‘Quality of life for people with motor dysfunction or paralysis or even locked-in syndrome might be improved using a new wearable brain-machine interface (BMI) system. The technology employs soft wireless circuits to offer improved signal acquisition with powerful machine learning algorithms and virtual reality.’
“The major advantage of this system to the user, compared to what currently exists, is that it is soft and comfortable to wear, and doesn’t have any wires,” says Yeo, associate professor on the George W. Woodruff School of Mechanical Engineering.
A person’s brain signals (neural activity) are generally analyzed and translated into commands that are then turned into intentions and then actions in a BMI systems-based rehabilitation technology.
One of the most common non-invasive methods for acquiring these signals is through ElectroEncephaloGraphy (EEG). However, the technique has shortcomings like a tangled web of wires, heavily relying on gels, and often encounters artifacts or ancillary “noise”.
The Advanced Technology
The newly designed portable EEG system employs microneedle electrodes with soft wireless circuits to offers improved signal acquisition and integrated with a powerful machine learning algorithm and virtual reality.
This allows for accurate, high-quality control of thoughts – motor imagery. Although the technique has been tested on 4 humans, it is yet to be analyzed in disabled ones.
“This new brain-machine interface uses an entirely different paradigm, involving imagined motor actions, such as grasping with either hand, which frees the subject from having to look at too much stimuli,” says Mahmood, a Ph. D. student in Yeo’s lab.
The team focuses on further advancing the integration of this technology.