Assessing Exposure to Slip, Trip, and Fall Hazards by Measuring Construction Worker Loss of Balance
Publication: Computing in Civil Engineering 2021
ABSTRACT
A worker repeatedly exposed to slip, trip, and fall (STF) hazards is at an increased risk of an STF event. To monitor an individual’s exposure to STF hazards, previous approaches have assessed the loss of body balance (LOB). However, these approaches were not fully validated in field settings, where dynamic workplace environments can impact workers’ bodily movements. This study aims to develop and evaluate a new approach to assess workers’ exposures to STF hazards by LOB assessment in a real construction site. A waist-worn inertial measurement unit sensor was used to extract features of waist movements, which were modified into a single value to measure LOB using the Mahalanobis distance (MD) metric. The MD value was calculated for each step a worker took, and exposure to the STF hazards was detected when the MD value was larger than a predetermined threshold. The results provided an average of an unweighted average recall of 89.13% (without exposures: 90.30%, and with exposures: 87.96%) that would strongly indicate generalizability and robustness for practical applications.
Get full access to this chapter
View all available purchase options and get full access to this chapter.
REFERENCES
Ahn, C. R., Lee, S., Sun, C., Jebelli, H., Yang, K., and Choi, B. (2019). “Wearable Sensing Technology Applications in Construction Safety and Health.” Journal of Construction Engineering and Management, 145(11), 03119007.
Bourke, A. K., and Lyons, G. M. (2008). “A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor.” Medical Engineering & Physics, 30(1), 84–90.
Bourke, A. K., O’Brien, J. V., and Lyons, G. M. (2007). “Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm.” Gait & Posture, 26(2), 194–199.
Dzeng, R.-J., Fang, Y.-C., and Chen, I.-C. (2014). “A feasibility study of using smartphone built-in accelerometers to detect fall portents.” Automation in Construction, 38, 74–86.
Fang, Y.-C., and Dzeng, R.-J. (2017). “Accelerometer-based fall-portent detection algorithm for construction tiling operation.” Automation in Construction, 84, 214–230.
Gheisari, M., Irizarry, J., and Walker, B. N. (2014). “UAS4SAFETY: The Potential of Unmanned Aerial Systems for Construction Safety Applications.” 1801–1810.
Hu, B., Dixon, P. C., Jacobs, J. V., Dennerlein, J. T., and Schiffman, J. M. (2018). “Machine learning algorithms based on signals from a single wearable inertial sensor can detect surface- and age-related differences in walking.” Journal of Biomechanics, 71, 37–42.
Kim, M., and Lee, D. (2016). “Development of an IMU-based foot-ground contact detection (FGCD) algorithm.” Ergonomics, 60(3), 384–403.
Lai, C.-F., Chang, S.-Y., Chao, H.-C., and Huang, Y.-M. (2011). “Detection of Cognitive Injured Body Region Using Multiple Triaxial Accelerometers for Elderly Falling.” IEEE Sensors Journal, 11(3), 763–770.
Lim, T.-K., Park, S.-M., Lee, H.-C., and Lee, D.-E. (2016). “Artificial Neural Network–Based Slip-Trip Classifier Using Smart Sensor for Construction Workplace.” Journal of Construction Engineering and Management, 142(2), 04015065.
Lipscomb, H. J., Glazner, J. E., Bondy, J., Guarini, K., and Lezotte, D. (2006). “Injuries from slips and trips in construction.” Applied Ergonomics, 37(3), 267–274.
Liu, J., Zhang, X., and Lockhart, T. E. (2012). “Fall Risk Assessments Based on Postural and Dynamic Stability Using Inertial Measurement Unit.” Safety and Health at Work, 3(3), 192–198.
BLS (Bureau of Labor Statistics). (2020). Census of Fatal Occupational Injuries. Washington, DC: Bureau of Labor Statistics.
Toole, T. M. (2002). “Construction Site Safety Roles.” Journal of Construction Engineering and Management, 128(3), 203–210.
Yang, K., and Ahn, C. R. (2019). “Inferring workplace safety hazards from the spatial patterns of workers’ wearable data.” Advanced Engineering Informatics, 41, 100924.
Yang, K., Ahn, C. R., Vuran, M. C., and Aria, S. S. (2016). “Semi-supervised near-miss fall detection for ironworkers with a wearable inertial measurement unit.” Automation in Construction, 68, 194–202.
Yang, K., Ahn, C. R., Vuran, M. C., and Kim, H. (2017). “Collective sensing of workers’ gait patterns to identify fall hazards in construction.” Automation in Construction, 82(Gait Posture282008), 166–178.
Yang, K., Aria, S., Ahn, C. R., and Stentz, T. L. (2014). “Automated Detection of Near-miss Fall Incidents in Iron Workers Using Inertial Measurement Units.” 935–944.
Yang, K., Jebelli, H., Ahn, C. R., and Vuran, M. C. (2015). “Threshold-Based Approach to Detect Near-Miss Falls of Iron Workers Using Inertial Measurement Units.” 148–155.
Information & Authors
Information
Published In
History
Published online: May 24, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.