AI-Powered Exercise Recognition Glove

This project involves designing and creating a smart, wearable glove that recognizes different exercise movements using AI. The glove uses an Arduino Nano BLE 33 Sense board, an accelerometer and gyroscope to detect hand movements, and an AI model to classify and validate the movements. The system provides real-time feedback and progress tracking.

Features:

• Movement Recognition: Differentiates between at least five different exercise movements.
• Interactive Button Interface: Allows users to select exercises.
• Real-Time Feedback: Buzzer announces the exercise and counts repetitions.
• Statechart Management: Visualizes and manages the system's states and transitions.
• Hardware: Arduino Nano BLE 33 Sense, accelerometer, gyroscope, Buzzer, and button.

Hardware Requirements:

• Arduino Nano BLE 33 Sense
• Accelerometer and gyroscope
• Buzzer
• Push button
• LED for feedback

How to Use:

1. Clone the repository or download the ZIP file.
2. Open the glove.ino file in the Arduino IDE.
3. Connect the Arduino Nano BLE 33 Sense to your computer.
4. Upload the code to the Arduino board.
5. Interact with the glove by pressing the button to cycle through different exercises.

AI Model:

The AI model is trained on the sensor data to recognize movements. It is stored in the model.h file, which is integrated into the Arduino code for real-time classification.

Data Collection:

The Data/ folder contains the dataset used for training the AI model. You can collect more data if needed to improve classification accuracy.

Statechart:

The system is visualized using a statechart, which helps in managing various states like Idle, Counting down, Detecting movement, and Classifying gesture. You can find the statechart diagram in the statechart/ folder.