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ActiVAtE – Activity Tracking Data to Understand Volition, Attrition and Engagement towards Healthy Behaviors in Diabetic Patients and Controls

This project examines physical activity for study participants with and without type II diabetes diagnosis over one year. The collected data is transferred, merged, processed and evaluated with the help of inferential statistical and exploratory data mining processes.
Volkswagen Stiftung VW ZN3426

Team: link

Local Contact :

Prof. Dr. Kristof van Laerhoven, University of Siegen
M. Sc. Alexander Hölzemann, University of Siegen

The Project:

Type II diabetes is one of the most common chronic diseases in adults and is triggered by insulin resistance due to genetic, age-associated and lifestyle factors, including lack of exercise, malnutrition and smoking. Hyperglycemia due to diabetes is associated with other diseases and impairments, such as diseases of the eyes, kidneys, nerves, or cardiovascular system.

Relevant prevention strategies to prevent type II diabetes (primary prevention) or to prevent progression and secondary diseases of this disease (tertiary prevention) primarily refer to changes in lifestyle, such as a change in diet, the reduction of body weight and the promotion of physical activity. With regard to the promotion of physical activity, both the promotion of physical activity in everyday life and structured physical activity programs in the form of aerobic endurance and/or strength training are recommended for type II diabetes.

Within the framework of the ActiVAtE_Prevention project, it is planned to examine study participants with and without diagnosed type II diabetes with regard to their physical activity behavior within one year. The collected data will be transferred, merged, processed and evaluated using inferential statistical and explorative data mining methods.

Following the current design phase, recruitment of study participants is planned to start in summer 2021. The interdisciplinary approach and the analysis of the relatively large amounts of data obtained represent particular strengths and challenges of the study.


Fig.:  A small and wrist-worn sensor unit to detect a person's activities continuously over weeks and months


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