Fig. 2: Model performance.
From: Neural models for detection and classification of brain states and transitions
a Averaged accuracies of the first CNN) model in classifying Awake (AW), Slow oscillations (SO) and Microarousals (MA) states in all subjects (n = 4) with a confidence threshold of 90% (unknowns are excluded from the confusion matrix). b Exemplary samples. Different state traces with the corresponding confidence level. c Power spectral density (PSD) clustered samples. The spectral power in the different bands was computed in the autoencoder-reconstructed unknown samples. d Exemplary unknowns classified with the PSD-cluster algorithm. e Accuracy across different models, Global, CNN, centroids-with-transitions and centroids-with-no-transitions. Boxplots show IQR, line is median, whiskers extend to 1.5× IQR or min/max non-outliers.
