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On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2022-08-12

Cited: 0

Clicked: 1920

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Kezhou LIU

https://orcid.org/0000-0002-5235-7357

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Journal of Zhejiang University SCIENCE B 2022 Vol.23 No.8 P.625-641

http://doi.org/10.1631/jzus.B2100999


Research and application advances in rehabilitation assessment of stroke


Author(s):  Kezhou LIU, Mengjie YIN, Zhengting CAI

Affiliation(s):  Department of Biomedical Engineering, School of Automation (Artificial Intelligence), Hangzhou Dianzi University, Hangzhou 310018, China

Corresponding email(s):   liukezhou@hdu.edu.cn

Key Words:  Stroke, Rehabilitation assessment, Stroke assessment scales, Detection technology, Artificial intelligence



Abstract: 
stroke has a high incidence and disability rate, and rehabilitation is an effective means to reduce the disability rate of patients. To systematize rehabilitation assessment, which is the foundation for rehabilitation therapy, we summarize the assessment methods commonly used in research and clinical applications, including the various types of stroke rehabilitation scales and their applicability, and related biomedical detection technologies, including surface electromyography (sEMG), motion analysis systems, transcranial magnetic stimulation (TMS), magnetic resonance imaging (MRI), and combinations of different techniques. We also introduce some assessment techniques that are still in the experimental phase, such as the prospective application of artificial intelligence (AI) with optical correlation tomography (OCT) in stroke rehabilitation. This review provides a useful bibliography for the assessment of not only the severity of stroke injury, but also the therapeutic effects of stroke rehabilitation, and establishes a solid base for the future development of stroke rehabilitation skills.

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