brain-computer interface Archives - Amazing Health Advances

New Brain-Computer Interface Allows Man with ALS to ‘Speak’ Again

The AHA! Team — Fri, 11 Oct 2024 08:20:41 +0000

UC Davis Health via Newswise – Technology developed by UC Davis Health restores interpersonal communication A new brain-computer interface (BCI) developed at UC Davis Health translates brain signals into speech with up to 97% accuracy — the most accurate system of its kind. The researchers implanted sensors in the brain of a man with severely impaired speech due to amyotrophic lateral sclerosis (ALS). The man was able to communicate his intended speech within minutes of activating the system. A study about this work was published today in the New England Journal of Medicine. ALS, also known as Lou Gehrig’s disease, affects the nerve cells that control movement throughout the body. The disease leads to a gradual loss of the ability to stand, walk and use one’s hands. It can also cause a person to lose control of the muscles used to speak, leading to a loss of understandable speech. The new technology is being developed to restore communication for people who can’t speak due to paralysis or neurological conditions like ALS. It can interpret brain signals when the user tries to speak and turns them into text that is ‘spoken’ aloud by the computer. “Our BCI technology helped a man with paralysis to communicate with friends, families and caregivers,” said UC Davis neurosurgeon David Brandman. “Our paper demonstrates the most accurate speech neuroprosthesis (device) ever reported.” Brandman is the co-principal investigator and co-senior author of this study. He is an assistant professor in the UC Davis Department of Neurological Surgery and co-director of the UC Davis Neuroprosthetics Lab. The new BCI breaks the communication barrier When someone tries to speak, the new BCI device transforms their brain activity into text on a computer screen. The computer can then read the text out loud. To develop the system, the team enrolled Casey Harrell, a 45-year-old man with ALS, in the BrainGate clinical trial. At the time of his enrollment, Harrell had weakness in his arms and legs (tetraparesis). His speech was very hard to understand (dysarthria) and required others to help interpret for him. In July 2023, Brandman implanted the investigational BCI device. He placed four microelectrode arrays into the left precentral gyrus, a brain region responsible for coordinating speech. The arrays are designed to record the brain activity from 256 cortical electrodes. “We’re really detecting their attempt to move their muscles and talk,” explained neuroscientist Sergey Stavisky. Stavisky is an assistant professor in the Department of Neurological Surgery. He is the co-director of the UC Davis Neuroprosthetics Lab and co-principal investigator of the study. “We are recording from the part of the brain that’s trying to send these commands to the muscles. And we are basically listening into that, and we’re translating those patterns of brain activity into a phoneme — like a syllable or the unit of speech — and then the words they’re trying to say.” Faster training, better results Despite recent advances in BCI technology, efforts to enable communication have been slow and prone to errors. This is because the machine-learning programs that interpreted brain signals required a large amount of time and data to perform. “Previous speech BCI systems had frequent word errors. This made it difficult for the user to be understood consistently and was a barrier to communication,” Brandman explained. “Our objective was to develop a system that empowered someone to be understood whenever they wanted to speak.” Harrell used the system in both prompted and spontaneous conversational settings. In both cases, speech decoding happened in real time, with continuous system updates to keep it working accurately. The decoded words were shown on a screen. Amazingly, they were read aloud in a voice that sounded like Harrell’s before he had ALS. The voice was composed using software trained with existing audio samples of his pre-ALS voice. At the first speech data training session, the system took 30 minutes to achieve 99.6% word accuracy with a 50-word vocabulary. “The first time we tried the system, he cried with joy as the words he was trying to say correctly appeared on-screen. We all did,” Stavisky said. In the second session, the size of the potential vocabulary increased to 125,000 words. With just an additional 1.4 hours of training data, the BCI achieved a 90.2% word accuracy with this greatly expanded vocabulary. After continued data collection, the BCI has maintained 97.5% accuracy. “At this point, we can decode what Casey is trying to say correctly about 97% of the time, which is better than many commercially available smartphone applications that try to interpret a person’s voice,” Brandman said. “This technology is transformative because it provides hope for people who want to speak but can’t. I hope that technology like this speech BCI will help future patients speak with their family and friends.” The study reports on 84 data collection sessions over 32 weeks. In total, Harrell used the speech BCI in self-paced conversations for over 248 hours to communicate in person and over video chat. “Not being able to communicate is so frustrating and demoralizing. It is like you are trapped,” Harrell said. “Something like this technology will help people back into life and society.” “It has been immensely rewarding to see Casey regain his ability to speak with his family and friends through this technology,” said the study’s lead author, Nicholas Card. Card is a postdoctoral scholar in the UC Davis Department of Neurological Surgery. “Casey and our other BrainGate participants are truly extraordinary. They deserve tremendous credit for joining these early clinical trials. They do this not because they’re hoping to gain any personal benefit, but to help us develop a system that will restore communication and mobility for other people with paralysis,” said co-author and BrainGate trial sponsor-investigator Leigh Hochberg. Hochberg is a neurologist and neuroscientist at Massachusetts General Hospital, Brown University and the VA Providence Healthcare System. Brandman is the site-responsible principal investigator of the BrainGate2 clinical trial. The trial is enrolling participants. To learn more about the study, visit braingate.org or contact braingate@ucdavis.edu. A complete list of coauthors and funders is available in the article. Caution: Investigational device. Limited by Federal law to investigational use. To read the original article click here.

