Frontiers9d
Brain-Computer Interfaces (BCIs) for daily activities: Innovations in EEG signal analysis and machine learning approaches
With recent advancements in Electroencephalography (EEG) signal analysis and machine learning, BCIs have evolved from ...
These headphones can track brainwaves to measure your focus levels — here's what they're like to use
Made in partnership between Master & Dynamic and Neurable, the MW75 Neuro headphones use EEG sensors and AI tech to measure ...
Using Thoughts Alone, Paralyzed Man Flies Virtual Drone With Remarkable Precision
The brain–computer interface allowed the participant to control the drone with six times the accuracy of EEG-based systems.
GitHub19d
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG, and other kinds of data from biosensors.
powerful API with many features to simplify development Straightforward API for data acquisition Powerful API for signal filtering, denoising, downsampling... Development tools like Synthetic board, ...
IEEE24d
A Multi-Modality Attention Network for Driver Fatigue Detection Based on Frontal EEG, EDA and PPG Signals
for driver fatigue detection with frontal electroencephalography (EEG), electrodermal activity (EDA) and photoplethysmography (PPG) signals for a hybrid. Specifically, a signal adaptive coding module ...
The Daily Signal26d
Renowned Historian Victor Davis Hanson Joins The Daily Signal
Katrina Trinko is the editor-in-chief of The Daily Signal. Send an email to Katrina. If your New Year’s resolution was to discover more astute analysis of politics and current events ...
Frontiers27d
Commentary: Handwriting but not typewriting leads to widespread brain connectivity: a high-density EEG study with implications for the classroom
Van Der Weel and Van Der Meer (2024, hereafter VWVM2024) claims that, unlike typing, handwriting generates brain connectivity patterns that promote learning. This result leads the authors to stress ...
IEEE27d
An Effective Deep Neural Network Architecture for EEG-Based Recognition of Emotions
Current research in EEG-based emotion recognition faces significant challenges ... The autoencoder layers seek a lower dimensionality encoding for optimal input signal reconstruction, and the 2D ...