards using angular velocity data during gait. Here, an algorithm based on quaternion calculation was implemented for orientation estimation of the sensor units. The orientations of the sensor units were converted to the orientations of the body segments by a rotation matrix obtained from a calibration trial. Body segment orientations were then used for constructing a three dimensional wire frame animation of the volunteers during the gait. Gait analysis was conducted on five volunteers, and results were compared with those from a camera-based motion analysis system. Comparisons were made for the joint trajectory in the horizontal and sagittal plane. The average RMSE and correlation coefficient (CC) were 10.14 deg and 0.98, 7.88 deg and 0.97, 9.75 deg and 0.78 for the hip, knee and ankle flexion angles, respectively. PMID:23877128

Quantifying Variation in Gait Features from Wearable Inertial Sensors Using Mixed Effects Models

PubMed Central

Cresswell, Kellen Garrison; Shin, Yongyun; Chen, Shanshan

2017-01-01

The emerging technology of wearable inertial sensors has shown its advantages in collecting continuous longitudinal gait data outside laboratories. This freedom also presents challenges in collecting high-fidelity gait data. In the free-living environment, without constant supervision from researchers, sensor-based gait features are susceptible to variation from confounding factors such as gait speed and mounting uncertainty, which are challenging to control or estimate. This paper is one of the first attempts in the field to tackle such challenges using statistical modeling. By accepting the uncertainties and variation associated with wearable sensor-based gait data, we shift our efforts from detecting and correcting those variations to modeling them statistically. From gait data collected on one healthy, non-elderly subject during 48 full-factorial trials, we identified four major sources of variation, and quantified their impact on one gait outcome—range per cycle—using a random effects model and a fixed effects model. The methodology developed in this paper lays the groundwork for a statistical framework to account for sources of variation in wearable gait data, thus facilitating informative statistical inference for free-living gait analysis. PMID:28245602

Wearable physiological systems and technologies for metabolic monitoring.

PubMed

Gao, Wei; Brooks, George A; Klonoff, David C

2018-03-01

Wearable sensors allow continuous monitoring of metabolites for diabetes, sports medicine, exercise science, and physiology research. These sensors can continuously detect target analytes in skin interstitial fluid (ISF), tears, saliva, and sweat. In this review, we will summarize developments on wearable devices and their potential applications in research, clinical practice, and recreational and sporting activities. Sampling skin ISF can require insertion of a needle into the skin, whereas sweat, tears, and saliva can be sampled by devices worn outside the body. The most widely sampled metabolite from a wearable device is glucose in skin ISF for monitoring diabetes patients. Continuous ISF glucose monitoring allows estimation of the glucose concentration in blood without the pain, inconvenience, and blood waste of fingerstick capillary blood glucose testing. This tool is currently used by diabetes patients to provide information for dosing insulin and determining a diet and exercise plan. Similar technologies for measuring concentrations of other analytes in skin ISF could be used to monitor athletes, emergency responders, warfighters, and others in states of extreme physiological stress. Sweat is a potentially useful substrate for sampling analytes for metabolic monitoring during exercise. Lactate, sodium, potassium, and hydrogen ions can be measured in sweat. Tools for converting the concentrations of these analytes sampled from sweat, tears, and saliva into blood concentrations are being developed. As an understanding of the relationships between the concentrations of analytes in blood and easily sampled body fluid increases, then the benefits of new wearable devices for metabolic monitoring will also increase.

A wearable multiplexed silicon nonvolatile memory array using nanocrystal charge confinement

PubMed Central

Kim, Jaemin; Son, Donghee; Lee, Mincheol; Song, Changyeong; Song, Jun-Kyul; Koo, Ja Hoon; Lee, Dong Jun; Shim, Hyung Joon; Kim, Ji Hoon; Lee, Minbaek; Hyeon, Taeghwan; Kim, Dae-Hyeong

2016-01-01

Strategies for efficient charge confinement in nanocrystal floating gates to realize high-performance memory devices have been investigated intensively. However, few studies have reported nanoscale experimental validations of charge confinement in closely packed uniform nanocrystals and related device performance characterization. Furthermore, the system-level integration of the resulting devices with wearable silicon electronics has not yet been realized. We introduce a wearable, fully multiplexed silicon nonvolatile memory array with nanocrystal floating gates. The nanocrystal monolayer is assembled over a large area using the Langmuir-Blodgett method. Efficient particle-level charge confinement is verified with the modified atomic force microscopy technique. Uniform nanocrystal charge traps evidently improve the memory window margin and retention performance. Furthermore, the multiplexing of memory devices in conjunction with the amplification of sensor signals based on ultrathin silicon nanomembrane circuits in stretchable layouts enables wearable healthcare applications such as long-term data storage of monitored heart rates. PMID:26763827

Wearable ear EEG for brain interfacing

NASA Astrophysics Data System (ADS)

Schroeder, Eric D.; Walker, Nicholas; Danko, Amanda S.

2017-02-01

Brain-computer interfaces (BCIs) measuring electrical activity via electroencephalogram (EEG) have evolved beyond clinical applications to become wireless consumer products. Typically marketed for meditation and neu- rotherapy, these devices are limited in scope and currently too obtrusive to be a ubiquitous wearable. Stemming from recent advancements made in hearing aid technology, wearables have been shrinking to the point that the necessary sensors, circuitry, and batteries can be fit into a small in-ear wearable device. In this work, an ear-EEG device is created with a novel system for artifact removal and signal interpretation. The small, compact, cost-effective, and discreet device is demonstrated against existing consumer electronics in this space for its signal quality, comfort, and usability. A custom mobile application is developed to process raw EEG from each device and display interpreted data to the user. Artifact removal and signal classification is accomplished via a combination of support matrix machines (SMMs) and soft thresholding of relevant statistical properties.

A wearable multiplexed silicon nonvolatile memory array using nanocrystal charge confinement.

PubMed

Kim, Jaemin; Son, Donghee; Lee, Mincheol; Song, Changyeong; Song, Jun-Kyul; Koo, Ja Hoon; Lee, Dong Jun; Shim, Hyung Joon; Kim, Ji Hoon; Lee, Minbaek; Hyeon, Taeghwan; Kim, Dae-Hyeong

2016-01-01

Strategies for efficient charge confinement in nanocrystal floating gates to realize high-performance memory devices have been investigated intensively. However, few studies have reported nanoscale experimental validations of charge confinement in closely packed uniform nanocrystals and related device performance characterization. Furthermore, the system-level integration of the resulting devices with wearable silicon electronics has not yet been realized. We introduce a wearable, fully multiplexed silicon nonvolatile memory array with nanocrystal floating gates. The nanocrystal monolayer is assembled over a large area using the Langmuir-Blodgett method. Efficient particle-level charge confinement is verified with the modified atomic force microscopy technique. Uniform nanocrystal charge traps evidently improve the memory window margin and retention performance. Furthermore, the multiplexing of memory devices in conjunction with the amplification of sensor signals based on ultrathin silicon nanomembrane circuits in stretchable layouts enables wearable healthcare applications such as long-term data storage of monitored heart rates.

Flexible Transparent Electronic Gas Sensors.

PubMed

Wang, Ting; Guo, Yunlong; Wan, Pengbo; Zhang, Han; Chen, Xiaodong; Sun, Xiaoming

2016-07-01

Flexible and transparent electronic gas sensors capable of real-time, sensitive, and selective analysis at room-temperature, have gained immense popularity in recent years for their potential to be integrated into various smart wearable electronics and display devices. Here, recent advances in flexible transparent sensors constructed from semiconducting oxides, carbon materials, conducting polymers, and their nanocomposites are presented. The sensing material selection, sensor device construction, and sensing mechanism of flexible transparent sensors are discussed in detail. The critical challenges and future development associated with flexible and transparent electronic gas sensors are presented. Smart wearable gas sensors are believed to have great potential in environmental monitoring and noninvasive health monitoring based on disease biomarkers in exhaled gas. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Integrated Wireless Wearable Sensor System for Posture Recognition and Indoor Localization.

PubMed

Huang, Jian; Yu, Xiaoqiang; Wang, Yuan; Xiao, Xiling

2016-10-31

In order to provide better monitoring for the elderly or patients, we developed an integrated wireless wearable sensor system that can realize posture recognition and indoor localization in real time. Five designed sensor nodes which are respectively fixed on lower limbs and a standard Kalman filter are used to acquire basic attitude data. After the attitude angles of five body segments (two thighs, two shanks and the waist) are obtained, the pitch angles of the left thigh and waist are used to realize posture recognition. Based on all these attitude angles of body segments, we can also calculate the coordinates of six lower limb joints (two hip joints, two knee joints and two ankle joints). Then, a novel relative localization algorithm based on step length is proposed to realize the indoor localization of the user. Several sparsely distributed active Radio Frequency Identification (RFID) tags are used to correct the accumulative error in the relative localization algorithm and a set-membership filter is applied to realize the data fusion. The experimental results verify the effectiveness of the proposed algorithms.

NFC-enabled, tattoo-like stretchable biosensor manufactured by "cut-and-paste" method.

PubMed

Hyoyoung Jeong; Taewoo Ha; Kuang, Irene; Linxiao Shen; Zhaohe Dai; Nan Sun; Nanshu Lu

2017-07-01

The wearables industry is lacking in devices that have the ability to provide valuable biometrics data in a soft, wireless and disposable system. Such a system should be high performance, multifunctional, but battery-free and low cost. Near field communication (NFC) is a wireless communication protocol built in many smartphones nowadays that can read data from battery-free passive tags. As a result, NFC-enabled wearable biosensors have been reported, but they are either unstretchable or have to be manufactured by labor- and time-intensive photolithography and transfer-printing processes. Using a dry and freeform "cut-and-paste" method, we have built a wireless and low-cost stretchable biosensor that integrates temperature sensor, light source/sensor, NFC chip, and antenna. It is battery-free and can be laminated on any part of human skin like a temporary transfer tattoo. The sensor can fully follow the stretching and compression of skin without mechanical failure or delamination. Thus, it is imperceptible to wear and can perform high-fidelity sensing. Potential applications include, but are not limited to, skin thermography and photometry.

An Integrated Wireless Wearable Sensor System for Posture Recognition and Indoor Localization

PubMed Central

Huang, Jian; Yu, Xiaoqiang; Wang, Yuan; Xiao, Xiling

2016-01-01

In order to provide better monitoring for the elderly or patients, we developed an integrated wireless wearable sensor system that can realize posture recognition and indoor localization in real time. Five designed sensor nodes which are respectively fixed on lower limbs and a standard Kalman filter are used to acquire basic attitude data. After the attitude angles of five body segments (two thighs, two shanks and the waist) are obtained, the pitch angles of the left thigh and waist are used to realize posture recognition. Based on all these attitude angles of body segments, we can also calculate the coordinates of six lower limb joints (two hip joints, two knee joints and two ankle joints). Then, a novel relative localization algorithm based on step length is proposed to realize the indoor localization of the user. Several sparsely distributed active Radio Frequency Identification (RFID) tags are used to correct the accumulative error in the relative localization algorithm and a set-membership filter is applied to realize the data fusion. The experimental results verify the effectiveness of the proposed algorithms. PMID:27809230

Leveraging knowledge from physiological data: on-body heat stress risk prediction with sensor networks.

PubMed

Gaura, Elena; Kemp, John; Brusey, James

2013-12-01

The paper demonstrates that wearable sensor systems, coupled with real-time on-body processing and actuation, can enhance safety for wearers of heavy protective equipment who are subjected to harsh thermal environments by reducing risk of Uncompensable Heat Stress (UHS). The work focuses on Explosive Ordnance Disposal operatives and shows that predictions of UHS risk can be performed in real-time with sufficient accuracy for real-world use. Furthermore, it is shown that the required sensory input for such algorithms can be obtained with wearable, non-intrusive sensors. Two algorithms, one based on Bayesian nets and another on decision trees, are presented for determining the heat stress risk, considering the mean skin temperature prediction as a proxy. The algorithms are trained on empirical data and have accuracies of 92.1±2.9% and 94.4±2.1%, respectively when tested using leave-one-subject-out cross-validation. In applications such as Explosive Ordnance Disposal operative monitoring, such prediction algorithms can enable autonomous actuation of cooling systems and haptic alerts to minimize casualties.

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.

Free-living monitoring of Parkinson's disease: Lessons from the field.

PubMed

Del Din, Silvia; Godfrey, Alan; Mazzà, Claudia; Lord, Sue; Rochester, Lynn

2016-09-01

Wearable technology comprises miniaturized sensors (eg, accelerometers) worn on the body and/or paired with mobile devices (eg, smart phones) allowing continuous patient monitoring in unsupervised, habitual environments (termed free-living). Wearable technologies are revolutionizing approaches to health care as a result of their utility, accessibility, and affordability. They are positioned to transform Parkinson's disease (PD) management through the provision of individualized, comprehensive, and representative data. This is particularly relevant in PD where symptoms are often triggered by task and free-living environmental challenges that cannot be replicated with sufficient veracity elsewhere. This review concerns use of wearable technology in free-living environments for people with PD. It outlines the potential advantages of wearable technologies and evidence for these to accurately detect and measure clinically relevant features including motor symptoms, falls risk, freezing of gait, gait, functional mobility, and physical activity. Technological limitations and challenges are highlighted, and advances concerning broader aspects are discussed. Recommendations to overcome key challenges are made. To date there is no fully validated system to monitor clinical features or activities in free-living environments. Robust accuracy and validity metrics for some features have been reported, and wearable technology may be used in these cases with a degree of confidence. Utility and acceptability appears reasonable, although testing has largely been informal. Key recommendations include adopting a multidisciplinary approach for standardizing definitions, protocols, and outcomes. Robust validation of developed algorithms and sensor-based metrics is required along with testing of utility. These advances are required before widespread clinical adoption of wearable technology can be realized. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Data fusion of multiple kinect sensors for a rehabilitation system.

PubMed

Huibin Du; Yiwen Zhao; Jianda Han; Zheng Wang; Guoli Song

2016-08-01

Kinect-like depth sensors have been widely used in rehabilitation systems. However, single depth sensor processes limb-blocking, data loss or data error poorly, making it less reliable. This paper focus on using two Kinect sensors and data fusion method to solve these problems. First, two Kinect sensors capture the motion data of the healthy arm of the hemiplegic patient; Second, merge the data using the method of Set-Membership-Filter (SMF); Then, mirror this motion data by the Middle-Plane; In the end, control the wearable robotic arm driving the patient's paralytic arm so that the patient can interactively and initiatively complete a variety of recovery actions prompted by computer with 3D animation games.

Development of a Wearable Assist Robot for Walk Rehabilitation After Knee Arthroplasty Surgery

NASA Astrophysics Data System (ADS)

Terada, H.; Zhu, Y.; Horiguchi, K.; Nakamura, M.; Takahashi, R.

In Japan, it is popular that the disease knee joints will be replaced to artificial joints by surgery. And we have to assist so many patients for walk rehabilitation. So, the wearable assist robot has been developed. This robot includes the knee motion assist mechanism and the hip joint support mechanism. Especially, the knee motion assist mechanism consists of a non-circular gear and grooved cams. This mechanism rotates and slides simultaneously, which has two degree-of-freedom. Also, the hip joint support mechanism consists of a hip brace and a ball-joint. This mechanism can avoid motion constraints which are the internal or external rotation and the adduction or abduction. Then, the control algorithm, which considers an assisting timing for the walk rehabilitation, has been proposed. A sensing system of a walk state for this control system uses a heel contacts sensor and knee and hip joint rotation angle sensors. Also, the prototype robot has been tested. And it is confirmed that the assisting system is useful.

Freezing of gait and fall detection in Parkinson's disease using wearable sensors: a systematic review.

PubMed

Silva de Lima, Ana Lígia; Evers, Luc J W; Hahn, Tim; Bataille, Lauren; Hamilton, Jamie L; Little, Max A; Okuma, Yasuyuki; Bloem, Bastiaan R; Faber, Marjan J

2017-08-01

Despite the large number of studies that have investigated the use of wearable sensors to detect gait disturbances such as Freezing of gait (FOG) and falls, there is little consensus regarding appropriate methodologies for how to optimally apply such devices. Here, an overview of the use of wearable systems to assess FOG and falls in Parkinson's disease (PD) and validation performance is presented. A systematic search in the PubMed and Web of Science databases was performed using a group of concept key words. The final search was performed in January 2017, and articles were selected based upon a set of eligibility criteria. In total, 27 articles were selected. Of those, 23 related to FOG and 4 to falls. FOG studies were performed in either laboratory or home settings, with sample sizes ranging from 1 PD up to 48 PD presenting Hoehn and Yahr stage from 2 to 4. The shin was the most common sensor location and accelerometer was the most frequently used sensor type. Validity measures ranged from 73-100% for sensitivity and 67-100% for specificity. Falls and fall risk studies were all home-based, including samples sizes of 1 PD up to 107 PD, mostly using one sensor containing accelerometers, worn at various body locations. Despite the promising validation initiatives reported in these studies, they were all performed in relatively small sample sizes, and there was a significant variability in outcomes measured and results reported. Given these limitations, the validation of sensor-derived assessments of PD features would benefit from more focused research efforts, increased collaboration among researchers, aligning data collection protocols, and sharing data sets.

Stochastic analysis of motor-control stability, polymer based force sensing, and optical stimulation as a preventive measure for falls

NASA Astrophysics Data System (ADS)

Landrock, Clinton K.

Falls are the leading cause of all external injuries. Outcomes of falls include the leading cause of traumatic brain injury and bone fractures, and high direct medical costs in the billions of dollars. This work focused on developing three areas of enabling component technology to be used in postural control monitoring tools targeting the mitigation of falls. The first was an analysis tool based on stochastic fractal analysis to reliably measure levels of motor control. The second focus was on thin film wearable pressure sensors capable of relaying data for the first tool. The third was new thin film advanced optics for improving phototherapy devices targeting postural control disorders. Two populations, athletes and elderly, were studied against control groups. The results of these studies clearly show that monitoring postural stability in at-risk groups can be achieved reliably, and an integrated wearable system can be envisioned for both monitoring and treatment purposes. Keywords: electro-active polymer, ionic polymer-metal composite, postural control, motor control, fall prevention, sports medicine, fractal analysis, physiological signals, wearable sensors, phototherapy, photobiomodulation, nano-optics.

A wearable conformal bandage for non-invasive two-dimensional imaging of skin oxygenation (Conference Presentation)

NASA Astrophysics Data System (ADS)

Li, Zongxi; Roussakis, Emmanuel; Keeley, Emily; Apiou-Sbirlea, Gabriela; Birngruber, Reginald; Huang, Christene; Evans, Conor L.

2016-03-01

The complex surface topology and soft mechanics of the skin poses a considerable challenge to the development of wearable, conformal sensors. As a results, current clinical assessments of healing-related skin parameters often rely on bulky and expensive optical systems that are difficult to deploy at the point of care. Here, using a rapid-drying, liquid bandage containing oxygen-sensing molecules, we created a wearable sensor bandage that conforms the surface geometry of skin and wounds, and provides two-dimensional maps of cutaneous oxygenation in a non-disruptive fashion. Custom oxygen sensing phosphors have been developed in house that are at least five times brighter than the commercial sensing molecules, enabling the visualization of oxygen concentration using a simple color camera or even by eye under ambient lighting conditions. The oxygen-sensing bandage has been applied to monitor tissue ischemia, graft integration, as well as the progression of burn in animal models. Recent studies have demonstrated its ability to track and quantify skin inflammation induced by complete Freund's adjuvant in an in vivo porcine model.

An Ultra-Low Power Turning Angle Based Biomedical Signal Compression Engine with Adaptive Threshold Tuning

PubMed Central

Zhou, Jun; Wang, Chao

2017-01-01

Intelligent sensing is drastically changing our everyday life including healthcare by biomedical signal monitoring, collection, and analytics. However, long-term healthcare monitoring generates tremendous data volume and demands significant wireless transmission power, which imposes a big challenge for wearable healthcare sensors usually powered by batteries. Efficient compression engine design to reduce wireless transmission data rate with ultra-low power consumption is essential for wearable miniaturized healthcare sensor systems. This paper presents an ultra-low power biomedical signal compression engine for healthcare data sensing and analytics in the era of big data and sensor intelligence. It extracts the feature points of the biomedical signal by window-based turning angle detection. The proposed approach has low complexity and thus low power consumption while achieving a large compression ratio (CR) and good quality of reconstructed signal. Near-threshold design technique is adopted to further reduce the power consumption on the circuit level. Besides, the angle threshold for compression can be adaptively tuned according to the error between the original signal and reconstructed signal to address the variation of signal characteristics from person to person or from channel to channel to meet the required signal quality with optimal CR. For demonstration, the proposed biomedical compression engine has been used and evaluated for ECG compression. It achieves an average (CR) of 71.08% and percentage root-mean-square difference (PRD) of 5.87% while consuming only 39 nW. Compared to several state-of-the-art ECG compression engines, the proposed design has significantly lower power consumption while achieving similar CRD and PRD, making it suitable for long-term wearable miniaturized sensor systems to sense and collect healthcare data for remote data analytics. PMID:28783079

An Ultra-Low Power Turning Angle Based Biomedical Signal Compression Engine with Adaptive Threshold Tuning.

PubMed

Zhou, Jun; Wang, Chao

2017-08-06

Intelligent sensing is drastically changing our everyday life including healthcare by biomedical signal monitoring, collection, and analytics. However, long-term healthcare monitoring generates tremendous data volume and demands significant wireless transmission power, which imposes a big challenge for wearable healthcare sensors usually powered by batteries. Efficient compression engine design to reduce wireless transmission data rate with ultra-low power consumption is essential for wearable miniaturized healthcare sensor systems. This paper presents an ultra-low power biomedical signal compression engine for healthcare data sensing and analytics in the era of big data and sensor intelligence. It extracts the feature points of the biomedical signal by window-based turning angle detection. The proposed approach has low complexity and thus low power consumption while achieving a large compression ratio (CR) and good quality of reconstructed signal. Near-threshold design technique is adopted to further reduce the power consumption on the circuit level. Besides, the angle threshold for compression can be adaptively tuned according to the error between the original signal and reconstructed signal to address the variation of signal characteristics from person to person or from channel to channel to meet the required signal quality with optimal CR. For demonstration, the proposed biomedical compression engine has been used and evaluated for ECG compression. It achieves an average (CR) of 71.08% and percentage root-mean-square difference (PRD) of 5.87% while consuming only 39 nW. Compared to several state-of-the-art ECG compression engines, the proposed design has significantly lower power consumption while achieving similar CRD and PRD, making it suitable for long-term wearable miniaturized sensor systems to sense and collect healthcare data for remote data analytics.

