基于表面肌电图的股直肌急性抗阻疲劳动态评估
樊佳慧

南京体育学院 运动健康学院，江苏南京，210014；

摘要：目的：应用表面肌电图（Surface Electromyography，sEMG）评估股直肌在急性抗阻疲劳状态下的神经肌肉功能,以期探索sEMG评估股直肌急性疲劳的价值，为优化运动性疲劳监测方案提供实证依据。方法：本研究采用重复测量实验设计。共纳入35例健康青年受试者（年龄：21.31±2.17岁），以80%1RM（One Repetition Maximum，一次重复最大值）负荷执行单腿伸膝抗阻至力竭训练。实验方案包含3组训练，组间休息3分钟，以无法维持50次/分钟的运动节奏或伸膝角度<45°作为每组力竭标准。分别在基线状态及每组抗阻训练（Resistance Exercise，RE）采集股直肌神经电活动sEMG平均功率频率（Mean Power Frequency，MPF）和中位频率（Median Frequency，MDF）。结果：MPF与MDF时间效应显著（P＜0.001）且在RE1阶段显著下降（P＜0.05）；RE3时两指标较基线均显著降低（均P＜0.001）；ΔMPF（RE3-基线）与ΔMDF呈极强正相关（r=0.950）。结论：MPF与MDF的早期陡降可作为外周疲劳实时预警指标，而后续动态平衡特征提示抗阻训练中疲劳发展存在阶段性适应机制。频域参数间的高度协同性为简化疲劳检测方案提供了理论依据。

关键词：股直肌疲劳；表面肌电图；抗阻训练

参考文献

[1]ALBA-JIMÉNEZ C, MORENO-DOUTRES D, PEÑA J. Trends Assessing Neuromuscular Fatigue in Team Sports: A Narrative Review[J]. Sports (Basel, Switzerland), 2022, 10(3): 33.

[2]CONSTANTIN-TEODOSIU D, CONSTANTIN D. Molecular Mechanisms of Muscle Fatigue[J]. International Journal of Molecular Sciences, 2021, 22(21): 11587.

[3]BOKSEM M A S,MEIJMAN T F,LORIST M M. Mental fatigue, motivation and action monitoring[J].Biological Psychology, 2006, 72(2): 123-132.

[4]HUDGINS B, PARKER P, SCOTT R N. A new strategy for multifunction myoelectric control[J]. IEEE transactions on bio-medical engineering, 1993, 40(1): 82-94.

[5]ERTL P, KRUSE A, TILP M. Detecting fatigue thresholds from electromyographic signals: A systematic review on approaches and methodologies[J]. Journal of Electromyography and Kinesiology: Official Journal of the International Society of Electrophysiological Kinesiology, 2016, 30: 216-230.

[6]DUFAUG A, BARTHOD C, GOUJON L, et al. New joint analysis of electromyography spectrum and amplitude-based methods towards real-time muscular fatigue evaluation during a simulated surgical procedure: A pilot analysis on the statistical significance[J]. Medical Engineering & Physics, 2020, 79: 1-9.

[7]ENDRIX C R, HOUSH T J, CAMIC C L, et al. Comparing electromyographic and mechanomyographic frequency-based fatigue thresholds to critical torque during isometric forearm flexion[J]. Journal of Neuroscience Methods, 2010, 194(1): 64-72.

[8]KHANAM F, AHMAD M. Frequency Based EMG Power Spectrum Analysis of Salat Associated Muscle Contraction[C]. 2015.

[9]DE LUCA C J. Myoelectrical manifestations of localized muscular fatigue in humans[J]. Critical Reviews in Biomedical Engineering, 1984, 11(4): 251-279.

[10]王健, 刘加海. 肌肉疲劳的表面肌电信号特征研究与展望[J]. 中国体育科技, 2003(2): 5-8.

[11]MOHSENI BANDPEI M A, RAHMANI N, MAJDOLESLAM B, et al. Reliability of surface electromyography in the assessment of paraspinal muscle fatigue: an updated systematic review[J]. Journal of Manipulative and Physiological Therapeutics, 2014, 37(7): 510-521.

[12]FARINA D. Interpretation of the surface electromyogram in dynamic contractions[J]. Exercise and Sport Sciences Reviews, 2006, 34(3): 121-127.

[13]TANIGUCHI M, YAMADA Y, ICHIHASHI N. Acute effect of multiple sets of fatiguing resistance exercise on muscle thickness, echo intensity, and extracellular-to-intracellular water ratio[J]. Applied Physiology, Nutrition, and Metabolism, 2020, 45(2): 213-219.

[14]BARCELOS L C, NUNES P R P,DE SOUZA L R M F,et al. Low-load resistance training promotes muscular adaptation regardless of vascular occlusion, load, or volume[J]. European Journal of Applied Physiology,2015,115(7): 1559-1568.

[15]SMALE K B, SHOURIJEH M S, BENOIT D L. Use of muscle synergies and wavelet transforms to identify fatigue during squatting[J]. Journal of Electromyography and Kinesiology, 2016, 28: 158-166.

[16]HERMENS H J, FRERIKS B, DISSELHORST-KLUG C, et al. Development of recommendations for SEMG sensors and sensor placement procedures[J]. Journal of Electromyography and Kinesiology: Official Journal of the International Society of Electrophysiological Kinesiology, 2000, 10(5): 361-374.

[17]吴冬梅,孙欣,张志成,等.表面肌电信号的分析和特征提取-期刊-万方数据知识服务平台[J].中国组织工程研究与临床康复,2010,14(43):8073-8076.

[18]卢蕾,殷涛,靳静娜,等.采集表面肌电信号应用于动作识别的可行性-期刊-万方数据知识服务平台[J].中国组织工程研究与临床康复,2011,15(22):4103-4106.

[19]ÖZGÖREN N, ARITAN S. Peak counting in surface electromyography signals for quantification of muscle fatigue during dynamic contractions[J]. Medical Engineering & Physics, 2022, 107: 103844.

[20]DANTAS J L, CAMATA T V, BRUNETTO M A C, et al. Fourier and wavelet spectral analysis of EMG signals in isometric and dynamic maximal effort exercise[J]. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2010, 2010: 5979-5982.

[21]AZMI N L, GHAFAR N A A, NOR K A M, et al. Classification of Muscle Fatigue during Prolonged Driving[J]. ELEKTRIKA- Journal of Electrical Engineering, 2022, 21(3): 40-46.

[22]GANDEVIA S C. Spinal and supraspinal factors in human muscle fatigue[J]. Physiological Reviews, 2001, 81(4): 1725-1789.

[23]DECORTE N, LAFAIX P A, MILLET G Y, et al. Central and peripheral fatigue kinetics during exhaustive constant-load cycling[J]. Scandinavian Journal of Medicine & Science in Sports, 2012, 22(3): 381-391.

[24]PHINYOMARK A, THONGPANJA S, HU H, et al. The Usefulness of Mean and Median Frequencies in Electromyography Analysis[M]//Computational Intelligence in Electromyography Analysis - A Perspective on Current Applications and Future Challenges. 2012: 195-220.

[25]DANIEL N, MAŁACHOWSKI J, SYBILSKI K, et al. Quantitative assessment of muscle fatigue during rowing ergometer exercise using wavelet analysis of surface electromyography (sEMG)[J]. Frontiers in Bioengineering and Biotechnology, 2024, 12: 1344239.