@inproceedings{98c18aec90ca40e699165cbc9cdd27f2,
title = "Improving Health Monitoring of Construction Workers Using Physiological Data-Driven Techniques: An Ensemble Learning-Based Framework to Address Distributional Shifts",
abstract = "While researchers have used various off-the-shelf physiological sensors and prevalent machine learning (ML) algorithms to objectively assess construction workers' health status, there remain specific challenges for consistent and accurate health monitoring on the jobsite. The existing physiological-based data-driven frameworks for predicting workers' health status in the field are not robust to the distribution shift of physiological signals and face challenges in stability, reliability, and accuracy. To overcome these issues, this paper proposes using an ensemble learning technique implemented on a support vector machine (SVM) with the Adaptive Boosting (AdaBoost) algorithm to develop a resilient predictive performance of the data-driven framework. To examine the performance of the framework, physiological signals were collected from 10 subjects performing material handling tasks with varying levels of physical fatigue. The proposed framework predicted the physical fatigue level with over 88% accuracy, better than single machine learning classifiers. This study has significant implications for improving the accuracy and stability of physiological-sensing-based health monitoring.",
author = "Amit Ojha and Yizhi Liu and Houtan Jebelli and Hunayu Cheng and Mehdi Kiani",
note = "Publisher Copyright: {\textcopyright} ASCE 2023.All rights reserved.; ASCE International Conference on Computing in Civil Engineering 2023: Resilience, Safety, and Sustainability, i3CE 2023 ; Conference date: 25-06-2023 Through 28-06-2023",
year = "2024",
doi = "10.1061/9780784485248.076",
language = "English (US)",
series = "Computing in Civil Engineering 2023: Resilience, Safety, and Sustainability - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "631--638",
editor = "Yelda Turkan and Joseph Louis and Fernanda Leite and Semiha Ergan",
booktitle = "Computing in Civil Engineering 2023",
address = "United States",
}