A Novel Wearable Device for Food Intake and Physical Activity Recognition

PubMed Central

Farooq, Muhammad; Sazonov, Edward

2016-01-01

Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active and/or talking. The device consists of a piezoelectric strain sensor placed on the temporalis muscle, an accelerometer, and a data acquisition module connected to the temple of eyeglasses. Data from 10 participants was collected while they performed activities including quiet sitting, talking, eating while sitting, eating while walking, and walking. Piezoelectric strain sensor and accelerometer signals were divided into non-overlapping epochs of 3 s; four features were computed for each signal. To differentiate between eating and not eating, as well as between sedentary postures and physical activity, two multiclass classification approaches are presented. The first approach used a single classifier with sensor fusion and the second approach used two-stage classification. The best results were achieved when two separate linear support vector machine (SVM) classifiers were trained for food intake and activity detection, and their results were combined using a decision tree (two-stage classification) to determine the final class. This approach resulted in an average F1-score of 99.85% and area under the curve (AUC) of 0.99 for multiclass classification. With its ability to differentiate between food intake and activity level, this device may potentially be used for tracking both energy intake and energy expenditure. PMID:27409622

A Novel Wearable Device for Food Intake and Physical Activity Recognition.

PubMed

Farooq, Muhammad; Sazonov, Edward

2016-07-11

Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active and/or talking. The device consists of a piezoelectric strain sensor placed on the temporalis muscle, an accelerometer, and a data acquisition module connected to the temple of eyeglasses. Data from 10 participants was collected while they performed activities including quiet sitting, talking, eating while sitting, eating while walking, and walking. Piezoelectric strain sensor and accelerometer signals were divided into non-overlapping epochs of 3 s; four features were computed for each signal. To differentiate between eating and not eating, as well as between sedentary postures and physical activity, two multiclass classification approaches are presented. The first approach used a single classifier with sensor fusion and the second approach used two-stage classification. The best results were achieved when two separate linear support vector machine (SVM) classifiers were trained for food intake and activity detection, and their results were combined using a decision tree (two-stage classification) to determine the final class. This approach resulted in an average F1-score of 99.85% and area under the curve (AUC) of 0.99 for multiclass classification. With its ability to differentiate between food intake and activity level, this device may potentially be used for tracking both energy intake and energy expenditure.

Beyond activity tracking: next-generation wearable and implantable sensor technologies (Conference Presentation)

NASA Astrophysics Data System (ADS)

Mercier, Patrick

2017-05-01

Current-generation wearable devices have had success continuously measuring the activity and heart rate of subjects during exercise and daily life activities, resulting in interesting new data sets that can, though machine learning algorithms, predict a small subset of health conditions. However, this information is only very peripherally related to most health conditions, and thus offers limited utility to a wide range of the population. In this presentation, I will discuss emerging sensor technologies capable of measuring new and interesting parameters that can potentially offer much more meaningful and actionable data sets. Specifically, I will present recent work on wearable chemical sensors that can, for the first time, continuously monitor a suite of parameters like glucose, alcohol, lactate, and electrolytes, all while wirelessly delivering these results to a smart phone in real time. Demonstration platforms featuring patch, temporary tattoo, and mouthguard form factors will be described, in addition to the corresponding electronics necessary to perform sensor conditioning and wireless readout. Beyond chemical sensors, I will also discuss integration strategies with more conventional electrophysiological and physical parameters like ECG and strain gauges for cardiac and respiration rate monitoring, respectively. Finally, I will conclude the talk by introducing a new form of wireless communications in body-area networks that utilize the body itself as a channel for magnetic energy. Since the power consumption of conventional RF circuits often dominates the power of wearable devices, this new magnetic human body communication technique is specifically architected to dramatically reduce the path loss compared to conventional RF and capacitive human body communication techniques, thereby enabling ultra-low-power body area networks for next-generation wearable devices.

Feasibility of large-scale deployment of multiple wearable sensors in Parkinson's disease

PubMed Central

Hahn, Tim; Evers, Luc J. W.; de Vries, Nienke M.; Cohen, Eli; Afek, Michal; Bataille, Lauren; Daeschler, Margaret; Claes, Kasper; Boroojerdi, Babak; Terricabras, Dolors; Little, Max A.; Baldus, Heribert; Bloem, Bastiaan R.; Faber, Marjan J.

2017-01-01

Wearable devices can capture objective day-to-day data about Parkinson’s Disease (PD). This study aims to assess the feasibility of implementing wearable technology to collect data from multiple sensors during the daily lives of PD patients. The Parkinson@home study is an observational, two-cohort (North America, NAM; The Netherlands, NL) study. To recruit participants, different strategies were used between sites. Main enrolment criteria were self-reported diagnosis of PD, possession of a smartphone and age≥18 years. Participants used the Fox Wearable Companion app on a smartwatch and smartphone for a minimum of 6 weeks (NAM) or 13 weeks (NL). Sensor-derived measures estimated information about movement. Additionally, medication intake and symptoms were collected via self-reports in the app. A total of 953 participants were included (NL: 304, NAM: 649). Enrolment rate was 88% in the NL (n = 304) and 51% (n = 649) in NAM. Overall, 84% (n = 805) of participants contributed sensor data. Participants were compliant for 68% (16.3 hours/participant/day) of the study period in NL and for 62% (14.8 hours/participant/day) in NAM. Daily accelerometer data collection decreased 23% in the NL after 13 weeks, and 27% in NAM after 6 weeks. Data contribution was not affected by demographics, clinical characteristics or attitude towards technology, but was by the platform usability score in the NL (χ2 (2) = 32.014, p<0.001), and self-reported depression in NAM (χ2(2) = 6.397, p = .04). The Parkinson@home study shows that it is feasible to collect objective data using multiple wearable sensors in PD during daily life in a large cohort. PMID:29261709

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

Wearable Wide-Range Strain Sensors Based on Ionic Liquids and Monitoring of Human Activities

PubMed Central

Zhang, Shao-Hui; Wang, Feng-Xia; Li, Jia-Jia; Peng, Hong-Dan; Yan, Jing-Hui; Pan, Ge-Bo

2017-01-01

Wearable sensors for detection of human activities have encouraged the development of highly elastic sensors. In particular, to capture subtle and large-scale body motion, stretchable and wide-range strain sensors are highly desired, but still a challenge. Herein, a highly stretchable and transparent stain sensor based on ionic liquids and elastic polymer has been developed. The as-obtained sensor exhibits impressive stretchability with wide-range strain (from 0.1% to 400%), good bending properties and high sensitivity, whose gauge factor can reach 7.9. Importantly, the sensors show excellent biological compatibility and succeed in monitoring the diverse human activities ranging from the complex large-scale multidimensional motions to subtle signals, including wrist, finger and elbow joint bending, finger touch, breath, speech, swallow behavior and pulse wave. PMID:29135928

Soft elastomers with ionic liquid-filled cavities as strain isolating substrates for wearable electronics

PubMed Central

Wang, Liang; Kim, Jeonghyun; Liu, Yuhao; Xue, Yeguang; Ning, Rui; Wang, Xiufeng; Chung, Ha Uk; Feng, Xue; Rogers, John A.; Huang, Yonggang

2017-01-01

Managing the mechanical mismatch between hard semiconductor components and soft biological tissues represents a key challenge in the development of advanced forms of wearable electronic devices. An ultra-low modulus material or a liquid that surrounds the electronics and resides in a thin elastomeric shell provides a strain-isolation effect that not only enhances the wearability but also the range of stretchability in suitably designed devices. The results presented here build on these concepts by (1) replacing traditional liquids explored in the past, which have some non-negligible vapor pressure and finite permeability through the encapsulating elastomers, with ionic liquids to eliminate any possibility for leakage or evaporation, and (2) positioning the liquid between the electronics and the skin, within an enclosed, elastomeric microfluidic space, but not in direct contact with the active elements of the system, to avoid any negative consequences on electronic performance. Combined experimental and theoretical results establish the strain-isolating effects of this system, and the considerations that dictate mechanical collapse of the fluid-filled cavity. Examples in skin-mounted wearable include wireless sensors for measuring temperature and wired systems for recording mechano-acoustic responses. PMID:28026109

Soft Elastomers with Ionic Liquid-Filled Cavities as Strain Isolating Substrates for Wearable Electronics.

PubMed

Ma, Yinji; Pharr, Matt; Wang, Liang; Kim, Jeonghyun; Liu, Yuhao; Xue, Yeguang; Ning, Rui; Wang, Xiufeng; Chung, Ha Uk; Feng, Xue; Rogers, John A; Huang, Yonggang

2017-03-01

Managing the mechanical mismatch between hard semiconductor components and soft biological tissues represents a key challenge in the development of advanced forms of wearable electronic devices. An ultralow modulus material or a liquid that surrounds the electronics and resides in a thin elastomeric shell provides a strain-isolation effect that enhances not only the wearability but also the range of stretchability in suitably designed devices. The results presented here build on these concepts by (1) replacing traditional liquids explored in the past, which have some nonnegligible vapor pressure and finite permeability through the encapsulating elastomers, with ionic liquids to eliminate any possibility for leakage or evaporation, and (2) positioning the liquid between the electronics and the skin, within an enclosed, elastomeric microfluidic space, but not in direct contact with the active elements of the system, to avoid any negative consequences on electronic performance. Combined experimental and theoretical results establish the strain-isolating effects of this system, and the considerations that dictate mechanical collapse of the fluid-filled cavity. Examples in skin-mounted wearable include wireless sensors for measuring temperature and wired systems for recording mechano-acoustic responses. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Wearable Smart System for Visually Impaired People

PubMed Central

2018-01-01

In this paper, we present a wearable smart system to help visually impaired persons (VIPs) walk by themselves through the streets, navigate in public places, and seek assistance. The main components of the system are a microcontroller board, various sensors, cellular communication and GPS modules, and a solar panel. The system employs a set of sensors to track the path and alert the user of obstacles in front of them. The user is alerted by a sound emitted through a buzzer and by vibrations on the wrist, which is helpful when the user has hearing loss or is in a noisy environment. In addition, the system alerts people in the surroundings when the user stumbles over or requires assistance, and the alert, along with the system location, is sent as a phone message to registered mobile phones of family members and caregivers. In addition, the registered phones can be used to retrieve the system location whenever required and activate real-time tracking of the VIP. We tested the system prototype and verified its functionality and effectiveness. The proposed system has more features than other similar systems. We expect it to be a useful tool to improve the quality of life of VIPs. PMID:29533970

Wearable Smart System for Visually Impaired People.

PubMed

Ramadhan, Ali Jasim

2018-03-13

In this paper, we present a wearable smart system to help visually impaired persons (VIPs) walk by themselves through the streets, navigate in public places, and seek assistance. The main components of the system are a microcontroller board, various sensors, cellular communication and GPS modules, and a solar panel. The system employs a set of sensors to track the path and alert the user of obstacles in front of them. The user is alerted by a sound emitted through a buzzer and by vibrations on the wrist, which is helpful when the user has hearing loss or is in a noisy environment. In addition, the system alerts people in the surroundings when the user stumbles over or requires assistance, and the alert, along with the system location, is sent as a phone message to registered mobile phones of family members and caregivers. In addition, the registered phones can be used to retrieve the system location whenever required and activate real-time tracking of the VIP. We tested the system prototype and verified its functionality and effectiveness. The proposed system has more features than other similar systems. We expect it to be a useful tool to improve the quality of life of VIPs.

Deformable devices with integrated functional nanomaterials for wearable electronics.

PubMed

Kim, Jaemin; Lee, Jongsu; Son, Donghee; Choi, Moon Kee; Kim, Dae-Hyeong

2016-01-01

As the market and related industry for wearable electronics dramatically expands, there are continuous and strong demands for flexible and stretchable devices to be seamlessly integrated with soft and curvilinear human skin or clothes. However, the mechanical mismatch between the rigid conventional electronics and the soft human body causes many problems. Therefore, various prospective nanomaterials that possess a much lower flexural rigidity than their bulk counterparts have rapidly established themselves as promising electronic materials replacing rigid silicon and/or compound semiconductors in next-generation wearable devices. Many hybrid structures of multiple nanomaterials have been also developed to pursue both high performance and multifunctionality. Here, we provide an overview of state-of-the-art wearable devices based on one- or two-dimensional nanomaterials (e.g., carbon nanotubes, graphene, single-crystal silicon and oxide nanomembranes, organic nanomaterials and their hybrids) in combination with zero-dimensional functional nanomaterials (e.g., metal/oxide nanoparticles and quantum dots). Starting from an introduction of materials strategies, we describe device designs and the roles of individual ones in integrated systems. Detailed application examples of wearable sensors/actuators, memories, energy devices, and displays are also presented.

Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios.

PubMed

de Arriba-Pérez, Francisco; Caeiro-Rodríguez, Manuel; Santos-Gago, Juan M

2016-09-21

Over recent years, we have witnessed the development of mobile and wearable technologies to collect data from human vital signs and activities. Nowadays, wrist wearables including sensors (e.g., heart rate, accelerometer, pedometer) that provide valuable data are common in market. We are working on the analytic exploitation of this kind of data towards the support of learners and teachers in educational contexts. More precisely, sleep and stress indicators are defined to assist teachers and learners on the regulation of their activities. During this development, we have identified interoperability challenges related to the collection and processing of data from wearable devices. Different vendors adopt specific approaches about the way data can be collected from wearables into third-party systems. This hinders such developments as the one that we are carrying out. This paper contributes to identifying key interoperability issues in this kind of scenario and proposes guidelines to solve them. Taking into account these topics, this work is situated in the context of the standardization activities being carried out in the Internet of Things and Machine to Machine domains.

Deformable devices with integrated functional nanomaterials for wearable electronics

NASA Astrophysics Data System (ADS)

Kim, Jaemin; Lee, Jongsu; Son, Donghee; Choi, Moon Kee; Kim, Dae-Hyeong

2016-03-01

As the market and related industry for wearable electronics dramatically expands, there are continuous and strong demands for flexible and stretchable devices to be seamlessly integrated with soft and curvilinear human skin or clothes. However, the mechanical mismatch between the rigid conventional electronics and the soft human body causes many problems. Therefore, various prospective nanomaterials that possess a much lower flexural rigidity than their bulk counterparts have rapidly established themselves as promising electronic materials replacing rigid silicon and/or compound semiconductors in next-generation wearable devices. Many hybrid structures of multiple nanomaterials have been also developed to pursue both high performance and multifunctionality. Here, we provide an overview of state-of-the-art wearable devices based on one- or two-dimensional nanomaterials (e.g., carbon nanotubes, graphene, single-crystal silicon and oxide nanomembranes, organic nanomaterials and their hybrids) in combination with zero-dimensional functional nanomaterials (e.g., metal/oxide nanoparticles and quantum dots). Starting from an introduction of materials strategies, we describe device designs and the roles of individual ones in integrated systems. Detailed application examples of wearable sensors/actuators, memories, energy devices, and displays are also presented.

Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios

PubMed Central

de Arriba-Pérez, Francisco; Caeiro-Rodríguez, Manuel; Santos-Gago, Juan M.

2016-01-01

Over recent years, we have witnessed the development of mobile and wearable technologies to collect data from human vital signs and activities. Nowadays, wrist wearables including sensors (e.g., heart rate, accelerometer, pedometer) that provide valuable data are common in market. We are working on the analytic exploitation of this kind of data towards the support of learners and teachers in educational contexts. More precisely, sleep and stress indicators are defined to assist teachers and learners on the regulation of their activities. During this development, we have identified interoperability challenges related to the collection and processing of data from wearable devices. Different vendors adopt specific approaches about the way data can be collected from wearables into third-party systems. This hinders such developments as the one that we are carrying out. This paper contributes to identifying key interoperability issues in this kind of scenario and proposes guidelines to solve them. Taking into account these topics, this work is situated in the context of the standardization activities being carried out in the Internet of Things and Machine to Machine domains. PMID:27657081

Wearable Spiral Passive Electromagnetic Sensor (SPES) glove for sign language recognition of alphabet letters and numbers: a preliminary study

NASA Astrophysics Data System (ADS)

Iervolino, Onorio; Meo, Michele

2017-04-01

Sign language is a method of communication for deaf-mute people with articulated gestures and postures of hands and fingers to represent alphabet letters or complete words. Recognizing gestures is a difficult task, due to intrapersonal and interpersonal variations in performing them. This paper investigates the use of Spiral Passive Electromagnetic Sensor (SPES) as a motion recognition tool. An instrumented glove integrated with wearable multi-SPES sensors was developed to encode data and provide a unique response for each hand gesture. The device can be used for recognition of gestures; motion control and well-defined gesture sets such as sign languages. Each specific gesture was associated to a unique sensor response. The gloves encode data regarding the gesture directly in the frequency spectrum response of the SPES. The absence of chip or complex electronic circuit make the gloves light and comfortable to wear. Results showed encouraging data to use SPES in wearable applications.

A wearable fingernail chemical sensing platform: pH sensing at your fingertips.

PubMed

Kim, Jayoung; Cho, Thomas N; Valdés-Ramírez, Gabriela; Wang, Joseph

2016-04-01

This article demonstrates an example of a wearable chemical sensor based on a fingernail platform. Fingernails represent an attractive wearable platform, merging beauty products with chemical sensing, to enable monitoring of our surrounding environment. The new colorimetric pH fingernail sensor relies on coating artificial nails with a recognition layer consisted of pH indicators entrapped in a polyvinyl chloride (PVC) matrix. Such color changing fingernails offer fast and reversible response to pH changes, repeated use, and intense color change detected easily with naked eye. The PVC matrix prevents leaching out of the indicator molecules from the fingernail sensor toward such repeated use. The limited narrow working pH range of a single pH indicator has been addressed by multiplexing three different pH indicators: bromothymol blue (pH 6.0-7.6), bromocresol green (pH 3.8-5.4), and cresol red (pH 7.2-8.8), as demonstrated for analyses of real-life samples of acidic, neutral, and basic character. The new concept of an optical wearable chemical sensor on fingernail platforms can be expanded towards diverse analytes for various applications in connection to the judicious design of the recognition layer. Copyright © 2016 Elsevier B.V. All rights reserved.

Wearable, Flexible, and Multifunctional Healthcare Device with an ISFET Chemical Sensor for Simultaneous Sweat pH and Skin Temperature Monitoring.

PubMed

Nakata, Shogo; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2017-03-24

Real-time daily healthcare monitoring may increase the chances of predicting and diagnosing diseases in their early stages which, currently, occurs most frequently during medical check-ups. Next-generation noninvasive healthcare devices, such as flexible multifunctional sensor sheets designed to be worn on skin, are considered to be highly suitable candidates for continuous real-time health monitoring. For healthcare applications, acquiring data on the chemical state of the body, alongside physical characteristics such as body temperature and activity, are extremely important for predicting and identifying potential health conditions. To record these data, in this study, we developed a wearable, flexible sweat chemical sensor sheet for pH measurement, consisting of an ion-sensitive field-effect transistor (ISFET) integrated with a flexible temperature sensor: we intend to use this device as the foundation of a fully integrated, wearable healthcare patch in the future. After characterizing the performance, mechanical flexibility, and stability of the sensor, real-time measurements of sweat pH and skin temperature are successfully conducted through skin contact. This flexible integrated device has the potential to be developed into a chemical sensor for sweat for applications in healthcare and sports.

Application of data fusion techniques and technologies for wearable health monitoring.

PubMed

King, Rachel C; Villeneuve, Emma; White, Ruth J; Sherratt, R Simon; Holderbaum, William; Harwin, William S

2017-04-01

Technological advances in sensors and communications have enabled discrete integration into everyday objects, both in the home and about the person. Information gathered by monitoring physiological, behavioural, and social aspects of our lives, can be used to achieve a positive impact on quality of life, health, and well-being. Wearable sensors are at the cusp of becoming truly pervasive, and could be woven into the clothes and accessories that we wear such that they become ubiquitous and transparent. To interpret the complex multidimensional information provided by these sensors, data fusion techniques are employed to provide a meaningful representation of the sensor outputs. This paper is intended to provide a short overview of data fusion techniques and algorithms that can be used to interpret wearable sensor data in the context of health monitoring applications. The application of these techniques are then described in the context of healthcare including activity and ambulatory monitoring, gait analysis, fall detection, and biometric monitoring. A snap-shot of current commercially available sensors is also provided, focusing on their sensing capability, and a commentary on the gaps that need to be bridged to bring research to market. Copyright © 2017. Published by Elsevier Ltd.

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.

An Electronic Patch for wearable health monitoring by reflectance pulse oximetry.

PubMed

Haahr, Rasmus G; Duun, Sune B; Toft, Mette H; Belhage, Bo; Larsen, Jan; Birkelund, Karen; Thomsen, Erik V

2012-02-01

We report the development of an Electronic Patch for wearable health monitoring. The Electronic Patch is a new health monitoring system incorporating biomedical sensors, microelectronics, radio frequency (RF) communication, and a battery embedded in a 3-dimensional hydrocolloid polymer. In this paper the Electronic Patch is demonstrated with a new optical biomedical sensor for reflectance pulse oximetry so that the Electronic Patch in this case can measure the pulse and the oxygen saturation. The reflectance pulse oximetry solution is based on a recently developed annular backside silicon photodiode to enable low power consumption by the light emitting components. The Electronic Patch has a disposable part of soft adhesive hydrocolloid polymer and a reusable part of hard polylaurinlactam. The disposable part contains the battery. The reusable part contains the reflectance pulse oximetry sensor and microelectronics. The reusable part is 'clicked' into the disposable part when the patch is prepared for use. The patch has a size of 88 mm by 60 mm and a thickness of 5 mm.

