Reprint

Smart Sensing Technologies for Personalised Coaching

Edited by
August 2021
232 pages
  • ISBN978-3-0365-1790-2 (Hardback)
  • ISBN978-3-0365-1789-6 (PDF)

This book is a reprint of the Special Issue Smart Sensing Technologies for Personalised Coaching that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary

People living in both developed and developing countries face serious health challenges related to sedentary lifestyles. It is therefore essential to find new ways to improve health so that people can live longer and can age well. With an ever-growing number of smart sensing systems developed and deployed across the globe, experts are primed to help coach people toward healthier behaviors. The increasing accountability associated with app- and device-based behavior tracking not only provides timely and personalized information and support but also gives us an incentive to set goals and to do more. This book presents some of the recent efforts made towards automatic and autonomous identification and coaching of troublesome behaviors to procure lasting, beneficial behavioral changes.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
activity recognition; wearable devices; inertial sensors; Bluetooth beacons; machine learning; e-coaching; m-health intervention; personalization; healthy lifestyle; physical activity; tangible user interface; affordance; multimodal cueing; animate objects; activities of daily living; human activity recognition; context-awareness; Bayesian network; mobile application; wearable computing; wrist-worn heart rate devices; cardiac rehabilitation; real-time wearable monitoring; fuzzy logic; fuzzy linguistic approach; m-health; remote coaching; telemonitoring; telehealth; cadence; marathon; elevation change analysis; personalized assistance level; coaching; physical activity; electric bicycles; ubiquitous computing; health; human-centered computing; digital coaching; diabetes education; serious gaming; self-management; user evaluations; physical activity; machine learning; coaching; sedentary lifestyle; context recognition; self-management; unhealthy sitting habits; e-coaching; wearable sensors; smartphones; smart objects; activity recognition; context-awareness; behavior change