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作 者:徐红旗[1] 史冀鹏[1] 张欣[2] 冉令华[2] 杨帆[2] 王安利[3] 郑秀瑗[4]
机构地区:[1]东北师范大学体育学院,吉林长春130024 [2]中国标准化研究院,北京100088 [3]北京体育大学运动康复系,北京100084 [4]清华大学体育部,北京100084
出 处:《体育科学》2011年第12期44-54,共11页China Sport Science
基 金:中央基本科研业务费资助项目(52096S-1827)
摘 要:目的:验证表面肌电信号(sMES)小波变换分析技术监测重复性手工提放重物作业中肌肉疲劳变化特征的准确性与合理性;方法:BTE primusRS与肌电仪同步,40名男大学生进行两次重复性提放重物能力测试,频率12次/min,木箱(35cm×25cm×25cm)重13kg,蹲举与半蹲举交替,间歇30min;记录sMES与结束即刻问卷评分;测试前、后进行3次持续6s间歇15s的最大腰拉力测试。结果:半蹲举疲劳集中在少数几个部位,尤其是下背部且更明显;BTE primusRS输出参数蹲举高于半蹲举;蹲举时,右T10竖脊肌,左、右L3竖脊肌,股直肌,股外侧肌瞬时中位频率(IMDF)显著下降(P<0.01);半蹲举时,右斜方肌IMDF显著下降(P<0.05),左、右L3竖脊肌,腓肠肌内侧头IMDF显著下降(P<0.01)。结论:表面肌电小波变换分析技术能准确合理地监测重复性手工提放重物作业中肌肉疲劳的变化特征。Objective: To validate accuracy and rationality of the wavelet transform analysis of surface myoelectric signal (sMES) when muscle fatigue was monitored in the repetitive manual lifting and lowering tasks. Methods: BTE PrimusRS system and surface electromyography instrument were synchronized, 40 male undergraduate students repeated twice the test of repeti tive lifting and lowering capacity. The lifting frequency was 12 lifts/min, wooden box (35 cm × 25 cm ×25cm) was 13kg, squat and semi-squat were undertaken by turns, and the interval was 30 minutes, sMES and the immediate discomfort self-ratings after this test were recorded. Be- fore and after this test, subjects were instructed to pull upwards the handle at maximum effort for 6s, each set contained 3 times, and the interval was 15s. Results:The fatigue concentrated in a few parts of the body under the semi-squat, especially in the lower back, and the degree of fatigue became more apparent. The parameters detected by BTE PrimusRs system showed that squat was better than semi-squat. The instantaneous median frequency (1MDF) significantly decreased in the right paravertebral back muscles at T10 , pairs of paravertebral back muscles at L3, rectus femoris and vastus lateralis under the squat. The results were similar with the right trapezius, pairs of paravertebral back muscles at L3 and medial gastrocnemius muscle under the semi-squat. Conclusion:The wavelet transform analysis technique of sMES could monitor the muscle fatigue accurately and reasonably in the repetitive manual lifting and lowering tasks.
分 类 号:G804.6[文化科学—运动人体科学]
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