Comparison of nine heart rate-based models to predict work metabolism of Forest workers

Abstract

Predicted work metabolism (WM) from 9 heart rate (HR)-based models were compared to measured WM obtained during work in 39 forest workers. Using measured (i.e. raw) HR in these models can overestimate actual WM since the HR increase associated with body heat accumulation is non-metabolic. Hence, accuracy of WM prediction was assessed on all possible combinations of models using raw HR and corrected HR (thermal component removed) and with five different estimates of maximum work capacity (MWC) for the models that require it as an input. The 50 model combinations produced a wide range of WM estimates. Three models using individual calibration produced the lowest RMSE and narrowest LoA with corrected HR (rRMSE ≤13%; LoA [rBias <5% ± 25%]). One of the models that requires neither determination of the thermal component nor individual calibration performed very well (rRMSE = 18%; LoA [rBias = 1% ± 36%]).

Practitioner Summary: These results provide a better understanding of the accuracy of various HR-based work metabolism (WM) estimation models. This information should prove particularly useful to ergonomics professionals wishing to select a method that provides accurate estimation of WM from HR measurements during work in varied thermal environments.

Abbreviations: BMI: body mass index; HR: heart rate (beats per min); HR99: HR value exceeded during 99% of the duration of the HR recording period; HRcorr: heart rate without thermal pulses; HRraw: measured heart rate; HRres: heart rate reserve; HRrest: heart rate at rest; LoA: limits of agreement; Mrest: resting metabolism; MWC: maximum work capacity; RMSE: root mean square error; VO2: oxygen consumption; VO2 max: maximum oxygen consumption; WM: work metabolism

Keywords:

• Work metabolism
• energy expenditure
• heart rate
• methods comparison
• maximum work capacity
• field measurements

Acknowledgements

The authors are grateful to the anonymous reviewers for their insightful and detailed comments. The authors wish to thank Dr. Luc Lebel for his assistance and technical advice regarding forest work operations and Dr. Mario Leone for his technical advice with oxygen consumption measurement with the K4b2. The authors are grateful to the Association des entrepreneurs forestiers du Québec, the Fédération Québécoise des coopératives forestières and the Regroupement des sociétés d'aménagement forestier du Québec for their help in recruiting silvicultural enterprises to participate in this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This project was funded jointly by the Natural Science and Engineering Research Council of Canada (NSERC) and the Ministère des Ressources naturelles et de la Faune du Québec, and the Fonds de recherche du Québec - Nature et technologies.