With the discovery of chronic traumatic encephalopathy (CTE) in 2002, the topic of brain injuries in high-contact sports gained plenty of deserved attention. CTE is a progressive degenerative brain disease. It is a consequence of a repeated concussions and traumatic brain injuries, such as those experienced by athletes in high-contact sports. A brain with CTE gradually deteriorates and loses mass. The disease not only deteriorates skills necessary for daily life (e.g. memory, self-control, time-management, focus); but it also causes much bigger mental problems (e.g. strong suicidal thoughts, depression, cognitive and thinking problems, anxiety, violent/abusive behavior, dementia) which become worse over time. The main issue with CTE is that it can only be diagnosed after death. Therefore, early detection is impossible, and prevention relies on monitoring individual impacts. While there have been significant efforts in the development of helmets with capabilities of measuring head injuries in athletes, current technologies come with limitations and inaccuracies that are inherent to the approaches and transduction mechanisms used. For example, current approaches consists on using an array of accelerometers that are physically connected to the helmet, and trigger data collection whenever any of the accelerometers measures an acceleration beyond certain threshold. The main limitation of this approach is that it relies on accelerator-based sensors attached to the helmet's not the athlete's head. Thus, the sliding that can occur between the helmet and the head makes it difficult to predict how the brain moves inside the skull. The resonance of the micro-mechanical structures inside the MEMS-based accelerometers are within the range of head motion frequencies; which has been found to cause large errors when measuring the peak angular accelerations. The proposed work is aimed at developing a reliable, robust, flexible patch that overcomes the sliding problems and frequency issues present in the current technologies by developing a reliable patch monitor that is in direct contact with the athlete's head and does not rely on suspended micrometer structures to measure acceleration. A 2-week summer activity for high-school students will be developed as part of this project. Undergraduate students and high-school teachers from the summer research opportunities program and research experience for teachers site at MSU will participate. This program will also help to motivate talented underrepresented student from The University of Puerto Rico to continue graduate studies.
Three Major Research Tasks have been designed to start at the device level, continue with system integration, and finalize with a validation process. In the first task, we will perform fundamental studies on the integration of PPFE films with carbon nanotube-based thin films as electrodes of a flexible patch; where a mechanical impact will produce an electrical signal from which the force and acceleration of the mechanical impact will be extracted. The use of CNT films (instead of metal electrodes) is aimed at eliminating issues due to metal electrode cracking and enabling a reliable patch. The second task we will look for integration of the patch into a reliable, self-powered wireless transmitter, from which the information of the mechanical impact can be extracted. The third task looks for the validation of the developed patch, where the device will characterized and compared to a benchmark to confirm its performance. The idea is that the final patch can produce and transmit signals that provide a comprehensive representation of the impact; and from which the severity of an impact on the human body (particularly the head) can be assessed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
