The advanced brain-computer interface was developed by Distinguished Professor Chin-Teng Lin and Professor Francesca Iacopi, from the UTS Faculty of Engineering and IT, in collaboration with the Australian Army and Defence Innovation Hub. As well as defence applications, the technology has significant potential in fields such as advanced manufacturing, aerospace and healthcare -- for example allowing people with a disability to control a wheelchair or operate prosthetics. "The hands-free, voice-free technology works outside laboratory settings, anytime, anywhere. It makes interfaces such as consoles, keyboards, touchscreens and hand-gesture recognition redundant," said Professor Iacopi. "By using cutting edge graphene material, combined with silicon, we were able to overcome issues of corrosion, durability and skin contact resistance, to develop the wearable dry sensors," she said.

Aerial robots, on the other hand, are not so resilient. Poke holes in the robot's wing motors or chop off part of its propellor, and odds are pretty good it will be grounded. Inspired by the hardiness of bumblebees, MIT researchers have developed repair techniques that enable a bug-sized aerial robot to sustain severe damage to the actuators, or artificial muscles, that power its wings -- but to still fly effectively. They optimized these artificial muscles so the robot can better isolate defects and overcome minor damage, like tiny holes in the actuator. In addition, they demonstrated a novel laser repair method that can help the robot recover from severe damage, such as a fire that scorches the device.

To avoid a bottleneck of bots, a team of MIT engineers is designing a kit of universal robotic parts that an astronaut could easily mix and match to rapidly configure different robot "species" to fit various missions on the moon. Once a mission is completed, a robot can be disassembled and its parts used to configure a new robot to meet a different task. The team calls the system WORMS, for the Walking Oligomeric Robotic Mobility System. The system's parts include worm-inspired robotic limbs that an astronaut can easily snap onto a base, and that work together as a walking robot. Depending on the mission, parts can be configured to build, for instance, large "pack" bots capable of carrying heavy solar panels up a hill.

Researchers from the University of Cambridge carried out a study in a tech consultancy firm using two different robot wellbeing coaches, where 26 employees participated in weekly robot-led wellbeing sessions for four weeks. Although the robots had identical voices, facial expressions, and scripts for the sessions, the robots' physical appearance affected how participants interacted with it. Participants who did their wellbeing exercises with a toy-like robot said that they felt more of a connection with their'coach' than participants who worked with a humanoid-like robot. The researchers say that perception of robots is affected by popular culture, where the only limit on what robots can do is the imagination. When faced with a robot in the real world however, it often does not live up to expectations.

Dejan Milutinovic, professor of electrical and computer engineering at UC Santa Cruz, has long worked with colleagues on the complex subset of game theory called differential games, which have to do with game players in motion. One of these games is called the wall pursuit game, a relatively simple model for a situation in which a faster pursuer has the goal to catch a slower evader who is confined to moving along a wall. Since this game was first described nearly 60 years ago, there has been a dilemma within the game -- a set of positions where it was thought that no game optimal solution existed. But now, Milutinovic and his colleagues have proved in a new paper published in the journal IEEE Transactions on Automatic Control that this long-standing dilemma does not actually exist, and introduced a new method of analysis that proves there is always a deterministic solution to the wall pursuit game. This discovery opens the door to resolving other similar challenges that exist within the field of differential games, and enables better reasoning about autonomous systems such as driverless vehicles.

Virtual reality gamers (VR game) who finished it faster than their fellow gamers also have higher levels of general intelligence and processing capacity. This was the result of a study conducted by the University of Cologne, the University of Liechtenstein and Vorarlberg University of Applied Sciences. The results also indicate that virtual reality games can be useful supplementary human resource management tools in companies for predicting the job performance of an applicant. The study "Intelligence at play: game-based assessment using a virtual-reality application" by Markus Weinmann of the University of Cologne and his fellow scientists was published in the journal Virtual Reality. Several studies have already shown that video games may indicate or even help to develop intellectual and cognitive abilities.

"With the successful execution of our model, we predicted the association of highly significant cardiovascular disease genes tied to demographic variables like race, gender and age." said Zeeshan Ahmed, a core faculty member at the Rutgers Institute for Health, Health Care Policy and Aging Research (IFH) and lead author of the study, published in Genomics. According to the World Health Organization, cardiovascular disease is the leading cause of death globally, yet it is estimated that more than 75 percent of premature cardiovascular disease is preventable. Atrial fibrillation and heart failure contribute to about 45 percent of all cardiovascular disease deaths. Despite significant advancements in cardiovascular disease diagnostics, prevention and treatment, about half of the affected patients reportedly die within five years of receiving a diagnosis because of a variety of reasons. Researchers said the use of AI and machine learning can accelerate our ability to identify genes that have important implications for cardiovascular disease, which can lead to improvements in diagnoses and treatment.

Using artificial intelligence, Cornell University engineers have simplified … In this work, the group developed four machine learning models for …

In a new study published November 28 in Annals of Neurology, an artificial intelligence platform called DystoniaBoTXNet used brain MRIs to automatically identify which patients would respond to botulinum toxin treatment with 96.3 percent accuracy. Such a platform can inform clinicians' treatment decisions, according to senior study author Kristina Simonyan, MD, PhD, Dr med, director of Laryngology Research at Mass Eye and Ear, a member of Mass General Brigham, and professor of Otolaryngology-Head and Neck Surgery at Harvard Medical School. "Typically, a patient with dystonia would undergo a series of dose- and location-finding injections to determine whether botulinum toxin relieves their symptoms. Injections are painful and costly," said Dr. Simonyan. "Yet, some may find no benefits from this treatment despite multiple injection attempts, while some might benefit from injections but give up after only one dose or forgo the treatment altogether. With this artificial intelligence algorithm, we can empower clinicians and patients in their therapeutic decision-making by providing them with an objective tool to replace the trial-and-error approach to botulinum toxin efficacy."

The study used "connectome-based predictive modeling" to compare five theories about how the brain gives rise to intelligence, said Aron Barbey, a professor of psychology, bioengineering and neuroscience at the University of Illinois Urbana-Champaign who led the new work with first author Evan Anderson, now a researcher for Ball Aerospace and Technologies Corp. working at the Air Force Research Laboratory. "To understand the remarkable cognitive abilities that underlie intelligence, neuroscientists look to their biological foundations in the brain," Barbey said. "Modern theories attempt to explain how our capacity for problem-solving is enabled by the brain's information-processing architecture." A biological understanding of these cognitive abilities requires "characterizing how individual differences in intelligence and problem-solving ability relate to the underlying architecture and neural mechanisms of brain networks," Anderson said. Historically, theories of intelligence focused on localized brain regions such as the prefrontal cortex, which plays a key role in cognitive processes such as planning, problem-solving and decision-making.