Construction Systems


Date of this Version

Summer 5-2015


H. Jebelli, Assessing Gait and Postural Stability of Construction Workers Using Wearable Wireless Sensor Networks. MSc thesis., Construction Engineering and Management Department, University of Nebraska–Lincoln, 2015.


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Construction Engineering and Management, Under the Supervision of Professor Changbum R. Ahn. Lincoln, Nebraska: May, 2015

Copyright (c) 2015 Houtan Jebelli


Falling accidents are a leading cause of fatal and nonfatal injuries in the construction industry. This fact demonstrates the need for a comprehensive fall-risk analysis that incorporates the effects of construction workers’ physiological characteristics. In this context, the objective of the thesis is to investigate and validate the usefulness of the gait- and postural-stability metrics in assessing construction workers’ fall risks. Diverse metrics that assess the capability to keep the body balanced and maintain coordination of body segments during locomotion (gait stability) and stationary postures (postural stability) have been introduced and used in clinical applications. However, their usefulness in the industry settings, in particular construction domain, has not been fully examined. Specifically, the thesis investigates the usefulness of one gait-stability metric and two postural-stability metrics which are computed using kinematic data captured from wearable inertial measurement units (IMUs). The usefulness of the selected metrics is validated by demonstrating their distinguishable powers in characterizing construction tasks with different fall-risk profiles.

This thesis consists of three independent papers that have been published in other venues. The first paper focuses on validating the predictive power of fall risk of the Maximum Lyapunov exponent (Max LE), a gait-stability metric established in clinical settings. The results of the first paper demonstrate that the Max LE is able to distinguish workers’ gait stability while doing tasks with different fall-risk profiles. The second paper aims to test the usefulness of two postural-stability metrics that can be calculated from inertial measurement unit (IMU) data—the velocity of the bodily center of pressure (COPv) and the resultant accelerometer (rAcc)—as predictors for measuring construction workers’ fall risk in stationary postures. The results showed the distinguishing powers of Acc and COPv in tasks with different fall-risk profiles in stationary postures. The third paper explores the application of the postrual-stability metrics to analyze fall risks of the effects of tool-loading formation on workers’ fall risks. The results of the last paper demonstrate the higher risk values associated with tools connected asymmetrically to a full-body safety harness. The postrual- and dyanamic-stability metrics demonstrated in this thesis can be used as the metrics to find tasks and postures that have a higher risk of falling. Knowing the most dangerous locations at construction sites can help the manager provide appropriate fall-prevention systems; these can decrease the hazards at the job sites. Merging the suggested approach with certain alarm systems can provide real-time monitoring, which can assess the fall risk of construction workers.

Advisor: Changbum R. Ahn