TY - BOOK ID - 146093842 TI - Data Analytics and Applications of the Wearable Sensors in Healthcare AU - Syed Abdul, Shabbir AU - Luque, Luis Fernandez AU - Garcia-Gomez, Juan Miguel AU - Garcia-Zapirain, Begoña AU - Hsueh, Pei-Yun PY - 2020 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Humanities KW - Social interaction KW - eHealth KW - wearable KW - monitoring KW - services KW - integration KW - IoT KW - Telemedicine KW - wearable sensors KW - multivariate analysis KW - longitudinal study KW - functional decline KW - exercise intervention KW - accidental falls KW - fall detection KW - real-world KW - signal analysis KW - performance measures KW - non-wearable sensors KW - accelerometers KW - cameras KW - machine learning KW - smart textiles KW - healthcare KW - talking detection KW - activity recognition and monitoring KW - patient health and state monitoring KW - wearable sensing KW - orientation-invariant sensing KW - motion sensors KW - accelerometer KW - gyroscope KW - magnetometer KW - pattern classification KW - artificial intelligence KW - supervised machine learning KW - predictive analytics KW - hemodialysis KW - non-contact sensor KW - heart rate KW - respiration rate KW - heart rate variability KW - time-domain features KW - frequency-domain features KW - principal component analysis KW - behaviour analysis KW - classifier efficiency KW - personal risk detection KW - one-class classification KW - actigraphy KW - encoding KW - data compression KW - denoising KW - edge computing KW - signal processing KW - wearables KW - activity monitoring KW - citizen science KW - cluster analysis KW - physical activity KW - sedentary behavior KW - walking KW - energy expenditure KW - wearable device KW - impedance pneumography KW - neural network KW - mechanocardiogram (MCG) KW - smart clothes KW - heart failure (HF) KW - left ventricular ejection fraction (LVEF) KW - technology acceptance model (TAM) KW - physical activity classification KW - free-living KW - GENEactiv accelerometer KW - Gaussian mixture model KW - hidden Markov model KW - wavelets KW - skill assessment KW - deep learning KW - LSTM KW - state space model KW - probabilistic inference KW - latent features KW - human activity recognition KW - MIMU KW - genetic algorithm KW - feature selection KW - classifier optimization KW - bispectrum KW - entropy KW - feature extraction KW - heat stroke KW - filtering algorithm KW - physiological parameters KW - exercise experiment KW - biomedical signal processing KW - wearable biomedical sensors KW - wireless sensor network KW - respiratory monitoring KW - optoelectronic plethysmography KW - biofeedback KW - biomedical technology KW - exercise therapy KW - orthopedics KW - mobile health KW - qualitative KW - human factors KW - inertial measurement unit KW - disease prevention KW - occupational healthcare KW - P-Ergonomics KW - precision ergonomics KW - musculoskeletal disorders KW - wellbeing at work KW - electrocardiogram KW - conductive gels KW - noncontact electrode KW - myocardial ischemia KW - pacemaker KW - ventricular premature contraction KW - upper extremity KW - motion KW - action research arm test KW - activities of daily living KW - IoT wearable monitor KW - health KW - posture analysis KW - spinal posture KW - wearable sensor KW - embedded system KW - recurrent neural networks KW - physical workload KW - wearable systems for healthcare KW - machine learning for real-time applications KW - actigraph KW - body worn sensors KW - clothing sensors KW - cross correlation analysis KW - healthcare movement sensing KW - wearable devices KW - calibration KW - inertial measurement units KW - human movement KW - physical activity type KW - real-life KW - GPS KW - GIS UR - https://www.unicat.be/uniCat?func=search&query=sysid:146093842 AB - 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. ER -