Advantages of Nanosensors in the Development of Interfaces for Bioelectric Prostheses

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.

Original language	English
Article number	01051
Journal	MATEC Web of Conferences
Volume	79
DOIs	https://doi.org/10.1051/matecconf/20167901051
Publication status	Published - 11 Oct 2016
Event	7th Scientific Conference on Information-Measuring Equipment and Technologies, IME and T 2016 - Tomsk, Russian Federation Duration: 25 May 2016 → 28 May 2016

ASJC Scopus subject areas

Chemistry(all)
Engineering(all)
Materials Science(all)

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10.1051/matecconf/20167901051

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Avdeeva, D., Zakharchenko, E., Nguyen, D. Q., Turushev, N., Abdrakhmanov, A., Vorona, R., Popkov, A., & Tverdokhlebov, S. (2016). Advantages of Nanosensors in the Development of Interfaces for Bioelectric Prostheses. MATEC Web of Conferences, 79, [01051]. https://doi.org/10.1051/matecconf/20167901051

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title = "Advantages of Nanosensors in the Development of Interfaces for Bioelectric Prostheses",

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.",

author = "Diana Avdeeva and Ekaterina Zakharchenko and Nguyen, {Dang Quang} and Nikita Turushev and Aryslan Abdrakhmanov and Roman Vorona and Arnold Popkov and Sergey Tverdokhlebov",

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AU - Avdeeva, Diana

AU - Zakharchenko, Ekaterina

AU - Nguyen, Dang Quang

AU - Turushev, Nikita

AU - Abdrakhmanov, Aryslan

AU - Vorona, Roman

AU - Popkov, Arnold

AU - Tverdokhlebov, Sergey

PY - 2016/10/11

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AB - 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.

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