Identification of Complex Activity Patterns through Smart Sensors in Geriatric Rehabilitation

In cooperation with:
Prof. Dr. Timo Ropinski, Visual Computing Group, Ulm University (Germany)
Prof. Dr. Jochen Klenk, Clinic for Geriatric Rehabilitation, Robert-Bosch-Hospital Stuttgart, Robert-Bosch Society for Medical Research mbH (Germany)
Prof. Dr. Alexandra Jorzig, Faculty of Health and Social Sciences, IB Hochschule Berlin (Germany)
Prof. Dr. Enrico Rukzio, Human-Computer-Interaction Group, Ulm University (Germany)


Physical activity is an important aspect of health and everyday activities are made up of very complex movement patterns. The combination and frequency of these movement patterns reflect the ability to independently organize everyday life. These abilities are limited in case of sick or aging people.

This is particularly evident in geriatric rehabilitation, which aim is to enable people to lead a life that is as independent and self-determined as possible. Accurate monitoring of patient activities can help identify treatment needs that are relevant to everyday life, control care and therapy in a targeted manner, and document the progress of treatment. The identification of specific activity patterns, their context, and frequency can help to offer the optimal care for patients.

In order to record and analyze activity patterns in geriatric rehabilitation, smart sensors in the form of activity trackers worn on the body will be integrated into the patient's living environment as a proof-of-concept. Through this, it should be possible to analyze for example the radius of action of patients, detect falls, and examine the frequency of everyday activities.

In addition to developments of this technology, the usability of the developed procedures and the consideration of data security and ethical aspects play a central role. As part of the ethical component project, investigated will be how an evidence-based, participatory, process-oriented, and transparent involvement of the patients or their legal representative can be achieved.

Lead of the component project: Prof. Dr. Florian Steger

Research team of the component project: Dr. Cristian Timmermann, Christopher Predel

Duration: 2020–2022

funded by the Federal Ministry of Health (BMG)