Development of an Augmented Reality Training Programme for Stroke Patients
At a glance
- Project leader : Prof. Dr. Daniel Baumgartner
- Deputy of project leader : Dr. Christoph Bauer
- Project team : Dr. Jens Bansi, Michelle Haas, Martin Huber, Andrea Kilchenmann, Dr. Irina Nast, Mandy Scheermesser, Bettina Sommer, Dominik Textor, Christa Wachter Oberli, Robin Waibel, Michaela Wenger
- Project budget : CHF 380'400
- Project status : completed
- Funding partner : Innosuisse (Innovationsprojekt / Projekt Nr. 43266.1 IP-LS)
- Project partner : rotavis AG, Bitforge AG, Stiftung Kliniken Valens
- Contact person : Daniel Baumgartner
Stroke is a serious burden for the health system and the affected individuals. Globally, around 16 million people per year experience a stroke for the first time, of which 5 million remain limited in their functionality and participation. Since improvements in functionality after a stroke take time and require many repetitions during exercises, intensive therapy is often necessary. On the other hand, efficiency will be one of the key factors to keeping control of health care costs.
The project team will build upon the existing knowledge and experience of the Zurich University of Applied Sciences, rotavis AG, and Bitforge AG as well as a clinical partner (Clinic Valens). We will develop an augmented reality (AR) training system that allows patients to perform their reaching and trunk control exercises on their own while being supervised by AR technology and being motivated and guided by therapeutic AR games. In addition, the system will be able to challenge the patients’ trunk control with a movable 3-D seat, and monitor improvements over time. The system is intended to be used in the clinic and at a later stage at home.
The key technological challenges are the tracking of hand movement with enough sensitivity to distinguish between different types of grip, the design of the AR environment according to stroke patients’ needs and the integration of the two parts of the system, the AR technology and the movable 3-D seat. We will identify the precision required for the intended use and identify the right technology to address these challenges.
18(7), pp. e0289115.
Available from: https://doi.org/10.1371/journal.pone.0289115
Archives of Rehabilitation Research and Clinical Translation.
Available from: https://doi.org/10.1016/j.arrct.2023.100289
17(7), pp. e0272382.
Available from: https://doi.org/10.1371/journal.pone.0272382
Open Data and Downloads
- Haas, Michelle; Sommer, Bettina; Graf, Eveline; Bauer, Christoph, 2022. Electromyographic data mobile and stable seat [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/FX5C3D.
- Haas, Michelle; Sommer, Bettina; Graf, Eveline; Bauer, Christoph, 2023. Hip and trunk kinematics : mobile and stable seat [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/LP3W8J.