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SmartCar: Detecting Driver Stress

Published: 03 September 2000 Publication History

Abstract

Smart physiological sensors embedded in an automobile afford a novel opportunity to capture naturally occurring episodes of driver stress. In a series of ten ninety minute drives on public roads and highways, electrocardiogram, electromyogram, respiration and skin conductance sensors were used to measure autonomic nervous system activation. The signals were digitized in real time and stored on the SmartCar's Pentium class computer. Each drive followed a pre-specified route through fifteen different events, from which four stress level categories were created according to the results of the subject's self-report questionnaires. In total, 545 one-minute segments were classified. A linear discriminant function was used to rank each feature individually based on recognition performance and a sequential forward floating selection (SFFS) algorithm was used to find an optimal set of features for recognizing patterns of driver stress (88.6%). Using multiple features improved performance significantly over the best single feature performance (62.2%).

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  • (2019)BreathListenerProceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3307334.3326074(54-66)Online publication date: 12-Jun-2019
  • (2018)Intelligent smart home energy efficiency model using artificial TensorFlow engineHuman-centric Computing and Information Sciences10.1186/s13673-018-0132-y8:1(1-18)Online publication date: 1-Dec-2018
  • (2018)Mental Stress Evaluation of Car Driver in Different Road Complexity Using Heart Rate Variability (HRV) AnalysisProceedings of the 5th International Conference on Bioinformatics Research and Applications10.1145/3309129.3309145(90-94)Online publication date: 27-Dec-2018
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Published In

cover image Guide Proceedings
ICPR '00: Proceedings of the International Conference on Pattern Recognition - Volume 4
September 2000

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IEEE Computer Society

United States

Publication History

Published: 03 September 2000

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Cited By

View all
  • (2019)BreathListenerProceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3307334.3326074(54-66)Online publication date: 12-Jun-2019
  • (2018)Intelligent smart home energy efficiency model using artificial TensorFlow engineHuman-centric Computing and Information Sciences10.1186/s13673-018-0132-y8:1(1-18)Online publication date: 1-Dec-2018
  • (2018)Mental Stress Evaluation of Car Driver in Different Road Complexity Using Heart Rate Variability (HRV) AnalysisProceedings of the 5th International Conference on Bioinformatics Research and Applications10.1145/3309129.3309145(90-94)Online publication date: 27-Dec-2018
  • (2018)Mining spatio-temporal data for computing driver stress and observing its effects on driving behaviorProceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/3274895.3274941(452-455)Online publication date: 6-Nov-2018
  • (2018)Touch SenseProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32142902:2(1-18)Online publication date: 5-Jul-2018
  • (2018)A Critical Review of Proactive Detection of Driver Stress Levels Based on Multimodal MeasurementsACM Computing Surveys10.1145/318658551:5(1-35)Online publication date: 4-Sep-2018
  • (2018)Non-Invasive Measurement of Cognitive Load and Stress Based on the Reflected Stress-Induced Vascular Response IndexACM Transactions on Applied Perception10.1145/318566515:3(1-17)Online publication date: 24-Jul-2018
  • (2018)Multimodal behavioral and physiological signals as indicators of cognitive loadThe Handbook of Multimodal-Multisensor Interfaces10.1145/3107990.3108002(287-329)Online publication date: 1-Oct-2018
  • (2018)Towards pervasive geospatial affect perceptionGeoinformatica10.1007/s10707-017-0294-122:1(143-169)Online publication date: 1-Jan-2018
  • (2017)DiVAProceedings of the 16th International Conference on Mobile and Ubiquitous Multimedia10.1145/3152832.3152836(273-278)Online publication date: 26-Nov-2017
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