| The number of the upper limb amputation patients is increasing because ofaccident and disease, which severely affects the normal life of the patients, so it isnecessary to study prosthetic hand with hand movement function. As the developmentin the physiological signal and corresponding detection technology, sEMG signals hasbeen widely used in clinical medicine, computer control, artificial intelligence and so onbecause of non-invasive and flexible method of signal processing, scholars at home andabroad have done a great deal of research in the application of prosthetic hand control,making staggered results, and sEMG signals has became been the ideal source in thecontrol of prosthetic limbs. Prosthetic hand, with intuitionistic and naturalcharacteristics, can help amputees with daily life and work and reduce the psychologicalpressure of patients, and prosthetic hand has important significance in clinicalrehabilitation.The premise that sEMG signal can be used for prosthetic limbs is to pick andanalysis sEMG signals which is from the body effectively. This paper first introducedmulti-channel and real-time sEMG detection system based on LabVIEW. This system iscomposed of analog processing unit and the software programming, analog processingunit includes pre-amplifier, band-pass filters,50Hz notch filter and power amplifiercircuit. The software programming part designed by LabVIEW which is a graphicprogramming language is mainly used to complete collection and analysis of signals.The software programming includes the collection display of signals and thecharacteristics analysis of time domain and frequency domain. Combining withelectrode array and experimental system about hand motor function, the systemcollected sEMG signal from the forearm muscles on subjects when the power wasincreasing and analyzed RMS and maxim power spectrum accordingly. Results showthat the detection system can realize the detection and analysis of time-frequencydomain characteristics about sEMG signal for4-channel, while RMS and the maximumpower spectrum is increasing with the strength level, which the sEMG signal can beused for the output control of prosthetic hand. In order to study the application of sEMGsignals in control of prosthetic hand, this topic designed a prosthetic hand refers to threefingers with stepping motor as a driving way. The digital signal processor (DSP)TMS320F2812finished real-time detection and analysis of sEMG signal under different level of strength, converting into the corresponding control signal that is used to outputto drive stepping motor, so as to control the output power of prosthetic hand.The topic designed a real-time detection and analysis system for sEMG signalbased on DSP first, including the acquisition circuit of sEMG signal and collection andanalysis based on DSP software. The system finished detection and analysis of sEMGsignal from subjects under different level of strength and gained the relationshipbetween sEMG signal and finger strength. And then the sEMG signal in different levelof strength was converted into the pulse signal PWM by digital signal processor (DSP)TMS320F2812, outputting to driver step motor and control the fingers strength ofprosthetic hand. On the other hand, the sEMG signal when the subjects’ fingers are indifferent motion position was real-time collected and used to realize flexion andextension control of the prosthetic hand movement. The experimental results show thatsEMG signal for muscle contraction under the different condition of exercise can beused to control the finger movement of prosthetic hand.System of sEMG signal detection and analysis and prosthetic hand control aremainly studied in this topic, and multi-channel sEMG signal analysis system can realizereal-time detection and analysis of time-frequency domain, the sEMG signal collectedcan be used to control prosthetic hand, contributing to further research for theapplication of the prosthetic hand control based on pattern recognition of multi-channelsEMG signal. |
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