4.5 Article

A convolutional neural network-based decision support system for neonatal quiet sleep detection

Related references

Note: Only part of the references are listed.
Article Mathematical & Computational Biology

EEG-based emotion recognition using hybrid CNN and LSTM classification

Bhuvaneshwari Chakravarthi et al.

Summary: This study describes the EEG signals, brain wave patterns, and emotion analysis in relation to Post-Traumatic Stress Disorder (PTSD). The study proposes an improved deep learning algorithm to analyze emotions more accurately.

FRONTIERS IN COMPUTATIONAL NEUROSCIENCE (2022)

Article Computer Science, Information Systems

EEG-Based Neonatal Sleep Stage Classification Using Ensemble Learning

Saadullah Farooq Abbasi et al.

Summary: This study proposes an internet of things and ensemble-based automatic sleep stage classification method that uses neural networks for training and testing. By combining the outputs of classifiers, it can achieve high classification accuracy in newborn infants, making it a promising candidate for use in hospitals.

CMC-COMPUTERS MATERIALS & CONTINUA (2022)

Article Computer Science, Information Systems

A Hybrid DCNN-SVM Model for Classifying Neonatal Sleep and Wake States Based on Facial Expressions in Video

Muhammad Awais et al.

Summary: A novel video-based unobtrusive method for neonatal sleep-wake classification was investigated in this study by analyzing the behavioral changes in the neonatal facial region. A hybrid model combining deep convolutional neural network (DCNN) and support vector machine (SVM) was proposed to monitor the sleep-wake patterns of human neonates, achieving reliable performances in classifying neonatal sleep and wake states in RGB video frames.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2021)

Article Computer Science, Interdisciplinary Applications

Orthogonal convolutional neural networks for automatic sleep stage classification based on single-channel EEG

Junming Zhang et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)

Article Computer Science, Interdisciplinary Applications

Neonatal sleep stage identification using long short-term memory learning system

Luay Fraiwan et al.

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2020)

Article Computer Science, Information Systems

Novel Framework: Face Feature Selection Algorithm for Neonatal Facial and Related Attributes Recognition

Muhammad Awais et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network

Saadullah Farooq Abbasi et al.

IEEE ACCESS (2020)

Article Engineering, Biomedical

A convolutional neural network for sleep stage scoring from raw single-channel EEG

Arnaud Sors et al.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2018)

Article Engineering, Biomedical

Mixed Neural Network Approach for Temporal Sleep Stage Classification

Hao Dong et al.

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING (2018)

Article Engineering, Biomedical

Automated EEG sleep staging in the term-age baby using a generative modelling approach

Kirubin Pillay et al.

JOURNAL OF NEURAL ENGINEERING (2018)

Article Engineering, Biomedical

Quiet sleep detection in preterm infants using deep convolutional neural networks

Amir Hossein Ansari et al.

JOURNAL OF NEURAL ENGINEERING (2018)

Article Engineering, Biomedical

A New Method for Automatic Sleep Stage Classification

Junming Zhang et al.

IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS (2017)

Article Computer Science, Artificial Intelligence

An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation

Anneleen Dereymaeker et al.

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS (2017)

Article Computer Science, Artificial Intelligence

An automated method for sleep staging from EEG signals using normal inverse Gaussian parameters and adaptive boosting

Ahnaf Rashik Hassan et al.

NEUROCOMPUTING (2017)

Review Clinical Neurology

Unobtrusive sleep state measurements in preterm infants - A review

Jan Werth et al.

SLEEP MEDICINE REVIEWS (2017)

Article Computer Science, Information Systems

Cardiorespiratory Sleep Stage Detection Using Conditional Random Fields

Pedro Fonseca et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2017)

Article Clinical Neurology

Automated classification of neonatal sleep states using EEG

Ninah Koolen et al.

CLINICAL NEUROPHYSIOLOGY (2017)

Article Biochemical Research Methods

A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features

Ahnaf Rashik Hassan et al.

JOURNAL OF NEUROSCIENCE METHODS (2016)

Article Engineering, Biomedical

Sleep stages classification based on heart rate variability and random forest

Meng Xiao et al.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2013)

Article Computer Science, Interdisciplinary Applications

Automated detection of neonate EEG sleep stages

Alexandra Piryatinska et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2009)

Article Biophysics

Neurodevelopment in newborns: a sample entropy analysis of electroencephalogram

Dandan Zhang et al.

PHYSIOLOGICAL MEASUREMENT (2009)