-
摘要: 長期頸部前屈對頸椎造成嚴重影響。為定量評估長時間低頭對頸椎疲勞造成的影響，選取20名健康受試者，保持低頭角度40°～60°持續3 h。選擇胸鎖乳突肌，頸部夾肌和肩部斜方肌測量其表面肌電信號。經濾波、整流、振幅標準化等處理后，對每60 s的肌電值進行積分和求其平均功率頻率。研究發現，積分肌電值的波動變化具有規律性，首次增大后的減小表征肌肉進入疲勞狀態；不同肌肉的平均功率頻率(mean power frequency，MPF)值具有明顯差異，決定著該肌肉疲勞耐受性的持續時間，且在整個頸部前屈過程中MPF并非簡單的線性關系。提出用MPF的導數來提取疲勞特征，用窗口化的MPF負數累積判定肌肉疲勞。結果表明，MPF負數累積能很好地判斷肌肉疲勞，胸鎖乳突肌在20 min內出現最終疲勞，而頸部夾肌和肩部斜方肌在20 min左右出現了短暫性疲勞，隨后在75～100 min時又出現了最終疲勞。因此建議持續頸部前屈時長不超過20 min。Abstract: Long-term neck flexion posture is a common awkward posture resulting from long-term head-down work, long-term looking at a computer screen, and long-term playing with a mobile phone. Fatigue and chronic injury of cervical muscles are easily caused by long-term bowing of the head. Long-term bowing of the head to play with a mobile phone causes injury to the cervical spine. Long-term neck muscle contraction is an important cause of fatigue and chronic injury of the neck muscles and tissues. Therefore, it is of significance to analyze the changes of muscle activity during long-term neck muscle contraction and to determine the time threshold of neck muscle fatigue to reduce the damage caused by neck muscle fatigue. To quantitatively evaluate the effect of long-term head-down playing with a mobile phone on cervical spine fatigue, 20 healthy subjects were selected and kept the head-down angle between 40° and 60° for 3 h. On the basis of the analysis of cervical spine muscle architecture and anthropometry, the surface electromyography (sEMG) of the sternocleidomastoid, cervical gripper, and shoulder trapezius muscles was recorded. The original sEMG data were processed by filtering, rectifying, and amplitude standardization. The EMG values every 60 s were integrated, and their mean power frequency (MPF) was calculated. Results show that the fluctuation of the integral EMG is regular and the decrease after the initial increase indicates that the muscle is in the fatigue state. The MPF values of different muscles have obvious differences, which determine the duration of fatigue tolerance of the muscle. Moreover, the MPF does not exhibit a simple linear relationship during the entire bowing process. The results also show that negative MPF accumulation can be used to assess neck muscle fatigue. The sternocleidomastoid muscle is in the fatigue state in 20 min, whereas the cervical gripper and shoulder trapezius muscles are temporarily fatigued in approximately 20 min and in the final fatigue state in 75–100 min. Therefore, it is suggested that the duration of continuous bowing should not exceed 20 min.
-
圖 5 不同肌肉肌電積分值. (a) 1號受試者胸鎖乳突肌；(b) 1號受試者頸部夾肌；(c) 1號受試者斜方肌；(d) 2號受試者胸鎖乳突肌肌；(e) 2號受試者頸部夾肌；(f) 2號受試者頸部夾肌；(g) 3號受試者胸鎖乳突肌；(h) 3號受試者頸部夾肌；(i) 3號受試者斜方肌；(j) 4號受試者胸鎖乳突肌；(k) 4號受試者頸部夾肌；(l) 4號受試者斜方肌
Figure 5. iEMG of different muscles: (a) sternocleidomastoid muscle of subject 1; (b) cervical clamp muscle of subject 1; (c) trapezius muscle of subject 1; (d) sternocleidomastoid muscle of subject 2; (e) cervical clamp muscle of subject 2; (f) cervical clamp muscle of subject 2; (g) sternocleidomastoid muscle of subject 3; (h) cervical clamp muscle of subject 3; (i) trapezius muscle of subject 3; (j) sternocleidomastoid muscle of subject 4; (k) cervical clamp muscle of subject 4; (l) trapezius muscle of subject 4
中文字幕在线观看表 1 iEMG變化時間統計
Table 1. iEMG change time
肌肉部位 iEMG首次明顯增大時刻/min t檢驗 iEMG再次明顯增大時刻/min t檢驗 胸鎖乳突肌 16±4 P<0.05 62±8 P<0.05 頸部夾肌 15±5 P<0.05 82±10 P<0.05 斜方肌 17±4 P<0.05 72±8 P<0.05 
下載: 導出CSV
-
參考文獻
