Health Examination with Smartwatches: Tracker-App

Thesis Type Master
Thesis Status
Currently running
Student Thomas Berthold
Thesis Supervisor

In cooperation with the Department of Internal Medicine II at the Innsbruck Medical University, our aim is to investigate the body's healthiness under different working conditions. Here, we are interested in the impact of night shifts, office jobs, and hard workers. 

Therefore, we aim to create a system for individuals that is easy to use and requires minimal effort to investigate healthiness with medical foundation. In close collaboration with the Medical University of Innsbruck (Internal Medicine II),  we create a full stack system to log, compare and visualize daily life activity. We collect medical data by exercise & long-term ECG, heart rate, saturation of peripheral oxygen, blood pressure and sleep phases. Raw as well as enriched sensor data is transformed into comparable time-series. Enriched sensor data include activity detection, sleep phases, heart rate, step counters, and burnt calories. We are going to use digital signal processing algorithms, such as cross-correlation, to find similarities. Here, we aim to verify causation through correlation. To complement the automated data collection, we will also employ concentration tests throughout the day for participants.