A FBG pulse wave demodulation method based on PCF modal interference filter

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Xu, Shan; Shen, Ziqi; Zhao, Junfa; Miao, Changyun; Bai, Hua

2016-10-01

Fiber optic sensor embedded in textiles has been a new direction of researching smart wearable technology. Pulse signal which is generated by heart beat contains vast amounts of physio-pathological information about the cardiovascular system. Therefore, the research for textile-based fiber optic sensor which can detect pulse wave has far-reaching effects on early discovery and timely treatment of cardiovascular diseases. A novel wavelength demodulation method based on photonic crystal fiber (PCF) modal interference filter is proposed for the purpose of developing FBG pulse wave sensing system embedded in smart clothing. The mechanism of the PCF modal interference and the principle of wavelength demodulation based on In-line Mach-Zehnder interferometer (In-line MZI) are analyzed in theory. The fabricated PCF modal interferometer has the advantages of good repeatability and low temperature sensitivity of 3.5pm/°C from 25°C to 60°C. The designed demodulation system can achieve linear demodulation in the range of 2nm, with the wavelength resolution of 2.2pm and the wavelength sensitivity of 0.055nm-1. The actual experiments' result indicates that the pulse wave can be well detected by this demodulation method, which is in accordance with the commercial demodulation instrument (SM130) and more sensitive than the traditional piezoelectric pulse sensor. This demodulation method provides important references for the research of smart clothing based on fiber grating sensor embedded in textiles and accelerates the developments of wearable fiber optic sensors technology.

Flexible self-powered piezo-supercapacitor system for wearable electronics.

PubMed

Gilshteyn, Evgenia P; Amanbaev, Daler; Silibin, Maxim V; Sysa, Artem; Kondrashov, Vladislav A; Anisimov, Anton S; Kallio, Tanja; Nasibulin, Albert G

2018-08-10

The integration of energy harvesting and energy storage in a single device both enables the conversion of ambient energy into electricity and provides a sustainable power source for various electronic devices and systems. On the other hand, mechanical flexibility, coupled with optical transparency of the energy storage devices, is required for many applications, ranging from self-powered rolled-up displays to wearable optoelectronic devices. We integrate a piezoelectric poly(vinylidene-trifluoroethylene) (P(VDF-TrFE)) film into a flexible supercapacitor system to harvest and store the energy. The asymmetric output characteristics of the piezoelectric P(VDF-TrFE) film under mechanical impacts results in effective charging of the supercapacitors. The integrated piezo-supercapacitor exhibits a specific capacitance of 50 F g -1 . The open-circuit voltage of the flexible and transparent supercapacitor reached 500 mV within 20 s during the mechanical action. Our hybridized energy harvesting and storage device can be further extended to provide a sustainable power source for various types of sensors integrated into wearable units.

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%.

Sub-micron surface plasmon resonance sensor systems

NASA Technical Reports Server (NTRS)

Glazier, James A. (Inventor); Amarie, Dragos (Inventor)

2013-01-01

Wearable or implantable devices combining microfluidic control of sample and reagent flow and micro-cavity surface plasmon resonance sensors functionalized with surface treatments or coatings capable of specifically binding to target analytes, ligands, or molecules in a bodily fluid are provided. The devices can be used to determine the presence and concentration of target analytes in the bodily fluids and thereby help diagnose, monitor or detect changes in disease conditions.

Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System

PubMed Central

2018-01-01

Partial body weight support or loading sit-to-stand (STS) rehabilitation can be useful for persons with lower limb dysfunction to achieve movement again based on the internal residual muscle force and external assistance. To explicate how the muscles contribute to the kinetics and kinematics of STS performance by non-invasive in vitro detection and to nondestructively estimate the muscle contributions to STS training with different loadings, a wearable sensor system was developed with ground reaction force (GRF) platforms, motion capture inertial sensors and electromyography (EMG) sensors. To estimate the internal moments of hip, knee and ankle joints and quantify the contributions of individual muscle and gravity to STS movement, the inverse dynamics analysis on a simplified STS biomechanical model with external loading is proposed. The functional roles of the lower limb individual muscles (rectus femoris (RF), gluteus maximus (GM), vastus lateralis (VL), tibialis anterior (TA) and gastrocnemius (GAST)) during STS motion and the mechanism of the muscles’ synergies to perform STS-specific subtasks were analyzed. The muscle contributions to the biomechanical STS subtasks of vertical propulsion, anteroposterior (AP) braking and propulsion for body balance in the sagittal plane were quantified by experimental studies with EMG, kinematic and kinetic data. PMID:29587391

Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System.

PubMed

Liu, Kun; Liu, Yong; Yan, Jianchao; Sun, Zhenyuan

2018-03-25

Partial body weight support or loading sit-to-stand (STS) rehabilitation can be useful for persons with lower limb dysfunction to achieve movement again based on the internal residual muscle force and external assistance. To explicate how the muscles contribute to the kinetics and kinematics of STS performance by non-invasive in vitro detection and to nondestructively estimate the muscle contributions to STS training with different loadings, a wearable sensor system was developed with ground reaction force (GRF) platforms, motion capture inertial sensors and electromyography (EMG) sensors. To estimate the internal moments of hip, knee and ankle joints and quantify the contributions of individual muscle and gravity to STS movement, the inverse dynamics analysis on a simplified STS biomechanical model with external loading is proposed. The functional roles of the lower limb individual muscles (rectus femoris (RF), gluteus maximus (GM), vastus lateralis (VL), tibialis anterior (TA) and gastrocnemius (GAST)) during STS motion and the mechanism of the muscles' synergies to perform STS-specific subtasks were analyzed. The muscle contributions to the biomechanical STS subtasks of vertical propulsion, anteroposterior (AP) braking and propulsion for body balance in the sagittal plane were quantified by experimental studies with EMG, kinematic and kinetic data.

Posture and activity recognition and energy expenditure estimation in a wearable platform.

PubMed

Sazonov, Edward; Hegde, Nagaraj; Browning, Raymond C; Melanson, Edward L; Sazonova, Nadezhda A

2015-07-01

The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here, we describe the use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time recognition of various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we compare the use of support vector machines (SVM), multinomial logistic discrimination (MLD), and multilayer perceptrons (MLP) for posture and activity classification followed by activity-branched EE estimation. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a 4-h stay in a room calorimeter. MLD and MLP demonstrated activity classification accuracy virtually identical to SVM (∼ 95%) while reducing the running time and the memory requirements by a factor of >10 3. Comparison of per-minute EE estimation using activity-branched models resulted in accurate EE prediction (RMSE = 0.78 kcal/min for SVM and MLD activity classification, 0.77 kcal/min for MLP versus RMSE of 0.75 kcal/min for manual annotation). These results suggest that low-power computational algorithms can be successfully used for real-time physical activity monitoring and EE estimation on a wearable platform.

Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors

PubMed Central

2012-01-01

A brain-computer interface (BCI) is a communication system that can help users interact with the outside environment by translating brain signals into machine commands. The use of electroencephalographic (EEG) signals has become the most common approach for a BCI because of their usability and strong reliability. Many EEG-based BCI devices have been developed with traditional wet- or micro-electro-mechanical-system (MEMS)-type EEG sensors. However, those traditional sensors have uncomfortable disadvantage and require conductive gel and skin preparation on the part of the user. Therefore, acquiring the EEG signals in a comfortable and convenient manner is an important factor that should be incorporated into a novel BCI device. In the present study, a wearable, wireless and portable EEG-based BCI device with dry foam-based EEG sensors was developed and was demonstrated using a gaming control application. The dry EEG sensors operated without conductive gel; however, they were able to provide good conductivity and were able to acquire EEG signals effectively by adapting to irregular skin surfaces and by maintaining proper skin-sensor impedance on the forehead site. We have also demonstrated a real-time cognitive stage detection application of gaming control using the proposed portable device. The results of the present study indicate that using this portable EEG-based BCI device to conveniently and effectively control the outside world provides an approach for researching rehabilitation engineering. PMID:22284235

An affordable wearable video system for emergency response training

NASA Astrophysics Data System (ADS)

King-Smith, Deen; Mikkilineni, Aravind; Ebert, David; Collins, Timothy; Delp, Edward J.

2009-02-01

Many emergency response units are currently faced with restrictive budgets that prohibit their use of advanced technology-based training solutions. Our work focuses on creating an affordable, mobile, state-of-the-art emergency response training solution through the integration of low-cost, commercially available products. The system we have developed consists of tracking, audio, and video capability, coupled with other sensors that can all be viewed through a unified visualization system. In this paper we focus on the video sub-system which helps provide real time tracking and video feeds from the training environment through a system of wearable and stationary cameras. These two camera systems interface with a management system that handles storage and indexing of the video during and after training exercises. The wearable systems enable the command center to have live video and tracking information for each trainee in the exercise. The stationary camera systems provide a fixed point of reference for viewing action during the exercise and consist of a small Linux based portable computer and mountable camera. The video management system consists of a server and database which work in tandem with a visualization application to provide real-time and after action review capability to the training system.

The Use of Wearable Inertial Motion Sensors in Human Lower Limb Biomechanics Studies: A Systematic Review

PubMed Central

Fong, Daniel Tik-Pui; Chan, Yue-Yan

2010-01-01

Wearable motion sensors consisting of accelerometers, gyroscopes and magnetic sensors are readily available nowadays. The small size and low production costs of motion sensors make them a very good tool for human motions analysis. However, data processing and accuracy of the collected data are important issues for research purposes. In this paper, we aim to review the literature related to usage of inertial sensors in human lower limb biomechanics studies. A systematic search was done in the following search engines: ISI Web of Knowledge, Medline, SportDiscus and IEEE Xplore. Thirty nine full papers and conference abstracts with related topics were included in this review. The type of sensor involved, data collection methods, study design, validation methods and its applications were reviewed. PMID:22163542

The use of wearable inertial motion sensors in human lower limb biomechanics studies: a systematic review.

PubMed

Fong, Daniel Tik-Pui; Chan, Yue-Yan

2010-01-01

Wearable motion sensors consisting of accelerometers, gyroscopes and magnetic sensors are readily available nowadays. The small size and low production costs of motion sensors make them a very good tool for human motions analysis. However, data processing and accuracy of the collected data are important issues for research purposes. In this paper, we aim to review the literature related to usage of inertial sensors in human lower limb biomechanics studies. A systematic search was done in the following search engines: ISI Web of Knowledge, Medline, SportDiscus and IEEE Xplore. Thirty nine full papers and conference abstracts with related topics were included in this review. The type of sensor involved, data collection methods, study design, validation methods and its applications were reviewed.

POF-IMU sensor system: A fusion between inertial measurement units and POF sensors for low-cost and highly reliable systems

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Vargas-Valencia, Laura; dos Santos, Wilian M.; Schneider, Felipe B. A.; Siqueira, Adriano A. G.; Pontes, Maria José; Frizera, Anselmo

2018-07-01

This paper presents a low cost and highly reliable system for angle measurement based on a sensor fusion between inertial and fiber optic sensors. The system consists of the sensor fusion through Kalman filter of two inertial measurement units (IMUs) and an intensity variation-based polymer optical fiber (POF) curvature sensor. In addition, the IMU was applied as a reference for a compensation technique of POF curvature sensor hysteresis. The proposed system was applied on the knee angle measurement of a lower limb exoskeleton in flexion/extension cycles and in gait analysis. Results show the accuracy of the system, where the Root Mean Square Error (RMSE) between the POF-IMU sensor system and the encoder was below 4° in the worst case and about 1° in the best case. Then, the POF-IMU sensor system was evaluated as a wearable sensor for knee joint angle assessment without the exoskeleton, where its suitability for this purpose was demonstrated. The results obtained in this paper pave the way for future applications of sensor fusion between electronic and fiber optic sensors in movement analysis.

Development of gait segmentation methods for wearable foot pressure sensors.

PubMed

Crea, S; De Rossi, S M M; Donati, M; Reberšek, P; Novak, D; Vitiello, N; Lenzi, T; Podobnik, J; Munih, M; Carrozza, M C

2012-01-01

We present an automated segmentation method based on the analysis of plantar pressure signals recorded from two synchronized wireless foot insoles. Given the strict limits on computational power and power consumption typical of wearable electronic components, our aim is to investigate the capability of a Hidden Markov Model machine-learning method, to detect gait phases with different levels of complexity in the processing of the wearable pressure sensors signals. Therefore three different datasets are developed: raw voltage values, calibrated sensor signals and a calibrated estimation of total ground reaction force and position of the plantar center of pressure. The method is tested on a pool of 5 healthy subjects, through a leave-one-out cross validation. The results show high classification performances achieved using estimated biomechanical variables, being on average the 96%. Calibrated signals and raw voltage values show higher delays and dispersions in phase transition detection, suggesting a lower reliability for online applications.

Optical sensor array platform based on polymer electronic devices

NASA Astrophysics Data System (ADS)

Koetse, Marc M.; Rensing, Peter A.; Sharpe, Ruben B. A.; van Heck, Gert T.; Allard, Bart A. M.; Meulendijks, Nicole N. M. M.; Kruijt, Peter G. M.; Tijdink, Marcel W. W. J.; De Zwart, René M.; Houben, René J.; Enting, Erik; van Veen, Sjaak J. J. F.; Schoo, Herman F. M.

2007-10-01

Monitoring of personal wellbeing and optimizing human performance are areas where sensors have only begun to be used. One of the reasons for this is the specific demands that these application areas put on the underlying technology and system properties. In many cases these sensors will be integrated in clothing, be worn on the skin, or may even be placed inside the body. This implies that flexibility and wearability of the systems is essential for their success. Devices based on polymer semiconductors allow for these demands since they can be fabricated with thin film technology. The use of thin film device technology allows for the fabrication of very thin sensors (e.g. integrated in food product packaging), flexible or bendable sensors in wearables, large area/distributed sensors, and intrinsically low-cost applications in disposable products. With thin film device technology a high level of integration can be achieved with parts that analyze signals, process and store data, and interact over a network. Integration of all these functions will inherently lead to better cost/performance ratios, especially if printing and other standard polymer technology such as high precision moulding is applied for the fabrication. In this paper we present an optical transmission sensor array based on polymer semiconductor devices made by thin film technology. The organic devices, light emitting diodes, photodiodes and selective medium chip, are integrated with classic electronic components. Together they form a versatile sensor platform that allows for the quantitative measurement of 100 channels and communicates wireless with a computer. The emphasis is given to the sensor principle, the design, fabrication technology and integration of the thin film devices.

Printing-based fabrication method using sacrificial paper substrates for flexible and wearable microfluidic devices

NASA Astrophysics Data System (ADS)

Chung, Daehan; Gray, Bonnie L.

2017-11-01

We present a simple, fast, and inexpensive new printing-based fabrication process for flexible and wearable microfluidic channels and devices. Microfluidic devices are fabricated on textiles (fabric) for applications in clothing-based wearable microfluidic sensors and systems. The wearable and flexible microfluidic devices are comprised of water-insoluable screen-printable plastisol polymer. Sheets of paper are used as sacrificial substrates for multiple layers of polymer on the fabric’s surface. Microfluidic devices can be made within a short time using simple processes and inexpensive equipment that includes a laser cutter and a thermal laminator. The fabrication process is characterized to demonstrate control of microfluidic channel thickness and width. Film thickness smaller than 100 micrometers and lateral dimensions smaller than 150 micrometers are demonstrated. A flexible microfluidic mixer is also developed on fabric and successfully tested on both flat and curved surfaces at volumetric flow rates ranging from 5.5-46 ml min-1.

Improving spatial resolution in skin-contact thermography: comparison between a spline based and linear interpolation.

PubMed

Giansanti, Daniele

2008-07-01

A wearable device for skin-contact thermography [Giansanti D, Maccioni G. Development and testing of a wearable integrated thermometer sensor for skin contact thermography. Med Eng Phys 2006 [ahead of print

A Q-backpropagated time delay neural network for diagnosing severity of gait disturbances in Parkinson's disease.

PubMed

Nancy Jane, Y; Khanna Nehemiah, H; Arputharaj, Kannan

2016-04-01

Parkinson's disease (PD) is a movement disorder that affects the patient's nervous system and health-care applications mostly uses wearable sensors to collect these data. Since these sensors generate time stamped data, analyzing gait disturbances in PD becomes challenging task. The objective of this paper is to develop an effective clinical decision-making system (CDMS) that aids the physician in diagnosing the severity of gait disturbances in PD affected patients. This paper presents a Q-backpropagated time delay neural network (Q-BTDNN) classifier that builds a temporal classification model, which performs the task of classification and prediction in CDMS. The proposed Q-learning induced backpropagation (Q-BP) training algorithm trains the Q-BTDNN by generating a reinforced error signal. The network's weights are adjusted through backpropagating the generated error signal. For experimentation, the proposed work uses a PD gait database, which contains gait measures collected through wearable sensors from three different PD research studies. The experimental result proves the efficiency of Q-BP in terms of its improved classification accuracy of 91.49%, 92.19% and 90.91% with three datasets accordingly compared to other neural network training algorithms. Copyright © 2016 Elsevier Inc. All rights reserved.

Flexible and wearable 3D graphene sensor with 141 KHz frequency signal response capability

NASA Astrophysics Data System (ADS)

Xu, R.; Zhang, H.; Cai, Y.; Ruan, J.; Qu, K.; Liu, E.; Ni, X.; Lu, M.; Dong, X.

2017-09-01

We developed a flexible force sensor consisting of 3D graphene foam (GF) encapsulated in flexible polydimethylsiloxane (PDMS). Because the 3D GF/PDMS sensor is based on the transformation of an electronic band structure aroused by static mechanical strain or KHz vibration, it can detect frequency signals by both tuning fork tests and piezoelectric ceramic transducer tests, which showed a clear linear response from audio frequencies, including frequencies up to 141 KHz in the ultrasound range. Because of their excellent response with a wide bandwidth, the 3D GF/PDMS sensors are attractive for interactive wearable devices or artificial prosthetics capable of perceiving seismic waves, ultrasonic waves, shock waves, and transient pressures.

Enabling Smart Air Conditioning by Sensor Development: A Review

PubMed Central

Cheng, Chin-Chi; Lee, Dasheng

2016-01-01

The study investigates the development of sensors, in particular the use of thermo-fluidic sensors and occupancy detectors, to achieve smart operation of air conditioning systems. Smart operation refers to the operation of air conditioners by the reinforcement of interaction to achieve both thermal comfort and energy efficiency. Sensors related to thermal comfort include those of temperature, humidity, and pressure and wind velocity anemometers. Improvements in their performance in the past years have been studied by a literature survey. Traditional occupancy detection using passive infra-red (PIR) sensors and novel methodologies using smartphones and wearable sensors are both discussed. Referring to the case studies summarized in this study, air conditioning energy savings are evaluated quantitatively. Results show that energy savings of air conditioners before 2000 was 11%, and 30% after 2000 by the integration of thermo-fluidic sensors and occupancy detectors. By utilizing wearable sensing to detect the human motions, metabolic rates and related information, the energy savings can reach up to 46.3% and keep the minimum change of predicted mean vote (∆PMV→0), which means there is no compromise in thermal comfort. This enables smart air conditioning to compensate for the large variations from person to person in terms of physiological and psychological satisfaction, and find an optimal temperature for everyone in a given space. However, this tendency should be evidenced by more experimental results in the future. PMID:27916906

A Novel Remote Rehabilitation System with the Fusion of Noninvasive Wearable Device and Motion Sensing for Pulmonary Patients.

PubMed

Tey, Chuang-Kit; An, Jinyoung; Chung, Wan-Young

2017-01-01

Chronic obstructive pulmonary disease is a type of lung disease caused by chronically poor airflow that makes breathing difficult. As a chronic illness, it typically worsens over time. Therefore, pulmonary rehabilitation exercises and patient management for extensive periods of time are required. This paper presents a remote rehabilitation system for a multimodal sensors-based application for patients who have chronic breathing difficulties. The process involves the fusion of sensory data-captured motion data by stereo-camera and photoplethysmogram signal by a wearable PPG sensor-that are the input variables of a detection and evaluation framework. In addition, we incorporated a set of rehabilitation exercises specific for pulmonary patients into the system by fusing sensory data. Simultaneously, the system also features medical functions that accommodate the needs of medical professionals and those which ease the use of the application for patients, including exercises for tracking progress, patient performance, exercise assignments, and exercise guidance. Finally, the results indicate the accurate determination of pulmonary exercises from the fusion of sensory data. This remote rehabilitation system provides a comfortable and cost-effective option in the healthcare rehabilitation system.

mDurance: A Novel Mobile Health System to Support Trunk Endurance Assessment

PubMed Central

Banos, Oresti; Moral-Munoz, Jose Antonio; Diaz-Reyes, Ignacio; Arroyo-Morales, Manuel; Damas, Miguel; Herrera-Viedma, Enrique; Hong, Choong Seon; Lee, Sungyong; Pomares, Hector; Rojas, Ignacio; Villalonga, Claudia

2015-01-01

Low back pain is the most prevalent musculoskeletal condition. This disorder constitutes one of the most common causes of disability worldwide, and as a result, it has a severe socioeconomic impact. Endurance tests are normally considered in low back pain rehabilitation practice to assess the muscle status. However, traditional procedures to evaluate these tests suffer from practical limitations, which potentially lead to inaccurate diagnoses. The use of digital technologies is considered here to facilitate the task of the expert and to increase the reliability and interpretability of the endurance tests. This work presents mDurance, a novel mobile health system aimed at supporting specialists in the functional assessment of trunk endurance by using wearable and mobile devices. The system employs a wearable inertial sensor to track the patient trunk posture, while portable electromyography sensors are used to seamlessly measure the electrical activity produced by the trunk muscles. The information registered by the sensors is processed and managed by a mobile application that facilitates the expert's normal routine, while reducing the impact of human errors and expediting the analysis of the test results. In order to show the potential of the mDurance system, a case study has been conducted. The results of this study prove the reliability of mDurance and further demonstrate that practitioners are certainly interested in the regular use of a system of this nature. PMID:26057034

Fall Detection Devices and their Use with Older Adults: A Systematic Review

PubMed Central

Chaudhuri, Shomir; Thompson, Hilaire; Demiris, George

2013-01-01

Background Falls represent a significant threat to the health and independence of adults 65 years of age and older. As a wide variety and large amount of passive monitoring systems are currently and increasingly available to detect when an individual has fallen, there is a need to analyze and synthesize the evidence regarding their ability to accurately detect falls to determine which systems are most effective. Objectives The purpose of this literature review is to systematically assess the current state of design and implementation of fall detection devices. This review also examines the extent to which these devices have been tested in the real world as well as the acceptability of these devices to older adults. Data sources A systematic literature review was conducted in PubMed, CINAHL, EMBASE and PsycINFO from their respective inception dates to June 25, 2013. Study Eligibility Criteria and Interventions Articles were included if they discussed a project or multiple projects involving a system with the purpose of detecting a fall in adults. It was not a requirement for inclusion in this review that the system targets persons over the age of 65. Articles were excluded if they were not written in English or if they looked at fall risk, fall detection in children, fall prevention or a Personal Emergency Response device. Study appraisal and synthesis methods Studies were initially divided into those using sensitivity, specificity or accuracy in their evaluation methods, and those using other methods to evaluate their devices. Studies were further classified into wearable devices and non-wearable devices. Studies were appraised for inclusion of older adults in sample and if evaluation included real world settings. Results This review identified 57 projects that used wearable systems and 35 projects using non-wearable systems, regardless of evaluation technique. Non-wearable systems included cameras, motion sensors, microphones and floor sensors. Of the projects examining wearable systems, only 7.1% reported monitoring older adults in a real world setting. There were no studies of non-wearable devices that used older adults as subjects in either a lab or a real world setting. In general, older adults appear to be interested in using such devices although they express concerns over privacy and understanding exactly what the device is doing at specific times. Limitations This systematic review was limited to articles written in English and did not include gray literature. Manual paper screening and review processes may have been subject to interpretive bias. Conclusions and implications of key findings There exists a large body of working describing various fall detection devices. The challenge in this area is to create highly accurate unobtrusive devices. From this review it appears that the technology is becoming more able to accomplish such a task. There is a need now for more real world tests as well as standardization of the evaluation of these devices. PMID:24406708

Embedded sensor systems for health - providing the tools in future healthcare.

