Evaluating EMG Signal Characteristics for Differential Diagnosis of Myopathies to Prohibit Contractures
Download| Volume 6 Issue 2, 2025 | |
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| Author(s): |
Mehwish Faiz Ziauddin University, Karachi, mehwish.faiz@zu.edu.pk Samia Kidwai Ziauddin University, Karachi, samia.17030@zu.edu.pk Muskan Moin Ziauddin University, Karachi, muskan.16434@zu.edu.pk Aneela Kiran The Begum Nusrat Bhutto Women University, Sukkur, aneelakiranansari73@gmail.com Shahzad Nasim The Begum Nusrat Bhutto Women University, Sukkur, shahzad.nasim@bnbwu.edu.pk |
| Abstract | Neuromuscular disorders, such as myopathy are a major cause of muscle weakness, fatigue and dysfunction. Electromyography (EMG) is a diagnostic tool used to identify muscle disorders based on the analysis of electrical signals from the muscles. This study based on EMG-signal analysis to differentiate between healthy individuals and myopathic patients using the software MATLAB. The methodology involves preprocessing of the bio signals through statistical analysis, Root Mean Square (RMS), peak detection, envelope analysis, Power Spectral Density (PSD), cross-correlation, and coherence analysis. Publicly available EMG datasets from PhysioNet were used for healthy individuals and myopathic patients sampled at 1kHz. Unlike other works that use machine learning and classification for this purpose, the approach in this research paper does not contain classification, which makes the analysis more interpretable and reproducible. The results show a clear difference between the healthy and myopathic signals including reduced amplitude, decreased peak distribution, lower RMS values, and lower spectral power in myopathic signals, indicating reduced muscle activity and neuromuscular efficiency in myopathic patients. These findings reveal that the use of complex algorithms for signal detection does not achieve the same sensitivity as MATLAB scripts; as a result, the interpretation of the signal’s properties is straightforward, and there are no components such as deep learning. |
| Keywords | Electromyography (EMG), Myopathy Detection, MATLAB, Biomedical Signal Analysis, Clinical Neurophysiology. |
| Year | 2025 |
| Volume | 6 |
| Issue | 2 |
| Type | Research paper, manuscript, article |
| Recognized by | Higher Education Commission of Pakistan, HEC | Category | Journal Name | ILMA Journal of Technology & Software Management | Publisher Name | ILMA University | Jel Classification | -- | DOI | - | ISSN no (E, Electronic) | 2790-590X | ISSN no (P, Print) | 2709-2240 | Country | Pakistan | City | Karachi | Institution Type | University | Journal Type | Open Access | Manuscript Processing | Blind Peer Reviewed | Format | Paper Link | https://ijtsm.ilmauniversity.edu.pk/arc/Vol6/i2/pdf3.pdf | Page | 59-63 |