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BrainGate: First Human Use of High-Bandwidth Wireless Brain-Computer Interface

AHA Publisher — Wed, 07 Apr 2021 07:00:48 +0000

Brown University via Newswise – PROVIDENCE, R.I. [Brown University and Providence Veterans Affairs Medical Center] — Brain-computer interfaces (BCIs) are an emerging assistive technology, enabling people with paralysis to type on computer screens or manipulate robotic prostheses just by thinking about moving their own bodies. For years, investigational BCIs used in clinical trials have required cables to connect the sensing array in the brain to computers that decode the signals and use them to drive external devices. Now, for the first time, BrainGate clinical trial participants with tetraplegia have demonstrated use of an intracortical wireless BCI with an external wireless transmitter. The system is capable of transmitting brain signals at single-neuron resolution and in full broadband fidelity without physically tethering the user to a decoding system. The traditional cables are replaced by a small transmitter about 2 inches in its largest dimension and weighing a little over 1.5 ounces. The unit sits on top of a user’s head and connects to an electrode array within the brain’s motor cortex using the same port used by wired systems. For a study published in IEEE Transactions on Biomedical Engineering, two clinical trial participants with paralysis used the BrainGate system with a wireless transmitter to point, click and type on a standard tablet computer. The study showed that the wireless system transmitted signals with virtually the same fidelity as wired systems, and participants achieved similar point-and-click accuracy and typing speeds. “We’ve demonstrated that this wireless system is functionally equivalent to the wired systems that have been the gold standard in BCI performance for years,” said John Simeral, an assistant professor of engineering (research) at Brown University, a member of the BrainGate research consortium and the study’s lead author. “The signals are recorded and transmitted with appropriately similar fidelity, which means we can use the same decoding algorithms we used with wired equipment. The only difference is that people no longer need to be physically tethered to our equipment, which opens up new possibilities in terms of how the system can be used.” The researchers say the study represents an early but important step toward a major objective in BCI research: a fully implantable intracortical system that aids in restoring independence for people who have lost the ability to move. While wireless devices with lower bandwidth have been reported previously, this is the first device to transmit the full spectrum of signals recorded by an intracortical sensor. That high-broadband wireless signal enables clinical research and basic human neuroscience that is much more difficult to perform with wired BCIs. The new study demonstrated some of those new possibilities. The trial participants — a 35-year-old man and a 63-year-old man, both paralyzed by spinal cord injuries — were able to use the system in their homes, as opposed to the lab setting where most BCI research takes place. Unencumbered by cables, the participants were able to use the BCI continuously for up to 24 hours, giving the researchers long-duration data including while participants slept. “We want to understand how neural signals evolve over time,” said Leigh Hochberg, an engineering professor at Brown, a researcher at Brown’s Carney Institute for Brain Science and leader of the BrainGate clinical trial. “With this system, we’re able to look at brain activity, at home, over long periods in a way that was nearly impossible before. This will help us to design decoding algorithms that provide for the seamless, intuitive, reliable restoration of communication and mobility for people with paralysis.” The device used in the study was first developed at Brown in the lab of Arto Nurmikko, a professor in Brown’s School of Engineering. Dubbed the Brown Wireless Device (BWD), it was designed to transmit high-fidelity signals while drawing minimal power. In the current study, two devices used together recorded neural signals at 48 megabits per second from 200 electrodes with a battery life of over 36 hours. While the BWD has been used successfully for several years in basic neuroscience research, additional testing and regulatory permission were required prior to using the system in the BrainGate trial. Nurmikko says the step to human use marks a key moment in the development of BCI technology. “I am privileged to be part of a team pushing the frontiers of brain-machine interfaces for human use,” Nurmikko said. “Importantly, the wireless technology described in our paper has helped us to gain crucial insight for the road ahead in pursuit of next generation of neurotechnologies, such as fully implanted high-density wireless electronic interfaces for the brain.” The new study marks another significant advance by researchers with the BrainGate consortium, an interdisciplinary group of researchers from Brown, Stanford and Case Western Reserve universities, as well as the Providence Veterans Affairs Medical Center and Massachusetts General Hospital. In 2012, the team published landmark research in which clinical trial participants were able, for the first time, to operate multidimensional robotic prosthetics using a BCI. That work has been followed by a steady stream of refinements to the system, as well as new clinical breakthroughs that have enabled people to type on computers, use tablet apps and even move their own paralyzed limbs. “The evolution of intracortical BCIs from requiring a wire cable to instead using a miniature wireless transmitter is a major step toward functional use of fully implanted, high-performance neural interfaces,” said study co-author Sharlene Flesher, who was a postdoctoral fellow at Stanford and is now a hardware engineer at Apple. “As the field heads toward reducing transmitted bandwidth while preserving the accuracy of assistive device control, this study may be one of few that captures the full breadth of cortical signals for extended periods of time, including during practical BCI use.” The new wireless technology is already paying dividends in unexpected ways, the researchers say. Because participants are able to use the wireless device in their homes without a technician on hand to maintain the wired connection, the BrainGate team has been able to continue their work during the COVID-19 pandemic. “In March 2020, it became clear that we would not be able to visit our research participants’ homes,” said Hochberg, who is also a critical care neurologist at Massachusetts General Hospital and director of the V.A. Rehabilitation Research and Development Center for Neurorestoration and Neurotechnology. “But by training caregivers how to establish the wireless connection, a trial participant was able to use the BCI without members of our team physically being there. So not only were we able to continue our research, this technology allowed us to continue with the full bandwidth and fidelity that we had before.” Simeral noted that, “Multiple companies have wonderfully entered the BCI field, and some have already demonstrated human use of low-bandwidth wireless systems, including some that are fully implanted. In this report, we’re excited to have used a high-bandwidth wireless system that advances the scientific and clinical capabilities for future systems.” To read the original article click here.

