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 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.

Methylxanthine Drug Monitoring with Wearable Sweat Sensors.

PubMed

Tai, Li-Chia; Gao, Wei; Chao, Minghan; Bariya, Mallika; Ngo, Quynh P; Shahpar, Ziba; Nyein, Hnin Y Y; Park, Hyejin; Sun, Junfeng; Jung, Younsu; Wu, Eric; Fahad, Hossain M; Lien, Der-Hsien; Ota, Hiroki; Cho, Gyoujin; Javey, Ali

2018-06-01

Drug monitoring plays crucial roles in doping control and precision medicine. It helps physicians tailor drug dosage for optimal benefits, track patients' compliance to prescriptions, and understand the complex pharmacokinetics of drugs. Conventional drug tests rely on invasive blood draws. While urine and sweat are attractive alternative biofluids, the state-of-the-art methods require separate sample collection and processing steps and fail to provide real-time information. Here, a wearable platform equipped with an electrochemical differential pulse voltammetry sensing module for drug monitoring is presented. A methylxanthine drug, caffeine, is selected to demonstrate the platform's functionalities. Sweat caffeine levels are monitored under various conditions, such as drug doses and measurement time after drug intake. Elevated sweat caffeine levels upon increasing dosage and confirmable caffeine physiological trends are observed. This work leverages a wearable sweat sensing platform toward noninvasive and continuous point-of-care drug monitoring and management. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Wearable Textile Platform for Assessing Stroke Patient Treatment in Daily Life Conditions

PubMed Central

Lorussi, Federico; Carbonaro, Nicola; De Rossi, Danilo; Paradiso, Rita; Veltink, Peter; Tognetti, Alessandro

2016-01-01

Monitoring physical activities during post-stroke rehabilitation in daily life may help physicians to optimize and tailor the training program for patients. The European research project INTERACTION (FP7-ICT-2011-7-287351) evaluated motor capabilities in stroke patients during the recovery treatment period. We developed wearable sensing platform based on the sensor fusion among inertial, knitted piezoresistive sensors and textile EMG electrodes. The device was conceived in modular form and consists of a separate shirt, trousers, glove, and shoe. Thanks to the novel fusion approach it has been possible to develop a model for the shoulder taking into account the scapulo-thoracic joint of the scapular girdle, considerably improving the estimation of the hand position in reaching activities. In order to minimize the sensor set used to monitor gait, a single inertial sensor fused with a textile goniometer proved to reconstruct the orientation of all the body segments of the leg. Finally, the sensing glove, endowed with three textile goniometers and three force sensors showed good capabilities in the reconstruction of grasping activities and evaluating the interaction of the hand with the environment, according to the project specifications. This paper reports on the design and the technical evaluation of the performance of the sensing platform, tested on healthy subjects. PMID:27047939

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

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.

A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices.

PubMed

Ravi, Daniele; Wong, Charence; Lo, Benny; Yang, Guang-Zhong

2017-01-01

The increasing popularity of wearable devices in recent years means that a diverse range of physiological and functional data can now be captured continuously for applications in sports, wellbeing, and healthcare. This wealth of information requires efficient methods of classification and analysis where deep learning is a promising technique for large-scale data analytics. While deep learning has been successful in implementations that utilize high-performance computing platforms, its use on low-power wearable devices is limited by resource constraints. In this paper, we propose a deep learning methodology, which combines features learned from inertial sensor data together with complementary information from a set of shallow features to enable accurate and real-time activity classification. The design of this combined method aims to overcome some of the limitations present in a typical deep learning framework where on-node computation is required. To optimize the proposed method for real-time on-node computation, spectral domain preprocessing is used before the data are passed onto the deep learning framework. The classification accuracy of our proposed deep learning approach is evaluated against state-of-the-art methods using both laboratory and real world activity datasets. Our results show the validity of the approach on different human activity datasets, outperforming other methods, including the two methods used within our combined pipeline. We also demonstrate that the computation times for the proposed method are consistent with the constraints of real-time on-node processing on smartphones and a wearable sensor platform.

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.

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.

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.

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.

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.

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.

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.

Ubiquitous Computing for Remote Cardiac Patient Monitoring: A Survey

PubMed Central

Kumar, Sunil; Kambhatla, Kashyap; Hu, Fei; Lifson, Mark; Xiao, Yang

2008-01-01

New wireless technologies, such as wireless LAN and sensor networks, for telecardiology purposes give new possibilities for monitoring vital parameters with wearable biomedical sensors, and give patients the freedom to be mobile and still be under continuous monitoring and thereby better quality of patient care. This paper will detail the architecture and quality-of-service (QoS) characteristics in integrated wireless telecardiology platforms. It will also discuss the current promising hardware/software platforms for wireless cardiac monitoring. The design methodology and challenges are provided for realistic implementation. PMID:18604301

Ubiquitous computing for remote cardiac patient monitoring: a survey.

PubMed

Kumar, Sunil; Kambhatla, Kashyap; Hu, Fei; Lifson, Mark; Xiao, Yang

2008-01-01

New wireless technologies, such as wireless LAN and sensor networks, for telecardiology purposes give new possibilities for monitoring vital parameters with wearable biomedical sensors, and give patients the freedom to be mobile and still be under continuous monitoring and thereby better quality of patient care. This paper will detail the architecture and quality-of-service (QoS) characteristics in integrated wireless telecardiology platforms. It will also discuss the current promising hardware/software platforms for wireless cardiac monitoring. The design methodology and challenges are provided for realistic implementation.

Increasing fall risk awareness using wearables: A fall risk awareness protocol.

PubMed

Danielsen, Asbjørn; Olofsen, Hans; Bremdal, Bernt Arild

2016-10-01

Each year about a third of elderly aged 65 or older experience a fall. Many of these falls may have been avoided if fall risk assessment and prevention tools where available in a daily living situation. We identify what kind of information is relevant for doing fall risk assessment and prevention using wearable sensors in a daily living environment by investigating current research, distinguishing between prospective and context-aware fall risk assessment and prevention. Based on our findings, we propose a fall risk awareness protocol as a fall prevention tool integrating both wearables and ambient sensing technology into a single platform. Copyright © 2016. Published by Elsevier Inc.

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).

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

Open source platform for collaborative construction of wearable sensor datasets for human motion analysis and an application for gait analysis.

PubMed

Llamas, César; González, Manuel A; Hernández, Carmen; Vegas, Jesús

2016-10-01

Nearly every practical improvement in modeling human motion is well founded in a properly designed collection of data or datasets. These datasets must be made publicly available for the community could validate and accept them. It is reasonable to concede that a collective, guided enterprise could serve to devise solid and substantial datasets, as a result of a collaborative effort, in the same sense as the open software community does. In this way datasets could be complemented, extended and expanded in size with, for example, more individuals, samples and human actions. For this to be possible some commitments must be made by the collaborators, being one of them sharing the same data acquisition platform. In this paper, we offer an affordable open source hardware and software platform based on inertial wearable sensors in a way that several groups could cooperate in the construction of datasets through common software suitable for collaboration. Some experimental results about the throughput of the overall system are reported showing the feasibility of acquiring data from up to 6 sensors with a sampling frequency no less than 118Hz. Also, a proof-of-concept dataset is provided comprising sampled data from 12 subjects suitable for gait analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Enabling breakthroughs in Parkinson’s disease with wearable technologies and big data analytics

PubMed Central

Cohen, Shahar; Martig, Adria K.

2016-01-01

Parkinson’s disease (PD) is a progressive, degenerative disorder of the central nervous system that is diagnosed and measured clinically by the Unified Parkinson’s Disease Rating Scale (UPDRS). Tools for continuous and objective monitoring of PD motor symptoms are needed to complement clinical assessments of symptom severity to further inform PD therapeutic development across several arenas, from developing more robust clinical trial outcome measures to establishing biomarkers of disease progression. The Michael J. Fox Foundation for Parkinson’s Disease Research and Intel Corporation have joined forces to develop a mobile application and an Internet of Things (IoT) platform to support large-scale studies of objective, continuously sampled sensory data from people with PD. This platform provides both population and per-patient analyses, measuring gait, activity level, nighttime activity, tremor, as well as other structured assessments and tasks. All data collected will be available to researchers on an open-source platform. Development of the IoT platform raised a number of engineering considerations, including wearable sensor choice, data management and curation, and algorithm validation. This project has successfully demonstrated proof of concept that IoT platforms, wearable technologies and the data they generate offer exciting possibilities for more robust, reliable, and low-cost research methodologies and patient care strategies. PMID:28293596

Enabling breakthroughs in Parkinson's disease with wearable technologies and big data analytics.

PubMed

Cohen, Shahar; Bataille, Lauren R; Martig, Adria K

2016-01-01

Parkinson's disease (PD) is a progressive, degenerative disorder of the central nervous system that is diagnosed and measured clinically by the Unified Parkinson's Disease Rating Scale (UPDRS). Tools for continuous and objective monitoring of PD motor symptoms are needed to complement clinical assessments of symptom severity to further inform PD therapeutic development across several arenas, from developing more robust clinical trial outcome measures to establishing biomarkers of disease progression. The Michael J. Fox Foundation for Parkinson's Disease Research and Intel Corporation have joined forces to develop a mobile application and an Internet of Things (IoT) platform to support large-scale studies of objective, continuously sampled sensory data from people with PD. This platform provides both population and per-patient analyses, measuring gait, activity level, nighttime activity, tremor, as well as other structured assessments and tasks. All data collected will be available to researchers on an open-source platform. Development of the IoT platform raised a number of engineering considerations, including wearable sensor choice, data management and curation, and algorithm validation. This project has successfully demonstrated proof of concept that IoT platforms, wearable technologies and the data they generate offer exciting possibilities for more robust, reliable, and low-cost research methodologies and patient care strategies.

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

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 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.

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.

Plug-and-play web-based visualization of mobile air monitoring data

EPA Science Inventory

The collection of air measurements in real-time on moving platforms, such as wearable, bicycle-mounted, or vehicle-mounted air sensors, is becoming an increasingly common method to investigate local air quality. However, visualizing and analyzing geospatial air monitoring data r...

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.

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

PubMed

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

2011-01-01

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

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

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.

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

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.

Mobile health: the power of wearables, sensors, and apps to transform clinical trials.

PubMed

Munos, Bernard; Baker, Pamela C; Bot, Brian M; Crouthamel, Michelle; de Vries, Glen; Ferguson, Ian; Hixson, John D; Malek, Linda A; Mastrototaro, John J; Misra, Veena; Ozcan, Aydogan; Sacks, Leonard; Wang, Pei

2016-07-01

Mobile technology has become a ubiquitous part of everyday life, and the practical utility of mobile devices for improving human health is only now being realized. Wireless medical sensors, or mobile biosensors, are one such technology that is allowing the accumulation of real-time biometric data that may hold valuable clues for treating even some of the most devastating human diseases. From wearable gadgets to sophisticated implantable medical devices, the information retrieved from mobile technology has the potential to revolutionize how clinical research is conducted and how disease therapies are delivered in the coming years. Encompassing the fields of science and engineering, analytics, health care, business, and government, this report explores the promise that wearable biosensors, along with integrated mobile apps, hold for improving the quality of patient care and clinical outcomes. The discussion focuses on groundbreaking device innovation, data optimization and validation, commercial platform integration, clinical implementation and regulation, and the broad societal implications of using mobile health technologies. © 2016 New York Academy of Sciences.

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.

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 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.

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

Nanomaterial-Enabled Wearable Sensors for Healthcare.

PubMed

Yao, Shanshan; Swetha, Puchakayala; Zhu, Yong

2018-01-01

Highly sensitive wearable sensors that can be conformably attached to human skin or integrated with textiles to monitor the physiological parameters of human body or the surrounding environment have garnered tremendous interest. Owing to the large surface area and outstanding material properties, nanomaterials are promising building blocks for wearable sensors. Recent advances in the nanomaterial-enabled wearable sensors including temperature, electrophysiological, strain, tactile, electrochemical, and environmental sensors are presented in this review. Integration of multiple sensors for multimodal sensing and integration with other components into wearable systems are summarized. Representative applications of nanomaterial-enabled wearable sensors for healthcare, including continuous health monitoring, daily and sports activity tracking, and multifunctional electronic skin are highlighted. Finally, challenges, opportunities, and future perspectives in the field of nanomaterial-enabled wearable sensors are discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Wearable sensors for health monitoring

NASA Astrophysics Data System (ADS)

Suciu, George; Butca, Cristina; Ochian, Adelina; Halunga, Simona

2015-02-01

In this paper we describe several wearable sensors, designed for monitoring the health condition of the patients, based on an experimental model. Wearable sensors enable long-term continuous physiological monitoring, which is important for the treatment and management of many chronic illnesses, neurological disorders, and mental health issues. The system is based on a wearable sensors network, which is connected to a computer or smartphone. The wearable sensor network integrates several wearable sensors that can measure different parameters such as body temperature, heart rate and carbon monoxide quantity from the air. After the portable sensors measuring parameter values, they are transmitted by microprocessor through the Bluetooth to the application developed on computer or smartphone, to be interpreted.

A wireless energy transfer platform, integrated at the bedside.

PubMed

De Clercq, Hans; Puers, Robert

2013-01-01

This paper presents the design of a wireless energy transfer platform, integrated at the bedside. The system contains a matrix of identical inductive power transmitters, which are optimised to provide power to a wearable sensor network, with the purpose of wirelessly recording vital signals over an extended period of time. The magnetic link, operates at a transfer frequency of 6.78MHz and is able to transfer a power of 3.3mW to the remote side at an inter-coil distance of 100mm. The total efficiency of the power link is 26%. Moreover, the platform is able to dynamically determine the position of freely moving sensor nodes and selectively induce a magnetic field in the area where the sensor nodes are positioned. As a result, the patient will not be subjected to unnecessary radiation and the specific absorption rate standards are met more easily.

Real-Time Geospatial Data Viewer (RETIGO): Web-Based Tool for Researchers and Citizen Scientists to Explore their Air Measurements

EPA Science Inventory

The collection of air measurements in real-time on moving platforms, such as wearable, bicycle-mounted, or vehicle-mounted air sensors, is becoming an increasingly common method to investigate local air quality. However, visualizing and analyzing geospatial air monitoring data re...

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.

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.

Improved response time of flexible microelectromechanical sensors employing eco-friendly nanomaterials.

PubMed

Fan, Shicheng; Dan, Li; Meng, Lingju; Zheng, Wei; Elias, Anastasia; Wang, Xihua

2017-11-09

Flexible force/pressure sensors are of interest for academia and industry and have applications in wearable technologies. Most of such sensors on the market or reported in journal publications are based on the operation mechanism of probing capacitance or resistance changes of the materials under pressure. Recently, we reported the microelectromechanical (MEM) sensors based on a different mechanism: mechanical switches. Multiples of such MEM sensors can be integrated to achieve the same function of regular force/pressure sensors while having the advantages of ease of fabrication and long-term stability in operation. Herein, we report the dramatically improved response time (more than one order of magnitude) of these MEM sensors by employing eco-friendly nanomaterials-cellulose nanocrystals. For instance, the incorporation of polydimethysiloxane filled with cellulose nanocrystals shortened the response time of MEM sensors from sub-seconds to several milliseconds, leading to the detection of both diastolic and systolic pressures in the radial arterial blood pressure measurement. Comprehensive mechanical and electrical characterization of the materials and the devices reveal that greatly enhanced storage modulus and loss modulus play key roles in this improved response time. The demonstrated fast-response flexible sensors enabled continuous monitoring of heart rate and complex cardiovascular signals using pressure sensors for future wearable sensing platforms.

Nanopaper as an Optical Sensing Platform.

PubMed

Morales-Narváez, Eden; Golmohammadi, Hamed; Naghdi, Tina; Yousefi, Hossein; Kostiv, Uliana; Horák, Daniel; Pourreza, Nahid; Merkoçi, Arben

2015-07-28

Bacterial cellulose nanopaper (BC) is a multifunctional material known for numerous desirable properties: sustainability, biocompatibility, biodegradability, optical transparency, thermal properties, flexibility, high mechanical strength, hydrophilicity, high porosity, broad chemical-modification capabilities and high surface area. Herein, we report various nanopaper-based optical sensing platforms and describe how they can be tuned, using nanomaterials, to exhibit plasmonic or photoluminescent properties that can be exploited for sensing applications. We also describe several nanopaper configurations, including cuvettes, plates and spots that we printed or punched on BC. The platforms include a colorimetric-based sensor based on nanopaper containing embedded silver and gold nanoparticles; a photoluminescent-based sensor, comprising CdSe@ZnS quantum dots conjugated to nanopaper; and a potential up-conversion sensing platform constructed from nanopaper functionalized with NaYF4:Yb(3+)@Er(3+)&SiO2 nanoparticles. We have explored modulation of the plasmonic or photoluminescent properties of these platforms using various model biologically relevant analytes. Moreover, we prove that BC is and advantageous preconcentration platform that facilitates the analysis of small volumes of optically active materials (∼4 μL). We are confident that these platforms will pave the way to optical (bio)sensors or theranostic devices that are simple, transparent, flexible, disposable, lightweight, miniaturized and perhaps wearable.

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.

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.

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

PubMed

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

2017-07-01

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

Wearable sensors for human health monitoring

NASA Astrophysics Data System (ADS)

Asada, H. Harry; Reisner, Andrew

2006-03-01

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

A review of wearable sensors and systems with application in rehabilitation

PubMed Central

2012-01-01

The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed. PMID:22520559

What Does Big Data Mean for Wearable Sensor Systems?

PubMed Central

Lovell, N. H.; Yang, G. Z.; Horsch, A.; Lukowicz, P.; Murrugarra, L.; Marschollek, M.

2014-01-01

Summary Objectives The aim of this paper is to discuss how recent developments in the field of big data may potentially impact the future use of wearable sensor systems in healthcare. Methods The article draws on the scientific literature to support the opinions presented by the IMIA Wearable Sensors in Healthcare Working Group. Results The following is discussed: the potential for wearable sensors to generate big data; how complementary technologies, such as a smartphone, will augment the concept of a wearable sensor and alter the nature of the monitoring data created; how standards would enable sharing of data and advance scientific progress. Importantly, attention is drawn to statistical inference problems for which big datasets provide little assistance, or may hinder the identification of a useful solution. Finally, a discussion is presented on risks to privacy and possible negative consequences arising from intensive wearable sensor monitoring. Conclusions Wearable sensors systems have the potential to generate datasets which are currently beyond our capabilities to easily organize and interpret. In order to successfully utilize wearable sensor data to infer wellbeing, and enable proactive health management, standards and ontologies must be developed which allow for data to be shared between research groups and between commercial systems, promoting the integration of these data into health information systems. However, policy and regulation will be required to ensure that the detailed nature of wearable sensor data is not misused to invade privacies or prejudice against individuals. PMID:25123733

Wireless inertial measurement unit with GPS (WIMU-GPS)--wearable monitoring platform for ecological assessment of lifespace and mobility in aging and disease.

PubMed

Boissy, Patrick; Brière, Simon; Hamel, Mathieu; Jog, Mandar; Speechley, Mark; Karelis, Antony; Frank, James; Vincent, Claude; Edwards, Rodrick; Duval, Christian

2011-01-01

This paper proposes an innovative ambulatory mobility and activity monitoring approach based on a wearable datalogging platform that combines inertial sensing with GPS tracking to assess the lifespace and mobility profile of individuals in their home and community environments. The components, I/O architecture, sensors and functions of the WIMU-GPS are presented. Outcome variables that can be measured with it are described and illustrated. Data on the power usage, operating autonomy of the WIMU-GPS and the GPS tracking performances and time to first fix of the unit are presented. The study of lifespace and mobility with the WIMU-GPS can potentially provide unique insights into intrapersonal and environmental factors contributing to mobility restriction. On-going studies are underway to establish the validity and reliability of the WIMU-GPS in characterizing the lifespace and mobility profile of older adults.

Recent Progress of Self-Powered Sensing Systems for Wearable Electronics.

