eye-eeg Search Results


eye eeg toolbox  (Radboud University)
86
Radboud University eye eeg toolbox
Multimodal feature contribution and classification performance for suicide ideation detection in individuals with depression . (A) Variable importance plot derived from the Random Forest model. The Beck Depression Inventory (BDI) score ranks highest in importance, followed by eye movement measures including saccade amplitude (sac_amp), first fixation duration, and EEG features such as rERP and rFRP components at specific time windows (368–628 ms and 564–620 ms) and channels. (B) Receiver Operating Characteristic (ROC) curves comparing classification performance between models using combined eye movement and EEG features <t>(EYE-EEG,</t> Area Under the Curve (AUC) = 0.771) versus eye movement features alone (EYE, AUC = 0.643) for detecting suicide ideation in depressed individuals.
Eye Eeg Toolbox, supplied by Radboud University, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/eye eeg toolbox/product/Radboud University
Average 86 stars, based on 1 article reviews
eye eeg toolbox - by Bioz Stars, 2026-05
86/100 stars
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eye-eeg extension  (EyeTracking Inc)
90
EyeTracking Inc eye-eeg extension
Multimodal feature contribution and classification performance for suicide ideation detection in individuals with depression . (A) Variable importance plot derived from the Random Forest model. The Beck Depression Inventory (BDI) score ranks highest in importance, followed by eye movement measures including saccade amplitude (sac_amp), first fixation duration, and EEG features such as rERP and rFRP components at specific time windows (368–628 ms and 564–620 ms) and channels. (B) Receiver Operating Characteristic (ROC) curves comparing classification performance between models using combined eye movement and EEG features <t>(EYE-EEG,</t> Area Under the Curve (AUC) = 0.771) versus eye movement features alone (EYE, AUC = 0.643) for detecting suicide ideation in depressed individuals.
Eye Eeg Extension, supplied by EyeTracking Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/eye-eeg extension/product/EyeTracking Inc
Average 90 stars, based on 1 article reviews
eye-eeg extension - by Bioz Stars, 2026-05
90/100 stars
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Image Search Results


Multimodal feature contribution and classification performance for suicide ideation detection in individuals with depression . (A) Variable importance plot derived from the Random Forest model. The Beck Depression Inventory (BDI) score ranks highest in importance, followed by eye movement measures including saccade amplitude (sac_amp), first fixation duration, and EEG features such as rERP and rFRP components at specific time windows (368–628 ms and 564–620 ms) and channels. (B) Receiver Operating Characteristic (ROC) curves comparing classification performance between models using combined eye movement and EEG features (EYE-EEG, Area Under the Curve (AUC) = 0.771) versus eye movement features alone (EYE, AUC = 0.643) for detecting suicide ideation in depressed individuals.

Journal: Alpha Psychiatry

Article Title: Neurocognitive Processing of Facial Emotion Recognition in Individuals With Depression and Suicidal Ideation: An Eye-Tracking and EEG Study

doi: 10.31083/AP44992

Figure Lengend Snippet: Multimodal feature contribution and classification performance for suicide ideation detection in individuals with depression . (A) Variable importance plot derived from the Random Forest model. The Beck Depression Inventory (BDI) score ranks highest in importance, followed by eye movement measures including saccade amplitude (sac_amp), first fixation duration, and EEG features such as rERP and rFRP components at specific time windows (368–628 ms and 564–620 ms) and channels. (B) Receiver Operating Characteristic (ROC) curves comparing classification performance between models using combined eye movement and EEG features (EYE-EEG, Area Under the Curve (AUC) = 0.771) versus eye movement features alone (EYE, AUC = 0.643) for detecting suicide ideation in depressed individuals.

Article Snippet: Eye-tracking data were preprocessed to detect saccades and fixations using EYE-EEG toolbox (version 1.0, available at https://github.com/olafdimigen/eye-eeg/releases/tag/v1.0 , developed by the Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands) [ ].

Techniques: Derivative Assay