scholarly journals Modelling the effects of stress on gap-acceptance decisions combining data from driving simulator and physiological sensors

2018 ◽  
Vol 59 ◽  
pp. 418-435 ◽  
Author(s):  
Evangelos Paschalidis ◽  
Charisma F. Choudhury ◽  
Stephane Hess
Keyword(s):  
Driving Simulator ◽  
Gap Acceptance ◽  
Combining Data ◽  
Effects Of Stress ◽  
Physiological Sensors

scholarly journals A Physiological Sensor-Based Android Application Synchronized with a Driving Simulator for Driver Monitoring

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 399 ◽  
Author(s):  
David González-Ortega ◽  
Francisco Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez
Keyword(s):  
Driving Simulator ◽  
Android Application ◽  
Game Engine ◽  
Vehicle Data ◽  
Driver Monitoring ◽  
Skin Response ◽  
Android App ◽  
Physiological Sensors ◽  
Electrocardiogram Ecg ◽  
Physiological Sensor

In this paper, we present an Android application to control and monitor the physiological sensors from the Shimmer platform and its synchronized working with a driving simulator. The Android app can monitor drivers and their parameters can be used to analyze the relation between their physiological states and driving performance. The app can configure, select, receive, process, represent graphically, and store the signals from electrocardiogram (ECG), electromyogram (EMG) and galvanic skin response (GSR) modules and accelerometers, a magnetometer and a gyroscope. The Android app is synchronized in two steps with a driving simulator that we previously developed using the Unity game engine to analyze driving security and efficiency. The Android app was tested with different sensors working simultaneously at various sampling rates and in different Android devices. We also tested the synchronized working of the driving simulator and the Android app with 25 people and analyzed the relation between data from the ECG, EMG, GSR, and gyroscope sensors and from the simulator. Among others, some significant correlations between a gyroscope-based feature calculated by the Android app and vehicle data and particular traffic offences were found. The Android app can be applied with minor adaptations to other different users such as patients with chronic diseases or athletes.

scholarly journals Driving me crazy: the effects of stress on the driving abilities of paramedic students

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Trevor Hines Duncliffe ◽  
Brittany D'Angelo ◽  
Michael Brock ◽  
Cal Fraser ◽  
Nick Austin ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Acute Stress ◽  
Management Education ◽  
Negative Impact ◽  
Driving Ability ◽  
Driver Training ◽  
Before And After ◽  
Effects Of Stress ◽  
Working Day ◽  
Post Stress

<p><strong>Background</strong></p><p>Previous research has demonstrated that stress has a negative impact on the performance of paramedics while performing medical related tasks. Acute stress has also been shown to negatively impact the driving abilities of the general population increasing the number of critical driving errors performed. No literature was discovered that discussed the effects of stress on the driving abilities of paramedics.</p><p><strong>Methods</strong></p><p>Paramedic students underwent a driving ability assessment in a driving simulator. We then exposed them to a stress inducing medical scenario. Another driving assessment was then conducted. The numbers, and types of errors were documented before and after the scenario.</p><p><strong>Results</strong></p><p>36 students participated in the study. Paramedic students demonstrated no increase in overall error rate after a stressful scenario, but demonstrated an increase in three critical driving errors; failure to wear a seatbelt (3 baseline v 10 post stress, p= 0.0087), failing to stop for red lights or stop signs (7 v 35, p= &lt;0.0001), and losing controlling of the vehicle (2 v 11, p= 0.0052).</p><p><strong>Conclusion</strong></p><p>Paramedic students demonstrated an increase in critical driving errors after a stressful simulated clinical scenario. Paramedics are routinely exposed to acute stress during the course of their working day. This stress could increase the number of critical driving errors that occur. These results reinforce the need for further research, and highlight the potential need for increased driver training and stress management education in order to mitigate the frequency and severity of driving errors made by paramedics.</p>

Examining the effects of stress on the driving abilities of paramedic students

2019 ◽  
Vol 9 (4) ◽  
pp. 76-83
Author(s):  
Trevor Hines Duncliffe ◽  
Brittany D'Angelo ◽  
Michael Brock ◽  
Cal Fraser ◽  
Jake Lamarra ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Acute Stress ◽  
Clinical Performance ◽  
Seat Belt ◽  
Task Load ◽  
Stress Levels ◽  
Before And After ◽  
Negative Effect ◽  
Effects Of Stress ◽  
Nasa Task Load Index

Background: Research has suggested that stress may have a negative effect on paramedics' clinical performance. Stress has also been demonstrated to negatively affect the driving abilities of the general population, increasing the number of driving errors. However, no studies have explored stress and its potential impact on the non-clinical performance of paramedics, particularly their driving abilities. Methods: Paramedic students underwent emergency driving assessment in a driving simulator before and after exposure to a stressful medical scenario. The number and type of errors were documented before and after through the use of both driving simulator software and observation by two members of the research team. The NASA Task Load Index (TLX) was used to record self-reported stress levels. Results: Thirty-six students participated in the study. Following exposure to a stressful medical scenario, paramedic students had no rise in overall error rate, but demonstrated increases in three critical driving errors: namely, failure to wear a seat belt (three baseline versus 10 after stress); failing to stop for red lights or stop signs (seven versus 35); and losing control of the vehicle (two versus 11). Self-reported stress levels also increased after the clinical scenario, particularly in the area of mental (cognitive) demand. Conclusion: Paramedics are routinely exposed to acute stress in their everyday work, and this stress could affect their non-clinical performance. The critical errors committed by participants in the present study closely matched those considered to be contributory factors in many ambulance collisions. These results illustrate the need for further research into the effects of stress on non-clinical performance in general, and highlight the potential need to consider additional driver training and stress management education to mitigate the frequency and severity of driving errors among paramedics.

