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Iranian Journal of Medical Physics، جلد ۸، شماره ۱، صفحات ۳۱-۴۰
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عنوان انگلیسی Detecting and Predicting Muscle Fatigue during Typing By SEMG Signal Processing and Artificial Neural Networks
چکیده انگلیسی مقاله Introduction: Repetitive strain injuries are one of the most prevalent problems in occupational diseases. Repetition, vibration and bad postures of the extremities are physical risk factors related to work that can cause chronic musculoskeletal disorders. Repetitive work on a computer with low level contraction requires the posture to be maintained for a long time, which can cause muscle fatigue. Muscle fatigue in shoulders and neck is one of the most prevalent problems reported with computer users especially during typing. Surface electromyography (SEMG) signals are used for detecting muscle fatigue as a non-invasive method. Material and Methods: Nine healthy females volunteered for signal recoding during typing. EMG signals were recorded from the trapezius muscle, which is subjected to muscle fatigue during typing. After signal analysis and feature extraction, detecting and predicting muscle fatigue was performed by using the MLP artificial neural network. Results: Recorded signals were analyzed in time and frequency domains for feature extraction. Results of classification showed that the MLP neural network can detect and predict muscle fatigue during typing with 80.79 % ± 1.04% accuracy. Conclusion: Intelligent classification and prediction of muscle fatigue can have many applications in human factors engineering (ergonomics), rehabilitation engineering and biofeedback equipment for mitigating the injuries of repetitive works.
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نویسندگان مقاله الهام قوچانی | elham ghoochani
m.sc. in biomedical engineering, young researchers club, islamic azad university, mashhad branch, mashhad, iran.

سازمان اصلی تایید شده: دانشگاه آزاد اسلامی علوم و تحقیقات (Islamic azad university science and research branch)

سعید راحتی قوچانی | saeed rahati ghoochani
assistant professor of electric engineering, islamic azad university, mashhad branch, mashhad, iran.

سازمان اصلی تایید شده: دانشگاه آزاد اسلامی علوم و تحقیقات (Islamic azad university science and research branch)

محمد راوری | mohammad ravari
ِm.sc., biomedical engineering dept., mashhad branch, islamic azad university, mashhad, iran

سازمان اصلی تایید شده: دانشگاه آزاد اسلامی علوم و تحقیقات (Islamic azad university science and research branch)

حسین اصغر حسینی | hossein asghar hoseyni
assistant professor, physical therapy dept., faculty of paramedical science, mashhad university of medical sciences, mashhad, iran.

سازمان اصلی تایید شده: دانشگاه علوم پزشکی مشهد (Mashhad university of medical sciences)

نشانی اینترنتی http://ijmp.mums.ac.ir/article_7205.html
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Original Paper
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