Author/Authors :
Tayarani Darbandy, Mohammad School of Architecture - Islamic Azad University Taft, Iran , Rostamnezhad, Mozhdeh School of Architecture and Built Environment - Deakin University , Hussain, Sadiq Dibrugarh University, Assam, India , Khosravi, Abbas Institute for Intelligent Systems Research and Innovation - Deakin University, Geelong, Australia , Nahavandi, Saeid Institute for Intelligent Systems Research and Innovation - Deakin University, Geelong, Australia , Alizadeh Sani, Zahra Rajaie Cardiovascular Medical and Research Center - Iran University of Medical Sciences, Tehran, Iran
Abstract :
Aim: One of the most crucial and common occupational hazards in different industries is physical fatigue. Fatigue plays a vast role in all
industries in terms of health, safety, and productivity and is continually ranked among the top‑five health‑related risk factors year after year.
The current study focuses on a novel method to detect workers’ physical fatigue employing heart rate signals. Materials and Methods: First,
domain features are extracted from the heart signals utilizing different entropies and statistical tests. Then, K‑nearest neighbors algorithm
is used to detect the physical fatigue. The experimental results reveal that the proposed method has a good performance to recognize the
physical fatigue. Results: The achieved measures of accuracy, sensitivity, and specificity rates are 78.18%, 60.96%, and 82.15%, respectively,
discretely for fatigue detection. Discussion: Based on the achieved results, it is conceived that monitoring of heart rate signals is an effective
tool to assess the physical fatigue in manufacturing and construction sites since there is a direct relationship between fatigue and heart rate
features. The results presented in this article showed that the proposed method would work well as an effective tool for accurate and real‑time
monitoring of physical fatigue and help to increase workers’ safety and minimize accidents. Conclusion: The results presented in this article
shows that the proposed method would work well as an effective tool for accurate and real‑time monitoring of physical fatigue and helps to
increase workers’ safety and minimize accidents.