Mobile Health : Sensors, Analytic Methods, and Applications - Rehg, James M.; Murphy, Susan A.; Kumar, Santosh; SpringerLink (Online service) (Cham : Springer International Publishing : Imprint: Springer, 2017)
Introduction to Section 1: mHealth Applications and Tools -- StudentLife: Using Smartphone to Assess Mental Health and Academic Performance of College Students -- Circadian Computing: Sensing, Modeling, and Maintaining Biological Rhythms -- Design Lessons from a Micro-Randomized Pilot Study in Mobile Health -- The Use of Asset-Based Community Development in a Research Project Aimed at Developing mHealth Technologies for Older Adults -- Designing Mobile Health Technologies for Self-Monitoring: The Bit Counter as a Case Study -- mDebugger: Assessing and Diagnosing the Fidelity and Yield of Mobile Sensor Data -- Introduction to Section II: Sensors to mHealth Markers -- Challenges and Opportunities in Automated Detection of Eating Activity -- Detecting Eating and Smoking Behavior Using Smartwatches -- Wearable Motion Sensing Devices and Algorithms for Precise Healthcare Diagnostics and Guidance -- Paralinguistic Analysis of Children's Speech in Natural Environments -- Pulmonary Monitoring Using Smartphones -- Wearable Sensing of Left Ventricular Function -- A new direction for Biosensing: RF sensors for monitoring cardio-pulmonary function -- Wearable Optical Sensors -- Introduction to Section III: Markers to mHealth Predictors -- Exploratory Visual Analytics of Mobile Health Data: Sensemaking Challenges and Opportunities -- Learning Continuous-Time Hidden Markov Models for Event Data -- Time-series Feature Learning with Applications to Healthcare Domain -- From Markers to Interventions: The Case of Just-in-Time Stress Intervention -- Introduction to Section IV: Predictors to mHealth Interventions -- Modeling Opportunities in mHealth Cyber-Physical Systems -- Control Systems Engineering for Optimizing Behavioral mHealth Interventions -- From Ads to Interventions: Contextual Bandits in Mobile Health -- Towards Health Recommendation Systems: An Approach for Providing Automated Personalized Health Feedback from Mobile Data.
Keywords: Health informatics; Artificial intelligence; Statistics .; Data mining; Computer communication systems; Health Informatics; Artificial Intelligence; Statistics for Life Sciences, Medicine, Health Sciences; Data Mining and Knowledge Discovery; Health Informatics; Computer Communication Networks