Honors College Theses

Date

2021

Major

Computer Science (B.S.)

Document Type and Release Option

Thesis (open access)

Faculty Mentor

Andrew Allen

Abstract

Sports are not simply an entertainment source. For many, it creates a sense of community, support, and trust among both fans and athletes alike. In order to continue the sense of community sports provides, athletes must be properly cared for in order to perform at the highest level possible. Thus, their fitness and health must be monitored continuously. In a professional sense, one can expect individualized attention to athletes daily due to an abundance of funding and resources. However, when looking at college communities and student athletes within them, the number of athletes per athletic trainer increases due to both limited funds and resources. Athletic trainers are responsible for athlete care but can be overwhelmed with high ratios of athletes per athletic trainer. Thus, the question comes into play, how can adequate monitoring of student athletes’ health and fitness levels be implemented on a consistent basis to ensure appropriate exercise regimens are being followed to allow for maximum performance? In order to help alleviate this issue, a web application was developed to ensure student athletes are getting appropriate accommodations and exercise routines needed on an individualized basis. The algorithm used assesses the activity and fitness levels of each student athlete through user input and evaluates what type of exercise regimen is needed based on various factors discussed throughout this paper. After the deployment of this application, it was found to be effective in monitoring students’ health and fitness levels.

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