Lifeboat Foundation

In a new study published in Scientific Reports, researchers have uncovered a phenomenon known as the “phantom touch illusion,” where individuals experience tactile sensations without actual physical contact in a virtual reality (VR) setting. This intriguing discovery raises questions about how the brain processes sensory information.

Previous research has shown that our nervous system can differentiate between self-generated touch and touch from external sources, a process often described as tactile gating. This ability helps us understand our interactions with the world around us.

When you perform an action that results in self-touch, your brain anticipates this contact. It knows that the sensation is a result of your own movement. Because of this anticipation, the brain ‘turns down the volume’ on the sensory response. Essentially, it partially “cancels” or gates out the sensation because it’s expected and self-generated. This is why you can’t effectively tickle yourself – your brain knows the touch is coming and reduces the response.

In the exercise, an engineer equipped with a set of virtual reality (VR) goggles is orchestrating the robot’s actions.

Advanced proposition.

Continue reading “IHMC’s Nadia: A task-ready humanoid robot with a boxing edge” »

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In the grand theater of the cosmos, amidst a myriad of distant suns and ancient galaxies, the Fermi Paradox presents a haunting silence, where a cacophony of alien conversations should exist. Where is Everyone? Or are we alone?

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Meta, the parent company of Facebook, has made a groundbreaking development in brain-computer interface technology. They have unveiled an AI system that can decode visual representations and even “hear” what someone is hearing by studying their brainwaves. These advancements in brain-machine interface technology have the potential to transform our relationship with artificial intelligence and its potential applications in healthcare, communication, and virtual reality.

The University of Texas at Austin has developed a new technology that can translate brain activity into written text without surgical implants. This breakthrough uses functional Magnetic Resonance Imaging (fMRI) scan data to reconstruct speech. An AI-based decoder then creates text based on the patterns of neuronal activity that correspond to the intended meaning. This new technology could help people who have lost the ability to speak due to conditions such as stroke or motor neuron disease.

Despite the fMRI having a time lag, which makes tracking brain activity in real-time challenging, the decoder was still able to achieve impressive accuracy. The University of Texas researchers faced challenges in dealing with the inherent “noisiness” of brain signals picked up by sensors, but by employing advanced technology and machine learning, they successfully aligned representations of speech and brain activity. The decoder works at the level of ideas and semantics, providing the gist of thoughts rather than an exact word-for-word translation. This study marks a significant advance in non-invasive brain decoding, showcasing the potential for future applications in neuroscience and communication.

An artificial sensory system that is able to recognize fine textures—such as twill, corduroy and wool—with a high resolution, similar to a human finger, is reported in a Nature Communications paper. The findings may help improve the subtle tactile sensation abilities of robots and human limb prosthetics and could be applied to virtual reality in the future, the authors suggest.

Humans can gently slide a finger on the surface of an object and identify it by capturing both static pressure and high-frequency vibrations. Previous approaches to create artificial tactile sensors for sensing physical stimuli, such as pressure, have been limited in their ability to identify real-world objects upon touch, or they rely on multiple sensors. Creating a real-time artificial sensory system with high spatiotemporal resolution and sensitivity has been challenging.

Chuan Fei Guo and colleagues present a flexible slip sensor that mimics the features of a human fingerprint to enable the system to recognize small features on surface textures when touching or sliding the sensor across the surface. The authors integrated the sensor onto a prosthetic human hand and added machine learning to the system.

Throughout history, sonar’s distinctive “ping” has been used to map oceans, spot enemy submarines and find sunken ships. Today, a variation of that technology – in miniature form, developed by Cornell researchers – is proving a game-changer in wearable body-sensing technology.

PoseSonic is the latest sonar-equipped wearable from Cornell’s Smart Computer Interfaces for Future Interactions (SciFi) lab. It consists of off-the-shelf eyeglasses outfitted with micro sonar that can track the wearer’s upper body movements in 3D through a combination of inaudible soundwaves and artificial intelligence (AI).

With further development, PoseSonic could enhance augmented reality and virtual reality, and track detailed physical and behavioral data for personal health, the researchers said.

XRHealth, HTC Vive and Nord-Space Aps engineered the Vive Focus 3 headset to withstand microgravity conditions to help treat astronauts’ mental health in space.

Researchers have developed a virtual reality application where a range of 3D modeling tools can be opened and controlled using just the movement of a user’s hand.

The researchers, from the University of Cambridge, used machine learning to develop ‘HotGestures’—analogous to the hot keys used in many desktop applications.

HotGestures give users the ability to build figures and shapes in virtual reality without ever having to interact with a menu, helping them stay focused on a task without breaking their train of thought.

Minimizing the use of sedatives during operations could shorten hospital stays and reduce the risk of complications.