Disabled people could soon wirelessly control an electric wheelchair or interact with a computer without the need for a bulky hair-electrode cap, according to a new research project.
A collaborative project between researchers from the Georgia Institute of Technology, University of Kent and Wichita State University showed that combining new classes of nanomembrane electrodes with flexible electronics and a deep learning algorithm could provide a wireless solution.
By providing a fully portable, wireless brain-machine interface (BMI), the wearable system could offer an improvement over conventional electroencephalography (EEG) for measuring signals from visually evoked potentials in the human brain.
The system’s ability to measure EEG signals for BMI has been evaluated with six human subjects, but has not been studied with disabled individuals.
Woon-Hong Yeo, an assistant professor in Georgia Tech’s George W. Woodruff School of Mechanical Engineering and Wallace H. Coulter Department of Biomedical Engineering, said: “This work reports fundamental strategies to design an ergonomic, portable EEG system for a broad range of assistive devices, smart home systems and neuro-gaming interfaces.”
“The primary innovation is in the development of a fully integrated package of high-resolution EEG monitoring systems and circuits within a miniaturized skin-conformal system.”
BMI is an essential part of rehabilitation technology that allows those with amyotrophic lateral sclerosis (ALS), chronic stroke or other severe motor disabilities to control prosthetic systems.
Gathering brain signals known as steady-state virtually evoked potentials (SSVEP) currently requires use of an electrode-studded hair cap that uses wet electrodes, adhesives and wires to connect with computer equipment that interprets the signals.