A new approach to detect the physical fatigue utilizing heart rate signals

IF 0.2 Q4 CARDIAC & CARDIOVASCULAR SYSTEMS Research in Cardiovascular Medicine Pub Date : 2020-01-01 DOI:10.4103/rcm.rcm_8_20
M. Darbandy, Mozhdeh Rostamnezhad, Sadiq Hussain, A. Khosravi, S. Nahavandi, Z. Sani
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引用次数: 11

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.
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一种利用心率信号检测身体疲劳的新方法
目的:在不同行业中,最重要和最常见的职业危害之一是身体疲劳。疲劳在所有行业的健康、安全和生产力方面都发挥着巨大作用,并年复一年地被列为与健康相关的五大风险因素之一。目前的研究重点是一种利用心率信号检测工人身体疲劳的新方法。材料和方法:首先,利用不同的熵和统计检验从心脏信号中提取领域特征。然后,利用K-近邻算法检测身体疲劳。实验结果表明,该方法具有良好的物理疲劳识别性能。结果:疲劳检测的准确性、敏感性和特异性分别为78.18%、60.96%和82.15%。讨论:根据所获得的结果,认为心率信号监测是评估制造和施工现场身体疲劳的有效工具,因为疲劳与心率特征之间存在直接关系。本文的结果表明,所提出的方法将成为准确、实时监测身体疲劳的有效工具,有助于提高工人的安全性,最大限度地减少事故。结论:本文的结果表明,该方法是一种准确、实时监测身体疲劳的有效工具,有助于提高工人的安全性,最大限度地减少事故。
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来源期刊
Research in Cardiovascular Medicine
Research in Cardiovascular Medicine CARDIAC & CARDIOVASCULAR SYSTEMS-
自引率
0.00%
发文量
13
审稿时长
17 weeks
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