Institute of Sports Science, University of Oldenburg, Oldenburg, Germany.
Med Sci Sports Exerc. 2012 Nov;44(11):2235-42. doi: 10.1249/MSS.0b013e318260402b.
Accuracy of estimating activity-related energy expenditure (AEE) from raw body acceleration may improve by using prediction equations that are specific for the type of activity. The current study aims to improve published equations by deriving an equation for overground walking and to evaluate whether overground cycling and stair walking require specific prediction equations.
Participants (91 male/95 female, 8-81 yr old) were equipped with a triaxial accelerometer (DynaPort MiniMod; McRoberts BV, The Hague, The Netherlands) on their lower back. Total energy expenditure (TEE) was measured using a mobile oxygen analyzer (MetaMax 3b; Cortex Biophysik, Leipzig, Germany). Resting energy expenditure (REE) was measured for 30 min, following which a physical activity course was completed involving walking on level ground at slow (8 min), normal (8 min), and fast speed (3 min), stair walking (3 min), and cycling (8 min). AEE was calculated as TEE - REE, expressed in both absolute (kJ·min) and relative (J·min·kg) units. Mixed linear regression analysis was used for developing regression equations for walking, stair walking, and cycling.
Acceleration contributed 76% and 93% (P < 0.001) to explained variance in walking AEE for absolute and relative AEE models, respectively. Age and gender improved estimation accuracy by <1%. Applying a conservative walking equation, AEE (J·min·kg) = -40.19 + 816.11 acceleration (g) (root-mean-square error = 34.00 J·min·kg), to cycling and stair walking resulted in mean bias (95% limits of agreement) of -253 (-449, 46) and -276 (-442, 109) J·min·kg, respectively (approximately 50% bias). Acceleration added 35% and 42% to explained variance in relative AEE (J·min·kg) during cycling and stair walking, respectively; this fraction was approximately 20% for absolute AEE (kJ·min) in both activities.
AEE during walking can be predicted across a wide age range using raw acceleration, but activity-specific equations are needed for cycling and stair walking.
通过使用特定于活动类型的预测方程，从原始身体加速度估算与活动相关的能量消耗（AEE）的准确性可能会提高。本研究旨在通过推导出一个用于地面行走的方程来改进已发表的方程，并评估地面骑行和爬楼梯是否需要特定的预测方程。
参与者（91 名男性/95 名女性，8-81 岁）在其下背部佩戴三轴加速度计（DynaPort MiniMod；McRoberts BV，荷兰海牙）。总能量消耗（TEE）使用移动氧气分析仪（MetaMax 3b；Cortex Biophysik，德国莱比锡）进行测量。休息能量消耗（REE）测量 30 分钟，然后完成一项体育活动课程，包括在水平地面上以慢（8 分钟）、正常（8 分钟）和快（3 分钟）速度行走、爬楼梯（3 分钟）和骑自行车（8 分钟）。AEE 计算为 TEE - REE，以绝对（kJ·min）和相对（J·min·kg）单位表示。使用混合线性回归分析为步行、爬楼梯和骑行建立回归方程。
加速度分别对绝对和相对 AEE 模型的步行 AEE 解释方差的贡献为 76%和 93%（P < 0.001）。年龄和性别仅将估计精度提高了<1%。应用保守的步行方程，AEE（J·min·kg）=-40.19 + 816.11 加速度（g）（均方根误差=34.00 J·min·kg），用于骑行和爬楼梯导致平均偏差（95%置信区间）分别为-253（-449, 46）和-276（-442, 109）J·min·kg（约 50%偏差）。加速度分别为 35%和 42%，解释了骑行和爬楼梯过程中相对 AEE（J·min·kg）的方差；在这两种活动中，绝对 AEE（kJ·min）的这一分量约为 20%。
使用原始加速度可以预测整个年龄段的步行时的 AEE，但需要针对骑行和爬楼梯的特定活动方程。
