Investigating Heart Rate Variability of Metro Drivers before an Inappropriate Stop at Platform with Wearable Devices

Abstract

Inappropriate stops at platforms (ISPs) of metros, including platform early stops (PESs) and platform overruns (POs), may hinder operation safety and efficiency. One possible reasons is that metro drivers suffer aberrant physiological states before braking on the metro. However, this issue has rarely been analyzed in previous studies. This study investigated metro drivers’ heart rate variability (HRV) features before metro stops and uncovered an association between HRV features and ISPs. Electrocardiogram signals from 32 professional metro drivers were collected through simulated driving experiments. Their RR intervals (The drivers' time difference between successive R waves on an electrocardiogram) within 8, 30, and 60 s before metro stops were examined. Drivers’ sociodemographic and HRV features extracted from different time-windows were processed using principal component analysis to reduce multicollinearity. The study applied multinomial logistic regressions to relate the principal components to the types of metro stop. The results revealed that drivers’ RR intervals within 8 and 60 s before PESs/POs were significantly different from those within 0 and 8 s before PESs/POs. The RR intervals before PESs and POs were significantly larger and smaller, respectively, than those before non-ISPs. Drivers who were relaxed during the approaches tended to trigger more PESs, whereas those who were tense and nervous during the operations tended to trigger more POs. The associations between 12 HRV features extracted by the 8-s time-window and ISP type were different from those extracted by the 30- and 60-s time-window. Additionally, older and experienced drivers were likely to trigger PESs, whereas young and experienced drivers were likely to trigger more POs.

Keywords

inappropriate stop at platform metro drivers principal component analysis multinomial logistic regression heart rate variability

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