Back in my sophomore year here at George Mason, I took a course called HHS 491: Foundations of Clinical Research; I had heard about it through an email sent out via Honors college announcements and saw it as a golden opportunity to get a more substantial understanding of clinical research. I had always wanted to somehow participate in undergraduate research of some form, and this class gave me the chance to later apply for an internship as the second semester of the class, HHS 492. Luckily, I was accepted to work on a project in the Lab for the Study and Simulation of human movement under the direction of Dr. Naomi Lynn Gerber and Dr. Zoran Duric. These two phenomenal professors, along with my partner in research, GMU Senior Mohamed Salih, helped me to find a passion in research that could only result in applying for OSCAR funding. My interest in my project stemmed from learning more about the project that Dr. Duric’s PhD student, Gene Shuman, is currently working on. His dissertation is called “Using Myoelectric Signals to Recognize Grips and Movements of the Hand,” which, to summarize very briefly, aims to distinguish signals produced by the hand and arm when performing an everyday task such as opening a jar or gripping a ball. These signals are recorded by a number of sensors; this is where my project is going to take place. We hope to somewhat standardize the findings of Gene’s work by seeing if we can quantitatively see which specific sensor is measuring what depending on the task; which could thus show if one particular placement of a sensor will be the key to recognizing a specific task. This relates to my long term goals because I am interested in the field of prosthetics and rehabilitative technology. On a weekly basis, I meet with Dr. Duric, Dr. Gerber, and Gene to discuss his progress and to gather more data for the signals. We are still formulating a method to determine how we will organize the data we will be collecting and we are still in the literature review process. An exciting thing I learned this week was the use of SAX (symbolic aggregate approximation) in data collection and analysis.
