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Technical Briefs

Determination of Low-Pass Filter Cutoff Frequencies for High-Rate Biomechanical Signals Obtained Using Videographic Analysis

[+] Author and Article Information
Ronald J. Fijalkowski

Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226; Department of Biomedical Engineering, Marquette University, Milwaukee, WI 53201-1881; Department of Veterans Affairs Medical Center, Milwaukee, WI 53295

Kristina M. Ropella

Department of Biomedical Engineering, Marquette University, Milwaukee, WI 53201-1881

Brian D. Stemper1

Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226; Department of Biomedical Engineering, Marquette University, Milwaukee, WI 53201-1881; Department of Veterans Affairs Medical Center, Milwaukee, WI 53295stemps@mcw.edu

1

Corresponding author.

J Biomech Eng 131(5), 054502 (Mar 20, 2009) (6 pages) doi:10.1115/1.3078182 History: Received March 19, 2008; Revised November 12, 2008; Published March 20, 2009

Diffuse brain injury (DBI) commonly results from blunt impact followed by sudden head rotation, wherein severity is a function of rotational kinematics. A noninvasive in vivo rat model was designed to further investigate this relationship. Due to brain mass differences between rats and humans, rotational acceleration magnitude indicative of rat DBI (350krad/s2) has been estimated as approximately 60 times greater than that of human DBI (6krad/s2). Prior experimental testing attempted to use standard transducers such as linear accelerometers to measure loading kinematics. However, such measurement techniques were intrusive to experimental model operation. Therefore, initial studies using this experimental model obtained rotational displacement data from videographic images and implemented a finite difference differentiation (FDD) method to obtain rotational velocity and acceleration. Unfortunately, this method amplified high-frequency, low-amplitude noise, which interfered with signal magnitude representation. Therefore, a coherent average technique was implemented to improve the measurement of rotational kinematics from videographic images, and its results were compared with those of the previous FDD method. Results demonstrated that the coherent method accurately determined a low-pass filter cutoff frequency specific to pulse characteristics. Furthermore, noise interference and signal attenuation were minimized compared with the FDD technique.

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Copyright © 2009 by American Society of Mechanical Engineers
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Figures

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Figure 1

Illustration of the rat helmet with targets used to track rotational kinematics

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Figure 2

(a) Flow chart for FDD analysis; (b) determination of FDD cutoff frequency dependence for comparison to coherent analysis. θ=rotational displacement, ω=rotational velocity, α=rotational acceleration, p=peak, A=average, and fc=cutoff frequency.

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Figure 3

Flow chart for coherent analysis. θ=rotational displacement, ω=rotational velocity, α=rotational acceleration, p=peak, A=average, and fc=cutoff frequency.

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Figure 4

Mean rotational acceleration magnitude versus filter cutoff frequency using FDD analysis. (a) HASD test pulse. (b) LAMD test pulse.

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Figure 5

An example of each analysis. (a) Raw temporal rotational displacement of a HASD test pulse. (b) Subsequent temporal rotational acceleration derived using each technique.

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Figure 6

HASD pulse. (a) Rotational acceleration magnitude versus filter cutoff frequency. (b) Rotational deceleration magnitude versus filter cutoff frequency.

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Figure 7

LAMD pulse. (a) Rotational acceleration magnitude versus filter cutoff frequency. (b) Rotational deceleration magnitude versus filter cutoff frequency.

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