Reprint
Data Analytics and Applications of the Wearable Sensors in Healthcare
Edited by
June 2020
498 pages
- ISBN978-3-03936-350-6 (Paperback)
- ISBN978-3-03936-351-3 (PDF)
This book is a reprint of the Special Issue Data Analytics and Applications of the Wearable Sensors in Healthcare that was published in
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary
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.
Format
- Paperback
License
© 2020 by the authors; CC BY-NC-ND license
Keywords
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; wearable sensors; non-wearable sensors; accelerometers; cameras; wearable sensors; 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; wearable sensors; actigraphy; encoding; data compression; denoising; edge computing; signal processing; wearables; activity monitoring; machine learning; citizen science; cluster analysis; physical activity; sedentary behavior; walking; energy expenditure; wearable device; accelerometer; 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; machine learning; Gaussian mixture model; hidden Markov model; wavelets; wearable sensors; skill assessment; deep learning; LSTM; state space model; probabilistic inference; latent features; human activity recognition; wearable sensors; MIMU; genetic algorithm; feature selection; classifier optimization; machine learning; actigraphy; bispectrum; entropy; feature extraction; heat stroke; filtering algorithm; physiological parameters; exercise experiment; principal component analysis; biomedical signal processing; wearable biomedical sensors; wireless sensor network; respiratory monitoring; optoelectronic plethysmography; biofeedback; biomedical technology; exercise therapy; orthopedics; mobile health; qualitative; human factors; wearables; inertial measurement unit; disease prevention; occupational healthcare; P-Ergonomics; precision ergonomics; musculoskeletal disorders; smart textiles; wearable sensors; wellbeing at work; electrocardiogram; conductive gels; noncontact electrode; myocardial ischemia; pacemaker; ventricular premature contraction; inertial measurement unit; upper extremity; motion; action research arm test; activities of daily living; heart rate; IoT wearable monitor; health; posture analysis; spinal posture; accelerometer; wearable sensor; accelerometer; deep learning; embedded system; fall detection; wearable; recurrent neural networks; human activity recognition; 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; accelerometer; calibration; inertial measurement units; human movement; physical activity type; real-life; GPS; GIS; n/a