Our project focuses on real-time biofeedback using sonification to improve movement quality during walking and rehabilitation exercises. By combining pressure-sensitive insoles and machine learning models, we classify movement quality in real-time and convert this information into intuitive acoustic feedback. This innovative approach eliminates the need for visual cues, allowing patients to focus on their exercises while receiving clear guidance to achieve better outcomes.
This collection comprises a video explaining our sonification project along with two associated publications.
de Jesus Oliveira, V. A., Slijepčević, D., Dumphart, B., Ferstl, S., Reis, J., Raberger, A.-M., Heller, M., Horsak, B., Iber, M. (2023). Auditory feedback in tele-rehabilitation based on automated gait classification. Personal and Ubiquitous Computing 27, 1873–1886 (2023). doi.org/10.1007/s00779-023-01723-2
Simonlehner, M., de Jesus Oliveira, V. A., Prock, K., Iber, M., Horsak, B., & Siragy, T. (2024). Sonification can alter Joint Alignment for Personalized Rehabilitation: Evidence from a Controlled Pilot Study. Gait & Posture, 113, 212–213. doi.org/10.1016/j.gaitpost.2024.07.229