PubMed

Lou, Zheng; Li, La; Wang, Lili; Shen, Guozhen

2017-12-01

Wearable/flexible electronic sensing systems are considered to be one of the key technologies in the next generation of smart personal electronics. To realize personal portable devices with mobile electronics application, i.e., wearable electronic sensors that can work sustainably and continuously without an external power supply are highly desired. The recent progress and advantages of wearable self-powered electronic sensing systems for mobile or personal attachable health monitoring applications are presented. An overview of various types of wearable electronic sensors, including flexible tactile sensors, wearable image sensor array, biological and chemical sensor, temperature sensors, and multifunctional integrated sensing systems is provided. Self-powered sensing systems with integrated energy units are then discussed, separated as energy harvesting self-powered sensing systems, energy storage integrated sensing systems, and all-in-on integrated sensing systems. Finally, the future perspectives of self-powered sensing systems for wearable electronics are discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modification and fixed-point analysis of a Kalman filter for orientation estimation based on 9D inertial measurement unit data.

PubMed

Brückner, Hans-Peter; Spindeldreier, Christian; Blume, Holger

2013-01-01

A common approach for high accuracy sensor fusion based on 9D inertial measurement unit data is Kalman filtering. State of the art floating-point filter algorithms differ in their computational complexity nevertheless, real-time operation on a low-power microcontroller at high sampling rates is not possible. This work presents algorithmic modifications to reduce the computational demands of a two-step minimum order Kalman filter. Furthermore, the required bit-width of a fixed-point filter version is explored. For evaluation real-world data captured using an Xsens MTx inertial sensor is used. Changes in computational latency and orientation estimation accuracy due to the proposed algorithmic modifications and fixed-point number representation are evaluated in detail on a variety of processing platforms enabling on-board processing on wearable sensor platforms.

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.

Wearable sensor systems for infants.

PubMed

Zhu, Zhihua; Liu, Tao; Li, Guangyi; Li, Tong; Inoue, Yoshio

2015-02-05

Continuous health status monitoring of infants is achieved with the development and fusion of wearable sensing technologies, wireless communication techniques and a low energy-consumption microprocessor with high performance data processing algorithms. As a clinical tool applied in the constant monitoring of physiological parameters of infants, wearable sensor systems for infants are able to transmit the information obtained inside an infant's body to clinicians or parents. Moreover, such systems with integrated sensors can perceive external threats such as falling or drowning and warn parents immediately. Firstly, the paper reviews some available wearable sensor systems for infants; secondly, we introduce the different modules of the framework in the sensor systems; lastly, the methods and techniques applied in the wearable sensor systems are summarized and discussed. The latest research and achievements have been highlighted in this paper and the meaningful applications in healthcare and behavior analysis are also presented. Moreover, we give a lucid perspective of the development of wearable sensor systems for infants in the future.

Wearable Sensor Systems for Infants

PubMed Central

Zhu, Zhihua; Liu, Tao; Li, Guangyi; Li, Tong; Inoue, Yoshio

2015-01-01

Continuous health status monitoring of infants is achieved with the development and fusion of wearable sensing technologies, wireless communication techniques and a low energy-consumption microprocessor with high performance data processing algorithms. As a clinical tool applied in the constant monitoring of physiological parameters of infants, wearable sensor systems for infants are able to transmit the information obtained inside an infant's body to clinicians or parents. Moreover, such systems with integrated sensors can perceive external threats such as falling or drowning and warn parents immediately. Firstly, the paper reviews some available wearable sensor systems for infants; secondly, we introduce the different modules of the framework in the sensor systems; lastly, the methods and techniques applied in the wearable sensor systems are summarized and discussed. The latest research and achievements have been highlighted in this paper and the meaningful applications in healthcare and behavior analysis are also presented. Moreover, we give a lucid perspective of the development of wearable sensor systems for infants in the future. PMID:25664432

A Portable Wireless Communication Platform Based on a Multi-Material Fiber Sensor for Real-Time Breath Detection

PubMed Central

Bellemare-Rousseau, Simon; Khalil, Mazen; Messaddeq, Younes

2018-01-01

In this paper, we present a new mobile wireless communication platform for real-time monitoring of an individual’s breathing rate. The platform takes the form of a wearable stretching T-shirt featuring a sensor and a detection base station. The sensor is formed by a spiral-shaped antenna made from a multi-material fiber connected to a compact transmitter. Based on the resonance frequency of the antenna at approximately 2.4 GHz, the breathing sensor relies on its Bluetooth transmitter. The contactless and non-invasive sensor is designed without compromising the user’s comfort. The sensing mechanism of the system is based on the detection of the signal amplitude transmitted wirelessly by the sensor, which is found to be sensitive to strain. We demonstrate the capability of the platform to detect the breathing rates of four male volunteers who are not in movement. The breathing pattern is obtained through the received signal strength indicator (RSSI) which is filtered and analyzed with home-made algorithms in the portable system. Numerical simulations of human breath are performed to support the experimental detection, and both results are in a good agreement. Slow, fast, regular, irregular, and shallow breathing types are successfully recorded within a frequency interval of 0.16–1.2 Hz, leading to a breathing rate varying from 10 to 72 breaths per minute. PMID:29587396

A Portable Wireless Communication Platform Based on a Multi-Material Fiber Sensor for Real-Time Breath Detection.

PubMed

Roudjane, Mourad; Bellemare-Rousseau, Simon; Khalil, Mazen; Gorgutsa, Stepan; Miled, Amine; Messaddeq, Younes

2018-03-25

In this paper, we present a new mobile wireless communication platform for real-time monitoring of an individual's breathing rate. The platform takes the form of a wearable stretching T-shirt featuring a sensor and a detection base station. The sensor is formed by a spiral-shaped antenna made from a multi-material fiber connected to a compact transmitter. Based on the resonance frequency of the antenna at approximately 2.4 GHz, the breathing sensor relies on its Bluetooth transmitter. The contactless and non-invasive sensor is designed without compromising the user's comfort. The sensing mechanism of the system is based on the detection of the signal amplitude transmitted wirelessly by the sensor, which is found to be sensitive to strain. We demonstrate the capability of the platform to detect the breathing rates of four male volunteers who are not in movement. The breathing pattern is obtained through the received signal strength indicator (RSSI) which is filtered and analyzed with home-made algorithms in the portable system. Numerical simulations of human breath are performed to support the experimental detection, and both results are in a good agreement. Slow, fast, regular, irregular, and shallow breathing types are successfully recorded within a frequency interval of 0.16-1.2 Hz, leading to a breathing rate varying from 10 to 72 breaths per minute.

Sensible organizations: technology and methodology for automatically measuring organizational behavior.

PubMed

Olguin Olguin, Daniel; Waber, Benjamin N; Kim, Taemie; Mohan, Akshay; Ara, Koji; Pentland, Alex

2009-02-01

We present the design, implementation, and deployment of a wearable computing platform for measuring and analyzing human behavior in organizational settings. We propose the use of wearable electronic badges capable of automatically measuring the amount of face-to-face interaction, conversational time, physical proximity to other people, and physical activity levels in order to capture individual and collective patterns of behavior. Our goal is to be able to understand how patterns of behavior shape individuals and organizations. By using on-body sensors in large groups of people for extended periods of time in naturalistic settings, we have been able to identify, measure, and quantify social interactions, group behavior, and organizational dynamics. We deployed this wearable computing platform in a group of 22 employees working in a real organization over a period of one month. Using these automatic measurements, we were able to predict employees' self-assessments of job satisfaction and their own perceptions of group interaction quality by combining data collected with our platform and e-mail communication data. In particular, the total amount of communication was predictive of both of these assessments, and betweenness in the social network exhibited a high negative correlation with group interaction satisfaction. We also found that physical proximity and e-mail exchange had a negative correlation of r = -0.55 (p 0.01), which has far-reaching implications for past and future research on social networks.

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

PubMed

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

2010-01-01

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

Flexible wearable sensor nodes with solar energy harvesting.

PubMed

Taiyang Wu; Arefin, Md Shamsul; Redoute, Jean-Michel; Yuce, Mehmet Rasit

2017-07-01

Wearable sensor nodes have gained a lot of attention during the past few years as they can monitor and record people's physical parameters in real time. Wearable sensor nodes can promote healthy lifestyles and prevent the occurrence of potential illness or injuries. This paper presents a flexible wearable sensor system powered by an efficient solar energy harvesting technique. It can measure the subject's heartbeats using a photoplethysmography (PPG) sensor and perform activity monitoring using an accelerometer. The solar energy harvester adopts an output current based maximum power point tracking (MPPT) algorithm, which controls the solar panel to operate within its high output power range. The power consumption of the flexible sensor nodes has been investigated under different operation conditions. Experimental results demonstrate that wearable sensor nodes can work for more than 12 hours when they are powered by the solar energy harvester for 3 hours in the bright sunlight.

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.

Performance Evaluation of Wearable Sensor Systems: A Case Study in Moderate-Scale Deployment in Hospital Environment.

PubMed

Sun, Wen; Ge, Yu; Zhang, Zhiqiang; Wong, Wai-Choong

2015-09-25

A wearable sensor system enables continuous and remote health monitoring and is widely considered as the next generation of healthcare technology. The performance, the packet error rate (PER) in particular, of a wearable sensor system may deteriorate due to a number of factors, particularly the interference from the other wearable sensor systems in the vicinity. We systematically evaluate the performance of the wearable sensor system in terms of PER in the presence of such interference in this paper. The factors that affect the performance of the wearable sensor system, such as density, traffic load, and transmission power in a realistic moderate-scale deployment case in hospital are all considered. Simulation results show that with 20% duty cycle, only 68.5% of data transmission can achieve the targeted reliability requirement (PER is less than 0.05) even in the off-peak period in hospital. We then suggest some interference mitigation schemes based on the performance evaluation results in the case study.

A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition.

PubMed

Benatti, Simone; Casamassima, Filippo; Milosevic, Bojan; Farella, Elisabetta; Schönle, Philipp; Fateh, Schekeb; Burger, Thomas; Huang, Qiuting; Benini, Luca

2015-10-01

Wearable devices offer interesting features, such as low cost and user friendliness, but their use for medical applications is an open research topic, given the limited hardware resources they provide. In this paper, we present an embedded solution for real-time EMG-based hand gesture recognition. The work focuses on the multi-level design of the system, integrating the hardware and software components to develop a wearable device capable of acquiring and processing EMG signals for real-time gesture recognition. The system combines the accuracy of a custom analog front end with the flexibility of a low power and high performance microcontroller for on-board processing. Our system achieves the same accuracy of high-end and more expensive active EMG sensors used in applications with strict requirements on signal quality. At the same time, due to its flexible configuration, it can be compared to the few wearable platforms designed for EMG gesture recognition available on market. We demonstrate that we reach similar or better performance while embedding the gesture recognition on board, with the benefit of cost reduction. To validate this approach, we collected a dataset of 7 gestures from 4 users, which were used to evaluate the impact of the number of EMG channels, the number of recognized gestures and the data rate on the recognition accuracy and on the computational demand of the classifier. As a result, we implemented a SVM recognition algorithm capable of real-time performance on the proposed wearable platform, achieving a classification rate of 90%, which is aligned with the state-of-the-art off-line results and a 29.7 mW power consumption, guaranteeing 44 hours of continuous operation with a 400 mAh battery.

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 sweat detector device design for health monitoring and clinical diagnosis

NASA Astrophysics Data System (ADS)

Wu, Qiuchen; Zhang, Xiaodong; Tian, Bihao; Zhang, Hongyan; Yu, Yang; Wang, Ming

2017-06-01

Miniaturized sensor is necessary part for wearable detector for biomedical applications. Wearable detector device is indispensable for online health care. This paper presents a concept of an wearable digital health monitoring device design for sweat analysis. The flexible sensor is developed to quantify the amount of hydrogen ions in sweat and skin temperature in real time. The detection system includes pH sensor, temperature sensor, signal processing module, power source, microprocessor, display module and so on. The sweat monitoring device is designed for sport monitoring or clinical diagnosis.

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.

All-Printed Flexible and Stretchable Electronics.

PubMed

Mohammed, Mohammed G; Kramer, Rebecca

2017-05-01

A fully automated additive manufacturing process that produces all-printed flexible and stretchable electronics is demonstrated. The printing process combines soft silicone elastomer printing and liquid metal processing on a single high-precision 3D stage. The platform is capable of fabricating extremely complex conductive circuits, strain and pressure sensors, stretchable wires, and wearable circuits with high yield and repeatability. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Wireless chest wearable vital sign monitoring platform for hypertension.

PubMed

Janjua, G; Guldenring, D; Finlay, D; McLaughlin, J

2017-07-01

Hypertension, a silent killer, is the biggest challenge of the 21 st century in public health agencies worldwide [1]. World Health Organization (WHO) statistic shows that the mortality rate of hypertension is 9.4 million per year and causes 55.3% of total deaths in cardiovascular (CV) patients [2]. Early detection and prevention of hypertension can significantly reduce the CV mortality. We are presenting a wireless chest wearable vital sign monitoring platform. It measures Electrocardiogram (ECG), Photoplethsmogram (PPG) and Ballistocardiogram (BCG) signals and sends data over Bluetooth low energy (BLE) to mobile phone-acts as a gateway. A custom android application relays the data to thingspeak server where MATLAB based offline analysis estimates the blood pressure. A server reacts on the health of subject to friends & family on the social media - twitter. The chest provides a natural position for the sensor to capture legitimate signals for hypertension condition. We have done a clinical technical evaluation of prototypes on 11 normotensive subjects, 9 males 2 females.

Wearable salivary uric acid mouthguard biosensor with integrated wireless electronics.

PubMed

Kim, Jayoung; Imani, Somayeh; de Araujo, William R; Warchall, Julian; Valdés-Ramírez, Gabriela; Paixão, Thiago R L C; Mercier, Patrick P; Wang, Joseph

2015-12-15

This article demonstrates an instrumented mouthguard capable of non-invasively monitoring salivary uric acid (SUA) levels. The enzyme (uricase)-modified screen printed electrode system has been integrated onto a mouthguard platform along with anatomically-miniaturized instrumentation electronics featuring a potentiostat, microcontroller, and a Bluetooth Low Energy (BLE) transceiver. Unlike RFID-based biosensing systems, which require large proximal power sources, the developed platform enables real-time wireless transmission of the sensed information to standard smartphones, laptops, and other consumer electronics for on-demand processing, diagnostics, or storage. The mouthguard biosensor system offers high sensitivity, selectivity, and stability towards uric acid detection in human saliva, covering the concentration ranges for both healthy people and hyperuricemia patients. The new wireless mouthguard biosensor system is able to monitor SUA level in real-time and continuous fashion, and can be readily expanded to an array of sensors for different analytes to enable an attractive wearable monitoring system for diverse health and fitness applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Wearable salivary uric acid mouthguard biosensor with integrated wireless electronics

PubMed Central

Kim, Jayoung; Imani, Somayeh; de Araujo, William R.; Warchall, Julian; Valdés-Ramírez, Gabriela; Paixão, Thiago R.L.C.; Mercier, Patrick P.; Wang, Joseph

2016-01-01

This article demonstrates an instrumented mouthguard capable of non-invasively monitoring salivary uric acid (SUA) levels. The enzyme (uricase)-modified screen printed electrode system has been integrated onto a mouthguard platform along with anatomically-miniaturized instrumentation electronics featuring a potentiostat, microcontroller, and a Bluetooth Low Energy (BLE) transceiver. Unlike RFID-based biosensing systems, which require large proximal power sources, the developed platform enables real-time wireless transmission of the sensed information to standard smartphones, laptops, and other consumer electronics for on-demand processing, diagnostics, or storage. The mouthguard biosensor system offers high sensitivity, selectivity, and stability towards uric acid detection in human saliva, covering the concentration ranges for both healthy people and hyperuricemia patients. The new wireless mouthguard biosensor system is able to monitor SUA level in real-time and continuous fashion, and can be readily expanded to an array of sensors for different analytes to enable an attractive wearable monitoring system for diverse health and fitness applications. PMID:26276541

A wearable context aware system for ubiquitous healthcare.

PubMed

Kang, Dong-Oh; Lee, Hyung-Jik; Ko, Eun-Jung; Kang, Kyuchang; Lee, Jeunwoo

2006-01-01

Recent developments of information technologies are leading the advent of the era of ubiquitous healthcare, which means healthcare services at any time and at any places. The ubiquitous healthcare service needs a wearable system for more continual measurement of biological signals of a user, which gives information of the user from wearable sensors. In this paper, we propose a wearable context aware system for ubiquitous healthcare, and its systematic design process of a ubiquitous healthcare service. Some wearable sensor systems are introduced with Zigbee communication. We develop a context aware framework to send information from wearable sensors to healthcare service entities as a middleware to solve the interoperability problem between sensor makers and healthcare service providers. And, we propose a systematic process of design of ubiquitous healthcare services with the context aware framework. In order to show the feasibility of the proposed system, some application examples are given, which are applied to remote monitoring, and a self check service.

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

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.

Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches.

PubMed

Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

2015-09-08

As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.

Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches

PubMed Central

Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

2015-01-01

As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras. PMID:26370997

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

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

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators

PubMed Central

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Rossi, Camilla Baj; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-01-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine. PMID:26928456

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators

NASA Astrophysics Data System (ADS)

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Rossi, Camilla Baj; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-03-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine.

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators.

PubMed

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Baj Rossi, Camilla; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-03-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine.

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

Eyeglasses based wireless electrolyte and metabolite sensor platform.

PubMed

Sempionatto, Juliane R; Nakagawa, Tatsuo; Pavinatto, Adriana; Mensah, Samantha T; Imani, Somayeh; Mercier, Patrick; Wang, Joseph

2017-05-16

The demand for wearable sensors has grown rapidly in recent years, with increasing attention being given to epidermal chemical sensing. Here, we present the first example of a fully integrated eyeglasses wireless multiplexed chemical sensing platform capable of real-time monitoring of sweat electrolytes and metabolites. The new concept has been realized by integrating an amperometric lactate biosensor and a potentiometric potassium ion-selective electrode into the two nose-bridge pads of the glasses and interfacing them with a wireless electronic backbone placed on the glasses' arms. Simultaneous real-time monitoring of sweat lactate and potassium levels with no apparent cross-talk is demonstrated along with wireless signal transduction. The electrochemical sensors were screen-printed on polyethylene terephthalate (PET) stickers and placed on each side of the glasses' nose pads in order to monitor sweat metabolites and electrolytes. The electronic backbone on the arms of the glasses' frame offers control of the amperometric and potentiometric transducers and enables Bluetooth wireless data transmission to the host device. The new eyeglasses system offers an interchangeable-sensor feature in connection with a variety of different nose-bridge amperometric and potentiometric sensor stickers. For example, the lactate bridge-pad sensor was replaced with a glucose one to offer convenient monitoring of sweat glucose. Such a fully integrated wireless "Lab-on-a-Glass" multiplexed biosensor platform can be readily expanded for the simultaneous monitoring of additional sweat electrolytes and metabolites.

A Review of Wearable Sensor Systems for Monitoring Body Movements of Neonates

PubMed Central

Chen, Hongyu; Xue, Mengru; Mei, Zhenning; Bambang Oetomo, Sidarto; Chen, Wei

2016-01-01

Characteristics of physical movements are indicative of infants’ neuro-motor development and brain dysfunction. For instance, infant seizure, a clinical signal of brain dysfunction, could be identified and predicted by monitoring its physical movements. With the advance of wearable sensor technology, including the miniaturization of sensors, and the increasing broad application of micro- and nanotechnology, and smart fabrics in wearable sensor systems, it is now possible to collect, store, and process multimodal signal data of infant movements in a more efficient, more comfortable, and non-intrusive way. This review aims to depict the state-of-the-art of wearable sensor systems for infant movement monitoring. We also discuss its clinical significance and the aspect of system design. PMID:27983664

Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors.

PubMed

Yurtman, Aras; Barshan, Billur

2017-08-09

Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is of interest to develop wearable systems that operate invariantly to sensor position and orientation. We focus on invariance to sensor orientation and develop two alternative transformations to remove the effect of absolute sensor orientation from the raw sensor data. We test the proposed methodology in activity recognition with four state-of-the-art classifiers using five publicly available datasets containing various types of human activities acquired by different sensor configurations. While the ordinary activity recognition system cannot handle incorrectly oriented sensors, the proposed transformations allow the sensors to be worn at any orientation at a given position on the body, and achieve nearly the same activity recognition performance as the ordinary system for which the sensor units are not rotatable. The proposed techniques can be applied to existing wearable systems without much effort, by simply transforming the time-domain sensor data at the pre-processing stage.

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.

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

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.

