The analysis of muscle activity during the gait cycle based upon surface electromyography measurement and signal processing methods
The analysis of muscle activity during the gait cycle based upon surface electromyography measurement and signal processing methods
In the analysis of different gait patterns during normal and pathological walking, the surface electromyography (EMG) offers a safe and non-invasive approach to assess the muscle activity and function. The correlation between the surface EMG and gait analysis is addressed in this study to provide valuable information on muscle activity of clinical interest. The history and characteristics of the surface EMG during various clinical applications are reviewed at eh beginning of this thesis. Physiological details, measurement, and acquisition system of the surface EMG are introduced. The fundamental concepts of gait analysis, such as gait phases and muscle control during different gait patterns are also described. To assess new methods and algorithms used to explore the muscle activity during the gait cycle, a model is generated with a multiple-layer structure, which contains most of features of the surface EMG, such as the fibre distribution, motor unit type, location and recruitment, tissue anisotropy, electrode configuration, and gait phases. A series of simulated surface EMG signals during the gait cycle are then produced by modifying the values of existing modular parameters depending upon the anatomical conditions and detection system configuration. Comparing the simulated signals with real EMG data, the results illustrate that the simulated signals are able to reproduce the surface EMG signals. The model has the potential to facilitate the assessment of algorithms or methods that are used to process normal or abnormal surface EMG signals during normal or pathological gait. Based upon the simulation model, an algorithm to detect the timing of muscle activation is developed in order to overcome shortcomings of approaches proposed previously, and is then used to process the real raw surface EMG signals recorded from the lower limb muscles during gait. The performance of the algorithm indicates that it is more suitable than previous methods for the estimation of muscle activation intervals.
University of Southampton
Wang, Wei
85862755-49c9-4c7d-a1f4-d838d35cb7b7
2005
Wang, Wei
85862755-49c9-4c7d-a1f4-d838d35cb7b7
Wang, Wei
(2005)
The analysis of muscle activity during the gait cycle based upon surface electromyography measurement and signal processing methods.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
In the analysis of different gait patterns during normal and pathological walking, the surface electromyography (EMG) offers a safe and non-invasive approach to assess the muscle activity and function. The correlation between the surface EMG and gait analysis is addressed in this study to provide valuable information on muscle activity of clinical interest. The history and characteristics of the surface EMG during various clinical applications are reviewed at eh beginning of this thesis. Physiological details, measurement, and acquisition system of the surface EMG are introduced. The fundamental concepts of gait analysis, such as gait phases and muscle control during different gait patterns are also described. To assess new methods and algorithms used to explore the muscle activity during the gait cycle, a model is generated with a multiple-layer structure, which contains most of features of the surface EMG, such as the fibre distribution, motor unit type, location and recruitment, tissue anisotropy, electrode configuration, and gait phases. A series of simulated surface EMG signals during the gait cycle are then produced by modifying the values of existing modular parameters depending upon the anatomical conditions and detection system configuration. Comparing the simulated signals with real EMG data, the results illustrate that the simulated signals are able to reproduce the surface EMG signals. The model has the potential to facilitate the assessment of algorithms or methods that are used to process normal or abnormal surface EMG signals during normal or pathological gait. Based upon the simulation model, an algorithm to detect the timing of muscle activation is developed in order to overcome shortcomings of approaches proposed previously, and is then used to process the real raw surface EMG signals recorded from the lower limb muscles during gait. The performance of the algorithm indicates that it is more suitable than previous methods for the estimation of muscle activation intervals.
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Published date: 2005
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Local EPrints ID: 465874
URI: http://eprints.soton.ac.uk/id/eprint/465874
PURE UUID: c550c444-4ccb-4963-90b4-57e9f1d6afdc
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Date deposited: 05 Jul 2022 03:23
Last modified: 16 Mar 2024 20:25
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Author:
Wei Wang
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