Identification of electromyographic patterns of bradykinesia in patients with Parkinson's disease

Parkinson's disease (PD) is a common neurodegenerative disease characterized by rest tremor, rigidity, and bradykinesia. Assessing the severity of these symptoms is typically done using the third part of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS III), relying on subjective evaluations by neurologists, which may lead to challenges in result interpretation. To address this issue, incorporation of surface electromyography (sEMG) in diagnostics. The aim of the study is to search for specific sEMG patterns that allow assessing the severity of bradykinesia. This case-control study involved 8 patients with PD at Hoehn & Yahr stages 2–3, and 7 healthy volunteers. sEMG was measured while the subjects performed the "finger tapping" and "hand movements" tests of the MDS-UPDRS III. The tests were conducted both before and after levodopa intake to identify patterns indicating changes in motor functions. During the tests, we observed the peak activity of the sEMG signal, reflecting the moments of activation of individual muscle groups involved in the implementation of the movement. Peak activity was characterized by the total number of maximum sEMG signal extrema and the distance between them. The data were compared with the healthy group. Peak activity increased after levodopa intake, indicating a reduction in bradykinesia. This feature partially correlates with clinicians' assessments and enhances the similarity of predictions by the MDS-UPDRS III scoring model to physician scores. The results show the effectiveness of using sEMG and the number of peaks corresponding to the moments of muscle activation to assess bradykinesia. •To objectively identify bradykinesia, we developed a feature called “number of peaks”.•The number of peaks in sEMG signals indicates a change in velocity of hand movements.•The number of peaks after L-DOPA intake nears the indicators of the healthy group.•The model trained on the extended set demonstrated high reliability in predictions.•Results demonstrate the feasibility of using sEMG in the assessment of bradykinesia.