communication system for paralyzed patients
Communication is the most important part of human life, but due to some unfortunate events (medical condition/accidents) humans are unable to communicate or deliver a message and therefore they are unable to interact with their environment which hinders their day to day life. According to the study
2025-06-28 16:30:51 - Adil Khan
communication system for paralyzed patients
Project Area of Specialization Artificial IntelligenceProject SummaryCommunication is the most important part of human life, but due to some unfortunate events (medical condition/accidents) humans are unable to communicate or deliver a message and therefore they are unable to interact with their environment which hinders their day to day life. According to the study (in 2013), there are nearly 1 in 50 people living with some sort of paralysis – approximately 5.4 million people. That's the same number of people as the combined populations of Los Angeles, Philadelphia, and Washington D.C. In order to resolve the communication problem for paralyzed patients our aim is build such a device through which user will be able to control a cursor using only his eye blink and eyeball movement on a designated GUI (graphical user interface) and through this GUI user will communicate with his respective surroundings. This device will use computer vision techniques, such as pattern recognition using convolutional neural networks (CNN) to control cursor via eye blink and eyeball movements. The proposed system will be tested and implemented on the both available and locally generated datasets.
Project Objectives- To design such a system that is able to detect eye blink and eye ball movements of paralyzed patients.
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Through this device user will be able to translate the movements to control the cursor appearing on the provided screen.
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A designated GUI( graphical user interface) will be provided through which user will be perform specific tasks by selecting different buttons
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Implementing the tested algorithms on raspberrypi in order to make a standalone embedded system
Python is the most useful programming language to work on AI, we will be implementing algorithms using python to detect the main key points, user will be able to perform specific task on designated GUI, those task will allow a disable person to communicate with the real world.
Once the ROI finding algorithms are working fine we will be implementing them on RPI along with the camera to take real time input and a screen to display the GUI and output.
Disabled persons will be having a proper device to communicate with the world just using his eye, there a number of deseases which make the body of human paralyzed and make them unable to even speak and move body musceles.
Their are various types of paralysis as explained in the picture below, patients having the ability to move his or her eyeball and blink are in the scope of our project and can take complete benifit from it.
A raspberry pi-4 based stand alone system taking the facial features of the patient using computer vision to detect the movement of eyeball and eyeblink and syncing it with the GUI to perform specific task such as ' I need water' ,'I am in pain', 'yes i agree' etc.
GUI will also be a python based GUI using Tkinter, it might be a keyboard or a suitable GUI that will be displaying on the screen attached with RPI.
For the keypoint selection we will be using facial landmarks based on CNN(Convolutional Neural Network) which will help us to generate our ROI(Region Of Intrest).
Final Deliverable of the Project HW/SW integrated systemCore Industry HealthOther IndustriesCore Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 77000 | |||
| Logitech C930E HD Business Webcam 1080p webcam with wide field of view | Equipment | 1 | 34000 | 34000 |
| Raspberry pi 4 gb Ram | Equipment | 1 | 16000 | 16000 |
| 7 inch HDMI capacitive touch lcd screen for raspberry pi | Equipment | 1 | 8000 | 8000 |
| Speakers | Equipment | 1 | 4000 | 4000 |
| 16 gb sd card for rpi | Equipment | 1 | 1000 | 1000 |
| 8mp rpi camera v2 | Equipment | 1 | 4000 | 4000 |
| chargers, supplies, hdmi cables, cases,cooling fans, prints etc | Miscellaneous | 1 | 10000 | 10000 |