Electroencephalography Controlled Wheelchair

This project is basically an IOT based project. In this project we are using EEG device to get the signals from the human brain and translate them into the computerized analog signals these are inputted into the algorithm implemented in pyth

Project Title

Electroencephalography Controlled Wheelchair

Project Area of Specialization

Internet of Things

Project Summary

This project is basically an IOT based project. In this project we are using EEG device to get the signals from the human brain and translate them into the computerized analog signals these are inputted into the algorithm implemented in python language that analyze the signals and apply the results on the actuators. Technically, after applying actuators (motors, GPS tracker) on the wheelchair we have to transmit the computerized signals from EEG to the edge device (Raspberry pi) connected to cloud storage through internet and have algorithms in it that analyze the signals and transmits the output to the micro-controller that implements the output on the actuators. There is GPS tracker on the wheelchair that locate the location of the wheelchair on the application that is installed on the caretaker smartphone. By using this application caretaker is able to check the current location of the patient and trace the movement of the patient wheelchair. In some condition caretaker can able to overwrite the command of the EEG device using mobile application that implemented on the wheelchair through edge device using cloud storage and wheelchair is able to move using mobile application.

Project Objectives

Our project objectives are

1. Attachment of actuators on wheelchair and setting up edge device on wheel chair.
2. Connection of the EEG headset with edge device and setting up cloud storage.
3. Implementation of Machine learning based algorithom model and model training using EEG Signal processing.
4. Creation of mobile application and connecting to the cloud storage.

Project Implementation Method

Design phase

• Designing phase includes the designing of the wheelchair using actuators, edge device and headset that make the wheelchair to move.
• After that we have to design the algorithm based on python language that translate the signals from the headset into commands and by using these commands micro-controller assign work to the actuators.
• Designing of application that provides the caretaker to keep track the location and movement of the patient.

Implementation phase

• Implementation of wheelchair includes the connection and implementation of the actuators on the wheelchair wheels, these actuators will connect to the micro-controller (embedded in Raspberry pi), the edge device (Raspberry pi) connected to the EEG headset by the means of Bluetooth, the GPS tracker will also connected to the wheelchair that trace the location and transfer it to cloud storage using edge device.
• Implementation of the algorithm based on the python language that burns on the edge device where all the calculation and translation of the computerized analog signal into the commands, then these commands will transmitted to the actuators using the microcontroller that is also embedded in the edge device.
• Implementation of the application will be done in React native language. Application consist of the login page and the home page. Home page contains the map which pointing the location of the wheelchair and the movement of the wheelchair will be show in the map. Application have also some emergency extra functions to control the wheelchair by overwriting the commands from the EEG device using the cloud storage that is directly connected to the edge device.    

Testing phase

• Testing is most important phase of any project that make the projects to achieve its goals. So, for the testing purpose we decide to use the unit testing approach during the each step of the   implementation of the project. After the completion of the each implementation step we will run the integration test that verifies us that all the components are connected well and working as its required. After the completion of all the implementation steps we will run the System test that verifies us that the system is working perfectly and ready for the acceptance test.

Evaluation phase

• We will evaluate the final results of the project using the EEG signals simulated graphs, algorithm performance chart and patient performance charts.

Benefits of the Project

• Empowering Disabled Persons 

By using this wheelchair the disable people will able to move anywhere independently.

• Brain Controlled Wheelchair

This EEG technology automates the wheelchair in the new perspective then previous.

• Patient Tracking

Patient can able to track by using the mobile application that where patient is moving on the wheelchair.

• Provide Patient Data

By using the dataset generated using wheelchair will able caretaker to predict the patient movement???????

Technical Details of Final Deliverable

The technical details of the final deliverable of the EEG controlled wheelchair are as follows

Software Deliverables: 

• Alogorithm: 

Algorithm is implemented for converting brain signals into the mental commands using Cortex api provided by the emotiv company for creating  application by getting direct access to the brain signals from any program implemented in python and other programming languages.

• Mobile Application:

Mobile application created for the caretaker of the patient. Implemented in the react native framework using the cloud storage. mobile application is connected with the edge device and GPS tracker in the wheelchair that transmits each and every information of the patient headset like condition, stress rate, relax rate, battery etc. Using the GPS traker in the wheelchair caretaker can able to track the location of the patient wheelchair using google map api. In special cases caretaker is able to overwrite the mentel commands using application through cloud storage to the edge device comming from the headset.

Hardware Deliverables:   

•  Electroencephalography Controlled Wheelchair:

Wheelchair consist of the four integrated components 

1. Emotiv EEG headset
2. Edge device (Raspberry pi 3)
3. GPS module
4. Actuators (motors and breaks)

Headset connected with the raspberry using bluetooth 4.0 and transmits its signal to the raspberry here signal are interpretated using the algorithm and then generated mental commands are transmitted to the actuators i.e motors using motor driver controller L298N and motor moves. Cloud storage is storing all the information from heatset and mobile application. Here the GPS tracker modul is connected with the raspberry pi that continously transmitting the current location of the wheelchair into cloud storage and caretaker is getting the live location of the wheelchair in application.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Medical

Other Industries

Energy , Health

Core Technology

Internet of Things (IoT)

Other Technologies

NeuroTech, Wearables and Implantables

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure, Reduced Inequality

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com