Comparison of PAEE from combined and separate heart rate and movement models in children
Comparison of PAEE from combined and separate heart rate and movement models in children
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DOI：
10.1249/01.mss.0000176466.78408.cc
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发表时间：
2005-10-01
期刊：
影响因子：
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通讯作者：
Ekelund, U
中科院分区：
文献类型：
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作者：
Corder, K;Brage, S;Ekelund, U
目的：准确测量儿童的体力活动是一项挑战。结合生理(例如，心率(HR))和身体运动记录(例如，加速度法)可以克服单独使用这两种方法中的任何一种的局限性。这项研究旨在比较臀部和脚踝安装的MTI Actigraph和新的心率和运动组合传感器ActiHeart(剑桥神经技术公司，英国帕普沃斯)的估计体力活动能量消耗(PAEE)。方法：采用间接量热法对39例儿童(13.2+/-0.3岁)进行递增负荷平板运动时的静息EE和次极量EE(跑台步行和跑步)的测定。通过线性回归模型检验监测结果(活动计数、HR和活动计数+HR)与标准之间的关系。通过修改的Bland-Altman曲线图在参与者的一个子样本中检验了测量的PAEE和预测的PAEE之间的一致性。结果：心动联合模型(活动次数+心率)与PAEE的相关性最强(R2=0.86)，而单指标模型与活动模型和HR模型的相关系数分别为0.69和0.82。对于髋关节MTI、踝关节MTI和ACTIC，其他活动监测仪的解释方差较低(R2分别为0.50、0.37和0.67)。在交叉验证分析中，在仅使用活动计数的所有模型中，方法的估计误差与标准之间存在显著相关性(r=0.49至0.90)，表明存在较大的系统误差。HR模型和组合模型的系统误差较小(r分别为0.41和0.33)。结论：在所考虑的技术中，与单独运动或HR相比，联合HR和运动感知是评估儿童在跑步机上行走和跑步时PAEE最有效的方法。它的系统误差水平也是最低的。
Purpose: Accurate measurement of physical activity in children is a challenge. Combining physiological (e.g., heart rate (HR)) and body movement registration (e.g., accelerometry) may overcome limitations with either method used alone. This study aimed to compare the estimated physical activity energy expenditure (PAEE) from hip- and ankle-mounted MTI Actigraphs, a hip-mounted Actical, and a new combined HR and movement sensor, the Actiheart (Cambridge Neurotechnology, Papworth, UK). Methods: Resting EE and submaximal EE (treadmill walking and running) were measured in 39 children (13.2 +/- 0.3 yr) by indirect calorimetry during a progressive treadmill exercise bout. Associations between monitor Outputs (activity counts, HR, and activity counts + HR) and the criterion were examined by linear regression models. The agreement between measured and predicted PAEE was examined by modified Bland-Altman plots in a subsample of participants. Results: The combined Actiheart model (activity counts + HR) had the strongest relationship with PAEE (R-2 = 0.86), compared with those from the single-measure models (R-2 = 0.69 and 0.82 for the activity model and HR model). The explained variances from the other activity monitors were lower (R-2 = 0.50, 0.37, and 0.67) for the hip MTI, ankle MTI, and Actical, respectively. In cross-validation analyses, significant correlations were observed between estimation errors of the methods with the criterion (r = 0.49 to 0.90) in all models using only activity counts indicating a large systematic error. The HR and combined models indicated less systematic error (r = 0.41 and 0.33, respectively). Conclusions: Of the techniques considered, combined HR and movement sensing is the most valid for estimating PAEE in children during treadmill walking and running, compared with movement or HR alone. It also has the lowest level of systematic error.