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

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

PubMed

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

2017-11-30

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

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

A Method of Data Aggregation for Wearable Sensor Systems

PubMed Central

Shen, Bo; Fu, Jun-Song

2016-01-01

Data aggregation has been considered as an effective way to decrease the data to be transferred in sensor networks. Particularly for wearable sensor systems, smaller battery has less energy, which makes energy conservation in data transmission more important. Nevertheless, wearable sensor systems usually have features like frequently dynamic changes of topologies and data over a large range, of which current aggregating methods can’t adapt to the demand. In this paper, we study the system composed of many wearable devices with sensors, such as the network of a tactical unit, and introduce an energy consumption-balanced method of data aggregation, named LDA-RT. In the proposed method, we develop a query algorithm based on the idea of ‘happened-before’ to construct a dynamic and energy-balancing routing tree. We also present a distributed data aggregating and sorting algorithm to execute top-k query and decrease the data that must be transferred among wearable devices. Combining these algorithms, LDA-RT tries to balance the energy consumptions for prolonging the lifetime of wearable sensor systems. Results of evaluation indicate that LDA-RT performs well in constructing routing trees and energy balances. It also outperforms the filter-based top-k monitoring approach in energy consumption, load balance, and the network’s lifetime, especially for highly dynamic data sources. PMID:27347953

Estimation of ground reaction forces and joint moments on the basis on plantar pressure insoles and wearable sensors for joint angle measurement.

PubMed

Ostaszewski, Michal; Pauk, Jolanta

2018-05-16

Gait analysis is a useful tool medical staff use to support clinical decision making. There is still an urgent need to develop low-cost and unobtrusive mobile health monitoring systems. The goal of this study was twofold. Firstly, a wearable sensor system composed of plantar pressure insoles and wearable sensors for joint angle measurement was developed. Secondly, the accuracy of the system in the measurement of ground reaction forces and joint moments was examined. The measurements included joint angles and plantar pressure distribution. To validate the wearable sensor system and examine the effectiveness of the proposed method for gait analysis, an experimental study on ten volunteer subjects was conducted. The accuracy of measurement of ground reaction forces and joint moments was validated against the results obtained from a reference motion capture system. Ground reaction forces and joint moments measured by the wearable sensor system showed a root mean square error of 1% for min. GRF and 27.3% for knee extension moment. The correlation coefficient was over 0.9, in comparison with the stationary motion capture system. The study suggests that the wearable sensor system could be recommended both for research and clinical applications outside a typical gait laboratory.

Mobile voice health monitoring using a wearable accelerometer sensor and a smartphone platform.

PubMed

Mehta, Daryush D; Zañartu, Matías; Feng, Shengran W; Cheyne, Harold A; Hillman, Robert E

2012-11-01

Many common voice disorders are chronic or recurring conditions that are likely to result from faulty and/or abusive patterns of vocal behavior, referred to generically as vocal hyperfunction. An ongoing goal in clinical voice assessment is the development and use of noninvasively derived measures to quantify and track the daily status of vocal hyperfunction so that the diagnosis and treatment of such behaviorally based voice disorders can be improved. This paper reports on the development of a new, versatile, and cost-effective clinical tool for mobile voice monitoring that acquires the high-bandwidth signal from an accelerometer sensor placed on the neck skin above the collarbone. Using a smartphone as the data acquisition platform, the prototype device provides a user-friendly interface for voice use monitoring, daily sensor calibration, and periodic alert capabilities. Pilot data are reported from three vocally normal speakers and three subjects with voice disorders to demonstrate the potential of the device to yield standard measures of fundamental frequency and sound pressure level and model-based glottal airflow properties. The smartphone-based platform enables future clinical studies for the identification of the best set of measures for differentiating between normal and hyperfunctional patterns of voice use.

Mobile voice health monitoring using a wearable accelerometer sensor and a smartphone platform

PubMed Central

Mehta, Daryush D.; Zañartu, Matías; Feng, Shengran W.; Cheyne, Harold A.; Hillman, Robert E.

2012-01-01

Many common voice disorders are chronic or recurring conditions that are likely to result from faulty and/or abusive patterns of vocal behavior, referred to generically as vocal hyperfunction. An ongoing goal in clinical voice assessment is the development and use of noninvasively derived measures to quantify and track the daily status of vocal hyperfunction so that the diagnosis and treatment of such behaviorally based voice disorders can be improved. This paper reports on the development of a new, versatile, and cost-effective clinical tool for mobile voice monitoring that acquires the high-bandwidth signal from an accelerometer sensor placed on the neck skin above the collarbone. Using a smartphone as the data acquisition platform, the prototype device provides a user-friendly interface for voice use monitoring, daily sensor calibration, and periodic alert capabilities. Pilot data are reported from three vocally normal speakers and three subjects with voice disorders to demonstrate the potential of the device to yield standard measures of fundamental frequency and sound pressure level and model-based glottal airflow properties. The smartphone-based platform enables future clinical studies for the identification of the best set of measures for differentiating between normal and hyperfunctional patterns of voice use. PMID:22875236

The mid-IR silicon photonics sensor platform (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kimerling, Lionel; Hu, Juejun; Agarwal, Anuradha M.

2017-02-01

Advances in integrated silicon photonics are enabling highly connected sensor networks that offer sensitivity, selectivity and pattern recognition. Cost, performance and the evolution path of the so-called `Internet of Things' will gate the proliferation of these networks. The wavelength spectral range of 3-8um, commonly known as the mid-IR, is critical to specificity for sensors that identify materials by detection of local vibrational modes, reflectivity and thermal emission. For ubiquitous sensing applications in this regime, the sensors must move from premium to commodity level manufacturing volumes and cost. Scaling performance/cost is critically dependent on establishing a minimum set of platform attributes for point, wearable, and physical sensing. Optical sensors are ideal for non-invasive applications. Optical sensor device physics involves evanescent or intra-cavity structures for applied to concentration, interrogation and photo-catalysis functions. The ultimate utility of a platform is dependent on sample delivery/presentation modalities; system reset, recalibration and maintenance capabilities; and sensitivity and selectivity performance. The attributes and performance of a unified Glass-on-Silicon platform has shown good prospects for heterogeneous integration on materials and devices using a low cost process flow. Integrated, single mode, silicon photonic platforms offer significant performance and cost advantages, but they require discovery and qualification of new materials and process integration schemes for the mid-IR. Waveguide integrated light sources based on rare earth dopants and Ge-pumped frequency combs have promise. Optical resonators and waveguide spirals can enhance sensitivity. PbTe materials are among the best choices for a standard, waveguide integrated photodetector. Chalcogenide glasses are capable of transmitting mid-IR signals with high transparency. Integrated sensor case studies of i) high sensitivity analyte detection in solution; ii) gas sensing in air and iii) on-chip spectrometry provide good insight into the tradeoffs being made en route to ubiquitous sensor deployment in an Internet of Things.

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.

The smartphone as a platform for wearable cameras in health research.

PubMed

Gurrin, Cathal; Qiu, Zhengwei; Hughes, Mark; Caprani, Niamh; Doherty, Aiden R; Hodges, Steve E; Smeaton, Alan F

2013-03-01

The Microsoft SenseCam, a small camera that is worn on the chest via a lanyard, increasingly is being deployed in health research. However, the SenseCam and other wearable cameras are not yet in widespread use because of a variety of factors. It is proposed that the ubiquitous smartphones can provide a more accessible alternative to SenseCam and similar devices. To perform an initial evaluation of the potential of smartphones to become an alternative to a wearable camera such as the SenseCam. In 2012, adults were supplied with a smartphone, which they wore on a lanyard, that ran life-logging software. Participants wore the smartphone for up to 1 day and the resulting life-log data were both manually annotated and automatically analyzed for the presence of visual concepts. The results were compared to prior work using the SenseCam. In total, 166,000 smartphone photos were gathered from 47 individuals, along with associated sensor readings. The average time spent wearing the device across all users was 5 hours 39 minutes (SD=4 hours 11 minutes). A subset of 36,698 photos was selected for manual annotation by five researchers. Software analysis of these photos supports the automatic identification of activities to a similar level of accuracy as for SenseCam images in a previous study. Many aspects of the functionality of a SenseCam largely can be replicated, and in some cases enhanced, by the ubiquitous smartphone platform. This makes smartphones good candidates for a new generation of wearable sensing devices in health research, because of their widespread use across many populations. It is envisioned that smartphones will provide a compelling alternative to the dedicated SenseCam hardware for a number of users and application areas. This will be achieved by integrating new types of sensor data, leveraging the smartphone's real-time connectivity and rich user interface, and providing support for a range of relatively sophisticated applications. Copyright © 2013 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

3D printing of highly elastic strain sensors using polyurethane/multiwall carbon nanotube composites

NASA Astrophysics Data System (ADS)

Christ, Josef F.; Hohimer, Cameron J.; Aliheidari, Nahal; Ameli, Amir; Mo, Changki; Pötschke, Petra

2017-04-01

As the desire for wearable electronics increases and the soft robotics industry advances, the need for novel sensing materials has also increased. Recently, there have been many attempts at producing novel materials, which exhibit piezoresistive behavior. However, one of the major shortcomings in strain sensing technologies is in the fabrication of such sensors. While there is significant research and literature covering the various methods for developing piezoresistive materials, fabricating complex sensor platforms is still a manufacturing challenge. Here, we report a facile method to fabricate multidirectional embedded strain sensors using additive manufacturing technology. Pure thermoplastic polyurethane (TPU) and TPU/multiwall carbon nanotubes (MWCNT) nanocomposites were 3D printed in tandem using a low-cost multi-material FDM printer to fabricate uniaxial and biaxial strain sensors with conductive paths embedded within the insulative TPU platform. The sensors were then subjected to a series of cyclic strain loads. The results revealed excellent piezoresistive responses of the sensors with cyclic repeatability in both the axial and transverse directions and in response to strains as high as 50%. Further, while strain-softening did occur in the embedded printed strain sensors, it was predictable and similar to the results found in the literature for bulk polymer nanocomposites. This works demonstrates the possibility of manufacturing embedded and multidirectional flexible strain sensors using an inexpensive and versatile method, with potential applications in soft robotics and flexible electronics and health monitoring.

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.

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.

'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.

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.

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 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.

Highly Strong and Elastic Graphene Fibres Prepared from Universal Graphene Oxide Precursors

PubMed Central

Huang, Guoji; Hou, Chengyi; Shao, Yuanlong; Wang, Hongzhi; Zhang, Qinghong; Li, Yaogang; Zhu, Meifang

2014-01-01

Graphene fibres are continuously prepared from universal graphene oxide precursors by a novel hydrogel-assisted spinning method. With assistance of a rolling process, meters of ribbon-like GFs, or GRs with improved conductivity, tensile strength, and a long-range ordered compact layer structure are successfully obtained. Furthermore, we refined our spinning process to obtained elastic GRs with a mixing microstructure and exceptional elasticity, which may provide a platform for electronic skins and wearable electronics, sensors, and energy devices. PMID:24576869

Clinical validation of the CHRONIOUS wearable system in patients with chronic disease.

PubMed

Bellos, Christos; Papadopoulos, Athanassios; Rosso, Roberto; Fotiadis, Dimitrios I

2013-01-01

The CHRONIOUS system defines a powerful and easy to use framework which has been designed to provide services to clinicians and their patients suffering from chronic diseases. The system is composed of a wearable shirt that integrate several body sensors, a portable smart device and a central sub-system that is responsible for the long term storage of the collected patient's data. A multi-parametric expert system is developed for the analysis of the collected data using intelligent algorithms and complex techniques. Apart for the vital signals, dietary habits, drug intake, activity data, environmental and biochemical parameters are recorded. The CHRONIOUS platform is validated through clinical trials in several medical centers and patient's home environments recruiting patients suffering from Chronic Obstructive pulmonary disease (COPD) and Chronic Kidney Disease (CKD) diseases. The clinical trials contribute in improving the system's accuracy, while Pulmonologists and Nephrologists experts utilized the CHRONIOUS platform to evaluate its efficiency and performance. The results of the utilization of the system were very encouraging. The CHRONIOUS system has been proven to be a well-validated real-time patient monitoring and supervision platform, providing a useful tool for the clinician and the patient that would contribute to the more effective management of chronic diseases.

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

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.

All-soft, battery-free, and wireless chemical sensing platform based on liquid metal for liquid- and gas-phase VOC detection.

PubMed

Kim, Min-Gu; Alrowais, Hommood; Kim, Choongsoon; Yeon, Pyungwoo; Ghovanloo, Maysam; Brand, Oliver

2017-06-27

Lightweight, flexible, stretchable, and wireless sensing platforms have gained significant attention for personal healthcare and environmental monitoring applications. This paper introduces an all-soft (flexible and stretchable), battery-free, and wireless chemical microsystem using gallium-based liquid metal (eutectic gallium-indium alloy, EGaIn) and poly(dimethylsiloxane) (PDMS), fabricated using an advanced liquid metal thin-line patterning technique based on soft lithography. Considering its flexible, stretchable, and lightweight characteristics, the proposed sensing platform is well suited for wearable sensing applications either on the skin or on clothing. Using the microfluidic sensing platform, detection of liquid-phase and gas-phase volatile organic compounds (VOC) is demonstrated using the same design, which gives an opportunity to have the sensor operate under different working conditions and environments. In the case of liquid-phase chemical sensing, the wireless sensing performance and microfluidic capacitance tunability for different dielectric liquids are evaluated using analytical, numerical, and experimental approaches. In the case of gas-phase chemical sensing, PDMS is used both as a substrate and a sensing material. The gas sensing performance is evaluated and compared to a silicon-based, solid-state gas sensor with a PDMS sensing film.

Flexible graphene bio-nanosensor for lactate.

PubMed

Labroo, Pratima; Cui, Yue

2013-03-15

The development of a flexible nanosensor for detecting lactate could expand opportunities for using graphene, both in fundamental studies for a variety of device platforms and in practical applications. Graphene is a delicate single-layer, two-dimensional network of carbon atoms with ultrasensitive sensing capabilities. Lactic acid is important for clinical analysis, sports medicine, and the food industry. Recently, wearable and flexible bioelectronics on plastics have attracted great interest for healthcare, sports and defense applications due to their advantages of being light-weight, bendable, or stretchable. Here, we demonstrate for the first time the development of a flexible graphene-based bio-nanosensor to detect lactate. Our results show that flexible lactate biosensors can be fabricated on a variety of plastic substrates. The sensor can detect lactate sensitively from 0.08 μM to 20 μM with a fast steady-state measuring time of 2s. The sensor can also detect lactate under different mechanical bending conditions, the sensor response decreased as the bending angle and number of bending repetitions increased. We anticipate that these results could open exciting opportunities for fundamental studies of flexible graphene bioelectronics by using other bioreceptors, as well as a variety of wearable, implantable, real-time, or on-site applications in fields ranging from clinical analysis to defense. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

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

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.

A Software Development Platform for Wearable Medical Applications.

PubMed

Zhang, Ruikai; Lin, Wei

2015-10-01

Wearable medical devices have become a leading trend in healthcare industry. Microcontrollers are computers on a chip with sufficient processing power and preferred embedded computing units in those devices. We have developed a software platform specifically for the design of the wearable medical applications with a small code footprint on the microcontrollers. It is supported by the open source real time operating system FreeRTOS and supplemented with a set of standard APIs for the architectural specific hardware interfaces on the microcontrollers for data acquisition and wireless communication. We modified the tick counter routine in FreeRTOS to include a real time soft clock. When combined with the multitasking features in the FreeRTOS, the platform offers the quick development of wearable applications and easy porting of the application code to different microprocessors. Test results have demonstrated that the application software developed using this platform are highly efficient in CPU usage while maintaining a small code foot print to accommodate the limited memory space in microcontrollers.

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.

A Low Power, Parallel Wearable Multi-Sensor System for Human Activity Evaluation.

PubMed

Li, Yuecheng; Jia, Wenyan; Yu, Tianjian; Luan, Bo; Mao, Zhi-Hong; Zhang, Hong; Sun, Mingui

2015-04-01

In this paper, the design of a low power heterogeneous wearable multi-sensor system, built with Zynq System-on-Chip (SoC), for human activity evaluation is presented. The powerful data processing capability and flexibility of this SoC represent significant improvements over our previous ARM based system designs. The new system captures and compresses multiple color images and sensor data simultaneously. Several strategies are adopted to minimize power consumption. Our wearable system provides a new tool for the evaluation of human activity, including diet, physical activity and lifestyle.

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.

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.

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

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.

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.

An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things.

PubMed

Pasluosta, Cristian F; Gassner, Heiko; Winkler, Juergen; Klucken, Jochen; Eskofier, Bjoern M

2015-11-01

Current challenges demand a profound restructuration of the global healthcare system. A more efficient system is required to cope with the growing world population and increased life expectancy, which is associated with a marked prevalence of chronic neurological disorders such as Parkinson's disease (PD). One possible approach to meet this demand is a laterally distributed platform such as the Internet of Things (IoT). Real-time motion metrics in PD could be obtained virtually in any scenario by placing lightweight wearable sensors in the patient's clothes and connecting them to a medical database through mobile devices such as cell phones or tablets. Technologies exist to collect huge amounts of patient data not only during regular medical visits but also at home during activities of daily life. These data could be fed into intelligent algorithms to first discriminate relevant threatening conditions, adjust medications based on online obtained physical deficits, and facilitate strategies to modify disease progression. A major impact of this approach lies in its efficiency, by maximizing resources and drastically improving the patient experience. The patient participates actively in disease management via combined objective device- and self-assessment and by sharing information within both medical and peer groups. Here, we review and discuss the existing wearable technologies and the Internet-of-Things concept applied to PD, with an emphasis on how this technological platform may lead to a shift in paradigm in terms of diagnostics and treatment.

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.

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.

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

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.

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.

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.

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.

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.

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.

A Wearable Microfluidic Sensing Patch for Dynamic Sweat Secretion Analysis.

PubMed

Nyein, Hnin Yin Yin; Tai, Li-Chia; Ngo, Quynh Phuong; Chao, Minghan; Zhang, George B; Gao, Wei; Bariya, Mallika; Bullock, James; Kim, Hyungjin; Fahad, Hossain M; Javey, Ali

2018-05-25

Wearable sweat sensing is a rapidly rising research area driven by its promising potential in health, fitness, and diagnostic applications. Despite the growth in the field, major challenges in relation to sweat metrics remain to be addressed. These challenges include sweat rate monitoring for its complex relation with sweat compositions and sweat sampling for sweat dynamics studies. In this work, we present a flexible microfluidic sweat sensing patch that enhances real-time electrochemical sensing and sweat rate analysis via sweat sampling. The device contains a spiral-patterned microfluidic component that is embedded with ion-selective sensors and an electrical impedance-based sweat rate sensor on a flexible plastic substrate. The patch is enabled to autonomously perform sweat analysis by interfacing the sensing component with a printed circuit board that is capable of on-site signal conditioning, analysis, and transmission. Progressive sweat flow in the microfluidic device, governed by the pressure induced by the secreted sweat, enhances sweat sampling and electrochemical detection via a defined sweat collection chamber and a directed sweat route. The characteristic of the sweat rate sensor is validated through a theoretical simulation, and the precision and accuracy of the flow rate is verified with a commercial syringe pump and a Macroduct sweat collector. On-body simultaneous monitoring of ion (H + , Na + , K + , Cl - ) concentration and sweat rate is also demonstrated for sensor functionality. This sweat sensing patch provides an integrated platform for a comprehensive sweat secretion analysis and facilitates physiological and clinical investigations by closely monitoring interrelated sweat parameters.

Field Programmable Gate Array (FPGA) Respiratory Monitoring System Using a Flow Microsensor and an Accelerometer

NASA Astrophysics Data System (ADS)

Mellal, Idir; Laghrouche, Mourad; Bui, Hung Tien

2017-04-01

This paper describes a non-invasive system for respiratory monitoring using a Micro Electro Mechanical Systems (MEMS) flow sensor and an IMU (Inertial Measurement Unit) accelerometer. The designed system is intended to be wearable and used in a hospital or at home to assist people with respiratory disorders. To ensure the accuracy of our system, we proposed a calibration method based on ANN (Artificial Neural Network) to compensate the temperature drift of the silicon flow sensor. The sigmoid activation functions used in the ANN model were computed with the CORDIC (COordinate Rotation DIgital Computer) algorithm. This algorithm was also used to estimate the tilt angle in body position. The design was implemented on reconfigurable platform FPGA.

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.

