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作 者:苟明
出 处:《中国体育科技》2017年第5期54-59,83,共7页China Sport Science and Technology
基 金:重庆市教委科技项目(1400100)
摘 要:目的:模拟排球拦网起跳的下肢肌肉动作,建立排球拦网动作骨骼肌肉模型,并以表面肌电验证所建立的肌肉骨骼模型。方法:采用3名优秀女子排球运动员为受试者。9台Vicon Mcam2光学摄影机(250 Hz)、2块三维测力板(1000 Hz)和表面肌电同步撷取数据,以Matlab和Anybody软件进行数据处理,并以动力学逆过程算得下肢内在动力学参数。结果:1)排球拦网起跳动作主要作用肌群为股外侧肌、股内侧肌、股直肌、胫前肌和腓肠肌群;2)起跳动作右脚髋关节最大力矩约121.7 N·m,左脚髋关节最大值力矩约83.5 N·m;右脚膝关节最大值力矩约107.9 N·m,左脚膝关节最大值力矩约103.4 N·m;右脚踝关节最大值力矩约78.9 N·m,左脚踝关节最大值力矩约65.6 N·m;3)表面肌电与模拟数值趋势相同的有股二头肌、股内侧肌、股外侧肌、股直肌、腓肠肌外侧头、腓肠肌内侧头,趋势不相同的有半腱肌、半膜肌、胫骨前肌。结论:使用运动学数据驱动肌肉骨骼模型,发现预测值与表面肌电的讯号有密切关系,并验证所建立的骨骼肌肉模型符合实际动作肌肉活化情况。Objective: To simulate the muscle movements of lower limbs while jumping off to do the action of blocking and building the model construction of skeletal muscles on blocking, which will be verified by the surface electromyography ( SEMG ). Method: The subjects are three excellent female volleyball players in this study. Nine sets of Vicon Mcam2 optical cameras ( 250 Hz ), two force plates and surface electromyography ( SEMG ) were used to collect data simultaneously. The data processing is based on Matlab and Anybody and an inverse dynamic process was used to calculate the kinetically parameters for the lower extremity. Result: 1 ) the main functional muscle groups while jumping off to do the volleyball blocking action are rectus femoris, Vastus medial, rectus femoris, rectus femoris, tibialis anterior and gastrocne mius. 2 ) While jumping off, the maximal torque of right hip joint is about 121.7 N·m, the maximal torque of left hip joint is about 83.5 N·m; the maximal torque of right knee is about 107.9 N·m, the maximal torque of left knee knee is about 103.4 N'm; the maximal torque of right ankle is about 78.9 N·m, the maximal torque of left ankle maximum is about 65.6 N·m. 3 )The surface electromyography ( SEMG ) of vastus medialis, vastus lateralis, rectus femoris, lateral gastrocnemius triceps, medial head of gastrocnemius muscle, showed the same trend with the simulated data. On the other side, the surface electromyography ( SEMG ) of semitendinosus, semimembranous, tibialis anterior showed a different trend with the simulated data. Conclusion: This study uses the kinematic data to drive the musculoskeletal model and finds out that the predicted value is closely related to the SEMG signal and verified the established skeletal muscle model is consistent with the actual muscle activation.
分 类 号:G804.6[文化科学—运动人体科学]
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