Method: The study proposes a novel EEG-based classification approach, focusing on effective connectivity (EC) derived from resting-state EEG signals in combination with support vector machine (SVM) ...

With recent advancements in Electroencephalography (EEG) signal analysis and machine learning, BCIs have evolved from laboratory prototypes to applications in real-world environments. This Research ...

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 ...

Such techniques can be used to report all neurological diseases. They need to be assessed and compared for implementing with EEG machines or for the development of automated diagnosis of various ...

Alexander Fleming’s moldy petri dish led him to discover penicillin; Isaac Newton’s observation of an apple falling from a tree led him to write the laws of motion and the universal law of gravitation ...

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

As AI continues to evolve, the ECG and EEG equipment market is expected to see further advancements in machine learning applications, intelligent monitoring systems, and real-time data analysis, ...

Standard EEG – electrodes are attached to the head using glue or paste. The EEG machine records the electrical signals from the brain on a computer. Video EEG telemetry – you will have continuous EEG ...