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AI allows paralyzed man control robotic arm using brain signals

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Researchers from UC San Francisco achieved a remarkable advancement in brain-computer interaction (BCI) technologies, enabling individuals who have paralysis to operate robotic devices by thought alone. This innovation combines artificial (AI) and neuroscience, allowing paralyzed men to manipulate robotic arms by imagining movement.

Brain-computer interface (BCI) technology (UC San Francisco)

The brain-computer interface: A new era of control

The device, known as a brain-computer interface (BCI), represents a fusion of advanced AI and neural engineering. BCIs have previously struggled to maintain functionality over extended periods, often losing effectiveness after just one or two days. However, the newly developed BCI has set a record by functioning seamlessly for seven months without requiring major adjustments.

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It is the AI model’s ability to adapt over time to subtle changes in brain activities that makes it so effective. As people imagine movements repeatedly, the AI improves its understanding of neural signals. This allows for more precise control of robot devices. Dr. Karunesh Ganguly, neurologist at UCSF and professor, stressed that this adaptive learning between AI and humans is crucial for achieving lifelike function in neuroprosthetics.

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Brain-computer interface technology (UC San Francisco)


Understanding brain changes: Science behind the breakthrough

The research of Dr. Ganguly revealed that, while the shape and location of brain activity representations remain constant, they shift slightly day to day. This discovery explains how previous BCIs lost their ability quickly to interpret neural signals.

Ganguly and team studied a participant paralyzed from a stroke that occurred years earlier to address this challenge. Sensors implanted in his brain surface recorded neural signals while he imagined movements such as grasping or lifting an object. These signals were used over a period of two weeks to train an AI model that could account for daily changes in brain activity patterns.

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Brain-computer interface technology (UC San Francisco)

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From Virtual Practice to Real-World Success

At first, the participant practiced control of a virtual robotic hand that provided feedback on imagined movements. This training helped him refine his ability visualize precise actions. He quickly mastered tasks like picking up blocks, opening cupboards, and holding a cup underneath a water dispenser.

The participant was able to control the robotic hand with minimal recalibration months later, highlighting its long-term reliability.

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Brain-computer interface technology (UC San Francisco)


This revolutionary technology has profound implications on individuals with paralysis. The ability to feed oneself and access water independently could dramatically improve quality of living. Dr. Ganguly believes that the AI can be improved to improve speed and fluidity of movement in the home environment.

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Brain-computer interface technology (UC San Francisco)

Kurt’s key takeaways

The integration of adaptive AI into BCIs marks an exciting new chapter in neuroprosthetics, offering hope for millions living with paralysis worldwide. With continued advancements, these systems could soon restore essential functions and independence, transforming lives in ways once thought impossible.

As AI-powered brain-computer interfaces begin to offer new independence to individuals with paralysis, what do you think are the most important next steps in developing these technologies to improve daily life for those affected? Let us know by writing us at
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