BCI based system for aiding disable person for independent movement

The brain-computer interface is designed for physically disabled people's wheelchairs. The suggested system's architecture is based on receiving, processing, and classifying data, then controlling the wheelchair. Human control instructions of the wheelchair have been used in various experiments to m

Project Title

BCI based system for aiding disable person for independent movement

Project Area of Specialization

NeuroTech

Project Summary

The brain-computer interface is designed for physically disabled people's wheelchairs. The suggested system's architecture is based on receiving, processing, and classifying data, then controlling the wheelchair. Human control instructions of the wheelchair have been used in various experiments to monitor brain activity, and it is the technology that allows you to control your computer using your thoughts. Electroencephalography records brain waves so that a computer can analyze them. Various studies have used BCI, including measuring brain waves in people. Because of the many things that can be done with BCI, many researchers are utilizing it to develop smart wheelchairs that employ brain control. And improvements are still being made to produce the best system possible. In this study, we employ a still-under-development subject, the BCI-based wheelchair, in which we record and analyze brain waves while doing cognitive tasks like moving hands, walking, jogging, and so on. This record will be used as a data reference to start the computer operation that will move the wheelchair. This research intends to operate the wheelchair utilizing BCI and the Neurosky Mind wave headset to get motor motions. The data from one electrode are examined by concentration and meditation levels in this headset, which contains one electrode. This project is more portable than traditional EEG data-gathering equipment, which is bulky and includes several channels. Furthermore, this headset can wirelessly transmit data to a PC (Personal Computer) through Bluetooth, allowing the signal to be analyzed and categorized into five-movement classes using Mat lab, including default/motionless, forward, backward, right, and left. The approach for the wheelchair was to replace the default joystick in the electric wheelchair with a self-made controller module based on brain waves signals acquired from the headset that was processed and categorized by Matlab before being transmitted to Arduino Uno to drive the wheelchair's motor.

Project Objectives

We found a solution better solution for all types of paralyzed people, such as some people who cannot walk, can’t talk, and even a total disabled people; this wheelchair is especially for them. The smartness of a wheelchair depends on the Neurosky headset. It takes the signals from the mind and moves forward towards the microprocessor, and signals depend upon the patient’s mental condition.

• We navigate wheelchair-using BCI.
• We help disabled people.
• We make a freehand wheelchair with a muscle brain signal.
• We analyze alpha, beta, gamma, and other rays generated by the human brain.

Project Implementation Method

Patients who are disabled or have significant physical limitations have restricted mobility in their surroundings. Electroencephalogram (EEG) signals are being exploited to develop novel communication and control mechanisms between humans and computers. The Brain-Computer Interface (BCI) is an aggressive communication and control option in the user-system interface. This technique allows brain impulses to control specific external activity. The "Brain-Machine Interface (BMI)" is another name for the BCI system. The Neurosky in the BCI system collects signals from the human scalp. The experimental findings revealed that EEG signals are acquired from the dataset and that once received, the signals are processed, and the wheelchair is controlled.

Benefits of the Project

• It allows paraplegic persons to use their minds to operate prosthetic limbs.
• Transmit visual pictures to a blind person's consciousness, enabling them to see.
• Transmit audio data to a deaf person's consciousness to enable them to hear.
• It allows gamers to use their thoughts to control video games.
• It enables a deaf person's thoughts to be shown and spoken by a computer.

Technical Details of Final Deliverable

The brain signal control architecture is based on fuzzy means classification and the gradient descent technique. The 100 percent classification findings show that the approaches utilized are a viable choice for EEG signal classification in the construction of a brain-based control wheelchair. In the future, we plan to increase the number of commands for controlling the wheelchair, reduce the detection time of the EEG signal used to measure brain processes, and build a brain-controlled wheelchair that is efficient.

• We will provide a prototype solution.
• We will drive a wheelchair by brain signals.
• We will provide solutions for paralyzed people.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

Medical

Core Technology

NeuroTech

Other Technologies

Robotics

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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