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Wearable Electronics Demonstrate Promise of Brain-Machine Interfaces

Research conducted by a new member of the bioengineering faculty at the University of California, San Diego has demonstrated that a thin flexible, skin-like device, mounted with tiny electronic components, is capable of acquiring electrical signals from the brain and skeletal muscles and potentially transmitting the information wirelessly to an external computer.

The development, published Aug. 12 in the journal Science, means that in the future, patients struggling with reduced motor or brain function, or research subjects, could be monitored in their natural environment outside the lab. For example, a person who struggles with epilepsy could wear the device to monitor for signs of oncoming seizures.

It also opens up a slew of previously unimaginable possibilities in the field of brain-machine interfaces well beyond biomedical applications, said Professor Todd Coleman, who joined the Department of Bioengineering at the UC San Diego Jacobs School of Engineering this summer. Until now, Coleman said, this brain-machine interface has been limited by the clunky, artificial coupling required by a vast array of electronic components and devices.

“The brain-machine interface paradigm is very exciting and I think it need not be limited to thinking about prosthetics or people with some type of motor deficit,” said Coleman. “I think taking the lens of the human and computer interacting, and if you could evolve a very nice coupling that is remarkably natural and almost ubiquitous, I think there are applications that we haven’t even imagined. That is what really fascinates me – really the coupling between the biological system and the computer system.”

Coleman co-led the multidisciplinary team that developed the device while working as a professor of electrical and computer engineering and neuroscience at the University of Illinois last year. The device is made of a thin sheet of plastic covered with a water-soluble layer that sticks to skin after washing with water. Once applied, the plastic dissolves, leaving the electronic components imprinted into the skin like a temporary tattoo.

Coleman said he had been thinking about how to record brain and muscle electrical signals in a way that doesn’t limit the subject’s ability to move about in a natural setting when he saw a presentation by University of Illinois engineering professor John Rogers, who developed the flexible electronic device. Currently, electrical signals from the brain and skeletal muscle are collected through electroencephalography (EEG) and electromyography (EMG), respectively. EEG and EMG diagnostics involve mounting plastic electrodes to the body with adhesives or clamps, applying a conductive gel and attaching it all to boxes of circuit boards, power supplies and communications devices. EEGs and EMGs also typically require a person to be monitored in a lab setting, removing them from the rich and dynamic environments in which they normally operate. The research team showed that a wide array of electrical components, including sensors, transistors, power supplies such as solar cells and wireless antennas, could be combined on a single device that is nearly unnoticeable by the wearer.

In addition to Rogers, who was the main enabler of the technology with his expertise in stretchable electronics, the project was led by Northwestern University Mechanical Engineering Professor Yonggang Huang, who optimized the mechanical properties of the device, and Coleman, who helped define and demonstrate the utility of the device in biomedical applications. Coleman’s research group, with combined backgrounds in electrical engineering and neuroscience, helped in the circuit design for active electrodes to enable efficient coupling between the device and brain waves without the need for a conductive gel, and in the statistical signal processing required to reliably acquire the neural signals from the brain or muscles through Rogers’ device. For example, Coleman’s research group used the device to enable someone to control a computer game with muscles in his throat by speaking the commands. In principle, the same function could have been achieved by simply mouthing commands rather than speaking them out loud. This was done by applying a pattern-recognition algorithm implemented by Coleman’s group to data taken from a throat-based EMG. Now that the capability has been demonstrated, the next step is to integrate all the components onto a single device. Coleman believes the ramifications for health care are significant at a time when people are living longer but suffering more neurological problems like Parkinson’s disease and dementia.

“If you think about the advances that are being made in artificial hips and rehabilitation and the fact that people are living longer, it is no longer the case that your body is giving up before your mind,” said Coleman. “It’s going to be increasingly the case that we need to think about fixing minds along with fixing bodies.”

What’s Possible When Brains and Computers Work Together?
Understanding the performance capabilities that could be achieved by an efficient union between brains and machines is a central theme of Coleman’s research and he envisions endless applications in areas such as military operations, gaming, education and consumer electronics. For example, the ability to communicate with a computer without actually verbalizing your message out loud clearly benefits patients with muscular or neurological disorders such as amyothropic lateral sclerosis, also known as Lou Gehrig’s disease. But its discrete tattoo-like appearance makes it useful for covert military operations requiring the operator to communicate with a remote command station. In this scenario, the operator could mouth what he needs to say using the muscles in his throat to transmit an electrical signal.

At UC San Diego, Coleman is exploring what other capabilities could be achieved by the coupling of brain signals with computers, enabling two decision makers to cooperate to achieve a common goal. For example, by simultaneously acquiring the neural signals of many people collaborating with computers, this technology could enable the whole group to operate as a team with enhanced capabilities.

“Ideally, you want them to cooperate to achieve a common goal and new theoretical approaches are needed to optimize the nature of their interaction. What is also crucially important is designing an effective interface between the brain and the machine where this neurosignal acquisition takes place,” said Coleman. “So if you can develop a better interface so that you can get a richer class of signals, you could potentially achieve levels of performance that cannot be attained otherwise.”

The research was funded by the National Science Foundation and the Air Force Research Laboratory.

Catherine Hockmuth | Newswise Science News
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