Efficacy of Eye Movement Desensitization and Reprocessing (EMDR) on Anxiety Severity Among Physicians and Nurses Working in Intensive Care Units.

Electroencephalography (EEG) is widely used for cognitive state decoding due to its high temporal resolution, non-invasiveness, and compatibility with wearable acquisition systems. In Lie and Truth condition classification, EEG provides temporally sensitive physiological measurements that may capture task-related signal variations associated with cognitive load, attention, response preparation, and other experimental processes under controlled conditions []. Publicly available wearable datasets, such as LieWaves, have enabled the systematic development of EEG-based lie-detection pipelines, with reported classification accuracies frequently exceeding 90% under controlled paradigms [,]. Despite these advances, several methodological limitations persist. First, many deception detection frameworks rely on single-domain feature representations, such as event-related potentials (ERPs), spectral band power distributions, or connectivity measures, which are analyzed independently [, , ]. ERP-based approaches capture stimulus-locked neural responses but are often sensitive to inter-subject variability. Spectral features quantify oscillatory redistribution across frequency bands but may fail to capture nonlinear dynamics present in EEG signals. Connectivity metrics describe synchronization patterns but are often applied without structured integration with temporal or nonlinear descriptors.