PubMed

Lindén, Maria; Björkman, Mats

2014-01-01

Wearable, embedded sensor systems for health applications are foreseen to be enablers in the future healthcare. They will provide ubiquitous monitoring of multiple parameters without restricting the person to stay at home or in the hospital. By following trend changes in the health status, early deteriorations will be detected and treatment can start earlier. Also health prevention will be supported. Such future healthcare requires technology development, including miniaturized sensors, smart textiles and wireless communication. The tremendous amount of data generated by these systems calls for both signal processing and decision support to guarantee the quality of data and avoid overflow of information. Safe and secure communications have to protect the integrity of the persons monitored.

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.

Wireless body sensor networks for health-monitoring applications.

PubMed

Hao, Yang; Foster, Robert

2008-11-01

Current wireless technologies, such as wireless body area networks and wireless personal area networks, provide promising applications in medical monitoring systems to measure specified physiological data and also provide location-based information, if required. With the increasing sophistication of wearable and implantable medical devices and their integration with wireless sensors, an ever-expanding range of therapeutic and diagnostic applications is being pursued by research and commercial organizations. This paper aims to provide a comprehensive review of recent developments in wireless sensor technology for monitoring behaviour related to human physiological responses. It presents background information on the use of wireless technology and sensors to develop a wireless physiological measurement system. A generic miniature platform and other available technologies for wireless sensors have been studied in terms of hardware and software structural requirements for a low-cost, low-power, non-invasive and unobtrusive system.

Smart sensors enable smart air conditioning control.

PubMed

Cheng, Chin-Chi; Lee, Dasheng

2014-06-24

In this study, mobile phones, wearable devices, temperature and human motion detectors are integrated as smart sensors for enabling smart air conditioning control. Smart sensors obtain feedback, especially occupants' information, from mobile phones and wearable devices placed on human body. The information can be used to adjust air conditioners in advance according to humans' intentions, in so-called intention causing control. Experimental results show that the indoor temperature can be controlled accurately with errors of less than ±0.1 °C. Rapid cool down can be achieved within 2 min to the optimized indoor capacity after occupants enter a room. It's also noted that within two-hour operation the total compressor output of the smart air conditioner is 48.4% less than that of the one using On-Off control. The smart air conditioner with wearable devices could detect the human temperature and activity during sleep to determine the sleeping state and adjusting the sleeping function flexibly. The sleeping function optimized by the smart air conditioner with wearable devices could reduce the energy consumption up to 46.9% and keep the human health. The presented smart air conditioner could provide a comfortable environment and achieve the goals of energy conservation and environmental protection.

Engineering the Charge Transport of Ag Nanocrystals for Highly Accurate, Wearable Temperature Sensors through All-Solution Processes.

PubMed

Joh, Hyungmok; Lee, Seung-Wook; Seong, Mingi; Lee, Woo Seok; Oh, Soong Ju

2017-06-01

All-nanocrystal (NC)-based and all-solution-processed wearable resistance temperature detectors (RTDs) are introduced. The charge transport mechanisms of Ag NC thin films are engineered through various ligand treatments to design high performance RTDs. Highly conductive Ag NC thin films exhibiting metallic transport behavior with high positive temperature coefficients of resistance (TCRs) are achieved through tetrabutylammonium bromide treatment. Ag NC thin films showing hopping transport with high negative TCRs are created through organic ligand treatment. All-solution-based, one-step photolithography techniques that integrate two distinct opposite-sign TCR Ag NC thin films into an ultrathin single device are developed to decouple the mechanical effects such as human motion. The unconventional materials design and strategy enables highly accurate, sensitive, wearable and motion-free RTDs, demonstrated by experiments on moving or curved objects such as human skin, and simulation results based on charge transport analysis. This strategy provides a low cost and simple method to design wearable multifunctional sensors with high sensitivity which could be utilized in various fields such as biointegrated sensors or electronic skin. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Smart Sensors Enable Smart Air Conditioning Control

PubMed Central

Cheng, Chin-Chi; Lee, Dasheng

2014-01-01

In this study, mobile phones, wearable devices, temperature and human motion detectors are integrated as smart sensors for enabling smart air conditioning control. Smart sensors obtain feedback, especially occupants' information, from mobile phones and wearable devices placed on human body. The information can be used to adjust air conditioners in advance according to humans' intentions, in so-called intention causing control. Experimental results show that the indoor temperature can be controlled accurately with errors of less than ±0.1 °C. Rapid cool down can be achieved within 2 min to the optimized indoor capacity after occupants enter a room. It's also noted that within two-hour operation the total compressor output of the smart air conditioner is 48.4% less than that of the one using On-Off control. The smart air conditioner with wearable devices could detect the human temperature and activity during sleep to determine the sleeping state and adjusting the sleeping function flexibly. The sleeping function optimized by the smart air conditioner with wearable devices could reduce the energy consumption up to 46.9% and keep the human health. The presented smart air conditioner could provide a comfortable environment and achieve the goals of energy conservation and environmental protection. PMID:24961213

Toward real time detection of the basic living activity in home using a wearable sensor and smart home sensors.

PubMed

Bang, Sunlee; Kim, Minho; Song, Sa-Kwang; Park, Soo-Jun

2008-01-01

As the elderly people living alone are enormously increasing recently, we need the system inferring activities of daily living (ADL) for maintaining healthy life and recognizing emergency. The system should be constructed with sensors, which are used to associate with people's living while remaining as non intrusive views as possible. To do this, the proposed system use a triaxial accelerometer sensor and environment sensors indicating contact with subject in home. Particularly, in order to robustly infer ADLs, we present component ADL, which is decided with conjunction of human motion together, not just only contacted object identification. It is an important component in inferring ADL. In special, component ADL decision firstly refines misclassified initial activities, which improves the accuracy of recognizing ADL. Preliminary experiments results for proposed system provides overall recognition rate of over 97% over 8 component ADLs, which can be effectively applicable to recognize the final ADLs.

A wearable biochemical sensor for monitoring alcohol consumption lifestyle through Ethyl glucuronide (EtG) detection in human sweat.

PubMed

Selvam, Anjan Panneer; Muthukumar, Sriram; Kamakoti, Vikramshankar; Prasad, Shalini

2016-03-21

We demonstrate for the first time a wearable biochemical sensor for monitoring alcohol consumption through the detection and quantification of a metabolite of ethanol, ethyl glucuronide (EtG). We designed and fabricated two co-planar sensors with gold and zinc oxide as sensing electrodes. We also designed a LED based reporting for the presence of EtG in the human sweat samples. The sensor functions on affinity based immunoassay principles whereby monoclonal antibodies for EtG were immobilized on the electrodes using thiol based chemistry. Detection of EtG from human sweat was achieved through chemiresistive sensing mechanism. In this method, an AC voltage was applied across the two coplanar electrodes and the impedance across the sensor electrodes was measured and calibrated for physiologically relevant doses of EtG in human sweat. EtG detection over a dose concentration of 0.001-100 μg/L was demonstrated on both glass and polyimide substrates. Detection sensitivity was lower at 1 μg/L with gold electrodes as compared to ZnO, which had detection sensitivity of 0.001 μg/L. Based on the detection range the wearable sensor has the ability to detect alcohol consumption of up to 11 standard drinks in the US over a period of 4 to 9 hours.

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).

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.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

PubMed

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-02-19

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation

PubMed Central

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-01-01

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver’s EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver’s vigilance level . Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model. PMID:26907278

Flexible tension sensor based on poly(l-lactic acid) film with coaxial structure

NASA Astrophysics Data System (ADS)

Yoshida, Mitsunobu; Onishi, Katsuki; Tanimoto, Kazuhiro; Nishikawa, Shigeo

2017-10-01

We have developed a tension sensor with a coaxial structure using a narrow slit ribbon made of a uniaxially stretched poly(l-lactic acid) (PLLA) film for application to a wearable device. The tension sensor is produced as follows. We used tinsel wire as the center conductor of the sensor. The tinsel wire consists of a yarn of synthetic fibers arranged at the center, with a spirally wound rolled copper foil ribbon on the side surface. Next, slit ribbons obtained from a uniaxially oriented film of PLLA are wound helically on the side surface of the center conductor in the direction of a left-handed screw, at an angle of 45° to the central axis. The rolled copper foil is used as an outer conductor and covers the yarn without a gap. The prototype of the fabricated tension sensor has good flexibility, since the sensor is in the form of a filament and consists of a highly flexible material. For the 1 mm tension sensor, it was found that for a tension of 1 N, a charge of 14 pC was output. It was also found that the sensor maintained its room-temperature sensitivity up to 60 °C. Compared with an existing coaxial line sensor using poly(vinylidene fluoride) (PVDF), the sensor using PLLA does not exhibit pyroelectricity, meaning that no undesirable voltage is generated when in contact with body heat, which is a significant advantage as wearable sensors. The result has demonstrated the potential application of the PLLA film to wearable devices for detecting heartbeat and respiration.

Development and characterization of a multilayer matrix textile sensor for interface pressure measurements

NASA Astrophysics Data System (ADS)

Baldoli, Ilaria; Maselli, Martina; Cecchi, Francesca; Laschi, Cecilia

2017-10-01

Matrix textile sensors hold great potential for measuring pressure distribution in applications of modern daily lives, mainly regarding the biomedical field, but also robotics, automotive systems, and wearable and consumer electronics. However, an experimental analysis of their metrological properties is lacking in the literature, thus compromising their widespread acceptance. In the present work, we report the characterization of an 8 × 8 textile sensor assembled by sandwiching a piezoresistive fabric sheet between two outer fabric layers embedding conductive rows and columns. The location of the applied pressure can be identified by detecting the position where the change of resistances occurs between the external conductive paths. The sensor structure, its electrical circuit and characteristics are described in detail, after studying both the integration levels of the hierarchical structure and the composition of the piezoresistive fabric sheet. The pressure measurement range and the calibration curve were studied by tuning circuital parameters. Repeatability, time drift, temperature dependence, signal-to-noise ratio and dynamic response were analyzed. Novel tests were employed to consider the sensor sensitivity to stretch, shear force and surface curvature. A special analysis was taken over hysteresis and dynamic accuracy, focusing on a possible compensating solution. Results indicated that the system provides overall good quality performances with the main drawback of a limited dynamic accuracy, typical of piezoresistive sensing elements. Nevertheless, the use of textiles allows the realization of lightweight, wearable, washable, thin and stretchable sensors. In addition fabric sensors are robust, cheap, easy-to-use and employable to cover large area three dimensional surfaces. The wide characterization reported here could provide precious insights and guidelines to help researchers and users in taking advantages from all of these benefits, supporting them in choosing the best sensor design and application.

A data-driven approach to modeling physical fatigue in the workplace using wearable sensors.

PubMed

Sedighi Maman, Zahra; Alamdar Yazdi, Mohammad Ali; Cavuoto, Lora A; Megahed, Fadel M

2017-11-01

Wearable sensors are currently being used to manage fatigue in professional athletics, transportation and mining industries. In manufacturing, physical fatigue is a challenging ergonomic/safety "issue" since it lowers productivity and increases the incidence of accidents. Therefore, physical fatigue must be managed. There are two main goals for this study. First, we examine the use of wearable sensors to detect physical fatigue occurrence in simulated manufacturing tasks. The second goal is to estimate the physical fatigue level over time. In order to achieve these goals, sensory data were recorded for eight healthy participants. Penalized logistic and multiple linear regression models were used for physical fatigue detection and level estimation, respectively. Important features from the five sensors locations were selected using Least Absolute Shrinkage and Selection Operator (LASSO), a popular variable selection methodology. The results show that the LASSO model performed well for both physical fatigue detection and modeling. The modeling approach is not participant and/or workload regime specific and thus can be adopted for other applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Activity Monitoring and Heart Rate Variability as Indicators of Fall Risk: Proof-of-Concept for Application of Wearable Sensors in the Acute Care Setting.

PubMed

Razjouyan, Javad; Grewal, Gurtej Singh; Rishel, Cindy; Parthasarathy, Sairam; Mohler, Jane; Najafi, Bijan

2017-07-01

Growing concern for falls in acute care settings could be addressed with objective evaluation of fall risk. The current proof-of-concept study evaluated the feasibility of using a chest-worn sensor during hospitalization to determine fall risk. Physical activity and heart rate variability (HRV) of 31 volunteers admitted to a 29-bed adult inpatient unit were recorded using a single chest-worn sensor. Sensor data during the first 24-hour recording were analyzed. Participants were stratified using the Hendrich II fall risk assessment into high and low fall risk groups. Univariate analysis revealed age, daytime activity, nighttime side lying posture, and HRV were significantly different between groups. Results suggest feasibility of wearable technology to consciously monitor physical activity, sleep postures, and HRV as potential markers of fall risk in the acute care setting. Further study is warranted to confirm the results and examine the efficacy of the proposed wearable technology to manage falls in hospitals. [Journal of Gerontological Nursing, 43(7), 53-62.]. Copyright 2017, SLACK Incorporated.

Wearable sensor-based objective assessment of motor symptoms in Parkinson's disease.

PubMed

Ossig, Christiana; Antonini, Angelo; Buhmann, Carsten; Classen, Joseph; Csoti, Ilona; Falkenburger, Björn; Schwarz, Michael; Winkler, Jürgen; Storch, Alexander

2016-01-01

Effective management and development of new treatment strategies of motor symptoms in Parkinson's disease (PD) largely depend on clinical rating instruments like the Unified PD rating scale (UPDRS) and the modified abnormal involuntary movement scale (mAIMS). Regarding inter-rater variability and continuous monitoring, clinical rating scales have various limitations. Patient-administered questionnaires such as the PD home diary to assess motor stages and fluctuations in late-stage PD are frequently used in clinical routine and as clinical trial endpoints, but diary/questionnaire are tiring, and recall bias impacts on data quality, particularly in patients with cognitive dysfunction or depression. Consequently, there is a strong need for continuous and objective monitoring of motor symptoms in PD for improving therapeutic regimen and for usage in clinical trials. Recent advances in battery technology, movement sensors such as gyroscopes, accelerometers and information technology boosted the field of objective measurement of movement in everyday life and medicine using wearable sensors allowing continuous (long-term) monitoring. This systematic review summarizes the current wearable sensor-based devices to objectively assess the various motor symptoms of PD.

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.

Channel Model on Various Frequency Bands for Wearable Body Area Network

NASA Astrophysics Data System (ADS)

Katayama, Norihiko; Takizawa, Kenichi; Aoyagi, Takahiro; Takada, Jun-Ichi; Li, Huan-Bang; Kohno, Ryuji

Body Area Network (BAN) is considered as a promising technology in supporting medical and healthcare services by combining with various biological sensors. In this paper, we look at wearable BAN, which provides communication links among sensors on body surface. In order to design a BAN that manages biological information with high efficiency and high reliability, the propagation characteristics of BAN must be thoroughly investigated. As a preliminary effort, we measured the propagation characteristics of BAN at frequency bands of 400MHz, 600MHz, 900MHz and 2400MHz respectively. Channel models for wearable BAN based on the measurement were derived. Our results show that the channel model can be described by using a path loss model for all frequency bands investigated.

Digital Suicide Prevention: Can Technology Become a Game-changer?

PubMed

Vahabzadeh, Arshya; Sahin, Ned; Kalali, Amir

2016-01-01

Suicide continues to be a leading cause of death and has been recognized as a significant public health issue. Rapid advances in data science can provide us with useful tools for suicide prevention, and help to dynamically assess suicide risk in quantitative data-driven ways. In this article, the authors highlight the most current international research in digital suicide prevention, including the use of machine learning, smartphone applications, and wearable sensor driven systems. The authors also discuss future opportunities for digital suicide prevention, and propose a novel Sensor-driven Mental State Assessment System.

Defining Requirements and Related Methods for Designing Sensorized Garments.

PubMed

Andreoni, Giuseppe; Standoli, Carlo Emilio; Perego, Paolo

2016-05-26

Designing smart garments has strong interdisciplinary implications, specifically related to user and technical requirements, but also because of the very different applications they have: medicine, sport and fitness, lifestyle monitoring, workplace and job conditions analysis, etc. This paper aims to discuss some user, textile, and technical issues to be faced in sensorized clothes development. In relation to the user, the main requirements are anthropometric, gender-related, and aesthetical. In terms of these requirements, the user's age, the target application, and fashion trends cannot be ignored, because they determine the compliance with the wearable system. Regarding textile requirements, functional factors-also influencing user comfort-are elasticity and washability, while more technical properties are the stability of the chemical agents' effects for preserving the sensors' efficacy and reliability, and assuring the proper duration of the product for the complete life cycle. From the technical side, the physiological issues are the most important: skin conductance, tolerance, irritation, and the effect of sweat and perspiration are key factors for reliable sensing. Other technical features such as battery size and duration, and the form factor of the sensor collector, should be considered, as they affect aesthetical requirements, which have proven to be crucial, as well as comfort and wearability.

Stretchable Biofuel Cells as Wearable Textile-based Self-Powered Sensors.

PubMed

Jeerapan, Itthipon; Sempionatto, Juliane R; Pavinatto, Adriana; You, Jung-Min; Wang, Joseph

2016-12-21

Highly stretchable textile-based biofuel cells (BFCs), acting as effective self-powered sensors, have been fabricated using screen-printing of customized stress-enduring inks. Due to synergistic effects of nanomaterial-based engineered inks and the serpentine designs, these printable bioelectronic devices endure severe mechanical deformations, e.g., stretching, indentation, or torsional twisting. Glucose and lactate BFCs with the single enzyme and membrane-free configurations generated the maximum power density of 160 and 250 µW cm -2 with the open circuit voltages of 0.44 and 0.46 V, respectively. The textile-BFCs were able to withstand repeated severe mechanical deformations with minimal impact on its structural integrity, as was indicated from their stable power output after 100 cycles of 100% stretching. By providing power signals proportional to the sweat fuel concentration, these stretchable devices act as highly selective and stable self-powered textile sensors. Applicability to sock-based BFC and self-powered biosensor and mechanically compliant operations was demonstrated on human subjects. These stretchable skin-worn "scavenge-sense-display" devices are expected to contribute to the development of skin-worn energy harvesting systems, advanced non-invasive self-powered sensors and wearable electronics on a stretchable garment.

The Language of Glove: Wireless gesture decoder with low-power and stretchable hybrid electronics.

PubMed

O'Connor, Timothy F; Fach, Matthew E; Miller, Rachel; Root, Samuel E; Mercier, Patrick P; Lipomi, Darren J

2017-01-01

This communication describes a glove capable of wirelessly translating the American Sign Language (ASL) alphabet into text displayable on a computer or smartphone. The key components of the device are strain sensors comprising a piezoresistive composite of carbon particles embedded in a fluoroelastomer. These sensors are integrated with a wearable electronic module consisting of digitizers, a microcontroller, and a Bluetooth radio. Finite-element analysis predicts a peak strain on the sensors of 5% when the knuckles are fully bent. Fatigue studies suggest that the sensors successfully detect the articulation of the knuckles even when bent to their maximal degree 1,000 times. In concert with an accelerometer and pressure sensors, the glove is able to translate all 26 letters of the ASL alphabet. Lastly, data taken from the glove are used to control a virtual hand; this application suggests new ways in which stretchable and wearable electronics can enable humans to interface with virtual environments. Critically, this system was constructed of components costing less than $100 and did not require chemical synthesis or access to a cleanroom. It can thus be used as a test bed for materials scientists to evaluate the performance of new materials and flexible and stretchable hybrid electronics.

The Language of Glove: Wireless gesture decoder with low-power and stretchable hybrid electronics

PubMed Central

O’Connor, Timothy F.; Fach, Matthew E.; Miller, Rachel; Root, Samuel E.; Mercier, Patrick P.

2017-01-01

This communication describes a glove capable of wirelessly translating the American Sign Language (ASL) alphabet into text displayable on a computer or smartphone. The key components of the device are strain sensors comprising a piezoresistive composite of carbon particles embedded in a fluoroelastomer. These sensors are integrated with a wearable electronic module consisting of digitizers, a microcontroller, and a Bluetooth radio. Finite-element analysis predicts a peak strain on the sensors of 5% when the knuckles are fully bent. Fatigue studies suggest that the sensors successfully detect the articulation of the knuckles even when bent to their maximal degree 1,000 times. In concert with an accelerometer and pressure sensors, the glove is able to translate all 26 letters of the ASL alphabet. Lastly, data taken from the glove are used to control a virtual hand; this application suggests new ways in which stretchable and wearable electronics can enable humans to interface with virtual environments. Critically, this system was constructed of components costing less than $100 and did not require chemical synthesis or access to a cleanroom. It can thus be used as a test bed for materials scientists to evaluate the performance of new materials and flexible and stretchable hybrid electronics. PMID:28700603

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.