A wearable sensor system for lower-limb rehabilitation evaluation using the GRF and CoP distributions

NASA Astrophysics Data System (ADS)

Tao, Weijun; Zhang, Jianyun; Li, Guangyi; Liu, Tao; Liu, Fengping; Yi, Jingang; Wang, Hesheng; Inoue, Yoshio

2016-02-01

Wearable sensors are attractive for gait analysis because these systems can measure and obtain real-time human gait and motion information outside of the laboratory for a longer duration. In this paper, we present a new wearable ground reaction force (GRF) sensing system for ambulatory gait measurement. In addition, the GRF sensor system is also used to quantify the patients' lower-limb gait rehabilitation. We conduct a validation experiment for the sensor system on seven volunteer subjects (weight 62.39 +/- 9.69 kg and height 169.13 +/- 5.64 cm). The experiments include the use of the GRF sensing system for the subjects in the following conditions: (1) normal walking; (2) walking with the rehabilitation training device; and (3) walking with a knee brace and the rehabilitation training device. The experiment results support the hypothesis that the wearable GRF sensor system is capable of quantifying patients' lower-limb rehabilitation. The proposed GRF sensing system can also be used for assessing the effectiveness of a gait rehabilitation system and for providing bio-feedback information to the subjects.

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.

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.

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.

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.

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.

Personalized cumulative UV tracking on mobiles & wearables.

PubMed

Dey, S; Sahoo, S; Agrawal, H; Mondal, A; Bhowmik, T; Tiwari, V N

2017-07-01

Maintaining a balanced Ultra Violet (UV) exposure level is vital for a healthy living as the excess of UV dose can lead to critical diseases such as skin cancer while the absence can cause vitamin D deficiency which has recently been linked to onset of cardiac abnormalities. Here, we propose a personalized cumulative UV dose (CUVD) estimation system for smartwatch and smartphone devices having the following novelty factors; (a) sensor orientation invariant measurement of UV exposure using a bootstrap resampling technique, (b) estimation of UV exposure using only light intensity (lux) sensor (c) optimal UV exposure dose estimation. Our proposed method will eliminate the need for a dedicated UV sensor thus widen the user base of the proposed solution, render it unobtrusive by eliminating the critical requirement of orienting the device in a direction facing the sun. The system is implemented on android mobile platform and validated on 1200 minutes of lux and UV index (UVI) data collected across several days covering morning to evening time frames. The result shows very impressive final UVI estimation accuracy. We believe our proposed solution will enable the future wearable and smartphone users to obtain a seamless personalized UV exposure dose across a day paving a way for simple yet very useful recommendations such as right skin protective measure for reducing risk factors of long term UV exposure related diseases like skin cancer and, cardiac abnormality.

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.

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.

Novel Flexible Wearable Sensor Materials and Signal Processing for Vital Sign and Human Activity Monitoring.

PubMed

Servati, Amir; Zou, Liang; Wang, Z Jane; Ko, Frank; Servati, Peyman

2017-07-13

Advances in flexible electronic materials and smart textile, along with broad availability of smart phones, cloud and wireless systems have empowered the wearable technologies for significant impact on future of digital and personalized healthcare as well as consumer electronics. However, challenges related to lack of accuracy, reliability, high power consumption, rigid or bulky form factor and difficulty in interpretation of data have limited their wide-scale application in these potential areas. As an important solution to these challenges, we present latest advances in novel flexible electronic materials and sensors that enable comfortable and conformable body interaction and potential for invisible integration within daily apparel. Advances in novel flexible materials and sensors are described for wearable monitoring of human vital signs including, body temperature, respiratory rate and heart rate, muscle movements and activity. We then present advances in signal processing focusing on motion and noise artifact removal, data mining and aspects of sensor fusion relevant to future clinical applications of wearable technology.

Novel Flexible Wearable Sensor Materials and Signal Processing for Vital Sign and Human Activity Monitoring

PubMed Central

Servati, Amir; Wang, Z. Jane; Ko, Frank; Servati, Peyman

2017-01-01

Advances in flexible electronic materials and smart textile, along with broad availability of smart phones, cloud and wireless systems have empowered the wearable technologies for significant impact on future of digital and personalized healthcare as well as consumer electronics. However, challenges related to lack of accuracy, reliability, high power consumption, rigid or bulky form factor and difficulty in interpretation of data have limited their wide-scale application in these potential areas. As an important solution to these challenges, we present latest advances in novel flexible electronic materials and sensors that enable comfortable and conformable body interaction and potential for invisible integration within daily apparel. Advances in novel flexible materials and sensors are described for wearable monitoring of human vital signs including, body temperature, respiratory rate and heart rate, muscle movements and activity. We then present advances in signal processing focusing on motion and noise artifact removal, data mining and aspects of sensor fusion relevant to future clinical applications of wearable technology. PMID:28703744

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).

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.

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

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.

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.

A Preliminary Design Of Application Of Wireless Identification And Sensing Platform On External Beam Radiotherapy

NASA Astrophysics Data System (ADS)

Heranudin; Bakhri, S.

2018-02-01

A linear accelerator (linac) is widely used as a means of radiotherapy by focusing high-energy photons in the targeted tumor of patient. Incorrectness of the shooting can lead normal tissue surrounding the tumor received unnecessary radiation and become damaged cells. A method is required to minimize the incorrectness that mostly caused by movement of the patient during radiotherapy process. In this paper, the Wireless Identification and Sensing Platform (WISP) architecture was employed to monitor in real time the movement of the patient’s body during radiotherapy process. In general, the WISP is a wearable sensors device that can transmit measurement data wirelessly. In this design, the measurement devices consist of an accelerometer, a barometer and an ionizing radiation sensor. If any changes in the body position which resulted in incorrectness of the shooting, the accelerometer and the barometer will trigger a warning to the linac operator. In addition, the radiation sensor in the WISP will detect unwanted radiation and that can endanger the patient. A wireless feature in this device can ease in implementation. Initial analyses have been performed and showed that the WISP is feasible to be applied on external beam radiotherapy.

Investigations of fluid-strain interaction using Plate Boundary Observatory borehole data

NASA Astrophysics Data System (ADS)

Boyd, Jeffrey Michael

Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense and encompasses sensors, feature calculations, activity classification algorithms, sleep schedules, and transmission protocols. Design choices in each of these areas impact energy use, overall accuracy, and usefulness of the system. This thesis explores methods software can influence the trade-off between energy consumption and system accuracy. In general the more energy a system consumes the more accurate will be. We explore how finding the transitions between human activities is able to reduce the energy consumption of such systems without reducing much accuracy. We introduce the Log-likelihood Ratio Test as a method to detect transitions, and explore how choices of sensor, feature calculations, and parameters concerning time segmentation affect the accuracy of this method. We discovered an approximate 5X increase in energy efficiency could be achieved with only a 5% decrease in accuracy. We also address how a system's sleep mode, in which the processor enters a low-power state and sensors are turned off, affects a wearable computing platform that does activity recognition. We discuss the energy trade-offs in each stage of the activity recognition process. We find that careful analysis of these parameters can result in great increases in energy efficiency if small compromises in overall accuracy can be tolerated. We call this the ``Great Compromise.'' We found a 6X increase in efficiency with a 7% decrease in accuracy. We then consider how wireless transmission of data affects the overall energy efficiency of a wearable computing platform. We find that design decisions such as feature calculations and grouping size have a great impact on the energy consumption of the system because of the amount of data that is stored and transmitted. For example, storing and transmitting vector-based features such as FFT or DCT do not compress the signal and would use more energy than storing and transmitting the raw signal. The effect of grouping size on energy consumption depends on the feature. For scalar features energy consumption is proportional in the inverse of grouping size, so it's reduced as grouping size goes up. For features that depend on the grouping size, such as FFT, energy increases with the logarithm of grouping size, so energy consumption increases slowly as grouping size increases. We find that compressing data through activity classification and transition detection significantly reduces energy consumption and that the energy consumed for the classification overhead is negligible compared to the energy savings from data compression. We provide mathematical models of energy usage and data generation, and test our ideas using a mobile computing platform, the Texas Instruments Chronos watch.

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.

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.

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.

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.

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.

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.

A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare.

PubMed

Mezghani, Emna; Exposito, Ernesto; Drira, Khalil; Da Silveira, Marcos; Pruski, Cédric

2015-12-01

Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients' health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the "Knowledge as a Service" approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.

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.

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.

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.

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.

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

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

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.

Logic-centered architecture for ubiquitous health monitoring.

PubMed

Lewandowski, Jacek; Arochena, Hisbel E; Naguib, Raouf N G; Chao, Kuo-Ming; Garcia-Perez, Alexeis

2014-09-01

One of the key points to maintain and boost research and development in the area of smart wearable systems (SWS) is the development of integrated architectures for intelligent services, as well as wearable systems and devices for health and wellness management. This paper presents such a generic architecture for multiparametric, intelligent and ubiquitous wireless sensing platforms. It is a transparent, smartphone-based sensing framework with customizable wireless interfaces and plug'n'play capability to easily interconnect third party sensor devices. It caters to wireless body, personal, and near-me area networks. A pivotal part of the platform is the integrated inference engine/runtime environment that allows the mobile device to serve as a user-adaptable personal health assistant. The novelty of this system lays in a rapid visual development and remote deployment model. The complementary visual Inference Engine Editor that comes with the package enables artificial intelligence specialists, alongside with medical experts, to build data processing models by assembling different components and instantly deploying them (remotely) on patient mobile devices. In this paper, the new logic-centered software architecture for ubiquitous health monitoring applications is described, followed by a discussion as to how it helps to shift focus from software and hardware development, to medical and health process-centered design of new SWS applications.

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.

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.

Fabrication Methods and Performance of Low-Permeability Microfluidic Components for a Miniaturized Wearable Drug Delivery System

PubMed Central

Mescher, Mark J.; Swan, Erin E. Leary; Fiering, Jason; Holmboe, Maria E.; Sewell, William F.; Kujawa, Sharon G.; McKenna, Michael J.; Borenstein, Jeffrey T.

2010-01-01

In this paper, we describe low-permeability components of a microfluidic drug delivery system fabricated with versatile micromilling and lamination techniques. The fabrication process uses laminate sheets which are machined using XY milling tables commonly used in the printed-circuit industry. This adaptable platform for polymer microfluidics readily accommodates integration with silicon-based sensors, printed-circuit, and surface-mount technologies. We have used these methods to build components used in a wearable liquid-drug delivery system for in vivo studies. The design, fabrication, and performance of membrane-based fluidic capacitors and manual screw valves provide detailed examples of the capability and limitations of the fabrication method. We demonstrate fluidic capacitances ranging from 0.015 to 0.15 μL/kPa, screw valves with on/off flow ratios greater than 38 000, and a 45× reduction in the aqueous fluid loss rate to the ambient due to permeation through a silicone diaphragm layer. PMID:20852729

Fabric Organic Electrochemical Transistors for Biosensors.

PubMed

Yang, Anneng; Li, Yuanzhe; Yang, Chenxiao; Fu, Ying; Wang, Naixiang; Li, Li; Yan, Feng

2018-06-01

Flexible fabric biosensors can find promising applications in wearable electronics. However, high-performance fabric biosensors have been rarely reported due to many special requirements in device fabrication. Here, the preparation of organic electrochemical transistors (OECTs) on Nylon fibers is reported. By introducing metal/conductive polymer multilayer electrodes on the fibers, the OECTs show very stable performance during bending tests. The devices with functionalized gates are successfully used as various biosensors with high sensitivity and selectivity. The fiber-based OECTs are woven together with cotton yarns successfully by using a conventional weaving machine, resulting in flexible and stretchable fabric biosensors with high performance. The fabric sensors show much more stable signals in the analysis of moving aqueous solutions than planar devices due to a capillary effect in fabrics. The fabric devices are integrated in a diaper and remotely operated by using a mobile phone, offering a unique platform for convenient wearable healthcare monitoring. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A reconfigurable, wearable, wireless ECG system.

PubMed

Borromeo, S; Rodriguez-Sanchez, C; Machado, F; Hernandez-Tamames, J A; de la Prieta, R

2007-01-01

New emerging concepts as "wireless hospital", "mobile healthcare" or "wearable telemonitoring" require the development of bio-signal acquisition devices to be easily integrated into the clinical routine. In this work, we present a new system for Electrocardiogram (ECG) acquisition and its processing, with wireless transmission on demand (either the complete ECG or only one alarm message, just in case a pathological heart rate detected). Size and power consumption are optimized in order to provide mobility and comfort to the patient. We have designed a modular hardware system and an autonomous platform based on a Field-Programmable Gate Array (FPGA) for developing and debugging. The modular approach allows to redesign the system in an easy way. Its adaptation to a new biomedical signal would only need small changes on it. The hardware system is composed of three layers that can be plugged/unplugged: communication layer, processing layer and sensor layer. In addition, we also present a general purpose end-user application developed for mobile phones or Personal Digital Assistant devices (PDAs).

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.

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.

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

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.

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.

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

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.

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

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.

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.

Multi-Residential Activity Labelling in Smart Homes with Wearable Tags Using BLE Technology

PubMed Central

Mokhtari, Ghassem; Zhang, Qing; Karunanithi, Mohanraj

2018-01-01

Smart home platforms show promising outcomes to provide a better quality of life for residents in their homes. One of the main challenges that exists with these platforms in multi-residential houses is activity labeling. As most of the activity sensors do not provide any information regarding the identity of the person who triggers them, it is difficult to label the sensor events in multi-residential smart homes. To deal with this challenge, individual localization in different areas can be a promising solution. The localization information can be used to automatically label the activity sensor data to individuals. Bluetooth low energy (BLE) is a promising technology for this application due to how easy it is to implement and its low energy footprint. In this approach, individuals wear a tag that broadcasts its unique identity (ID) in certain time intervals, while fixed scanners listen to the broadcasting packet to localize the tag and the individual. However, the localization accuracy of this method depends greatly on different settings of broadcasting signal strength, and the time interval of BLE tags. To achieve the best localization accuracy, this paper studies the impacts of different advertising time intervals and power levels, and proposes an efficient and applicable algorithm to select optimal value settings of BLE sensors. Moreover, it proposes an automatic activity labeling method, through integrating BLE localization information and ambient sensor data. The applicability and effectiveness of the proposed structure is also demonstrated in a real multi-resident smart home scenario. PMID:29562666

Multi-Residential Activity Labelling in Smart Homes with Wearable Tags Using BLE Technology.

PubMed

Mokhtari, Ghassem; Anvari-Moghaddam, Amjad; Zhang, Qing; Karunanithi, Mohanraj

2018-03-19

Smart home platforms show promising outcomes to provide a better quality of life for residents in their homes. One of the main challenges that exists with these platforms in multi-residential houses is activity labeling. As most of the activity sensors do not provide any information regarding the identity of the person who triggers them, it is difficult to label the sensor events in multi-residential smart homes. To deal with this challenge, individual localization in different areas can be a promising solution. The localization information can be used to automatically label the activity sensor data to individuals. Bluetooth low energy (BLE) is a promising technology for this application due to how easy it is to implement and its low energy footprint. In this approach, individuals wear a tag that broadcasts its unique identity (ID) in certain time intervals, while fixed scanners listen to the broadcasting packet to localize the tag and the individual. However, the localization accuracy of this method depends greatly on different settings of broadcasting signal strength, and the time interval of BLE tags. To achieve the best localization accuracy, this paper studies the impacts of different advertising time intervals and power levels, and proposes an efficient and applicable algorithm to select optimal value settings of BLE sensors. Moreover, it proposes an automatic activity labeling method, through integrating BLE localization information and ambient sensor data. The applicability and effectiveness of the proposed structure is also demonstrated in a real multi-resident smart home scenario.

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

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.

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

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.

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.

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

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.

CHRONIOUS: a wearable platform for monitoring and management of patients with chronic disease.

PubMed

Bellos, Christos; Papadopoulos, Athanassios; Rosso, Roberto; Fotiadis, Dimitrios I

2011-01-01

The CHRONIOUS system has been developed based on an open architecture design that consists of a set of subsystems which interact in order to provide all the needed services to the chronic disease patients. An advanced multi-parametric expert system is being implemented that fuses information effectively from various sources using intelligent techniques. Data are collected by sensors of a body network controlling vital signals while additional tools record dietary habits and plans, drug intake, environmental and biochemical parameters and activity data. The CHRONIOUS platform provides guidelines and standards for the future generations of "chronic disease management systems" and facilitates sophisticated monitoring tools. In addition, an ontological information retrieval system is being delivered satisfying the necessities for up-to-date clinical information of Chronic Obstructive pulmonary disease (COPD) and Chronic Kidney Disease (CKD). Moreover, support tools are being embedded in the system, such as the Mental Tools for the monitoring of patient mental health status. The integrated platform provides real-time patient monitoring and supervision, both indoors and outdoors and represents a generic platform for the management of various chronic diseases.

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.

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.

Real-time bio-sensors for enhanced C2ISR operator performance

NASA Astrophysics Data System (ADS)

Miller, James C.

2005-05-01

The objectives of two Air Force Small Business research topics were to develop a real-time, unobtrusive, biological sensing and monitoring technology for evaluating cognitive readiness in command and control environments (i.e., console operators). We sought an individualized status monitoring system for command and control operators and teams. The system was to consist of a collection of bio-sensing technologies and processing and feedback algorithms that could eventually guide the effective incorporation of fatigue-adaptive workload interventions into weapon systems to mitigate episodes of cognitive overload and lapses in operator attention that often result in missed signals and catastrophic failures. Contractors set about determining what electro-physiological and other indicators of compromised operator states are most amenable for unobtrusive monitoring of psychophysiological and warfighter performance data. They proposed multi-sensor platforms of bio-sensing technologies for development. The sensors will be continuously-wearable or off-body and will not require complicated or uncomfortable preparation. A general overview of the proposed approaches and of progress toward the objective is presented.

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.

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 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).

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.

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.

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

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.

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

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

Implementation of a smartphone as a wireless gyroscope platform for quantifying reduced arm swing in hemiplegie gait with machine learning classification by multilayer perceptron neural network.

PubMed

LeMoyne, Robert; Mastroianni, Timothy

2016-08-01

Natural gait consists of synchronous and rhythmic patterns for both the lower and upper limb. People with hemiplegia can experience reduced arm swing, which can negatively impact the quality of gait. Wearable and wireless sensors, such as through a smartphone, have demonstrated the ability to quantify various features of gait. With a software application the smartphone (iPhone) can function as a wireless gyroscope platform capable of conveying a gyroscope signal recording as an email attachment by wireless connectivity to the Internet. The gyroscope signal recordings of the affected hemiplegic arm with reduced arm swing arm and the unaffected arm are post-processed into a feature set for machine learning. Using a multilayer perceptron neural network a considerable degree of classification accuracy is attained to distinguish between the affected hemiplegic arm with reduced arm swing arm and the unaffected arm.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

Feasibility Study on a Microwave-Based Sensor for Measuring Hydration Level Using Human Skin Models

PubMed Central

Brendtke, Rico; Wiehl, Michael; Groeber, Florian; Schwarz, Thomas; Walles, Heike; Hansmann, Jan

2016-01-01

Tissue dehydration results in three major types of exsiccosis—hyper-, hypo-, or isonatraemia. All three types entail alterations of salt concentrations leading to impaired biochemical processes, and can finally cause severe morbidity. The aim of our study was to demonstrate the feasibility of a microwave-based sensor technology for the non-invasive measurement of the hydration status. Electromagnetic waves at high frequencies interact with molecules, especially water. Hence, if a sample contains free water molecules, this can be detected in a reflected microwave signal. To develop the sensor system, human three-dimensional skin equivalents were instituted as a standardized test platform mimicking reproducible exsiccosis scenarios. Therefore, skin equivalents with a specific hydration and density of matrix components were generated and microwave measurements were performed. Hydration-specific spectra allowed deriving the hydration state of the skin models. A further advantage of the skin equivalents was the characterization of the impact of distinct skin components on the measured signals to investigate mechanisms of signal generation. The results demonstrate the feasibility of a non-invasive microwave-based hydration sensor technology. The sensor bears potential to be integrated in a wearable medical device for personal health monitoring. PMID:27046226

Feasibility Study on a Microwave-Based Sensor for Measuring Hydration Level Using Human Skin Models.

