Reprint
Wearable and Nearable Biosensors and Systems for Healthcare
Edited by
July 2021
226 pages
- ISBN978-3-0365-0974-7 (Hardback)
- ISBN978-3-0365-0975-4 (PDF)
This book is a reprint of the Special Issue Wearable and Nearable Biosensors and Systems for Healthcare that was published in
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary
Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
tangent space; Riemannian geometry; particle swarm optimization (PSO); BCI; EEG; electro-oscillography (EOG); CSP; FBCSP (filter bank common spatial pattern); online learning; ballistocardiography; pressure sensor; Emfit; home monitoring; sleep recording; sleep apnea; unsupervised learning; synchronization; acoustic emissions; joint sounds; glove; wearable sensing; knee joint loading; quaternion; smartphone; feature engineering; human activity recognition; sensor fusion; ballistocardiography; ballistocardiogram; blood pressure; stroke volume; cardiac output; total peripheral resistance; photoplethysmography; photoplethysmogram; photoplethysmography; heart rate; consumer-wearable devices; in-ear; validation; optical pulse rate monitoring; pulse rate; ballistocardiography; seismocardiography; ultra-short heart rate variability; stress evaluation; smartphone; accelerometers; robotic assistant systems for surgery; expertise; pick-and-drop simulator task; grip force profiles; grip force control; body sensor network; wearable sensor; telemedicine; telerehabilitation; seismocardiogram; acceleration; electrocardiogram; cardiac mechanics; photoplethysmogram; pulse transit time; adaptive recursive least squares filter (ARLSF); Seismocardiography (SCG); motion artifact; Electrocardiogram (ECG); heart rate; ageing; gender; machine learning; support vector machine; voice analysis; pressure sensors; compression therapy; thin-film sensors; wireless sensors; medical pressure monitoring; capacitive sensors; flexible sensors; LC sensor; wound monitoring; n/a