Backtrainer, FHNW School of Life Sciences

An effective way to treat low back pain is through active and supervised movement exercises. The effectiveness of such exercises however is limited by inadequate awareness of patients of their own posture, requiring the continuous supervision by a physical therapist.

To increase patient independence and support physical therapy of low back pain, we built a sensor system that provides real-time information about the geometry of the low back. We investigate how this information can be turned into visual feedback that is intuitive and easy to understand.

We first analyzed the whole gamut of typical movement exercises, and classified them according to the therapy goal into the two basic types of stabilizing and mobilizing exercises. A visual metaphor for each of these types was then developed, and implemented as visual feedback. To free patients from having to focus their attention on a computer screen during exercises, we used techniques from ambient visualization.

The visual feedback was evaluated during five weeks in a rehabilitation clinic with 26 patients and 15 physiotherapists. Subjective satisfaction of participants was good and study results showed that the abstract visual feedback that we designed was helpful. Ambient feedback modalities proved to be a very useful addition to the computer screen in a real-life therapy setting.