Tokuyama Kumpei, Ogata Hitomi, Katayose Yasuko, Satoh Makoto
University of Tsukuba, Ibaraki, Japan 305-8574.
J Appl Physiol (1985). 2009 Feb;106(2):640-50. doi: 10.1152/japplphysiol.90718.2008. Epub 2008 Nov 13.
A whole body indirect calorimeter provides accurate measurement of energy expenditure over long periods of time, but it has limitations to assess its dynamic changes. The present study aimed to improve algorithms to compute O(2) consumption and CO(2) production by adopting a stochastic deconvolution method, which controls the relative weight of fidelity to the data and smoothness of the estimates. The performance of the new algorithm was compared with that of other algorithms (moving average, trends identification, Kalman filter, and Kalman smoothing) against validation tests in which energy metabolism was evaluated every 1 min. First, an in silico simulation study, rectangular or sinusoidal inputs of gradually decreasing periods (64, 32, 16, and 8 min) were applied, and samples collected from the output were corrupted with superimposed noise. Second, CO(2) was infused into a chamber in gradually decreasing intervals and the CO(2) production rate was estimated by algorithms. In terms of recovery, mean square error, and correlation to the known input signal in the validation tests, deconvolution performed better than the other algorithms. Finally, as a case study, the time course of energy metabolism during sleep, the stages of which were assessed by a standard polysomnogram, was measured in a whole body indirect calorimeter. Analysis of covariance revealed an association of energy expenditure with sleep stage, and energy expenditure computed by deconvolution and Kalman smoothing was more closely associated with sleep stages than that based on trends identification and the Kalman filter. The new algorithm significantly improved the transient response of the whole body indirect calorimeter.
全身间接热量计可长时间准确测量能量消耗，但在评估其动态变化方面存在局限性。本研究旨在通过采用随机反卷积方法改进计算氧气消耗和二氧化碳产生的算法，该方法可控制数据保真度和估计平滑度的相对权重。将新算法的性能与其他算法（移动平均、趋势识别、卡尔曼滤波器和卡尔曼平滑）进行比较，以验证测试为对照，其中每1分钟评估一次能量代谢。首先，进行计算机模拟研究，应用逐渐缩短周期（64、32、16和8分钟）的矩形或正弦输入，并对从输出中收集的样本叠加噪声。其次，以逐渐减小的时间间隔向腔室内注入二氧化碳，并通过算法估计二氧化碳产生率。在验证测试中，就恢复情况、均方误差以及与已知输入信号的相关性而言，反卷积算法比其他算法表现更好。最后，作为一个案例研究，在全身间接热量计中测量睡眠期间能量代谢的时间进程，睡眠阶段通过标准多导睡眠图进行评估。协方差分析揭示了能量消耗与睡眠阶段之间的关联，并且通过反卷积和卡尔曼平滑计算的能量消耗与睡眠阶段的关联比基于趋势识别和卡尔曼滤波器的计算更为紧密。新算法显著改善了全身间接热量计的瞬态响应。
