脑卒中患者表面肌电特征提取方法研究

2012 Fifth International Conference on Intelligent Networks and Intelligent Systems Pub Date : 2012-11-01 DOI:10.1109/ICINIS.2012.78

Ren Liye, W. Xiaoli, Wang Xiao

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引用次数: 3

摘要

表面肌电图是从皮肤表面记录的神经肌肉系统的一维时间序列信号。能准确反映肌肉活动状态和肌肉功能状态。在实验中，所有受试者都必须对中风患者的膝关节屈伸进行动态收缩。表面肌电图由表面电极采集，经线性时频域法处理。进行了表面肌电信号特征提取，建立了模式识别的特征向量空间，为脑卒中患者康复训练奠定了理论和技术基础。

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Research of Feature Extraction Method for Stroke Patients' Surface Electromyography

Surface electromyography is a one-dimensional time series signal of neuromuscular system recorded from skin surface. It can reflect the states of muscle activity and muscle function accurately. All the subjects had to perform dynamic contraction for stroke's knee flexion and extension in experiment. The surface electromyography were collected by surface electrodes and then processed by linear time and frequency-domain method. SEMG characteristics extraction has been done and an eigenvector space of mode recognition was built, and lies the theoretical and technical foundation for stroke patients' rehabilitation training.

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2012 Fifth International Conference on Intelligent Networks and Intelligent Systems

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