Design of upper limb rehabilitation evaluation system based on deep learning

Le Ding; Haoyu Wang; Chao Chen; Jiayan Xu; Pingping Zhou

doi:10.1117/12.2660914

2 February 2023 Design of upper limb rehabilitation evaluation system based on deep learning

Le Ding, Haoyu Wang, Chao Chen, Jiayan Xu, Pingping Zhou

Proceedings Volume 12462, Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022); 124622R (2023) https://doi.org/10.1117/12.2660914
Event: International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022), 2022, Xi'an, China

Abstract

The topic of non-contact diagnosis became a hot topic during COVID-19 and online consultation gained popularity. In this research, a deep learning-based autonomous limb evaluation system is developed for online consultation and remote rehabilitation training for people with physical limitations. Its main goal is to collect and analyze information about limb states. The patient can evaluate the limb state at home using the mobile app, and the doctor can view the data and connect with the patient via the web's chat module to offer diagnostic opinions. Deep learning is used for the Start/End Attitude Determination Model and OpenCV for the limb and hand evaluation model, with the results being uploaded to the server.

Citation Download Citation

Le Ding, Haoyu Wang, Chao Chen, Jiayan Xu, and Pingping Zhou "Design of upper limb rehabilitation evaluation system based on deep learning", Proc. SPIE 12462, Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022), 124622R (2 February 2023); https://doi.org/10.1117/12.2660914

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