PubMed

Brendtke, Rico; Wiehl, Michael; Groeber, Florian; Schwarz, Thomas; Walles, Heike; Hansmann, Jan

2016-01-01

Tissue dehydration results in three major types of exsiccosis--hyper-, hypo-, or isonatraemia. All three types entail alterations of salt concentrations leading to impaired biochemical processes, and can finally cause severe morbidity. The aim of our study was to demonstrate the feasibility of a microwave-based sensor technology for the non-invasive measurement of the hydration status. Electromagnetic waves at high frequencies interact with molecules, especially water. Hence, if a sample contains free water molecules, this can be detected in a reflected microwave signal. To develop the sensor system, human three-dimensional skin equivalents were instituted as a standardized test platform mimicking reproducible exsiccosis scenarios. Therefore, skin equivalents with a specific hydration and density of matrix components were generated and microwave measurements were performed. Hydration-specific spectra allowed deriving the hydration state of the skin models. A further advantage of the skin equivalents was the characterization of the impact of distinct skin components on the measured signals to investigate mechanisms of signal generation. The results demonstrate the feasibility of a non-invasive microwave-based hydration sensor technology. The sensor bears potential to be integrated in a wearable medical device for personal health monitoring.

Framework of sensor-based monitoring for pervasive patient care.

PubMed

Triantafyllidis, Andreas K; Koutkias, Vassilis G; Chouvarda, Ioanna; Adami, Ilia; Kouroubali, Angelina; Maglaveras, Nicos

2016-09-01

Sensor-based health systems can often become difficult to use, extend and sustain. The authors propose a framework for designing sensor-based health monitoring systems aiming to provide extensible and usable monitoring services in the scope of pervasive patient care. The authors' approach relies on a distributed system for monitoring the patient health status anytime-anywhere and detecting potential health complications, for which healthcare professionals and patients are notified accordingly. Portable or wearable sensing devices measure the patient's physiological parameters, a smart mobile device collects and analyses the sensor data, a Medical Center system receives notifications on the detected health condition, and a Health Professional Platform is used by formal caregivers in order to review the patient condition and configure monitoring schemas. A Service-oriented architecture is utilised to provide extensible functional components and interoperable interactions among the diversified system components. The framework was applied within the REMOTE ambient-assisted living project in which a prototype system was developed, utilising Bluetooth to communicate with the sensors and Web services for data exchange. A scenario of using the REMOTE system and preliminary usability results show the applicability, usefulness and virtue of our approach.

Framework of sensor-based monitoring for pervasive patient care

PubMed Central

Koutkias, Vassilis G.; Chouvarda, Ioanna; Adami, Ilia; Kouroubali, Angelina; Maglaveras, Nicos

2016-01-01

Sensor-based health systems can often become difficult to use, extend and sustain. The authors propose a framework for designing sensor-based health monitoring systems aiming to provide extensible and usable monitoring services in the scope of pervasive patient care. The authors’ approach relies on a distributed system for monitoring the patient health status anytime-anywhere and detecting potential health complications, for which healthcare professionals and patients are notified accordingly. Portable or wearable sensing devices measure the patient's physiological parameters, a smart mobile device collects and analyses the sensor data, a Medical Center system receives notifications on the detected health condition, and a Health Professional Platform is used by formal caregivers in order to review the patient condition and configure monitoring schemas. A Service-oriented architecture is utilised to provide extensible functional components and interoperable interactions among the diversified system components. The framework was applied within the REMOTE ambient-assisted living project in which a prototype system was developed, utilising Bluetooth to communicate with the sensors and Web services for data exchange. A scenario of using the REMOTE system and preliminary usability results show the applicability, usefulness and virtue of our approach. PMID:27733920

Designing of a small wearable conformal phased array antenna for wireless communications

NASA Astrophysics Data System (ADS)

Roy, Sayan

In this thesis, a unique design of a self-adapting conformal phased-array antenna system for wireless communications is presented. The antenna system is comprised of one microstrip antenna array and a sensor circuit. A 1x4 printed microstrip patch antenna array was designed on a flexible substrate with a resonant frequency of 2.47 GHz. However, the performance of the antenna starts to degrade as the curvature of the surface of the substrate changes. To recover the performance of the system, a flexible sensor circuitry was designed. This sensor circuitry uses analog phase shifters, a flexible resistor and operational-amplifier circuitry to compensate the phase of each array element of the antenna. The proposed analytical method for phase compensation has been first verified by designing an RF test platform consisting of a microstrip antenna array, commercially available analog phase shifters, analog voltage attenuators, 4-port power dividers and amplifiers. The platform can be operated through a LabVIEW GUI interface using a 12-bit digital-to-analog converter. This test board was used to design and calibrate the sensor circuitry by observing the behavior of the antenna array system on surfaces with different curvatures. In particular, this phased array antenna system was designed to be used on the surface of a spacesuit or any other flexible prototype. This work was supported in part by the Defense Miroelectronics Activity (DMEA), NASA ND EPSCoR and DARPA/MTO.

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 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.

A paraeducator glove for counting disabled-child behaviors that incorporates a Bluetooth Low Energy wireless link to a smart phone.

PubMed

Luan, Shiwei; Gude, Dana; Prakash, Punit; Warren, Steve

2014-01-01

Behavior tracking with severely disabled children can be a challenge, since dealing directly with a child's behavior is more immediately pressing than the need to record an event for tracking purposes. By the time a paraeducator (`para') is able to break away and record events, behavior counts can be forgotten. This paper presents a paraeducator glove design that can help to track behaviors with minimal distraction by allowing a paraeducator to touch their thumb to one of their other four fingers, where each finger represents a different behavior. Count data are packaged by a microcontroller board on the glove and then sent wirelessly to a smart phone via a Bluetooth Low Energy (BLE) link. A customized BLE profile was designed for this application to promote real-time recording. These data can be forwarded to a database for further analysis. This para glove design addresses basic needs of a wearable device that employs BLE, including local data collection, BLE data transmission, and remote data recording. More functional sensors can be added to this platform to support other wearable scenarios.

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.

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.

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.

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.

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.

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.

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.

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.

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

Hybrid integration of VCSELs onto a silicon photonic platform for biosensing application

NASA Astrophysics Data System (ADS)

Lu, Huihui; Lee, Jun Su; Zhao, Yan; Cardile, Paolo; Daly, Aidan; Carroll, Lee; O'Brien, Peter

2017-02-01

This paper presents a technology of hybrid integration vertical cavity surface emitting lasers (VCSELs) directly on silicon photonics chip. By controlling the reflow of the solder balls used for electrical and mechanical bonding, the VCSELs were bonded at 10 degree to achieve the optimum angle-of-incidence to the planar grating coupler through vision based flip-chip techniques. The 1 dB discrepancy between optical loss values of flip-chip passive assembly and active alignment confirmed that the general purpose of the flip-chip design concept is achieved. This hybrid approach of integrating a miniaturized light source on chip opens the possibly of highly compact sensor system, which enable future portable and wearable diagnostics devices.

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.

Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys.

PubMed

Mastrandrea, Rossana; Fournet, Julie; Barrat, Alain

2015-01-01

Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations.

Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys

PubMed Central

Mastrandrea, Rossana; Fournet, Julie; Barrat, Alain

2015-01-01

Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations. PMID:26325289

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.

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

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 wellness software platform with smart wearable devices and the demonstration report for personal wellness management

NASA Astrophysics Data System (ADS)

Kang, Won-Seok; Son, Chang-Sik; Lee, Sangho; Choi, Rock-Hyun; Ha, Yeong-Mi

2017-07-01

In this paper, we introduce a wellness software platform, called WellnessHumanCare, is a semi-automatic wellness management software platform which has the functions of complex wellness data acquisition(mental, physical and environmental one) with smart wearable devices, complex wellness condition analysis, private-aware online/offline recommendation, real-time monitoring apps (Smartphone-based, Web-based) and so on and we has demonstrated a wellness management service with 79 participants (experimental group: 39, control group: 40) who has worked at experimental group (H Corp.) and control group (K Corp.), Korea and 3 months in order to show the efficiency of the WellnessHumanCare.

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

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

CHRONIOUS: an open, ubiquitous and adaptive chronic disease management platform for chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD) and renal insufficiency.

PubMed

Rosso, R; Munaro, G; Salvetti, O; Colantonio, S; Ciancitto, F

2010-01-01

CHRONIOUS is an highly innovative Information and Communication Technologies (ICT) research Initiative that aspires to implement its vision for ubiquitous health and lifestyle monitoring. The 17 European project partners are strictly working together since February 2008 to realize and open platform to manage and monitor elderly patients with chronic diseases and many difficulties to reach hospital centers for routine controls. The testing activities will be done in Italy and Spain involving COPD (Chronic Obstructive Pulmonary Disease) and CKD (Chronic Kidney Disease) patients, these being widespread and highly expensive in terms of social and economic costs. Patients, equipped by wearable technologies and sensors and interacting with lifestyle interfaces, will be assisted by healthcare personnel able to check the health record and critical conditions through the Chronious platform data analysis and decision support system. Additionally, the new ontology based literature search engine will help the clinicians in the standardization of care delivery process. This paper is to present the main project objectives and its principal components from the intelligent system point of view.

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.

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.

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

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

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

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.

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.

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.

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.

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.

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.

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.

Design and Evaluation of a Pervasive Coaching and Gamification Platform for Young Diabetes Patients.

PubMed

Klaassen, Randy; Bul, Kim C M; Op den Akker, Rieks; van der Burg, Gert Jan; Kato, Pamela M; Di Bitonto, Pierpaolo

2018-01-30

Self monitoring, personal goal-setting and coaching, education and social support are strategies to help patients with chronic conditions in their daily care. Various tools have been developed, e.g., mobile digital coaching systems connected with wearable sensors, serious games and patient web portals to personal health records, that aim to support patients with chronic conditions and their caregivers in realizing the ideal of self-management. We describe a platform that integrates these tools to support young patients in diabetes self-management through educational game playing, monitoring and motivational feedback. We describe the design of the platform referring to principles from healthcare, persuasive system design and serious game design. The virtual coach is a game guide that can also provide personalized feedback about the user's daily care related activities which have value for making progress in the game world. User evaluations with patients under pediatric supervision revealed that the use of mobile technology in combination with web-based elements is feasible but some assumptions made about how users would connect to the platform were not satisfied in reality, resulting in less than optimal user experiences. We discuss challenges with suggestions for further development of integrated pervasive coaching and gamification platforms in medical practice.

Design and Evaluation of a Pervasive Coaching and Gamification Platform for Young Diabetes Patients †

PubMed Central

Klaassen, Randy; Bul, Kim C. M.; op den Akker, Rieks; van der Burg, Gert Jan; Di Bitonto, Pierpaolo

2018-01-01

Self monitoring, personal goal-setting and coaching, education and social support are strategies to help patients with chronic conditions in their daily care. Various tools have been developed, e.g., mobile digital coaching systems connected with wearable sensors, serious games and patient web portals to personal health records, that aim to support patients with chronic conditions and their caregivers in realizing the ideal of self-management. We describe a platform that integrates these tools to support young patients in diabetes self-management through educational game playing, monitoring and motivational feedback. We describe the design of the platform referring to principles from healthcare, persuasive system design and serious game design. The virtual coach is a game guide that can also provide personalized feedback about the user’s daily care related activities which have value for making progress in the game world. User evaluations with patients under pediatric supervision revealed that the use of mobile technology in combination with web-based elements is feasible but some assumptions made about how users would connect to the platform were not satisfied in reality, resulting in less than optimal user experiences. We discuss challenges with suggestions for further development of integrated pervasive coaching and gamification platforms in medical practice. PMID:29385750

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

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.

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

Wireless, intraoral hybrid electronics for real-time quantification of sodium intake toward hypertension management.

PubMed

Lee, Yongkuk; Howe, Connor; Mishra, Saswat; Lee, Dong Sup; Mahmood, Musa; Piper, Matthew; Kim, Youngbin; Tieu, Katie; Byun, Hun-Soo; Coffey, James P; Shayan, Mahdis; Chun, Youngjae; Costanzo, Richard M; Yeo, Woon-Hong

2018-05-22

Recent wearable devices offer portable monitoring of biopotentials, heart rate, or physical activity, allowing for active management of human health and wellness. Such systems can be inserted in the oral cavity for measuring food intake in regard to controlling eating behavior, directly related to diseases such as hypertension, diabetes, and obesity. However, existing devices using plastic circuit boards and rigid sensors are not ideal for oral insertion. A user-comfortable system for the oral cavity requires an ultrathin, low-profile, and soft electronic platform along with miniaturized sensors. Here, we introduce a stretchable hybrid electronic system that has an exceptionally small form factor, enabling a long-range wireless monitoring of sodium intake. Computational study of flexible mechanics and soft materials provides fundamental aspects of key design factors for a tissue-friendly configuration, incorporating a stretchable circuit and sensor. Analytical calculation and experimental study enables reliable wireless circuitry that accommodates dynamic mechanical stress. Systematic in vitro modeling characterizes the functionality of a sodium sensor in the electronics. In vivo demonstration with human subjects captures the device feasibility for real-time quantification of sodium intake, which can be used to manage hypertension.

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.

Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform.

PubMed

Emaminejad, Sam; Gao, Wei; Wu, Eric; Davies, Zoe A; Yin Yin Nyein, Hnin; Challa, Samyuktha; Ryan, Sean P; Fahad, Hossain M; Chen, Kevin; Shahpar, Ziba; Talebi, Salmonn; Milla, Carlos; Javey, Ali; Davis, Ronald W

2017-05-02

Perspiration-based wearable biosensors facilitate continuous monitoring of individuals' health states with real-time and molecular-level insight. The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 µL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. A wearable and miniaturized iontophoresis interface is an excellent solution to overcome this barrier. The iontophoresis process involves delivery of stimulating agonists to the sweat glands with the aid of an electrical current. The challenge remains in devising an iontophoresis interface that can extract sufficient amount of sweat for robust sensing, without electrode corrosion and burning/causing discomfort in subjects. Here, we overcame this challenge through realizing an electrochemically enhanced iontophoresis interface, integrated in a wearable sweat analysis platform. This interface can be programmed to induce sweat with various secretion profiles for real-time analysis, a capability which can be exploited to advance our knowledge of the sweat gland physiology and the secretion process. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation. With our platform, we detected the elevated sweat electrolyte content of cystic fibrosis patients compared with that of healthy control subjects. Furthermore, our results indicate that oral glucose consumption in the fasting state is followed by increased glucose levels in both sweat and blood. Our solution opens the possibility for a broad range of noninvasive diagnostic and general population health monitoring applications.

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

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.

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 untapped potential of smartphone sensors for stroke rehabilitation and after-care.

PubMed

Zhang, Melvyn W; Chew, Poh Yim; Yeo, Leonard L; Ho, Roger C

2016-01-01

With the increasing incidences of cerebrovascular disease, as well as the morbidity and mortality associated with it, it is of no surprise that there have been much global governmental interest in the primary prevention of this disorder; or at least in the secondary and tertiary prevention and rehabilitation of individuals who have suffered disabilities arising from a recent cerebrovascular attack. Developers and clinicians have not considered one of the key areas in Stroke prevention and management, which is that of secondary prevention, and in particular that of tapping onto smartphone technologies for stroke rehabilitation. There has been much interest in the development of devices for rehabilitation of stroke patients instead. One of the concerns with regards to conventional bio and mechanical sensors are the costs involved in development, as well as the costs involved when stroke survivors and their caregivers are required to purchase the devices for monitoring and rehabilitation. In view of the current limitations, the S3 Rehab application, which makes use of the smartphone build in sensors, has been conceptualized and has been developed for the two major platforms (Apple and Android platforms). The authors believe that by tapping onto these sensors and by programming a smartphone application that is specifically catered for rehabilitation, it would keep costs minimal for researchers, patients and caregivers. Whilst there is a growing interest in wearable devices and sensors, it is important for developers and researchers to be cognizant that certain interventions, such as rehabilitation could still be done through a smartphone device, instead of investing in new research and development. There are various untapped potential in the smartphone that researchers and developers need to be cognizant of.

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.

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

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.

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.

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.

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.

Stretchable, Transparent, Ultrasensitive, and Patchable Strain Sensor for Human-Machine Interfaces Comprising a Nanohybrid of Carbon Nanotubes and Conductive Elastomers.

PubMed

Roh, Eun; Hwang, Byeong-Ung; Kim, Doil; Kim, Bo-Yeong; Lee, Nae-Eung

2015-06-23

Interactivity between humans and smart systems, including wearable, body-attachable, or implantable platforms, can be enhanced by realization of multifunctional human-machine interfaces, where a variety of sensors collect information about the surrounding environment, intentions, or physiological conditions of the human to which they are attached. Here, we describe a stretchable, transparent, ultrasensitive, and patchable strain sensor that is made of a novel sandwich-like stacked piezoresisitive nanohybrid film of single-wall carbon nanotubes (SWCNTs) and a conductive elastomeric composite of polyurethane (PU)-poly(3,4-ethylenedioxythiophene) polystyrenesulfonate ( PSS). This sensor, which can detect small strains on human skin, was created using environmentally benign water-based solution processing. We attributed the tunability of strain sensitivity (i.e., gauge factor), stability, and optical transparency to enhanced formation of percolating networks between conductive SWCNTs and PEDOT phases at interfaces in the stacked PU-PEDOT:PSS/SWCNT/PU-PEDOT:PSS structure. The mechanical stability, high stretchability of up to 100%, optical transparency of 62%, and gauge factor of 62 suggested that when attached to the skin of the face, this sensor would be able to detect small strains induced by emotional expressions such as laughing and crying, as well as eye movement, and we confirmed this experimentally.

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.

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.

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.

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.

Combination of Wearable Multi-Biosensor Platform and Resonance Frequency Training for Stress Management of the Unemployed Population

PubMed Central

Wu, Wanqing; Gil, Yeongjoon; Lee, Jungtae

2012-01-01

Currently considerable research is being directed toward developing methodologies for controlling emotion or releasing stress. An applied branch of the basic field of psychophysiology, known as biofeedback, has been developed to fulfill clinical and non-clinical needs related to such control. Wearable medical devices have permitted unobtrusive monitoring of vital signs and emerging biofeedback services in a pervasive manner. With the global recession, unemployment has become one of the most serious social problems; therefore, the combination of biofeedback techniques with wearable technology for stress management of unemployed population is undoubtedly meaningful. This article describes a wearable biofeedback system based on combining integrated multi-biosensor platform with resonance frequency training (RFT) biofeedback strategy for stress management of unemployed population. Compared to commercial system, in situ experiments with multiple subjects indicated that our biofeedback system was discreet, easy to wear, and capable of offering ambulatory RFT biofeedback.Moreover, the comparative studies on the altered autonomic nervous system (ANS) modulation before and after three week RFT biofeedback training was performed in unemployed population with the aid of our wearable biofeedback system. The achieved results suggested that RFT biofeedback in combination with wearable technology was capable of significantly increasingoverall HRV, which indicated by decreasing sympathetic activities, increasing parasympathetic activities, and increasing ANS synchronization. After 3-week RFT-based respiration training, the ANS's regulating function and coping ability of unemployed population have doubled, and tended toward a dynamic balance. PMID:23201994

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.

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

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.

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.

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

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.

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

Using Technology to Improve Cancer Care: Social Media, Wearables, and Electronic Health Records.

PubMed

Fisch, Michael J; Chung, Arlene E; Accordino, Melissa K

2016-01-01

Digital engagement has become pervasive in the delivery of cancer care. Internet- and cellular phone-based tools and systems are allowing large groups of people to engage with each other and share information. Health systems and individual health professionals are adapting to this revolution in consumer and patient behavior by developing ways to incorporate the benefits of technology for the purpose of improving the quality of medical care. One example is the use of social media platforms by oncologists to foster interaction with each other and to participate with the lay public in dialogue about science, medicine, and cancer care. In addition, consumer devices and sensors (wearables) have provided a new, growing dimension of digital engagement and another layer of patient-generated health data to foster better care and research. Finally, electronic health records have become the new standard for oncology care delivery, bringing new opportunities to measure quality in real time and follow practice patterns, as well as new challenges as providers and patients seek ways to integrate this technology along with other forms of digital engagement to produce more satisfaction in the process of care along with measurably better outcomes.

