---
title: "Eye-Tracking Smart Home | Sobhan Heravian"
description: "People with spinal cord injuries control the lights, their bed and emergency calls just by looking at a panel. 97% of commands were recognized correct"
url: "https://sobhan.heravian.com/projects/eye-tracking/"
lang: "en"
---

# Eye-Tracking Smart Home for People with Spinal Cord Injuries

People with severe spinal cord injuries (SCI) often depend on someone else for the smallest change in their room. This system gives some of that control back: a camera follows the user's eyes, the user looks at a command on a panel and confirms it, and an IoT controller carries it out.

Image processing runs in MATLAB. A custom “Six Segmented” method finds the pupil, estimates where the user is looking, and keeps working with head rotation of up to 20 degrees. A statistically weighted average discards bad samples, which brought correct command recognition to 97%. Tracking works in visible light, and an infrared ring around the camera keeps it working below 5 lux; at night, a fixed gaze turns on the light and opens nine preset emergency SMS messages.

The controller is an Arduino Mega 2560 with a SIM800L cellular module. It drives 10 relay outputs (bed position, lights, temperature) and can send an emergency SMS or call a caregiver. From looking at a command to its execution takes under 10 seconds. The project was carried out with the support of the State Welfare Organization of Khorasan Razavi, and its results were published in Modern Care Journal in 2019.

- **97%** of commands recognized correctly in tests
- **< 10 s** from a look to the action
- **10** relay outputs: bed, lights, temperature

## At a glance

- Non-invasive: nothing is attached to the user.
- 97% of commands recognized correctly in tests.
- Under 10 seconds from look to action.
- Works regardless of age, gender, glasses, hairstyle, facial hair or headscarf.
- User authentication on the network to block unauthorized access.

- Read the paper: https://doi.org/10.5812/modernc.96107

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