The superiority verification of morphological features in the EEG-based assessment of depression
出版年份 2022 全文链接
标题
The superiority verification of morphological features in the EEG-based assessment of depression
作者
关键词
-
出版物
JOURNAL OF NEUROSCIENCE METHODS
Volume 381, Issue -, Pages 109690
出版商
Elsevier BV
发表日期
2022-08-23
DOI
10.1016/j.jneumeth.2022.109690
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- A major depressive disorder classification framework based on EEG signals using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis
- (2021) Reza Akbari Movahed et al. JOURNAL OF NEUROSCIENCE METHODS
- Spontaneous traveling waves naturally emerge from horizontal fiber time delays and travel through locally asynchronous-irregular states
- (2021) Zachary W. Davis et al. Nature Communications
- Rapid adaptation of brain–computer interfaces to new neuronal ensembles or participants via generative modelling
- (2021) Shixian Wen et al. Nature Biomedical Engineering
- EEG based emotion recognition using fusion feature extraction method
- (2020) Qiang Gao et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Emotional EEG classification using connectivity features and convolutional neural networks
- (2020) Seong-Eun Moon et al. NEURAL NETWORKS
- Influence of music liking on EEG based emotion recognition
- (2020) Daimi Syed Naser et al. Biomedical Signal Processing and Control
- Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals
- (2019) Nicola Michielli et al. COMPUTERS IN BIOLOGY AND MEDICINE
- A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures
- (2019) Yong Yu et al. NEURAL COMPUTATION
- Depression biomarkers using non-invasive EEG: A review
- (2019) Fernando Soares de Aguiar Neto et al. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
- Classification of Depression Patients and Normal Subjects Based on Electroencephalogram (EEG) Signal Using Alpha Power and Theta Asymmetry
- (2019) Shalini Mahato et al. JOURNAL OF MEDICAL SYSTEMS
- Automated EEG-based screening of depression using deep convolutional neural network
- (2018) U. Rajendra Acharya et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Methods for classifying depression in single channel EEG using linear and nonlinear signal analysis
- (2018) Maie Bachmann et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Specificity of spontaneous EEG associated with different levels of cognitive and communicative dysfunctions in children
- (2018) Nadezhda Ju. Kozhushko et al. INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY
- Neurophysiological correlates of depressive symptoms in young adults: A quantitative EEG study
- (2018) Poh Foong Lee et al. JOURNAL OF CLINICAL NEUROSCIENCE
- Individuals with depressive tendencies experience difficulty in forgetting negative material: two mechanisms revealed by ERP data in the directed forgetting paradigm
- (2018) Hui Xie et al. Scientific Reports
- Study on Feature Selection Methods for Depression Detection Using Three-Electrode EEG Data
- (2018) Hanshu Cai et al. Interdisciplinary Sciences-Computational Life Sciences
- Altered cortical functional network in major depressive disorder: A resting-state electroencephalogram study
- (2018) Miseon Shim et al. NeuroImage-Clinical
- A Systematic Review for Human EEG Brain Signals Based Emotion Classification, Feature Extraction, Brain Condition, Group Comparison
- (2018) Mohamed Hamada et al. JOURNAL OF MEDICAL SYSTEMS
- Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
- (2018) Spencer L James et al. LANCET
- Algorithm for automatic EEG classification according to the epilepsy type: Benign focal childhood epilepsy and structural focal epilepsy
- (2018) Andrius Vytautas Misiukas Misiūnas et al. Biomedical Signal Processing and Control
- Automatic Detection and Classification of High-Frequency Oscillations in Depth-EEG Signals
- (2017) Nisrine Jrad et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Major Depression Detection from EEG Signals Using Kernel Eigen-Filter-Bank Common Spatial Patterns
- (2017) Shih-Cheng Liao et al. SENSORS
- Where Does EEG Come From and What Does It Mean?
- (2017) Michael X Cohen TRENDS IN NEUROSCIENCES
- A wavelet-based technique to predict treatment outcome for Major Depressive Disorder
- (2017) Wajid Mumtaz et al. PLoS One
- Beta oscillations in major depression – signalling a new cortical circuit for central executive function
- (2017) Yuezhi Li et al. Scientific Reports
- Evidence of successful modulation of brain activation and subjective experience during reappraisal of negative emotion in unmedicated depression
- (2013) Daniel Gerard Dillon et al. PSYCHIATRY RESEARCH-NEUROIMAGING
- Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal
- (2012) Behshad Hosseinifard et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- LIBSVM
- (2012) Chih-Chung Chang et al. ACM Transactions on Intelligent Systems and Technology
- Evaluation of Empirical Mode Decomposition for Event-Related Potential Analysis
- (2011) N. Williams et al. EURASIP Journal on Advances in Signal Processing
- Frontal EEG asymmetry during emotional challenge differentiates individuals with and without lifetime major depressive disorder
- (2010) Jennifer L. Stewart et al. JOURNAL OF AFFECTIVE DISORDERS
- Electroencephalographic spectral asymmetry index for detection of depression
- (2009) Hiie Hinrikus et al. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started