Abstract. The present research aims to explore the bioelectric activity of muscles using a high-resolution electromyograph and to analyze the prospects of the electromyograph to develop bioelectric patterns for the prosthesis control method based on the data recognition system. The activity of the healthy forearm muscles was investigated during the cyclic activity of fingers in different modes. In addition, the impact of filters on the quality and informativity of myoelectric signals, as well as on the development of bioelectric activity patterns was analyzed. The virtually developed bandpass filters were utilized as experimental filters. The filter impact analysis included the comparison of the signal recorded in the frequency band from 0 to 10000 Hz with the signal filtered in the frequency band from 20 to 500 Hz. The research revealed the advantages of a high-resolution electromyogram for the pattern recognition-based myocontrol.
Abstract.The problems of designing the system for automatic analysis of cardiograms are considered. The structure of the system for recording and storing electrocardiograms was formed. The procedures that make up the complex of automatic analysis are listed.
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