EEG-Controlled Wheelchair Project: Innovations in Mobility
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Introduction
This innovative project centers around a wheelchair that can be operated through EEG signals. The inspiration stemmed from an article discussing mind-controlled wheelchairs. As part of the school's Innovation Program, we frequently engage with students to explore potential research projects for the academic year. One group decided to pursue this project for two key reasons: it offered an opportunity to create a practical solution for individuals in need, particularly those facing mobility challenges, and it presented a unique challenge of integrating an EEG headset with a wheelchair. The students were eager to determine the feasibility of developing a functional prototype.
The primary goal of this project is to assist individuals facing various mobility-related challenges, including:
- Complete dependence on caregivers for those without limbs or those with significant motor impairments.
- Partial paralysis, restricting them to basic motor functions such as blinking.
- The desire for autonomy among individuals with intact cognitive functions who are otherwise unable to move independently.
Quadriplegics, who have lost the use of all four limbs, and paraplegics, who can still move their upper body to some degree, are the primary beneficiaries of this technology.
EEG Technology Overview
Electroencephalography (EEG) is a non-invasive technique used to assess and record brain activity. It operates on the principle that all mammals, including humans, generate low-frequency electrical signals known as brain waves. EEG captures these signals to create a continuous graph of their frequencies and amplitudes over time. This technology is often employed to diagnose conditions such as epilepsy and sleep disorders.
Brain activity is monitored through electrodes placed on the scalp, measuring voltage changes resulting from ionic currents in the brain's neurons. EEG recordings from multiple electrodes allow for comprehensive analysis of brain activity. The primary brainwave frequencies are as follows:
- Gamma Waves: Linked to learning and processing new information.
- Beta Waves: Associated with logical and analytical thinking.
- Alpha Waves: Connected to calmness and mental coordination.
- Theta Waves: Present during deep sleep and meditation.
- Delta Waves: Indicate deep relaxation and tranquility.
In this project, EEG technology is embedded in a wheelchair, enabling users with limited mobility to navigate by concentrating on specific thoughts while connected to the chair’s brain sensors via electrodes. These sensors detect signals when users intend to move in different directions, eliminating the need for physical controls like levers or joysticks.
Incorporating Eye Movement Detection
In addition to EEG, we utilized Electrooculography (EOG) to record eye movements, which helps in detecting blinks and rapid eye movements (saccades). This technique relies on the electrical changes caused by muscle activity around the eyes, providing measurable signals that we can use for wheelchair activation.
Neurosky's Mindwave Mobile headset can also detect blinks using EOG, where a spike in EOG data indicates a blink event. For our project, we achieved blink detection through an eye blink listener integrated within Neurosky's Android SDK, which outputs blink strength values ranging from 0 to 255.
Hardware and Software Components
We employed an OEM TGAM Module EEG Sensor Brainwave Neurosky Mindwave Arduino kit for reading brainwaves and detecting blinks. Given the high cost of the current Neurosky Mindwave Mobile headsets, our team opted for this more affordable solution, compatible with both Android and iOS devices through Bluetooth connectivity.
The HC-06 Bluetooth module serves as a wireless link, connecting the Arduino Uno microcontroller to an Android device, facilitating data transmission. The HC-06 module indicates the connection status via an LED light, ensuring seamless communication between devices.
An Android application was developed to function as the data receptor and transmitter, receiving information from the EEG headset and relaying it to the Arduino. This setup enables users to operate their devices while wearing the EEG headset.
The Arduino microcontroller processes the data received from the Android application into commands that control the wheelchair's movements, allowing for navigation in multiple directions.
Motor Control and Operation
Using an L298N motor driver module, we controlled the miniature wheelchair's motors. This popular driver can manage multiple DC motors, making it suitable for our project's needs. The Arduino Uno board orchestrates the entire system, processing data from the Android application to facilitate wheelchair movement.
The TGAM Module Mindwave EEG Sensor and HC-06 Bluetooth module work in tandem, with the Android application acting as an intermediary. This design choice enhances user safety by filtering out irrelevant data before it reaches the Arduino, which ultimately controls the wheelchair's motors.
Testing and Future Directions
The EEG-based wheelchair control system shows great promise in enhancing the quality of life for individuals with disabilities. The team believes this technology can significantly improve mobility but acknowledges that further research is necessary before widespread implementation.
This video showcases the development and testing of the EEG-controlled wheelchair, demonstrating its potential applications and the technology behind it.
This video provides insights into the Arduino Starter Kit TGAM Module, highlighting its use with the Neurosky Brainwave EEG Sensor and SDK for mindwave feedback and control.
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