Muscle Electrical Impedance Analysis Based on Blind Source Separation

摘要

Electrical impedance myography (EIM) is a relatively new technique to evaluate neuromuscular diseases and muscle fatigue. However, EIM is a biomarker of muscle status, and its sensitivity is influenced by skin and fat. To restore the impedivity of the muscle layer from EIM data, we use the ICA and EASI algorithms to estimate the impedivity of each tissue layer and compare the performance of ICA and EASI methods. The results showed that the EASI algorithm can better restore the muscle impedivity with an accuracy rate of 0.999. This work provides a new idea for the treatment of muscle diseases and muscle fatigue recovery.