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A new approach to detect the physical fatigue utilizing heart rate signals
journal contribution
posted on 2020-01-01, 00:00 authored by Mohammad Tayarani Darbandy, Mozhdeh Rostamnezhad, Sadiq Hussain, Abbas KhosraviAbbas Khosravi, Saeid Nahavandi, Zahra Alizadeh SaniOne 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.
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Journal
Research in cardiovascular medicineVolume
9Issue
1Pagination
23 - 27Publisher
Wolters KluwerLocation
Philadelphia, Pa.Publisher DOI
Link to full text
ISSN
2251-9572eISSN
2251-9580Language
EnglishPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2020, Research in Cardiovascular MedicineUsage metrics
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