Physiological Methods and Measurements in Driving Simulation

Evaluation of physiological responses to mental workload in n-back and arithmetic tasks

A sample of 33 experiments was extracted from the Web-of-Science database over a 5-year period (2016–2020) that used physiological measures to measure intrinsic cognitive load. Only studies that required participants to solve tasks of varying complexities using a within-subjects design were included. The sample identified a number of different physiological measures obtained by recording signals from four main body categories (heart and lungs, eyes, skin, and brain), as well as subjective measures. The overall validity of the measures was assessed by examining construct validity and sensitivity. It was found that the vast majority of physiological measures had some level of validity, but varied considerably in sensitivity to detect subtle changes in intrinsic cognitive load. Validity was also influenced by the type of task. Eye-measures were found to be the most sensitive followed by the heart and lungs, skin, and brain. However, subjective measures had the highest levels of validity. It is concluded that a combination of physiological and subjective measures is most effective in detecting changes in intrinsic cognitive load.

Ambulatory assessment methods in psychology and clinical neuroscience are powerful research tools for collecting data outside of the laboratory. These methods encompass physiological, behavioral, and self-report measures obtained while individuals navigate in real-world environments, thereby increasing the ecological validity of experimental approaches. Despite the recent increase in applications of ambulatory physiology, data on the reliability of these measures is still limited. To address this issue, twenty-six healthy participants (N = 15 female, 18-34 years) completed an urban walking route (distance M = 2.2km, ±SD = 0.11; duration M = 30.8min, ±SD = 1.34; temperature M = 18.34° degree Celsius, ±SD = 1.19, Range = 16°-21° degrees Celsius) on two separate testing days, while assessing the effect of metabolic state (sated vs. fasted). GPS-location and ambulatory physiological measures (cardiovascular and electrodermal activity) were continuously recorded. The results showed no significant differences in single physiological measures between fasted and sated states. Bootstrapped test-retest reliabilities of single measures and aggregate scores derived via principal component analysis (PCA) were computed. The first principal component (PC#1) accounted for 39-45% of variance across measures. PC#1 scores demonstrated an acceptable test-retest reliability (r = .60) across testing days, exceeding the reliabilities of most individual measures (heart rate: r = .53, heart rate variability: r = .50, skin conductance level: r = .53, no. of skin conductance responses: r = .28, skin conductance response amplitude: r = .60). Results confirm that ambulatory physiological measures recorded during naturalistic navigation in urban environments exhibit acceptable test-retest reliability, in particular when compound scores across physiological measures are analyzed, a prerequisite for applications in (clinical) psychology and digital health.

Mental workload is reflected in driver behaviour, physiology, eye movements and prefrontal cortex activation

This dissertation advanced the deception field by examining the psychological processes associated with deceptive intent. The main focus forms the intention to deceive and more specifically, whether cues to deception already can be measured during truth telling with the mere intention to lie. In order to test this prediction, we examined truth telling with the intention to lie on a crucial aspect later on and compared this with ‘sincere’ truth telling and lying across four empirical studies. In order to deliver a theoretical as well as practical contribution to the deception field, these studies ranged from controlled to more realistic experiments and varied in interpersonal context as well as stakes for the deceiver. Cues to deception were measured in form of electrodermal activity (EDA), a direct indicator for sympathetic nervous system activity and most frequently used physiological measure in the lie detection context. Across all studies, constant lying evoked higher EDA than constant truth telling. But deceptive accounts, which consists of truth telling with the intention to lie, did not necessarily induce an increase in EDA. Rather, elevated EDA levels during the mere intention to deceive seem to depend highly on the degree of interpersonal contact. Particularly, we could not measure the intention to deceive in situations involving direct face-to-face interaction. However, in situations where the deceiver did not have access to the interviewer’s reactions we did found elevated EDA levels during deceptive intentions. These results may be explained from an impression-management perspective. We propose that deceptive intentions may especially increase cognitive and emotional load when deceivers are deprived from social feedback of the interviewer. In order to measure the intention to deceive, it thus may be beneficial to withhold deceivers from target’s (non)verbal reactions.

