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Online optimization of EMG using a hybrid model approach

Aalten, Thijs van (2021) Online optimization of EMG using a hybrid model approach.

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Abstract:Two state of the art methods for neuromusculoskeletal (NMS) modeling are inverse dynamics (ID) based modeling and electromyography (EMG) driven modeling. These methods can be combined into a hybrid model to benefit from the strengths of both methods. A real-time hybrid NMS model was developed that enables real-time measurement of ankle joint's EMG signals that account for realistic joint torques. Simulated annealing is used to optimize for excitations that resemble measured EMG and produce joint torque close to joint torque measured by ID. Human kinematic data, ground reaction force and EMG were measured and used to test the model's ability to calculate optimized excitations in real-time. It is shown that real-time calculated optimized excitations show large correlation with EMG signals that were optimized in an offline environment. Joint torques resulting from optimized excitations show large correlation with ID joint torques. This real-time hybrid NMS model can potentially be used in a clinical environment to obtain online measurements of neuromuscular data and can be used to drive a wearable robotic device.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:42 biology, 52 mechanical engineering, 54 computer science
Programme:Mechanical Engineering MSc (60439)
Link to this item:http://purl.utwente.nl/essays/85526
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