Linking Mental Health and Exercise via Remote Sensing

A substantial body of research has demonstrated that physical exercise has beneficial effects on various aspects of mental health and cognition, and that these effects are mediated through specific physiological changes in the brain. In addition, different types of exercise have differential effects on both the brain and behavior. This poses a significant challenge to successfully translating research findings to exercise-based interventions in humans to maximize the effects of exercise on mental health and cognition. Compounding the problem is that fact that the effects of exercise are inherently dependent on individual characteristics, such as age, fitness level, sex differences, time-of-day, and mental state. We propose that these challenges can be overcome if more personalized information could be obtained and used to inform an individual’s decision on how and when to exercise. In this project, we seek to develop a framework that leverages advances in remote sensing technology to provide real-time, personalized information to guide informed and deliberate decisions involving exercise. Our team pulls together expertise in optimizing human memory, physiological changes associated with exercise and cognition, remote sensing technologies and software development, and data analysis/app design. During the project period we will develop new software and app-based technology to motivate exercise and to collect custom-designed physiological and behavioral data in lab-based experiments.