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Clinical detection and movement recognition of neuro signals

摘要Neuro signal has many more advantages than myoelectricity in providing information for prosthesis control, and can be an ideal source for developing new prosthesis. In this work, by implanting intrafascicular electrode clinically in the amputee's upper extremity, collective signals from fascicules of three main nerves (radial nerve, ulnar nerve and medium nerve) were successfully detected with sufficient fidelity and without infection. Initial analysis of features under different actions was performed and movement recognition of detected samples was attempted. Singular value decomposition features (SVD) extracted from wavelet coefficients were used as inputs for neural network classifier to predict amputee's movement intentions. The whole training rate was up to 80.94% and the test rate was 56.87% without over-training. This result gives inspiring prospect that collective signals from fascicules of the three main nerves are feasible sources for controlling prosthesis. Ways for improving accuracy in developing prosthesis controlled by neuro signals are discussed in the end.

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作者单位 Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China [1] Zhongshan Hospital, Medical Center, Fudan University, Shanghai 200032, China [2]
发布时间 2005-06-02(万方平台首次上网日期,不代表论文的发表时间)
基金项目
国家自然科学基金(39930070)
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浙江大学学报B(英文版)

浙江大学学报B(英文版)

2005年6卷4期

272-279页

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