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• W2347203589 abstract "Concussion and mild traumatic brain injury risk remain high for young athletes participating in helmeted and non-helmeted sports. Because of the short and potential long-term effects on young athletes and early onset Alzheimer’s and Parkinson’s disease, there is a dire need to correlate a relationship between head impact intensity, frequency, duration and athlete brain health. To address this need, the Cleveland Clinic is developing a custom mouthguard embedded with flexible circuitry and sensors, known as the “Intelligent Mouthguard”(IMG). To accurately quantify peak values of head impacts or concussions, orientation and position of each sensor relative to CG (Center of Gravity) of human head should be calculated. In this study, registration of IMG PCB sensor position and orientation from magnetic resonance images (MRI) was developed and implemented as an image processing method. This method consisted of creating both “Rigid MRI PCB” and “Human MRI PCB” from the same MRI visible material (Fullcure705) having exactly the same dimensions as the IMG PCB. As a Validation Part 1, the “Rigid MRI PCB” was scanned by itself and compared with a reference CAD drawing of the PCB called “CAD Image”. In Validation Part 2, “Human MRI PCB” was scanned while inside a volunteer’s mouth. Custom written MATLAB code was v used as an image post-processing tool in order to extract IMG PCB sensor position and orientation data with respect to the CG of the volunteer’s head. In summary, the method expresses a very simple but reliable and efficient way to obtain any position and orientation data with respect to a human subject’s head anthropometry. The method gave 0.46 mm maximum difference in position determination and 2.1 difference as an angle for orientation. This means if an athlete received an impact which effects CG as 132.7g impact in X direction, impact can be calculated 132.1g or 133.6g from Sensor 3 due to IMG position and orientation inaccuracies. Therefore, IMG measurement uncertainty is in the ±1% range based on sensor position and orientation calculation. Future work should involve in vivo validation testing using more human scans and correlating external anthropometric landmarks with sensors’ positions determined by MRI." @default.
• W2347203589 created "2016-06-24" @default.
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• W2347203589 date "2013-01-01" @default.
• W2347203589 modified "2023-09-27" @default.
• W2347203589 title "Method for Determination of Kinematic Sensor Position and Orientation from Magnetic Resonance Images" @default.
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