震颤信号分析的研究现状及展望

震颤是人身体某一个或多个功能区肌肉的节律性、不自主振动,是运动神经元异常同步化的结果。用信号处理的方法检测分析震颤患者加速度(accelerometer,ACC)、表面肌电(electromyography,EMG)、脑电(electroencephalography,EEG)信号对震颤临床诊断、等级评定、疾病早期发现等方面具有重要意义。介绍了时域分析、频域分析、人工神经网络、高阶谱、近似熵、模糊、浑沌、判别分析等方法在震颤信号研究中的应用情况,最后展望了震颤信号分析的应用前景。

The Current Situation and Development of Tremor Signals Analysis

Tremor, a rhythmic and involuntary oscillatory movement of one or several body parts, is the movement resulting from the abnormal synchronization of motor neural units. Detecting and analyzing the ACC, EMG and EEG signals of tremor patients by signal processing methods are very important for clinical diagnosis,rating evaluation and detection of incipient illness. This paper introduces the applications of time domain,frequency domain,artificial neural network,high order accumulation,approximate entropy,fuzzy,chaos,discriminant analysis in the researches of tremor signals, and finally points out the application foreground of researches on tremor signals.