Detecting stress during real-world driving tasks using physiological sensors

By Jennifer A. Healey, Rosalind W. Picard. IEEE transactions on intelligent transportation systems (Print), 2005

2,136 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cardiology and Cardiovascular Medicine, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/0a69f74ca6dfcae8509e62725fd5c0e6999a81ef

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In Biomedical Engineering

In Cardiology and Cardiovascular Medicine

In Experimental and Cognitive Psychology

Citations in the corpus

Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study (2019, methodology): “Most of the studies used DriveDB database [39].”
Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables (2006, methodology): “Our development adds to the progress made by groups such as the MIT Affective Computing research group who have developed a real-world driving stress detection system via recording physiological signals (EKG, EMG, GSR and Respiration), achieving an overall accuracy of up to 97% [ 15 ].”
Empirically building and evaluating a probabilistic model of user affect (2009, background): “In contrast, most work on affect recognition has focused on detecting one specific emotion (e.g., Kapoor and Picard 2005, Healey and Picard 2005), lower–level affective measures such as affective valence and arousal (e.g., Prendinger et al. 2005, Litman and Forbes-Riley 2004) or overall emotional…”
Online Driver Distraction Detection Using Long Short-Term Memory (2011, background): “A considerable number of studies concentrate on the detection and modeling of fatigue or stress as important causes for inattention (e.g., [15]–[ 18 ]).”
cStress: Towards a Gold Standard for Continuous Stress Assessment in the Mobile Environment (2015, background): “While there are other physiological manifestations of stress, such as changes in skin conductivity, skin temperature, and blood-pressure, ECG and respiration are the primary ones [17, 20, 21, 40].”
Continuous inference of psychological stress from sensory measurements collected in the natural environment (2011, methodology): “Several attempts at measuring stress or emotion physiologically exist in the literature [20, 31, 26, 41, 25, 27, 36, 9, 21], but these measurement tools are not suitable for use in natural environments.”
Review on Psychological Stress Detection Using Biosignals (2019, methodology): “A bipolar montage is typically employed with electrodes placed on the trapezius muscle (occipital bone of the upper thoracic vertebrae) [150, 151] and forehead muscles [152].”
Estimating driving behavior by a smartphone (2012, background): “Optimal threshold for the distance between the present and candidate neighbors are empirically determined and is set at 0.05.”
A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques (2021, methodology): “A dataset was available on the PHYSIONET website (http://www.physionet.org/) which was created by Jennifer Healey and Rosalind Picard [51], wherein they used four sensors namely electrocardiogram (EKG), EMG, skin conductivity, and respiration (through chest cavity expansion) for real-time…”
A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances (2022, methodology): “(DSdRD) [7] is used to determine relative stress levels in drivers.”
Physiological Signals-based Emotion Recognition via High-order Correlation Learning (2019, methodology): “Reference [14] utilized electrocardiogram, electromyogram, and skin conductance collected from 24 drives which lasted for at least 50 minutes for analysis and prediction of driver stress and argued that the relationship between metrics of skin conductivity and heart rate and the stress level of…”
Discriminating Stress From Cognitive Load Using a Wearable EDA Device (2010, methodology): “” Some of them [18], [21] also include an emotional com-”
Monitoring stress with a wrist device using context (2017, methodology): “The term ‘‘constrained environments” implies that the method for stress detection is developed using constraints, e.g., stress detection while driving [10], stress detection while sleeping) [11], stress detection in a laboratory [19], etc.”
The impact of a naturalistic hands-free cellular phone task on heart rate and simulated driving performance in two age groups (2011, neutral): “…load is becoming apparent (Collet, Clarion, Morel, Chapon, & Petit, 2009; Collet, Petit, Champely, & Dittmar, 2003; De Warrd, van der Hulst, & Brookhuis, 1999; Haigney, Taylor, & Westerman, 2000; Healey & Picard, 2005; Mehler, Reimer, & Coughlin, 2010; Mehler, Reimer, Coughlin, & Dusek, 2009).”