Local muscle fatigue (LMF) is a common physiological phenomenon that occurs in daily exercise training and medical rehabilitation. Without timely treatment it can easily lead to muscle spasm, ligament rupture, and even stress fractures. Electrical impedance myography (EIM) is a noninvasive bioelectrical impedance technique suitable for the wearable LMF monitoring anytime and anywhere. In this paper, a novel EIM electrode configuration was proposed by establishing a four-layer simulation model of the human upper arm in FEM software. Sensitivity parameters were introduced to optimize muscle selectivity. The effect of fat thickness on impedance change rate was explored to reduce the influence of individual fat differences on EIM results. Dynamic and static contraction experiments of muscle fatigue were performed on the biceps brachii muscles of 10 volunteers to verify the effectiveness and feasibility of the proposed electrode configuration. The proposed electrode configuration reduced the measurement area by 25%, whereas the impedance amplitude and sensitivity remained the same. The influence of individual fat differences on EIM results was significantly reduced. When the fat thickness increased from 6 mm to 18 mm, the impedance change decreased by 31.78% compared with the traditional electrode configuration. When the muscles were extremely exhausted, the decrease in resistance varied around 10 Ω and within 10-1 order of magnitude in different volunteers. In a word, the proposed electrode configuration effectively evaluated the degree of LMF, providing more feasibility for the design of wearable devices. INDEX TERMS Electrical impedance myography, local muscle fatigue, optimized electrode configurations, finite element method, the biceps brachii muscles.
Intrabody communication (IBC) can achieve better power efficiency and higher levels of security than other traditional wireless communication technologies. Currently, the majority of research on the body channel characteristics of galvanic coupling IBC are motionless and have only been evaluated in the frequency domain. Given the long measuring times of traditional methods, the access to dynamic variations and the simultaneous evaluation of the time-frequency domain remains a challenge for dynamic body channels such as the cardiac channel. To address this challenge, we proposed a parallel measurement methodology with a multi-tone strategy and a time-parameter processing approach to obtain a time-frequency evaluation for dynamic body channels. A group search algorithm has been performed to optimize the crest factor of multitone excitation in the time domain. To validate the proposed methods, in vivo experiments, with both dynamic and motionless conditions were measured using the traditional method and the proposed method. The results indicate that the proposed method is more time efficient (Tmeas=1 ms) with a consistent performance (ρc > 98%). Most importantly, it is capable of capturing dynamic variations in the body channel and provides a more comprehensive evaluation and richer information for the study of IBC.
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