Measurement, acquisition and processing of biopotential signals for early detection of sleep paralysis
Nataša Stojnić, Marjan Urekar
PROCEEDINGS 13th International Conference IcETRAN 2026 DOI: 10.69994/13ic26019 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Proposes a conceptual wearable smart headband that detects sleep paralysis through a hierarchical combination of accelerometry, EOG, and EEG spectral analysis, with the aim of interrupting episodes and logging data for later review. The design is presented as a proposal; no prototype or clinical validation is reported. |
Abstract
This paper presents a conceptual design of a wearable system for detecting and interrupting sleep paralysis in order to help patients with this disorder. The proposed solution, envisioned as a smart headband, integrates an accelerometer, electrooculography (EOG), and electroencephalography (EEG) for precise monitoring of the user's condition. The detection methodology is based on a hierarchical logic: first, the absence of head movement is analyzed, then the REM phase is identified through the analysis of the EOG signal, while the final confirmation is performed by analyzing the spectral analysis of the EEG signal (FFT and PSD). In a practical implementation, the system is expected to store recorded data and detected events for later analysis.