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Rehabilitation for Motor Dysfunction Eased By Brain-Machine Interface (BMI)

by Karishma Abhishek on Jul 22 2021 11:46 PM

Quality of life for people with motor dysfunction or paralysis might be improved using a new wearable brain-machine interface (BMI) system.

Rehabilitation for Motor Dysfunction Eased By Brain-Machine Interface (BMI)
Quality of life for people with motor dysfunction or paralysis, or even locked-in syndrome (when a person is fully conscious but unable to move or communicate) might be improved using a new wearable brain-machine interface (BMI) system as per a study at the Georgia Institute Of Technology, published in the journal Advanced Science.
The study team combined wireless soft scalp electronics and virtual reality in a BMI system for allowing the user to imagine an action and wirelessly control a wheelchair or robotic arm.

The Motor Imagery-Based BMI System

"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

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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.

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"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.

Source-Medindia


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