The Classification and Objective Measure of Strength of an Exercise via Analysis of Electromyography

In recent years, telehealth and telerehabilitation have been on the rise due to lockdown and quarantine placing restrictions on in-person healthcare during the 2020 COVID-19 Pandemic. However, there are some limitations to the service that physicians are able to do remotely. This paper proposes a contemporary way of collecting more data from the remote patient to help during their telerehabilitation appointments. Surface electrodes are placed on the participants’ forearm flexor muscles, and samples were collected for each exercise. The data were then analyzed, and the features-RMS, IEMG, and VARwere used. The exertion of the strength of the muscle during an exercise could be seen from plotting the RMS of the exercise to the IEMG time domain graph, and the classification of the exercise could be interpreted from the IEMG data from one exercise, that has been normalized, which was plotted as a box plot diagram to be compared with the other exercises. The findings from this paper could be used in helping to build a model to ensure that the exercises are done correctly and the muscles are not being strained too hard during an exercise by the physician during a telerehabilitation session.

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Published
2024-10-24
DOI
https://doi.org/10.1109/asiancomnet63184.2024.10811064
Primary Topic
Muscle activation and electromyography studies
Type
article
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article

The Classification and Objective Measure of Strength of an Exercise via Analysis of Electromyography

Lerson Kirasamuthranon, Panusorn Hanchaikul, Minchaya Sirilerdsacksakul, Preeyaporn Manichan
Muscle activation and electromyography studies
article

The Classification and Objective Measure of Strength of an Exercise via Analysis of Electromyography

Lerson Kirasamuthranon, Panusorn Hanchaikul, Minchaya Sirilerdsacksakul, Preeyaporn Manichan
article en

Abstract

In recent years, telehealth and telerehabilitation have been on the rise due to lockdown and quarantine placing restrictions on in-person healthcare during the 2020 COVID-19 Pandemic. However, there are some limitations to the service that physicians are able to do remotely. This paper proposes a contemporary way of collecting more data from the remote patient to help during their telerehabilitation appointments. Surface electrodes are placed on the participants’ forearm flexor muscles, and samples were collected for each exercise. The data were then analyzed, and the features-RMS, IEMG, and VARwere used. The exertion of the strength of the muscle during an exercise could be seen from plotting the RMS of the exercise to the IEMG time domain graph, and the classification of the exercise could be interpreted from the IEMG data from one exercise, that has been normalized, which was plotted as a box plot diagram to be compared with the other exercises. The findings from this paper could be used in helping to build a model to ensure that the exercises are done correctly and the muscles are not being strained too hard during an exercise by the physician during a telerehabilitation session.

Bangkok University (TH), Srinakharinwirot University (TH), King Mongkut's University of Technology North Bangkok (TH)
Openalex Percentile: Top 77%
Muscle activation and electromyography studies
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