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.

Intelligent Medical Garments with Graphene-Functionalized Smart-Cloth ECG Sensors.

PubMed

Yapici, Murat Kaya; Alkhidir, Tamador Elboshra

2017-04-16

Biopotential signals are recorded mostly by using sticky, pre-gelled electrodes, which are not ideal for wearable, point-of-care monitoring where the usability of the personalized medical device depends critically on the level of comfort and wearability of the electrodes. We report a fully-wearable medical garment for mobile monitoring of cardiac biopotentials from the wrists or the neck with minimum restriction to regular clothing habits. The wearable prototype is based on elastic bands with graphene functionalized, textile electrodes and battery-powered, low-cost electronics for signal acquisition and wireless transmission. Comparison of the electrocardiogram (ECG) recordings obtained from the wearable prototype against conventional wet electrodes indicate excellent conformity and spectral coherence among the two signals.

Synchronous wearable wireless body sensor network composed of autonomous textile nodes.

PubMed

Vanveerdeghem, Peter; Van Torre, Patrick; Stevens, Christiaan; Knockaert, Jos; Rogier, Hendrik

2014-10-09

A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted to a base station, directly, as well as forwarded by other on-body nodes. For each node, a dual-polarized textile patch antenna serves as a platform for the flexible electronic circuitry. Therefore, the system is particularly suitable for comfortable and unobtrusive integration into garments. In the meantime, polarization diversity can be exploited to improve the reliability and energy-efficiency of the wireless transmission. Extensive experiments in realistic conditions have demonstrated that this new autonomous, body-centric, textile-antenna, wireless sensor network is able to correctly detect different operating conditions of a firefighter during an intervention. By relying on four network nodes integrated into the protective garment, this functionality is implemented locally, on the body, and in real time. In addition, the received sensor data are reliably transferred to a central access point at the command post, for more detailed and more comprehensive real-time visualization. This information provides coordinators and commanders with situational awareness of the entire rescue operation. A statistical analysis of measured on-body node-to-node, as well as off-body person-to-person channels is included, confirming the reliability of the communication system.

Synchronous Wearable Wireless Body Sensor Network Composed of Autonomous Textile Nodes

PubMed Central

Vanveerdeghem, Peter; Van Torre, Patrick; Stevens, Christiaan; Knockaert, Jos; Rogier, Hendrik

2014-01-01

A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted to a base station, directly, as well as forwarded by other on-body nodes. For each node, a dual-polarized textile patch antenna serves as a platform for the flexible electronic circuitry. Therefore, the system is particularly suitable for comfortable and unobtrusive integration into garments. In the meantime, polarization diversity can be exploited to improve the reliability and energy-efficiency of the wireless transmission. Extensive experiments in realistic conditions have demonstrated that this new autonomous, body-centric, textile-antenna, wireless sensor network is able to correctly detect different operating conditions of a firefighter during an intervention. By relying on four network nodes integrated into the protective garment, this functionality is implemented locally, on the body, and in real time. In addition, the received sensor data are reliably transferred to a central access point at the command post, for more detailed and more comprehensive real-time visualization. This information provides coordinators and commanders with situational awareness of the entire rescue operation. A statistical analysis of measured on-body node-to-node, as well as off-body person-to-person channels is included, confirming the reliability of the communication system. PMID:25302808

Hand-arm vibration exposure monitoring with wearable sensor module.

PubMed

Austad, Hanne O; Røed, Morten H; Liverud, Anders E; Dalgard, Steffen; Seeberg, Trine M

2013-01-01

Vibration exposure is a serious risk within work physiology for several work groups. Combined with cold artic climate, the risk for permanent harm is even higher. Equipment that can monitor the vibration exposure and warn the user when at risk will provide a safer work environment for these work groups. This study evaluates whether data from a wearable wireless multi-parameter sensor module can be used to estimate vibration exposure and exposure time. This work has been focused on the characterization of the response from the accelerometer in the sensor module and the optimal location of the module in the hand-arm configuration.

Real-time monitoring of ubiquitous wireless ECG sensor node for medical care using ZigBee

NASA Astrophysics Data System (ADS)

Vijayalakshmi, S. R.; Muruganand, S.

2012-01-01

Sensor networks have the potential to impact many aspects of medical care greatly. By outfitting patients with wireless, wearable vital sign sensors, collecting detailed real-time data on physiological status can be greatly simplified. In this article, we propose the system architecture for smart sensor platform based on advanced wireless sensor networks. An emerging application for wireless sensor networks involves their use in medical care. In hospitals or clinics, outfitting every patient with tiny, wearable wireless vital sign sensors would allow doctors, nurses and other caregivers to continuously monitor the status of their patients. In an emergency or disaster scenario, the same technology would enable medics to more effectively care for a large number of casualties. First responders could receive immediate notifications on any changes in patient status, such as respiratory failure or cardiac arrest. Wireless sensor network is a set of small, autonomous devices, working together to solve different problems. It is a relatively new technology, experiencing true expansion in the past decade. People have realised that integration of small and cheap microcontrollers with sensors can result in the production of extremely useful devices, which can be used as an integral part of the sensor nets. These devices are called sensor nodes. Today, sensor nets are used in agriculture, ecology and tourism, but medicine is the area where they certainly meet the greatest potential. This article presents a medical smart sensor node platform. This article proposes a wireless two-lead EKG. These devices collect heart rate and EKG data and relay it over a short-range (300 m) wireless network to any number of receiving devices, including PDAs, laptops or ambulance-based terminals.

Enzymatic Fuel Cells: Towards Self-Powered Implantable and Wearable Diagnostics.

PubMed

Gonzalez-Solino, Carla; Lorenzo, Mirella Di

2018-01-29

With the rapid progress in nanotechnology and microengineering, point-of-care and personalised healthcare, based on wearable and implantable diagnostics, is becoming a reality. Enzymatic fuel cells (EFCs) hold great potential as a sustainable means to power such devices by using physiological fluids as the fuel. This review summarises the fundamental operation of EFCs and discusses the most recent advances for their use as implantable and wearable self-powered sensors.

Enzymatic Fuel Cells: Towards Self-Powered Implantable and Wearable Diagnostics

PubMed Central

Gonzalez-Solino, Carla; Lorenzo, Mirella Di

2018-01-01

With the rapid progress in nanotechnology and microengineering, point-of-care and personalised healthcare, based on wearable and implantable diagnostics, is becoming a reality. Enzymatic fuel cells (EFCs) hold great potential as a sustainable means to power such devices by using physiological fluids as the fuel. This review summarises the fundamental operation of EFCs and discusses the most recent advances for their use as implantable and wearable self-powered sensors. PMID:29382147

The promise of wearable sensors and ecological momentary assessment measures for dynamical systems modeling in adolescents: a feasibility and acceptability study.

PubMed

Brannon, Erin E; Cushing, Christopher C; Crick, Christopher J; Mitchell, Tarrah B

2016-12-01

Intervention development can be accelerated by using wearable sensors and ecological momentary assessment (EMA) to study how behaviors change within a person. The purpose of this study was to determine the feasibility and acceptability of a novel, intensive EMA method for assessing physiology, behavior, and psychosocial variables utilizing two objective sensors and a mobile application (app). Adolescents (n = 20) enrolled in a 20-day EMA protocol. Participants wore a physiological monitor and an accelerometer that measured sleep and physical activity and completed four surveys per day on an app. Participants provided approximately 81 % of the expected survey data. Participants were compliant to the wrist-worn accelerometer (75.3 %), which is a feasible measurement of physical activity/sleep (74.1 % complete data). The data capture (47.8 %) and compliance (70.28 %) with the physiological monitor were lower than other study variables. The findings support the use of an intensive assessment protocol to study real-time relationships between biopsychosocial variables and health behaviors.

Wearable, wireless gas sensors using highly stretchable and transparent structures of nanowires and graphene.

PubMed

Park, Jihun; Kim, Joohee; Kim, Kukjoo; Kim, So-Yun; Cheong, Woon Hyung; Park, Kyeongmin; Song, Joo Hyeb; Namgoong, GyeongHo; Kim, Jae Joon; Heo, Jaeyeong; Bien, Franklin; Park, Jang-Ung

2016-05-19

Herein, we report the fabrication of a highly stretchable, transparent gas sensor based on silver nanowire-graphene hybrid nanostructures. Due to its superb mechanical and optical characteristics, the fabricated sensor demonstrates outstanding and stable performances even under extreme mechanical deformation (stable until 20% of strain). The integration of a Bluetooth system or an inductive antenna enables the wireless operation of the sensor. In addition, the mechanical robustness of the materials allows the device to be transferred onto various nonplanar substrates, including a watch, a bicycle light, and the leaves of live plants, thereby achieving next-generation sensing electronics for the 'Internet of Things' area.

Damage Detection Sensor System for Aerospace and Multiple Applications

NASA Technical Reports Server (NTRS)

Williams, M.; Lewis, M.; Gibson, T.; Medelius, P.; Lane, J.

2017-01-01

The damage detection sensory system is an intelligent damage detection ‘skin’ that can be embedded into rigid or flexible structures, providing a lightweight capability for in-situ health monitoring for applications such as spacecraft, expandable or inflatable structures, extravehicular activities (EVA) suits, smart wearables, and other applications where diagnostic impact damage monitoring might be critical. The sensor systems can be customized for detecting location, damage size, and depth, with velocity options and can be designed for particular environments for monitoring of impact or physical damage to a structure. The operation of the sensor detection system is currently based on the use of parallel conductive traces placed on a firm or flexible surface. Several detection layers can be implemented, where alternate layers are arranged in orthogonal direction with respect to the adjacent layers allowing for location and depth calculations. Increased flexibility of the damage detection sensor system designs will also be introduced.

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.

Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures.

PubMed

Kubota, Ken J; Chen, Jason A; Little, Max A

2016-09-01

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, "wearable," sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that "learn" from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Testing and evaluation of a wearable augmented reality system for natural outdoor environments

NASA Astrophysics Data System (ADS)

Roberts, David; Menozzi, Alberico; Cook, James; Sherrill, Todd; Snarski, Stephen; Russler, Pat; Clipp, Brian; Karl, Robert; Wenger, Eric; Bennett, Matthew; Mauger, Jennifer; Church, William; Towles, Herman; MacCabe, Stephen; Webb, Jeffrey; Lupo, Jasper; Frahm, Jan-Michael; Dunn, Enrique; Leslie, Christopher; Welch, Greg

2013-05-01

This paper describes performance evaluation of a wearable augmented reality system for natural outdoor environments. Applied Research Associates (ARA), as prime integrator on the DARPA ULTRA-Vis (Urban Leader Tactical, Response, Awareness, and Visualization) program, is developing a soldier-worn system to provide intuitive `heads-up' visualization of tactically-relevant geo-registered icons. Our system combines a novel pose estimation capability, a helmet-mounted see-through display, and a wearable processing unit to accurately overlay geo-registered iconography (e.g., navigation waypoints, sensor points of interest, blue forces, aircraft) on the soldier's view of reality. We achieve accurate pose estimation through fusion of inertial, magnetic, GPS, terrain data, and computer-vision inputs. We leverage a helmet-mounted camera and custom computer vision algorithms to provide terrain-based measurements of absolute orientation (i.e., orientation of the helmet with respect to the earth). These orientation measurements, which leverage mountainous terrain horizon geometry and mission planning landmarks, enable our system to operate robustly in the presence of external and body-worn magnetic disturbances. Current field testing activities across a variety of mountainous environments indicate that we can achieve high icon geo-registration accuracy (<10mrad) using these vision-based methods.

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

Fabrication of Ultra-Thin Printed Organic TFT CMOS Logic Circuits Optimized for Low-Voltage Wearable Sensor Applications.

PubMed

Takeda, Yasunori; Hayasaka, Kazuma; Shiwaku, Rei; Yokosawa, Koji; Shiba, Takeo; Mamada, Masashi; Kumaki, Daisuke; Fukuda, Kenjiro; Tokito, Shizuo

2016-05-09

Ultrathin electronic circuits that can be manufactured by using conventional printing technologies are key elements necessary to realize wearable health sensors and next-generation flexible electronic devices. Due to their low level of power consumption, complementary (CMOS) circuits using both types of semiconductors can be easily employed in wireless devices. Here, we describe ultrathin CMOS logic circuits, for which not only the source/drain electrodes but also the semiconductor layers were printed. Both p-type and n-type organic thin film transistor devices were employed in a D-flip flop circuit in the newly developed stacked structure and exhibited excellent electrical characteristics, including good carrier mobilities of 0.34 and 0.21 cm(2) V(-1) sec(-1), and threshold voltages of nearly 0 V with low operating voltages. These printed organic CMOS D-flip flop circuits exhibit operating frequencies of 75 Hz and demonstrate great potential for flexible and printed electronics technology, particularly for wearable sensor applications with wireless connectivity.

Fabrication of Ultra-Thin Printed Organic TFT CMOS Logic Circuits Optimized for Low-Voltage Wearable Sensor Applications

PubMed Central

Takeda, Yasunori; Hayasaka, Kazuma; Shiwaku, Rei; Yokosawa, Koji; Shiba, Takeo; Mamada, Masashi; Kumaki, Daisuke; Fukuda, Kenjiro; Tokito, Shizuo

2016-01-01

Ultrathin electronic circuits that can be manufactured by using conventional printing technologies are key elements necessary to realize wearable health sensors and next-generation flexible electronic devices. Due to their low level of power consumption, complementary (CMOS) circuits using both types of semiconductors can be easily employed in wireless devices. Here, we describe ultrathin CMOS logic circuits, for which not only the source/drain electrodes but also the semiconductor layers were printed. Both p-type and n-type organic thin film transistor devices were employed in a D-flip flop circuit in the newly developed stacked structure and exhibited excellent electrical characteristics, including good carrier mobilities of 0.34 and 0.21 cm2 V−1 sec−1, and threshold voltages of nearly 0 V with low operating voltages. These printed organic CMOS D-flip flop circuits exhibit operating frequencies of 75 Hz and demonstrate great potential for flexible and printed electronics technology, particularly for wearable sensor applications with wireless connectivity. PMID:27157914

Studies on a wearable, electronic, transdermal alcohol sensor.

PubMed

Swift, R M; Martin, C S; Swette, L; LaConti, A; Kackley, N

1992-08-01

The measurement of alcohol consumption over long time periods is important for monitoring treatment outcome and for research applications. Giner, Inc. has developed a wearable device that senses ethanol vapor at the surface of the skin, using an electrochemical cell that produces a continuous current signal proportional to ethanol concentration. A thermistor monitors continuous contact of the sensor with the skin, and a data-acquisition/logic circuit stores days of data recorded at 2- to 5-min intervals. Testing of this novel ethanol sensor/recorder was conducted on nonalcoholic human subjects consuming known quantities of ethanol and on intoxicated alcoholic subjects. The transdermal sensor signal closely follows the pattern of the blood alcohol concentration curve, although with a delay. This paper describes the concept of electrochemical ethanol measurement and presents some of the clinical data collected in support of the sensor/recorder development.

Potentiometric sensors using cotton yarns, carbon nanotubes and polymeric membranes.

PubMed

Guinovart, Tomàs; Parrilla, Marc; Crespo, Gastón A; Rius, F Xavier; Andrade, Francisco J

2013-09-21

A simple and generalized approach to build electrochemical sensors for wearable devices is presented. Commercial cotton yarns are first turned into electrical conductors through a simple dyeing process using a carbon nanotube ink. These conductive yarns are then partially coated with a suitable polymeric membrane to build ion-selective electrodes. Potentiometric measurements using these yarn-potentiometric sensors are demonstrated. Examples of yarns that can sense pH, K(+) and NH4(+) are presented. In all cases, these sensing yarns show limits of detection and linear ranges that are similar to those obtained with lab-made solid-state ion-selective electrodes. Through the immobilization of these sensors in a band-aid, it is shown that this approach could be easily implemented in a wearable device. Factors affecting the performance of the sensors and future potential applications are discussed.

Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study.

PubMed

Sano, Akane; Taylor, Sara; McHill, Andrew W; Phillips, Andrew Jk; Barger, Laura K; Klerman, Elizabeth; Picard, Rosalind

2018-06-08

Wearable and mobile devices that capture multimodal data have the potential to identify risk factors for high stress and poor mental health and to provide information to improve health and well-being. We developed new tools that provide objective physiological and behavioral measures using wearable sensors and mobile phones, together with methods that improve their data integrity. The aim of this study was to examine, using machine learning, how accurately these measures could identify conditions of self-reported high stress and poor mental health and which of the underlying modalities and measures were most accurate in identifying those conditions. We designed and conducted the 1-month SNAPSHOT study that investigated how daily behaviors and social networks influence self-reported stress, mood, and other health or well-being-related factors. We collected over 145,000 hours of data from 201 college students (age: 18-25 years, male:female=1.8:1) at one university, all recruited within self-identified social groups. Each student filled out standardized pre- and postquestionnaires on stress and mental health; during the month, each student completed twice-daily electronic diaries (e-diaries), wore two wrist-based sensors that recorded continuous physical activity and autonomic physiology, and installed an app on their mobile phone that recorded phone usage and geolocation patterns. We developed tools to make data collection more efficient, including data-check systems for sensor and mobile phone data and an e-diary administrative module for study investigators to locate possible errors in the e-diaries and communicate with participants to correct their entries promptly, which reduced the time taken to clean e-diary data by 69%. We constructed features and applied machine learning to the multimodal data to identify factors associated with self-reported poststudy stress and mental health, including behaviors that can be possibly modified by the individual to improve these measures. We identified the physiological sensor, phone, mobility, and modifiable behavior features that were best predictors for stress and mental health classification. In general, wearable sensor features showed better classification performance than mobile phone or modifiable behavior features. Wearable sensor features, including skin conductance and temperature, reached 78.3% (148/189) accuracy for classifying students into high or low stress groups and 87% (41/47) accuracy for classifying high or low mental health groups. Modifiable behavior features, including number of naps, studying duration, calls, mobility patterns, and phone-screen-on time, reached 73.5% (139/189) accuracy for stress classification and 79% (37/47) accuracy for mental health classification. New semiautomated tools improved the efficiency of long-term ambulatory data collection from wearable and mobile devices. Applying machine learning to the resulting data revealed a set of both objective features and modifiable behavioral features that could classify self-reported high or low stress and mental health groups in a college student population better than previous studies and showed new insights into digital phenotyping. ©Akane Sano, Sara Taylor, Andrew W McHill, Andrew JK Phillips, Laura K Barger, Elizabeth Klerman, Rosalind Picard. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.06.2018.

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.

An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice

PubMed Central

Özdemir, Ahmet Turan

2016-01-01

Wearable devices for fall detection have received attention in academia and industry, because falls are very dangerous, especially for elderly people, and if immediate aid is not provided, it may result in death. However, some predictive devices are not easily worn by elderly people. In this work, a huge dataset, including 2520 tests, is employed to determine the best sensor placement location on the body and to reduce the number of sensor nodes for device ergonomics. During the tests, the volunteer’s movements are recorded with six groups of sensors each with a triaxial (accelerometer, gyroscope and magnetometer) sensor, which is placed tightly on different parts of the body with special straps: head, chest, waist, right-wrist, right-thigh and right-ankle. The accuracy of individual sensor groups with their location is investigated with six machine learning techniques, namely the k-nearest neighbor (k-NN) classifier, Bayesian decision making (BDM), support vector machines (SVM), least squares method (LSM), dynamic time warping (DTW) and artificial neural networks (ANNs). Each technique is applied to single, double, triple, quadruple, quintuple and sextuple sensor configurations. These configurations create 63 different combinations, and for six machine learning techniques, a total of 63 × 6 = 378 combinations is investigated. As a result, the waist region is found to be the most suitable location for sensor placement on the body with 99.96% fall detection sensitivity by using the k-NN classifier, whereas the best sensitivity achieved by the wrist sensor is 97.37%, despite this location being highly preferred for today’s wearable applications. PMID:27463719

An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice.

PubMed

Özdemir, Ahmet Turan

2016-07-25

Wearable devices for fall detection have received attention in academia and industry, because falls are very dangerous, especially for elderly people, and if immediate aid is not provided, it may result in death. However, some predictive devices are not easily worn by elderly people. In this work, a huge dataset, including 2520 tests, is employed to determine the best sensor placement location on the body and to reduce the number of sensor nodes for device ergonomics. During the tests, the volunteer's movements are recorded with six groups of sensors each with a triaxial (accelerometer, gyroscope and magnetometer) sensor, which is placed tightly on different parts of the body with special straps: head, chest, waist, right-wrist, right-thigh and right-ankle. The accuracy of individual sensor groups with their location is investigated with six machine learning techniques, namely the k-nearest neighbor (k-NN) classifier, Bayesian decision making (BDM), support vector machines (SVM), least squares method (LSM), dynamic time warping (DTW) and artificial neural networks (ANNs). Each technique is applied to single, double, triple, quadruple, quintuple and sextuple sensor configurations. These configurations create 63 different combinations, and for six machine learning techniques, a total of 63 × 6 = 378 combinations is investigated. As a result, the waist region is found to be the most suitable location for sensor placement on the body with 99.96% fall detection sensitivity by using the k-NN classifier, whereas the best sensitivity achieved by the wrist sensor is 97.37%, despite this location being highly preferred for today's wearable applications.

Telehealth, Wearable Sensors, and the Internet: Will They Improve Stroke Outcomes Through Increased Intensity of Therapy, Motivation, and Adherence to Rehabilitation Programs?

