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Structured multi-domain EEG descriptors with phase-based connectivity for lie and truth detection
Dwi Utari Surya1, Sholeh Hadi Pramono2, Panca Mudjirahardjo2
1Department of Creative and Digital Industry, Faculty of Vocational Studies, Universitas Brawijaya, 65145, Indonesia.
Methodsx
|August 9, 2026
Summary
This study introduces a structured framework for wearable electroencephalography (EEG) to improve lie and truth detection. The new method enhances reproducibility and transparency in EEG-based deception detection research.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Computer Science
Background:
- Wearable electroencephalography (EEG)-based lie detection lacks standardized methods, hindering reproducibility and transparency.
- Current approaches often use poorly integrated features and opaque models, complicating result interpretation and cross-study comparisons.
- A deterministic framework is needed to document and standardize wearable EEG systems for deception detection.
Purpose of the Study:
- To introduce a reproducible framework for wearable EEG-based lie and truth detection.
- To develop a structured descriptor system integrating multiple EEG signal domains.
- To enhance transparency and verifiability in deception detection research.
Main Methods:
- Developed the Structured Multi-Domain EEG Descriptor with Phase-Based Connectivity framework.
- Integrated temporal statistics, fractal complexity, spectral power, and phase-based connectivity into a unified descriptor.
- Employed a processing framework with detailed specifications for preprocessing, segmentation, descriptor extraction, normalization, and classifier evaluation.
- Utilized a controlled evaluation strategy assessing statistical consistency, feature contribution, and computational feasibility.
Main Results:
- The framework demonstrated stable fold-wise behavior and consistent classifier responses on the LieWaves dataset.
- The structured integration of diverse EEG features within a unified descriptor was achieved.
- Controlled evaluation confirmed the framework's statistical consistency and computational feasibility.
Conclusions:
- The Structured Multi-Domain EEG Descriptor with Phase-Based Connectivity offers a reproducible and transparent approach to wearable EEG-based deception detection.
- This framework addresses the research gap by providing standardized methods for descriptor engineering.
- The findings support the potential of this structured approach for advancing lie and truth detection technologies.
