Individual differences in BEV drivers' range stress during first encounter of a critical range situation

Stress influence on real-world driving identified by monitoring heart rate variability and morphologic variability of electrocardiogram signals: the case of intercity roads

Objectives. This study examines which of the heart rate variability (HRV) and morphologic variability (MV) metrics may have the highest accuracy in different stress detection during real-world driving. Methods. The cross-sectional study was carried out among 93 intercity mini-bus male drivers aged 22-67 years. The Trillium 5000 Holter Recorder and GARMIN Virb Elite camera were used to determine heart rate and vehicle speed measurements along the path, respectively. We considered the HRV and MV metrics of electrocardiogram (ECG) signals including the mean RR interval (mRR), mean heart rate (mHR), normalized low-frequency spectrum (nLF), normalized high-frequency spectrum (nHF), normalized very low-frequency spectrum (nVLF), difference of normalized low-frequency spectrum and normalized high-frequency spectrum (dLFHF), and sympathovagal balance index (SVI). Results. The analysis showed that the HRV metrics mHR, mRR, nVLF, nLF, nHF, dLFHF and SVI are effective in mental stress detection while driving as compared to rest time. We obtained a high accuracy of stress detection for MV metrics as compared to the traditional HRV analysis, of approximately 92%. Conclusions. Our findings indicate that driver stress could be detected with an accuracy of 92% using MV metrics as an accurate physiological index of the driver's state.

Individual differences in cardiorespiratory measures of mental workload: An investigation of negative affectivity and cognitive avoidant coping in pilot candidates

Cardiorespiratory measures provide useful information in addition to well-established self-report measures when monitoring operator capacity. The purpose of our study was to refine the assessment of operator load by considering individual differences in personality and their associations with cardiorespiratory activation. Physiological and self-report measures were analyzed in 115 pilot candidates at rest and while performing a multiple task covering perceptual speed, spatial orientation, and working memory. In the total sample and particularly in individuals with a general tendency to worry a lot, a cognitive avoidant coping style was associated with a smaller task-related increase in heart rate. Negative affectivity was found to moderate the association between cardiac and self-reported arousal. Given that physiological and self-report measures of mental workload are usually combined when evaluating operator load (e.g., in pilot selection and training), our findings suggest that integrating individual differences may reduce unexplained variance and increase the validity of workload assessments.

Human factors for a sustainable future

Current human activities are seriously eroding the ability of natural and social systems to cope. Clearly we cannot continue along our current path without seriously damaging our own ability to survive as a species. This problem is usually framed as one of sustainability. As concerned professionals, citizens, and humans there is a strong collective will to address what we see as a failure to protect the natural and social environments that supports us. While acknowledging that we cannot do this alone, human factors and ergonomics needs to apply its relevant skills and knowledge to assist where it can in addressing the commonly identified problem areas. These problems include pollution, climate change, renewable energy, land transformation, and social unrest amongst numerous other emerging global problems. The issue of sustainability raises two fundamental questions for human factors and ergonomics: which system requires sustaining and what length of time is considered sustainable? In this paper we apply Wilson (2014) parent-sibling-child model to understanding what is required of an HFE sustainability response. This model is used to frame the papers that appear in this Special Issue.