Sleeve Based Knee Angle Calculation for Rehabilitation

Maurer M, Zrenner M, Reynolds D, Dümler B, Eskofier B (2018)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2018

Pages Range: 1-4

Conference Proceedings Title: Proceedings of the 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN)

Event location: Las Vegas, Nevada US

DOI: 10.1109/bsn.2018.8329644

Abstract

The knee flexion-extension angle is an important criterion for the rehabilitation process after a rupture of the anterior cruciate ligament (ACL), which is a typical sports injury. This paper describes the development and evaluation of a smart knee sleeve, which is capable of calculating the knee flexion-extension angle based on inertial sensors. The output is to be used to supervise and speed up rehabilitation by guiding patients through exercises and giving feedback about the execution. The accuracy of the knee angle calculation was evaluated in a study with twelve healthy subjects performing six different exercises with an optical system as reference. The effects of different functional alignment movements, knee sleeve material and recalibration on the final knee angle were evaluated. The mean absolute error (MAE) of all maxima and minima was calculated and averaged over all subjects and exercises. An MAE of 5.2° compared to the gold standard was achieved while the Pearson correlation was 0.96 for 30 minutes training without recalibration or restart of the system.

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APA:

Maurer, M., Zrenner, M., Reynolds, D., Dümler, B., & Eskofier, B. (2018). Sleeve Based Knee Angle Calculation for Rehabilitation. In IEEE (Eds.), Proceedings of the 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (pp. 1-4). Las Vegas, Nevada, US.

MLA:

Maurer, Mathias, et al. "Sleeve Based Knee Angle Calculation for Rehabilitation." Proceedings of the 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN), Las Vegas, Nevada Ed. IEEE, 2018. 1-4.

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