People With Disability Can Control Wheelchairs With This New Brain-Machine Interface

Georgia Tech has just made a new BMI (stand for brain-machine interface) by combining a new deep learning algorithm, flexible electronics, and a new class of nano-membrane electrode. This invention is expected to help people with disability control devices wirelessly. The new BMI can cover devices like a computer, an electric wheelchair, and a robotic vehicle without the users bothering themselves with wires or hair-electrode cap.

This BMI proves to be an enhancement in comparison with the traditional EEG, which can measure the signals from potentials evoked visually in the brain. The new BMI has been tested on six human subjects in measuring EEG but not on a person with disability.

According to the researchers, BMI plays an important part in helping people with severe motor disabilities like chronic stroke and ALS to take control of their prosthetic systems. For now, to measure virtually evoked potentials, the patient must wear a hair cap studded with electrodes, wire, and plenty of adhesives.

This new system of BMI involves wireless and flexible electronics and sensors that can be applied easily to the skin. The telemetry unit will receive data via Bluetooth. A flexible circuit will process the EEG data and then send them to a computer to be interpreted. The wireless range of the system is 15 meters.

The system calls for three elastomeric scalp electrodes kelp on the head by a fabric band. There are also sensors on the patient’s neck and electrode under their ears. All of the electrodes need no gel and adhesive as they are soft and dry.

The next step in the researchers’ study is to test the new BMI system on disabled individuals. Woon-Hong Yeo, Georgia Tech's assistant professor said that this creation could serve as the foundation for smart home systems, assistive devices, and neuro-gaming interfaces.