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AI allows a paralyzed person to control the robotic hand with brain signals

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Researchers from UC San Francisco have reached a great breakthrough in brain-computer interface technology (BCI), which allows people with paralysis to control robotic devices only through thought.

This innovation combines Artificial intelligence (AI) of neurology, which allows a paralyzed person to manipulate robotic hand, imagining movements, a feat, which means a significant milestone in the restoration of autonomy with serious motor disorders.

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Brain interface technology (BCI) (UC San Francisco)

Brain-Computer Interface: New Management Era

A device known as Brain interface (BCI), is a fusion of advanced II and nervous engineering. BCIS previously fought for maintaining functionality for long periods, often losing efficiency in just one day. However, the recently developed BCI installed a record, functioning freely for seven months, without requiring serious adjustments.

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The key is the ability of the AI ​​model to adapt to subtle changes in brain activity over time. Because people repeatedly represent the movements, II clarifies their understanding of these nerve signals, which allows for more accurate control over robotic devices. Dr. Karunesh Ganguli, a neurologist and professor of UCSF, emphasized that this adaptive learning between people and II is crucial to achieve realistic functionality in neuroprotection.

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Brain interface technology (UC San Francisco)

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Understanding brain changes: Science behind the breakthrough

Dr. Gangul’s research It turned out that while the form of brain activity remains consistent, their location changes slightly from day to day. This discovery explains why the previous BPS quickly lost the ability to interpret nerve signals.

To solve this problem, Ganguli and his team studied a participant who was paralyzed by a stroke years earlier. The implanted sensors on the surface of his brain recorded nerve signals, as he imagined movements such as hiding or lifting objects. For two weeks, these signals were used to train AI to account for daily shifts in brain activity models.

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Brain interface technology (UC San Francisco)

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From virtual practice to success in the real world

Initially, the participant practiced, controlled the virtual robotic hand that provided feedback on his imaginary movements. This training helped to clarify its ability to visualize accurate actions. After he moved to the use of a true robotic hand, he quickly mastered tasks such as picking up blocks, opening cabinets and even holding a cup under the water dispenser.

A few months later, the participant retained his ability to control the robotic hand with a minimum reconstruction, emphasizing the long -term reliability of the BTI.

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Brain interface technology (UC San Francisco)

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The consequences for people with paralysis

This innovative technology has deep consequences for people with paralysis. Tasks such as feeding yourself or access to water may significantly improve the quality of life. Dr. Gangula optimisticly evaluates the refinement of II to further increase the speed and fluidity when checking the system at home.

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Brain interface technology (UC San Francisco)

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The integration of the adaptive II into the BPP means a new exciting chapter in a neuroprotetic, which offers hope for millions that live with paralysis worldwide. With the help of constant achievements, these systems can soon restore the necessary functions and independence, turning life in this way when they considered it impossible.

Because interfaces that work on AI begin to offer new independence to people with paralysis, which, in your opinion, the most important steps in the development of these technologies to improve everyday life for those who have suffered? Tell us by writing us in Cyberguy.com/contact

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