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Detecting Stress During Real-World Driving Tasks Using Physiological Sensors

Healey, Jennifer A.; Picard, Rosalind W.


Keyword(s): driver; stress; traffic; automobile; physiology; sensor; signal; computer; affect; EKG; skin conductivity

Abstract: This paper presents methods for collecting and analyzing physiological data during real world driving tasks to determine a driver's relative stress level. Electrocardiogram, electromyogram, skin conductance and respiration were recorded continuously while drivers followed a set route through open roads in the greater Boston area. Data from twenty-four drives of at least fifty minute duration were collected for analysis. In Analysis I features from five minute intervals of data were used to distinguish three levels of driver stress with an accuracy of over 97% across multiple drivers and driving days. In Analysis II, continuous physiological features were correlated with a continuous metric of observable stressors showing that on a real-time basis metrics of skin conductivity and heart rate were most closely correlated with driver stress level. Such automatically calculated physiological features could be used to help manage non-critical in-vehicle information systems and improve the driving experience. Notes: Copyright IEEE. To be published in IEEE Transactions on Intelligent Transportation Systems

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