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Electrical Stimulation Could Restore Vision in Blind People

AHA Publisher — Fri, 10 Jul 2020 07:00:40 +0000

University of Zurich via News-Medical Net – In a project under Horizon 2020, researchers from seven European organizations will examine how the vision of visually impaired people can be restored using electrical stimulation of the brain. The project is being coordinated by the University of Zurich and supported by the European Union with funding of 4 million euros. If a project receives funding from the European Union, it must involve excellent science in innovative and promising interdisciplinary research fields that provide new and relevant ideas for industry and society. The international Neural Active Visual Prosthetics for Restoring Function project meets all these criteria and has been awarded an EU research grant totaling 4 million euros over four years. The project will kick off on 1 September 2020 and is being coordinated by Prof. Shih-Chii Liu at the Institute of Neuroinformatics of the University of Zurich. Working in interdisciplinary teams from seven European universities and institutions with complementary expertise in computational, systems and clinical neuroscience, materials engineering, microsystems design, and deep learning, the project will develop technology to restore the vision of blind people through electrical stimulation of the brain. Close Interdisciplinary Cooperation The aim of the project is to develop a neuroprosthesis with thousands of electrodes driven by adaptive machine learning algorithms for a new brain-computer interfacing technology. “We want to create a novel neuroprosthesis system that is lightweight, robust and portable, and which will remain effective for decades,” explains Shih-Chii Liu. Current systems only stimulate a small set of neurons in the brain, and interfaces have longevity of only a few months. Liu is convinced that the project will succeed in its goals: “All the partners have long-time experience in their respective fields, so the required background knowledge is already in place. The breakthroughs will come with the planned larger-scale efforts and partner interactions in this project.” The challenge will be coordinating the expected breakthroughs across multiple disciplines. Establishing Innovation These breakthroughs include innovative approaches for stimulation with high-electrode-count interfacing with the visual cortex. For this, thin flexible probes are needed that cause minimal tissue damage as well as new electrode coatings and novel microchip methods. The researchers will also channel the stimulation currents to many thousands of electrodes and monitor neuronal activity in higher cortical areas. Breakthroughs are also expected when it comes to artificial neural networks trained by deep learning, which will only extract the most relevant visual information from a camera input to enable blind individuals to recognize objects and facial expressions and navigate through unfamiliar environments. These networks will transform the camera footage into stimulation patterns that drive the neurons in a way that the blind person can interpret. This is the only way that the signals can be processed and passed on. At the same time, eye tracking will be used to improve perception in a closed-loop approach. The Algorithm Translates Stimulation Patterns In addition to coordinating the project, the University of Zurich is also contributing to its technological expertise. The neuroinformatics team of Shih-Chii Liu and Tobi Delbruck will be working with consortium partners to develop power-efficient neuromorphic deep learning hardware and algorithms. The network implemented on the neuromorphic hardware will translate camera input into stimulation patterns to drive the stimulation electrodes. This research project is important because it lays ground-breaking work for constructing a new brain neuroprosthesis and brings added benefits to other neuroprosthesis research.” Shih-Chii Liu, Professor, Institute of Neuroinformatics, University of Zurich The involved researchers hope that the project will raise Europe’s still relatively low profile in this research field. To read the original article click here.

