Electrocardiographic features for the measurement of drivers' mental workload. (May 2017)

• Record Type: Journal Article
• Authors: Heine, Tobias; Lenis, Gustavo; Reichensperger, Patrick; Beran, Tobias; Doessel, Olaf; Deml, Barbara
• Is Part Of: Applied ergonomics. Volume 61(2017)
• Page Start: 31
• Page End: 43
• Publication Date: 2017-05
• Subjects: Mental workload -- Driving -- Electrocardiogram -- Feature comparison -- Heart rate variability -- Wave morphology; Human engineering -- Periodicals; 620.82
• DOI: 10.1016/j.apergo.2016.12.015
• Languages: English
• ISSNs: 0003-6870

Abstract

Abstract: This study examines the effect of mental workload on the electrocardiogram (ECG) of participants driving the Lane Change Task (LCT). Different levels of mental workload were induced by a secondary task (n-back task) with three levels of difficulty. Subjective data showed a significant increase of the experienced workload over all three levels. An exploratory approach was chosen to extract a large number of rhythmical and morphological features from the ECG signal thereby identifying those which differentiated best between the levels of mental workload. No single rhythmical or morphological feature was able to differentiate between all three levels. A group of parameters were extracted which were at least able to discriminate between two levels. For future research, a combination of features is recommended to achieve best diagnosticity for different levels of mental workload. Highlights: The effect of drivers' mental workload on the electrocardiogram was examined. Rhythmical and morphological features were extracted from the electrocardiogram. Features were compared with regard to diagnosticity of mental workload. Mental workload was associated with a higher heart rate and a lower variability.