A Wearable Inertial Measurement Unit for Long-Term Monitoring in the Dependency Care Area

PubMed Central

Rodríguez-Martín, Daniel; Pérez-López, Carlos; Samà, Albert; Cabestany, Joan; Català, Andreu

2013-01-01

Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU's movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A μSD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson's disease symptoms, in gait analysis, and in a fall detection system. PMID:24145917

A wearable inertial measurement unit for long-term monitoring in the dependency care area.

PubMed

Rodríguez-Martín, Daniel; Pérez-López, Carlos; Samà, Albert; Cabestany, Joan; Català, Andreu

2013-10-18

Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU's movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A µSD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson's disease symptoms, in gait analysis, and in a fall detection system.

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.

Link technologies and BlackBerry mobile health (mHealth) solutions: a review.

PubMed

Adibi, Sasan

2012-07-01

The number of wearable wireless sensors is expected to grow to 400 million by the year 2014, while the number of operational mobile subscribers has already passed the 5.2 billion mark in 2011. This growth results in an increasing number of mobile applications including: Machine-to-Machine (M2M) communications, Electronic-Health (eHealth), and Mobile-Health (mHealth). A number of emerging mobile applications that require 3G and 4G mobile networks for data transport relate to telemedicine, including establishing, maintaining, and transmitting health-related information, research, education, and training. This review paper takes a closer look at these applications, specifically with regard to the healthcare industry and their underlying link technologies. The authors believe that the BlackBerry platform and the associated infrastructure (i.e., BlackBerry Enterprise Server) is a logical and practical solution for eHealth, mHealth, sensor and M2M deployments, which are considered in this paper.

Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform

DOE PAGES

Emaminejad, Sam; Gao, Wei; Wu, Eric; ...

2017-04-17

Perspiration-based wearable biosensors facilitate continuous monitoring of individuals' health states with real-time and molecular-level insight. The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 μL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. A wearable and miniaturized iontophoresis interface is an excellent solution to overcome this barrier. The iontophoresis process involves delivery of stimulating agonists to the sweat glands with the aid of an electrical current. The challenge remains in devising an iontophoresis interface that can extract sufficient amount of sweat for robust sensing, withoutmore » electrode corrosion and burning/causing discomfort in subjects. Here, we overcame this challenge through realizing an electrochemically enhanced iontophoresis interface, integrated in a wearable sweat analysis platform. This interface can be programmed to induce sweat with various secretion profiles for real-time analysis, a capability which can be exploited to advance our knowledge of the sweat gland physiology and the secretion process. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation. With our platform, we detected the elevated sweat electrolyte content of cystic fibrosis patients compared with that of healthy control subjects. Furthermore, our results indicate that oral glucose consumption in the fasting state is followed by increased glucose levels in both sweat and blood. In conclusion, our solution opens the possibility for a broad range of noninvasive diagnostic and general population health monitoring applications.« less

Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform

PubMed Central

Emaminejad, Sam; Gao, Wei; Wu, Eric; Davies, Zoe A.; Yin Yin Nyein, Hnin; Challa, Samyuktha; Ryan, Sean P.; Fahad, Hossain M.; Chen, Kevin; Shahpar, Ziba; Talebi, Salmonn; Milla, Carlos; Javey, Ali; Davis, Ronald W.

2017-01-01

Perspiration-based wearable biosensors facilitate continuous monitoring of individuals’ health states with real-time and molecular-level insight. The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 µL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. A wearable and miniaturized iontophoresis interface is an excellent solution to overcome this barrier. The iontophoresis process involves delivery of stimulating agonists to the sweat glands with the aid of an electrical current. The challenge remains in devising an iontophoresis interface that can extract sufficient amount of sweat for robust sensing, without electrode corrosion and burning/causing discomfort in subjects. Here, we overcame this challenge through realizing an electrochemically enhanced iontophoresis interface, integrated in a wearable sweat analysis platform. This interface can be programmed to induce sweat with various secretion profiles for real-time analysis, a capability which can be exploited to advance our knowledge of the sweat gland physiology and the secretion process. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation. With our platform, we detected the elevated sweat electrolyte content of cystic fibrosis patients compared with that of healthy control subjects. Furthermore, our results indicate that oral glucose consumption in the fasting state is followed by increased glucose levels in both sweat and blood. Our solution opens the possibility for a broad range of noninvasive diagnostic and general population health monitoring applications. PMID:28416667

Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform

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

Emaminejad, Sam; Gao, Wei; Wu, Eric

Perspiration-based wearable biosensors facilitate continuous monitoring of individuals' health states with real-time and molecular-level insight. The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 μL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. A wearable and miniaturized iontophoresis interface is an excellent solution to overcome this barrier. The iontophoresis process involves delivery of stimulating agonists to the sweat glands with the aid of an electrical current. The challenge remains in devising an iontophoresis interface that can extract sufficient amount of sweat for robust sensing, withoutmore » electrode corrosion and burning/causing discomfort in subjects. Here, we overcame this challenge through realizing an electrochemically enhanced iontophoresis interface, integrated in a wearable sweat analysis platform. This interface can be programmed to induce sweat with various secretion profiles for real-time analysis, a capability which can be exploited to advance our knowledge of the sweat gland physiology and the secretion process. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation. With our platform, we detected the elevated sweat electrolyte content of cystic fibrosis patients compared with that of healthy control subjects. Furthermore, our results indicate that oral glucose consumption in the fasting state is followed by increased glucose levels in both sweat and blood. In conclusion, our solution opens the possibility for a broad range of noninvasive diagnostic and general population health monitoring applications.« less

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.

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.

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.

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.

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.

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

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.

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.

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".

Impact of motor fluctuations on real-life gait in Parkinson's patients.

PubMed

Silva de Lima, Ana Lígia; Evers, Luc J W; Hahn, Tim; de Vries, Nienke M; Daeschler, Margaret; Boroojerdi, Babak; Terricabras, Dolors; Little, Max A; Bloem, Bastiaan R; Faber, Marjan J

2018-05-01

People with PD (PWP) have an increased risk of becoming inactive. Wearable sensors can provide insights into daily physical activity and walking patterns. (1) Is the severity of motor fluctuations associated with sensor-derived average daily walking quantity? (2) Is the severity of motor fluctuations associated with the amount of change in sensor-derived walking quantity after levodopa intake? 304 Dutch PWP from the Parkinson@Home study were included. At baseline, all participants received a clinical examination. During the follow-up period (median: 97 days; 25-Interquartile range-IQR: 91 days, 75-IQR: 188 days), participants used the Fox Wearable Companion app and streamed smartwatch accelerometer data to a cloud platform. The first research question was assessed by linear regression on the sensor-derived mean time spent walking/day with the severity of fluctuations (MDS-UPDRS item 4.4) as independent variable, controlled for age and MDS-UPDRS part-III score. The second research question was assessed by linear regression on the sensor-derived mean post-levodopa walking quantity, with the sensor-derived mean pre-levodopa walking quantity and severity of fluctuations as independent variables, controlled for mean time spent walking per day, age and MDS-UPDRS part-III score. PWP spent most time walking between 8am and 1pm, summing up to 72 ± 39 (mean ± standard deviation) minutes of walking/day. The severity of motor fluctuations did not influence the mean time spent walking (B = 2.4 ± 1.9, p = 0.20), but higher age (B = -1.3 ± 0.3, p = < 0.001) and greater severity of motor symptoms (B = -0.6 ± 0.2, p < 0.001) was associated with less time spent walking (F(3216) = 14.6, p < .001, R 2  = .17). The severity of fluctuations was not associated with the amount of change in time spent walking in relation to levodopa intake in any part of the day. Analysis of sensor-derived gait quantity suggests that the severity of motor fluctuations is not associated with changes in real-life walking patterns in mildly to moderate affected PWP. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Multisite Study of an Implanted Continuous Glucose Sensor Over 90 Days in Patients With Diabetes Mellitus.

PubMed

Dehennis, Andrew; Mortellaro, Mark A; Ioacara, Sorin

2015-07-29

Continuous glucose monitoring (CGM), which enables real-time glucose display and trend information as well as real-time alarms, can improve glycemic control and quality of life in patients with diabetes mellitus. Previous reports have described strategies to extend the useable lifetime of a single sensor from 1-2 weeks to 28 days. The present multisite study describes the characterization of a sensing platform achieving 90 days of continuous use for a single, fully implanted sensor. The Senseonics CGM system is composed of a long-term implantable glucose sensor and a wearable smart transmitter. Study subjects underwent subcutaneous implantation of sensors in the upper arm. Eight-hour clinic sessions were performed every 14 days, during which sensor glucose values were compared against venous blood lab reference measurements collected every 15 minutes using mean absolute relative differences (MARDs). All subjects (mean ± standard deviation age: 43.5 ± 11.0 years; with 10 sensors inserted in men and 14 in women) had type 1 diabetes mellitus. Most (22 of 24) sensors reported glucose values for the entire 90 days. The MARD value was 11.4 ± 2.7% (range, 8.1-19.5%) for reference glucose values between 40-400 mg/dl. There was no significant difference in MARD throughout the 90-day study (P = .31). No serious adverse events were noted. The Senseonics CGM, composed of an implantable sensor, external smart transmitter, and smartphone app, is the first system that uses a single sensor for continuous display of accurate glucose values for 3 months. © 2015 Diabetes Technology Society.

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

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.

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

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.

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.

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

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.

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.

A training approach to improve stepping automaticity while dual-tasking in Parkinson's disease: A prospective pilot study.

PubMed

Chomiak, Taylor; Watts, Alexander; Meyer, Nicole; Pereira, Fernando V; Hu, Bin

2017-02-01

Deficits in motor movement automaticity in Parkinson's disease (PD), especially during multitasking, are early and consistent hallmarks of cognitive function decline, which increases fall risk and reduces quality of life. This study aimed to test the feasibility and potential efficacy of a wearable sensor-enabled technological platform designed for an in-home music-contingent stepping-in-place (SIP) training program to improve step automaticity during dual-tasking (DT). This was a 4-week prospective intervention pilot study. The intervention uses a sensor system and algorithm that runs off the iPod Touch which calculates step height (SH) in real-time. These measurements were then used to trigger auditory (treatment group, music; control group, radio podcast) playback in real-time through wireless headphones upon maintenance of repeated large amplitude stepping. With small steps or shuffling, auditory playback stops, thus allowing participants to use anticipatory motor control to regain positive feedback. Eleven participants were recruited from an ongoing trial (Trial Number: ISRCTN06023392). Fear of falling (FES-I), general cognitive functioning (MoCA), self-reported freezing of gait (FOG-Q), and DT step automaticity were evaluated. While we found no significant effect of training on FES-I, MoCA, or FOG-Q, we did observe a significant group (music vs podcast) by training interaction in DT step automaticity (P<0.01). Wearable device technology can be used to enable musically-contingent SIP training to increase motor automaticity for people living with PD. The training approach described here can be implemented at home to meet the growing demand for self-management of symptoms by patients.

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

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.

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.

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 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.

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

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.

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).

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 carbon nanotube based dry-electrodes for electrophysiological sensors

NASA Astrophysics Data System (ADS)

Kang, Byeong-Cheol; Ha, Tae-Jun

2018-05-01

In this paper, we demonstrate all-solution-processed carbon nanotube (CNT) dry-electrodes for the detection of electrophysiological signals such as electrocardiograms (ECG) and electromyograms (EMG). The key parameters of P, Q, R, S, and T peaks are successfully extracted by such CNT based dry-electrodes, which is comparable with conventional silver/chloride (Ag/AgCl) wet-electrodes with a conducting gel film for the ECG recording. Furthermore, the sensing performance of CNT based dry-electrodes is secured during the bending test of 200 cycles, which is essential for wearable electrophysiological sensors in a non-invasive method on human skin. We also investigate the application of wearable CNT based dry-electrodes directly attached to the human skins such as forearm for sensing the electrophysiological signals. The accurate and rapid sensing response can be achieved by CNT based dry-electrodes to supervise the health condition affected by excessive physical movements during the real-time measurements.

3D electrode localization on wireless sensor networks for wearable BCI.

PubMed

Figueiredo, C P; Dias, N S; Hoffmann, K P; Mendes, P M

2008-01-01

This paper presents a solution for electrode localization on wearable BCI radio-enabled electrodes. Electrode positioning is a common issue in any electrical physiological recording. Although wireless node localization is a very active research topic, a precise method with few centimeters of range and a resolution in the order of millimeters is still to be found, since far-field measurements are very prone to error. The calculation of 3D coordinates for each electrode is based on anchorless range-based localization algorithms such as Multidimensional Scaling and Self-Positioning Algorithm. The implemented solution relies on the association of a small antenna to measure the magnetic field and a microcontroller to each electrode, which will be part of the wireless sensor network module. The implemented solution is suitable for EEG applications, namely the wearable BCI, with expected range of 20 cm and resolution of 5 mm.

Domain Adaptation Methods for Improving Lab-to-field Generalization of Cocaine Detection using Wearable ECG.

PubMed

Natarajan, Annamalai; Angarita, Gustavo; Gaiser, Edward; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin M

2016-09-01

Mobile health research on illicit drug use detection typically involves a two-stage study design where data to learn detectors is first collected in lab-based trials, followed by a deployment to subjects in a free-living environment to assess detector performance. While recent work has demonstrated the feasibility of wearable sensors for illicit drug use detection in the lab setting, several key problems can limit lab-to-field generalization performance. For example, lab-based data collection often has low ecological validity, the ground-truth event labels collected in the lab may not be available at the same level of temporal granularity in the field, and there can be significant variability between subjects. In this paper, we present domain adaptation methods for assessing and mitigating potential sources of performance loss in lab-to-field generalization and apply them to the problem of cocaine use detection from wearable electrocardiogram sensor data.

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.

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.

Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults.

PubMed

Schwenk, Michael; Grewal, Gurtej S; Honarvar, Bahareh; Schwenk, Stefanie; Mohler, Jane; Khalsa, Dharma S; Najafi, Bijan

2014-12-13

Wearable sensor technology can accurately measure body motion and provide incentive feedback during exercising. The aim of this pilot study was to evaluate the effectiveness and user experience of a balance training program in older adults integrating data from wearable sensors into a human-computer interface designed for interactive training. Senior living community residents (mean age 84.6) with confirmed fall risk were randomized to an intervention (IG, n = 17) or control group (CG, n = 16). The IG underwent 4 weeks (twice a week) of balance training including weight shifting and virtual obstacle crossing tasks with visual/auditory real-time joint movement feedback using wearable sensors. The CG received no intervention. Outcome measures included changes in center of mass (CoM) sway, ankle and hip joint sway measured during eyes open (EO) and eyes closed (EC) balance test at baseline and post-intervention. Ankle-hip postural coordination was quantified by a reciprocal compensatory index (RCI). Physical performance was quantified by the Alternate-Step-Test (AST), Timed-up-and-go (TUG), and gait assessment. User experience was measured by a standardized questionnaire. After the intervention sway of CoM, hip, and ankle were reduced in the IG compared to the CG during both EO and EC condition (p = .007-.042). Improvement was obtained for AST (p = .037), TUG (p = .024), fast gait speed (p = . 010), but not normal gait speed (p = .264). Effect sizes were moderate for all outcomes. RCI did not change significantly. Users expressed a positive training experience including fun, safety, and helpfulness of sensor-feedback. Results of this proof-of-concept study suggest that older adults at risk of falling can benefit from the balance training program. Study findings may help to inform future exercise interventions integrating wearable sensors for guided game-based training in home- and community environments. Future studies should evaluate the added value of the proposed sensor-based training paradigm compared to traditional balance training programs and commercial exergames. http://www.clinicaltrials.govNCT02043834.

The usefulness and actual use of wearable devices among the elderly population.

PubMed

Kekade, Shwetambara; Hseieh, Chung-Ho; Islam, Md Mohaimenul; Atique, Suleman; Mohammed Khalfan, Abdulwahed; Li, Yu-Chuan; Abdul, Shabbir Syed

2018-01-01

Elderly populations are more prone to diseases and need continuous monitoring of parameters to ensure good health. Wearable devices (WDs) can be helpful in the early detection and management of medical conditions. However, less is known about the use of currently available WDs among elderly populations. The objectives of this study were to determine the usefulness and actual use of wearable devices among the elderly population. Our methodology was based on a systematic review and a survey questionnaire. In the systematic review, search was conducted in four databases PubMed, MDPI, Sage, and Scopus with search terms "wearable device" and "elderly", "wearable sensor" and "elderly". The inclusion criteria were the studies which described health-related wearable devices, its use as the outcome, conducted on a minimum of ten participants and published in the last five years. The survey was conducted on the MOOCs (Massive Open Online Course) platform. The questionnaire was related to the use of technology, intention to use, security and privacy concerns, and willingness to pay. The review identified 4915 articles, of which, 31 studies eventually met the inclusion criteria. All studies reported positive impacts after assessing devices, despite certain drawbacks. The majority of the samples were males. The survey revealed responses from 233 individuals out of the 1100 participants of the course. The survey results were categorized into two age groups: 54.3% were elderly (>65 years) and 45.49% were non-elderly (≤65 years). Very few elderly people were currently using WD. More than 60% of elderly people were interested in the future use of wearable devices, and preferred future use to improve physical and mental activities. A majority of the respondents were female. This study suggests awareness should be created among elderly populations regarding the use of WDs for the early detection and prevention of complications and emergencies. Elderly populations are more prone to benefits from using WDs. The review concluded that devices should be tested on elderly groups as well, considering sex equality, and on both healthy and sick participants for better insights. The survey determined the elderly as frequent users of technology, but lack of knowledge of WD and demonstrated female interest in the use of WD. In future research on WDs, it is suggested that clinical studies be conducted for longer durations, and standard protocols such as age and sex equality should be considered. Requirements from both users and physicians should be acknowledged for better cognizance of WDs. Copyright © 2017 Elsevier B.V. All rights reserved.

Solution-Processed Metal Coating to Nonwoven Fabrics for Wearable Rechargeable Batteries.

PubMed

Lee, Kyulin; Choi, Jin Hyeok; Lee, Hye Moon; Kim, Ki Jae; Choi, Jang Wook

2017-12-27

Wearable rechargeable batteries require electrode platforms that can withstand various physical motions, such as bending, folding, and twisting. To this end, conductive textiles and paper have been highlighted, as their porous structures can accommodate the stress built during various physical motions. However, fabrics with plain weaves or knit structures have been mostly adopted without exploration of nonwoven counterparts. Also, the integration of conductive materials, such as carbon or metal nanomaterials, to achieve sufficient conductivity as current collectors is not well-aligned with large-scale processing in terms of cost and quality control. Here, the superiority of nonwoven fabrics is reported in electrochemical performance and bending capability compared to currently dominant woven counterparts, due to smooth morphology near the fiber intersections and the homogeneous distribution of fibers. Moreover, solution-processed electroless deposition of aluminum and nickel-copper composite is adopted for cathodes and anodes, respectively, demonstrating the large-scale feasibility of conductive nonwoven platforms for wearable rechargeable batteries. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of Fabric-Based Chemical Gas Sensors for Use as Wearable Electronic Noses

PubMed Central

Seesaard, Thara; Lorwongtragool, Panida; Kerdcharoen, Teerakiat

2015-01-01

Novel gas sensors embroidered into fabric substrates based on polymers/ SWNT-COOH nanocomposites were proposed in this paper, aiming for their use as a wearable electronic nose (e-nose). The fabric-based chemical gas sensors were fabricated by two main processes: drop coating and embroidery. Four potential polymers (PVC, cumene-PSMA, PSE and PVP)/functionalized-SWCNT sensing materials were deposited onto interdigitated electrodes previously prepared by embroidering conductive thread on a fabric substrate to make an optimal set of sensors. After preliminary trials of the obtained sensors, it was found that the sensors yielded a electrical resistance in the region of a few kilo-Ohms. The sensors were tested with various volatile compounds such as ammonium hydroxide, ethanol, pyridine, triethylamine, methanol and acetone, which are commonly found in the wastes released from the human body. These sensors were used to detect and discriminate between the body odors of different regions and exist in various forms such as the urine, armpit and exhaled breath odor. Based on a simple pattern recognition technique, we have shown that the proposed fabric-based chemical gas sensors can discriminate the human body odor from two persons. PMID:25602265

Development of fabric-based chemical gas sensors for use as wearable electronic noses.

