CAJ | 학술논문

为研究专业运动员在不同蹬踏频率下的下肢肌电信号与输出功率之间的特征关系,选取9名专业场地自行车运动员在8%的自身体重负荷下分别以100rpm、120rpm、130rpm、140rpm骑行,同时测试下肢9块肌肉的EMG信号和输出功率的变化值。结果表明：（1）TA、RF、VM、GAS（M）、GAS（L）、BF、STG、GM的AVG和RMS值随着蹬踏频率的增高而变大,而MNF值先降低再增加最后又下降;其中TA、VM、GAS（M）、GAS（L）、STG、GM的AVG和RMS值呈显著性增加,且相关性较明显;（2）峰值（最大输出功率）随蹬踏频率的增高而变大,且相关性十分显著,而相对峰值、最小功率、相对最小功率、平均功率、相对平均功率值随着蹬踏频率的增高而变大,但除蹬踏频率在140RPM外,其他蹬踏频率之间的各个指标不具有相关性;（3）从单因素的Anova分析指标、共线性诊断指标、残差统计量指标出发,结合回归指标建立相关的多元线性模型。
위연구전업운동원재불동등답빈솔하적하지기전신호여수출공솔지간적특정관계,선취9명전업장지자행차운동원재8%적자신체중부하하분별이100rpm、120rpm、130rpm、140rpm기행,동시측시하지9괴기육적EMG신호화수출공솔적변화치。결과표명：（1）TA、RF、VM、GAS（M）、GAS（L）、BF、STG、GM적AVG화RMS치수착등답빈솔적증고이변대,이MNF치선강저재증가최후우하강;기중TA、VM、GAS（M）、GAS（L）、STG、GM적AVG화RMS치정현저성증가,차상관성교명현;（2）봉치（최대수출공솔）수등답빈솔적증고이변대,차상관성십분현저,이상대봉치、최소공솔、상대최소공솔、평균공솔、상대평균공솔치수착등답빈솔적증고이변대,단제등답빈솔재140RPM외,기타등답빈솔지간적각개지표불구유상관성;（3）종단인소적Anova분석지표、공선성진단지표、잔차통계량지표출발,결합회귀지표건립상관적다원선성모형。
As the research professional athletes in different pedaling frequency of lower limb muscle electrical signals and output power between the feature relation,the selection of nine professional athletes bikes in 8% of their body weight load respectively under 100 RPM,120 RPM,130 RPM,140 RPM riding,at the same time to test the changes in value of the lower extremity 9 muscle EMG signal and output power.The results show that:(1)TA、RF、VM、GAS(M)、GAS(L)、BF、STG、GM's AVG and RMS value with cadence of frequency and change,and to reduce the MNF value add then down;The TA、VM、GAS(M)、GAS(L)、STG、GM's AVG and RMS value was significantly increased,and the correlation is obvious;(2)Peak(maximum output power) along with the cadence of frequency and change,and correlation is very remarkable,and relatively peak,minimum power,relative minimum power,average power,relative average power value with cadence of frequency and change,but the addition to the the pedaling frequency 140RPM outside,other pedaling frequency between the indicators do not have relevance;(3)From the single factor also revealed by one-way Anova analysis index,collinearity diagnosis index,residual statistics indicators,combined with the regression index set up related multivariate linear model.