Volume 8, Issue 4 (12-2018)
J Health Saf Work 2018, 8(4): 333-344 |
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Jafari M, Hassanzadeh-Rangi N, Khosravi Y, Khodakarim S. Mental workload assessment among train drivers using ECG-related indices. J Health Saf Work 2018; 8 (4) :333-344
URL: http://jhsw.tums.ac.ir/article-1-5957-en.html
URL: http://jhsw.tums.ac.ir/article-1-5957-en.html
1- Professor, Department of Occupational Health Engineering, Environmental and Occupational Hazards Control Research Center, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2- M.Sc., Department of Occupational Health Engineering, Student Research Committee, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran , narminhassanzadeh@sbmu.ac.ir
3- Assistant Professor, Department of Occupational Health and Safety, School of Health, Alborz University of Medical Sciences, Karaj, Iran
4- Assistant Professor, Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2- M.Sc., Department of Occupational Health Engineering, Student Research Committee, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran , narminhassanzadeh@sbmu.ac.ir
3- Assistant Professor, Department of Occupational Health and Safety, School of Health, Alborz University of Medical Sciences, Karaj, Iran
4- Assistant Professor, Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Abstract: (3611 Views)
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.
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.
Type of Study: Research |
Received: 2018/12/7 | Accepted: 2018/12/7 | Published: 2018/12/7
Received: 2018/12/7 | Accepted: 2018/12/7 | Published: 2018/12/7
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