Exploration About The Relationship Of Triaxial Acceleration Counts And Energy Expenditure In Walking And Jogging

Purpose: To explore the variety characteristics about energy consumption and three accelerometer（ActiGraph GT3X） counts, and each index with body counts; Analysis the correlation betweencounts and energy consumption, put forward the energy consumption forecast equations, bycomparing the indirect hot measurement based on the three accelerometer （Actigraph GT3X） counts,seek different intensity body movement counts range.Methods: Choose nanjing sports institute,institute of technology of nanjing university and other institutions college students and teachers were115general health subjects, experimental use4.8km/h,5.6km/h,6.4km/h,7.2km/h,8.0km/h,8.8km/h pace movement, the use of indirect heat test method as standard, not synchronous speedmovement analysis of three dimensional counts and the change characteristics of the energyconsumption, different gender of acceleration count change characteristics, as well as the differentbody counts index and the energy consumption.Results: At4.8km/h,5.6km/h,6.4km/h speed walk,men and women MET, VO2(ml·kg^-1·min^-1) there is no difference value,7.2km/h,8.0km/h,8.8km/h speed when running a statistically significant difference between gender （P <0.05）, and theincreased pace, difference gradually improve; In not synchronous speed, and vector counts genderdifferences between not significant, but the vertical axis, loss of shape shaft, coronary shaft counts allhave different level difference; Not synchronous speed between weight group under close vectorcounts were no statistically significant differences, MET with weight gain, VO2value and drop;Height, weight and energy consumption indicators to fat low correlation, weight, sex, BMI is around0.2significant level in related; According to the physical activity intensity grading standards,calculate GT3X different physical activity level counts value range: mild physical activity≤1997cnts/min,moderate intensity physical activity（1998～5415）cnts/min, high strength physicalactivity （5416～8844）cnts/min, very high intensity physical activity quartile≥8845cnts/min;Put forward the energy consumption forecast equations:（1） VO2(ml·kg^-1·min^-1)=0.039*Vector+0.728*gender﹣0.51*BMI+14.188;（2） the METs=0.011*Vector+0.212*gender﹣0.146*BMI+4.066;（3） the energy consumption （kcal/min）=0.13*Vector+1.193*gender+0.194*BMI﹣4.235.Conclusion: in the evaluation of the physical activity predict energy consumption, threeaccelerometer counts and vector than vertical axis counts can reduce weight between differentgender and forecasting error between groups, but in a single movement way （walking and jogging）,single axis （vertical axis） predictions may more effective than$vector. The calculation of thestrength of the physical activity counts scope and Freedson etc of the classification of the lowcompared, this may and the design of experiments, the experiment object, and the accelerometer type.BMI and gender into equation, improve the prediction accuracy of counts energy consumption.