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URI Engineering Professor Helping ALS Patients Use Their Brains to Communicate

AHA Publisher — Wed, 01 Jul 2020 07:00:20 +0000

University of Rhode Island via Newswise – Doug Sawyer was diagnosed with amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig’s disease, 11 years ago. His only muscles that still function are those that control eye movement. Despite his disability, Sawyer still works as an engineer from his home, designing electronics for Hayward Industries. Using only his eyes, the 57-year-old writes reports and other papers, draws pictures and schematics, talks on the phone, sends text messages and emails, and attends meetings online multiple times a week. However, Sawyer’s gaze weakens as he gets tired, causing the technology he currently uses to become ineffective. That’s why the Seekonk, Massachusetts resident was eager to work with University of Rhode Island Assistant Professor Yalda Shahriari to develop a new way for ALS patients to communicate. Shahriari and her team of student researchers in URI’s College of Engineering are developing a way for those with severe motor deficits such as ALS to communicate using brain signals, eliminating the need for patients to maintain fine eye-gaze control. Her project, funded by a National Science Foundation (NSF) grant, has two main goals. The first is to develop multimodal personalized algorithms to improve the robustness of the brain-computer interface (BCI) systems for patients with severe motor deficits. The second is to develop an autonomous hybrid system for non-communicative patients who are without residual motor control, such as those who lose their fine eye-gaze control in the late stages of ALS. Through longitudinal recordings taken of several patients with ALS during this and previous projects, Shahriari and her group have noticed significant day-to-day variations in brain-computer interface performance. “These variations are speculated to be associated with several factors, including cognitive fluctuations and environmental factors,” said Shahriari. “Developing personalized algorithms will enable us to predict these fluctuations and optimize performance based on each patient’s specifications and needs.” To ensure more accurate readings of brain activity, two non-invasive techniques are implemented simultaneously: electroencephalogram (EEG) and functional Near Infrared Spectroscopy (fNIRS) signals. EEG detects electrical activity in the brain using small, metal discs called electrodes. Functional Near Infrared Spectroscopy is an optical imaging technique in which an emitter transmits near infrared light and a detector detects the light reflected from the surface of the brain. This technique measures oxygen changes in the concentration of hemoglobin in the brain. The higher the concentration, the more activity is taking place. “We will use a hybrid of EEG and fNIRS signals to compensate for each neuroimaging modality shortage and use the complementary features obtained from each modality to improve our system,” said Shahriari. For patients in the later stages of ALS who experience cognitive dysfunction, such as memory loss and the inability to maintain eye gaze on objects, Functional Near Infrared Spectroscopy has shown to be a more accurate method of measurement. Shahriari and her students have developed a visuo-mental dual task paradigm which relies on conventional oddball-based protocols, but require the subjects to do some mental arithmetic tasks. This BCI approach is accomplished by displaying a grid of letters and numbers and intermittently flashing an image (matrix of digits) over each row and column. “By giving the patient higher demanding tasks to focus on, we can trigger several cognitive functions and extract the associated signatures or neural biomarkers,” said doctoral student Bahram Borgheai. “The computer can then decode the pattern of neural activities that appear after the patient performs the tasks. The patterns can be used for diagnostic and communication purposes.” Shahriari has collaborated with the National Center for Adaptive Neurotechnologies on projects since 2012. With the support of the national center, the Rhode Island Chapter of the ALS Association and Rhode Island Hospital, the professor would like to add more patients to the study. “Our analysis of the data becomes much more powerful if we can significantly increase the number of patients in the study,” said Shahriari. Patients will be asked to wear a cap with sensors attached that can record brain activity in the comfort of their homes or at a care center. Recordings of those with healthy brains will take place in Shahriari’s Neural Processing and Control Laboratory in URI’s Fascitelli Center for Advanced Engineering. All data processing and analysis will be conducted in the lab. Once enough patients have volunteered to participate in the research project, Shahriari plans to partner with more local hospitals and medical schools to take advantage of their clinical expertise. Sawyer has relished the opportunity to participate in the study. “Taking part in the brain activity study has been very rewarding,” said Sawyer. “I enjoy learning new things and staying abreast of the latest technology. Dr. Shahriari and her team have been willing to share their progress. They make me feel as if I’m part of their team and not just a test number.” Sawyer hopes that his participation will help Shahriari develop a way for ALS patients to work and communicate after their motor functions have ceased. “I don’t consider myself a victim of ALS and I don’t consider myself handicapped,” Sawyer said. “I just need help sometimes. There are people out there far worse off than me. Hopefully the time I give to Dr. Shahriari will someday improve their lives.” To read the original article click here.

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