| Rehabilitation robots are used for the treatment of limb function disorder,restore the body tissue motion function to realize the action of the natural body equipment.Most of the rehabilitation robots use EEG/EMG as the control signal,so it is very meaningful to study the relationship between electroencephalograph(EEG)and electromyography(EMG)for rehabilitation robots innovation.In this paper,a physiological signal acquisition system is designed to collect EEG and EMG,the method of signal feature extraction is studied,a model for the forecast between EEG and EMG is proposed.First of all,combined with physiological characteristics of EEG/EMG and standard acquisition requirements,the overall design of the acquisition system is given,including the architectures of hardware and software.Secondly,the detailed design of hardware and software of the physiological signal acquisition system are given.The hardware is consisted of the DSP peripheral circuit module,the data acquisition module,the communication management module,the power management module.The software of the system is divided into software of an upper computer and a lower computer.The Ethernet is used as the communication tools by the upper and lower computers,which achieve the transmission of signals.Thirdly,The detrended fluctuation analysis method based on EMD is proposed,in order to solve the detrended method removing useful signal.The method solved the trended element in fluctuation analysis.The character of EMG and EEG is confirmed including fluctuation coefficient,mean value,root-mean-square and character spectrum.These characters are used for forecast.Fourthly,Based on the mean value,root-mean-square,spectrum of EMG and fluctuation coefficient of EEG,the forecast model of time series of EEG&EMG is given,combined with multiple self-regression analysis.Finally,the forecast model was verified by acquisition and analysis experiment,the result indicated that the system achieved the preestablished requirement. |
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