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

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.