ABSTRACT
We present an open system for sleep staging, based explicitly on the criteria used in visual EEG analysis. Slow waves, theta and alpha waves, sleep spindles and K-complexes are parameterized in terms of time duration, amplitude, and frequency of each waveform by means of the matching pursuit algorithm. It allows the detection of these structures using mostly the criteria from visual EEG analysis. For example, within this framework for the first time we compute directly the relative duration of slow waves, which is a basic parameter in recognition of deep sleep stages. Performance of the system is evaluated on 20 polysomnographic recordings, scored by experienced encephalographers. Seven recordings were scored by more than one expert. Proposed system gives concordance with visual staging close to the inter-expert concordance. The algorithm is implemented in a user-friendly software system for display and analysis of polysomnographic recordings, freely available with complete source code from http://signalml.org/svarog.html .
Subject(s)
Algorithms , Brain/physiology , Electroencephalography/methods , Signal Processing, Computer-Assisted , Sleep Stages/physiology , Access to Information , Automation , Eye Movements/physiology , Humans , Internet , Movement/physiology , Polysomnography , Software , User-Computer InterfaceABSTRACT
We propose and discuss a complete framework for estimating significant changes in the average time-frequency density of energy of event-related signals. Addressed issues include estimation of time-frequency energy density (matching pursuit and spectrogram), choice of resampling statistics to test the hypothesis of change in one small region (resel), and correction for multiplicity (false discovery rate). We present estimation of the significance of event-related electroencephalograph desynchronization and synchronization (ERD/ERS) in the time-frequency plane.
