Remote measurement of cognitive stress via heart rate variability
By Daniel J. McDuff, Sarah Gontarek, Rosalind W. Picard. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
298 citations recorded by the source corpus.
Remote detection of cognitive load has many powerful applications, such as measuring stress in the workplace. Cognitive tasks have an impact on breathing and heart rate variability (HRV). We show that changes in physiological parameters during cognitive stress can be captured remotely (at a distance of 3m) using a digital camera. A study (n=10) was conducted with participants at rest and under cognitive stress. A novel five band digital camera was used to capture videos of the face of the participant. Significantly higher normalized low frequency HRV components and breathing rates were measured in the stress condition when compared to the rest condition. Heart rates were not significantly different between the two conditions. We built a person-independent classifier to predict cognitive stress based on the remotely detected physiological parameters (heart rate, breathing rate and heart rate variability). The accuracy of the model was 85% (35% greater than chance).
Subfields: Biomedical Engineering, Cardiology and Cardiovascular Medicine, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/67767b175523fe79edd12d4fb858d8c1a315241f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Sander Stuijk
- Wenjin Wang
- A. D. den Brinker
- Dimitris Grigoriadis
- Giorgos Giannakakis
- G. de Haan
- Katerina Giannakaki
- Olympia Simantiraki
In Cardiology and Cardiovascular Medicine
- Sander Stuijk
- Wenjin Wang
- A. D. den Brinker
- Dimitris Grigoriadis
- Giorgos Giannakakis
- G. de Haan
- Katerina Giannakaki
- Olympia Simantiraki
In Experimental and Cognitive Psychology
- Dimitris Grigoriadis
- Giorgos Giannakakis
- Katerina Giannakaki
- Olympia Simantiraki
- Manolis Tsiknakis
- Alexandros Roniotis
Citations in the corpus
- Review on Psychological Stress Detection Using Biosignals (2019, methodology): “McDuff (2014) [165] 10 subjects 7/3 18-30 Mental Arithmetic Task”
- Algorithmic Principles of Remote PPG (2017, background): “A better understanding of the core rPPG methods could benefit many systems/applications for video health monitoring, such as the monitoring of heart-rate [7]– [11], respiration [8], SpO2 [8], [12], blood pressure [13], neonates [14], [15], and the detection of atrial fibrillation [16] and mental str”