Gym Assistant is an iOS workout tracking application built with C# and .NET MAUI. The project is designed to provide a structured way to create workout programs, manage training sessions, record notes, and track training progress from a mobile device.
The application follows the MVVM architectural pattern, separating the user interface, application logic, data models, navigation, and data persistence.
Status: 🚧 Active development
Gym Assistant is being developed as a practical companion for gym training. The goal is to bring workout planning, session tracking, notes, progress monitoring, and eventually health data into a single mobile application.
The project focuses on maintaining a clean architecture while supporting future expansion into Apple Health integration and AI-assisted workout analysis.
- Create custom workout programs
- Add exercises to a workout
- Configure sets, repetitions, working weight, and rest periods
- View and manage existing workout programs
- Start workouts based on saved programs
- Track exercises and sets during a session
- Store workout session data
- Maintain workout history
- Create general training notes
- View and edit existing notes
- Store notes locally for later reference
- Search for exercises while creating workout programs
- Retrieve exercise information through an external exercise API
Planned progress tracking includes:
- Workout frequency
- Body weight history
- Training consistency
- Exercise performance over time
- Workout duration and other session metrics
The application follows the MVVM (Model–View–ViewModel) pattern.
View
↓
ViewModel
↓
Services
↓
Models / Data
Represent the application's core data, including:
- Workout programs
- Workout exercises
- Workout sessions
- Workout history
- Notes
Handle page state, commands, data binding, and communication between the user interface and application services.
Provide reusable application functionality including:
- Database operations
- Navigation
- Exercise API communication
- Workout-related data management
This separation keeps UI code independent from data access and core application logic.
Gym_application/
│
├── Models/ # Application data models
├── Pages/ # Views and ViewModels
├── Services/ # Database, navigation and API services
├── Helpers/ # Shared helper functionality
├── Resources/ # Images, fonts and application resources
├── Platforms/ # Platform-specific configuration
│
├── App.xaml
├── AppShell.xaml
├── MauiProgram.cs
└── gym_assistant.csproj
- C#
- .NET MAUI
- XAML
- MVVM
- SQLite / Local Data Persistence
- REST API Integration
- iOS Development
- Object-Oriented Programming
- Git & GitHub
- Workout program creation and management
- Exercise configuration
- Local data persistence
- Workout session architecture
- Training journal
- Navigation and application structure
- Active workout mode
- Set and repetition tracking
- Workout and rest timers
- Body weight tracking
- Progress charts and analytics
- Workout history improvements
- Apple Health integration
- Heart rate and activity data
- AI-powered training assistant
- Training history analysis
- AI-generated workout recommendations
- Personalized workout program generation
The interface is designed specifically for mobile use during workouts, with an emphasis on quick interaction, clear information hierarchy, and minimal distraction.
The application uses a tab-based navigation structure to provide quick access to the main areas of the app, including workouts, progress, training notes, and the dashboard.
This project is being developed both as a practical workout application and as an exploration of mobile software architecture with .NET MAUI.
Key development goals include:
- Applying MVVM in a larger mobile application
- Maintaining clear separation of responsibilities
- Designing reusable services and data models
- Implementing persistent local data storage
- Working with external APIs
- Building a native iOS-focused user experience
- Preparing the architecture for future health and AI integrations
Gym Assistant is currently under active development. Core architecture, workout program management, navigation, notes, data persistence, and exercise-related functionality are being developed and refined as the project progresses.
Additional workout tracking, analytics, Apple Health, and AI features will be introduced incrementally.