Fast sleep stage classification using cascaded support vector machines with single-channel eeg signals

HIGHLIGHTS

• who: Dezhao Li and collaborators from the Information Technology in Biological and Medical Physics, College of Science, Zhejiang University of Technology, Hangzhou, China have published the Article: Fast Sleep Stage Classification Using Cascaded Support Vector Machines with Single-Channel EEG Signals, in the Journal: Sensors 2022, 22, 9914. of 16/Dec/2022
• what: In this study, nonlinear-dynamics-domain features of Renyi entropy, Lempel-Ziv complexity, multi-scale entropy, spectral entropy, sample entropy, and fuzzy entropy were calculated with denoised EEG signals.
• how: With the development of wearable electroencephalogram (EEG) devices the authors . . .
  

   

  

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