[1] He J B. Analysis of the Correlation of Neck Pain with Cervical Curvature and Tendon Injury in Juveniles[Dissertation]. Guangzhou: Guangzhou University of Chinese Medicine, 2017何劍波. 青少年頸痛與筋傷、頸椎曲度的相關性研究[學位論文]. 廣州: 廣州中醫藥大學, 2017 [2] Zhao Y. The prevalence of cervical spondylosis in young Chinese is higher than that in middle-aged people[J/OL]. People's Political Consultative Conference Network (2016−01−14)[2019−06−13]. http://www.rmzxb.com.cn/c/2016-01-14/672352.shtml趙彥. 中國年輕人頸椎患病率已超中年人[J/OL]. 人民政協網(2016-01−14)[2019−06−13]. http://www.rmzxb.com.cn/c/2016−01−14/672352.shtml [3] Bai J B, Yu K L, Sun Y N, et al. Prevalence of and risk factors for Modic change in patients with symptomatic cervical spondylosis: an observational study. J Pain Res, 2018, 11: 355 doi: 10.2147/JPR.S151795 [4] Ko P H, Hwang Y H, Liang H W. Influence of smartphone use styles on typing performance and biomechanical exposure. Ergonomics, 2016, 59(6): 821 doi: 10.1080/00140139.2015.1088075 [5] Lee H, Nicholson L L, Adams R D. Neck muscle endurance, self-report, and range of motion data from subjects with treated and untreated neck pain. J Manipulative Physiol Ther, 2005, 28(1): 25 doi: 10.1016/j.jmpt.2004.12.005 [6] Moreno A J, Utrilla G, Marin J, et al. Cervical spine assessment using passive and active mobilization recorded through an optical motion capture. J Chiropractic Med, 2018, 17(3): 167 doi: 10.1016/j.jcm.2017.12.004 [7] Burhan N, Kasno M A, Ghazali R. Feature extraction of surface electromyography (sEMG) and signal processing technique in wavelet transform: A review //2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS). Shah Alam, 2016: 141 [8] Sasaki M, Onishi K, Stefanov D, et al. Tongue interface based on surface EMG signals of suprahyoid muscles. ROBOMECH J, 2016, 3(1): 9 doi: 10.1186/s40648-016-0048-0 [9] Neblett R. Surface electromyographic (SEMG) biofeedback for chronic low back pain. Healthcare, 2016, 4(2): 27 doi: 10.3390/healthcare4020027 [10] Du Y X Wang S Y, Ndaro N Z, et al. Comparative study on evaluation algorithms for neck muscle fatigue based on surface electromyography signal. J Biomed Eng, 2018, 35(1): 31杜云霄, 王殊軼, Ndaro N Z, 等. 基于表面肌電信號的頸部肌肉疲勞評價算法比較研究. 生物醫學工程學雜志, 2018, 35(1):31 [11] Strimpakos N. The assessment of the cervical spine. Part 1: Range of motion and proprioception. J Bodywork Movement Therapies, 2011, 15(1): 114 doi: 10.1016/j.jbmt.2009.06.003 [12] Wang L, Luo X, Jiang X, et al. Detection on driver fatigue based on biomechanics and EMG of cervical and lumbar muscles. Automot Eng, 2017, 39(8): 955王琳, 羅旭, 姜鑫, 等. 基于生物力學和頸腰部EMG判別駕駛員疲勞狀態. 汽車工程, 2017, 39(8):955 [13] Ren Z, Yang W Q. A miniature two-plate electrical capacitance tomography sensor. IEEE Sensors J, 2015, 15(5): 3037 doi: 10.1109/JSEN.2014.2383491 [14] Al-Alangari H M, Kanitz G, Tarantino S, et al. Distance and mutual information methods for EMG feature and channel subset selection for classification of hand movements. Biomed Signal Process Control, 2016, 27: 24 doi: 10.1016/j.bspc.2016.01.011 [15] Eveleth P B, Andres R, Chumlea W C, et al. Uses and interpretation of anthropometry in the elderly for the assessment of physical status. Report to the Nutrition Unit of the World Health Organization: the Expert Subcommittee on the Use and Interpretation of Anthropometry in the Elderly. J Nutrition Health Aging, 1998, 2(1): 5 [16] Portero R, Quaine F, Cahouet V, et al. Musculo-tendinous stiffness of head-neck segment in the sagittal plane: An optimization approach for modeling the cervical