Contactless Vital-Sign Monitoring of Construction Machinery Operators Using Millimeter-Wave Technology

Accidents related to construction machinery primarily result from operators engaging in unsafe behavior. Continuous monitoring of the vital signs of heavy machinery operators is necessary to enable timely intervention in the event of abnormal physical or mental states, thereby reducing the risk of accidents. Researchers have proposed methods for monitoring vital signs in heavy machinery operators through wearable devices. However, sensor-based wearable systems, such as surface electromyography, are often invasive or necessitate the affixing of numerous sensors to the workers’ bodies, which may result in discomfort for the workers and potential instability within the system, thereby constraining their utilization on construction sites. To mitigate these limitations, this study proposes a contactless monitoring method based on millimeter-wave (MMW) radar and tests the accuracy and robustness of the method. Ten participants of various figures were recruited for sensing and robustness tests within a simulated heavy machinery cabin. The experimental results demonstrate that MMW radar can accurately monitor the respiration rate and heart rate of heavy machinery operators within a range of ±45° horizontally and ±30° vertically and unaffected by illumination and attire conditions. The proposed method has great potential for enabling continuous monitoring of vital signs in heavy machinery operators in harsh construction environments. Further analysis of the vital sign information obtained from MMW radar can be involved to enable future research, such as fatigue monitoring and attention assessment.

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Publication Details

Journal
Journal of Construction Engineering and Management
Published
2024-10-16
DOI
https://doi.org/10.1061/jcemd4.coeng-14834
Citations
5
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.92
Controls
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article

Contactless Vital-Sign Monitoring of Construction Machinery Operators Using Millimeter-Wave Technology

Heng Li, Wei Ren, Shuai Han, Jia Wang et al.
5 citations
Journal of Construction Engineering and Management
Non-Invasive Vital Sign Monitoring
0.92
article

Contactless Vital-Sign Monitoring of Construction Machinery Operators Using Millimeter-Wave Technology

Heng Li, Wei Ren, Shuai Han, Jia Wang, Guangbin Wang
article en
5 citations

Abstract

Accidents related to construction machinery primarily result from operators engaging in unsafe behavior. Continuous monitoring of the vital signs of heavy machinery operators is necessary to enable timely intervention in the event of abnormal physical or mental states, thereby reducing the risk of accidents. Researchers have proposed methods for monitoring vital signs in heavy machinery operators through wearable devices. However, sensor-based wearable systems, such as surface electromyography, are often invasive or necessitate the affixing of numerous sensors to the workers’ bodies, which may result in discomfort for the workers and potential instability within the system, thereby constraining their utilization on construction sites. To mitigate these limitations, this study proposes a contactless monitoring method based on millimeter-wave (MMW) radar and tests the accuracy and robustness of the method. Ten participants of various figures were recruited for sensing and robustness tests within a simulated heavy machinery cabin. The experimental results demonstrate that MMW radar can accurately monitor the respiration rate and heart rate of heavy machinery operators within a range of ±45° horizontally and ±30° vertically and unaffected by illumination and attire conditions. The proposed method has great potential for enabling continuous monitoring of vital signs in heavy machinery operators in harsh construction environments. Further analysis of the vital sign information obtained from MMW radar can be involved to enable future research, such as fatigue monitoring and attention assessment.

Journal of Construction Engineering and ManagementVol. 151(1)
Tongji University (CN), Hong Kong Polytechnic University (HK)
Openalex Percentile: Top 28%
Non-Invasive Vital Sign Monitoring
0.92
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