Hegi, Heinz (2025). Sensor–based Feedback for Coordination Training on the Sensopro. (Thesis). Universität Bern, Bern
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Abstract
The incidence of coordination problems and poor balance in the general population is at least partly associated with a lack of physical activity linked to the modern sedentary lifestyle, and the recent trends in digitalization may further exacerbate these issues in the future. Balance and coordination training on the Sensopro may constitute one promising tool to mitigate these problems: While performing exercises on the Sensopro, users stand on an unstable base of support that requires continual adjustments to maintain balance, which provides a challenging environment that, thanks to available safety features, allows risk-free training conditions even for people with diminished mobility. An automated sensor-based feedback system could provide additional training incentives through gamification and progress tracking, in addition to guiding users to better movement solutions to facilitate motor learning during autonomous training. However, the Sensopro previously only supported video instructions without augmented feedback. Consequently, the development of an automated sensor-based feedback system that provides relevant feedback during Sensopro exercises could improve motivation, training adherence, and training outcomes. The goal of this project was therefore to develop a feedback system for the Sensopro in order to improve motivational aspects and training outcomes. First, a scoping review of the existing literature informed the design of the subsequent system, but it also revealed some potential gaps in the research that prevented the establishment of more general guidelines. Next, the training data gathered in a cross-sectional study of eight basis exercises on the Sensopro served as a reference for functional movement analyses and provided a training set for neural network models. Furthermore, a validation study demonstrated that the developed measurement system produces adequate tape kinematic data, including foot placement and orientation estimations. All these building blocks were then combined to develop algorithms that are able to produce relevant and understandable performance metrics. Finally, a longitudinal study was planned with the objective of empirically verifying the desired long-term benefits provided by the developed feedback system. We thus successfully developed an automated sensor-based feedback system capable of providing relevant performance metrics for balance and coordination exercises on the Sensopro. Future research may include an empirical assessment of the expected benefits in a longitudinal study, improvements to the measurement capabilities by examining key aspects of the measurement setup in more detail, generalizing the measurement system to other unstable bases of support, and a systematic investigation of the effects of different feedback properties in complex movement tasks on the Sensopro.
| Item Type: | Thesis |
|---|---|
| Dissertation Type: | Cumulative |
| Date of Defense: | 14 August 2025 |
| Subjects: | 700 Arts > 790 Sports, games & entertainment |
| Institute / Center: | 07 Faculty of Human Sciences > Institute of Sport Science (ISPW) |
| Depositing User: | Hammer Igor |
| Date Deposited: | 02 Oct 2025 10:17 |
| Last Modified: | 02 Oct 2025 10:18 |
| URI: | https://boristheses.unibe.ch/id/eprint/6764 |
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