Abstract

Background: Heart rate variability (HRV) is affected by many factors. This paper aims to explore the impact of water temperature (WT) on HRV during bathing. Methods: 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 t-tests, and the mean and standard deviation (SD) of each HRV feature based on the WT were calculated. Results: The statistics show that with increasing WT, 11 HRV features are significantly (p < 0.05) and monotonously reduced, four HRV features are significantly (p < 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. Conclusion: 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.

Highlights

  • Heart rate variability (HRV) is an important indicator of physical and mental health

  • The smaller dots with blue, yellow, and green colors represent the HRV features calculated based on each preset water temperature (WT), while the bigger black dots are the average values of the HRV features based on each preset WT calculated by the K-means clustering analysis method

  • This paper explores the impact of different WTs on HRV during bathing

Read more

Summary

Introduction

Heart rate variability (HRV) is an important indicator of physical and mental health. The quantitative analysis of HRV is considered an effective method for the diagnosis of many cardiac diseases in clinical applications. Many internal and external factors affect HRV. Heart rate variability (HRV) is affected by many factors. Each subject collected five electrocardiogram (ECG) recordings at each preset bathtub WT condition. Twenty HRV features were calculated using 1-min ECG segments each time. Analyses of the significant differences were performed using the multivariate analysis of variance of t-tests, and the mean and standard deviation (SD) of each HRV feature based on the WT were calculated. 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

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call