Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based Filters
Surface electromyography (sEMG) signals acquired with linear electrode array are useful in analyzing muscle anatomy and physiology. Most algorithms for signal processing, detection, and estimation require adequate quality of the input signals, however, multi-channel sEMG signals are commonly contami...
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doaj-23be36c967ee4bf6bfa76748d77be6fd2020-11-25T02:50:08ZengMDPI AGApplied Sciences2076-34172020-07-01105099509910.3390/app10155099Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based FiltersKhalil Ullah0Khalil Khan1Muhammad Amin2Muhammad Attique3Tae-Sun Chung4Rabia Riaz5Department of Software Engineering, University of Malakand, Chakdara 18800, PakistanDepartment of Electrical Engineering, University of Azad Jammu and Kashmir, Muzafarabbad 13100, PakistanDepartment of Computer Science, Iqra National University, Peshawar 25000, PakistanDepartment of Software, Sejong University, Seoul 05006, KoreaDepartment of Computer Engineering, Ajou University, Ajou 16499, KoreaDepartment of Computer Science, University of Azad Jammu and Kashmir, Muzafarabbad 13100, PakistanSurface electromyography (sEMG) signals acquired with linear electrode array are useful in analyzing muscle anatomy and physiology. Most algorithms for signal processing, detection, and estimation require adequate quality of the input signals, however, multi-channel sEMG signals are commonly contaminated due to several noise sources. The sEMG signal needs to be enhanced prior to the digital signal and image processing to achieve the best results. This study is using spatio-temporal images to represent surface EMG signals. The motor unit action potential (MUAP) in these images looks like a linear structure, making certain angles with the x-axis, depending on the conduction velocity of the MU. A multi-scale Hessian-based filter is used to enhance the linear structure, i.e., the MUAP region, and to suppress the background noise. The proposed framework is compared with some of the existing algorithms using synthetic, simulated, and experimental sEMG signals. Results show improved detection accuracy of the motor unit action potential after the proposed enhancement as a preprocessing step.https://www.mdpi.com/2076-3417/10/15/5099sEMGspatio-temporal imageimage enhancementmulti-scale Hessian-based filter |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Khalil Ullah Khalil Khan Muhammad Amin Muhammad Attique Tae-Sun Chung Rabia Riaz |
spellingShingle |
Khalil Ullah Khalil Khan Muhammad Amin Muhammad Attique Tae-Sun Chung Rabia Riaz Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based Filters Applied Sciences sEMG spatio-temporal image image enhancement multi-scale Hessian-based filter |
author_facet |
Khalil Ullah Khalil Khan Muhammad Amin Muhammad Attique Tae-Sun Chung Rabia Riaz |
author_sort |
Khalil Ullah |
title |
Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based Filters |
title_short |
Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based Filters |
title_full |
Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based Filters |
title_fullStr |
Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based Filters |
title_full_unstemmed |
Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based Filters |
title_sort |
multi-channel surface emg spatio-temporal image enhancement using multi-scale hessian-based filters |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2020-07-01 |
description |
Surface electromyography (sEMG) signals acquired with linear electrode array are useful in analyzing muscle anatomy and physiology. Most algorithms for signal processing, detection, and estimation require adequate quality of the input signals, however, multi-channel sEMG signals are commonly contaminated due to several noise sources. The sEMG signal needs to be enhanced prior to the digital signal and image processing to achieve the best results. This study is using spatio-temporal images to represent surface EMG signals. The motor unit action potential (MUAP) in these images looks like a linear structure, making certain angles with the x-axis, depending on the conduction velocity of the MU. A multi-scale Hessian-based filter is used to enhance the linear structure, i.e., the MUAP region, and to suppress the background noise. The proposed framework is compared with some of the existing algorithms using synthetic, simulated, and experimental sEMG signals. Results show improved detection accuracy of the motor unit action potential after the proposed enhancement as a preprocessing step. |
topic |
sEMG spatio-temporal image image enhancement multi-scale Hessian-based filter |
url |
https://www.mdpi.com/2076-3417/10/15/5099 |
work_keys_str_mv |
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