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 ...

Researchers at Tsinghua University developed the Optical Feature Extraction Engine (OFE2), an optical engine that processes data at 12.5 GHz using light rather than electricity. Its integrated ...

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, ...

ABSTRACT: Time series anomaly detection is important in fields such as industrial control, but faces challenges such as data distribution drifting over time, diverse normal patterns, and training data ...

Click to share on X (Opens in new window) X Click to share on Facebook (Opens in new window) Facebook “The Last of the Meheecans” is one of several of the series’ illegal immigration-focused episodes, ...

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 ...

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