PubMed

Burridge, Jane H; Lee, Alan Chong W; Turk, Ruth; Stokes, Maria; Whitall, Jill; Vaidyanathan, Ravi; Clatworthy, Phil; Hughes, Ann-Marie; Meagher, Claire; Franco, Enrico; Yardley, Lucy

2017-07-01

Stroke, predominantly a condition of older age, is a major cause of acquired disability in the global population and puts an increasing burden on health care resources. Clear evidence for the importance of intensity of therapy in optimizing functional outcomes is found in animal models, supported by neuroimaging and behavioral research, and strengthened by recent meta-analyses from multiple clinical trials. However, providing intensive therapy using conventional treatment paradigms is expensive and sometimes not feasible because of social and environmental factors. This article addresses the need for cost-effective increased intensity of practice and suggests potential benefits of telehealth (TH) as an innovative model of care in physical therapy. We provide an overview of TH and present evidence that a web-supported program, used in conjunction with constraint-induced therapy (CIT), can increase intensity and adherence to a rehabilitation regimen. The design and feasibility testing of this web-based program, "LifeCIT," is presented. We describe how wearable sensors can monitor activity and provide feedback to patients and therapists. The methodology for the development of a wearable device with embedded inertial and mechanomyographic sensors, algorithms to classify functional movement, and a graphical user interface to present meaningful data to patients to support a home exercise program is explained. We propose that wearable sensor technologies and TH programs have the potential to provide most-effective, intensive, home-based stroke rehabilitation.

Self-Healable Sensors Based Nanoparticles for Detecting Physiological Markers via Skin and Breath: Toward Disease Prevention via Wearable Devices.

PubMed

Jin, Han; Huynh, Tan-Phat; Haick, Hossam

2016-07-13

Flexible and wearable electronic sensors are useful for the early diagnosis and monitoring of an individual's health state. Sampling of volatile organic compounds (VOCs) derived from human breath/skin or monitoring abrupt changes in heart-beat/breath rate should allow noninvasive monitoring of disease states at an early stage. Nevertheless, for many reported wearable sensing devices, interaction with the human body leads incidentally to unavoidable scratches and/or mechanical cuts and bring about malfunction of these devices. We now offer proof-of-concept of nanoparticle-based flexible sensor arrays with fascinating self-healing abilities. By integrating a self-healable polymer substrate with 5 kinds of functionalized gold nanoparticle films, a sensor array gives a fast self-healing (<3 h) and attractive healing efficiency in both the substrate and sensing films. The proposed platform was used in sensing pressure variation and 11 kinds of VOCs. The sensor array had satisfactory sensitivity, a low detection limit, and promising discrimination features in monitoring both of VOCs and pressure variation, even after full healing. These results presage a new type of smart sensing device, with a desirable performance in the possible detection and/or clinical application for a number of different purposes.

A Wireless Biomedical Signal Interface System-on-Chip for Body Sensor Networks.

PubMed

Lei Wang; Guang-Zhong Yang; Jin Huang; Jinyong Zhang; Li Yu; Zedong Nie; Cumming, D R S

2010-04-01

Recent years have seen the rapid development of biosensor technology, system-on-chip design, wireless technology. and ubiquitous computing. When assembled into an autonomous body sensor network (BSN), the technologies become powerful tools in well-being monitoring, medical diagnostics, and personal connectivity. In this paper, we describe the first demonstration of a fully customized mixed-signal silicon chip that has most of the attributes required for use in a wearable or implantable BSN. Our intellectual-property blocks include low-power analog sensor interface for temperature and pH, a data multiplexing and conversion module, a digital platform based around an 8-b microcontroller, data encoding for spread-spectrum wireless transmission, and a RF section requiring very few off-chip components. The chip has been fully evaluated and tested by connection to external sensors, and it satisfied typical system requirements.

Remote monitoring of soldier safety through body posture identification using wearable sensor networks

NASA Astrophysics Data System (ADS)

Biswas, Subir; Quwaider, Muhannad

2008-04-01

The physical safety and well being of the soldiers in a battlefield is the highest priority of Incident Commanders. Currently, the ability to track and monitor soldiers rely on visual and verbal communication which can be somewhat limited in scenarios where the soldiers are deployed inside buildings and enclosed areas that are out of visual range of the commanders. Also, the need for being stealth can often prevent a battling soldier to send verbal clues to a commander about his or her physical well being. Sensor technologies can remotely provide various data about the soldiers including physiological monitoring and personal alert safety system functionality. This paper presents a networked sensing solution in which a body area wireless network of multi-modal sensors can monitor the body movement and other physiological parameters for statistical identification of a soldier's body posture, which can then be indicative of the physical conditions and safety alerts of the soldier in question. The specific concept is to leverage on-body proximity sensing and a Hidden Markov Model (HMM) based mechanism that can be applied for stochastic identification of human body postures using a wearable sensor network. The key idea is to collect relative proximity information between wireless sensors that are strategically placed over a subject's body to monitor the relative movements of the body segments, and then to process that using HMM in order to identify the subject's body postures. The key novelty of this approach is a departure from the traditional accelerometry based approaches in which the individual body segment movements, rather than their relative proximity, is used for activity monitoring and posture detection. Through experiments with body mounted sensors we demonstrate that while the accelerometry based approaches can be used for differentiating activity intensive postures such as walking and running, they are not very effective for identification and differentiation between low activity postures such as sitting and standing. We develop a wearable sensor network that monitors relative proximity using Radio Signal Strength indication (RSSI), and then construct a HMM system for posture identification in the presence of sensing errors. Controlled experiments using human subjects were carried out for evaluating the accuracy of the HMM identified postures compared to a naÃve threshold based mechanism, and its variations over different human subjects. A large spectrum of target human postures, including lie down, sit (straight and reclined), stand, walk, run, sprint and stair climbing, are used for validating the proposed system.

A wearable biochemical sensor for monitoring alcohol consumption lifestyle through Ethyl glucuronide (EtG) detection in human sweat

PubMed Central

Panneer Selvam, Anjan; Muthukumar, Sriram; Kamakoti, Vikramshankar; Prasad, Shalini

2016-01-01

We demonstrate for the first time a wearable biochemical sensor for monitoring alcohol consumption through the detection and quantification of a metabolite of ethanol, ethyl glucuronide (EtG). We designed and fabricated two co-planar sensors with gold and zinc oxide as sensing electrodes. We also designed a LED based reporting for the presence of EtG in the human sweat samples. The sensor functions on affinity based immunoassay principles whereby monoclonal antibodies for EtG were immobilized on the electrodes using thiol based chemistry. Detection of EtG from human sweat was achieved through chemiresistive sensing mechanism. In this method, an AC voltage was applied across the two coplanar electrodes and the impedance across the sensor electrodes was measured and calibrated for physiologically relevant doses of EtG in human sweat. EtG detection over a dose concentration of 0.001–100 μg/L was demonstrated on both glass and polyimide substrates. Detection sensitivity was lower at 1 μg/L with gold electrodes as compared to ZnO, which had detection sensitivity of 0.001 μg/L. Based on the detection range the wearable sensor has the ability to detect alcohol consumption of up to 11 standard drinks in the US over a period of 4 to 9 hours. PMID:26996103

A flexible transcutaneous oxygen sensor using polymer membranes.

PubMed

Kudo, Hiroyuki; Iguchi, Shigehito; Yamada, Takua; Kawase, Tatsuya; Saito, Hirokazu; Otsuka, Kimio; Mitsubayashi, Kohji

2007-02-01

A wearable and flexible oxygen sensor for transcutaneous blood gas monitoring was fabricated and tested. The sensor has a laminar film-like structure, which was fabricated by pouching KCl electrolyte solution by both non-permeable (metal weldable) sheet and gas-permeable membrane with Pt- and Ag/AgCl-electrodes patterned using microfabrication process. The electrolyte solution was fixed only by heat-sealing the edges of the weldable membranes without any chemical adhesives. The wearable oxygen sensor (thickness: 84 mum) was applied to the electrochemical measurement with a constant potential of -600 mV vs. Ag/AgCl, thus obtaining the calibration range to dissolved oxygen (DO) from 0.0 to 7.0 mg/l with a correlation coefficient of 0.998 and the quick response time (53.4 s to 90% of a steady-state current), which operate similarly to a commercially available oxygen electrode. The sensor was also utilized to transcutaneous oxygen monitoring for healthy human subject. The sensing region of the wearable oxygen sensor was attached onto the forearm-skin surface of the subject inhaling various concentrations of oxygen. As a result of physiological application, the output current was varied from -6.2 microA to -7.8 microA within 2 min when the concentration of inhaling oxygen was changed from atmospheric air to 60% oxygen. Thus, the transcutaneous oxygen was successfully monitored without any inconveniences such as skin inflammation, etc.

A wearable biochemical sensor for monitoring alcohol consumption lifestyle through Ethyl glucuronide (EtG) detection in human sweat

NASA Astrophysics Data System (ADS)

Panneer Selvam, Anjan; Muthukumar, Sriram; Kamakoti, Vikramshankar; Prasad, Shalini

2016-03-01

We demonstrate for the first time a wearable biochemical sensor for monitoring alcohol consumption through the detection and quantification of a metabolite of ethanol, ethyl glucuronide (EtG). We designed and fabricated two co-planar sensors with gold and zinc oxide as sensing electrodes. We also designed a LED based reporting for the presence of EtG in the human sweat samples. The sensor functions on affinity based immunoassay principles whereby monoclonal antibodies for EtG were immobilized on the electrodes using thiol based chemistry. Detection of EtG from human sweat was achieved through chemiresistive sensing mechanism. In this method, an AC voltage was applied across the two coplanar electrodes and the impedance across the sensor electrodes was measured and calibrated for physiologically relevant doses of EtG in human sweat. EtG detection over a dose concentration of 0.001-100 μg/L was demonstrated on both glass and polyimide substrates. Detection sensitivity was lower at 1 μg/L with gold electrodes as compared to ZnO, which had detection sensitivity of 0.001 μg/L. Based on the detection range the wearable sensor has the ability to detect alcohol consumption of up to 11 standard drinks in the US over a period of 4 to 9 hours.

Quantitative Analysis of Motor Status in Parkinson's Disease Using Wearable Devices: From Methodological Considerations to Problems in Clinical Applications.

PubMed

Suzuki, Masahiko; Mitoma, Hiroshi; Yoneyama, Mitsuru

2017-01-01

Long-term and objective monitoring is necessary for full assessment of the condition of patients with Parkinson's disease (PD). Recent advances in biotechnology have seen the development of various types of wearable (body-worn) sensor systems. By using accelerometers and gyroscopes, these devices can quantify motor abnormalities, including decreased activity and gait disturbances, as well as nonmotor signs, such as sleep disturbances and autonomic dysfunctions in PD. This review discusses methodological problems inherent in wearable devices. Until now, analysis of the mean values of motion-induced signals on a particular day has been widely applied in the clinical management of PD patients. On the other hand, the reliability of these devices to detect various events, such as freezing of gait and dyskinesia, has been less than satisfactory. Quantification of disease-specific changes rather than nonspecific changes is necessary.

A wearable computing platform for developing cloud-based machine learning models for health monitoring applications.

PubMed

Patel, Shyamal; McGinnis, Ryan S; Silva, Ikaro; DiCristofaro, Steve; Mahadevan, Nikhil; Jortberg, Elise; Franco, Jaime; Martin, Albert; Lust, Joseph; Raj, Milan; McGrane, Bryan; DePetrillo, Paolo; Aranyosi, A J; Ceruolo, Melissa; Pindado, Jesus; Ghaffari, Roozbeh

2016-08-01

Wearable sensors have the potential to enable clinical-grade ambulatory health monitoring outside the clinic. Technological advances have enabled development of devices that can measure vital signs with great precision and significant progress has been made towards extracting clinically meaningful information from these devices in research studies. However, translating measurement accuracies achieved in the controlled settings such as the lab and clinic to unconstrained environments such as the home remains a challenge. In this paper, we present a novel wearable computing platform for unobtrusive collection of labeled datasets and a new paradigm for continuous development, deployment and evaluation of machine learning models to ensure robust model performance as we transition from the lab to home. Using this system, we train activity classification models across two studies and track changes in model performance as we go from constrained to unconstrained settings.

Quantitative Analysis of Motor Status in Parkinson's Disease Using Wearable Devices: From Methodological Considerations to Problems in Clinical Applications

PubMed Central

2017-01-01

Long-term and objective monitoring is necessary for full assessment of the condition of patients with Parkinson's disease (PD). Recent advances in biotechnology have seen the development of various types of wearable (body-worn) sensor systems. By using accelerometers and gyroscopes, these devices can quantify motor abnormalities, including decreased activity and gait disturbances, as well as nonmotor signs, such as sleep disturbances and autonomic dysfunctions in PD. This review discusses methodological problems inherent in wearable devices. Until now, analysis of the mean values of motion-induced signals on a particular day has been widely applied in the clinical management of PD patients. On the other hand, the reliability of these devices to detect various events, such as freezing of gait and dyskinesia, has been less than satisfactory. Quantification of disease-specific changes rather than nonspecific changes is necessary. PMID:28607801

Lead zirconate titanate nanowire textile nanogenerator for wearable energy-harvesting and self-powered devices.

PubMed

Wu, Weiwei; Bai, Suo; Yuan, Miaomiao; Qin, Yong; Wang, Zhong Lin; Jing, Tao

2012-07-24

Wearable nanogenerators are of vital importance to portable energy-harvesting and personal electronics. Here we report a method to synthesize a lead zirconate titanate textile in which nanowires are parallel with each other and a procedure to make it into flexible and wearable nanogenerators. The nanogenerator can generate 6 V output voltage and 45 nA output current, which are large enough to power a liquid crystal display and a UV sensor.

Adaptive cancellation of motion artifact in wearable biosensors.

PubMed

Yousefi, Rasoul; Nourani, Mehrdad; Panahi, Issa

2012-01-01

The performance of wearable biosensors is highly influenced by motion artifact. In this paper, a model is proposed for analysis of motion artifact in wearable photoplethysmography (PPG) sensors. Using this model, we proposed a robust real-time technique to estimate fundamental frequency and generate a noise reference signal. A Least Mean Square (LMS) adaptive noise canceler is then designed and validated using our synthetic noise generator. The analysis and results on proposed technique for noise cancellation shows promising performance.

Wearable wireless sensor platform for studying autonomic activity and social behavior in non-human primates.

PubMed

Fletcher, Richard Ribón; Amemori, Ken-ichi; Goodwin, Matthew; Graybiel, Ann M

2012-01-01

A portable system has been designed to enable remote monitoring of autonomic nervous system output in non-human primates for the purpose of studying neural function related to social behavior over extended periods of time in an ambulatory setting. In contrast to prior systems which only measure heart activity, are restricted to a constrained laboratory setting, or require surgical attachment, our system is comprised of a multi-sensor self-contained wearable vest that can easily be transferred from one subject to another. The vest contains a small detachable low-power electronic sensor module for measuring electrodermal activity (EDA), electrocardiography (ECG), 3-axis acceleration, and temperature. The wireless transmission is implemented using a standard Bluetooth protocol and a mobile phone, which enables freedom of movement for the researcher as well as for the test subject. A custom Android software application was created on the mobile phone for viewing and recording live data as well as creating annotations. Data from up to seven monkeys can be recorded simultaneously using the mobile phone, with the option of real-time upload to a remote web server. Sample data are presented from two rhesus macaque monkeys showing stimulus-induced response in the laboratory as well as long-term ambulatory data collected in a large monkey cage. This system enables new possibilities for studying underlying mechanisms between autonomic brain function and social behavior with connection to human research in areas such as autism, substance abuse, and mood disorders.

Miniature low-power inertial sensors: promising technology for implantable motion capture systems.

PubMed

Lambrecht, Joris M; Kirsch, Robert F

2014-11-01

Inertial and magnetic sensors are valuable for untethered, self-contained human movement analysis. Very recently, complete integration of inertial sensors, magnetic sensors, and processing into single packages, has resulted in miniature, low power devices that could feasibly be employed in an implantable motion capture system. We developed a wearable sensor system based on a commercially available system-in-package inertial and magnetic sensor. We characterized the accuracy of the system in measuring 3-D orientation-with and without magnetometer-based heading compensation-relative to a research grade optical motion capture system. The root mean square error was less than 4° in dynamic and static conditions about all axes. Using four sensors, recording from seven degrees-of-freedom of the upper limb (shoulder, elbow, wrist) was demonstrated in one subject during reaching motions. Very high correlation and low error was found across all joints relative to the optical motion capture system. Findings were similar to previous publications using inertial sensors, but at a fraction of the power consumption and size of the sensors. Such ultra-small, low power sensors provide exciting new avenues for movement monitoring for various movement disorders, movement-based command interfaces for assistive devices, and implementation of kinematic feedback systems for assistive interventions like functional electrical stimulation.

Secured remote health monitoring system

PubMed Central

Ganesh Kumar, Pugalendhi

2017-01-01

Wireless medical sensor network is used in healthcare applications that have the collections of biosensors connected to a human body or emergency care unit to monitor the patient's physiological vital status. The real-time medical data collected using wearable medical sensors are transmitted to a diagnostic centre. The data generated from the sensors are aggregated at this centre and transmitted further to the doctor's personal digital assistant for diagnosis. The unauthorised access of one's health data may lead to misuse and legal complications while unreliable data transmission or storage may lead to life threatening risk to patients. So, this Letter combines the symmetric algorithm and attribute-based encryption to secure the data transmission and access control system for medical sensor network. In this work, existing systems and their algorithm are compared for identifying the best performance. The work also shows the graphical comparison of encryption time, decryption time and total computation time of the existing and the proposed systems. PMID:29383257

Intelligent Medical Garments with Graphene-Functionalized Smart-Cloth ECG Sensors

PubMed Central

Yapici, Murat Kaya; Alkhidir, Tamador Elboshra

2017-01-01

Biopotential signals are recorded mostly by using sticky, pre-gelled electrodes, which are not ideal for wearable, point-of-care monitoring where the usability of the personalized medical device depends critically on the level of comfort and wearability of the electrodes. We report a fully-wearable medical garment for mobile monitoring of cardiac biopotentials from the wrists or the neck with minimum restriction to regular clothing habits. The wearable prototype is based on elastic bands with graphene functionalized, textile electrodes and battery-powered, low-cost electronics for signal acquisition and wireless transmission. Comparison of the electrocardiogram (ECG) recordings obtained from the wearable prototype against conventional wet electrodes indicate excellent conformity and spectral coherence among the two signals. PMID:28420158

An Architecture to Support Wearables in Education and Wellbeing

ERIC Educational Resources Information Center

Luis-Ferreira, Fernando; Artifice, Andreia; McManus, Gary; Sarraipa, João

2017-01-01

Technological devices help extending a person's sensory experience of the environment. From sensors to cameras, devices currently use embedded systems that can be used for the main goal they were designed but they can also be used for other objectives without additional costs of material or service subscription. Emotional assessment is a useful…

An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes

PubMed Central

Casson, Alexander J.

2015-01-01

Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via gmC circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans. PMID:26694414

An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes.

PubMed

Casson, Alexander J

2015-12-17

Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via g(m)C circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans.

A sneak peek into digital innovations and wearable sensors for cardiac monitoring.

PubMed

Michard, Frederic

2017-04-01

Many mobile phone or tablet applications have been designed to control cardiovascular risk factors (obesity, smoking, sedentary lifestyle, diabetes and hypertension) or to optimize treatment adherence. Some have been shown to be useful but the long-term benefits remain to be demonstrated. Digital stethoscopes make easier the interpretation of abnormal heart sounds, and the development of pocket-sized echo machines may quickly and significantly expand the use of ultrasounds. Daily home monitoring of pulmonary artery pressures with wireless implantable sensors has been shown to be associated with a significant decrease in hospital readmissions for heart failure. There are more and more non-invasive, wireless, and wearable sensors designed to monitor heart rate, heart rate variability, respiratory rate, arterial oxygen saturation, and thoracic fluid content. They have the potential to change the way we monitor and treat patients with cardiovascular diseases in the hospital and beyond. Some may have the ability to improve quality of care, decrease the number of medical visits and hospitalization, and ultimately health care costs. Validation and outcome studies are needed to clarify, among the growing number of digital innovations and wearable sensors, which tools have real clinical value.

Capacitive wearable tactile sensor based on smart textile substrate with carbon black /silicone rubber composite dielectric

NASA Astrophysics Data System (ADS)

Guo, Xiaohui; Huang, Ying; Cai, Xia; Liu, Caixia; Liu, Ping

2016-04-01

To achieve the wearable comfort of electronic skin (e-skin), a capacitive sensor printed on a flexible textile substrate with a carbon black (CB)/silicone rubber (SR) composite dielectric was demonstrated in this paper. Organo-silicone conductive silver adhesive serves as a flexible electrodes/shielding layer. The structure design, sensing mechanism and the influence of the conductive filler content and temperature variations on the sensor performance were investigated. The proposed device can effectively enhance the flexibility and comfort of wearing the device asthe sensing element has achieved a sensitivity of 0.02536%/KPa, a hysteresis error of 5.6%, and a dynamic response time of ~89 ms at the range of 0-700 KPa. The drift induced by temperature variations has been calibrated by presenting the temperature compensation model. The research on the time-space distribution of plantar pressure information and the experiment of the manipulator soft-grasping were implemented with the introduced device, and the experimental results indicate that the capacitive flexible textile tactile sensor has good stability and tactile perception capacity. This study provides a good candidate for wearable artificial skin.

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

Nonenzymatic Wearable Sensor for Electrochemical Analysis of Perspiration Glucose.

PubMed

Zhu, Xiaofei; Ju, Yinhui; Chen, Jian; Liu, Deye; Liu, Hong

2018-05-25

We report a nonenzymatic wearable sensor for electrochemical analysis of perspiration glucose. Multipotential steps are applied on a Au electrode, including a high negative pretreatment potential step for proton reduction which produces a localized alkaline condition, a moderate potential step for electrocatalytic oxidation of glucose under the alkaline condition, and a positive potential step to clean and reactivate the electrode surface for the next detection. Fluorocarbon-based materials were coated on the Au electrode for improving the selectivity and robustness of the sensor. A fully integrated wristband is developed for continuous real-time monitoring of perspiration glucose during physical activities, and uploading the test result to a smartphone app via Bluetooth.

Digital Suicide Prevention: Can Technology Become a Game-changer?

