Research On The Biomechanical Model Of The Pathological Tremor Suppression Robotics

Pathological tremor is a disease and usually appears in upper limb, while thequality of life and mental health of patients are interfered. With the developedtechnology, the treatments of pathological tremor are also gradually improved. Inrecent years, exoskeleton adjuvant therapy is developed as a new treatment and hasbroad application prospects in the biomedical field. Functional electrical stimulationmethods will be employed for the next-generation tremor suppression robots. Dueto the requirement of simulation platform for tremor suppression, the biomechanicalmodel of upper limb was studied in this paper.Based on the theory of the Hill muscle model, the paper explores therelationship between the surface electromyography (sEMG) and the degree ofmuscle activation. A musculoskeletal system model of upper limb was ultimatelyestablished by the biomechanical simulation software-OpenSim and this model wasdriven by the degree of muscle activation.Muscle activity is an abstract concept used to characterize the degree of muscleactivity and the sEMG of muscles can also objectively reflect the level of muscleactivity, therefore the muscle activity is related with the sEMG. The Hill model ofmuscle was employed with neural network to convert the sEMG into the musclesactivity. Finally, the musculoskeletal model was active by the converted sEMG andthe model can also simulate the tremor movement of limb.The tremor movements are primarily analyzed in this article. The sEMG and theelbow joint kinematic signals of patients with pathological tremor are analyzed byusing the empirical mode decomposition method (EMD). The intentional movementsignals and tremor signals are separated and time-frequency analysis of signals arecompleted by the EMD. The indicators of time domain and frequency domain areproposed for discriminating the tremor from subjects’ normal activities and this isalso employed for the tremor suppression robot to evaluate the tremor.In the experiments, the musculoskeletal system is used to simulate the tremormovement. Using the simulation results, the frequency response characteristics ofthe model with muscle activity as the input and the factors impacting the frequencyresponse of limb are both analyzed. The relationship between EMG and joint torqueare identified based on the experimental data. Finally, the optimal distribution ofmuscle forces is completed by the static optimization algorithm.