Self‐similarity analysis of vehicle driver's electrodermal activity

Haouij, Neska El; Ghozi, Raja; Poggi, Jean‐Michel; Sevestre, Patrick

doi:10.1002/qre.2526

Cited by 5 publications

(3 citation statements)

References 48 publications

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“…It is usually assumed that the higher the LF/HF ratio, the more stressed individuals will be [ 13 ]. The term stress is frequently used instead of arousal [ 65 ]. Although the participants probably experienced stress during their first exposure to the ball (even if the simulated hazard was not strong enough to activate the sympathetic system) may have been triggered in both groups (as indicated by the LF/HF ratio).…”

Section: Discussionmentioning

confidence: 99%

Car drivers coping with hazardous events in real versus simulated situations: Declarative, behavioral and physiological data used to assess drivers’ feeling of presence

et al. 2021

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More than 1.3 million people lose their lives every year in traffic accidents. Improving road safety requires designing better vehicles and investigating drivers’ abilities more closely. Driving simulators are constantly being used for this purpose, but the question which often arises as to their validity tends to be a barrier to developments in this field. Here we studied the validity of a simulator, defined as how closely users’ behavior under simulated conditions resembles their behavior on the road, based on the concept of drivers’ feeling of presence. For this purpose, the driving behavior, physiological state and declarative data of 41 drivers were tested in the Sherpa2 simulator and in a real vehicle on a track while driving at a constant speed. During each trial, drivers had to cope with an unexpected hazardous event (a one-meter diameter gym ball crossing the road right in front of the vehicle), which occurred twice. During the speed-maintenance task, the simulator showed absolute validity, in terms of the driving and physiological parameters recorded. During the first hazardous event, the physiological parameters showed that the level of arousal (Low Heart Rate/High Heart Rate ratio x10) increased up to the end of the drive. On the other hand, the drivers’ behavioral (braking) responses were 20% more frequent in the simulator than in the real vehicle, and the physiological state parameters showed that stress reactions occurred only in the real vehicle (+5 beats per minute, +2 breaths per minute and the phasic skin conductance increased by 2). In the subjects’ declarative data, several feeling of presence sub-scales were lower under simulated conditions. These results suggest that the validity of motion based simulators for testing drivers coping with hazards needs to be questioned.

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Section: Discussionmentioning

confidence: 99%

Car drivers coping with hazardous events in real versus simulated situations: Declarative, behavioral and physiological data used to assess drivers’ feeling of presence

et al. 2021

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“…Other approaches based on the use of physiological signals that do not employ ML algorithms are also proposed in literature. As a few examples, in [14], a self-similarity analysis of EDA using a wavelet-based approach is presented to evaluate the stress levels in subjects during a real-world driving experiment. In this case, only the EDA signals logged from both the foot and hand of the test subjects are considered.…”

Section: Introductionmentioning

confidence: 99%

Exploring Physiological Signal Responses to Traffic-Related Stress in Simulated Driving

Zontone

Affanni

Piras

et al. 2022

Sensors

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In this paper, we propose a relatively noninvasive system that can automatically assess the impact of traffic conditions on drivers. We analyze the physiological signals recorded from a set of individuals while driving in a simulated urban scenario in two different traffic scenarios, i.e., with traffic and without traffic. The experiments were carried out in a laboratory located at the University of Udine, employing a driving simulator equipped with a moving platform. We acquired two Skin Potential Response (SPR) signals from the hands of the drivers, and an electrocardiogram (ECG) signal from their chest. In the proposed scheme, the SPR signals are then processed through a Motion Artifact (MA) removal algorithm such that possible motion artifacts arising during the drive are reduced. An analysis considering the scalogram of the single cleaned SPR signal is presented. This signal, along with the ECG, is then fed to various Machine Learning (ML) algorithms. More specifically, some statistical features are extracted from each signal segment which, after being analyzed through a binary ML model, are labeled as corresponding to a stressful situation or not. Our results confirm the applicability of the proposed approach to identify stress in the two scenarios. This is also in accordance with our findings considering the SPR signal scalograms.

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“…This model provides a generalisation of the popular Wiener process and maximum likelihood inference is discussed in detail. In the last paper, El Haouij et al use self‐similarity analysis for vehicle driver's electrodermal activity (EDA) . A wavelet‐based method is proposed to describe the different scales of the EDA.…”

mentioning

confidence: 99%

The ENBIS‐18 quality and reliability engineering international special issue

Stillman

Triantafyllopoulos

2019

Quality & Reliability Eng

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ENBIS was founded in 2000 to advance and facilitate the development and application of statistical methods to the benefit of European business and industry. It has been successful in promoting good practice in statistics, bridging the gap between methodology and application and fostering networking between practising statisticians in academic and commercial settings. This special issue contains 15 papers, which further demonstrate and illustrate these aims and activities.The special issue starts with three papers on design of experiments. Godolphin discusses the important issue of missing data and design breakdown and develops conditions for connectivity and robustness of incomplete block designs. 1 On a related theme, Alrweili et al propose a minimax loss response surface design which is robust to observation loss when compared to similar designs in the literature. 2 Han develops an optimal design for accelerated life testing of manufactured products. Various optimality criteria for the design are considered, and the existence of the optimal designs is investigated for exponential lifetimes with a single stress variable. 3 The next group of papers makes contributions to control charts in statistical process control (SPC). Abbas et al investigate dispersion control charts under median rank sampling schemes aimed at improving the design. The proposed charts are evaluated in terms of relative efficiency and power for normal and non-normal processes. 4 Perdikis and Psarakis contribute a survey paper on multivariate adaptive control charts. 5 The paper provides an extensive discussion of recent advances in a rapidly growing area of SPC. Wilson et al propose a method for monitoring changes in dynamic networks described by a degree corrected stochastic block model. 6 Their approach involves first estimating the model parameters and then monitoring the estimates using SPC techniques. The surveillance strategy is applied to a dynamic US Senate co-voting network. Dobi and Zempleni develop a monitoring procedure, based on Markov chains, to target healthcare data. 7 The proposed method is capable of monitoring shifts in the mean patient health indicator, as well as allowing for treatment effects and time between patient visits. The procedure also takes into account protocol costs, which can be a critical factor in adoption of a monitoring scheme.We then present three application-based papers within the remit of data science. Smith et al discuss issues in the provision of data analytic services through examples in the automotive aftermarket sector. 8 The data analysis is followed by a discussion of the implications for analyst and client and provides useful insight into the practicalities of working in this emerging field. An important subject within data science is semi-supervised learning and this is the topic of the next paper. Frumosu and Kulahci develop an outlier detection procedure for unlabelled data using scarce labelled data. 9 The proposed methodology uses a combination of Hotelling's T-square and Q statistics and...

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Self‐similarity analysis of vehicle driver's electrodermal activity

Cited by 5 publications

References 48 publications

Car drivers coping with hazardous events in real versus simulated situations: Declarative, behavioral and physiological data used to assess drivers’ feeling of presence

Car drivers coping with hazardous events in real versus simulated situations: Declarative, behavioral and physiological data used to assess drivers’ feeling of presence

Exploring Physiological Signal Responses to Traffic-Related Stress in Simulated Driving

The ENBIS‐18 quality and reliability engineering international special issue

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