Automated classification of bimanual movements in stroke telerehabilitation: a comparison of dimensionality reduction algorithms

Roni Barak Ventura; Francesco Vincenzo Surano; Maurizio Porfiri

doi:10.1117/12.2581433

26 March 2021 Automated classification of bimanual movements in stroke telerehabilitation: a comparison of dimensionality reduction algorithms

Roni Barak Ventura, Francesco Vincenzo Surano, Maurizio Porfiri

Author Affiliations +

Proceedings Volume 11590, Nano-, Bio-, Info-Tech Sensors and Wearable Systems; 1159005 (2021) https://doi.org/10.1117/12.2581433
Event: SPIE Smart Structures + Nondestructive Evaluation, 2021, Online Only

Abstract

Stroke survivors commonly experience unilateral muscle weakness, which limits their engagement in daily activities. Bimanual training has been demonstrated to effectively recover coordinated movements among those patients. We developed a low cost telerehabilitation platform dedicated to bimanual exercise, where the patient manipulates a dowel to control a computer program. Data on movement is collected using a Microsoft Kinect sensor and an inertial measurement unit to interface the platform, as well as to assess motor performance remotely. Toward automatic classification of bimanual movements executed by the user, we test the performance of a linear and a nonlinear dimensionality reduction techniques.

Conference Presentation

Citation Download Citation

Roni Barak Ventura, Francesco Vincenzo Surano, and Maurizio Porfiri "Automated classification of bimanual movements in stroke telerehabilitation: a comparison of dimensionality reduction algorithms", Proc. SPIE 11590, Nano-, Bio-, Info-Tech Sensors and Wearable Systems, 1159005 (26 March 2021); https://doi.org/10.1117/12.2581433

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