Data Analytics and Applications of the Wearable Sensors in Healthcare
This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research ar...
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| Year of Publication: | 2020 |
| Language: | English |
| Physical Description: | 1 electronic resource (498 p.) |
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Syed Abdul, Shabbir edt Data Analytics and Applications of the Wearable Sensors in Healthcare Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020 1 electronic resource (498 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research articles, we have organized the book to show various aspects covered in this field, such as eHealth, technology-integrated research, prediction models, rehabilitation studies, prototype systems, community health studies, ergonomics design systems, technology acceptance model evaluation studies, telemonitoring systems, warning systems, application of sensors in sports studies, clinical systems, feasibility studies, geographical location based systems, tracking systems, observational studies, risk assessment studies, human activity recognition systems, impact measurement systems, and a systematic review. We would like to take this opportunity to invite high quality research articles for our next Special Issue entitled “Digital Health and Smart Sensors for Better Management of Cancer and Chronic Diseases” as a part of Sensors journal. English Humanities bicssc Social interaction bicssc eHealth wearable monitoring services integration IoT Telemedicine wearable sensors multivariate analysis longitudinal study functional decline exercise intervention accidental falls fall detection real-world signal analysis performance measures non-wearable sensors accelerometers cameras machine learning smart textiles healthcare talking detection activity recognition and monitoring patient health and state monitoring wearable sensing orientation-invariant sensing motion sensors accelerometer gyroscope magnetometer pattern classification artificial intelligence supervised machine learning predictive analytics hemodialysis non-contact sensor heart rate respiration rate heart rate variability time-domain features frequency-domain features principal component analysis behaviour analysis classifier efficiency personal risk detection one-class classification actigraphy encoding data compression denoising edge computing signal processing wearables activity monitoring citizen science cluster analysis physical activity sedentary behavior walking energy expenditure wearable device impedance pneumography neural network mechanocardiogram (MCG) smart clothes heart failure (HF) left ventricular ejection fraction (LVEF) technology acceptance model (TAM) physical activity classification free-living GENEactiv accelerometer Gaussian mixture model hidden Markov model wavelets skill assessment deep learning LSTM state space model probabilistic inference latent features human activity recognition MIMU genetic algorithm feature selection classifier optimization bispectrum entropy feature extraction heat stroke filtering algorithm physiological parameters exercise experiment biomedical signal processing wearable biomedical sensors wireless sensor network respiratory monitoring optoelectronic plethysmography biofeedback biomedical technology exercise therapy orthopedics mobile health qualitative human factors inertial measurement unit disease prevention occupational healthcare P-Ergonomics precision ergonomics musculoskeletal disorders wellbeing at work electrocardiogram conductive gels noncontact electrode myocardial ischemia pacemaker ventricular premature contraction upper extremity motion action research arm test activities of daily living IoT wearable monitor health posture analysis spinal posture wearable sensor embedded system recurrent neural networks physical workload wearable systems for healthcare machine learning for real-time applications actigraph body worn sensors clothing sensors cross correlation analysis healthcare movement sensing wearable devices calibration inertial measurement units human movement physical activity type real-life GPS GIS 3-03936-350-6 3-03936-351-4 Luque, Luis Fernandez edt Garcia-Gomez, Juan Miguel edt Garcia-Zapirain, Begoña edt Hsueh, Pei-Yun edt Syed Abdul, Shabbir oth Luque, Luis Fernandez oth Garcia-Gomez, Juan Miguel oth Garcia-Zapirain, Begoña oth Hsueh, Pei-Yun oth |
| language |
English |
| format |
eBook |
| author2 |
Luque, Luis Fernandez Garcia-Gomez, Juan Miguel Garcia-Zapirain, Begoña Hsueh, Pei-Yun Syed Abdul, Shabbir Luque, Luis Fernandez Garcia-Gomez, Juan Miguel Garcia-Zapirain, Begoña Hsueh, Pei-Yun |
| author_facet |
Luque, Luis Fernandez Garcia-Gomez, Juan Miguel Garcia-Zapirain, Begoña Hsueh, Pei-Yun Syed Abdul, Shabbir Luque, Luis Fernandez Garcia-Gomez, Juan Miguel Garcia-Zapirain, Begoña Hsueh, Pei-Yun |
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HerausgeberIn HerausgeberIn HerausgeberIn HerausgeberIn Sonstige Sonstige Sonstige Sonstige Sonstige |
| title |
Data Analytics and Applications of the Wearable Sensors in Healthcare |
| spellingShingle |
Data Analytics and Applications of the Wearable Sensors in Healthcare |
| title_full |
Data Analytics and Applications of the Wearable Sensors in Healthcare |
| title_fullStr |
Data Analytics and Applications of the Wearable Sensors in Healthcare |
| title_full_unstemmed |
Data Analytics and Applications of the Wearable Sensors in Healthcare |
| title_auth |
Data Analytics and Applications of the Wearable Sensors in Healthcare |
| title_new |
Data Analytics and Applications of the Wearable Sensors in Healthcare |
| title_sort |
data analytics and applications of the wearable sensors in healthcare |
| publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
| publishDate |
2020 |
| physical |
1 electronic resource (498 p.) |
| isbn |
3-03936-350-6 3-03936-351-4 |
| illustrated |
Not Illustrated |
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