Measuring emotional responses to tastes and foods, using both self-reports and also implicit and physiological measurements is gaining attention. Among physiological measurements, skin conductance response (SCR) is one the most commonly used indicators of emotional activation but it has been rarely applied to taste and other oral stimuli and its interpretation is not yet clear. Furthermore, the effect of individual differences in SCR to tastes has been rarely taken into account. To address these issues, SCR to bitter, astringent, and sweet samples presented both at weak/moderate and moderate/strong intensity was recorded while eighty Italians, selected based on PROP (6-n-propylthiouracil) status (only Medium-Tasters), performed an implicit affective test. Samples were presented blind in aqueous solutions monadically in triplicate. Subjects (Ss) were asked to taste a sample, then a neutral face was briefly presented on a screen, and Ss were asked to indicate if they trusted the face (yes/no) and how much (on a 9-point Scale). Data on Ss’ psychological traits (anxiety, sensation seeking, food neophobia, emotional stability) was also collected. Two clusters were identified based individual SCR. These clusters differed in their SCR mainly to strong bitterness, and partially to astringency, while they did not differ for their response to the sweet samples. The High bitter responders were more anxious and neurotic than Low bitter responders. For this cluster higher intensities induced higher SCR, but this was not found in the Low bitter responders cluster that tended to have higher SCR to the least intense samples. No differences in the implicit affective responses to samples were found between clusters. These results indicate that SCR to tastes reflect mainly different sources of arousal, such as novelty/surprisingness, quality and intensity of the stimuli, and this may change at an individual level. This suggests that measurement of SC can contribute to a better understanding of individual differences in taste and oral experience and could provide a link between taste responsiveness and sympathetic nervous system activity.

Robotics holds the potential to streamline the execution of repetitive and dangerous tasks, which are difficult or impossible for a human operator. However, in complex scenarios, such as nuclear waste management or disaster response, full automation often proves unfeasible due to the diverse and intricate nature of tasks, coupled with the unpredictable hazards, and is typically prevented by stringent regulatory frameworks. Consequently, the predominant approach to managing activities in such settings remains human teleoperation. Teleoperation can be demanding, especially in high-stress situations, and involves a complex blend of both cognitive and physical workload. We present an experiment to explore a range of physiological and performance-related metrics for workload assessment during robotic teleoperation. Thirty-five participants performed a teleoperation task, during which we manipulated cognitive and physical workload conditions. We recorded multiple metrics, including brain activity using functional Near-Infrared Spectroscopy, galvanic skin responses, cardiovascular responses, subjective workload ratings, task and robot performance data. Our results suggest that robotic teleoperation performance may be the most robust metric for distinguishing between different levels of workload experienced during teleoperation, with most physiological measures becoming insignificant to distinguish high cognitive workload.

The combination of data visualization and auditory display (e.g., sonification) has been shown to increase accuracy, and reduce perceived difficulty, within 3D navigation tasks. While accuracy within such tasks can be measured in real time, subjective impressions about the difficulty of a task are more elusive to obtain. Prior work utilizing electrophysiology (EEG) has found robust support that cognitive load and working memory can be monitored in real time using EEG data. In this study, we replicated a 3D navigation task (within the context of image-guided surgery) while recording data pertaining to participants' cognitive load through the use of EEG relative alpha-band weighting data. Specifically, 13 subjects navigated a tracked surgical tool to randomly placed 3D virtual locations on a CT cerebral angiography volume while being aided by visual, aural, or both visual and aural feedback. During the study EEG data were captured from the participants, and after the study a NASA TLX questionnaire was filled out by the subjects. In addition to replicating an existing experimental design on auditory display within image-guided neurosurgery, our primary aim sought to determine whether EEG-based markers of cognitive load mirrored subjective ratings of task difficulty RESULTS : Similar to existing literature, our study found evidence consistent with the hypothesis that auditory display can increase the accuracy of navigating to a specified target. We also found significant differences in cognitive working load across different feedback modalities, but none of which supported the experiments hypotheses. Finally, we found mixed results regarding the relationship between real-time measurements of cognitive workload and a posteriori subjective impressions of task difficulty. Although we did not find a significant correlation between the subjective and physiological measurements, differences in cognitive working load were found. As well, our study further supports the use of auditory display in image-guided surgery.

