The Validation of Gait-Stability Metrics to Assess Construction Workers' Fall Risk

Falling from height is the top cause of injuries and fatalities in the construction industry. Understanding the fall risk at different work environments can help to prevent fall accidents on a jobsite. While many previous studies attempted to assess the fall risk on a construction site, most of them are qualitative or subject to cognitive biases. In this context, this paper aims to introduce and validate a quantitative measure that allows researchers to characterize the fall risks of construction workers. In particular, this paper focuses on validating the fall risk predictive power of Maximum Lyapunov exponent (Max LE), which is one of the gait-stability metrics established in clinical settings. The kinematic data were collected using an inertial measurement unit (IMU) sensor attached to the right ankle of the subject performing different tasks. The Max LE for each tasks were then calculated based upon the IMU measurements. The results indicated a significant difference in the Max LE between different tasks, which indicates that Max LE has the potential to evaluate the dynamic stability of construction workers.

[1]  M. Rosenstein,et al.  A practical method for calculating largest Lyapunov exponents from small data sets , 1993 .

[2]  L. Cao Practical method for determining the minimum embedding dimension of a scalar time series , 1997 .

[3]  D. Ruelle,et al.  Ergodic theory of chaos and strange attractors , 1985 .

[4]  H. Abarbanel,et al.  Determining embedding dimension for phase-space reconstruction using a geometrical construction. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[5]  Jonathan B Dingwell,et al.  Differences between local and orbital dynamic stability during human walking. , 2007, Journal of biomechanical engineering.

[6]  Nir Giladi,et al.  Gait instability and fractal dynamics of older adults with a "cautious" gait: why do certain older adults walk fearfully? , 2005, Gait & posture.

[7]  Tao Cheng,et al.  Location tracking and data visualization technology to advance construction ironworkers' education and training in safety and productivity , 2013 .

[8]  Peter J Beek,et al.  The validity of stability measures: a modelling approach. , 2011, Journal of biomechanics.

[9]  K. Newell,et al.  Walking speed influences on gait cycle variability. , 2007, Gait & posture.

[10]  H. H. E. Leipholz,et al.  Stability Theory: An Introduction to the Stability of Dynamic Systems and Rigid Bodies , 1987 .

[11]  Xingda Qu Effects of cognitive and physical loads on local dynamic stability during gait. , 2013, Applied ergonomics.

[12]  Martin G. Helander,et al.  Safety hazards and motivation for safe work in the construction industry , 1991 .

[13]  T. Chau,et al.  Measures of dynamic stability: Detecting differences between walking overground and on a compliant surface. , 2010, Human movement science.

[14]  H. Abarbanel,et al.  Local false nearest neighbors and dynamical dimensions from observed chaotic data. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[15]  Scott A. England,et al.  The influence of gait speed on local dynamic stability of walking. , 2007, Gait & posture.

[16]  J. Dingwell,et al.  Nonlinear time series analysis of normal and pathological human walking. , 2000, Chaos.

[17]  Thurmon E Lockhart,et al.  Fall Risk Assessments Based on Postural and Dynamic Stability Using Inertial Measurement Unit , 2012, Safety and health at work.

[18]  D. Sternad,et al.  Local dynamic stability versus kinematic variability of continuous overground and treadmill walking. , 2001, Journal of biomechanical engineering.