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

Journal: Journal of Clinical Medicine Research DOI: 10.32629/jcmr.v6i4.4809

Zhengyi Yang¹, Chuantao Li², Yongjie Yao²

1. School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
2. Naval Military Medical University, Shanghai 200082, China

Abstract

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.

Keywords

G-LOC; electromyographic features; anti-G physiology; G-LOC warning

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References

[1] Chang, W., Peng, Z., Li, C., et al. (2022). Research progress on physiological early warning indicators and alarm technology for high overload incapacitation. Academic Journal of Second Military Medical University, 43(2), 194-200. https://doi.org/10.16781/j.CN31-2187/R.20211025
[2] Yao, Y., Wu, X., & Sun, X. (1999). Mechanism and monitoring of loss of consciousness induced by sustained positive acceleration. Space Medicine & Medical Engineering, 12(5), 386-390. https://doi.org/10.3969/j.issn.1002-0837.1999.05.017
[3] Slungaard, E., McLeod, J., Green, N. D. C., et al. (2017). Incidence of G-induced loss of consciousness and almost loss of consciousness in the Royal Air Force. Aerospace Medicine and Human Performance, 88(6), 550-555. https://doi.org/10.3357/AMHP.4752.2017
[4] Cao, X. S., Wang, Y. C., Xu, L., et al. (2012). Visual symptoms and G-induced loss of consciousness in 594 Chinese Air Force aircrew—A questionnaire survey. Military Medicine, 177(2), 194-198. https://doi.org/10.7205/milmed-d-11-00003
[5] Li, Y., Zhang, T., Deng, L., et al. (2013). Review of EEG changes under high gravitational acceleration and its simulation conditions. Beijing Biomedical Engineering, 32, 647-654. https://doi.org/10.3969/j.issn.1002-3208.2013.06.18
[6] Wu, B., Xue, Y., You, G., et al. (2011). Study on prodromal reaction characteristics and warning methods of acceleration-induced loss of consciousness. Medical Journal of Air Force, 27, 28-32. https://doi.org/10.3969/j.issn.2095-3402.2011.01.009
[7] Mo, L., Wang, H., He, B., et al. (2018). Design and validation of ear pulse sensor for manned centrifuge training. Space Medicine & Medical Engineering, 31, 618-622.
[8] FLORENCE G, BONNIER R, RIONDET L, et al. Cerebral cortical blood flow during loss of consciousness induced by gravitational stress in rhesus monkeys[J]. Neurosci Lett, 2001, 305: 99-102. DOI:10.1016/s0304-3940(01)01818-3
[9] Cao, Z., Jin, C., Wang, C., et al. (2025). Research on acceleration-induced loss of consciousness warning model based on cerebral oxygen saturation. Journal of Air Force Medical University, 46(1), 57-62. https://doi.org/10.13276/j.issn.2097-1656.2025.01.010
[10] SPENCER G S, SMITH R. Exploring the origins of EEG motion artefacts during simultaneous fMRI acquisition: implications for motion artefact correction[J]. NeuroImage, 2018, 173: 188-198. DOI: 10.1016/j.neuroimage.2018.02.034.
[11] ZAWADZKA-BARTCZAK E K, KOPKA L H. Cardiac arrhythmias during aerobatic flight and its simulation on a centrifuge[J]. Aviat Space Environ Med, 2011, 82(6): 599-603. DOI: 10.3357/ASEM.2971.2011.
[12] ROMERO J, FERLINI A, SPATHIS D, et al. OptiBreathe: an earable-based PPG system for continuous respiration rate, breathing phase, and tidal volume monitoring[C]//Proc 25th Int Workshop on Mobile Computing Systems and Applications. ACM, 2024: 99-106. DOI: 10.1145/3638550.3639567.
[13] WANG F, JIN P, FENG Y, et al. Flexible Doppler ultrasound device for the monitoring of blood flow velocity[J]. Sci Adv, 2021, 7(44): eabi9283. DOI: 10.1126/sciadv.abi9283.
[14] LIAN C, LI P, WANG N, et al. Comparison of basic regional cerebral oxygen saturation values in patients of different ages: a pilot study[J]. J Int Med Res, 2020, 48(8): 0300060520936800. DOI: 10.1177/0300060520936800.
[15] CHOI B, KIM D, KIM M, et al. Effectiveness of EMG in development of G-induced loss of consciousness (G-LOC) warning system[C]//Proc Int Conf Biomed Eng Syst. Avestia, 2014: 1-4.
[16] Farina D, Merletti R, Enoka R M. The extraction of neural strategies from the surface EMG. Journal of Applied Phys-iology, 2004, 96(4): 1486−1495.
[17] Chu J U, Moon I, Lee Y J, Kim S K, Mun M S. A supervised feature-projection-based real-time EMG pattern recognition for multifunction myoelectric hand control. IEEE/ASME Transactions on Mechatronics, 2007, 12(3): 282−290
[18] Cornwall, M. W., & Krock, L. P. (1992). Electromyographic activity while performing the anti-G straining maneuver during high sustained acceleration. Aviation, space, and environmental medicine, 63(11), 971–975.
[19] KIM S, KIM D, CHO Y, et al. Analysis on electromyogram (EMG) signals by body parts for G-induced loss of consciousness (G-LOC) prediction[J]. J Korea Inst Mil Sci Technol, 2017, 20(1): 119-128. DOI: https: //doi.org/10.9766/KIMST.2017.20.1.119
[20] Li, Y., Yang, J., Li, B., et al. (2024). Effectiveness of EMG changes under centrifuge G-load for G-LOC early warning. Medical Equipment, 45(12), 25-31. https://doi.org/10.19745/j.1003-8868.20242431
[21] CHOI B, LEE Y. CHO T. et al. Detection of G-Induced Loss of Consciousness (G-LOC) prognosis through EMG monitoring on gastrocnemius muscle in flight[C]//2015 37th Annual In- ternational Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), August 25-29, 2015, Milan. New York: IEEE，2015: 7 007-7 010.
[22] Kim, S., Cho, T., Lee, Y., Koo, H., Choi, B., & Kim, D. (2017). G-LOC Warning Algorithms Based on EMG Features of the Gastrocnemius Muscle. Aerospace medicine and human performance, 88(8), 737–742. https://doi.org/10.3357/AMHP.4781.2017.
[23] Wu, C., & Yao, Y. (2024). Loss of consciousness monitoring and wake-up system based on head posture and EMG signals. Academic Journal of Naval Medical University, 45(11), 1425-1433. https://doi.org/10.16781/j.CN31-2187/R.20230305.

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