Combining new classes of nanomembrane electrodes with flexible electronics and a deep learning algorithm could help disabled people wirelessly control an electric wheelchair, interact with a computer or operate a small robotic vehicle without donning a bulky hair-electrode cap or contending with wires. For more information see the IDTechEx report on Neuroprosthetics 2018-2028: Technologies, Forecasts, Players.

 

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. The project, conducted by researchers from the Georgia Institute of Technology, University of Kent and Wichita State University, was reported in the journal Nature Machine Intelligence.

 

“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,” said 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. “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.”

 

Learn more at the next leading event on the topic: Printed Electronics USA 2019 External Link on 20 – 21 Nov 2019 at Santa Clara Convention Center, CA, USA hosted by IDTechEx.