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