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Real-time muscle fatigue monitoring based on median frequency of electromyography signal
Ma’As M.D.F.a, Masitoha, Azmi A.Z.U.a, Suprijantoa
a InstitutTeknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2017 IEEE.Muscle fatigue is one of the important parameters that must be known during physiotherapy. Undetected muscle fatigue for a long time can cause injury to the subject. This paper presents method and algorithm to determine fatigue of muscle during doing some exercise which can be used for real-time monitoring post-stroke rehabilitation patient by using Electromyography (EMG). In general, EMG signal is commonly used for recording muscle activity. Extracted features are purposed to minimize the loss of useful information embedded in the signal with noise. EMG signal has better performance in frequency domain than in time domain. Median Frequency (MDF) is one of the standard parameter to indicate fatigue. Using the proposed method and algorithm, some experimental test show shows that MDF decreases 1 to 3 Hz and the slope of MDF sticks to certain value below zero.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Electromyography signals,Experimental test,Frequency domains,Median frequency,Muscle activities,Muscle fatigues,Post-stroke rehabilitation,Real time monitoring[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Electromyography,Fatigue,Median Frequency,Realtime Monitoring[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]ACKNOWLEDGMENT This work was supported by Medical Laboratory at Institut Teknologi Bandung.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICA.2017.8068428[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]