This is the coding and solution for my MSc Computer Science Thesis (2023) that uses Garmin FIT files to visualise athletes data for their own training development.
Users will need to use the sign up button in the application and create an account and folder in the activities folder before logging in to the software solution.
The Real-World Garmin Visual Data Analysis of Garmin FIT Files for Training Development research is one that delves into performance metrics in the world of cycling. The research investigates how these performance metrics can be visualised for users to harness their data insights to create training plans to improve their performance metrics. With a world that has gone towards a subscription service state, cycling performance tracking solutions have followed suit and so the research has produced a freely accessible software solution harnessing the power of Python and visual analytical tools, in turn allowing athletes of all levels to analyse trends and patterns within their data to create personalised training plans based on their own data. The research has created a foundation that future endeavours can build upon when investigating correlations between performance metrics in the work of cycling, by demonstrating how performance metrics such as heart rate and power output do indeed affect one another along with how they can be target within training to develop stronger and faster riders. The research also examines the current literature regarding Garmin FIT files in the world of cycling creating a comprehensive review that showcases all of the previous research undertaken in this topic, along with the need for the Real-World Garmin Visual Data Analysis of Garmin FIT Files for Training Development research to take place.
The MSc Thesis of this can be found on my LinkedIn Page: https://www.linkedin.com/in/nathan-jones-001