
NGoggle: VR boosts glaucoma detection
Researchers launch study to compare wearable brain-based device called 'NGoggle' with conventional detection methods.
Researchers launch study to compare wearable brain-based device called 'NGoggle' with conventional detection methods.
Novel design of brain chip implant allows for measuring neuronal activity while simultaneously delivering drugs to the implant site.
Hongyu Chen has developed a wearable sensor system for the continuous monitoring of neonatal seizures.
The intention of a continuous movement was able to be read out from non-invasive brain signals.
Researchers investigated whether a humanoid robot's gaze influences the way people reason in a social decision-making context.
To enhance human-robot collaboration, researchers at Loughborough University have trained an AI to detect human intention.
Scientists have developed a bio-compatible implantable AI platform that classifies in real time healthy and pathological patterns in biological signals.
A wearable brain-machine interface system could improve the quality of life for people with motor dysfunction or paralysis, even those struggling with locked-in syndrome.
Researchers warn of the potential social, ethical, and legal consequences of technologies interacting heavily with human brains.
Researchers recorded VR users' brain activity using electroencephalography (EEG) to better understand and work toward solutions to prevent cybersickness.
A neuroscientist at University of Texas at Austin wants to democratize the field and support infrastructure.
Researchers have evaluated whether data derived solely from these wristbands could accurately predict various types of seizures in pediatric patients.
Researchers have succeeded in making an AI understand our subjective notions of what makes faces attractive.
A subset of wearables are the so-called hearables – in-ear devices that are well suited for long-term monitoring as they are non-invasive, inconspicuous and easy to fasten.
Researchers tested the efficacy of eight commercial sleep trackers. The result: you snooze, you lose – at least with with some of them.
Is it possible to read a person's mind by analyzing the electric signals from the brain? The answer may be much more complex than most people think.
More researchers and companies are moving into the brain-computer interfaces, yet major challenges remain, from user training to the reality of invasive brain implant procedures.
In the new priority program AUDICTIVE, experts want to use virtual reality (VR) to better understand complex auditory processes.
Graphene electrodes could enable higher quality imaging of brain cell activity.
The way humans interpret behavior of AI-endowed artificial agents, such as humanoid robots, depends on specific individual attitudes that can be detected from neural activity.
Researchers at the University of Helsinki have developed a technique in which a computer models visual perception by monitoring human brain signals.
Researchers are creating a wearable electronics device that can read brain waves while allowing the wearer to easily drift off into the various stages of sleep.
New electrode technology and AI analytics solve challenges in neurological emergency, acute and intensive care medicine.
A consortium is developing a mobile neurosensing system suitable for everyday use that detects epileptic seizures automatically.
A researcher has developed ultra-light tattoo electrodes that are hardly noticeable on the skin and make long-term measurements of brain activity cheaper and easier.
A trial suggests that a digital intervention for paediatric ADHD might help to improve inattention with minimal adverse effects.
Artificial intelligence may soon play a critical role in choosing which depression therapy is best for patients.
A deep learning model can identify sleep stages as accurately as an experienced physician.
NanoEDGE research project aims at converging production techniques for functionalized electrodes with expertise in nanomaterial fabrication and characterization.
Combining new wearable electronics and a deep learning algorithm could help disabled people wirelessly interact with a computer.
A research team has succeeded in identifying specific patterns in Electro-Encephalogram (EEG) analyses that the deep learning network uses for making prognosis decisions.
Researchers have created a wearable technology that monitors brain activity and sends back data without benching a player or asking a trucker to pull over.
A machine learning algorithm can spot abnormalities in pupil dilation that are predictive of autism spectrum disorder in mouse models.
New research has provided preliminary evidence that training time can be shortened & that user performance tends to improve within a relatively short period of time.
Researchers show that by using a noninvasive brain-computer interface they could control a robotic arm that’s tracking a cursor on a computer screen.
Researchers have shown that they can use online neurofeedback to modify an individual's arousal state to improve performance in a demanding sensory motor task.
Mobile Brain/Body Imaging system combines virtual reality, brain monitoring, and motion capture technology for researchers to study neurological disorders.
Getting a better grip on things: The MoreGrasp Horizon2020 research project is coming to an end with significant results in the field of thought-controlled grasp neuroprosthetics. A large-scale feasibility study is underway.
Multifunctional ‘smart bandage’ wirelessly monitors a variety of physical signals, from respiration, to body motion, to temperature, to eye movement, to heart and brain activity.
Electronic ‘skin’ will enable amputees to perceive through prosthetic fingertips.