A review on software and hardware developments in automatic epilepsy diagnosis using EEG datasets
Epilepsy is a common non‐communicable, group of neurological disorders affecting more
than 50 million individuals worldwide. Different approaches of basic, clinical, and …
than 50 million individuals worldwide. Different approaches of basic, clinical, and …
DCSENets: Interpretable deep learning for patient-independent seizure classification using enhanced EEG-based spectrogram visualization
Neurologists often face challenges in identifying epileptic activities within multichannel EEG
recordings, requiring extensive hours of analysis. Computer-aided diagnosis systems have …
recordings, requiring extensive hours of analysis. Computer-aided diagnosis systems have …
[HTML][HTML] Decoding brain signals: A convolutional neural network approach for motor imagery classification
Motor imagery-centered brain-computer interfaces (BCIs) have surfaced as a promising
technology with the potential to improve communication and control for people facing motor …
technology with the potential to improve communication and control for people facing motor …
[PDF][PDF] e-Prime-Advances in Electrical Engineering, Electronics and Energy
MS Javadi, AE Nezhad, M Gough, M Lotfi… - researchgate.net
abstract This paper presents a self-scheduling framework, using a risk-constrained
optimization model for the home energy management system (HEMS), considering fixed …
optimization model for the home energy management system (HEMS), considering fixed …