Design of flexible polyimide-based serpentine EMG sensor for AI-enabled fatigue detection in construction

Physical fatigue and musculoskeletal disorders are critical health issues for construction workers, stemming from repetitive motions, heavy lifting, and awkward postures. These factors compromise worker well-being, productivity, and safety while increasing the risk of accidents and long-term health...

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Main Authors: Yogesh Gautam, Houtan Jebelli
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Sensing and Bio-Sensing Research
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Online Access:http://www.sciencedirect.com/science/article/pii/S2214180424000953
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author Yogesh Gautam
Houtan Jebelli
author_facet Yogesh Gautam
Houtan Jebelli
author_sort Yogesh Gautam
collection DOAJ
description Physical fatigue and musculoskeletal disorders are critical health issues for construction workers, stemming from repetitive motions, heavy lifting, and awkward postures. These factors compromise worker well-being, productivity, and safety while increasing the risk of accidents and long-term health problems. Recent advancements in wearable health monitoring technology offer potential solutions, but current sensors encounter significant challenges in the dynamic construction environment. These include inadequate skin contact, increased contact impedance, and vulnerability to motion artifacts all of which degrade signal quality and reduce the accuracy of fatigue detection. This paper develops a fractal-based, flexible sensor for enhanced adaptability and accurate fatigue estimation. Finite element analysis compared five space-filling designs, with the serpentine curve exhibiting the highest contact area and lowest strain, making it the preferred choice for fabrication. Evaluations demonstrated significant improvements in signal-to-noise ratio (SNR) and motion artifact reduction, with the newly developed sensor achieving a 37 % to 59 % SNR improvement over commercial electrodes across different muscle groups. The developed flexible sensor was integrated with a fatigue-detecting framework based on a vision transformer model which provided an average accuracy of 87 % for fatigue detection. The developed sensor significantly enhances EMG signal quality and reliability, promising improved health monitoring and safety for construction workers.
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spelling doaj-art-1cfd285256834f88934a9c994541da9a2024-12-09T04:27:30ZengElsevierSensing and Bio-Sensing Research2214-18042024-12-0146100713Design of flexible polyimide-based serpentine EMG sensor for AI-enabled fatigue detection in constructionYogesh Gautam0Houtan Jebelli1Department Civil and Environmental Engineering, University of Illinois Urbana-Campaign, Champaign, IL, United States of AmericaCorresponding author.; Department Civil and Environmental Engineering, University of Illinois Urbana-Campaign, Champaign, IL, United States of AmericaPhysical fatigue and musculoskeletal disorders are critical health issues for construction workers, stemming from repetitive motions, heavy lifting, and awkward postures. These factors compromise worker well-being, productivity, and safety while increasing the risk of accidents and long-term health problems. Recent advancements in wearable health monitoring technology offer potential solutions, but current sensors encounter significant challenges in the dynamic construction environment. These include inadequate skin contact, increased contact impedance, and vulnerability to motion artifacts all of which degrade signal quality and reduce the accuracy of fatigue detection. This paper develops a fractal-based, flexible sensor for enhanced adaptability and accurate fatigue estimation. Finite element analysis compared five space-filling designs, with the serpentine curve exhibiting the highest contact area and lowest strain, making it the preferred choice for fabrication. Evaluations demonstrated significant improvements in signal-to-noise ratio (SNR) and motion artifact reduction, with the newly developed sensor achieving a 37 % to 59 % SNR improvement over commercial electrodes across different muscle groups. The developed flexible sensor was integrated with a fatigue-detecting framework based on a vision transformer model which provided an average accuracy of 87 % for fatigue detection. The developed sensor significantly enhances EMG signal quality and reliability, promising improved health monitoring and safety for construction workers.http://www.sciencedirect.com/science/article/pii/S2214180424000953Flexible sensorFatigue detectionVision transformerMotion artifactElectromyography (EMG)
spellingShingle Yogesh Gautam
Houtan Jebelli
Design of flexible polyimide-based serpentine EMG sensor for AI-enabled fatigue detection in construction
Sensing and Bio-Sensing Research
Flexible sensor
Fatigue detection
Vision transformer
Motion artifact
Electromyography (EMG)
title Design of flexible polyimide-based serpentine EMG sensor for AI-enabled fatigue detection in construction
title_full Design of flexible polyimide-based serpentine EMG sensor for AI-enabled fatigue detection in construction
title_fullStr Design of flexible polyimide-based serpentine EMG sensor for AI-enabled fatigue detection in construction
title_full_unstemmed Design of flexible polyimide-based serpentine EMG sensor for AI-enabled fatigue detection in construction
title_short Design of flexible polyimide-based serpentine EMG sensor for AI-enabled fatigue detection in construction
title_sort design of flexible polyimide based serpentine emg sensor for ai enabled fatigue detection in construction
topic Flexible sensor
Fatigue detection
Vision transformer
Motion artifact
Electromyography (EMG)
url http://www.sciencedirect.com/science/article/pii/S2214180424000953
work_keys_str_mv AT yogeshgautam designofflexiblepolyimidebasedserpentineemgsensorforaienabledfatiguedetectioninconstruction
AT houtanjebelli designofflexiblepolyimidebasedserpentineemgsensorforaienabledfatiguedetectioninconstruction