Development of a hardware-software system for gesture recognition based on electro-impedance, electromyographic, and force-myographic signals

Authors

DOI:

https://doi.org/10.15587/2706-5448.2025.340600

Keywords:

bionic manipulators, control, electrical impedance, electromyography, force myography, signals, analysis, proportional, anthropomorphic

Abstract

The object of the research is the process of gesture recognition and proportional assessment of muscle activity using electromyographic (EMG), electroimpedance (EI), and force myographic (FMG) signals. The subject of the research is methods and means of collecting and analyzing these signals to increase the accuracy of gesture recognition and assessment of muscle activity in real time.

The research is aimed at developing an integrated hardware and software system for collecting and analyzing EMG, EI, and FMG signals for gesture recognition and proportional assessment of muscle activity.

The problem that needs to be solved is the lack of reliable multimodal platforms capable of providing simultaneous acquisition, filtering, and digital processing of biosignals of various natures in real time. Existing solutions are limited to one or two modalities, are characterized by low noise immunity, and require complex equipment, which complicates practical use.

The proposed solution is based on the use of Ag/AgCl surface electrodes, piezoelectric and capacitive sensors in combination with multi-channel ADCs. Optimized filtering and amplification, digital processing and synchronization of signals, as well as data transfer via USB or UART to a personal computer, are implemented. The software performs frequency analysis based on the fast Fourier transform, visualization, and export of results.

Experimental studies have confirmed that the obtained signals correlate with motor activity: an increase in grip strength is accompanied by an increase in the amplitudes of FMG and EI, which allows for proportional control. The choice of optimal filtering frequencies, gain coefficients, and methods of sensor mounting made it possible to minimize noise and distortion, and the use of multi-channel ADCs ensured the processing of large volumes of data online.

The innovation of the development lies in the integration of bioelectrical and mechanical channels into a single multi-channel platform with support for up to 8 channels, high spatial and temporal resolution, and flexible architecture. This ensures high reliability and practical applicability of the system in rehabilitation, diagnostics, and control of bionic devices.

Author Biography

Anton Pastushenko, Vinnytsia National Technical University

PhD Student

Department of Biomedical Engineering and Optoelectronic Systems

References

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Development of a hardware-software system for gesture recognition based on electro-impedance, electromyographic, and force-myographic signals

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Published

2025-10-30

How to Cite

Pastushenko, A. (2025). Development of a hardware-software system for gesture recognition based on electro-impedance, electromyographic, and force-myographic signals. Technology Audit and Production Reserves, 5(1(85), 58–62. https://doi.org/10.15587/2706-5448.2025.340600

Issue

Vol. 5 No. 1(85) (2025): Industrial and technology systems

Section

Electrical Engineering and Industrial Electronics

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Copyright (c) 2025 Anton Pastushenko

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