Abstract
Stroke is a kind of cerebral vascular disease with high death rate and high disability rate, most stroke patients lose a lot of physiological function. For example, motor function, language function, etc. Two data acquisition methods of lower limb rehabilitation system for patients with stroke were introduced in this paper that is EEG signal extraction based on BCI and lower limb muscle electrical stimulation system based on EMG model. Through the wavelet packet transform (WPT) to analyze the EEG signal and collect the effective EEG signal. The wavelet transform is used to analyze the time and frequency domain, which provides a good feature vector for the dynamic analysis and motion recognition of EMG signals.
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Acknowledgments
This work was supported by grants of National Natural Science Foundation of China (Grant Nos. 51575407, 51575338, 51575412) and the UK Engineering and Physical Science Research Council (Grant No. EP/G041377/1).
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Tang, H. et al. (2017). Rehabilitation Training for Leg Based on EEG-EMG Fusion. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10462. Springer, Cham. https://doi.org/10.1007/978-3-319-65289-4_49
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DOI: https://doi.org/10.1007/978-3-319-65289-4_49
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