基于时间序列特征的肌电模式识别:初步结果

1993 IEEE Annual Northeast Bioengineering Conference Pub Date : 1993-03-18 DOI:10.1109/NEBC.1993.404442

R. Knox, D.H. Brooks, E. Manolakos, S. Markogiannakis

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引用次数: 4

摘要

总结了从上肢肌电图(EMG)信号中获得的特征结果。特征基于自回归(AR)模型，包括模型系数、反射系数和倒谱系数。其中一些系数显示了肌电图控制假肢上肢运动模式识别的潜力。

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Time-series based features for EMG pattern recognition: Preliminary results

A summary of results for features obtained from upper limb electromyographic (EMG) signals is given. The features are based on the autoregressive (AR) model and include model coefficients, reflection coefficients, and cepstral coefficients. Some of these coefficients demonstrate potential for pattern recognition of upper limb movements for a EMG controlled prosthesis.<>

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1993 IEEE Annual Northeast Bioengineering Conference

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