An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works
A Shoeibi, P Moridian, M Khodatars… - Computers in biology …, 2022 - Elsevier
Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …
A review of recurrent neural network-based methods in computational physiology
Artificial intelligence and machine learning techniques have progressed dramatically and
become powerful tools required to solve complicated tasks, such as computer vision, speech …
become powerful tools required to solve complicated tasks, such as computer vision, speech …
Deep learning for predicting respiratory rate from biosignals
In the past decade, deep learning models have been applied to bio-sensors used in a body
sensor network for prediction. Given recent innovations in this field, the prediction accuracy …
sensor network for prediction. Given recent innovations in this field, the prediction accuracy …
Robust Classification and Detection of Big Medical Data Using Advanced Parallel K-Means Clustering, YOLOv4, and Logistic Regression
Big-medical-data classification and image detection are crucial tasks in the field of
healthcare, as they can assist with diagnosis, treatment planning, and disease monitoring …
healthcare, as they can assist with diagnosis, treatment planning, and disease monitoring …
Knowledge representation and reasoning using interconnected uncertain rules for describing workflows in complex systems
DC Popescu, I Dumitrache - Information Fusion, 2023 - Elsevier
Abstract Knowledge representation and reasoning (KRR) in complex systems (CSs) usually
require facts from multiple experts having complementary backgrounds to fuse together …
require facts from multiple experts having complementary backgrounds to fuse together …
Recent trends in EEG based Motor Imagery Signal Analysis and Recognition: A comprehensive review.
The electroencephalogram (EEG) motor imagery (MI) signals are the widespread paradigms
in the brain-computer interface (BCI). Its significant applications in the gaming, robotics, and …
in the brain-computer interface (BCI). Its significant applications in the gaming, robotics, and …
Transformers in biosignal analysis: A review
Transformer architectures have become increasingly popular in healthcare applications.
Through outstanding performance in natural language processing and superior capability to …
Through outstanding performance in natural language processing and superior capability to …
[HTML][HTML] Real-time walking gait terrain classification from foot-mounted Inertial Measurement Unit using Convolutional Long Short-Term Memory neural network
We propose a novel online real-time gait terrain detection algorithm from the measurements
of a foot-mounted Inertial Measurement Unit (IMU), using a shallow cascaded Convolutional …
of a foot-mounted Inertial Measurement Unit (IMU), using a shallow cascaded Convolutional …
Enhancing EEG signal analysis with geometry invariants for multichannel fusion
Automated computer-aided diagnosis (CAD) has become an essential approach in the early
detection of health issues. One of the significant benefits of this approach is high accuracy …
detection of health issues. One of the significant benefits of this approach is high accuracy …
Non-Invasive sensor-based estimation of anterior-posterior upper esophageal sphincter opening maximal distension
Y Khalifa, AS Mahoney, E Lucatorto… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Objective: Dysphagia management relies on the evaluation of the temporospatial kinematic
events of swallowing performed in videofluoroscopy (VF) by trained clinicians. The upper …
events of swallowing performed in videofluoroscopy (VF) by trained clinicians. The upper …