康复
脑电图
物理医学与康复
人口
冲程(发动机)
神经反射
脑-机接口
计算机科学
医学
心理学
神经科学
工程类
机械工程
环境卫生
作者
Haiyang Yang,Jiacheng Wan,Jiang Ying,Xixia Yu,Yinfeng Fang
出处
期刊:IEEE Sensors Journal
[Institute of Electrical and Electronics Engineers]
日期:2022-12-15
卷期号:22 (24): 23649-23660
被引量:14
标识
DOI:10.1109/jsen.2022.3220930
摘要
Intelligent poststroke rehabilitation has attracted great attention worldwide, since the high incidence rate of stroke with the aging of the population. It is well known that effective rehabilitation training can help the rehabilitation of neuromuscular injuries. In recent decades, biological signal-based closed-loop rehabilitation has significantly progressed and attracted widespread attention in clinics and academia, achieving relatively promising results. These biological signals are mainly electromyographic (EMG) signals and electroencephalographic (EEG) signals. First, this article briefly overviews how to use EMG and EEG to be involved in rehabilitation. Special attention is paid to the detailed changes in the EMG signal, EEG signal, and brain rhythm after stroke, regarding technology-based intervention in stroke rehabilitation including intention cognitive, function rehabilitation devices, gesture decoded, and motor imagery (MI). Finally, the feasibility of state-of-the-art motor function rehabilitation with EEG and EMG signals is analyzed. Our results show that rehabilitation with EEG and EMG signals is relatively more favorable than a single signal. Though the challenges may be tough, new theories and technological approaches able to exploit the full potential of EEG and EMG.
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