In my research mentorship at Northwestern’s Neuro-Imaging and Motor Control Lab that initially seemed to be purely based on clinical sciences, I was shocked to see myself drawn more to the technology that made every study in our lab possible. Specifically, my study uses torque-measuring robotics, electromyography sensors, and a cutaneous electrical stimulator to measure the impacts of a light electric current on the bicep muscle in participants with hemiparetic stroke. In my observations of other lab experiments, lectures, and research presentations, I found that most of the technology developed and used in our lab, as well as means of data analysis and quantification, has growing dependence on programming. As my mentor introduced me to programming with Matlab, showing me the importance of code in data analysis and the measurement of electromyographic data & torque responses, my curiosity in computer science grew. I sought to learn more through computer science courses, implement code into projects and club work, and pursue another personal research project. When I continued my research over the summer, my mentor invited me to attend Northwestern’s Movement and Rehabilitation Sciences Bootcamp, a week of lectures, tours, and project presentations detailing the development of technology in human movement research. My favorite part of the camp was networking with graduate students and PhD attendees, asking about their personal projects and observing the diverse implementation of computation and engineering in every research project. I met a professor from WashU who established a lab to study the mechanics of hand grasping in monkeys with high-tech electromyography sensors, as well as a PhD working with Case Western to engineer a glove that uses an encoded algorithm to detect hypertonia in a patient with stroke. I was most fascinated by the tours of Northwestern’s rehabilitation robotics labs and Chicago’s Shirley-Ryan Ability Lab, the nation’s first “translational” research hospital; here, I saw engineers designing a virtual reality game to measure one’s motor control and researchers programming algorithms to objectively quantify the severity of a motor impairment. Fascinated to discover the role of computer science and technological innovation in movement and rehabilitation research, I developed a new understanding of my research and its applications, and moreover, an interest to pursue computer science to contribute to similar technological advancements in clinical research. I hope to major in computer science for the next four years at an institution like Northwestern that allows me to pursue undergraduate research with a professor in a human movement and rehabilitation laboratory. I want to continue my research in this field and moreover use electromyography sensors and movement measurement technology to work towards creating a quantitative measurement system for balance and coordination in children with stroke and developmental disorders. Outside of school, I am a taekwondo black belt and instructor who has dedicated over 600 hours instructing in a taekwondo clinical support program, working with students with ADHD, Autism, and Development Coordination Disorder. For the past couple years, I have been working on an independent study project and given a TEDx talk about the profound impacts of taekwondo on neurodiverse students through my observation as an instructor, and the lack of accessibility to an inclusive sports education for these children. As I continued my research through my independent study this year, I saw that there is not much research done to quantify the impacts of taekwondo on balance and coordination. Hoping to propose taekwondo as an effective form of exercise therapy for neurodiverse students, I want to use computer science and technical skills not only as a tool to conduct accurate clinical research, but also continue my advocacy efforts for neurodiverse students who are unable to find inclusive sports programs. I hope to one day develop FDA-approved apps and video games to teach martial arts to neurodiverse children, creating an accessible form of training for all students.

In my research mentorship at Northwestern’s Neuro-Imaging and Motor Control Lab that initially seemed to be purely based on clinical sciences, I was shocked to see myself drawn more to the technology that made every study in our lab possible. Specifically, my study uses torque-measuring robotics, electromyography sensors, and a cutaneous electrical stimulator to measure the impacts of a light electric current on the bicep muscle in participants with hemiparetic stroke. In my observations of other lab experiments, lectures, and research presentations, I found that most of the technology developed and used in our lab, as well as means of data analysis and quantification, has growing dependence on programming. As my mentor introduced me to programming with Matlab, showing me the importance of code in data analysis and the measurement of electromyographic data & torque responses, my curiosity in computer science grew. I sought to learn more through computer science courses, implement code into projects and club work, and pursue another personal research project. When I continued my research over the summer, my mentor invited me to attend Northwestern’s Movement and Rehabilitation Sciences Bootcamp, a week of lectures, tours, and project presentations detailing the development of technology in human movement research. My favorite part of the camp was networking with graduate students and phD attendees, asking about their personal projects and observing the diverse implementation of computation and engineering in every research project. I met a professor from WashU who established a lab to study the mechanics of hand grasping in monkeys with high-tech electromyography sensors, as well as a phD working with Case Western to engineer a glove that uses an encoded algorithm to detect hypertonia in a patient with stroke. I was most fascinated by the tours of Northwestern’s rehabilitation robotics labs and Chicago’s Shirley-Ryan Ability Lab, the nation’s first “translational” research hospital; here, I saw engineers designing a virtual reality game to measure one’s motor control and researchers programming algorithms to objectively quantify the severity of a motor impairment. Fascinated to discover the role of computer science and technological innovation in movement and rehabilitation research, I developed a new understanding of my research and its applications, and moreover, an interest to pursue computer science to contribute to similar technological advancements in clinical research. I hope to major in computer science for the next four years at an institution like Northwestern that allows me to pursue undergraduate research with a professor in a human movement and rehabilitation laboratory. I want to continue my research in this field and moreover use electromyography sensors and movement measurement technology to work towards creating a quantitative measurement system for balance and coordination in children with stroke and developmental disorders. Outside of school, I am a taekwondo black belt and instructor who has dedicated over 600 hours instructing in a taekwondo clinical support program, working with students with ADHD, Autism, and Development Coordination Disorder. For the past couple years, I have been working on an independent study project and given a TEDx talk about the profound impacts of taekwondo on neurodiverse students through my observation as an instructor, and the lack of accessibility to an inclusive sports education for these children. As I continued my research through my independent study this year, I saw that there is not much research done to quantify the impacts of taekwondo on balance and coordination. Hoping to propose taekwondo as an effective form of exercise therapy for neurodiverse students, I want to use computer science not only as a tool to conduct accurate research, but also create an FDA-approved app to teach taekwondo to neurodiverse children.