Mo.P4.B-56
DEEP LEARNING APPROACHES FOR SLEEP APNEA CLASSIFICATION FROM POLYSOMNOGRAPHIC EEG SIGNALS
Shashank Manjunath, Mukesh Cheemakurthi, Aarti Sathyanarayana, Northeastern University
Session:
Mo.P4: EEG Signal Processing, Representation learning, and Denoising Poster
Track:
Biomedical Signal Processing
Location:
Hall E; Bay B, Board #56
Presentation Time:
Monday, 27 July, 16:30 - 18:30
Presentation
Discussion
Resources
No resources available.
Session Mo.P4
Mo.P4.B-52: CNN-Transformer Network (CT-Net) for Automated Sleep Spindle (SS) Detection in Rat EEGs
Lan Wei, University College Dublin; Peter J. Soja, The University of British Columbia; Catherine Mooney, University College Dublin
Mo.P4.B-53: STC-EEGNet: A Method for Prognosis Prediction of Small-sample Stroke Cases
Ruihong He, Tianjin University; Hong Wang, The First Affiliated Hospital of Nankai University; Long Chen, Zhongpeng Wang, Tianjin University; Changcheng Sun, The First Affiliated Hospital of Nankai University; Haiyan Zhang, Tianjin University; Ying Zhang, The First Affiliated Hospital of Nankai University; Dong Ming, Tianjin University
Mo.P4.B-54: VECTORIZED GRAPH ANALYSIS OF DIRECTED PHASE LAG INDEX IN EEG DATA: THETA-BAND DYNAMICS REVEAL FEEDBACK VALENCE EFFECTS DURING EARLY AND LATE REINFORCEMENT LEARNING
Mohammadjavad Sedghizadeh, Sharif University of Technology, imec–TELIN-IPI, Gent University; Hamid Mohammadzadeh, Sharif University of Technology; Hamid Aghajan, Sharif University of Technology, imec–TELIN-IPI, Gent University; Danilo Babin, Wilfried Philips, imec–TELIN-IPI, Gent University
Mo.P4.B-55: Deep Learning Based Electroencephalography Source Separation with Generalization to Nonlinear Mixing Functions
Liyuan Ma, Xiaogang Hu, Pennsylvania State University-University Park
Mo.P4.B-56: DEEP LEARNING APPROACHES FOR SLEEP APNEA CLASSIFICATION FROM POLYSOMNOGRAPHIC EEG SIGNALS
Shashank Manjunath, Mukesh Cheemakurthi, Aarti Sathyanarayana, Northeastern University
Mo.P4.B-57: Interpretable Feature-Based Machine Learning for Automated Seizure Detection in Mouse EEG
Lan Wei, Maryam Saeedi, University College Dublin; Angélique Bordey, Yale University; Catherine Mooney, University College Dublin
Mo.P4.B-58: INVESTIGATION OF CHANNEL DENSITY AND REAL-TIME PROCESSING EFFECTS ON GED-BASED EEG DENOISING
Sahar Sattari, Naznin Virji-Babul, Lyndia Wu, University of British Columbia
Mo.P4.B-59: THALAMIC AROUSAL DYNAMICS DURING SLEEP FOR RECOVERY PREDICTION IN DISORDERS OF CONSCIOUSNESS
Yuankai Zhao, Tianjin University; Ziyi Liao, Beijing Tiantan Hospital, Capital Medical University; Qiangfan Meng, Ying Lan, Tianjin University; Qianqian Ge, Beijing Tiantan Hospital, Capital Medical University; Haiqing Yu, Tianjin University; Long Xu, Jianghong He, Beijing Tiantan Hospital, Capital Medical University; Yongzhi Huang, Minpeng Xu, Dong Ming, Tianjin University
Mo.P4.B-60: Spatio-Temporal Decoupling and Representation Refinement for Robust Auditory Attention Decoding
Xue Yuan, Qilin Liu, Qiong Guo, Ning Jiang, Jin Huang, Jiayuan He, Sichuan University
Mo.P4.B-61: Quantifying Seizure Onset Zone Signals Through VAE Reconstruction Failure
Nooshin Bahador, Milad Lankarany, University Health Network
Mo.P4.B-62: TRIAL-LEVEL TIME-FREQUENCY EEG DESYNCHRONIZATION AS A NEURAL MARKER OF PAIN
Diego Andrés Blanco Mora, Angelika Dierolf, Jorge Gonçalves, Marian van der Meulen, University of Luxembourg
Mo.P4.B-63: Subject-Independent Drowsiness Detection from Forehead Electroencephalography (EEG) Using Domain-Adversarial Learning and Spectral Separability Analysis
Zigurds Licis, Nasim Montazeri Ghahjaverestan, Queen's University
Mo.P4.B-64: EEG-DDGAN: DUAL-DOMAIN DISCRIMINATION FOR SYNTHETIC GENERATION OF P300 SIGNALS
Diego Varela, Carolina Saavedra, Universidad Técnica Federico Santa María
Mo.P4.B-65: CROSS-MODAL GRAPH ATTENTION FRAMEWORK TO ENHANCE THE GENERALIZATION OF EEG–FMRI CLASSIFICATION
Mohammad Hosseini, Cheol-Hong Min, University of St.Thomas
Mo.P4.B-66: Deep Learning for EEG Artifact Removal: A Preliminary Survey of Methodological Trends and Taxonomies
Erica Danielle Floreani, Ledycnarf Januario de Holanda, Mahwish Khan, Yara Corky, Ariel Motsenyat, University of Toronto; Jerry Wan, Holland Bloorview Kids Rehabilitation Hospital; Marita Cafazzo, Tom Chau, University of Toronto
Mo.P4.B-67: Modeling Latent Brain Dynamics: A Neural ODE Variational Autoencoder Approach for EEG Signal Reconstruction
Stefano Vannoni, Grace Fossaluzza, Flavia Carbone, Anna Maria Bianchi, Paola Antonietti, Politecnico di Milano; Paolo Brambilla, Università degli Studi di Milano; Eleonora Maggioni, Politecnico di Milano
Mo.P4.B-68: Physiologically Aware Loss Balancing (PALB): Selective Constraints Improve GAN-Based Imputation in Critical Care Data
Mahta Darvish, University of Sheffield; Timothy Dawes, University College London; Venet Osmani, Queen Mary University of London; George Panoutsos, University of Sheffield
Mo.P4.B-69: ATFAR: ADAPTIVE TRANSFORMER FUSION FOR OCULAR ARTIFACT REMOVAL IN SINGLE-CHANNEL EEG
Connor Johnston, Nasim Montazeri Ghahjaverestan, Queen's University
Mo.P4.B-70: CM-DRNet: Flexible and Efficient Inter-Channel Information Fusion for EEG Artifact Removal
Jiacheng Ma, Xuxin Cai, Weibei Dou, Tsinghua University; Yu Pan, Beijing Tsinghua Changgung Hospital, Tsinghua University
Resources
No resources available.