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A Way of Bionic Control Based on EI, EMG, and FMG Signals
Creating highly functional prosthetic, orthotic, and rehabilitation devices is a socially relevant scientific and engineering task. Currently, certain constraints hamper the development of such devices. The primary constraint is the lack of an intuitive and reliable control interface working between...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747574/ https://www.ncbi.nlm.nih.gov/pubmed/35009694 http://dx.doi.org/10.3390/s22010152 |
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author | Briko, Andrey Kapravchuk, Vladislava Kobelev, Alexander Hammoud, Ahmad Leonhardt, Steffen Ngo, Chuong Gulyaev, Yury Shchukin, Sergey |
author_facet | Briko, Andrey Kapravchuk, Vladislava Kobelev, Alexander Hammoud, Ahmad Leonhardt, Steffen Ngo, Chuong Gulyaev, Yury Shchukin, Sergey |
author_sort | Briko, Andrey |
collection | PubMed |
description | Creating highly functional prosthetic, orthotic, and rehabilitation devices is a socially relevant scientific and engineering task. Currently, certain constraints hamper the development of such devices. The primary constraint is the lack of an intuitive and reliable control interface working between the organism and the actuator. The critical point in developing these devices and systems is determining the type and parameters of movements based on control signals recorded on an extremity. In the study, we investigate the simultaneous acquisition of electric impedance (EI), electromyography (EMG), and force myography (FMG) signals during basic wrist movements: grasping, flexion/extension, and rotation. For investigation, a laboratory instrumentation and software test setup were made for registering signals and collecting data. The analysis of the acquired signals revealed that the EI signals in conjunction with the analysis of EMG and FMG signals could potentially be highly informative in anthropomorphic control systems. The study results confirm that the comprehensive real-time analysis of EI, EMG, and FMG signals potentially allows implementing the method of anthropomorphic and proportional control with an acceptable delay. |
format | Online Article Text |
id | pubmed-8747574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87475742022-01-11 A Way of Bionic Control Based on EI, EMG, and FMG Signals Briko, Andrey Kapravchuk, Vladislava Kobelev, Alexander Hammoud, Ahmad Leonhardt, Steffen Ngo, Chuong Gulyaev, Yury Shchukin, Sergey Sensors (Basel) Article Creating highly functional prosthetic, orthotic, and rehabilitation devices is a socially relevant scientific and engineering task. Currently, certain constraints hamper the development of such devices. The primary constraint is the lack of an intuitive and reliable control interface working between the organism and the actuator. The critical point in developing these devices and systems is determining the type and parameters of movements based on control signals recorded on an extremity. In the study, we investigate the simultaneous acquisition of electric impedance (EI), electromyography (EMG), and force myography (FMG) signals during basic wrist movements: grasping, flexion/extension, and rotation. For investigation, a laboratory instrumentation and software test setup were made for registering signals and collecting data. The analysis of the acquired signals revealed that the EI signals in conjunction with the analysis of EMG and FMG signals could potentially be highly informative in anthropomorphic control systems. The study results confirm that the comprehensive real-time analysis of EI, EMG, and FMG signals potentially allows implementing the method of anthropomorphic and proportional control with an acceptable delay. MDPI 2021-12-27 /pmc/articles/PMC8747574/ /pubmed/35009694 http://dx.doi.org/10.3390/s22010152 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Briko, Andrey Kapravchuk, Vladislava Kobelev, Alexander Hammoud, Ahmad Leonhardt, Steffen Ngo, Chuong Gulyaev, Yury Shchukin, Sergey A Way of Bionic Control Based on EI, EMG, and FMG Signals |
title | A Way of Bionic Control Based on EI, EMG, and FMG Signals |
title_full | A Way of Bionic Control Based on EI, EMG, and FMG Signals |
title_fullStr | A Way of Bionic Control Based on EI, EMG, and FMG Signals |
title_full_unstemmed | A Way of Bionic Control Based on EI, EMG, and FMG Signals |
title_short | A Way of Bionic Control Based on EI, EMG, and FMG Signals |
title_sort | way of bionic control based on ei, emg, and fmg signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747574/ https://www.ncbi.nlm.nih.gov/pubmed/35009694 http://dx.doi.org/10.3390/s22010152 |
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