Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9 September 2021, Sakarya, Turkey

Research Article

Investigation of the Effect of Diabetes on Lower Limb Muscles with Surface Electromyography (EMG)

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  • @INPROCEEDINGS{10.4108/eai.7-9-2021.2315286,
        author={Mahmoud I. Al-Kadi},
        title={Investigation of the Effect of Diabetes on Lower Limb Muscles with Surface Electromyography (EMG)},
        proceedings={Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9 September 2021, Sakarya, Turkey},
        publisher={EAI},
        proceedings_a={IMDC-IST},
        year={2022},
        month={1},
        keywords={diabetes muscles emg features},
        doi={10.4108/eai.7-9-2021.2315286}
    }
    
  • Mahmoud I. Al-Kadi
    Year: 2022
    Investigation of the Effect of Diabetes on Lower Limb Muscles with Surface Electromyography (EMG)
    IMDC-IST
    EAI
    DOI: 10.4108/eai.7-9-2021.2315286
Mahmoud I. Al-Kadi1,*
  • 1: Biomedical Engineering Department, Al-Khawarizmi College of Engineering, University of Baghdad
*Contact email: mahmoudalkadi67@kecbu.uobaghdad.edu.iq

Abstract

The ELECTROMYOGRAM (EMG) is a signal that indicates the muscle power and strength, It varies according to its type, location, and size of the muscle and other effectors, and in this project, it shows the muscle also affected by diseases like diabetes. The signals recorded were about 20 signals of cases (10 signals for normal cases and 10 signals for diabetes patients) after choosing three muscles in the lower limb (vastus lateralis (VL), TIBIALIS ANTERIOR (TA), and GASTROCNEMIUS medialis (GM)), each case apply three tests (standing, walking and stand over one foot) to know when the muscle affected greatly in which test and when the fatigue occurs. These signals were filtered carefully to eliminate the interface of other signals using three different stages according to the EMG frequencies (0.1 - 450) Hz. Three kinds of features were extracted (mean, standard deviation, and Shannon entropy) from EMG signals. The results show the variance between control muscles and patient muscles in amplitude and power where this variance increases whenever the duration and severity of the diabetes are increased.