Correlating the passive response of eye and brain to head impact using MEMS IMUs on 3D-printed human head phantom

Abstract

Objective: The eye may act as a surrogate for the brain in response to head acceleration during an impact. This paper reports the latest demonstration of the correlation between the passive human eye accelerations and the brain accelerations under head impacts using a model eye/brain/skull phantom. Approach: Experiments investigating rotational and linear accelerations were performed on a 3D-printed human head phantom, along with rotational experiments on a human volunteer. Data acquired during the passive eye response (PER) periods were processed and analysed using statistical methods including one-way normal analysis of variance, linear regression fit, and Pearson R correlation. Main results: The results have shown that, at least on the 3D-printed human head phantom, strong correlations can be found between the eye and the brain during the PER, which indicates a potential use of microelectromechanical systems inertial measurement units in real-time on-field monitoring and diagnosis of concussions or traumatic brain injuries. Significance: These discoveries pave the way for potential non-invasive wearable devices based on this technology to be applied in real-time on-field concussion monitoring, which is expected to provide vulnerable parties with instant alert thus timely treatment.

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“…In the same study where Meng et al (2020) showed that the skull kinematics do not correlate to the movements of the brain, they also found that the movements of the eyes are well correlated to the brain, especially for the posterior part of the brain where R-squared value is as high as 0.983. Meng and Prather et al (Meng et al 2020, Prather et al 2019 proposed to build a micro IMU in a contact lens as a way to monitor the movements of the brain due to an impact. However, sensor technology has a long way to go before this system can be safely realized outside of the lab.…”

“…Finite element models for head impact One of the likely reasons behind the failures of the kinematics-based head impact severity measures is that these models, based on head kinematics, simply are not representative of the motions of the brain. Meng et al (2020) investigated the correlations between skull movements and movements of different sections of the brain and found R-squared values of less than 0.4 across the board. To reasonably predict the actual impact on the brain due to external energy on a microstructural level, many finite element (FE) models have been constructed using (head impact) data from various sources, including MRI images of the human brain (Ji et al 2014).…”

“…In contrast to the software solutions above, Meng and Prather et al (Meng et al 2020, Prather et al 2019 presented a novel hardware approach. In the same study where Meng et al (2020) showed that the skull kinematics do not correlate to the movements of the brain, they also found that the movements of the eyes are well correlated to the brain, especially for the posterior part of the brain where R-squared value is as high as 0.983. Meng and Prather et al (Meng et al 2020, Prather et al 2019 proposed to build a micro IMU in a contact lens as a way to monitor the movements of the brain due to an impact.…”