Title

A Deep Analysis and Algorithmic Approach to Solving Complex Fitness Issues in Collegiate Student Athletes

Presenter Information

Holly N. PuckettFollow

Location

Presentation- Allen E. Paulson College of Engineering and Computing

Document Type and Release Option

Thesis Presentation (Archived)

Faculty Mentor

Andrew Allen

Faculty Mentor Email

andrewallen@georgiasouthern.edu

Presentation Year

2021

Start Date

26-4-2021 12:00 AM

End Date

30-4-2021 12:00 AM

Keywords

Algorithm, Complex fitness issues, Collegiate student athletes

Description

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.

Academic Unit

Allen E. Paulson College of Engineering and Computing

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Apr 26th, 12:00 AM Apr 30th, 12:00 AM

A Deep Analysis and Algorithmic Approach to Solving Complex Fitness Issues in Collegiate Student Athletes

Presentation- Allen E. Paulson College of Engineering and Computing

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.