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目的:根据不同思路建立Actigraph加速度传感器能耗预测模型并加以验证,为更好地应用加速度传感器监测体力活动提供依据。方法:以男女大学生各30人为实验组,进行静坐、看书、整理书桌、扫地、慢走(4 km/h)、快走(6 km/h)和慢跑(8 km/h)共7项活动;另以男女大学生各10人作为验证组,进行约4 h日常体力活动。分别以Actigraph GT3X加速度传感器和Cosmed K4b2气体代谢分析仪监测垂直轴加速度记数(accelerometry counts,AC)和能耗。采用线性回归法,根据实验组数据建立3个以AC为自变量的能耗预测模型。以验证组数据,采用配对t检验和Altman-Bland图验证上述3个模型和Freedson模型的有效性。结果:本研究建立的分段线性模型为:如AC<1630 counts/min,则METs=1.419+0.005644×AC-5.927×10-6×AC2+1.993×10-9×AC3;如AC≥1630 counts/min,则METs=1.818+0.000752×AC。经验证,使用Actigraph加速度传感器监测日常体力活动时,可应用上述模型推算体力活动总能耗。
OBJECTIVE: To establish and verify the Actigraph accelerometer energy consumption prediction model according to different ideas and provide a basis for better application of accelerometer monitoring physical activity. Methods: A total of 30 male and female undergraduates were enrolled in this study. There were 7 activities of sitting, reading, arranging desks, sweeping, walking (4 km / h), brisk walking (6 km / h) and jogging (8 km / h) The other men and women of the other 10 as a verification group, about 4 h daily physical activity. Vertical axis acceleration (accelerometry counts, AC) and energy consumption were monitored using the Actigraph GT3X accelerometer and the Cosmed K4b2 gas metabolism analyzer, respectively. Using linear regression method, three energy consumption prediction models with AC as independent variable were established based on experimental group data. To verify the data of the group, paired t-test and Altman-Bland plots were used to verify the validity of the above three models and the Freedson model. Results: The piecewise linear model established in this study is as follows: METs = 1.419 + 0.005644 × AC-5.927 × 10-6 × AC2 + 1.993 × 10-9 × AC3, such as AC <1630 counts / min; / min, then METs = 1.818 + 0.000752 × AC. Proved to use Actigraph accelerometer to monitor daily physical activity, the above model can be used to calculate the total energy consumption of physical activity.