Analysis of Surface EMG Parameters in the Overhead Deep Squat Performance
<b>Background and Objective:</b> This study aimed to examine the possibility of using surface electromyography (sEMG) to aid in assessing the correctness of overhead deep squat performance. Electromyography signals were recorded for 20 athletes from the lower (rectus femoris (RF), vastus...
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2025-07-01
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| author | Dariusz Komorowski Barbara Mika |
| author_facet | Dariusz Komorowski Barbara Mika |
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| description | <b>Background and Objective:</b> This study aimed to examine the possibility of using surface electromyography (sEMG) to aid in assessing the correctness of overhead deep squat performance. Electromyography signals were recorded for 20 athletes from the lower (rectus femoris (RF), vastus medialis (VM), biceps femoris (BF), and gluteus (GM)) and upper (deltoid (D), latissimus dorsi (L)) muscles. The sEMG signals were categorized into three groups based on physiotherapists’ evaluations of deep squat correctness. <b>Methods:</b> The raw sEMG signals were filtering at 10–250 Hz, and then the mean frequency, median frequency, and kurtosis were calculated. Next, the maximum excitation of the muscles expressed in percentage of maximum voluntary contraction (%MVC) and co-activation index (<i>CAI</i>) were estimated. To determine the muscle excitation level, the pulse interference filter and variance analysis of the sEMG signal derivative were applied. Next, analysis of variance (ANOVA) tests, that is, nonparametric Kruskal–Wallis and post hoc tests, were performed. <b>Results:</b> The parameter that most clearly differentiated the groups considered turned out to be %MVC. The statistically significant difference with a large effect size in the excitation of RF & GM (<i>p</i> = 0.0011) and VM & GM (<i>p</i> = 0.0002) in group 3, where the correctness of deep squat execution was the highest and ranged from 85% to 92%, was pointed out. With the decrease in the correctness of deep squat performance, an additional statistically significant difference appeared in the excitation of RF & BF and VM & BF for both groups 2 and 1, which was not present in group 3. However, in group 2, with the correctness of the deep squat execution at 62–77%, the statistically significant differences in muscle excitation found in group 3 were preserved, in contrast to group 1, with the lowest 23–54% correctness of the deep squat execution, where the statistical significance of these differences was not confirmed. <b>Conclusions:</b> The results indicate that sEMG can differentiate muscle activity and provide additional information for physiotherapists when assessing the correctness of deep squat performance. The proposed analysis can be used to evaluate the correctness of physical exercises when physiotherapist access is limited. |
| format | Article |
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| institution | DOAJ |
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| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Applied Sciences |
| spelling | doaj-art-b5d7237ece7b4a2fb08fc698c4b267942025-08-20T03:13:39ZengMDPI AGApplied Sciences2076-34172025-07-011514774910.3390/app15147749Analysis of Surface EMG Parameters in the Overhead Deep Squat PerformanceDariusz Komorowski0Barbara Mika1Faculty of Biomedical Engineering, Department of Medical Informatics and Artificial Intelligence, Silesian University of Technology, Roosevelt 40, 41-800 Zabrze, PolandFaculty of Biomedical Engineering, Department of Medical Informatics and Artificial Intelligence, Silesian University of Technology, Roosevelt 40, 41-800 Zabrze, Poland<b>Background and Objective:</b> This study aimed to examine the possibility of using surface electromyography (sEMG) to aid in assessing the correctness of overhead deep squat performance. Electromyography signals were recorded for 20 athletes from the lower (rectus femoris (RF), vastus medialis (VM), biceps femoris (BF), and gluteus (GM)) and upper (deltoid (D), latissimus dorsi (L)) muscles. The sEMG signals were categorized into three groups based on physiotherapists’ evaluations of deep squat correctness. <b>Methods:</b> The raw sEMG signals were filtering at 10–250 Hz, and then the mean frequency, median frequency, and kurtosis were calculated. Next, the maximum excitation of the muscles expressed in percentage of maximum voluntary contraction (%MVC) and co-activation index (<i>CAI</i>) were estimated. To determine the muscle excitation level, the pulse interference filter and variance analysis of the sEMG signal derivative were applied. Next, analysis of variance (ANOVA) tests, that is, nonparametric Kruskal–Wallis and post hoc tests, were performed. <b>Results:</b> The parameter that most clearly differentiated the groups considered turned out to be %MVC. The statistically significant difference with a large effect size in the excitation of RF & GM (<i>p</i> = 0.0011) and VM & GM (<i>p</i> = 0.0002) in group 3, where the correctness of deep squat execution was the highest and ranged from 85% to 92%, was pointed out. With the decrease in the correctness of deep squat performance, an additional statistically significant difference appeared in the excitation of RF & BF and VM & BF for both groups 2 and 1, which was not present in group 3. However, in group 2, with the correctness of the deep squat execution at 62–77%, the statistically significant differences in muscle excitation found in group 3 were preserved, in contrast to group 1, with the lowest 23–54% correctness of the deep squat execution, where the statistical significance of these differences was not confirmed. <b>Conclusions:</b> The results indicate that sEMG can differentiate muscle activity and provide additional information for physiotherapists when assessing the correctness of deep squat performance. The proposed analysis can be used to evaluate the correctness of physical exercises when physiotherapist access is limited.https://www.mdpi.com/2076-3417/15/14/7749overhead deep squatEMGmuscle excitation%MVC<i>CAI</i>median frequency |
| spellingShingle | Dariusz Komorowski Barbara Mika Analysis of Surface EMG Parameters in the Overhead Deep Squat Performance Applied Sciences overhead deep squat EMG muscle excitation %MVC <i>CAI</i> median frequency |
| title | Analysis of Surface EMG Parameters in the Overhead Deep Squat Performance |
| title_full | Analysis of Surface EMG Parameters in the Overhead Deep Squat Performance |
| title_fullStr | Analysis of Surface EMG Parameters in the Overhead Deep Squat Performance |
| title_full_unstemmed | Analysis of Surface EMG Parameters in the Overhead Deep Squat Performance |
| title_short | Analysis of Surface EMG Parameters in the Overhead Deep Squat Performance |
| title_sort | analysis of surface emg parameters in the overhead deep squat performance |
| topic | overhead deep squat EMG muscle excitation %MVC <i>CAI</i> median frequency |
| url | https://www.mdpi.com/2076-3417/15/14/7749 |
| work_keys_str_mv | AT dariuszkomorowski analysisofsurfaceemgparametersintheoverheaddeepsquatperformance AT barbaramika analysisofsurfaceemgparametersintheoverheaddeepsquatperformance |