# 48: Using Augmented Reality and Machine Learning to Guide Physical Exercise Routines

Project ID: 48
Team Members: Kyle Henry,
Faculty Advisor(s): Christoph Csallner
Department: Computer Science & Engineering
Project Type: REU
Title: Using Augmented Reality and Machine Learning to Guide Physical Exercise Routines
Abstract: This project creates prototype solutions for a 2-year Caruth-funded project. The ultimate goal is to leverage ongoing advances in augmented reality (AR) hardware, machine learning, and software to motivate seniors via AR-based smartphone apps to increase their physical activity levels. While there are clear software engineering challenges in developing an app seniors care about and want to interact with, this project focuses on the underlying technical challenges of understanding, comparing, and ultimately selecting recent AR hardware/software combinations that are most promising for achieving the ultimate goal of motivating seniors to increase their physical activity levels. Specifically, this research develops the application and evaluates how well the app runs on different platforms. The evaluation will compare different device features, such as the operating system and CPU architecture, memory usage, and detailed runtime performance measurements. The resulting implementation source code is available on GitHub (https://github.com/SonicHedghog/Senior-Fit) as open-source software.
Poster: View Poster #48 (PDF)
Judges Scoring: Submit Evaluation (judges only)