Mental workload assessment among train drivers using ECG-related indices

Autor: Mohammad-Javad Jafari, Narmin Hassanzadeh-Rangi, Yahya Khosravi, Soheila Khodakarim
Jazyk: perština
Rok vydání: 2018
Předmět:
Zdroj: بهداشت و ایمنی کار, Vol 8, Iss 4, Pp 333-344 (2018)
Druh dokumentu: article
ISSN: 2251-807X
2383-2088
Popis: Introduction: Driving a train is one of the high demand job due to high vigilance task requiring the ability to long periods monitor surrounding environment and recognizing signals. The aim of this study was to assess train drivers’ mental workload using heart rate (HR) and heart rate variability (HRV) indices. Material and Method: An experimental design was conducted among 12 well-trained subjects to induce two different levels of mental demands in a metro simulator and to monitor mental workload levels while driving the train. The HR and HRV parameters were recorded and analysis using ECG signals. Result: The HRV parameters including SDNNIX (p-value=0.01), RMSSD (p-value=0.00), %PNN50 (p-value=0.01), SDNN (p-value=0.07) and LF/HF Ratio (p-value=0.04) were significantly reduced in a normal operation task comparing to the abnormal one. Conclusion: The HR and HRV (SDNN, SDNNIX, RMSSD, %PNN50 and LF/HF Ratio) were found to be sensitive to mental workload in metro train driving .It is recommended to include the HRV parameters for mental workload assessment of train drivers.
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