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, ECG, EMG, respiration and skin conductance sensors were used to measure the 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 subjects self report questionnaires. In total, 545 one minute segments were classified. A linear discriminant function was used to rank each feature individually based on the recognition performance, and a sequential forward floating selection algorithm was used to find an optimal set of features for recognizing patterns of driver stress. Using multiple features improved performance significantly over the best single feature performance.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    SmartCar: detecting driver stress


    Contributors:
    Healey, J. (author) / Picard, R. (author)


    Publication date :

    2000


    Size :

    4 Seiten, 9 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Smartcar

    Appl,J. / Oswald,O. / Prozessberatung und IT Beratung Mieschke,Hoffmann u.Partner,MHP,Ludwigsburg,DE | Automotive engineering | 2013


    Graphical Models for Driver Behavior Recognition in a SmartCar

    Oliver, N. / Pentland, A. P. / IEEE | British Library Conference Proceedings | 2000


    SMaRTCaR: An integrated smartphone-based platform to support traffic management applications

    Campolo, Claudia / Iera, Antonio / Molinaro, Antonella et al. | IEEE | 2012


    DEVICE AND METHOD FOR DETECTING STRESS LEVEL OF DRIVER

    KIM GYUN HA / KIM EUNG HWAN / SEO SANG KYUNG et al. | European Patent Office | 2022

    Free access

    Device and method for detecting stress level of driver

    KIM GYUN HA / KIM EUNG HWAN / SEO SANG KYUNG et al. | European Patent Office | 2024

    Free access