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Respiration and Heart Rate Modulation Due to Competing Cognitive Tasks While Driving
Antonio R Hidalgo-Muñoz1, Adolphe J Béquet1, Mathis Astier-Juvenon1
1Univ Lyon, IFSTTAR, TS2, LESCOT, Lyon, France.
Frontiers in Human Neuroscience
|January 29, 2019
Summary
Analyzing breathing rate (BR) and its spectral features offers a promising alternative to heart rate (HR) for monitoring driver cognitive workload (CW). This research shows BR variations can effectively indicate CW changes, crucial for autonomous vehicle safety.
Area of Science:
- Human-Computer Interaction
- Cognitive Science
- Automotive Engineering
Background:
- Operator monitoring benefits from multimodal physiological signals for accurate mental state diagnosis.
- Heart rate (HR) is commonly used for cognitive workload (CW) assessment, while respiratory signals are underutilized.
Purpose of the Study:
- To investigate the utility of respiratory signals in evaluating driver activity and cognitive workload (CW) variations.
- To compare the effectiveness of respiratory parameters against heart rate (HR) in driver mental state monitoring.
Main Methods:
- Eighteen subjects performed single and competing cognitive tasks while driving in a simulator.
- Analysis of heart rate (HR) and breathing rate (BR) signals, including spectral features of respiration.
Main Results:
- Both HR and BR increase with driving and are sensitive to CW.
- HR is influenced by driving activity and CW, whereas BR variations are more indicative of CW changes when driving demands are lower.
- Spectral features of respiratory signals can detect high CW episodes, similar to HR variability indices.
Conclusions:
- Respiration analysis provides valuable insights into driver cognitive workload, complementing or potentially replacing HR monitoring.
- Respiratory signals offer a viable alternative for monitoring driver mental state in autonomous vehicles, aiding in predicting available cognitive resources for takeover scenarios.
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