EEG- and EMG-Driven Poststroke Rehabilitation: A Review
Haiyang Yang, Jiacheng Wan, Ying Jin, Xixia Yu, Yinfeng Fang
Abstract
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.