Possibly you'd also enjoy

ultrasonic therapy for the deep brain

a contribution to support biomedical research

It will be useful for people with mobility difficulties and paralyzed patients to be able to control robotic equipment non-invasively using only their thoughts.

BCIs have been proven to attain good performance for controlling robotic equipment using solely the signals detected from brain implants. When robotic devices can be operated with great precision, they may be employed to execute a range of daily chores. To date, however, BCIs successful in constantly commanding robotic arms have utilized invasive brain implants. In addition to the expense and possible hazards to individuals, installing and operating these implants appropriately requires a significant degree of medical and surgical knowledge. They have only been used in a few clinical situations as a result.

The development of less invasive, or even entirely noninvasive, technology that would enable paralyzed individuals to command their surroundings or robotic limbs with their own "thoughts" is a major problem in BCI research this noninvasive BCI technology is effective, it might be made available to the general public as well as a large number of patients.

The "dirtier" signals that are received by BCIs that don't rely on brain implants hurt resolution and control precision. Thus, a noninvasive BCI falls short of requiring implanted devices when controlling a robotic arm using solely the brain. Despite this, BCI researchers continue to work hard in pursuit of a less- or non-invasive technology that may benefit people daily all over the world.

One significant discovery at a time is how Bin He, department director and professor of biomedical engineering at Carnegie Mellon University, is attaining this aim.

"Brain implants have enabled significant advancements in mind-controlled robotic technology. He argues that the science is superb. The ultimate objective is to be noninvasive. The future development of noninvasive neurorobotics will be significantly impacted by developments in brain decoding and the practical usability of noninvasive robotic arm control.

He and his group have achieved high-resolution control over a robotic arm by accessing signals from deep within the brain using unique sensing and machine-learning approaches. He is overcoming the noisy EEG data, improving EEG-based brain decoding, and enabling continuous real-time 2D robotic device control using noninvasive neuroimaging and a unique continuous pursuit paradigm.

He has demonstrated in human subjects that a robotic arm can now follow the cursor constantly using a non-invasive BCI to operate one that is monitoring a cursor on a computer screen. A moving cursor was previously followed by robotic arms operated by humans noninvasively in jerky, discontinuous motions as if the robotic arm were attempting to "catch up" to the brain's orders. Now, the arm follows the cursor in a smooth, continuous course.

The team developed a new framework for BCI that addresses and enhances the "brain" and "computer" components by enhancing user training and engagement as well as the spatial resolution of noninvasive neural data through EEG source imaging. The framework was described in a paper that was published in Science RoboticsOpens in a new window.

The study, "Noninvasive neuroimaging enhances continuous neural tracking for robotic device control," demonstrates how the team's original approach to the issue improved continuous tracking of a computer cursor by more than 500% and BCI learning by almost 60% for conventional center-out tasks.

This work is a significant development in the field of non-invasive brain-computer interfaces, which might one day be as common as smartphones among assistive devices.

The technology also has uses that might benefit a range of individuals by enabling secure, non-intrusive "mind control" of objects that let users interact with and regulate their surroundings. The technology has so far been tested on 68 healthy human volunteers (up to 10 sessions per person), and tasks including directing a robotic arm for continuous chasing were included. The team intends to perform clinical studies soon because the technique immediately benefits patients.

The use of noninvasive signals presents technological obstacles, but He asserts that "we are fully committed to bringing this safe and practical technology to people who can benefit from it." This research offers a significant step toward noninvasive brain-computer interfaces, a field of study that someday could lead to everyone being helped by omnipresent assistive technology like cellphones.

The National Institute of Neurological Disorders and Stroke, the National Institute of Biomedical Imaging and Bioengineering, the National Institute of Mental Health, and the National Center for Complementary and Integrative Health all provided funding in part for this research.