This project detects driver drowsiness using EMG (Electromyography) signals captured through the BioAmp EXG Pill sensor connected to an Arduino. Real-time data is visualized using Python, and alerts are generated (beep sounds) when muscle activity drops below a defined threshold combined with eye and face data from Raspberry camera module — indicating possible fatigue or drowsiness.
Visit: https://youtube.com/shorts/ll5yq4PN2Z0
- Real-time EMG signal visualization using Biosignals, electrodes, arduino, matplotlib
- Real time eye and face monitoring using Computer Vision, Camera Module, and Raspeberry Pi
- Real time Sleep logging systems
- Map and Fatigue Predictor – Input your journey destination, and using past sleep data, the system estimates when you are likely to experience drowsiness during the trip.
- User Friendly cost effective app for admins and Drivers
- BioAmp EXG Pill
- Arduino UNO / Nano
- Jumper wires
- Electrodes (placed on wrist and forearm)
- Raspberry Pi
- Raspberry Pi Camera Module
- Arduino IDE (for firmware)
- Python 3.x
pyserialmatplotlibwinsound(for beeping on drowsiness detection)csvcollections(for buffering)
- JavaScript
- React Native(for app)
Upload the Arduino sketch to your board to read analog EMG values from the BioAmp EXG Pill.
- Connect the BioAmp EXG Pill's analog output to A0 pin on Arduino.
- Ensure electrodes are properly placed on the wrist and forearm.
- Plug in your Arduino via USB.
- Connect Camera module to Raspberry Pi
- Feed opencv code to Raspberry Pi: haar-cascades-raspberrypi.py
- Install required Python libraries:
- Update the correct COM port in the Python script (e.g., COM4).
- Run the script emg_visualiser.py and haar-cascades-raspberrypi.py
-
Real-time waveform of muscle activity through EMG signals will appear.
-
Blink rate will be monitored through camera
-
A CSV file will be created with timestamped EMG data.
-
Beep sound plays when muscle activity is too low or eyes are closed for more than threshold value(possible drowsiness).
