采用基于二阶统计量的盲源分离算法对多导表面肌电信号进行处理，实现噪声的分离和表面肌电信号的初步分解。
Some methods of SEMG signal pretreatment based on blind source separation using second order statistics were proposed for noise separation and the elementary decomposition of multi-channel SEMG.
采用可重复性好、受噪声影响小的电刺激方式诱发表面肌电信号（SEMG）。
Electrically evoked SEMG signals which are high repeatability and little influenced by noise were adopted in the experiment.
试验结果表明，采用该SEMG检测电极可以进一步提高信噪比，减少噪声，提取到有效的表面肌电信号。
The Experimental result shows that the SEMG detection electrode can further improve SNR, reduce the noise and get effective surface electromyographic signal.
试验结果表明，采用该SEMG检测电极可以进一步提高信噪比，减少噪声，提取到有效的表面肌电信号。
The Experimental result shows that the SEMG detection electrode can further improve SNR, reduce the noise and get effective surface electromyographic signal.
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