人体下肢前摆性鞭打动作的力—电关系研究

发布时间：2018-05-28 23:40

本文选题：肌肉 + 力矩　；参考：《鲁东大学》2015年硕士论文

【摘要】：肌肉收缩产生力从而为人体运动提供动力,研究肌肉的力学特性有助于深化了解人体运动的本质和规律。在肌肉评定这方面的信息是多方面、多维度的,首先,在肌肉收缩力学方面,肌肉收缩使关节发生转动从而产生力矩,力矩是评价肌肉功能的定量指标。另外,还包括肌肉运动时的电生理指标,例如表面肌电,表面肌电是肌肉收缩在时间上产生的一系列电信号,对表面肌电的相应参数进行分析可以评定肌肉的活动状态。基于统计学理论对以上两者进行力学建模,数学计算,以及人体实验相结合的方法可以获得运动时人体下肢控制肌群的力-电关系。通过以上运动信息的获得有助于对人体下肢鞭打动作的特点进行研究,确定动作实现的理论依据,评定动作的正确模式。同时还可以建立起相应的力-电关系方程,这样在得到表面肌电的情况下就可以预测相应的关节力矩,因为关节力矩的获取比较复杂费时,而表面肌电的获取则相对容易,这对分析动作技术和关节力矩损伤有非常重要的意义。在动力学方面,本实验建立了下肢环节链模型,通过三维录像与解析系统对实验录像进行解析,对解析后的数据使用自编写的Matlab语言程序包进行分析,从而计算出下肢各关节的关节肌力矩。在肌电学方面,本研究运用时频分析指标对肌电信号进行分析,这弥补了以往在表面肌电分析方面只能对时域参数或者频域参数进行分析的不足。时频分析是结合时间和频率两方面的指标,通过建立两者问的函数关系来描述信号的,可以反映信号频率在时间上的变化趋势。在传统表面肌电分析中运用的诸如平均频率、中值频率的肌电学指标通常适用于肌肉的静态收缩过程,但往往在实际运动中肌肉的收缩都处于动态收缩的过程,静态收缩过程中,肌肉的肌电信号属于平稳的电信号,可以运用中值频率等指标,但动态收缩的过程中肌电信号是非平稳的电信号,此时就需要结合时频分析法对动态收缩过程中的肌电信号进行分析。通过对下肢前摆性鞭打关节力矩的计算以及表面肌电的分析,本文采用逐步回归的方法对下肢髋、膝关节力矩、控制肌群的表面肌电及关节角度建立回归方程,具体方程如下 1、髋关节方程无预摆下肢前摆性鞭打方程:Y=108.985+0.143X5-340.914X6+2.469X7被动预摆下肢前摆性鞭打方程:Y=127.367-0.033X5+9285.734X6+5.287X7主动预摆下肢前摆性鞭打方程:Y=180.837+0.113X5+135.710X6+9.479X7Y：髋关节力矩15：股直肌瞬时平均功率16：股直肌瞬时平均频率17：髋关节角度 2、膝关节方程无预摆下肢前摆性鞭打方程：Y=77.475+0.209X1-0.029X3-0.575X5-3.901X7被动预摆下肢鞭打方程：Y=154.945-2327.52X2+1169.86X4-847.07X6-3.033X7主动预摆下肢前摆性鞭打方程：Y=54.730+732.971X2-688.835X4-1.711X7Y：膝关节力矩X1：股直肌瞬时平均功率X2：股直肌瞬时平均频率X3：股内侧肌瞬时平均功率14：股内侧肌瞬时平均频率15：股外侧肌瞬时平均功率16：股外侧肌瞬时平均频率17：膝关节角度
[Abstract]:Muscle contraction produces force to provide power for human motion. The study of the mechanical properties of muscles helps to deepen the understanding of the nature and laws of human motion. The information in this aspect is multidimensional and multidimensional. First, in the muscle contraction mechanics, muscle contraction causes the joints to turn to produce torque, and the torque is the evaluation of the muscles. The quantitative index of meat function. In addition, it also includes electrophysiological indexes of muscle movement, such as surface electromyography, surface electromyography is a series of electrical signals produced by muscle contraction in time. The analysis of the corresponding parameters of surface electromyography can evaluate the active state of muscles. Based on the theory of unified theory, the above two are mechanic modeling and mathematics. The calculation, and the method of combining the human body, can obtain the force electric relation of the muscle group in the lower limbs of the human body when the movement is exercised. The acquisition of the above motion information is helpful to the study of the characteristics of the movement of the leg whipping, the theoretical basis of the realization of the action and the positive mode of the action, and the corresponding force electricity can also be established. The equation of relation can predict the corresponding joint torque in the case of surface electromyography, because the acquisition of joint torque is more complex and time-consuming, and the acquisition of surface electromyography is relatively easy, which is of great significance for the analysis of action technology and joint torque damage.
In the field of dynamics, the lower limb link chain model was established in this experiment. The experimental video was analyzed by the three-dimensional video and analytical system, and the analytic data was analyzed by the Matlab language program package which was compiled and written by ourselves. Thus the joint muscle torque of the joints of the lower extremities was calculated. In the field of electromyography, the time frequency analysis index was used in this study. The analysis of EMG signal makes up for the deficiency that can only analyze the time domain parameters or frequency domain parameters in the surface electromyography analysis. The time frequency analysis is a combination of two aspects of time and frequency, which describes the signal by establishing the function relation of the two questions, which can reflect the change trend of the signal frequency in time. The electromyography indexes, such as average frequency and median frequency, are usually applied to the static contraction process of muscle, but the contraction of muscle is always in the process of dynamic contraction during the actual movement. In the process of static contraction, the signal of muscle electromyography is a stationary signal and can be used in the middle value frequency and so on. However, in the process of dynamic contraction, the EMG signal is a non-stationary signal. At this time, it is necessary to analyze the EMG signal during the dynamic contraction with the time frequency analysis.
Through the calculation of the torque of the anterior pendulum of the lower limbs and the analysis of the surface electromyography, the regression equation of the hip, knee torque, the surface electromyography and the joint angle of the muscle group is established by stepwise regression. The specific equations are as follows.
1, the hip equation had no pre pendulum whipping equation: Y=108.985+0.143X5-340.914X6+2.469X7 passive pre pendulum front pendulum whipping equation: Y=127.367-0.033X5+9285.734X6+5.287X7 active pre pendulum anterior pendulum whipping equation: Y=180.837+0.113X5+135.710X6+9.479X7Y: hip torque 15: the instantaneous average power of the rectus femoris is 16: stock The instantaneous average frequency of the rectus muscle 17: the hip joint angle
2, the knee joint equation has no pre pendulum front swing equation: Y=77.475+0.209X1-0.029X3-0.575X5-3.901X7 passive pre pendulum lower leg whip equation: Y=154.945-2327.52X2+1169.86X4-847.07X6-3.033X7 active pre pendulum anterior pendulum whipping equation: Y=54.730+ 732.971X2-688.835X4-1.711X7Y: knee torque X1: instantaneous averages of the rectus femoris Power X2: the instantaneous average frequency of the rectus femoris is X3: the instantaneous average power of the medial femoral muscle is 14: the instantaneous average frequency of the medial femoral muscle is 15, the instantaneous average power of the lateral femur muscle is 16: the instantaneous average frequency of the lateral femur muscle is 17: the knee joint angle.
【学位授予单位】：鲁东大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：G804.6

【参考文献】