Application of the Neural Network in the Study of Skeletal Muscle with Multi-parameters

The mechanical properties of skeletal muscles are always related to its architectural changes. But at present, there are very few documents that report the comprehensive study on skeletal muscle with structure morphology, mechanics, electrophysiology and so on. This paper introduced that the muscle thickness and surface electromyography (SEMG) sampled from the extensor carpi radialis by the ultrasound measurement of motion and elasticity system were used to fit the wrist angle with several regression algorithms. The results illuminate that the wrist angle is well fitted by combining the SMG and SEMG signals together, especially with the neural network algorithm, and the results are better than the results fitted by SMG or SEMG alone. So it is better to use multi-parameters to study the skeletal muscle.