Stanford Prevention Research Center, Stanford University, Stanford, CA, USA.
Med Sci Sports Exerc. 2013 May;45(5):964-75. doi: 10.1249/MSS.0b013e31827f0d9c.
Previously, the National Health and Examination Survey measured physical activity with an accelerometer worn on the hip for 7 d but recently changed the location of the monitor to the wrist. This study compared estimates of physical activity intensity and type with an accelerometer on the hip versus the wrist.
Healthy adults (n = 37) wore triaxial accelerometers (Wockets) on the hip and dominant wrist along with a portable metabolic unit to measure energy expenditure during 20 activities. Motion summary counts were created, and receiver operating characteristic (ROC) curves were then used to determine sedentary and activity intensity thresholds. Ambulatory activities were separated from other activities using the coefficient of variation of the counts. Mixed-model predictions were used to estimate activity intensity.
The ROC for determining sedentary behavior had greater sensitivity and specificity (71% and 96%) at the hip than at the wrist (53% and 76%), as did the ROC for moderate- to vigorous-intensity physical activity on the hip (70% and 83%) versus the wrist (30% and 69%). The ROC for the coefficient of variation associated with ambulation had a larger AUC at the hip compared to the wrist (0.83 and 0.74). The prediction model for activity energy expenditure resulted in an average difference of 0.55 ± 0.55 METs on the hip and 0.82 ± 0.93 METs on the wrist.
Methods frequently used for estimating activity energy expenditure and identifying activity intensity thresholds from an accelerometer on the hip generally do better than similar data from an accelerometer on the wrist. Accurately identifying sedentary behavior from a lack of wrist motion presents significant challenges.
先前,国家健康与体检调查(National Health and Examination Survey)使用佩戴在髋部的加速度计测量 7 天的身体活动,但最近将监测器的位置改为手腕。本研究比较了髋部和手腕加速度计测量身体活动强度和类型的估计值。
健康成年人(n=37)在髋部和优势手腕佩戴三轴加速度计(Wockets),同时佩戴便携式代谢单元以测量 20 种活动期间的能量消耗。创建运动汇总计数,然后使用接收器操作特征(ROC)曲线确定久坐和活动强度阈值。使用计数的变异系数将散步活动与其他活动分开。使用混合模型预测来估计活动强度。
确定久坐行为的 ROC 在髋部的敏感性和特异性(71%和 96%)均高于手腕(53%和 76%),髋部的中度至剧烈强度身体活动的 ROC(70%和 83%)也高于手腕(30%和 69%)。与步行相关的变异系数的 ROC 在髋部的 AUC 大于手腕(0.83 和 0.74)。活动能量消耗的预测模型导致髋部的平均差异为 0.55±0.55METs,而手腕为 0.82±0.93METs。
从髋部加速度计估计活动能量消耗和识别活动强度阈值的常用方法通常比手腕加速度计的类似数据更好。从手腕运动缺乏中准确识别久坐行为存在重大挑战。