Research on the fatigue of construction workers by heart rate monitoring

XU Ming-wei; JIN Long-zhe; ZHANG Lin; YU Lu; LIU Jian-guo; TIAN Xing-hua

doi:10.13374/j.issn2095-9389.2018.06.015

Volume 40 Issue 6

Jun. 2018

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of Engineering > 2018 > 40(6): 760-765

XU Ming-wei, JIN Long-zhe, ZHANG Lin, YU Lu, LIU Jian-guo, TIAN Xing-hua. Research on the fatigue of construction workers by heart rate monitoring[J]. Chinese Journal of Engineering, 2018, 40(6): 760-765. doi: 10.13374/j.issn2095-9389.2018.06.015

Citation:

XU Ming-wei, JIN Long-zhe, ZHANG Lin, YU Lu, LIU Jian-guo, TIAN Xing-hua. Research on the fatigue of construction workers by heart rate monitoring[J]. Chinese Journal of Engineering, 2018, 40(6): 760-765. doi: 10.13374/j.issn2095-9389.2018.06.015

Citation:

PDF( 417 KB)

Research on the fatigue of construction workers by heart rate monitoring

doi: 10.13374/j.issn2095-9389.2018.06.015

1) School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
2) State Administration of Work Safety Training Center, Beijing 100010, China

Received Date: 2017-11-27

Abstract

Abstract

The safety situation in the construction industry across the world has been complicated for a long time, and the high incidence of accidents poses great challenges to this situation. Research on occupational safety and health indicates that people are prone to misconduct or unsafe behavior when they are tired. A large number of accident analyses show that fatigue is one of the most important reasons for accidents. When the human body enters into a fatigue state, the physiological parameters change accordingly. The aim of this study was to investigate the effects of heart rate and heart rate variability (HRV) on physiological fatigue in a sustained bricklaying task. A mathematical model was proposed for evaluating physiological fatigue. Five male healthy participants were selected to imitate construction by engaging in bricklaying on an 86 cm platform. HRV data were collected every 30 min during the sustained task, and heart rate was measured every minute. Analysis of variance, one-sample t-test, and nonlinear curve fitting were adopted in this study. Physiological fatigue shows a significant change with heart rate fluctuation (significant level α=0.05, P<0.05). With an increase in physiological fatigue, the heart rate needs a longer time to decrease to the normal level. No significant difference is observed in HRV between the subjects (α=0.05, P>0.05). The trend of the physiological fatigue curve follows a cubic function. The nonlinear curve fitting results (R²=0.8892) show that the development trend of physiological fatigue shows an "S" trend, which can be divided into the following three stages:fatigue adjustment period, fatigue stability period, and fatigue instability period. Proper rest in the fatigue failure period (In this experiment, it was about 90 min.) can slow or delay physiological fatigue.
- construction worker,
- physiological fatigue,
- heart rate variability,
- relative heart rate,
- fatigue monitoring

FullText(HTML)

References(15)

References

[1]	Fang D P, Jiang Z M, Zhang M Z, et al. An experimental method to study the effect of fatigue on construction workers'safety performance. Saf Sci, 2015, 73:80
[2]	Bauer C M, Rast F M, Ernst M J, et al. The effect of muscle fatigue and low back pain on lumbar movement variability and complexity. J Electromyogr Kinesiol, 2017, 33:94
[3]	Monjo F, Forestier N. The postural control can be optimized by the first movement initiation condition encountered when submitted to muscle fatigue. Human Move Sci, 2017, 54:1
[4]	De Vries J, Michielsen H J, Van Heck G L. Assessment of fatigue among working people:a comparison of six questionnaires. Occup Environ Med, 2003, 60:i10
[5]	Holmström E B, Lindell J, Moritz U. Low back and neck/shoulder pain in construction workers:occupational workload and psychosocial risk factors. Part 2:Relationship to neck and shoulder pain. Spine, 1992, 17(6):672
[6]	Godwin A, Eger T, Salmoni A, et al. Postural implications of obtaining line-of-sight for seated operators of underground mining load-haul-dump vehicles. Ergonomics, 2007, 50(2):192
[7]	Lucini D, Marchetti I, Spataro A, et al. Heart rate variability to monitor performance in elite athletes:criticalities and avoidable pitfalls. Int J Cardiol, 2017, 240:307
[8]	Nath N D, Akhavian R, Behzadan A H. Ergonomic analysis of construction worker's body postures using wearable mobile sensors. Appl Ergon, 2017, 62:107
[9]	Harcombe H, Herbison G P, McBride D, et al. Musculoskeletal disorders among nurses compared with two other occupational groups. Occup Med, 2014, 64(8):601
[11]	Tak S W, Buchholz B, Punnett L, et al. Physical ergonomic hazards in highway tunnel construction:overview from the construction occupational health program. Appl Ergon, 2011, 42(5):665
[13]	Nadadur G, Raschke U, Parkinson M B. A quantile-based anthropometry synthesis technique for global user populations. Int J Ind Ergon, 2016, 53:167
[14]	Giles D, Draper N, Neil W. Validity of the polar V800 heart rate monitor to measure RR intervals at rest. Eur J Appl Physiol, 2016, 116(3):563
[16]	Kleiger R E, Stein P K, Bigger J T. Heart rate variability:measurement and clinical utility. Ann Noninvasive Electrocardiol, 2005, 10(1):88
[17]	Lee W, Seto E, Lin K Y, et al. An evaluation of wearable sensors and their placements for analyzing construction worker's trunk posture in laboratory conditions. Appl Ergon, 2017, 65:424
[18]	Thayer J F, Yamamoto S S, Brosschot J F. The relationship of autonomic imbalance, heart rate variability and cardiovascular disease risk factors. Int J Cardiol, 2010, 141(2):122