Detecting Drivers’ Stress in Emergency Using Physiological Sensors

2015 ◽  
Vol 742 ◽  
pp. 150-157
Author(s):  
Ying Chen
Keyword(s):  
Heart Rate ◽  
Stress State ◽  
Driving Simulator ◽  
Time Frame ◽  
Training System ◽  
Heart Rate Variability Analysis ◽  
Continuous Measure ◽  
Physiological Sensors ◽  
Emergency Scenarios ◽  
Driver Stress

This paper presented methods for collecting and analyzing heart rate data during virtual-world driving task in emergency to distinguish and assess a driver’s stress state. The primer study had developed the driver stress training system loaded on driving simulator to display 14 typical emergency scenarios in different road environment. Electrocardiogram was recorded continuously by Physiological Sensors while drivers followed a random simulated driving on the driving simulator. Data from 30 drivers of at least 10 times per scenario were collected for analysis. The data were analyzed in two ways of HRV (Heart Rate Variability) analysis. Analysis I used time domain indexes of data during the driving in the whole training to distinguish the stress occur during the time frame of the scenario with an accuracy of over 98% across multiple drivers and driving days. Analysis II compared frequency indexes of data in stress state in emergency and in clam, with a metric of observable stressors created by the scenarios. The results showed that heart rate metrics is most closely correlated with driver stress level for most drivers studied. These findings confirmed that heart rate signals can provide a metric of driver stress in future cars capable of physiological monitoring. Such measurement could be used to help manage non-critical and critical in-vehicle information systems and could also provide a continuous measure of how different road and traffic conditions affect drivers. Physiological sensors can be used in driving assistance system in future.

scholarly journals The effects of stress on the driving abilities of paramedic students: a pilot, simulator-based study

2019 ◽  
Author(s):  
Trevor Hines Duncliffe ◽  
Brittany D’Angelo ◽  
Michael Brock ◽  
Cal Fraser ◽  
Jake Lamarra ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Negative Impact ◽  
Clinical Performance ◽  
Significant Risk ◽  
List Type ◽  
Clinical Scenario ◽  
Clinical Scenarios ◽  
Stress Levels ◽  
Before And After ◽  
Effects Of Stress

AbstractBackgroundPrevious research has suggested that stress may have a negative effect on the clinical performance of paramedics. In addition, stress has been demonstrated to have a negative impact the driving abilities of the general population, increasing the number of driving errors. However, to date no studies have explored stress and its potential impact on non-clinical performance of paramedics, particularly their driving abilities.MethodsParamedic students underwent emergency driving assessment in a driving simulator before and after exposure to a stressful medical scenario. Number and type of errors were documented before and after by both driving simulator software and observation by two observers from the research team. The NASA Task Load Index (TLX) was utilised to record self-reported stress levels.Results36 students participated in the study. Following exposure to a stressful medical scenario, paramedic students demonstrated no increase in overall error rate, but demonstrated an increase in three critical driving errors, namely failure to wear a seatbelt (3 baseline v 10 post stress), failing to stop for red lights or stop signs (7 v 35), and losing control of the vehicle (2 v 11). Self-reported stress levels also increased after the clinical scenario, particularly in the area of mental (cognitive) demand.ConclusionParamedics are routinely exposed to acute stress in their everyday work, and this stress could affect their non-clinical performance. The critical errors committed by participants in this study closely matched those considered to be contributory factors in many ambulance collisions. These results stimulate the need for further research into the effects of stress on non-clinical performance in general, and highlight the potential need to consider additional driver training and stress management education in order to mitigate the frequency and severity of driving errors.Key pointsParamedics are exposed to stressful clinical scenarios during the course of their workMany critical and serious clinical calls require transport to hospitalAmbulance crashes occur regularly and pose a significant risk to the safety and wellbeing of both patients and paramedicsThis simulated clinical scenario followed by a simulated driving scenario has highlighted that stress appears to affect driving abilities in paramedic studentsThe findings of this study, although conducted in paramedic students in simulated environments, highlight the need to further investigate the effects of stress on driving abilities among paramedics

Driving Simulator System to Evaluate Driver’s Workload Using ADAS in Different Driving Contexts

2017 ◽  
Author(s):  
Giandomenico Caruso ◽  
Daniele Ruscio ◽  
Dedy Ariansyah ◽  
Monica Bordegoni
Keyword(s):  
Driving Simulator ◽  
Driving Simulation ◽  
Human Cognition ◽  
Driving Safety ◽  
Physiological Data ◽  
Driver Assistance Systems ◽  
Safe Driving ◽  
Dangerous Driving ◽  
Vehicle Technology ◽  
Physiological Sensors

The advancement of in-vehicle technology for driving safety has considerably improved. Current Advanced Driver-Assistance Systems (ADAS) make road safer by alerting the driver, through visual, auditory, and haptic signals about dangerous driving situations, and consequently, preventing possible collisions. However, in some circumstances the driver can fail to properly respond to the alert since human cognition systems can be influenced by the driving context. Driving simulation can help evaluating this aspect since it is possible to reproduce different ADAS in safe driving conditions. However, driving simulation alone does not provide information about how the change in driver’s workload affects the interaction of the driver with ADAS. This paper presents a driving simulator system integrating physiological sensors that acquire heart’s activity, blood volume pulse, respiration rate, and skin conductance parameters. Through a specific processing of these measurements, it is possible to measure different cognitive processes that contribute to the change of driver’s workload while using ADAS, in different driving contexts. The preliminary studies conducted in this research show the effectiveness of this system and provide guidelines for the future acquisition and the treatment of the physiological data to assess ADAS workload.

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