Research Progress on Surface Electromyography in Monitoring G-Induced Loss of Consciousness

G-induced Loss of Consciousness (G-LOC) caused by high overload is a primary cause of flight accidents. Although existing anti-G measures are effective, the risk has not been entirely eliminated. Traditional monitoring indicators (such as EEG, ECG, and cerebral oxygen saturation) face limitations in actual flight environments, including signal lag, susceptibility to interference, or high equipment costs. Surface electromyography (sEMG), as a non-invasive, highly sensitive, and real-time physiological indicator, provides a new technical pathway for the early warning of G-LOC. Research confirms that during the critical window approximately 3 seconds prior to the occurrence of G-LOC, the electromyographic features (such as RMS and WL) of anti-G muscle groups exhibit significant attenuation, reflecting a loss of neuromuscular control capabilities. Compared to the neck and abdomen, the gastrocnemius muscle of the lower leg has been established as the optimal monitoring site due to signal stability. Based on this regularity, researchers have developed G-LOC electromyographic recognition algorithms and constructed real-time warning and wake-up systems integrating head posture monitoring, verifying their engineering feasibility. This paper aims to systematically review the technical principles, feature evolution laws, algorithm progress, and system applications of sEMG in G-LOC monitoring.