使用度测量进行心肺运动测试时呼吸参数的可预测性
Léon Genecand1,2, Cyril Jaksic3, Gaëtan Simian4
1Service de Pneumologie, Département de Médecine, Hôpitaux Universitaires de Genève, Genève, Switzerland.
患有呼吸功能障碍 (DB) 的患者的不规律呼吸可以使用样本 (SampEn) 和近似 (ApEn) 来评估. 一种新的方法纠正了运动数据的趋势,提高了这些测量的准确性.
科学领域:
- 生理学 生理学 生理学
- 生物医学工程 生物医学工程
- 数据科学数据科学数据科学
背景情况:
- 功能障碍呼吸 (DB) 的特点是休息和运动期间的呼吸模式不稳定.
- 样本 (SampEn) 和近似 (ApEn) 用于测量时间序列的可预测性.
- 在经常包含趋势的心肺运动测试 (CPET) 数据中,SampEn和ApEn的应用是不确定的.
研究的目的:
- 评估趋势,呼吸周期变化和耐受间隔系数对SampEn和ApEn计算的影响.
- 评估LOESS0.75方法在运动期间纠正计算趋势的有效性.
主要方法:
- 使用现实生活练习数据进行模拟.
- 用和没有趋势调整计算SampEn和ApEn.
- 使用LOESS0.75趋势调整方法.
主要成果:
- 趋势显著低估了SampEn和ApEn值.
- LOESS0.75方法有效地对趋势进行了校正,产生接近预测值的结果.
- 呼吸周期数量和耐受系数的变化极大地影响了SampEn和ApEn的结果.
结论:
- 来自LOESS0.75方法的余量提供了一种可靠的方式来估计运动数据中的SampEn和ApEn.
- 报告呼吸周期数和耐受系数对于准确解释SampEn和ApEn结果至关重要.
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