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• W3197307971 endingPage "103920" @default.
• W3197307971 startingPage "103920" @default.
• W3197307971 abstract "Repetitive labor-intensive tasks are common in civil construction projects. Construction workers are prone to getting into musculoskeletal disorders-related injuries while performing such activities. The paper proposes a novel approach to identify the theoretical maximum attainable level of safety, safety frontier, for a given construction task that can be achieved in perfect conditions under good management. The paper outlines the method and the framework components and demonstrates them through an actual construction-lab-based case study. The case study includes computation of safety frontier for lifting and setting down tasks. For this, the paper proposes to use a depth sensor camera (Kinect) for workers' postural data collection while performing the task. With the postural data as an input feature, all the unique actions are identified using a random forest classifier model for each movement frame. Also, the paper proposes to develop a moment prediction model to predict the lower back moment exerted in each movement frame. The lower back moment is computed using inverse kinematics and inverse dynamic in OpenSim for the training data set. Then, the paper implements a random forest regression algorithm to create a moment prediction model with postural data and velocity as input features. Finally, the safe work posture, safety frontier is computed, combining the unique actions exerting minimum lower back moment. The computed safety frontier can potentially help the safety managers to improve their safety strategies by providing a higher safety benchmark for monitoring their construction site." @default.
• W3197307971 created "2021-09-13" @default.
• W3197307971 creator A5003636781 @default.
• W3197307971 creator A5084676763 @default.
• W3197307971 date "2021-11-01" @default.
• W3197307971 modified "2023-10-01" @default.
• W3197307971 title "Sensor-based computational approach to preventing back injuries in construction workers" @default.
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