ASSISTIVE ROBOTICS & BIOSIGNALS
Eye Movement (EOG) Hands-Free Mobility Arduino + Serial

Eye-Controlled Car for Assistive Mobility

A hands-free robotic car steered entirely by eye movements and blinks, built for people with severe physical mobility challenges.

Control Mechanism
Eye Blinks + Left/Right Eye Movement
Robot Hardware
4-Wheel Chassis + Arduino Uno + Motor Driver
System Latency
Live Instant Serial Telemetry (COM3)
Application
Hands-Free Mobility & Wheelchairs

Why Drive a Car with Your Eyes?

People with severe paralysis often lose hand movement, but their eye muscles still function normally. This project translates tiny electrical signals from eye movements and blinks into real-time steering commands for a 4-wheel robot car.

What was I trying to achieve?

Safely steer a vehicle using only the eyes: intentional blinks toggle Start / Stop, while looking left or right steers. Emergency stops must execute immediately with zero lag.

Hardware Prototype

Physical 4-Wheel Robot Car Prototype
Arduino Uno + Motor Driver
Eye Controlled Robot Car Hardware Prototype
Physical Prototype: 4-wheel drive chassis equipped with an Arduino Uno, L298N motor driver, and rechargeable battery pack powering 4 DC gear motors.
Component Part Role
Microcontroller Arduino Uno Decodes eye commands and controls the wheel motors.
Motor Driver Dual H-Bridge (L298N) Drives 4 DC motors (Forward, Reverse, Left, Right, Stop).
Power Li-ion Battery Pack Dedicated motor power supply preventing resets.
Sensors Biopotential Electrodes Measures tiny eye voltage shifts and streams live data over COM3.

Turning Eye Signals into Driving Commands

Blink Detection (Start / Stop)
Green 'X' Peaks
Eye Blink Waveform

A deliberate blink creates a sharp electrical spike (green 'X' marks). When detected, it toggles the car between Moving and Stop.

Gaze Shift (Steering)
Orange Markers
Eye Left Right Waveform

Looking left produces a positive wave; looking right produces a negative wave (orange marks). The software reads wave direction to turn left or right.

Practical Engineering Solutions

1. Involuntary Blinks: Normal everyday blinks are filtered out by duration and threshold checks—only intentional, firm blinks toggle the car.
2. Facial Muscle Noise: Filters reject high-frequency muscle noise so talking or smiling doesn't trigger false turns.
3. Instant Braking: Stop commands bypass serial queues to stop the motors in under 10 milliseconds.

Summary

Proves that low-cost biosensors and an Arduino microcontroller can provide reliable, hands-free mobility to people who cannot use manual controls.

Source Code on GitHub

Eye_Control_Movement Repository

Complete code repository with real-time signal filtering, blink/gaze detection scripts, and Arduino motor firmware.

View on GitHub