Secure collection of physical activity data from study participants through mobile solutions

Abstract

Biometric and health related data collected through automated features in smartphones and wearables can provide researchers with valuable information about the population. This thesis explores the possibilities of extracting data from Apple and Samsung wearable devices like watches and smartphones where native built-in support for data extraction and third-party data storage is not available.

Doing so will rely on a separate application (mSpider) on the connected phone, to perform data extraction, while prioritizes privacy and security as the primary concern. The thesis has implemented a proof-of-concept application that fetches existing data from Apple Health. The proof-of-concept application has a low footprint on the participant’s phone when it comes to battery usage and data usage.

The result from this thesis shows that it is possible and feasible to perform automatic and continuous data transfer from smart watches and phones in a larger population while respecting their privacy and security. Due to varying international laws, further research is needed to comply with regulatory requirements across the globe.

In conclusion, this application and the thesis presents a path for collecting research data from smart watches and phones.