Abstract: Decoding motor imagery (MI) from electroencephalogram (EEG) signals is a cornerstone of brain–computer interface (BCI) systems. However, existing methods often face a critical tradeoff ...

1 School of Automation, Nanjing University of Science and Technology, Nanjing, Jiangsu, China 2 School of Engineering, University of Birmingham, Birmingham, United Kingdom Electroencephalogram ...

Dr Andrei Alexandrov discusses his experience implementing point-of-care EEG equipped with artificial intelligence. As neurologists, our responsibility goes beyond interpreting electroencephalograms ...

Summary: New research shows that deep learning can use EEG signals to distinguish Alzheimer’s disease from frontotemporal dementia with high accuracy. By analyzing both the timing and frequency of ...

Researchers at örebro University have developed two new AI models that can analyze the brain's electrical activity and accurately distinguish between healthy individuals and patients with dementia, ...

Start your journey into machine learning with EEG time-series data in this easy-to-follow Python project. Perfect for beginners looking to explore brain signal analysis! #MachineLearning #EEG ...

PARIS--(BUSINESS WIRE)--Genomines, a company pioneering the future of metal extraction with efficient, plant-based metal farming, today announced it has raised an oversubscribed $45 million Series A.

If there's one thing you want in a PvP game, it's parity. Fairness. Justice. Ok, maybe justice only rears its head when Batman logs onto Fortnite in his favorite Ariana Grande skin, but generally you ...

Design a lightweight machine-learning pipeline that analyzes single-channel frontal EEG data (Fp1/Fp2) and accurately detects driver drowsiness in real-time. 50 Hz IIR notch filter + 0.5–30 Hz ...

Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia Introduction: This scientific investigation explored how meditation ...