Detection and classification of adult epilepsy using hybrid deep learning approach

S Srinivasan, S Dayalane, S Mathivanan… - Scientific Reports, 2023 - nature.com
The electroencephalogram (EEG) has emerged over the past few decades as one of the key
tools used by clinicians to detect seizures and other neurological abnormalities of the …

High-resolution superlet transform based techniques for Parkinson's disease detection using speech signal

K Bhatt, N Jayanthi, M Kumar - Applied Acoustics, 2023 - Elsevier
Parkinson's Disease (PD) is a matter of great concern when it comes to the health
management of elderly people. Tremors, muscle stiffness, change in cognitive abilities, and …

Deep learning based automatic seizure prediction with EEG time-frequency representation

X Dong, L He, H Li, Z Liu, W Shang, W Zhou - … Signal Processing and …, 2024 - Elsevier
Automatic seizure prediction is crucial for developing a new therapy for patients suffering
from medically intractable epilepsy, possessing important clinical application value. In order …

Collaborative masking based speckle disentanglement for self-supervised optical coherence tomography image despeckling

Q Zhou, M Wen, Y Wang, M Ding, X Zhang - Optics and Lasers in …, 2024 - Elsevier
Optical coherence tomography (OCT) has proven to be an effective and safe diagnostic tool
in clinical settings due to its unique advantages. Nonetheless, the OCT images are …

[HTML][HTML] LMPSeizNet: A Lightweight Multiscale Pyramid Convolutional Neural Network for Epileptic Seizure Detection on EEG Brain Signals

A Alsaadan, M Alzamel, M Hussain - Mathematics, 2024 - mdpi.com
Epilepsy is a chronic disease and one of the most common neurological disorders
worldwide. Electroencephalogram (EEG) signals are widely used to detect epileptic …

VRFNet-ASLiT: Fused Deep CNN and Adaptive Super Resolution Transform Based Hand Gesture Recognition

R Kushwaha, M Kumar, D Kumar - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Hand gesture recognition plays a vital role in human-computer interaction, offering a natural
and intuitive means of communication. However, vision-based hand gesture recognition is …

Cardiovascular Diseases Classification Using High-Resolution Superlet Transform on ECG and PCG Signals

S Singhal, M Kumar - 2023 14th International Conference on …, 2023 - ieeexplore.ieee.org
Heart-related disease is one of the crucial roots of mortality across the world. The
abnormality of the heart can be computed with different signals but early and accurate …

Analysis of dynamics of EEG signals in emotional valence using super-resolution superlet transform

H Kumar, N Ganapathy… - IEEE Sensors Letters, 2025 - ieeexplore.ieee.org
Electroencephalography (EEG) based emotional state assessment is widely preferred due
to its noninvasiveness and non-radiation approach. However, these signals are highly non …

Epileptic Seizure Prediction through ML And DL Models: A Survey

J Viswanath, S Annamalai… - 2024 8th International …, 2024 - ieeexplore.ieee.org
Epileptic seizures are unpredictable and pose significant risks to individuals affected by
epilepsy. Electroencephalogram (EEG) signals offer a promising avenue for early seizure …

EpiNet: A Hybrid Machine Learning Model for Epileptic Seizure Prediction using EEG Signals from a 500 Patient Dataset.

OK Esha, N Begum, S Rahman - International Journal of …, 2024 - search.ebscohost.com
The accurate prognosis of epileptic seizures has great significance in enhancing the
management of epilepsy, necessitating the creation of robust and precise predictive models …