mHealth through quantified-self: A user study

Abstract

Abstract-We describe a user study of a mHealth prototype system based on a wellbeing scenario, exploiting the quantifiedself approach to measurement and monitoring. We have used off-the-shelf equipment, with opensource, web-based, software, and exploiting the increasing popularity of smartphones and selfmeasurement devices in a user study. We emulate a mHealth scenario as a pre-clinical experiment, as a realistic alternative to a clinical scenario, with reduced risk to sensitive patient medical data. We discuss the efficacy of this approach for future mHealth systems for remote monitoring. Our system used the popular Fitbit device for monitoring personal wellbeing data, the Diaspora online social media platform (OSMP), and a simple Android/iOS remote notification application. We implemented remote monitoring, asynchronous user interaction, multiple actors, and usercontrolled security and privacy mechanisms. We propose that the use of a quantified-self approach to mHealth is particularly valuable to undertake research and systems development.

Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources

“…The quantified self (QS) movement [1, 2] led to the introduction of numerous wearable, primary wrist-worn, sensor solutions to the market, which are made for the application in daily routine (compact and comfortable). The measured parameters include e.g., step count, traveled distance, caloric analysis, energy and oxygen consumption, fitness tracking, heart rate and sleep stages, and additional features, as e.g., food documentation, data sharing, and alarm functions [3, 4].…”