PubMed

Seesaard, Thara; Lorwongtragool, Panida; Kerdcharoen, Teerakiat

2015-01-16

Novel gas sensors embroidered into fabric substrates based on polymers/ SWNT-COOH nanocomposites were proposed in this paper, aiming for their use as a wearable electronic nose (e-nose). The fabric-based chemical gas sensors were fabricated by two main processes: drop coating and embroidery. Four potential polymers (PVC, cumene-PSMA, PSE and PVP)/functionalized-SWCNT sensing materials were deposited onto interdigitated electrodes previously prepared by embroidering conductive thread on a fabric substrate to make an optimal set of sensors. After preliminary trials of the obtained sensors, it was found that the sensors yielded a electrical resistance in the region of a few kilo-Ohms. The sensors were tested with various volatile compounds such as ammonium hydroxide, ethanol, pyridine, triethylamine, methanol and acetone, which are commonly found in the wastes released from the human body. These sensors were used to detect and discriminate between the body odors of different regions and exist in various forms such as the urine, armpit and exhaled breath odor. Based on a simple pattern recognition technique, we have shown that the proposed fabric-based chemical gas sensors can discriminate the human body odor from two persons.

Wearable Platform for Real-time Monitoring of Sodium in Sweat.

PubMed

McCaul, Margaret; Porter, Adam; Barrett, Ruairi; White, Paddy; Stroiescu, Florien; Wallace, Gordon; Diamond, Dermot

2018-06-19

A fully integrated and wearable platform for harvesting and analysing sweat sodium concentration in real time during exercise has been developed and tested. The platform was largely produced using 3D printing, which greatly simplifies fabrication and operation compared to previous versions generated with traditional production techniques. The 3D printed platform doubles the capacity of the sample storage reservoir to about 1.3 ml, reduces the assembly time and provides simple and precise component alignment and contact of the integrated solid-state ion-selective and reference electrodes with the sorbent material. The sampling flowrate in the device can be controlled by introducing threads to enhance wicking of sweat from the skin, across the electrodes to the storage area. The platform was characterised in the lab and in exercise trials over a period of about 60 minutes continuous monitoring. Sweat sodium concentration was found to rise initially to approximately 17 mM and decline gradually over the period of the trial to about 11-12 mM. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Roll-to-Roll Gravure Printed Electrochemical Sensors for Wearable and Medical Devices.

PubMed

Bariya, Mallika; Shahpar, Ziba; Park, Hyejin; Sun, Junfeng; Jung, Younsu; Gao, Wei; Nyein, Hnin Yin Yin; Liaw, Tiffany Sun; Tai, Li-Chia; Ngo, Quynh P; Chao, Minghan; Zhao, Yingbo; Hettick, Mark; Cho, Gyoujin; Javey, Ali

2018-06-25

As recent developments in noninvasive biosensors spearhead the thrust toward personalized health and fitness monitoring, there is a need for high throughput, cost-effective fabrication of flexible sensing components. Toward this goal, we present roll-to-roll (R2R) gravure printed electrodes that are robust under a range of electrochemical sensing applications. We use inks and electrode morphologies designed for electrochemical and mechanical stability, achieving devices with uniform redox kinetics printed on 150 m flexible substrate rolls. We show that these electrodes can be functionalized into consistently high performing sensors for detecting ions, metabolites, heavy metals, and other small molecules in noninvasively accessed biofluids, including sensors for real-time, in situ perspiration monitoring during exercise. This development of robust and versatile R2R gravure printed electrodes represents a key translational step in enabling large-scale, low-cost fabrication of disposable wearable sensors for personalized health monitoring applications.

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.

Relationships between full-day arm movement characteristics and developmental status in infants with typical development as they learn to reach: An observational study

PubMed Central

Shida-Tokeshi, Joanne; Lane, Christianne J.; Trujillo-Priego, Ivan A.; Deng, Weiyang; Vanderbilt, Douglas L.; Loeb, Gerald E.; Smith, Beth A.

2018-01-01

Background: Advances in wearable sensor technology now allow us to quantify the number, type and kinematic characteristics of bouts of infant arm movement made across a full day in the natural environment. Our aim here was to determine whether the amount and kinematic characteristics of arm movements made across the day in the natural environment were related to developmental status in infants with typical development as they learned to reach for objects using their arms. Methods: We used wearable sensors to measure arm movement across days and months as infants developed arm reaching skills. In total, 22 infants with typical development participated, aged between 38 and 203 days. Of the participants, 2 infants were measured once and the other 20 infants were measured once per month for 3 to 6 visits. The Bayley Scales of Infant Development was used to measure developmental level. Results: Our main findings were: 1) infant arm movement characteristics as measured by full-day wearable sensor data were related to Bayley motor, cognitive and language scores, indicating a relationship between daily movement characteristics and developmental status; 2) infants who moved more had larger increases in language and cognitive scores across visits; and 3) larger changes in movement characteristics across visits were related to higher motor scores. Conclusions: This was a preliminary, exploratory, small study of the potential importance of infant arm movement characteristics as measured by full-day wearable sensor data. Our results support full-day arm movement activity as an area of interest for future study as a biomarker of neurodevelopmental status and as a target for early intervention. PMID:29708221

Ultrasensitive Wearable Soft Strain Sensors of Conductive, Self-healing, and Elastic Hydrogels with Synergistic "Soft and Hard" Hybrid Networks.

PubMed

Liu, Yan-Jun; Cao, Wen-Tao; Ma, Ming-Guo; Wan, Pengbo

2017-08-02

Robust, stretchable, and strain-sensitive hydrogels have recently attracted immense research interest because of their potential application in wearable strain sensors. The integration of the synergistic characteristics of decent mechanical properties, reliable self-healing capability, and high sensing sensitivity for fabricating conductive, elastic, self-healing, and strain-sensitive hydrogels is still a great challenge. Inspired by the mechanically excellent and self-healing biological soft tissues with hierarchical network structures, herein, functional network hydrogels are fabricated by the interconnection between a "soft" homogeneous polymer network and a "hard" dynamic ferric (Fe 3+ ) cross-linked cellulose nanocrystals (CNCs-Fe 3+ ) network. Under stress, the dynamic CNCs-Fe 3+ coordination bonds act as sacrificial bonds to efficiently dissipate energy, while the homogeneous polymer network leads to a smooth stress-transfer, which enables the hydrogels to achieve unusual mechanical properties, such as excellent mechanical strength, robust toughness, and stretchability, as well as good self-recovery property. The hydrogels demonstrate autonomously self-healing capability in only 5 min without the need of any stimuli or healing agents, ascribing to the reorganization of CNCs and Fe 3+ via ionic coordination. Furthermore, the resulted hydrogels display tunable electromechanical behavior with sensitive, stable, and repeatable variations in resistance upon mechanical deformations. Based on the tunable electromechanical behavior, the hydrogels can act as a wearable strain sensor to monitor finger joint motions, breathing, and even the slight blood pulse. This strategy of building synergistic "soft and hard" structures is successful to integrate the decent mechanical properties, reliable self-healing capability, and high sensing sensitivity together for assembling a high-performance, flexible, and wearable strain sensor.

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.

Remotely Delivered Exercise-Based Cardiac Rehabilitation: Design and Content Development of a Novel mHealth Platform.

PubMed

Rawstorn, Jonathan C; Gant, Nicholas; Meads, Andrew; Warren, Ian; Maddison, Ralph

2016-06-24

Participation in traditional center-based cardiac rehabilitation exercise programs (exCR) is limited by accessibility barriers. Mobile health (mHealth) technologies can overcome these barriers while preserving critical attributes of center-based exCR monitoring and coaching, but these opportunities have not yet been capitalized on. We aimed to design and develop an evidence- and theory-based mHealth platform for remote delivery of exCR to any geographical location. An iterative process was used to design and develop an evidence- and theory-based mHealth platform (REMOTE-CR) that provides real-time remote exercise monitoring and coaching, behavior change education, and social support. The REMOTE-CR platform comprises a commercially available smartphone and wearable sensor, custom smartphone and Web-based applications (apps), and a custom middleware. The platform allows exCR specialists to monitor patients' exercise and provide individualized coaching in real-time, from almost any location, and provide behavior change education and social support. Intervention content incorporates Social Cognitive Theory, Self-determination Theory, and a taxonomy of behavior change techniques. Exercise components are based on guidelines for clinical exercise prescription. The REMOTE-CR platform extends the capabilities of previous telehealth exCR platforms and narrows the gap between existing center- and home-based exCR services. REMOTE-CR can complement center-based exCR by providing an alternative option for patients whose needs are not being met. Remotely monitored exCR may be more cost-effective than establishing additional center-based programs. The effectiveness and acceptability of REMOTE-CR are now being evaluated in a noninferiority randomized controlled trial.

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

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

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.

Bio-assembled, piezoelectric prawn shell made self-powered wearable sensor for non-invasive physiological signal monitoring

NASA Astrophysics Data System (ADS)

Ghosh, Sujoy Kumar; Mandal, Dipankar

2017-03-01

A human interactive self-powered wearable sensor is designed using waste by-product prawn shells. The structural origin of intrinsic piezoelectric characteristics of bio-assembled chitin nanofibers has been investigated. It allows the prawn shell to make a tactile sensor that performs also as a highly durable mechanical energy harvester/nanogenerator. The feasibility and fundamental physics of self-powered consumer electronics even from human perception is highlighted by prawn shells made nanogenerator (PSNG). High fidelity and non-invasive monitoring of vital signs, such as radial artery pulse wave and coughing actions, may lead to the potential use of PSNG for early intervention. It is presumed that PSNG has enormous future aspects in real-time as well as remote health care assessment.

Wearable sensors in intelligent clothing for measuring human body temperature based on optical fiber Bragg grating.

PubMed

Li, Hongqiang; Yang, Haijing; Li, Enbang; Liu, Zhihui; Wei, Kejia

2012-05-21

Measuring body temperature is considerably important to physiological studies as well as clinical investigations. In recent years, numerous observations have been reported and various methods of measurement have been employed. The present paper introduces a novel wearable sensor in intelligent clothing for human body temperature measurement. The objective is the integration of optical fiber Bragg grating (FBG)-based sensors into functional textiles to extend the capabilities of wearable solutions for body temperature monitoring. In addition, the temperature sensitivity is 150 pm/°C, which is almost 15 times higher than that of a bare FBG. This study combines large and small pipes during fabrication to implant FBG sensors into the fabric. The law of energy conservation of the human body is considered in determining heat transfer between the body and its clothing. The mathematical model of heat transmission between the body and clothed FBG sensors is studied, and the steady-state thermal analysis is presented. The simulation results show the capability of the material to correct the actual body temperature. Based on the skin temperature obtained by the weighted average method, this paper presents the five points weighted coefficients model using both sides of the chest, armpits, and the upper back for the intelligent clothing. The weighted coefficients of 0.0826 for the left chest, 0.3706 for the left armpit, 0.3706 for the right armpit, 0.0936 for the upper back, and 0.0826 for the right chest were obtained using Cramer's Rule. Using the weighting coefficient, the deviation of the experimental result was ± 0.18 °C, which favors the use for clinical armpit temperature monitoring. Moreover, in special cases when several FBG sensors are broken, the weighted coefficients of the other sensors could be changed to obtain accurate body temperature.

Scalable Production of Graphene-Based Wearable E-Textiles

PubMed Central

2017-01-01

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. PMID:29185706

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.

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.

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

Lightweight, Wearable, Metal Rubber Sensor

NASA Technical Reports Server (NTRS)

Hill, Andrea

2015-01-01

For autonomous health monitoring. NanoSonic, Inc., has developed comfortable garments with multiple integrated sensors designed to monitor astronaut health throughout long-duration space missions. The combined high electrical conductivity, low mechanical modulus, and environmental robustness of the sensors make them an effective, lightweight, and comfortable alternative to conventional use of metal wiring and cabling.

One size fits all electronics for insole-based activity monitoring.

PubMed

Hegde, Nagaraj; Bries, Matthew; Melanson, Edward; Sazonov, Edward

2017-07-01

Footwear based wearable sensors are becoming prominent in many areas of monitoring health and wellness, such as gait and activity monitoring. In our previous research we introduced an insole based wearable system SmartStep, which is completely integrated in a socially acceptable package. From a manufacturing perspective, SmartStep's electronics had to be custom made for each shoe size, greatly complicating the manufacturing process. In this work we explore the possibility of making a universal electronics platform for SmartStep - SmartStep 3.0, which can be used in the most common insole sizes without modifications. A pilot human subject experiments were run to compare the accuracy between the one-size fits all (SmartStep 3.0) and custom size SmartStep 2.0. A total of ~10 hours of data was collected in the pilot study involving three participants performing different activities of daily living while wearing SmartStep 2.0 and SmartStep 3.0. Leave one out cross validation resulted in a 98.5% average accuracy from SmartStep 2.0, while SmartStep 3.0 resulted in 98.3% accuracy, suggesting that the SmartStep 3.0 can be as accurate as SmartStep 2.0, while fitting most common shoe sizes.

Recent Progress of Textile-Based Wearable Electronics: A Comprehensive Review of Materials, Devices, and Applications.

PubMed

Heo, Jae Sang; Eom, Jimi; Kim, Yong-Hoon; Park, Sung Kyu

2018-01-01

Wearable electronics are emerging as a platform for next-generation, human-friendly, electronic devices. A new class of devices with various functionality and amenability for the human body is essential. These new conceptual devices are likely to be a set of various functional devices such as displays, sensors, batteries, etc., which have quite different working conditions, on or in the human body. In these aspects, electronic textiles seem to be a highly suitable possibility, due to the unique characteristics of textiles such as being light weight and flexible and their inherent warmth and the property to conform. Therefore, e-textiles have evolved into fiber-based electronic apparel or body attachable types in order to foster significant industrialization of the key components with adaptable formats. Although the advances are noteworthy, their electrical performance and device features are still unsatisfactory for consumer level e-textile systems. To solve these issues, innovative structural and material designs, and novel processing technologies have been introduced into e-textile systems. Recently reported and significantly developed functional materials and devices are summarized, including their enhanced optoelectrical and mechanical properties. Furthermore, the remaining challenges are discussed, and effective strategies to facilitate the full realization of e-textile systems are suggested. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interoperability and security in wireless body area network infrastructures.

PubMed

Warren, Steve; Lebak, Jeffrey; Yao, Jianchu; Creekmore, Jonathan; Milenkovic, Aleksandar; Jovanov, Emil

2005-01-01

Wireless body area networks (WBANs) and their supporting information infrastructures offer unprecedented opportunities to monitor state of health without constraining the activities of a wearer. These mobile point-of-care systems are now realizable due to the convergence of technologies such as low-power wireless communication standards, plug-and-play device buses, off-the-shelf development kits for low-power microcontrollers, handheld computers, electronic medical records, and the Internet. To increase acceptance of personal monitoring technology while lowering equipment cost, advances must be made in interoperability (at both the system and device levels) and security. This paper presents an overview of WBAN infrastructure work in these areas currently underway in the Medical Component Design Laboratory at Kansas State University (KSU) and at the University of Alabama in Huntsville (UAH). KSU efforts include the development of wearable health status monitoring systems that utilize ISO/IEEE 11073, Bluetooth, Health Level 7, and OpenEMed. WBAN efforts at UAH include the development of wearable activity and health monitors that incorporate ZigBee-compliant wireless sensor platforms with hardware-level encryption and the TinyOS development environment. WBAN infrastructures are complex, requiring many functional support elements. To realize these infrastructures through collaborative efforts, organizations such as KSU and UAH must define and utilize standard interfaces, nomenclature, and security approaches.

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

Telehealth in older adults with cancer in the United States: The emerging use of wearable sensors.

PubMed

Shen, John; Naeim, Arash

2017-11-01

As the aging and cancer populations in the world continue to increase, the need for complements to traditional geriatric assessments and the logical incorporation of fast and reliable telehealth tools have become interlinked. In the United States, studies examining the use of telehealth for chronic disease management have shown promising results in small groups. The implementation of health technology on a broader scale requires older adults to both accept and adapt such innovation into routine medical care. Though the commercial and recreational use of new technology has increased in older individuals, the transition into creating a smart and connected home that can interface with both patients and healthcare professionals is in its early phases. Current limitations include an inherent digital divide, as well as concerns regarding privacy, data volume, rapid change, cost and reimbursement. The emergence of low-cost, high-fidelity wearable sensors with a spectrum of clinical utility may be the key to increased use and adaptation by older adults. An opportunity to utilize wearable sensors for objective and real-time assessment of older patients with cancer for baseline functional status and treatment toxicity may be on the horizon. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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

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

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

PlaIMoS: A Remote Mobile Healthcare Platform to Monitor Cardiovascular and Respiratory Variables

PubMed Central

Miramontes, Ramses; Aquino, Raúl; Flores, Arturo; Rodríguez, Guillermo; Anguiano, Rafael; Ríos, Arturo; Edwards, Arthur

2017-01-01

The number of elderly and chronically ill patients has grown significantly over the past few decades as life expectancy has increased worldwide, leading to increased demands on the health care system and significantly taxing traditional health care practices. Consequently, there is an urgent need to use technology to innovate and more constantly and intensely monitor, report and analyze critical patient physiological parameters beyond conventional clinical settings in a more efficient and cost effective manner. This paper presents a technological platform called PlaIMoS which consists of wearable sensors, a fixed measurement station, a network infrastructure that employs IEEE 802.15.4 and IEEE 802.11 to transmit data with security mechanisms, a server to analyze all information collected and apps for iOS, Android and Windows 10 mobile operating systems to provide real-time measurements. The developed architecture, designed primarily to record and report electrocardiogram and heart rate data, also monitors parameters associated with chronic respiratory illnesses, including patient blood oxygen saturation and respiration rate, body temperature, fall detection and galvanic resistance. PMID:28106832

PlaIMoS: A Remote Mobile Healthcare Platform to Monitor Cardiovascular and Respiratory Variables.

PubMed

Miramontes, Ramses; Aquino, Raúl; Flores, Arturo; Rodríguez, Guillermo; Anguiano, Rafael; Ríos, Arturo; Edwards, Arthur

2017-01-19

The number of elderly and chronically ill patients has grown significantly over the past few decades as life expectancy has increased worldwide, leading to increased demands on the health care system and significantly taxing traditional health care practices. Consequently, there is an urgent need to use technology to innovate and more constantly and intensely monitor, report and analyze critical patient physiological parameters beyond conventional clinical settings in a more efficient and cost effective manner. This paper presents a technological platform called PlaIMoS which consists of wearable sensors, a fixed measurement station, a network infrastructure that employs IEEE 802.15.4 and IEEE 802.11 to transmit data with security mechanisms, a server to analyze all information collected and apps for iOS, Android and Windows 10 mobile operating systems to provide real-time measurements. The developed architecture, designed primarily to record and report electrocardiogram and heart rate data, also monitors parameters associated with chronic respiratory illnesses, including patient blood oxygen saturation and respiration rate, body temperature, fall detection and galvanic resistance.

QuantifyMe: An Open-Source Automated Single-Case Experimental Design Platform.

PubMed

Taylor, Sara; Sano, Akane; Ferguson, Craig; Mohan, Akshay; Picard, Rosalind W

2018-04-05

Smartphones and wearable sensors have enabled unprecedented data collection, with many products now providing feedback to users about recommended step counts or sleep durations. However, these recommendations do not provide personalized insights that have been shown to be best suited for a specific individual. A scientific way to find individualized recommendations and causal links is to conduct experiments using single-case experimental design; however, properly designed single-case experiments are not easy to conduct on oneself. We designed, developed, and evaluated a novel platform, QuantifyMe, for novice self-experimenters to conduct proper-methodology single-case self-experiments in an automated and scientific manner using their smartphones. We provide software for the platform that we used (available for free on GitHub), which provides the methodological elements to run many kinds of customized studies. In this work, we evaluate its use with four different kinds of personalized investigations, examining how variables such as sleep duration and regularity, activity, and leisure time affect personal happiness, stress, productivity, and sleep efficiency. We conducted a six-week pilot study ( N = 13) to evaluate QuantifyMe. We describe the lessons learned developing the platform and recommendations for its improvement, as well as its potential for enabling personalized insights to be scientifically evaluated in many individuals, reducing the high administrative cost for advancing human health and wellbeing.

QuantifyMe: An Open-Source Automated Single-Case Experimental Design Platform †

PubMed Central

Sano, Akane; Ferguson, Craig; Mohan, Akshay; Picard, Rosalind W.

