Cargando…
Force-Invariant Improved Feature Extraction Method for Upper-Limb Prostheses of Transradial Amputees
A force-invariant feature extraction method derives identical information for all force levels. However, the physiology of muscles makes it hard to extract this unique information. In this context, we propose an improved force-invariant feature extraction method based on nonlinear transformation of...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151019/ https://www.ncbi.nlm.nih.gov/pubmed/34067203 http://dx.doi.org/10.3390/diagnostics11050843 |
_version_ | 1783698284826591232 |
---|---|
author | Islam, Md. Johirul Ahmad, Shamim Haque, Fahmida Reaz, Mamun Bin Ibne Bhuiyan, Mohammad Arif Sobhan Islam, Md. Rezaul |
author_facet | Islam, Md. Johirul Ahmad, Shamim Haque, Fahmida Reaz, Mamun Bin Ibne Bhuiyan, Mohammad Arif Sobhan Islam, Md. Rezaul |
author_sort | Islam, Md. Johirul |
collection | PubMed |
description | A force-invariant feature extraction method derives identical information for all force levels. However, the physiology of muscles makes it hard to extract this unique information. In this context, we propose an improved force-invariant feature extraction method based on nonlinear transformation of the power spectral moments, changes in amplitude, and the signal amplitude along with spatial correlation coefficients between channels. Nonlinear transformation balances the forces and increases the margin among the gestures. Additionally, the correlation coefficient between channels evaluates the amount of spatial correlation; however, it does not evaluate the strength of the electromyogram signal. To evaluate the robustness of the proposed method, we use the electromyogram dataset containing nine transradial amputees. In this study, the performance is evaluated using three classifiers with six existing feature extraction methods. The proposed feature extraction method yields a higher pattern recognition performance, and significant improvements in accuracy, sensitivity, specificity, precision, and F1 score are found. In addition, the proposed method requires comparatively less computational time and memory, which makes it more robust than other well-known feature extraction methods. |
format | Online Article Text |
id | pubmed-8151019 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81510192021-05-27 Force-Invariant Improved Feature Extraction Method for Upper-Limb Prostheses of Transradial Amputees Islam, Md. Johirul Ahmad, Shamim Haque, Fahmida Reaz, Mamun Bin Ibne Bhuiyan, Mohammad Arif Sobhan Islam, Md. Rezaul Diagnostics (Basel) Article A force-invariant feature extraction method derives identical information for all force levels. However, the physiology of muscles makes it hard to extract this unique information. In this context, we propose an improved force-invariant feature extraction method based on nonlinear transformation of the power spectral moments, changes in amplitude, and the signal amplitude along with spatial correlation coefficients between channels. Nonlinear transformation balances the forces and increases the margin among the gestures. Additionally, the correlation coefficient between channels evaluates the amount of spatial correlation; however, it does not evaluate the strength of the electromyogram signal. To evaluate the robustness of the proposed method, we use the electromyogram dataset containing nine transradial amputees. In this study, the performance is evaluated using three classifiers with six existing feature extraction methods. The proposed feature extraction method yields a higher pattern recognition performance, and significant improvements in accuracy, sensitivity, specificity, precision, and F1 score are found. In addition, the proposed method requires comparatively less computational time and memory, which makes it more robust than other well-known feature extraction methods. MDPI 2021-05-07 /pmc/articles/PMC8151019/ /pubmed/34067203 http://dx.doi.org/10.3390/diagnostics11050843 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 Islam, Md. Johirul Ahmad, Shamim Haque, Fahmida Reaz, Mamun Bin Ibne Bhuiyan, Mohammad Arif Sobhan Islam, Md. Rezaul Force-Invariant Improved Feature Extraction Method for Upper-Limb Prostheses of Transradial Amputees |
title | Force-Invariant Improved Feature Extraction Method for Upper-Limb Prostheses of Transradial Amputees |
title_full | Force-Invariant Improved Feature Extraction Method for Upper-Limb Prostheses of Transradial Amputees |
title_fullStr | Force-Invariant Improved Feature Extraction Method for Upper-Limb Prostheses of Transradial Amputees |
title_full_unstemmed | Force-Invariant Improved Feature Extraction Method for Upper-Limb Prostheses of Transradial Amputees |
title_short | Force-Invariant Improved Feature Extraction Method for Upper-Limb Prostheses of Transradial Amputees |
title_sort | force-invariant improved feature extraction method for upper-limb prostheses of transradial amputees |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151019/ https://www.ncbi.nlm.nih.gov/pubmed/34067203 http://dx.doi.org/10.3390/diagnostics11050843 |
work_keys_str_mv | AT islammdjohirul forceinvariantimprovedfeatureextractionmethodforupperlimbprosthesesoftransradialamputees AT ahmadshamim forceinvariantimprovedfeatureextractionmethodforupperlimbprosthesesoftransradialamputees AT haquefahmida forceinvariantimprovedfeatureextractionmethodforupperlimbprosthesesoftransradialamputees AT reazmamunbinibne forceinvariantimprovedfeatureextractionmethodforupperlimbprosthesesoftransradialamputees AT bhuiyanmohammadarifsobhan forceinvariantimprovedfeatureextractionmethodforupperlimbprosthesesoftransradialamputees AT islammdrezaul forceinvariantimprovedfeatureextractionmethodforupperlimbprosthesesoftransradialamputees |