Research on comfort evaluation of high-speed train passengers based on heart rate variability

被引：0
作者：
Peng Y. [1 ]
Xu D. [1 ]
Fan C. [1 ]
Tan S. [2 ]
Liang X. [1 ]
机构：
[1] School of Traffic & Transportation Engineering, Central South University, Changsha
[2] Xiangya Second Hospital, Central South University, Changsha
来源：
Journal of Railway Science and Engineering | 2023年 / 20卷 / 02期
关键词：
comfort; heart rate variability; high-speed train; machine learning; T-test;
D O I：
10.19713/j.cnki.43-1423/u.T20220386
中图分类号：
学科分类号：
摘要：
People-oriented development is the foundation of high-speed railway technology, making the evaluation of passenger comfort a key factor. Providing an intuitive reflection of the human body state, physiological signals has incomparable advantages in evaluating passenger comfort. Heart rate variability is the change of time interval between adjacent heartbeat intervals in electrocardiogram, which can reflect the balance state of the autonomic nervous system. To study the relationship between heart rate variability and passenger comfort of high-speed train, this paper presented a real vehicle experiment of passenger comfort of high-speed train on Shanghai-Kunming high-speed railway line. Combined with the results of the passenger subjective comfort questionnaire, the changes of ten heart rate variability characteristics of passengers under varying comfort levels were analyzed. To assess the comprehensive comfort, vibration comfort and ear pressure comfort of passengers, T-test was used to determine the significance of various characteristics on “comfortable” and “uncomfortable” states. Further, an evaluation model of passenger comfort of high-speed train based on random forest algorithm was established. The results show that the characteristics of heart rate variability have a similar change trend when the comfort level of different problems changes, and that Mean_rr is significantly correlated with comprehensive comfort, while SDNN and SD2 are significantly correlated with vibration comfort. The accuracy of the comfort recognition model for comprehensive comfort, vibration comfort and ear pressure comfort is 74.32%, 70.67% and 68.27%, respectively. © 2023, Central South University Press. All rights reserved.
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页码：453 / 462
页数：9
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