Electroencephalography (EEG) has emerged as a non-invasive tool to capture brain activity and facilitate the early detection of ASD using machine learning techniques. However, attaining high accuracy ...

Neuralink’s brain-computer interface technology also has been discussed for other potential uses, for example, in mental ...

With recent advancements in Electroencephalography (EEG) signal analysis and machine learning, BCIs have evolved from ...

BNA™ Metrics as Cognitive Biomarkers: Baseline brain activation latencies, as measured through Firefly's BNA™ technology, ...

We identify the imperative for improved signal processing, advanced modeling, integration of machine learning, and AI, to enhance source localization accuracy ... This review stands as a definitive ...

The study focuses on how visual information, like lip movements, enhances the brain’s ability to differentiate similar sounds, such as “F” and “S.” Using EEG caps to monitor brainwaves, the team will ...

And the other is kind of represented by Erik Brynjolfsson—he’s more of a techno-optimist—and he argues that recent breakthroughs in machine learning will boost productivity in places like ...

A Python-based GUI application for analyzing EEG data and identifying eye blinks. Features include noise filtering, threshold-based blink detection, and data visualization with export options. Built ...

The objectives of this study is to develop a robust and accurate machine learning algorithm for AUD detection using EC matrices derived from resting-state EEG signals. This paper employs PDC adjacency ...

The ONE headset. [Image courtesy of Zeto] Zeto announced today that it closed a $31 million funding round to support its AI-driven EEG brain monitoring technology. MindWorks Global (MWG ...