It has become increasingly popular to include dogs as a complement to regular therapy, with the expectation that they offer, among other benefits, pain-relieving effects. Meanwhile, studies covering the topic of painful situations within the field of animal-assisted interventions (AAI) present conflicting results and rarely consider the type and duration of interaction with the dog. Thus, the impact of human-dog interactions on physiological measurements during painful situations is largely unknown. Basic research is needed on the effects of interacting with a dog, using commonly applied immediate physiological measurements in healthy humans during experimental pain induction to fill this gap in the literature. The present study investigated how AAI influences physiological measurements when healthy humans are subjected to experimental heat pain induction. Simultaneously, the study explored how the duration of different types of interaction with a human companion or a dog as well as dog behavior during experimental heat pain induction affected physiological measurements. Fifty-eight healthy participants (14 men, 44 women, age: 18-66 years) were randomly assigned to one of two intervention groups: 1) a dog and a human companion or 2) a human companion only. Both intervention groups underwent two test conditions in a balanced order: an active test condition with their allocated intervention and a control test condition without their allocated intervention. The participants were exposed to a 5-minute heat pain induction trial in both test conditions with a 20-minute break between trials. Heart rate (HR), heart rate variability (HRV) and skin conductance (SC), analyzed as tonic level (SCL) and peak counts (SCR), were continuously recorded. Blood pressure (BP) and salivary cortisol (s-cortisol) were collected as pre- and post-measurements for each test condition. Behavioral interactions between the participant, dog and human companion as well as behavior of the dog were recorded and the influence of the behavioral interactions on each physiological measure was analyzed. Linear Mixed Models were applied. HR was higher for the intervention group with a dog and a human companion compared to a human companion only (p=0.013). Additionally, within-subject comparison showed an increased HR during the active condition compared to the control condition in both intervention groups (dog and human companion: p<0.001 and human companion only: p=0.025). None of the other physiological measurements were influenced by the mere presence of a dog in either the between- nor within-subject comparisons. Within the human companion only group, SCL and SCR were higher during the active condition compared to the control (both p<0.001). The duration of the behavioral interaction between the participant and human companion variously influenced HRV, SBP, s-cortisol and SCL during the active condition in both intervention groups. Further, the duration of the behavioral interactions with the dog and dog behavior variously influenced HR, HRV, s-cortisol and SCL during the active condition in the human companion and the dog intervention group. In conclusion, this study shows that the presence of a dog in addition to a human companion during experimental heat pain induction results in an increased HR compared to the presence of a human companion only. Thus, despite previously reported pain-relieving effects of the presence of a dog, this study suggests that dog presence may also induce a certain level of arousal and further studies are needed to explore the causal mechanisms. Interactions with a dog or a human companion influenced several physiological measurements and it is therefore important to quantify the type and duration of human-animal interaction in AAI-studies.

Slow breathing exercises, associated with meditation and other eastern style modalities like tai chi and hatha yoga, are now increasingly employed in mainstream medicine to reduce stress, attenuate moderate hypertension, and alleviate symptoms of lifestyle-related illnesses. The clinical literature on slow breathing exercises includes studies employing various physiological measurements, including heart rate variability (HRV), galvanic skin response, and changes in skin temperature. HRV has been increasingly used to measure the activity of the autonomic nervous system in various human studies employing healthy and chronically ill subjects. 1. Objective: To understand the effects of slow breathing exercises on heart rate variability as a complementary intervention for stress reduction. 2. Method: Four subjects, through repetitive trials, were instructed to slow down their breathing following a metronome at 10 breaths per minute or 6 breaths per minute or spontaneously relax to slow down their respiratory rate. The ECG, heart rate, and respiratory rate were recorded using a Powerlab set-up (ADI). 3. Key Results: Results showed an increase in amplitude of heart rate variability during these slow breathing exercises, either through the metronome-guided or spontaneous slow-breathing exercises, especially around a breathing frequency of 6 breaths per minute. The increased amplitude of heart rate variability can be seen as a positive sign, a marker for sympathovagal balance. 4. Conclusion: HRV measurements have shown that slow breathing exercises can increase heart rate variability. Future protocols for clinical trials are being projected using the HRV technique and other physiological measurements for studying effects of yoga-based complementary interventions for stress reduction.

