{"id":49950,"date":"2025-09-02T15:23:16","date_gmt":"2025-09-02T12:23:16","guid":{"rendered":"https:\/\/forklog.com\/en\/?p=49950"},"modified":"2025-09-02T15:25:10","modified_gmt":"2025-09-02T12:25:10","slug":"scientists-develop-non-invasive-ai-bci","status":"publish","type":"post","link":"https:\/\/forklog.com\/en\/scientists-develop-non-invasive-ai-bci\/","title":{"rendered":"Scientists Develop Non-Invasive AI-BCI"},"content":{"rendered":"<p>Researchers at the University of California, Los Angeles (UCLA) have developed a wearable non-invasive <span data-descr=\"a system that enables direct interaction between the human brain and an external device (computer, robot, prosthesis, etc.) without the involvement of muscles and sensory organs\" class=\"old_tooltip\">brain-computer interface (BCI)<\/span> using AI as a &#8220;co-pilot,&#8221; reports <a href=\"https:\/\/neurosciencenews.com\/ai-bci-movement-neurotech-29649\/\">Neuroscience News<\/a>.<\/p>\n<p>The system allows for more precise and faster control of a robotic arm or cursor.<\/p>\n<p>The device translates brain signals, captured via electroencephalography, into movement commands. Special algorithms have been developed to decode these impulses.<\/p>\n<p>AI cameras interpret the user&#8217;s intentions in real time. This system enables tasks to be completed significantly faster than without AI support.<\/p>\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>&#8220;By using artificial intelligence in addition to brain-computer interface systems, we aim to find much less risky and non-invasive approaches,&#8221; commented Jonathan Kao, the study&#8217;s lead researcher and assistant professor of electrical and computer engineering at UCLA&#8217;s Samueli School of Engineering.<\/p>\n<\/blockquote>\n<p>In tests, four participants, including one paralyzed individual, completed tasks significantly faster with AI support. Some tasks would have been impossible without it.<\/p>\n<p>In the first task, participants were asked to move a computer mouse cursor across the screen between eight targets, pausing for at least half a second on each. The second test required moving blocks on a table using a robotic arm.<\/p>\n<p>The paralyzed participant completed the robotic arm task in about six and a half minutes with AI support, whereas without it, the task was unachievable.<\/p>\n<p>Scientists believe this breakthrough will aid in developing safer and more accessible assistive technologies for individuals with paralysis or motor impairments.<\/p>\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>&#8220;Ultimately, we want to create AI-BCI systems with combined control that will allow people with motor impairments, such as paralysis or <span data-descr=\"amyotrophic lateral sclerosis\" class=\"old_tooltip\">ALS<\/span>, to regain some independence in daily activities,&#8221; Kao emphasized.<\/p>\n<\/blockquote>\n<p>Current BCI devices with surgical implants can translate brain signals into commands, but they carry high risks and are costly.<\/p>\n<p>Meanwhile, wearable and external gadgets show lower reliability in recognizing brain signals.<\/p>\n<p>In April, a woman paralyzed after a stroke <a href=\"https:\/\/forklog.com\/en\/news\/ai-restores-speech-to-paralyzed-woman-after-18-years\">regained her speech<\/a> after 18 years of silence thanks to an experimental BCI and artificial intelligence.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at the University of California have developed a wearable non-invasive brain-computer interface (BCI) using AI as a &#8220;co-pilot.&#8221;<\/p>\n","protected":false},"author":1,"featured_media":26216,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"select":"1","news_style_id":"1","cryptorium_level":"","_short_excerpt_text":"UCLA develops non-invasive AI-BCI for faster robotic control.","creation_source":"","_metatest_mainpost_news_update":false,"footnotes":""},"categories":[3],"tags":[438,1812],"class_list":["post-49950","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-analysis","tag-artificial-intelligence","tag-brain-computer-interface-bci"],"aioseo_notices":[],"amp_enabled":true,"views":"201","promo_type":"1","layout_type":"1","short_excerpt":"UCLA develops non-invasive AI-BCI for faster robotic control.","is_update":"","_links":{"self":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/49950","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/comments?post=49950"}],"version-history":[{"count":1,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/49950\/revisions"}],"predecessor-version":[{"id":49951,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/49950\/revisions\/49951"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/media\/26216"}],"wp:attachment":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/media?parent=49950"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/categories?post=49950"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/tags?post=49950"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}