fitness-tracker

SparkyFitness: Built for Families. Powered by AI. Track food, fitness, water, and health — together.

Roll your own tracker!

A workout tracking web application for personal use (or family, friends), geared towards running and other GPX-based activities

Self-hosted gym & body-weight tracker — plan routines, log workouts (supersets, warm-ups, cardio), see which muscles are trained, fatigued or detrained, import from FitNotes/Strong/Hevy, passkey login. Your data, your server.

ExerciseDB API is an fitness exercise database api that allows users to access high-quality exercises data which consists 11000+ exercises. This API offers extensive information on each exercise, including target body parts, equipment needed, video, gifs, images for visual guidance, and step-by-step instructions.

AI-powered fitness assistant for real-time pose estimation, exercise counting, and workout feedback.

FastNFitness Android app: Body, Cardio and Fitness tracking.

Extracting meaningful health information from large accelerometer datasets

A workout journal. Moved to https://codeberg.org/iamlooker/kenko

Self hosted web analytics for endurance athletes

Analyze your data from Garmin, Suunto, Coros to one centralized app

Repository for FOSS fitness tracking app Simple.

Standalone offline local desktop application to process, store, and visualize Garmin FIT file data in a comprehensive dashboard.

MCP server to connect to whoop API

An AI model used to help with the workout session by keeping track of counts and movement.

WARNING: This repository is no longer maintained ⚠️ This repository will not be updated. The repository will be kept available in read-only mode. Refer to https://developer.ibm.com/patterns/category/blockchain/ for other blockchain code patterns.

Make use of the power of Mediapipe’s pose detection, this project is built in order to analyze, detect and classifying the forms of fitness exercises.

Fitness Action Quality Assessment or your AI-Fitness Coach [ECCV 2022]

Android example showing Bluetooth communication with Xiaomi Mi Band 2. Demonstrates device pairing, data syncing, activity tracking, heart rate monitoring, and notification handling. Provides reference code for wearable device integration.

RunTrack is a Running Tracking app made using Modern Android Development (MAD), including Jetpack Compose, MVVM architecture, and Google Maps API. The app allows users to track their running activities and displaying real-time routes on an interactive map.