2018-01-01

Smartphones and wearable sensors have enabled unprecedented data collection, with many products now providing feedback to users about recommended step counts or sleep durations. However, these recommendations do not provide personalized insights that have been shown to be best suited for a specific individual. A scientific way to find individualized recommendations and causal links is to conduct experiments using single-case experimental design; however, properly designed single-case experiments are not easy to conduct on oneself. We designed, developed, and evaluated a novel platform, QuantifyMe, for novice self-experimenters to conduct proper-methodology single-case self-experiments in an automated and scientific manner using their smartphones. We provide software for the platform that we used (available for free on GitHub), which provides the methodological elements to run many kinds of customized studies. In this work, we evaluate its use with four different kinds of personalized investigations, examining how variables such as sleep duration and regularity, activity, and leisure time affect personal happiness, stress, productivity, and sleep efficiency. We conducted a six-week pilot study (N = 13) to evaluate QuantifyMe. We describe the lessons learned developing the platform and recommendations for its improvement, as well as its potential for enabling personalized insights to be scientifically evaluated in many individuals, reducing the high administrative cost for advancing human health and wellbeing. PMID:29621133

A Textile-Based Wearable Sensing Device Designed for Monitoring the Flexion Angle of Elbow and Knee Movements

PubMed Central

Shyr, Tien-Wei; Shie, Jing-Wen; Jiang, Chang-Han; Li, Jung-Jen

2014-01-01

In this work a wearable gesture sensing device consisting of a textile strain sensor, using elastic conductive webbing, was designed for monitoring the flexion angle of elbow and knee movements. The elastic conductive webbing shows a linear response of resistance to the flexion angle. The wearable gesture sensing device was calibrated and then the flexion angle-resistance equation was established using an assembled gesture sensing apparatus with a variable resistor and a protractor. The proposed device successfully monitored the flexion angle during elbow and knee movements. PMID:24577526

Dedicated cardiac rehabilitation wearable sensor and its clinical potential.

PubMed

Lee, Hooseok; Chung, Heewon; Ko, Hoon; Jeong, Changwon; Noh, Se-Eung; Kim, Chul; Lee, Jinseok

2017-01-01

We describe a wearable sensor developed for cardiac rehabilitation (CR) exercise. To effectively guide CR exercise, the dedicated CR wearable sensor (DCRW) automatically recommends the exercise intensity to the patient by comparing heart rate (HR) measured in real time with a predefined target heart rate zone (THZ) during exercise. The CR exercise includes three periods: pre-exercise, exercise with intensity guidance, and post-exercise. In the pre-exercise period, information such as THZ, exercise type, exercise stage order, and duration of each stage are set up through a smartphone application we developed for iPhones and Android devices. The set-up information is transmitted to the DCRW via Bluetooth communication. In the period of exercise with intensity guidance, the DCRW continuously estimates HR using a reflected pulse signal in the wrist. To achieve accurate HR measurements, we used multichannel photo sensors and increased the chances of acquiring a clean signal. Subsequently, we used singular value decomposition (SVD) for de-noising. For the median and variance of RMSEs in the measured HRs, our proposed method with DCRW provided lower values than those from a single channel-based method and template-based multiple-channel method for the entire exercise stage. In the post-exercise period, the DCRW transmits all the measured HR data to the smartphone application via Bluetooth communication, and the patient can monitor his/her own exercise history.

Designing Metallic and Insulating Nanocrystal Heterostructures to Fabricate Highly Sensitive and Solution Processed Strain Gauges for Wearable Sensors.

PubMed

Lee, Woo Seok; Lee, Seung-Wook; Joh, Hyungmok; Seong, Mingi; Kim, Haneun; Kang, Min Su; Cho, Ki-Hyun; Sung, Yun-Mo; Oh, Soong Ju

2017-12-01

All-solution processed, high-performance wearable strain sensors are demonstrated using heterostructure nanocrystal (NC) solids. By incorporating insulating artificial atoms of CdSe quantum dot NCs into metallic artificial atoms of Au NC thin film matrix, metal-insulator heterostructures are designed. This hybrid structure results in a shift close to the percolation threshold, modifying the charge transport mechanism and enhancing sensitivity in accordance with the site percolation theory. The number of electrical pathways is also manipulated by creating nanocracks to further increase its sensitivity, inspired from the bond percolation theory. The combination of the two strategies achieves gauge factor up to 5045, the highest sensitivity recorded among NC-based strain gauges. These strain sensors show high reliability, durability, frequency stability, and negligible hysteresis. The fundamental charge transport behavior of these NC solids is investigated and the combined site and bond percolation theory is developed to illuminate the origin of their enhanced sensitivity. Finally, all NC-based and solution-processed strain gauge sensor arrays are fabricated, which effectively measure the motion of each finger joint, the pulse of heart rate, and the movement of vocal cords of human. This work provides a pathway for designing low-cost and high-performance electronic skin or wearable devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review

PubMed Central

Rooksby, John; Gray, Cindy M

2018-01-01

Background Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work. Objectives This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. Method An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. Results A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). Conclusions The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines. PMID:29572200

Rapid, low cost prototyping of transdermal devices for personal healthcare monitoring.

PubMed

Sharma, Sanjiv; Saeed, Anwer; Johnson, Christopher; Gadegaard, Nikolaj; Cass, Anthony Eg

2017-04-01

The next generation of devices for personal healthcare monitoring will comprise molecular sensors to monitor analytes of interest in the skin compartment. Transdermal devices based on microneedles offer an excellent opportunity to explore the dynamics of molecular markers in the interstitial fluid, however good acceptability of these next generation devices will require several technical problems associated with current commercially available wearable sensors to be overcome. These particularly include reliability, comfort and cost. An essential pre-requisite for transdermal molecular sensing devices is that they can be fabricated using scalable technologies which are cost effective. We present here a minimally invasive microneedle array as a continuous monitoring platform technology. Method for scalable fabrication of these structures is presented. The microneedle arrays were characterised mechanically and were shown to penetrate human skin under moderate thumb pressure. They were then functionalised and evaluated as glucose, lactate and theophylline biosensors. The results suggest that this technology can be employed in the measurement of metabolites, therapeutic drugs and biomarkers and could have an important role to play in the management of chronic diseases.

Superior Self-Powered Room-Temperature Chemical Sensing with Light-Activated Inorganic Halides Perovskites.

PubMed

Chen, Hongjun; Zhang, Meng; Bo, Renheng; Barugkin, Chog; Zheng, Jianghui; Ma, Qingshan; Huang, Shujuan; Ho-Baillie, Anita W Y; Catchpole, Kylie R; Tricoli, Antonio

2018-02-01

Hybrid halide perovskite is one of the promising light absorber and is intensively investigated for many optoelectronic applications. Here, the first prototype of a self-powered inorganic halides perovskite for chemical gas sensing at room temperature under visible-light irradiation is presented. These devices consist of porous network of CsPbBr 3 (CPB) and can generate an open-circuit voltage of 0.87 V under visible-light irradiation, which can be used to detect various concentrations of O 2 and parts per million concentrations of medically relevant volatile organic compounds such as acetone and ethanol with very quick response and recovery time. It is observed that O 2 gas can passivate the surface trap sites in CPB and the ambipolar charge transport in the perovskite layer results in a distinct sensing mechanism compared with established semiconductors with symmetric electrical response to both oxidizing and reducing gases. The platform of CPB-based gas sensor provides new insights for the emerging area of wearable sensors for personalized and preventive medicine. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

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.

Live Social Semantics

NASA Astrophysics Data System (ADS)

Alani, Harith; Szomszor, Martin; Cattuto, Ciro; van den Broeck, Wouter; Correndo, Gianluca; Barrat, Alain

Social interactions are one of the key factors to the success of conferences and similar community gatherings. This paper describes a novel application that integrates data from the semantic web, online social networks, and a real-world contact sensing platform. This application was successfully deployed at ESWC09, and actively used by 139 people. Personal profiles of the participants were automatically generated using several Web 2.0 systems and semantic academic data sources, and integrated in real-time with face-to-face contact networks derived from wearable sensors. Integration of all these heterogeneous data layers made it possible to offer various services to conference attendees to enhance their social experience such as visualisation of contact data, and a site to explore and connect with other participants. This paper describes the architecture of the application, the services we provided, and the results we achieved in this deployment.

cHRV Uncovering Daily Stress Dynamics Using Bio-Signal from Consumer Wearables.

PubMed

Hao, Tian; Chang, Henry; Ball, Marion; Lin, Kun; Zhu, Xinxin

2017-01-01

Knowing the dynamics of one's daily stress is essential to effective stress management in the context of smart and connected health. However, there lacks a practical and unobtrusive means to obtain real-time and longitudinal stress information. In this paper, we attempt to derive a convenient HRV-based (heart rate variability) biomarker named cHRV, which can be used to reliably reflect stress dynamics. cHRV's key advantage lies in its low maintenance and high practicality. It can be efficiently calculated only using data from photoplethysmography (PPG) sensors, the mainstream heart rate sensor embedded in most of the consumer wearables like Apple Watch. Benefiting from the proliferation of wearables, cHRV is ideal for day-to-day stress monitoring. To evaluate its feasibility and performance, we have conducted 14 in-lab controlled experiments. The result shows that the proposed cHRV has strong correlation with the stress dynamics (r > 0.95), therefore exhibits great potential for continuous stress assessment.

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

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.

A training approach to improve stepping automaticity while dual-tasking in Parkinson's disease

PubMed Central

Chomiak, Taylor; Watts, Alexander; Meyer, Nicole; Pereira, Fernando V.; Hu, Bin

2017-01-01

Abstract Background: Deficits in motor movement automaticity in Parkinson's disease (PD), especially during multitasking, are early and consistent hallmarks of cognitive function decline, which increases fall risk and reduces quality of life. This study aimed to test the feasibility and potential efficacy of a wearable sensor-enabled technological platform designed for an in-home music-contingent stepping-in-place (SIP) training program to improve step automaticity during dual-tasking (DT). Methods: This was a 4-week prospective intervention pilot study. The intervention uses a sensor system and algorithm that runs off the iPod Touch which calculates step height (SH) in real-time. These measurements were then used to trigger auditory (treatment group, music; control group, radio podcast) playback in real-time through wireless headphones upon maintenance of repeated large amplitude stepping. With small steps or shuffling, auditory playback stops, thus allowing participants to use anticipatory motor control to regain positive feedback. Eleven participants were recruited from an ongoing trial (Trial Number: ISRCTN06023392). Fear of falling (FES-I), general cognitive functioning (MoCA), self-reported freezing of gait (FOG-Q), and DT step automaticity were evaluated. Results: While we found no significant effect of training on FES-I, MoCA, or FOG-Q, we did observe a significant group (music vs podcast) by training interaction in DT step automaticity (P<0.01). Conclusion: Wearable device technology can be used to enable musically-contingent SIP training to increase motor automaticity for people living with PD. The training approach described here can be implemented at home to meet the growing demand for self-management of symptoms by patients. PMID:28151878

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.

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.

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.

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.

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.

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 New Proxy Measurement Algorithm with Application to the Estimation of Vertical Ground Reaction Forces Using Wearable Sensors

PubMed Central

Billings, Stephen A.; Pavic, Aleksandar; Guo, Ling-Zhong

2017-01-01

Measurement of the ground reaction forces (GRF) during walking is typically limited to laboratory settings, and only short observations using wearable pressure insoles have been reported so far. In this study, a new proxy measurement method is proposed to estimate the vertical component of the GRF (vGRF) from wearable accelerometer signals. The accelerations are used as the proxy variable. An orthogonal forward regression algorithm (OFR) is employed to identify the dynamic relationships between the proxy variables and the measured vGRF using pressure-sensing insoles. The obtained model, which represents the connection between the proxy variable and the vGRF, is then used to predict the latter. The results have been validated using pressure insoles data collected from nine healthy individuals under two outdoor walking tasks in non-laboratory settings. The results show that the vGRFs can be reconstructed with high accuracy (with an average prediction error of less than 5.0%) using only one wearable sensor mounted at the waist (L5, fifth lumbar vertebra). Proxy measures with different sensor positions are also discussed. Results show that the waist acceleration-based proxy measurement is more stable with less inter-task and inter-subject variability than the proxy measures based on forehead level accelerations. The proposed proxy measure provides a promising low-cost method for monitoring ground reaction forces in real-life settings and introduces a novel generic approach for replacing the direct determination of difficult to measure variables in many applications. PMID:28937593

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.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

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.

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.

Overview of Robotic Devices for Nursing Care Project.

PubMed

Hirukawa, Hirohisa

2017-01-01

METI/AMED are conducting a project on the development and deployment of robotic devices for nursing care to enhance the autonomy of elderly persons and assist care givers. An evaluation protocol is presented and the devices developed in the project are introduced. The devices consist of transfer assist devices (wearable/non-wearable), walking assist devices (outdoor/indoor), safety surveillance sensors (nursing home/private home), bath lift and toilet assist.

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.

The Wearable Motherboard: a flexible information infrastructure or sensate liner for medical applications.

PubMed

Park, S; Gopalsamy, C; Rajamanickam, R; Jayaraman, S

1999-01-01

Research on the design and development of a Sensate Liner for Combat Casualty Care has led to the realization of the world's first Wearable Motherboard or an "intelligent" garment for the 21st Century. This Georgia Tech Wearable Motherboard (GTWM) provides an extremely versatile framework for the incorporation of sensing, monitoring and information processing devices. The principal advantage of GTWM is that it provides, for the first time, a very systematic way of monitoring the vital signs of humans in an unobtrusive manner. Appropriate sensors have been "plugged" into this motherboard using the developed Interconnection Technology and attached to any part of the individual being monitored, thereby creating a flexible wearable monitoring device. The flexible data bus integrated into the structure transmits the information to monitoring devices such as an EKG Machine, a temperature recorder, a voice recorder, etc. The bus also serves to transmit information to the sensors (and hence, the wearer) from external sources, thus making GTWM a valuable information infrastructure. GTWM is lightweight and can be worn easily by anyone--from infants to senior citizens. GTWM has enormous potential for applications in fields such as telemedicine, monitoring of patients in post-operative recovery, the prevention of SIDS (sudden infant death syndrome), and monitoring of astronauts, athletes, law enforcement personnel and combat soldiers.

Remotely Delivered Exercise-Based Cardiac Rehabilitation: Design and Content Development of a Novel mHealth Platform

PubMed Central

Gant, Nicholas; Meads, Andrew; Warren, Ian; Maddison, Ralph

2016-01-01

Background Participation in traditional center-based cardiac rehabilitation exercise programs (exCR) is limited by accessibility barriers. Mobile health (mHealth) technologies can overcome these barriers while preserving critical attributes of center-based exCR monitoring and coaching, but these opportunities have not yet been capitalized on. Objective We aimed to design and develop an evidence- and theory-based mHealth platform for remote delivery of exCR to any geographical location. Methods An iterative process was used to design and develop an evidence- and theory-based mHealth platform (REMOTE-CR) that provides real-time remote exercise monitoring and coaching, behavior change education, and social support. Results The REMOTE-CR platform comprises a commercially available smartphone and wearable sensor, custom smartphone and Web-based applications (apps), and a custom middleware. The platform allows exCR specialists to monitor patients’ exercise and provide individualized coaching in real-time, from almost any location, and provide behavior change education and social support. Intervention content incorporates Social Cognitive Theory, Self-determination Theory, and a taxonomy of behavior change techniques. Exercise components are based on guidelines for clinical exercise prescription. Conclusions The REMOTE-CR platform extends the capabilities of previous telehealth exCR platforms and narrows the gap between existing center- and home-based exCR services. REMOTE-CR can complement center-based exCR by providing an alternative option for patients whose needs are not being met. Remotely monitored exCR may be more cost-effective than establishing additional center-based programs. The effectiveness and acceptability of REMOTE-CR are now being evaluated in a noninferiority randomized controlled trial. PMID:27342791

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

Are Wearables Safe? We Carry Our Smart Devices with Us Everywhere--Even to Bed--But Have We Been Sleeping with the Enemy, or are Cautionary Tales Overinflated?

PubMed

Mertz, Leslie

2016-01-01

Sometime over the last few years, wearable electronics have become the norm. Whether it's a cell phone attached to a holster at the hip, a smart watch on the wrist, or sensors on and sometimes woven into clothing, these technologies are part of everyday life. Along with this trend, many of the devices are also now collecting and transmitting health information. That is certainly convenient, but the question with any kind of health care device, including wearable medical technology, has always been and continues to be: is it safe?

Towards Smart Homes Using Low Level Sensory Data

PubMed Central

Khattak, Asad Masood; Truc, Phan Tran Ho; Hung, Le Xuan; Vinh, La The; Dang, Viet-Hung; Guan, Donghai; Pervez, Zeeshan; Han, Manhyung; Lee, Sungyoung; Lee, Young-Koo

2011-01-01

Ubiquitous Life Care (u-Life care) is receiving attention because it provides high quality and low cost care services. To provide spontaneous and robust healthcare services, knowledge of a patient’s real-time daily life activities is required. Context information with real-time daily life activities can help to provide better services and to improve healthcare delivery. The performance and accuracy of existing life care systems is not reliable, even with a limited number of services. This paper presents a Human Activity Recognition Engine (HARE) that monitors human health as well as activities using heterogeneous sensor technology and processes these activities intelligently on a Cloud platform for providing improved care at low cost. We focus on activity recognition using video-based, wearable sensor-based, and location-based activity recognition engines and then use intelligent processing to analyze the context of the activities performed. The experimental results of all the components showed good accuracy against existing techniques. The system is deployed on Cloud for Alzheimer’s disease patients (as a case study) with four activity recognition engines to identify low level activity from the raw data captured by sensors. These are then manipulated using ontology to infer higher level activities and make decisions about a patient’s activity using patient profile information and customized rules. PMID:22247682

Conductive fiber-based ultrasensitive textile pressure sensor for wearable electronics.

PubMed

Lee, Jaehong; Kwon, Hyukho; Seo, Jungmok; Shin, Sera; Koo, Ja Hoon; Pang, Changhyun; Son, Seungbae; Kim, Jae Hyung; Jang, Yong Hoon; Kim, Dae Eun; Lee, Taeyoon

2015-04-17

A flexible and sensitive textile-based pressure sensor is developed using highly conductive fibers coated with dielectric rubber materials. The pressure sensor exhibits superior sensitivity, very fast response time, and high stability, compared with previous textile-based pressure sensors. By using a weaving method, the pressure sensor can be applied to make smart gloves and clothes that can control machines wirelessly as human-machine interfaces. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Wearable Sweat Rate Sensors for Human Thermal Comfort Monitoring.

PubMed

Sim, Jai Kyoung; Yoon, Sunghyun; Cho, Young-Ho

2018-01-19

We propose watch-type sweat rate sensors capable of automatic natural ventilation by integrating miniaturized thermo-pneumatic actuators, and experimentally verify their performances and applicability. Previous sensors using natural ventilation require manual ventilation process or high-power bulky thermo-pneumatic actuators to lift sweat rate detection chambers above skin for continuous measurement. The proposed watch-type sweat rate sensors reduce operation power by minimizing expansion fluid volume to 0.4 ml through heat circuit modeling. The proposed sensors reduce operation power to 12.8% and weight to 47.6% compared to previous portable sensors, operating for 4 hours at 6 V batteries. Human experiment for thermal comfort monitoring is performed by using the proposed sensors having sensitivity of 0.039 (pF/s)/(g/m 2 h) and linearity of 97.9% in human sweat rate range. Average sweat rate difference for each thermal status measured in three subjects shows (32.06 ± 27.19) g/m 2 h in thermal statuses including 'comfortable', 'slightly warm', 'warm', and 'hot'. The proposed sensors thereby can discriminate and compare four stages of thermal status. Sweat rate measurement error of the proposed sensors is less than 10% under air velocity of 1.5 m/s corresponding to human walking speed. The proposed sensors are applicable for wearable and portable use, having potentials for daily thermal comfort monitoring applications.

Development of Training/Self-Recognizing Tools for Disability Students Using a Face Expression Recognition Sensor and a Smart-Watch

ERIC Educational Resources Information Center

Kawada, Taku; Ando, Akinobu; Saito, Hirotaka; Uekida, Jun; Nagai, Nobuyuki; Takeshima, Hisashi; Davis, Darold

2016-01-01

In this paper, we developed two kinds of application software run on a mobile/wearable device for autistic spectrum disorder students, intellectual disability students, or physically challenged. One of the applications is expression detector/evaluator using a smartphone and a small expression sensor for social skill training. This sensor can…

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.