Multi-Class Anxiety Classification using Error-related
EEG Signals and Deep Learning Models

QR Code

Multi-Class Anxiety Classification using Error-related EEG Signals and Deep Learning Models

Anxiety disorders impact mental and physical health globally. This study classifies anxiety severity levels using Error-Related Negativity (ERN) signals from EEG data, analyzing 163 participants during a go/no-go task. Employing RNN, LSTM, and GRU models, anxiety was categorized as mild, moderate, o...

Full description

Bibliographic Details
Main Author:	Chandrasekar, Ramya
Format:	Thesis
Published:	Curtin University 2024
Online Access:	http://hdl.handle.net/20.500.11937/98033

Similar Items

Transfer learning and hybrid deep convolutional neural networks models for autism spectrum disorder classification from EEG signals
by: Al-Qazzaz, Noor Kamal, et al.
Published: (2024)

An Adaptive Error Modeling Scheme for the Lossless Compression of EEG Signals
by: Sriraam, N., et al.
Published: (2008)

The classification of wink-based eeg signals by means of transfer learning models
by: Jothi Letchumy, Mahendra Kumar
Published: (2021)

Classification of EEG Signal for Body Earthing Application
by: Noor Aisyah , Ab Rahman, et al.
Published: (2017)

EEG signal classification for wheelchair control application
by: Abu Hassan, Rozi Roslinda
Published: (2015)

Classification of multichannel EEG signal by single layer perceptron learning algorithm
by: Hasan, Mohammad Rubaiyat, et al.
Published: (2014)

Deep learning for EEG data analysis
by: Cheah, Kit Hwa
Published: (2018)

The classification of EEG-based wink signals: A CWT-Transfer Learning pipeline
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021)

Classification of multichannel EEG signal by linear discriminant analysis
by: Hasan, Mohammad Rubaiyat, et al.
Published: (2015)

Classification of multichannel EEG signal by linear discriminant analysis
by: Hasan, Mohammad Rubaiyat, et al.
Published: (2015)

Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
by: Asrul, Adam
Published: (2017)

Learners' Learning Style classification related to IQ and Stress based on EEG
by: Nazre, Abdul Rashid, et al.
Published: (2011)

Classification of mental tasks using fixed and adaptive autoregressive models of EEG signals
by: Huan,, NJ, et al.
Published: (2005)

The classification of EEG-based winking signals: a transfer learning and random forest pipeline
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021)

The classification of EEG signal processing using different machine learning techniques for BCI application
by: Rashid, Mamunur, et al.
Published: (2019)

Artifacts classification in EEG signals based on temporal average statistics
by: Abdul, Qayoom, et al.
Published: (2015)

The Classification of Hallucination: The Identification of Significant Time-Domain EEG Signals
by: Chin, Hau Lim, et al.
Published: (2022)

Classification of mental tasks using de-noised EEG Signals
by: Mohd Daud, Salwani, et al.
Published: (2004)

Classification of mental tasks using de-noised EEG signals
by: Daud, Salwani, et al.
Published: (2004)

The Classification of Wink-Based EEG Signals: The identification on efficiency of transfer learning models by means of kNN classifier
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021)

Neural Network Based Lossless And Quality Controlled Schemes With Error Modeling For The Compression Of Electroencephalography (EEG) Signal
by: Natarajan, Sriraam
Published: (2007)

Classification of EEG signals for understanding affective face processing impairment in autism
by: Abdul Rahman, Abdul Wahab, et al.
Published: (2011)

Artificial neural network modelling for IQ classification based on EEG signals / Aishah Hartini Jahidin
by: Jahidin, Aishah Hartini
Published: (2016)

Artificial neural network modelling for IQ classification based on EEG signals / Aisyah Hartini Jahidin
by: Jahidin, Aisyah Hartini
Published: (2015)

An evaluation of different fast fourier transform - transfer learning pipelines for the classification of wink-based EEG signals
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2020)

Classification of EEG signals using MLP based on categorical and dimensional perceptions of emotions.
by: Yaacob, Hamwira Sakti, et al.
Published: (2013)

The Classification of Wink-Based EEG Signals: The Identification of Significant Time-Domain Features
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021)

A relative evaluation of multi-class image classification by support vector machines
by: Foody, Giles M., et al.
Published: (2004)

Investigation of deep learning model for vehicle classification
by: Ahsiah, Ismail, et al.
Published: (2026)

Frequency modulation in EEG signals
by: Vijayakumar, V., et al.
Published: (2006)

EEG signals for emotion recognition
by: Abdul Rahman, Abdul Wahab, et al.
Published: (2010)

Robust classification of motor imagery EEG signals using statistical time–domain features
by: Khorshidtalab, Aida, et al.
Published: (2013)

EEG signal classification for real-time brain-computer interface applications: a review
by: Khorshidtalab, A., et al.
Published: (2011)

Determination and classification of human stress index using non-parametric analysis of EEG signals
by: Norizam, Sulaiman
Published: (2015)

Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals
by: Badaruddin, Muhammad, et al.
Published: (2018)

Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy
by: Amirul Aizad, Ahmad Fuad, et al.
Published: (2025)

Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy
by: Amirul Aizad, Ahmad Fuad, et al.
Published: (2025)

Multi-class Pattern Classification in Imbalanced Data
by: Ghanem, Amal, et al.
Published: (2010)

Deep learning for image classification
by: Koi, Chin Chong
Published: (2024)

Deep Learning for Coral Classification
by: Mahmood, A., et al.
Published: (2017)

Cannot write session to /tmp/vufind_sessions/sess_4m02tr9aamdhtg6qgmc5j1n73k