spine as a single-joint system. J Biomechanics, 2013, 46(5): 925 doi: 10.1016/j.jbiomech.2012.12.009 [17] Skinner M A, Kingshott R N, Jones D R, et al. Lack of efficacy for a cervicomandibular support collar in the management of obstructive sleep apnea. Chest, 2004, 125(1): 118 doi: 10.1378/chest.125.1.118 [18] Oi N, Pandy M G, Myers B S, et al. Variation of neck muscle strength along the human cervical spine. Stapp Car Crash J, 2004, 48: 389 [19] Suderman B L, Vasavada A N. Moving muscle points provide accurate curved muscle paths in a model of the cervical spine. J Biomechanics, 2012, 45(2): 400 doi: 10.1016/j.jbiomech.2011.10.014 [20] Artz N J, Adams M A, Dolan P. Sensorimotor function of the cervical spine in healthy volunteers. Clin Biomechanics, 2015, 30(3): 260 doi: 10.1016/j.clinbiomech.2015.01.005 [21] Nimbarte A D, Zreiqat M, Ning X P. Impact of shoulder position and fatigue on the flexion-relaxation response in cervical spine. Clin Biomechanics, 2014, 29(3): 277 doi: 10.1016/j.clinbiomech.2013.12.003 [22] Merletti R, Farina D. Detection and Conditioning of Surface EMG Signals. Hoboken: Wiley-IEEE Press, 2016 [23] Vesa E P, Ilie B. Equipment for SEMG signals acquisition and processing // International Conference on Advancements of Medicine and Health Care through Technology. Cluj-Napoca, 2014: 187 [24] Slim Y, Raoof K. Removal of ECG interference from surface respiratory electromyography. IRBM, 2010, 31(4): 209 doi: 10.1016/j.irbm.2010.05.002 [25] Chowdhury R H, Reaz M B I, Ali M A B M, et al. Surface electromyography signal processing and classification techniques. Sensors, 2013, 13(9): 12431 doi: 10.3390/s130912431 [26] Merletti R, Farina D. Surface EMG processing: Introduction to the special issue. Biomed Signal Process Control, 2008, 3(2): 115 doi: 10.1016/j.bspc.2008.01.001 [27] Dumitru D, King J C, Nandedkar S D. Comparison of single-fiber and macro electrode recordings: relationship to motor unit action potential duration. Muscle Nerve, 1997, 20(11): 1381 doi: 10.1002/(SICI)1097-4598(199711)20:11<1381::AID-MUS5>3.0.CO;2-6 [28] Min L, Sarkar N, Guang M, et al. Can surface EMG be adequately described by digital sampling? Nonlinear Dyn Psychology Life Sci, 2014, 18(3): 229 [29] Wang L L, Yang Z, Liu Y B, et al. Study on muscle fatigue characteristics of males at different ages based on sEMG signal. Chin J Rehabil Med, 2019, 34(2): 204 doi: 10.3969/j.issn.1001-1242.2019.02.016王立玲, 楊錚, 劉元博, 等. 基于sEMG信號的不同年齡下男性肌肉疲勞特性研究. 中國康復醫學雜志, 2019, 34(2):204 doi: 10.3969/j.issn.1001-1242.2019.02.016 [30] Wang L, Fu R R, Zhang C, et al. Biomechanics-based investigation on the relation between index Q and cervical muscle fatigue. Chin J Sci Instrum, 2017, 38(4): 878 doi: 10.3969/j.issn.0254-3087.2017.04.012王琳, 付榮榮, 張陳, 等. 基于生物力學分析Q值對頸肌疲勞的反映效果. 儀器儀表學報, 2017, 38(4):878 doi: 10.3969/j.issn.0254-3087.2017.04.012 [31] Guo Y L, Liu X P, Chen B H, et al. Types and distribution of cervical posterior deep muscle. Acta Acad Med Qingdao, 1999, 35(1): 13郭云良, 劉曉萍, 陳伯華, 等. 頸后深部肌肉纖維類型的分布. 青島醫學院學報, 1999, 35(1):13 [32] Huang Y Q. The Anatomical and Clinical Study on Myofascial pain of Sternocleidomastoid Muscle[Dissertation]. Guangzhou: First Military Medical University, 2005黃宇琦. 胸鎖乳突肌筋膜痛的解剖學及其臨床研究[學位論文]. 廣州: 第一軍醫大學, 2005 [33] Peng Y T, Huang H. Review on the effect of KAATUS training. Genomics Appl Biol, 2018, 37(12): 5676彭一騰, 黃驊. 加壓力量訓練的研究評述. 基因組學與應用生物學, 2018, 37(12):5676 -
點擊查看大圖
圖(8) / 表(1)
計量
- 文章訪問數: 1747
- HTML全文瀏覽量: 1138
- PDF下載量: 67
- 被引次數: 0
