Posted in | Medical Robotics

New Study Develops Brain-Controlled Robotic Arm

Research subjects at the University of Minnesota fitted with a specialized noninvasive brain cap were able to move the robotic arm just by imagining moving their own arms. (Credit: College of Science and Engineering)

In a major breakthrough, researchers from the University of Minnesota have developed a robotic arm that can be controlled using the mind. This breakthrough has immense potential to help millions of paralyzed people or those suffering from neurodegenerative diseases.

The paper was published online in the Nature research journal Scientific Reports, on 14th December, 2016.

This is the first time in the world that people can operate a robotic arm to reach and grasp objects in a complex 3D environment using only their thoughts without a brain implant. Just by imagining moving their arms, they were able to move the robotic arm.

Bin He, Biomedical Engineering Professor, University of Minnesota

This non-invasive method is known as electroencephalography (EEG) based brain-computer interface. It uses a specialized, high-tech EEG cap equipped with 64 electrodes, to record weak electrical activity of the subjects’ brain, and uses machine learning and advanced signal processing to convert the “thoughts” into action.

Eight healthy human subjects wore the EEG cap and completed the experimental sessions of the research. They gradually learned to imagine moving their arms while not actually moving them in order to manipulate a robotic arm in 3D space. The subjects started by learning how to move a virtual cursor on computer screen, after which they learned to move a robotic arm to reach for and grab hold of objects at fixed places on a table.

They eventually learned to reach for and grab hold of objects at random places on the table and move the objects from said table to a three-layer shelf by merely thinking these movements.

All of the subjects were able to control the robotic arm to lift objects from fixed places with an average success rate of more than 80%. There was an average success rate more than 70% with regard to moving objects from the table to the shelf.

This is exciting as all subjects accomplished the tasks using a completely noninvasive technique. We see a big potential for this research to help people who are paralyzed or have neurodegenerative diseases to become more independent without a need for surgical implants.

Bin He, Biomedical Engineering Professor, University of Minnesota

According to the researchers, the geography of motor cortex or the area of the cerebrum that is responsible for governing movement is the reason for the operation of the brain-computer interface technology. Tiny electric currents are produced by neurons in the motor cortex when humans think about movement or move.

A new assortment of neurons is activated when humans think about a different movement. He’s previous research has confirmed this phenomenon through cross-validation using functional MRI. He said that the groundwork for the recent brain-computer interface study was laid by sorting these assortments with advanced signal processing.

The recent research builds upon a study conducted three years ago by He. In this earlier research, the noninvasive EEG technology was used to help subjects fly a small quadcopter. This study gained international media attention.

Three years ago, we weren’t sure moving a more complex robotic arm to grasp and move objects using this brain-computer interface technology could even be achieved. We’re happily surprised that it worked with a high success rate and in a group of people.

Bin He, Biomedical Engineering Professor, University of Minnesota

According to He, the next step of his study will be to develop the brain-computer interface technology to achieve a robotic prosthetic limb connected to a patient’s body and is controlled by brain, or to see how the technology can be used to help a person who is paralyzed or has suffered a stroke.  

In addition to Professor He, who is also the director of the University of Minnesota Institute for Engineering in Medicine, the other members of the research team are biomedical engineering postdoctoral researcher Jianjun Meng (first author); biomedical engineering graduate student Bryan Baxter; Institute for Engineering in Medicine staff member Angeliki Bekyo; and biomedical engineering undergraduate students Shuying Zhang and Jaron Olsoe. The researchers are affiliated with the University of Minnesota College of Science and Engineering and the Medical School.

The National Science Foundation (NSF), National Institute of Biomedical Imaging and Bioengineering, the National Center for Complementary and Integrative Health, and National Institute of Neurological Disorders and Stroke of the National Institutes of Health (NIH), and the University of Minnesota’s MnDRIVE (Minnesota’s Discovery, Research and InnoVation Economy) Initiative funded by the Minnesota Legislature financially supported the study.

College of Science and Engineering, UMN/Youtube.com

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