32 citations · 59 across the 28 of their papers we have counts for
8 papers · 1 filter
Informed Bootstrap Augmentation Improves EEG Decoding
Woojae Jeong, Wenhui Cui, Kleanthis Avramidis +3
Electroencephalography (EEG) offers detailed access to neural dynamics but remains constrained by noise and trial-by-trial variability, limiting decoding performance in data-restri…
Teager-Kaiser Energy Methods For EEG Feature Extraction In Biomedical Applications
Ioanna Chourdaki, Kleanthis Avramidis, Christos Garoufis +2
Electroencephalography (EEG) signals are inherently non-linear, non-stationary, and vulnerable to noise sources, making the extraction of discriminative features a long-standing ch…
Neural Codecs as Biosignal Tokenizers
Kleanthis Avramidis, Tiantian Feng, Woojae Jeong +4
Neurophysiological recordings such as electroencephalography (EEG) offer accessible and minimally invasive means of estimating physiological activity for applications in healthcare…
A Point Process Model of Skin Conductance Responses in a Stroop Task for Predicting Depression and Suicidal Ideation
Kleanthis Avramidis, Myzelle Hughes, Idan A Blank +5
Accurate identification of mental health biomarkers can enable earlier detection and objective assessment of compromised mental well-being. In this study, we analyze electrodermal…
Time-Resolved EEG Decoding of Semantic Processing Reveals Altered Neural Dynamics in Depression and Suicidality
Woojae Jeong, Aditya Kommineni, Kleanthis Avramidis +15
Depression and suicidality affect cognitive and emotional processes, yet objective, task-evoked neural readouts of mental health remain limited. We investigated the spatiotemporal…
Neural Responses to Affective Sentences Reveal Signatures of Depression
Aditya Kommineni, Woojae Jeong, Kleanthis Avramidis +13
Major Depressive Disorder (MDD) is a highly prevalent mental health condition, and a deeper understanding of its neurocognitive foundations is essential for identifying how core fu…
Articulatory Feature Prediction from Surface EMG during Speech Production
Jihwan Lee, Kevin Huang, Kleanthis Avramidis +6
We present a model for predicting articulatory features from surface electromyography (EMG) signals during speech production. The proposed model integrates convolutional layers and…
Deep Learning Characterizes Depression and Suicidal Ideation from Eye Movements
Kleanthis Avramidis, Woojae Jeong, Aditya Kommineni +14
Identifying physiological and behavioral markers for mental health conditions is a longstanding challenge in psychiatry. Depression and suicidal ideation, in particular, lack objec…