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Fitness and Calorie Tracking Website with Injury Prediction
Author Name

Mr. G. Jegatheesh kumar, Prasanth N

Abstract

This project presents a comprehensive Food and Workout Tracking Application aimed at helping users effectively monitor and manage their daily nutrition intake and physical activity. With the growing importance of maintaining a healthy lifestyle, the application provides a digital solution that simplifies calorie tracking, macronutrient monitoring, and workout logging through an intuitive and user-friendly interface.The food tracking module allows users to add and manage food items with fully editable quantities, including support for decimal values such as 1.5 or 0.75 servings. Each food entry includes a dedicated edit option, ensuring flexibility and accuracy in daily nutrition tracking without requiring users to delete and re-enter data.Similarly, the workout tracking module enables users to log physical activities with editable parameters such as workout duration (in minutes) and number of sets. Based on these inputs, the application dynamically recalculates the calories burned, providing personalized and precise workout insights. To reduce manual data entry and enhance accuracy, the application integrates a barcode scanning feature

 

within the food tracker. Users can scan packaged food items using the device camera, and the scanned barcode is automatically processed through a backend API to retrieve corresponding food details from the database. This functionality significantly improves user convenience, minimizes errors, and speeds up the food logging process.For improved usability and visual appeal, food items are displayed along with representative images sourced from Unsplash.The backend of the application is developed using Node.js with the Express framework and MongoDB as the database.

Keywords: fitness tracking; calorie monitoring; injury prediction; wearable health; MERN stack; logistic regression.



Published On :
2026-03-10

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