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Subject Specific HD-EMG driven musculoskeletal modeling for stroke subjects

Choudhury, Krittika (2019) Subject Specific HD-EMG driven musculoskeletal modeling for stroke subjects.

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Abstract:Stroke induced disabilities of the upper extremity cause significant dysfunctions at the wrist, reducing an individual’s dexterity while performing activities of daily living. Limited research exists to study abnormal wrist movement patterns of stroke participants using neuromechanical modeling. Objective: Subject-specific musculoskeletal modeling of the wrist in stroke patients to help guide neuromechanical modeling strategies in the future. This study makes use of cumulative spike trains of extension and flexion generated from High Density EMG (HD-EMG) recordings of stroke patients which were decomposed using Convolution Kernel Compensation (CKC). Investigations were done to check if HD-EMG could drive the musculoskeletal modeling pipeline and if this previously tested modeling approach could work with neural and kinematic inputs from stroke patients. Methods: A subject-specific musculoskeletal model of 6 muscles and one degree of freedom, wrist flexion-extension was used in this study. The model was driven using decomposed HD-EMG recordings. Results: The subject-specific HD-EMG driven musculoskeletal model was validated for four stroke subjects on the basis of torque estimation and transformations estimated by the model, such as activations and muscle forces. Comparisons were done across all cycles for each trial of a participant, as well as across all trials of each participants. Conclusion: Results show that for stroke participants, the model estimated torques were well-correlated with the experimental torques in terms of shape and magnitude.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:50 technical science in general
Programme:Biomedical Engineering MSc (66226)
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