Single-input single-output EMG-based musculoskeletal modeling for hand tremulous motion

Musculoskeletal system modeling is one of the most challenging problems in rehabilitation engineering, especially when body part position or motion control is involved. Musculoskeletal system is known to be highly nonlinear due to complicated actuation mechanism of the muscle fiber to generate observable / measurable motion. Numerous researchers have proposed models with different approaches to meet the requirements for various applications. Complicated models are usually corresponding to complicated model parameters identification methods or procedures. A simple procedure for identification of the model parameters is preferred in most of modeling related to control problems. In this paper, we propose a simplification of the EMG-based musculoskeletal model for hand tremulous motion to a single-input single-output (SISO) model. A signal processing sequence to preprocess the EMG signal was performed using normalization, rectification, filtering and subtraction to merge the two signals captured from agonist-antagonist muscle groups responsible for the tremulous motion. The proposed SISO model was validated in a simulation using data captured from healthy subject performing 1 degree of freedom (DOF) flexion-extension tremor-like motion with predetermined frequency. Results show that the SISO model is fit for simulating 1 DOF tremulous motion in the hand. Another important result that can be drawn from this work is the reduction in the electromechanical delay (EMD) with increase of motion frequency.