Mental illness and drug addiction have always been a problem within the U.S. and although there do exist treatments and medication, access to these is quite limited. Recent research has shown that stress and mood (affect) plays an important role in drug craving and addiction in general. Our research plans to use mobile sensors and apps to gather heart rate variability data from patients. We will then develop a machine learning model to predict stress given such data in order to allow people easier access to treatments and therapy to reduce stress and prevent drug relapse.

From this SuperUROP, I hope to gain more knowledge and practical experience in applying what I’ve learned about machine learning and algorithms in classes. I look forward to developing a machine learning model by the end of the SuperUROP that will have an impact on other people’s lives.