PubMed Central

Sahin, Ned; Kalali, Amir

2016-01-01

Suicide continues to be a leading cause of death and has been recognized as a significant public health issue. Rapid advances in data science can provide us with useful tools for suicide prevention, and help to dynamically assess suicide risk in quantitative data-driven ways. In this article, the authors highlight the most current international research in digital suicide prevention, including the use of machine learning, smartphone applications, and wearable sensor driven systems. The authors also discuss future opportunities for digital suicide prevention, and propose a novel Sensor-driven Mental State Assessment System. PMID:27800282

Research and development of smart wearable health applications: the challenge ahead.

PubMed

Lymberis, Andreas

2004-01-01

Continuous monitoring of physiological and physical parameters is necessary for the assessment and management of personal health status. It can significantly contribute to the reduction of healthcare cost by avoiding unnecessary hospitalisations and ensuring that those who need urgent care get it sooner. In conjunction with cost-effective telemedicine platforms, ubiquitous health monitoring can significantly contribute to the enhancement of disease prevention and early diagnosis, disease management, treatment and home rehabilitation. Latest developments in the area of micro and nanotechnologies, information processing and wireless communication offer, today, the possibility for minimally (or non) invasive biomedical measurement but also wearable sensing, processing and data communication. Although the systems are being developed to satisfy specific user needs, a number of common critical issues have to be tackled to achieve reliable and acceptable smart health wearable applications e.g. biomedical sensors, user interface, clinical validation, data security and confidentiality, scenarios of use, decision support, user acceptance and business models. Major technological achievements have been realised the last few years. Cutting edge development combining functional clothing and integrated electronics open a new research area and possibilities for body sensing and communicating health parameters. This paper reviews the current status of research and development on smart wearable health systems and applications and discusses the outstanding issues and future challenges.

Towards Building a Computer Aided Education System for Special Students Using Wearable Sensor Technologies

PubMed Central

Mehmood, Raja Majid; Lee, Hyo Jong

2017-01-01

Human computer interaction is a growing field in terms of helping people in their daily life to improve their living. Especially, people with some disability may need an interface which is more appropriate and compatible with their needs. Our research is focused on similar kinds of problems, such as students with some mental disorder or mood disruption problems. To improve their learning process, an intelligent emotion recognition system is essential which has an ability to recognize the current emotional state of the brain. Nowadays, in special schools, instructors are commonly use some conventional methods for managing special students for educational purposes. In this paper, we proposed a novel computer aided method for instructors at special schools where they can teach special students with the support of our system using wearable technologies. PMID:28208734

Flexible heartbeat sensor for wearable device.

PubMed

Kwak, Yeon Hwa; Kim, Wonhyo; Park, Kwang Bum; Kim, Kunnyun; Seo, Sungkyu

2017-08-15

We demonstrate a flexible strain-gauge sensor and its use in a wearable application for heart rate detection. This polymer-based strain-gauge sensor was fabricated using a double-sided fabrication method with polymer and metal, i.e., polyimide and nickel-chrome. The fabrication process for this strain-gauge sensor is compatible with the conventional flexible printed circuit board (FPCB) processes facilitating its commercialization. The fabricated sensor showed a linear relation for an applied normal force of more than 930 kPa, with a minimum detectable force of 6.25Pa. This sensor can also linearly detect a bending radius from 5mm to 100mm. It is a thin, flexible, compact, and inexpensive (for mass production) heart rate detection sensor that is highly sensitive compared to the established optical photoplethysmography (PPG) sensors. It can detect not only the timing of heart pulsation, but also the amplitude or shape of the pulse signal. The proposed strain-gauge sensor can be applicable to various applications for smart devices requiring heartbeat detection. Copyright © 2017 Elsevier B.V. All rights reserved.

Sensor-Data Fusion for Multi-Person Indoor Location Estimation.

PubMed

Mohebbi, Parisa; Stroulia, Eleni; Nikolaidis, Ioanis

2017-10-18

We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other "wearable" device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary sensors (Passive Infrared motion sensors) and eponymous wearable sensors (smartphones interacting with Estimote beacons), and we propose a solution to the resulting sensor-fusion problem. Using a data set with sensor readings collected from one-person and two-person sessions engaged in a variety of activities of daily living, we investigate the relative merits of relying solely on anonymous sensors, solely on eponymous sensors, or on their combination. We examine how the lack of synchronization across different sensing sources impacts the quality of location estimates, and discuss how it could be mitigated without resorting to device-level mechanisms. Finally, we examine the trade-off between the sensors' coverage of the monitored space and the quality of the location estimates.

Solvent-free fabrication of biodegradable hot-film flow sensor for noninvasive respiratory monitoring

NASA Astrophysics Data System (ADS)

Dinh, Toan; Phan, Hoang-Phuong; Nguyen, Tuan-Khoa; Qamar, Afzaal; Woodfield, Peter; Zhu, Yong; Nguyen, Nam-Trung; Viet Dao, Dzung

2017-06-01

In this paper, we report on a low-cost, environment-friendly and wearable thermal flow sensor, which can be manufactured in-house using pencil graphite as a sensing hot film and biodegradable printing paper as a substrate, without using any toxic solvents or cleanroom facilities. The hot film flow sensor offers excellent performance such as high signal-to-noise ratio (≥slant 40 for an air flow velocity of 1 m s-1), high sensitivity to airflow (53.7 mV(m s-1)-0.8) and outstanding long-term stability (almost no drift in 24 h). The sensor can be comfortably affixed to the philtrum of patients and measures human respiration in realtime. The results indicate that the wearable thermal flow sensors fabricated by this solvent-free and user-friendly method could be employed in human respiratory monitoring.

Wearable system-on-a-chip radiometer for remote temperature sensing and its application to the safeguard of emergency operators.

PubMed

Fonte, A; Alimenti, F; Zito, D; Neri, B; De Rossi, D; Lanatà, A; Tognetti, A

2007-01-01

The remote sensing and the detection of events that may represent a danger for human beings have become more and more important thanks to the latest advances of the technology. A microwave radiometer is a sensor capable to detect a fire or an abnormal increase of the internal temperature of the human body (hyperthermia), or an onset of a cancer, or even meteorological phenomena (forest fires, pollution release, ice formation on road pavement). In this paper, the overview of a wearable low-cost low-power system-on-a-chip (SoaC) 13 GHz passive microwave radiometer in CMOS 90 nm technology is presented. In particular, we focused on its application to the fire detection for civil safeguard. In detail, this sensor has been thought to be inserted into the fireman jacket in order to help the fireman in the detection of a hidden fire behind a door or a wall. The simulation results obtained by Ptolemy system simulation have confirmed the feasibility of such a SoaC microwave radiometer in a low-cost standard silicon technology for temperature remote sensing and, in particular, for its application to the safeguard of emergency operators.

Wearable technology: role in respiratory health and disease.

PubMed

Aliverti, Andrea

2017-06-01

In the future, diagnostic devices will be able to monitor a patient's physiological or biochemical parameters continuously, under natural physiological conditions and in any environment through wearable biomedical sensors. Together with apps that capture and interpret data, and integrated enterprise and cloud data repositories, the networks of wearable devices and body area networks will constitute the healthcare's Internet of Things. In this review, four main areas of interest for respiratory healthcare are described: pulse oximetry, pulmonary ventilation, activity tracking and air quality assessment. Although several issues still need to be solved, smart wearable technologies will provide unique opportunities for the future or personalised respiratory medicine.

Wearable technology: role in respiratory health and disease

PubMed Central

2017-01-01

In the future, diagnostic devices will be able to monitor a patient’s physiological or biochemical parameters continuously, under natural physiological conditions and in any environment through wearable biomedical sensors. Together with apps that capture and interpret data, and integrated enterprise and cloud data repositories, the networks of wearable devices and body area networks will constitute the healthcare’s Internet of Things. In this review, four main areas of interest for respiratory healthcare are described: pulse oximetry, pulmonary ventilation, activity tracking and air quality assessment. Although several issues still need to be solved, smart wearable technologies will provide unique opportunities for the future or personalised respiratory medicine. PMID:28966692

Epidermal tattoo potentiometric sodium sensors with wireless signal transduction for continuous non-invasive sweat monitoring.

PubMed

Bandodkar, Amay J; Molinnus, Denise; Mirza, Omar; Guinovart, Tomás; Windmiller, Joshua R; Valdés-Ramírez, Gabriela; Andrade, Francisco J; Schöning, Michael J; Wang, Joseph

2014-04-15

This article describes the fabrication, characterization and application of an epidermal temporary-transfer tattoo-based potentiometric sensor, coupled with a miniaturized wearable wireless transceiver, for real-time monitoring of sodium in the human perspiration. Sodium excreted during perspiration is an excellent marker for electrolyte imbalance and provides valuable information regarding an individual's physical and mental wellbeing. The realization of the new skin-worn non-invasive tattoo-like sensing device has been realized by amalgamating several state-of-the-art thick film, laser printing, solid-state potentiometry, fluidics and wireless technologies. The resulting tattoo-based potentiometric sodium sensor displays a rapid near-Nernstian response with negligible carryover effects, and good resiliency against various mechanical deformations experienced by the human epidermis. On-body testing of the tattoo sensor coupled to a wireless transceiver during exercise activity demonstrated its ability to continuously monitor sweat sodium dynamics. The real-time sweat sodium concentration was transmitted wirelessly via a body-worn transceiver from the sodium tattoo sensor to a notebook while the subjects perspired on a stationary cycle. The favorable analytical performance along with the wearable nature of the wireless transceiver makes the new epidermal potentiometric sensing system attractive for continuous monitoring the sodium dynamics in human perspiration during diverse activities relevant to the healthcare, fitness, military, healthcare and skin-care domains. © 2013 Published by Elsevier B.V.

A wearable textile for respiratory monitoring: Feasibility assessment and analysis of sensors position on system response.

PubMed

Lo Presti, D; Massaroni, C; Saccomandi, P; Caponero, M A; Formica, D; Schena, E

2017-07-01

The interest on wearable textiles to monitor vital signs is growing in the research field and clinical scenario related to the increasing demands of long-term monitoring. Despite several smart textile-based solutions have been proposed for assessing the respiratory status, only a limited number of devices allow the respiratory monitoring in a harsh environment or in different positions of the human body. In this paper, we investigated the performances of a smart textile for respiratory rate monitoring characterized by 12 fiber optic sensors (i.e., fiber Bragg grating) placed on specific landmarks for compartmental analysis of the chest wall movements during quiet breathing. We focused on the analysis of the influence of sensor position on both peak-to-peak amplitude of sensors output and accuracy of respiratory rate measurements. This analysis was performed on two participants, who wore the textile in two positions (i.e., standing and supine). Bland-Altman analysis on respiratory rate showed promising results (better than 0.3 breaths per minute). Referring to the peak-to-peak output amplitude, the abdomen compartment showed the highest excursions in both the enrolled participants and positions. Our findings open up new approaches to design and develop smart textile for respiratory rate monitoring.

Sweat test for cystic fibrosis: Wearable sweat sensor vs. standard laboratory test.

PubMed

Choi, Dong-Hoon; Thaxton, Abigail; Jeong, In Cheol; Kim, Kain; Sosnay, Patrick R; Cutting, Garry R; Searson, Peter C

2018-03-23

Sweat chloride testing for diagnosis of cystic fibrosis (CF) involves sweat induction, collection and handling, and measurement in an analytical lab. We have developed a wearable sensor with an integrated salt bridge for real-time measurement of sweat chloride concentration. Here, in a proof-of-concept study, we compare the performance of the sensor to current clinical practice in CF patients and healthy subjects. Sweat was induced on both forearms of 10 individuals with CF and 10 healthy subjects using pilocarpine iontophoresis. A Macroduct sweat collection device was attached to one arm and sweat was collected for 30 min and then sent for laboratory analysis. A sensor was attached to the other arm and the chloride ion concentration monitored in real time for 30 min using a Bluetooth transceiver and smart phone app. Stable sweat chloride measurements were obtained within 15 min following sweat induction using the wearable sensor. We define the detection time as the time at which the standard deviation of the real-time chloride ion concentration remained below 2 mEq/L for 5 min. The sweat volume for sensor measurements at the detection time was 13.1 ± 11.4 μL (SD), in many cases lower than the minimum sweat volume of 15 μL for conventional testing. The mean difference between sweat chloride concentrations measured by the sensor and the conventional laboratory practice was 6.2 ± 9.5 mEq/L (SD), close to the arm-to-arm variation of about 3 mEq/L. The Pearson correlation coefficient between the two measurements was 0.97 highlighting the excellent agreement between the two methods. A wearable sensor can be used to make real-time measurements of sweat chloride within 15 min following sweat induction, requiring a small sweat volume, and with excellent agreement to standard methods. Copyright © 2018 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

Development of a Multisensory Wearable System for Monitoring Cigarette Smoking Behavior in Free-Living Conditions

PubMed Central

Imtiaz, Masudul Haider; Ramos-Garcia, Raul I.; Senyurek, Volkan Yusuf; Tiffany, Stephen; Sazonov, Edward

2017-01-01

This paper presents the development and validation of a novel multi-sensory wearable system (Personal Automatic Cigarette Tracker v2 or PACT2.0) for monitoring of cigarette smoking in free-living conditions. The contributions of the PACT2.0 system are: (1) the implementation of a complete sensor suite for monitoring of all major behavioral manifestations of cigarette smoking (lighting events, hand-to-mouth gestures, and smoke inhalations); (2) a miniaturization of the sensor hardware to enable its applicability in naturalistic settings; and (3) an introduction of new sensor modalities that may provide additional insight into smoking behavior e.g., Global Positioning System (GPS), pedometer and Electrocardiogram(ECG) or provide an easy-to-use alternative (e.g., bio-impedance respiration sensor) to traditional sensors. PACT2.0 consists of three custom-built devices: an instrumented lighter, a hand module, and a chest module. The instrumented lighter is capable of recording the time and duration of all lighting events. The hand module integrates Inertial Measurement Unit (IMU) and a Radio Frequency (RF) transmitter to track the hand-to-mouth gestures. The module also operates as a pedometer. The chest module monitors the breathing (smoke inhalation) patterns (inductive and bio-impedance respiratory sensors), cardiac activity (ECG sensor), chest movement (three-axis accelerometer), hand-to-mouth proximity (RF receiver), and captures the geo-position of the subject (GPS receiver). The accuracy of PACT2.0 sensors was evaluated in bench tests and laboratory experiments. Use of PACT2.0 for data collection in the community was validated in a 24 h study on 40 smokers. Of 943 h of recorded data, 98.6% of the data was found usable for computer analysis. The recorded information included 549 lighting events, 522/504 consumed cigarettes (from lighter data/self-registered data, respectively), 20,158/22,207 hand-to-mouth gestures (from hand IMU/proximity sensor, respectively) and 114,217/112,175 breaths (from the respiratory inductive plethysmograph (RIP)/bio-impedance sensor, respectively). The proposed system scored 8.3 ± 0.31 out of 10 on a post-study acceptability survey. The results suggest that PACT2.0 presents a reliable platform for studying of smoking behavior at the community level. PMID:29607211

A review on architectures and communications technologies for wearable health-monitoring systems.

PubMed

Custodio, Víctor; Herrera, Francisco J; López, Gregorio; Moreno, José Ignacio

2012-10-16

Nowadays society is demanding more and more smart healthcare services that allow monitoring patient status in a non-invasive way, anywhere and anytime. Thus, healthcare applications are currently facing important challenges guided by the u-health (ubiquitous health) and p-health (pervasive health) paradigms. New emerging technologies can be combined with other widely deployed ones to develop such next-generation healthcare systems. The main objective of this paper is to review and provide more details on the work presented in "LOBIN: E-Textile and Wireless-Sensor-Network-Based Platform for Healthcare Monitoring in Future Hospital Environments", published in the IEEE Transactions on Information Technology in Biomedicine, as well as to extend and update the comparison with other similar systems. As a result, the paper discusses the main advantages and disadvantages of using different architectures and communications technologies to develop wearable systems for pervasive healthcare applications.

A Review on Architectures and Communications Technologies for Wearable Health-Monitoring Systems

PubMed Central

Custodio, Víctor; Herrera, Francisco J.; López, Gregorio; Moreno, José Ignacio

2012-01-01

Nowadays society is demanding more and more smart healthcare services that allow monitoring patient status in a non-invasive way, anywhere and anytime. Thus, healthcare applications are currently facing important challenges guided by the u-health (ubiquitous health) and p-health (pervasive health) paradigms. New emerging technologies can be combined with other widely deployed ones to develop such next-generation healthcare systems. The main objective of this paper is to review and provide more details on the work presented in “LOBIN: E-Textile and Wireless-Sensor-Network-Based Platform for Healthcare Monitoring in Future Hospital Environments”, published in the IEEE Transactions on Information Technology in Biomedicine, as well as to extend and update the comparison with other similar systems. As a result, the paper discusses the main advantages and disadvantages of using different architectures and communications technologies to develop wearable systems for pervasive healthcare applications. PMID:23202028

3D printed stretchable capacitive sensors for highly sensitive tactile and electrochemical sensing

NASA Astrophysics Data System (ADS)

Li, Kai; Wei, Hong; Liu, Wenguang; Meng, Hong; Zhang, Peixin; Yan, Chaoyi

2018-05-01

Developments of innovative strategies for the fabrication of stretchable sensors are of crucial importance for their applications in wearable electronic systems. In this work, we report the successful fabrication of stretchable capacitive sensors using a novel 3D printing method for highly sensitive tactile and electrochemical sensing applications. Unlike conventional lithographic or templated methods, the programmable 3D printing technique can fabricate complex device structures in a cost-effective and facile manner. We designed and fabricated stretchable capacitive sensors with interdigital and double-vortex designs and demonstrated their successful applications as tactile and electrochemical sensors. Especially, our stretchable sensors exhibited a detection limit as low as 1 × 10-6 M for NaCl aqueous solution, which could have significant potential applications when integrated in electronics skins.

3D printed stretchable capacitive sensors for highly sensitive tactile and electrochemical sensing.

PubMed

Li, Kai; Wei, Hong; Liu, Wenguang; Meng, Hong; Zhang, Peixin; Yan, Chaoyi

2018-05-04

Developments of innovative strategies for the fabrication of stretchable sensors are of crucial importance for their applications in wearable electronic systems. In this work, we report the successful fabrication of stretchable capacitive sensors using a novel 3D printing method for highly sensitive tactile and electrochemical sensing applications. Unlike conventional lithographic or templated methods, the programmable 3D printing technique can fabricate complex device structures in a cost-effective and facile manner. We designed and fabricated stretchable capacitive sensors with interdigital and double-vortex designs and demonstrated their successful applications as tactile and electrochemical sensors. Especially, our stretchable sensors exhibited a detection limit as low as 1 × 10 -6 M for NaCl aqueous solution, which could have significant potential applications when integrated in electronics skins.

Wearable Sensors for Chemical & Biological Detection

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

Ozanich, Richard M.

2017-08-31

One of PNNL’s strengths is the ability to conduct comprehensive technology foraging and objective assessments of various technology areas. The following examples highlight leading research by others in the area of chemical and biological (chem/bio) detection that could be further developed into a robust, highly integrated wearables to aid preparedness, response and recovery.

Scalable Production of Graphene-Based Wearable E-Textiles.

PubMed

Karim, Nazmul; Afroj, Shaila; Tan, Sirui; He, Pei; Fernando, Anura; Carr, Chris; Novoselov, Kostya S

2017-12-26

Graphene-based wearable e-textiles are considered to be promising due to their advantages over traditional metal-based technology. However, the manufacturing process is complex and currently not suitable for industrial scale application. Here we report a simple, scalable, and cost-effective method of producing graphene-based wearable e-textiles through the chemical reduction of graphene oxide (GO) to make stable reduced graphene oxide (rGO) dispersion which can then be applied to the textile fabric using a simple pad-dry technique. This application method allows the potential manufacture of conductive graphene e-textiles at commercial production rates of ∼150 m/min. The graphene e-textile materials produced are durable and washable with acceptable softness/hand feel. The rGO coating enhanced the tensile strength of cotton fabric and also the flexibility due to the increase in strain% at maximum load. We demonstrate the potential application of these graphene e-textiles for wearable electronics with activity monitoring sensor. This could potentially lead to a multifunctional single graphene e-textile garment that can act both as sensors and flexible heating elements powered by the energy stored in graphene textile supercapacitors.

Ultrathin Quantum Dot Display Integrated with Wearable Electronics.

PubMed

Kim, Jaemin; Shim, Hyung Joon; Yang, Jiwoong; Choi, Moon Kee; Kim, Dong Chan; Kim, Junhee; Hyeon, Taeghwan; Kim, Dae-Hyeong

2017-10-01

An ultrathin skin-attachable display is a critical component for an information output port in next-generation wearable electronics. In this regard, quantum dot (QD) light-emitting diodes (QLEDs) offer unique and attractive characteristics for future displays, including high color purity with narrow bandwidths, high electroluminescence (EL) brightness at low operating voltages, and easy processability. Here, ultrathin QLED displays that utilize a passive matrix to address individual pixels are reported. The ultrathin thickness (≈5.5 µm) of the QLED display enables its conformal contact with the wearer's skin and prevents its failure under vigorous mechanical deformation. QDs with relatively thick shells are employed to improve EL characteristics (brightness up to 44 719 cd m -2 at 9 V, which is the record highest among wearable LEDs reported to date) by suppressing the nonradiative recombination. Various patterns, including letters, numbers, and symbols can be successfully visualized on the skin-mounted QLED display. Furthermore, the combination of the ultrathin QLED display with flexible driving circuits and wearable sensors results in a fully integrated QLED display that can directly show sensor data. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

IoT/M2M wearable-based activity-calorie monitoring and analysis for elders.

PubMed

Soraya, Sabrina I; Ting-Hui Chiang; Guo-Jing Chan; Yi-Juan Su; Chih-Wei Yi; Yu-Chee Tseng; Yu-Tai Ching

2017-07-01

With the growth of aging population, elder care service has become an important part of the service industry of Internet of Things. Activity monitoring is one of the most important services in the field of the elderly care service. In this paper, we proposed a wearable solution to provide an activity monitoring service on elders for caregivers. The system uses wireless signals to estimate calorie burned by the walking and localization. In addition, it also uses wireless motion sensors to recognize physical activity, such as drinking and restroom activity. Overall, the system can be divided into four parts: wearable device, gateway, cloud server, and caregiver's android application. The algorithms we proposed for drinking activity are Decision Tree (J48) and Random Forest (RF). While for restroom activity, we proposed supervised Reduced Error Pruning (REP) Tree and Variable Order Hidden Markov Model (VOHMM). We developed a prototype service Android app to provide a life log for the recording of the activity sequence which would be useful for the caregiver to monitor elder activity and its calorie consumption.

