Handicapped patients that have lost the ability to use their limbs and torso and therefore are unable to use a conventional joystick currently have limited ways of controlling a wheelchair.

Realising that methods such as blowing air into a sensor or using a chin stick can be exhausting, we came up with the idea of building a brain-controlled electric wheelchair: the patient thinks about where they want the wheelchair to go, and it then heads in that direction.

The brain-controlled wheelchair system comprises of four main units: a brain signals detector; a laptop; an electric wheelchair; and an interface unit. The brain signals detector consists of electrodes that are placed on the patient’s scalp and connected to signal processing circuits. In this project, we have used an Emotiv EEG Neuroheadset with multiple electrodes.

Data acquired by the brain signals detector is filtered, amplified, and converted to digital form. The digital data is processed by laptop using special software. After processing the data, specific features are extracted and classified to determine the desired direction of motion.

The command related to the desired direction of motion is then sent to the interface through a USB- serial RS232 port. The interface, equipped with an Arduino microcontroller, receives the command from the laptop, interprets it and sends the appropriate signal to the wheelchair motor controller that in turn provides the right amount of power from the battery to each motor to produce the desired motion.

Another important feature of this system is an Android App developed for the automatic transmission of messages to the mobile phone of an assistant or relative to alert them about some difficulties faced by the user such as low battery life or a significant displacement of the brain signals detector.

 The system has been implemented successfully and has been tested under various operating conditions. The electric wheelchair used in this project was provided by the Al Thiqah Club for Handicapped in Sharjah, UAE. However, the system can also be implemented with other types of electric wheelchairs. We are currently enhancing the capabilities of this system by using various types of motion and proximity sensors to provide feedback to the wheelchair system regarding its surroundings and thus the ability to avoid obstacles in the direction of motion.

The objective of our project is to provide a reliable and functional system that would take humanity one step further in aiding less fortunate handicapped patients by offering them a better and more independent life.