Recognition of wake-sleep stage 1 multichannel eeg patterns using spectral entropy features for drowsiness detection

• Published in: Australasian physical & engineering sciences in medicine Vol. 39; no. 3; pp. 797 - 806
• Main Authors: Sriraam, N., Padma Shri, T. K., Maheshwari, Uma
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2016; Springer Nature B.V
• Subjects: Algorithms; Biological and Medical Physics; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Biophysics; Databases as Topic; Electroencephalography; Electroencephalography - methods; Entropy; Humans; Medical and Radiation Physics; Neural Networks (Computer); Neurobiology; Sleep; Sleep - physiology; Sleep Stages - physiology; Spectrum analysis; Technical Paper; Wakefulness - physiology; Spectral entropy (SE); Electroencephalogram (EEG); Back propagation (BP) algorithm; Multilayer perceptron-feed forward (MLP-FF) neural network; Polysomnograms (PSG)

Electroencephalographic (EEG) activity recorded during the entire sleep cycle reflects various complex processes associated with brain and exhibits a high degree of irregularity through various stages of sleep. The identification of transition from wakefulness to stage1 sleep is a challenging area o...