Stroke can lead to severe neurological damage, impairing patients’ motor function. Identifying the relationship between muscle activity and generated force is crucial for evaluating motor recovery progress. This study aims to investigate and establish the relationship between surface electromyography (sEMG) signals of the flexor digitorum superficialis (FDS) muscle and handgrip force to assist in hand rehabilitation for stroke patients. Experimental data consisted of EMG signals recorded from the FDS muscle at three different handgrip force levels in a group of 10 individuals aged 19 to 22 years. The study employed a method of comparing the ratio of sEMG signals to the corresponding handgrip forces. Subsequently, interpolation was used to construct a relationship function. The results demonstrated a proportional and linear relationship between sEMG signals and handgrip force, providing supportive evidence for applying this model in hand rehabilitation devices and assessing patient recovery degrees.

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Evaluating Surface Electromyography Signal of Flexor Digitorum Superficialis Muscle

  • Trung T. Nguyen,
  • Hieu T. H. Le,
  • Khanh V. T. Dao,
  • Duc T. Luu,
  • Tam N. Bui

摘要

Stroke can lead to severe neurological damage, impairing patients’ motor function. Identifying the relationship between muscle activity and generated force is crucial for evaluating motor recovery progress. This study aims to investigate and establish the relationship between surface electromyography (sEMG) signals of the flexor digitorum superficialis (FDS) muscle and handgrip force to assist in hand rehabilitation for stroke patients. Experimental data consisted of EMG signals recorded from the FDS muscle at three different handgrip force levels in a group of 10 individuals aged 19 to 22 years. The study employed a method of comparing the ratio of sEMG signals to the corresponding handgrip forces. Subsequently, interpolation was used to construct a relationship function. The results demonstrated a proportional and linear relationship between sEMG signals and handgrip force, providing supportive evidence for applying this model in hand rehabilitation devices and assessing patient recovery degrees.