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Research Papers

Predicting Distal Radius Bone Strains and Injury in Response to Impacts Using Multi-Axial Accelerometers

[+] Author and Article Information
Timothy A. Burkhart1

 Department of Mechanical and Materials Engineering, Western University, 1151 Richmond Street, London, ON, N6A 5B9, Canadatburkhar@uwo.ca

Cynthia E. Dunning

 Departments of Mechanical and Materials Engineering, Department Medical Biophysics, Department of Surgery, Western University, 1151 Richmond Street, London, ON, N6A 5B9, Canadacdunning@uwo.ca

David M. Andrews

 Department of Kinesiology, Department of Industrial and Manufacturing Systems Engineering, University of Windsor, 401 Sunset Avenue, Windsor, ON, N9B 3P4, Canadadandrews@uwindsor.ca

1

Corresponding author.

J Biomech Eng 134(10), 101007 (Oct 04, 2012) (7 pages) doi:10.1115/1.4007631 History: Received April 13, 2012; Revised August 21, 2012; Posted September 25, 2012; Published October 04, 2012; Online October 04, 2012

Measuring a bone’s response to impact has traditionally been done using strain gauges that are attached directly to the bone. Accelerometers have also been used for this purpose because they are reusable, inexpensive and can be attached easily. However, little data are available relating measured accelerations to bone injury, or to judge if accelerometers are reasonable surrogates for strain gauges in terms of their capacity to predict bone injuries. Impacts were applied with a custom designed pneumatic impact system to eight fresh-frozen human cadaveric radius specimens. Impacts were repeatedly applied with increasing energy until ultimate failure occurred. Three multiaxial strain gauge rosettes were glued to the bone (two distally and one proximally). Two multiaxial accelerometers were attached to the distal dorsal and proximal volar aspects of the radius. Overall, peak minimum and maximum principal strains were calculated from the strain-time curves from each gauge. Peak accelerations and acceleration rates were measured parallel (axial) and perpendicular (off-axis) to the long axis of the radius. Logistic generalized estimating equations were used to create strain and acceleration-based injury prediction models. To develop strain prediction models based on the acceleration variables, Linear generalized estimating equations were employed. The logistic models were assessed according to the quasi-likelihood under independence model criterion (QIC), while the linear models were assessed by the QIC and the marginal R2 . Peak axial and off-axis accelerations increased significantly (with increasing impact energy) across all impact trials. The best injury prediction model (QIC = 9.42) included distal resultant acceleration (p < 0.001) and donor body mass index (BMI) (p < 0.001). Compressive and tensile strains were best predicted by separate uni-variate models, including peak distal axial acceleration (R2  = 0.79) and peak off-axis acceleration (R2  = 0.79), respectively. Accelerometers appear to be a valid surrogate to strain gauges for measuring the general response of the bone to impact and predicting the probability of bone injury.

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Copyright © 2012 by American Society of Mechanical Engineers
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Figures

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Figure 2

A distal radius specimen showing the locations of the three strain gauges and the two accelerometers. The locations of the sigmoid fossa and the radial styloid have been included to orient the position of the radius.

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Figure 1

Experimental setup for the cadaver radius specimens in the pneumatic impactor

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Figure 3

Typical distal and proximal axial acceleration (a) and gauge 1 and gauge 3 minimum principal strain (b) curves for a prefracture impact event. The vertical lines represent the times to peak for each respective curve.

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Figure 4

Typical fracture patterns experienced by the distal radius following ultimate failure shown on the articular surface (a) and into the dorsal aspect of the diaphysis (b)

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Figure 5

Comparison of the mean (SD) peak accelerations (a) and acceleration rate (b) between the prefracture, crack and fracture events (*p < 0.05)

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Figure 6

Comparison of the mean (SD) peak minimum and maximum principal strains (a) and strain rates (b) for gauges 1 and 2, between the prefracture, crack and fracture events (*p < 0.05)

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Figure 7

Mean (SD) shock wave velocities calculated from the times of the peak strains and the peak accelerations (*p < 0.05)

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