Quantifying the Peak Amplitude Distributions of Electromyogram in Bicep Brachii muscle after Stroke

التفاصيل البيبلوغرافية
العنوان: Quantifying the Peak Amplitude Distributions of Electromyogram in Bicep Brachii muscle after Stroke
المؤلفون: Andrew Lai, Taimoor Afzal, Nina L. Suresh, William Z. Rymer, Xiaogang Hu
المصدر: EMBC
بيانات النشر: IEEE, 2020.
سنة النشر: 2020
مصطلحات موضوعية: medicine.medical_specialty, Bicep brachii, 0206 medical engineering, Elbow, 02 engineering and technology, Isometric exercise, Biceps, 03 medical and health sciences, 0302 clinical medicine, Voluntary contraction, Physical medicine and rehabilitation, Elbow Joint, Humans, Medicine, Muscle, Skeletal, Chronic stroke, Stroke, Electromyography, business.industry, musculoskeletal system, medicine.disease, 020601 biomedical engineering, body regions, Amplitude, medicine.anatomical_structure, Arm, business, 030217 neurology & neurosurgery
الوصف: The objective of this study was to quantify the differences in surface electromyogram (EMG) signal characteristics between affected and contralateral arm muscles of hemispheric stroke survivors. EMG signals were recorded from the biceps brachii muscles using single differential electrodes. Four chronic stroke subjects performed isometric elbow flexions at sub-maximal voluntary contraction levels on both the affected and contralateral limbs. The force generated on the contralateral side was matched to the force generated on the affected side. We observed different types of EMG activation on the affected side compared to the contralateral side.Specifically, two subjects showed lower RMS EMG activity on the affected side whereas two subjects showed greater EMG activity on the affected side compared to the contralateral side. Analysis of the peak amplitudes of the EMG activity showed greater number of peaks in the EMG on affected side compared to the contralateral side in all subjects. The histogram of the peak amplitudes showed greater number of smaller peak amplitudes in subjects with lower EMG activity on the affected side suggesting a reliance on smaller motor units. Our combined EMG signal analysis techniques on one set of recorded signals provides insight regarding potential mechanisms of weakness.Clinical Relevance- Decoding neural information from surface EMG signals without decomposition into individual motor units could provide clinicians with quick insight about disease progress and potential treatment.
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3606c387391b6f5324efedd9b2d3814Test
https://doi.org/10.1109/embc44109.2020.9175253Test
حقوق: CLOSED
رقم الانضمام: edsair.doi.dedup.....d3606c387391b6f5324efedd9b2d3814
قاعدة البيانات: OpenAIRE