Describing the sleep EEG with an Adaptive Autoregressive Model
Figure 1: Sleep analysis using AAR parameters (healthy subject). On top, the hypnogram scored by an expert is shown. Below, the classification with AAR parameters using channels C3-M2 and C4-M1 is given for deep sleep (green line), REM (red line) and awake (blue line) – the highest curve indicates the appropriate sleep stage. The bottom plot shows the variance of the inverse filtered process (logarithmic scale). Spikes indicate artefacts and transient events. EEG processing The EEG of polygraphic recordings (SIESTA database)3 from eight European sleep labs was analysed; ECG artefacts and line interference were minimised with regression analysis and 50Hz notch filtering. The data were downsampled to 100Hz. Next, the AAR parameters were estimated with Kalman filtering assuming a multivariate random walk of AAR parameters2,4.