Heine Tobias, Lenis Gustavo, Reichensperger Patrick, Beran Tobias, Doessel Olaf, Deml Barbara
Institute of Human and Industrial Engineering (ifab), Karlsruhe Institute of Technology (KIT), Kaiserstrasse 12, 76131 Karlsruhe, Germany.
Institute of Biomedical Engineering (IBT), Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany.
Appl Ergon. 2017 May;61:31-43. doi: 10.1016/j.apergo.2016.12.015. Epub 2017 Jan 16.
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.
本研究考察了心理负荷对执行变道任务（LCT）的参与者心电图（ECG）的影响。通过具有三个难度级别的次要任务（n-back任务）诱导出不同水平的心理负荷。主观数据显示，在所有三个级别中，所体验到的负荷均显著增加。采用探索性方法从ECG信号中提取大量节律和形态特征，从而识别出在心理负荷水平之间区分效果最佳的特征。没有单一的节律或形态特征能够区分所有三个级别。提取了一组至少能够区分两个级别的参数。对于未来的研究，建议结合多种特征以实现对不同水平心理负荷的最佳诊断。
