<p>An accurate way to identify potentially concussive events is needed for military and athletic populations to prevent long-term consequences associated with repeated head injuries. Environmental sensors (ES) have been proposed as a way to identify potentially concussive events through measurement and analysis of kinematics at the head center of gravity (CG). Several ES types have been developed with varying mounting locations and strategies. Previous work has evaluated the accuracy of ES but did not explicitly examine errors due to rigid body kinematics assumptions such as sensor orientation (SO) and head CG position (HCGP). Further, errors in SO and HCGP are likely to be exacerbated by exposure severity. The objective of this study was to complete a parametric analysis, systematically investigating the extent that SO, HCGP, and exposure severity contribute to errors in peak resultant linear acceleration (PRLA) at the head CG. For the parametric analysis presented here, the head was chosen to be a spherical representation of the skull, with a diameter equal to the average of head length and head breadth from a 50<sup>th</sup> percentile male Soldier. A simulated ES was positioned at the relative location of the mastoid process. Simulated sensor readings were defined by idealized representations of head motion [extension (rotation about y, acceleration in x), lateral bending (rotation about x, acceleration in y) and axial rotation (rotation about z, acceleration in y)]. Linear and angular accelerations were represented as a half sine pulse with 10 milliseconds (ms) of zero motion at the end. Peak magnitudes of linear acceleration ranged between 12.5 and 100 Gs and angular accelerations ranged from 1250 to 10000 rad/s/s. Durations of linear and angular accelerations were independent of one another and ranged between 5 and 30 ms. The combination of these exposure variables resulted in 192 simulated head exposures read by the sensor. Simulated variations in HCGP and SO were chosen to represent errors in sensor placement, either from anthropometry differences of the user or human error by the administrator. Simulated HCGP variations ranged from -10% to 10% of the true HCGP in each direction and SO variations ranged from -20 to 20 degrees about each axis. True head CG response was calculated using zero degrees SO offset and zero error in HCGP for all axes. For all exposure conditions, samples of possible HCGP and SO values were selected using Latin hypercube sampling (50,000 out of 753,571 possible HCGP/SO combinations). Head CG linear accelerations were calculated for each exposure condition and combination of HCGP/SO. Errors due to simulated sensor readings and variations in HCGP/SO were summarized using percent error between the true PRLA (with zero HCGP/SO error) and the calculated PRLA (with the simulated HCGP/SO variations). Errors were grouped by exposure condition and the maximum percent error identified. The maximum and minimum calculated errors were 75.2% and 12.6% for all exposure conditions. The mean (+/- standard deviation) of calculated errors was 30.3% (+/-9.71). Maximum error across all head exposures was associated with worst case SO values (20 degrees offset about each axis) and HCGP errors between 5 and 10% of the radius of the head. Minimum error was associated with SO values between 1 and 20 degrees offset and HCGP errors between 0 and 10 % of the head radius. These results indicate that variations in SO and HCGP likely contribute to errors in PRLA at the head CG. Device administrators should be careful to have correct SO when attaching the devices to Soldiers/players. Maximum reported errors were at the extreme ends of the parametric analysis and likely due to a combination of user error and anthropometric variation. Future analyses will determine how variations in sensor position and orientation within unique mounting regions on the head contribute to errors in head CG kinematics.</p>

Parametric Evaluation of Head Center of Gravity Acceleration Error From Rigid Body Kinematics Assumptions Used in Environmental Sensors

Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2021/volume/85543

ASME 2021 International Mechanical Engineering Congress and Exposition (IMECE2021)

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