Cognitive workload across the spectrum of cognitive impairments: A systematic review of physiological measures

Driving simulation and training is one of the most typical applications of virtual reality (VR). This paper compares a VR based driving simulator to a desktop based one in terms of the level of user-felt presence and induced arousal. In particular, as the right level of arousal is important in learning and training, we focus on whether there is any difference in the level of arousal induced when different amounts of sensory feedback are given. An experiment was conducted in which subjects experienced two different driving simulators, VR-based (high amount of sensory stimulation) and desktop-based (low), under three different driving conditions (nominal/calm driving, driving on the curve, and driving through a collision accident). The level of presence was measured using a questionnaire, and arousal, indirectly through the galvanic skin response (GSR) and heart rate. Assuming that those physiological signals reflected the level of arousal of the user, our experimental results showed that while the level of presence was higher with the VR-based set up, no significant differences were found for arousal between the two system set ups. Arousal was dependent only on the task conditions. For one, this is contrary to several previous works [Meehan et al. 1998][Brogni et al. 2006] that had identified physiological signals (such as heart rate and GSR), as a reliable measure of presence. Even though VR simulators may not generate a differentiated amount of arousal, the training may still be effective for physical/spatial tasks (such as driving) due to other factors such as a large field of view and stereoscopy. However, for training of logical tasks, the cost to benefit ratio of VR based simulators may be too high.

Alprazolam reduces response to loud tones in panic disorder but not in posttraumatic stress disorder

Trust calibration poses a significant challenge in the interaction between drivers and automated vehicles (AVs) in the context of human-automation collaboration. To effectively calibrate trust, it becomes crucial to accurately measure drivers’ trust levels in real time, allowing for timely interventions or adjustments in the automated driving. One viable approach involves employing machine learning models and physiological measures to model the dynamic changes in trust. This study introduces a technique that leverages machine learning models to predict drivers’ real-time dynamic trust in conditional AVs using physiological measurements. We conducted the study in a driving simulator where participants were requested to take over control from automated driving in three conditions that included a control condition, a false alarm condition, and a miss condition. Each condition had eight takeover requests (TORs) in different scenarios. Drivers’ physiological measures were recorded during the experiment, including galvanic skin response (GSR), heart rate (HR) indices, and eye-tracking metrics. Using five machine learning models, we found that eXtreme Gradient Boosting (XGBoost) performed the best and was able to predict drivers’ trust in real time with an f1-score of 89.1% compared to a baseline model of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -nearest neighbor classifier of 84.5%. Our findings provide good implications on how to design an in-vehicle trust monitoring system to calibrate drivers’ trust to facilitate interaction between the driver and the AV in real time.

Background: While advanced driver assistance technologies have the potential to increase safety, there is concern that driver inattention resulting from overreliance on these features may result in crashes. Driver monitoring technologies to assess a driver’s state may be one solution. The purpose of this study was to replicate and extend the research on physiological responses to common driving hazards and examine how these may differ based on driving experience.Methods: Learner and Licensed drivers viewed a Driving Hazard Perception Task while electrodermal activity (EDA) was measured. The task presented 30 Event (hazard develops) and 30 Non-Event (routine driving) videos. A skin conductance response (SCR) score was calculated for each participant based on the percentage of videos that elicited an SCR.Results: Analysis of the SCR score during Event videos revealed a medium effect (d = 0.61) of group differences, whereby Licensed drivers were more likely to have an SCR than Learner drivers. Interaction effects revealed Licensed drivers were more likely to have an SCR earlier in the Event videos compared to the end, and the Learner drivers were more likely to have an SCR earlier in the Non-Event videos compared to the end.Conclusion: Our results support the viability of using SCR during driving videos as a marker of hazard anticipation differing based on experience. The interaction effects may illustrate situational awareness in licensed drivers and deficiencies in sustained vigilance among learner drivers. The findings demand further examination if physiological measures are to be validated as a tool to inform driver potential performance in an increasingly automated driving environment.