Material approaches to stretchable strain sensors.

PubMed

Park, Jaeyoon; You, Insang; Shin, Sangbaie; Jeong, Unyong

2015-04-27

With the recent progress made in wearable electronics, devices now require high flexibility and stretchability up to large strain levels (typically larger than 30 % strain). Wearable strain sensors or deformable strain sensors have been gaining increasing research interest because of the rapid development of electronic skins and robotics and because of their biomedical applications. Conventional brittle strain sensors made of metals and piezoresistors are not applicable for such stretchable sensors. This Review summarizes recent advances in stretchable sensors and focuses on material aspects for high stretchability and sensitivity. It begins with a brief introduction to the Wheatstone bridge circuit of conventional resistive strain sensors. Then, studies on the manipulation of materials are reviewed, including waved structural approaches for making metals and semiconductors stretchable, the use of liquid metals, and conductive filler/elastomer composites by using percolation among the fillers. For capacitive strain sensors, the constant conductivity of the electrode is a key factor in obtaining reliable sensors. Possible approaches to developing capacitive strain sensors are presented. This Review concludes with a discussion on the major challenges and perspectives related to stretchable strain sensors. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Compression in wearable sensor nodes: impacts of node topology.

PubMed

Imtiaz, Syed Anas; Casson, Alexander J; Rodriguez-Villegas, Esther

2014-04-01

Wearable sensor nodes monitoring the human body must operate autonomously for very long periods of time. Online and low-power data compression embedded within the sensor node is therefore essential to minimize data storage/transmission overheads. This paper presents a low-power MSP430 compressive sensing implementation for providing such compression, focusing particularly on the impact of the sensor node architecture on the compression performance. Compression power performance is compared for four different sensor nodes incorporating different strategies for wireless transmission/on-sensor-node local storage of data. The results demonstrate that the compressive sensing used must be designed differently depending on the underlying node topology, and that the compression strategy should not be guided only by signal processing considerations. We also provide a practical overview of state-of-the-art sensor node topologies. Wireless transmission of data is often preferred as it offers increased flexibility during use, but in general at the cost of increased power consumption. We demonstrate that wireless sensor nodes can highly benefit from the use of compressive sensing and now can achieve power consumptions comparable to, or better than, the use of local memory.

A Wearable Mobile Sensor Platform to Assist Fruit Grading

PubMed Central

Aroca, Rafael V.; Gomes, Rafael B.; Dantas, Rummennigue R.; Calbo, Adonai G.; Gonçalves, Luiz M. G.

2013-01-01

Wearable computing is a form of ubiquitous computing that offers flexible and useful tools for users. Specifically, glove-based systems have been used in the last 30 years in a variety of applications, but mostly focusing on sensing people's attributes, such as finger bending and heart rate. In contrast, we propose in this work a novel flexible and reconfigurable instrumentation platform in the form of a glove, which can be used to analyze and measure attributes of fruits by just pointing or touching them with the proposed glove. An architecture for such a platform is designed and its application for intuitive fruit grading is also presented, including experimental results for several fruits. PMID:23666134

Wearable Sensors in Huntington Disease: A Pilot Study.

PubMed

Andrzejewski, Kelly L; Dowling, Ariel V; Stamler, David; Felong, Timothy J; Harris, Denzil A; Wong, Cynthia; Cai, Hang; Reilmann, Ralf; Little, Max A; Gwin, Joseph T; Biglan, Kevin M; Dorsey, E Ray

2016-06-18

The Unified Huntington's Disease Rating Scale (UHDRS) is the principal means of assessing motor impairment in Huntington disease but is subjective and generally limited to in-clinic assessments. To evaluate the feasibility and ability of wearable sensors to measure motor impairment in individuals with Huntington disease in the clinic and at home. Participants with Huntington disease and controls were asked to wear five accelerometer-based sensors attached to the chest and each limb for standardized, in-clinic assessments and for one day at home. A second chest sensor was worn for six additional days at home. Gait measures were compared between controls, participants with Huntington disease, and participants with Huntington disease grouped by UHDRS total motor score using Cohen's d values. Fifteen individuals with Huntington disease and five controls completed the study. Sensor data were successfully captured from 18 of the 20 participants at home. In the clinic, the standard deviation of step time (time between consecutive steps) was increased in Huntington disease (p < 0.0001; Cohen's d = 2.61) compared to controls. At home with additional observations, significant differences were observed in seven additional gait measures. The gait of individuals with higher total motor scores (50 or more) differed significantly from those with lower total motor scores (below 50) on multiple measures at home. In this pilot study, the use of wearable sensors in clinic and at home was feasible and demonstrated gait differences between controls, participants with Huntington disease, and participants with Huntington disease grouped by motor impairment.

Stretchable, Twisted Conductive Microtubules for Wearable Computing, Robotics, Electronics, and Healthcare.

PubMed

Do, Thanh Nho; Visell, Yon

2017-05-11

Stretchable and flexible multifunctional electronic components, including sensors and actuators, have received increasing attention in robotics, electronics, wearable, and healthcare applications. Despite advances, it has remained challenging to design analogs of many electronic components to be highly stretchable, to be efficient to fabricate, and to provide control over electronic performance. Here, we describe highly elastic sensors and interconnects formed from thin, twisted conductive microtubules. These devices consist of twisted assemblies of thin, highly stretchable (>400%) elastomer tubules filled with liquid conductor (eutectic gallium indium, EGaIn), and fabricated using a simple roller coating process. As we demonstrate, these devices can operate as multimodal sensors for strain, rotation, contact force, or contact location. We also show that, through twisting, it is possible to control their mechanical performance and electronic sensitivity. In extensive experiments, we have evaluated the capabilities of these devices, and have prototyped an array of applications in several domains of stretchable and wearable electronics. These devices provide a novel, low cost solution for high performance stretchable electronics with broad applications in industry, healthcare, and consumer electronics, to emerging product categories of high potential economic and societal significance.

A Novel Method for Fabricating Wearable, Piezoresistive, and Pressure Sensors Based on Modified-Graphite/Polyurethane Composite Films

PubMed Central

He, Yin; Li, Wei; Yang, Guilin; Liu, Hao; Lu, Junyu; Zheng, Tongtong; Li, Xiaojiu

2017-01-01

A wearable, low-cost, highly repeatable piezoresistive sensor was fabricated by the synthesis of modified-graphite and polyurethane (PU) composites and polydimethylsiloxane (PDMS). Graphite sheets functionalized by using a silane coupling agent (KH550) were distributed in PU/N,N-dimethylformamide (DMF) solution, which were then molded to modified-graphite/PU (MG/PU) composite films. Experimental results show that with increasing modified-graphite content, the tensile strength of the MG/PU films first increased and then decreased, and the elongation at break of the composite films showed a decreasing trend. The electrical conductivity of the composite films can be influenced by filler modification and concentration, and the percolation threshold of MG/PU was 28.03 wt %. Under liner uniaxial compression, the 30 wt % MG/PU composite films exhibited 0.274 kPa−1 piezoresistive sensitivity within the range of low pressure, and possessed better stability and hysteresis. The flexible MG/PU composite piezoresistive sensors have great potential for body motion, wearable devices for human healthcare, and garment pressure testing. PMID:28773047

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

Two-Dimensional Atomic-Layered Alloy Junctions for High-Performance Wearable Chemical Sensor.

PubMed

Cho, Byungjin; Kim, Ah Ra; Kim, Dong Jae; Chung, Hee-Suk; Choi, Sun Young; Kwon, Jung-Dae; Park, Sang Won; Kim, Yonghun; Lee, Byoung Hun; Lee, Kyu Hwan; Kim, Dong-Ho; Nam, Jaewook; Hahm, Myung Gwan

2016-08-03

We first report that two-dimensional (2D) metal (NbSe2)-semiconductor (WSe2)-based flexible, wearable, and launderable gas sensors can be prepared through simple one-step chemical vapor deposition of prepatterned WO3 and Nb2O5. Compared to a control device with a Au/WSe2 junction, gas-sensing performance of the 2D NbSe2/WSe2 device was significantly enhanced, which might have resulted from the formation of a NbxW1-xSe2 transition alloy junction lowering the Schottky barrier height. This would make it easier to collect charges of channels induced by molecule adsorption, improving gas response characteristics toward chemical species including NO2 and NH3. 2D NbSe2/WSe2 devices on a flexible substrate provide gas-sensing properties with excellent durability under harsh bending. Furthermore, the device stitched on a T-shirt still performed well even after conventional cleaning with a laundry machine, enabling wearable and launderable chemical sensors. These results could pave a road toward futuristic gas-sensing platforms based on only 2D materials.

An integrated biomedical telemetry system for sleep monitoring employing a portable body area network of sensors (SENSATION).

PubMed

Astaras, Alexander; Arvanitidou, Marina; Chouvarda, Ioanna; Kilintzis, Vassilis; Koutkias, Vassilis; Sanchez, Eduardo Monton; Stalidis, George; Triantafyllidis, Andreas; Maglaveras, Nicos

2008-01-01

A flexible, scaleable and cost-effective medical telemetry system is described for monitoring sleep-related disorders in the home environment. The system was designed and built for real-time data acquisition and processing, allowing for additional use in intensive care unit scenarios where rapid medical response is required in case of emergency. It comprises a wearable body area network of Zigbee-compatible wireless sensors worn by the subject, a central database repository residing in the medical centre and thin client workstations located at the subject's home and in the clinician's office. The system supports heterogeneous setup configurations, involving a variety of data acquisition sensors to suit several medical applications. All telemetry data is securely transferred and stored in the central database under the clinicians' ownership and control.

Motor Impairment Evaluation for Upper Limb in Stroke Patients on the Basis of a Microsensor

ERIC Educational Resources Information Center

Huang, Shuai; Luo, Chun; Ye, Shiwei; Liu, Fei; Xie, Bin; Wang, Caifeng; Yang, Li; Huang, Zhen; Wu, Jiankang

2012-01-01

There has been an urgent need for an effective and efficient upper limb rehabilitation method for poststroke patients. We present a Micro-Sensor-based Upper Limb rehabilitation System for poststroke patients. The wearable motion capture units are attached to upper limb segments embedded in the fabric of garments. The body segment orientation…

Nanoalloy Printed and Pulse-Laser Sintered Flexible Sensor Devices with Enhanced Stability and Materials Compatibility

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

Zhao, Wei; Rovore, Thomas; Weerawarne, Darshana

2015-06-02

While conformal and wearable devices have become one of the most desired formats for printable electronics, it is challenging to establish a scalable process that produces stable conductive patterns but also uses substrates compatible with widely available wearable materials. Here, we describe findings of an investigation of a nanoalloy ink printed and pulsed laser sintered conductive patterns as flexible functional devices with enhanced stability and materials compatibility. While nanoparticle inks are desired for printable electronics, almost all existing nanoparticle inks are based on single-metal component, which, as an electronic element, is limited by its inherent stabilities of the metal suchmore » as propensity of metal oxidation and mobility of metal ions, especially in sintering processes. The work here has demonstrated the first example in exploiting plasmonic coupling of nanoalloys and pulsed-laser energy with controllable thermal penetration. The experimental and theoretical results have revealed clear correlation between the pulsed laser parameters and the nanoalloy structural characteristics. The superior performance of the resulting flexible sensor device, upon imparting nanostructured sensing materials, for detecting volatile organic compounds has significant implications to developing stable and wearable sensors for monitoring environmental pollutants and breath biomarkers. This simple “nanoalloy printing 'laser sintering' nanostructure printing” process is entirely general to many different sensor devices and nanostructured sensing materials, enabling the ability to easily construct sophisticated sensor array.« less

Nanoalloy Printed and Pulse-Laser Sintered Flexible Sensor Devices with Enhanced Stability and Materials Compatibility.

PubMed

Zhao, Wei; Rovere, Thomas; Weerawarne, Darshana; Osterhoudt, Gavin; Kang, Ning; Joseph, Pharrah; Luo, Jin; Shim, Bonggu; Poliks, Mark; Zhong, Chuan-Jian

2015-06-23

While conformal and wearable devices have become one of the most desired formats for printable electronics, it is challenging to establish a scalable process that produces stable conductive patterns but also uses substrates compatible with widely available wearable materials. Here, we describe findings of an investigation of a nanoalloy ink printed and pulsed-laser sintered conductive patterns as flexible functional devices with enhanced stability and materials compatibility. While nanoparticle inks are desired for printable electronics, almost all existing nanoparticle inks are based on single-metal component, which, as an electronic element, is limited by its inherent stabilities of the metal such as propensity of metal oxidation and mobility of metal ions, especially in sintering processes. The work here has demonstrated the first example in exploiting plasmonic coupling of nanoalloys and pulsed-laser energy with controllable thermal penetration. The experimental and theoretical results have revealed clear correlation between the pulsed laser parameters and the nanoalloy structural characteristics. The superior performance of the resulting flexible sensor device, upon imparting nanostructured sensing materials, for detecting volatile organic compounds has significant implications to developing stable and wearable sensors for monitoring environmental pollutants and breath biomarkers. This simple "nanoalloy printing-laser sintering-nanostructure printing" process is entirely general to many different sensor devices and nanostructured sensing materials, enabling the ability to easily construct sophisticated sensor array.

Design and test of a hybrid foot force sensing and GPS system for richer user mobility activity recognition.

PubMed

Zhang, Zelun; Poslad, Stefan

2013-11-01

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals.

Electronic Noses for Well-Being: Breath Analysis and Energy Expenditure

PubMed Central

Gardner, Julian W.; Vincent, Timothy A.

2016-01-01

The wealth of information concealed in a single human breath has been of interest for many years, promising not only disease detection, but also the monitoring of our general well-being. Recent developments in the fields of nano-sensor arrays and MEMS have enabled once bulky artificial olfactory sensor systems, or so-called “electronic noses”, to become smaller, lower power and portable devices. At the same time, wearable health monitoring devices are now available, although reliable breath sensing equipment is somewhat missing from the market of physical, rather than chemical sensor gadgets. In this article, we report on the unprecedented rise in healthcare problems caused by an increasingly overweight population. We first review recently-developed electronic noses for the detection of diseases by the analysis of basic volatile organic compounds (VOCs). Then, we discuss the primary cause of obesity from over eating and the high calorific content of food. We present the need to measure our individual energy expenditure from our exhaled breath. Finally, we consider the future for handheld or wearable devices to measure energy expenditure; and the potential of these devices to revolutionize healthcare, both at home and in hospitals. PMID:27347946

Electromagnetic disturbances rejection with single skin contact in the context of ECG measurements with cooperative sensors.

PubMed

Rapin, M; Ferrario, D; Haenni, E; Wacker, J; Falhi, A; Meier, C; Porchet, J-A; Chetelat, O

2017-07-01

Classical approaches to make high-quality measurements of biopotential signals require the use of shielded or multi-wire cables connecting the electrodes to a central unit in a star arrangement. Consequently, increasing the number of leads increases cabling and connector complexity which is not only limiting patient comfort but also anticipated as the main limiting factor for future miniaturization and cost reduction of tomorrow's wearables. We have recently introduced a novel sensing architecture that significantly reduces cabling complexity by eliminating shielded or multi-wire cables as well as by allowing simple connectors thanks to a bus arrangement. In this architecture, electrodes are replaced by so-called cooperative sensors. However, in this design, one of the cooperative sensors needs to be equipped with two contacts with the skin for proper common mode rejection, thus making its miniaturization problematic. This paper presents a novel common mode rejection principle which overcomes this limitation. When compared to others, the suggested approach is advantageous as it keeps the cabling complexity to its minimum. First measurements demonstrated in a real-life scenario the feasibility of this common mode rejection principle for a wearable 12-lead electrocardiogram monitoring system.

Influence of the UV radiation on the screen-printed pH-sensitive layers based on graphene and ruthenium dioxide

NASA Astrophysics Data System (ADS)

Pepłowski, A.; Grudziński, D.; Raczyński, T.; Wróblewski, G.; Janczak, D.; Jakubowska, M.

2017-08-01

Electrodes for measuring pH of the solution were fabricated by the means of screen-printing technology. Potentiometric sensors' layers comprised of composite with polymer matrix and graphene nanoplatelets/ruthenium (IV) oxide nanopowder as functional phase. Transceivers were printed on the elastic PMMA foil. Regarding potential application of the sensors in the wearable devices, dynamic response of the electrodes to changing ultraviolet radiation levels was assessed, since RuO2 is reported to be UV-sensitive. Observed changes of the electrodes' potential were of sub-millivolt magnitude, being comparable to simultaneously observed signal drift. Given this stability under varying UV conditions and previously verified good flexibility, fabricated sensors meet the requirements for wearable applications.

Home geriatric physiological measurements.

PubMed

Tamura, Toshiyo

2012-10-01

In an ageing society, the elderly can be monitored with numerous physiological, physical and passive devices. Sensors can be installed in the home for continuous mobility assistance and unobtrusive disease prevention. This review presents several modern sensors, which improve the quality of life and assist the elderly, disabled people and their caregivers. The main concept of geriatric sensors is that they are capable of providing assistance without limiting or disturbing the subject's daily routine, giving him or her greater comfort, pleasure and well-being. Furthermore, this review includes associated technologies of wearable/implantable monitoring systems and the 'smart-house' project. This review concludes by discussing future challenges of the future aged society.

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.

A wearable sensor based on CLYC scintillators

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

McDonald, Benjamin S.; Myjak, Mitchell J.; Zalavadia, Mital A.

We developed a wearable radiation sensor using Cs 2LiYCl 6:Ce (CLYC) for simultaneous gamma-ray and neutron detection. The system includes two ø2.5×2.5 cm 3 crystals coupled to small, metal-body photomultiplier tubes. A custom, low-power electronics base digitizes the output signal at three time points and enables both pulse height and pulse shape discrimination of neutrons and gamma-rays. Data, including spectra, can be transferred via a wired or wireless connection. The total gamma-ray and neutron counts, anomaly detection metrics, and identified isotopes are displayed on a small screen on the device. Users may leave the system in unattended mode to collectmore » long-dwell energy spectra. The prototype system has overall dimensions of 13×7.5×18 cm 3 and weight of 1.3 kg, not including the protective pouch, and runs on six AA alkaline batteries for 29 hours with a 1% wireless transmission duty cycle and 41 hours with the wireless turned off . In this paper, we summarize the system design and present characterization results from the detector modules. The energy resolution is about 6.5% full width at half maximum at 662 keV due to the small photomultiplier tube selected, and the linearity and pulse shape discrimination performance are very good.« less

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

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).

Sensing textile seam-line for wearable multimodal physiological monitoring.

PubMed

McKnight, M; Agcayazi, T; Kausche, H; Ghosh, T; Bozkurt, A

2016-08-01

This paper investigates a novel multimodal sensing method by forming seam-lines of conductive textile fibers into commercially available fabrics. The proposed ultra-low cost micro-electro-mechanical sensor would provide, wearable, flexible, textile based biopotential signal recording, wetness detection and tactile sensing simultaneously. Three types of fibers are evaluated for their array-based sensing capability, including a 3D printed conductive fiber, a multiwall carbon nanotube based fiber, and a commercially available stainless steel conductive thread. The sensors were shown to have a correlation between capacitance and pressure; impedance and wetness; and recorded potential and ECG waveforms.

Wearable-Sensor-Based Classification Models of Faller Status in Older Adults.

PubMed

Howcroft, Jennifer; Lemaire, Edward D; Kofman, Jonathan

2016-01-01

Wearable sensors have potential for quantitative, gait-based, point-of-care fall risk assessment that can be easily and quickly implemented in clinical-care and older-adult living environments. This investigation generated models for wearable-sensor based fall-risk classification in older adults and identified the optimal sensor type, location, combination, and modelling method; for walking with and without a cognitive load task. A convenience sample of 100 older individuals (75.5 ± 6.7 years; 76 non-fallers, 24 fallers based on 6 month retrospective fall occurrence) walked 7.62 m under single-task and dual-task conditions while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, and left and right shanks. Participants also completed the Activities-specific Balance Confidence scale, Community Health Activities Model Program for Seniors questionnaire, six minute walk test, and ranked their fear of falling. Fall risk classification models were assessed for all sensor combinations and three model types: multi-layer perceptron neural network, naïve Bayesian, and support vector machine. The best performing model was a multi-layer perceptron neural network with input parameters from pressure-sensing insoles and head, pelvis, and left shank accelerometers (accuracy = 84%, F1 score = 0.600, MCC score = 0.521). Head sensor-based models had the best performance of the single-sensor models for single-task gait assessment. Single-task gait assessment models outperformed models based on dual-task walking or clinical assessment data. Support vector machines and neural networks were the best modelling technique for fall risk classification. Fall risk classification models developed for point-of-care environments should be developed using support vector machines and neural networks, with a multi-sensor single-task gait assessment.

A Human Serum-Based Enzyme-Free Continuous Glucose Monitoring Technique Using a Needle-Type Bio-Layer Interference Sensor.

PubMed

Seo, Dongmin; Paek, Sung-Ho; Oh, Sangwoo; Seo, Sungkyu; Paek, Se-Hwan

2016-09-24

The incidence of diabetes is continually increasing, and by 2030, it is expected to have increased by 69% and 20% in underdeveloped and developed countries, respectively. Therefore, glucose sensors are likely to remain in high demand in medical device markets. For the current study, we developed a needle-type bio-layer interference (BLI) sensor that can continuously monitor glucose levels. Using dialysis procedures, we were able to obtain hypoglycemic samples from commercial human serum. These dialysis-derived samples, alongside samples of normal human serum were used to evaluate the utility of the sensor for the detection of the clinical interest range of glucose concentrations (70-200 mg/dL), revealing high system performance for a wide glycemic state range (45-500 mg/dL). Reversibility and reproducibility were also tested over a range of time spans. Combined with existing BLI system technology, this sensor holds great promise for use as a wearable online continuous glucose monitoring system for patients in a hospital setting.