Xu Jianbo, Chen Wenxi
Biomedical Information Engineering Laboratory, The University of Aizu, Aizu-Wakamatsu 965-8580, Japan.
Life (Basel). 2021 Apr 22;11(5):378. doi: 10.3390/life11050378.
Heart rate variability (HRV) is affected by many factors. This paper aims to explore the impact of water temperature (WT) on HRV during bathing.
The bathtub WT was preset at three conditions: i.e., low WT (36-38 °C), medium WT (38-40 °C), and high WT (40-42 °C), respectively. Ten subjects participated in the data collection. Each subject collected five electrocardiogram (ECG) recordings at each preset bathtub WT condition. Each recording was 18 min long with a sampling rate of 200 Hz. In total, 150 ECG recordings and 150 WT recordings were collected. Twenty HRV features were calculated using 1-min ECG segments each time. The k-means clustering analysis method was used to analyze the rough trends based on the preset WT. Analyses of the significant differences were performed using the multivariate analysis of variance of -tests, and the mean and standard deviation (SD) of each HRV feature based on the WT were calculated.
The statistics show that with increasing WT, 11 HRV features are significantly ( < 0.05) and monotonously reduced, four HRV features are significantly ( < 0.05) and monotonously rising, two HRV features are rising first and then reduced, two HRV features (fuzzy and approximate entropy) are almost unchanged, and vLF power is rising.
The WT has an important impact on HRV during bathing. The findings in the present work reveal an important physiological factor that affects the dynamic changes of HRV and contribute to better quantitative analyses of HRV in future research works.
心率变异性(HRV)受多种因素影响。本文旨在探讨洗澡期间水温(WT)对HRV的影响。
浴缸水温预设为三种条件,即低水温(36 - 38°C)、中水温(38 - 40°C)和高水温(40 - 42°C)。十名受试者参与数据收集。每位受试者在每个预设的浴缸水温条件下收集五份心电图(ECG)记录。每份记录时长18分钟,采样率为200Hz。总共收集了150份ECG记录和150份水温记录。每次使用1分钟的ECG片段计算20个HRV特征。采用k均值聚类分析方法基于预设水温分析大致趋势。使用方差分析的多变量检验进行显著差异分析,并计算基于水温的每个HRV特征的均值和标准差(SD)。
统计结果表明,随着水温升高,11个HRV特征显著(<0.05)且单调降低,4个HRV特征显著(<0.05)且单调升高,2个HRV特征先升高后降低,2个HRV特征(模糊熵和近似熵)几乎不变,且极低频功率升高。
洗澡期间水温对HRV有重要影响。本研究结果揭示了一个影响HRV动态变化的重要生理因素,并有助于未来研究工作中对HRV进行更好的定量分析。