PSGLab Project

PSGLab is a Matlab toolbox for processing of polysomnographic (PSG) data.

PSG recording encompasses a set of heterogeneous biological signals recorded simultaneously. Electroencephalographic (EEG) signals, electrooculogram (EOG) and electromyogram (EMG) are important parts of this kind of recording. PSG recording may also include electrocardiogram (ECG), respiratory effort and respiratory airflow, blood oxygen saturation and temperature, as well as movement or body position.

PSGLab Toolbox

PSGLab Features

PSGLab implements signal preprocessing, feature extraction, classification, cluster analysis and data visualization methods.

PSGLab main features:

  • Multiformat data importing/exporting
  • Signal preprocessing (filtering, resampling, artifact rejection, isoline removing)
  • Constant and adaptive segmentation
  • Feature extraction (mainly EEG oriented features)
  • Correlation and coherence analysis
  • Wavelet analysis
  • Principal component analysis
  • K-means clustering, Hierarchical clustering
  • KNN and HMM classifiers
  • Data visualization (2D EEG maps, hypnograms, spectrograms, clustering results visualization, etc.)


Additional information and download page: http://bio.felk.cvut.cz/psglab/

 

 


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