Sensitivity of Physiological Measures for Detecting Systematic Variations in Cognitive Demand From a Working Memory Task

Mehler, Bruce; Reimer, Bryan; Coughlin, Joseph F.

doi:10.1177/0018720812442086

Cited by 223 publications

(221 citation statements)

References 35 publications

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“…Physiological measures have been shown to be sensitive to subtle increases in demand prior to overt breakdowns in driving performance are observed (Mehler, Reimer, Coughlin, & Dusek, 2009). In contrast to earlier work where demands exceeded a driver's capability or willingness to engage in a secondary activity (Engström et al 2005), heart rate and skin conductance have been shown to scale relatively linearly with an increase in cognitive demand from an auditory presentation -verbal response working memory task (n-back) (Mehler, Reimer & Coughlin, 2012). In essence, the three levels of the n-back task create a three stage ruler, e.g.…”

Section: Introductionmentioning

confidence: 93%

“…The interface was engaged using a "push-to-talk" button on the steering wheel. The vehicle was instrumented for time synchronized recording of vehicle information from the controller area network (CAN) bus, a MEDAC System/3 physiology monitoring unit, FaceLAB® 5.0 eye tracking, cameras for capturing driver behavior and vehicle surroundings, and GPS tracking (see Mehler, Reimer and Coughlin (2012) for details on physiological recording). Subjective workload ratings were obtained using a single global rating per task on a scale consisting of 21 equally spaced dots oriented horizontally along a 10cm line with the numbers 0 through 10 equally spaced below the dots and end points labeled "Low" and "High" on the left and right respectively.…”

Section: Apparatusmentioning

confidence: 99%

“…Research suggests that physiological indices of workload reflect an individual's investment of cognitive resources corresponding to task demand (Brookhuis & de Waard, 1993;Lenneman & Backs, 2009;Mehler, Reimer, Coughlin, & Dusek, 2009;Mehler, Reimer & Coughlin, 2012;Wilson, 2002). Physiological measures have been shown to be sensitive to subtle increases in demand prior to overt breakdowns in driving performance are observed (Mehler, Reimer, Coughlin, & Dusek, 2009).…”

Section: Introductionmentioning

confidence: 99%

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A Preliminary Assessment of Perceived and Objectively Scaled Workload of a Voice-Based Driver Interface

Reimer

Mehler

McAnulty

et al. 2013

Proceedings of the 7th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

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Summary:Interaction with a voice-command interface for radio control, destination entry, MP3 song selection, and phone dialing was assessed along with traditional manual radio control and a multi-level audio-verbal calibration task (nback) on-road in 60 drivers. Subjective workload, compensatory behavior, and physiological indices of cognitive workload suggest that there may be both potential benefits and cautions in the implementation of a representative production level interface.

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Section: Introductionmentioning

confidence: 93%

Section: Apparatusmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Preliminary Assessment of Perceived and Objectively Scaled Workload of a Voice-Based Driver Interface

Reimer

Mehler

McAnulty

et al. 2013

Proceedings of the 7th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

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“…During cognitive pain modulation, for example, the autonomic nervous system responds to noxious stimulation, but also to orientation to a stimulus (24), cognitive load (25,26), and stress (27). As a result, it is difficult to isolate changes in pain-related physiology from those related to cognitive events surrounding pain, including cognitive regulation itself (28,29).…”

Section: Introductionmentioning

confidence: 99%

Cognitive self-regulation influences pain-related physiology

Matthewson¹,

Woo

Reddan³

et al. 2018

Preprint

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Cognitive self-regulation can shape pain experience, but little is known about whether it affects autonomic responses to painful events. In this study, participants (N = 41) deployed a cognitive strategy based on reappraisal and imagination to regulate pain up or down on different trials while skin conductance responses (SCR) and electrocardiogram (ECG) activity were recorded. Using a machine learning approach, we developed stimulus-locked SCR and ECG physiological markers predictive of pain ratings. The markers demonstrated high sensitivity when predicting pain ratings, r = 0.55-0.83. In an independent dataset (N = 84), they discriminated different levels of painful heat with 74-93% accuracy and showed some specificity relative to discriminating levels of vicarious pain (50-71% accuracy; chance is 50%). Cognitive self-regulation increased and decreased both pain ratings and physiology in accordance with regulatory goals. These findings suggest that self-regulation can impact autonomic nervous system responses to painful stimuli and provide painselective autonomic profiles for future studies.Keywords: pain, self-regulation, autonomic nervous system, SCR, ECGAll rights reserved. No reuse allowed without permission. was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint (which . http://dx.doi.org/10.1101/361519 doi: bioRxiv preprint first posted online Jul. 4, 2018; SELF-REGULATION AND PAIN PHYSIOLOGY 3 Author SummaryIt is well known that cognitive self-regulation can modulate pain perception in humans, yet its physiological consequences are difficult to quantify, as the pain-and task-related physiological responses are intricately intertwined. Here, we developed physiological markers predictive of pain report from skin conductance response (SCR) and electrocardiogram (ECG) data collected from 41 participants while they experienced painful thermal stimulations without regulating their pain. These markers were validated on an independent dataset, and then tested for effects of reappraisal-based cognitive selfregulation. When participants were instructed to use this strategy to increase the amount of pain they experienced, expression of the pain-predictive physiological markers increased, and when participants were instructed to reduce the amount of pain they felt, expression of the physiological markers decreased. These results demonstrate that cognitive pain regulation using a conscious, reappraisal-based strategy not only impacts the way participants report pain, but also the way their autonomic physiology responds to pain.All rights reserved. No reuse allowed without permission.was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

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“…As discussed in Mehler et al (2012), the pacing of this task may have a relationship to effective workload. In previous research, a fixed inter-stimulus interval of 2.25 seconds was employed.…”

Section: Introductionmentioning

confidence: 99%

An Initial Assessment of the Significance of Task Pacing on Self-Report and Physiological Measures of Workload While Driving

Mehler

2013

Proceedings of the 7th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

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Summary:In block A of a simulator study, a sample of 38 drivers showed a stepwise increase in heart rate and skin conductance level (SCL) from single task driving and across 3 levels of an auditory presentation -verbal response dual task (n-back), replicating findings from on-road research. Subjective ratings showed a similar stepwise increase, establishing concurrent validity of the physiological indices as measures of workload. In block B, varying the inter-stimulus interval in the intermediate 1-back level of the task resulted in a pattern across self-report workload ratings, heart rate, and SCL suggesting that task pacing may influence effective workload. Further consideration of the impact of task pacing in auditoryverbal in-vehicle applications is indicated.

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Sensitivity of Physiological Measures for Detecting Systematic Variations in Cognitive Demand From a Working Memory Task

Cited by 223 publications

References 35 publications

A Preliminary Assessment of Perceived and Objectively Scaled Workload of a Voice-Based Driver Interface

A Preliminary Assessment of Perceived and Objectively Scaled Workload of a Voice-Based Driver Interface

Cognitive self-regulation influences pain-related physiology

An Initial Assessment of the Significance of Task Pacing on Self-Report and Physiological Measures of Workload While Driving

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