Automated Classification of Sleep Stages Based on Electroencephalogram Signal Using Machine Learning Techniques

Santosh Kumar Satapathy; D. Loganathan; M. V. Sangameswar; Deepika Vodnala

doi:10.1007/978-981-16-2248-9_39

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Automated Classification of Sleep Stages Based on Electroencephalogram Signal Using Machine Learning Techniques

Santosh Kumar Satapathy D. Loganathan M. V. Sangameswar Deepika Vodnala

Year: 2021 Algorithms for intelligent systems Pages: 407-416 Publisher: Springer Nature

DOI: 10.1007/978-981-16-2248-9_39

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Keywords:

Polysomnography Sleep (system call) Sleep Stages Computer science Artificial intelligence Machine learning Test (biology) Electroencephalography Sleep medicine Slow-wave sleep Speech recognition Pattern recognition (psychology) Sleep disorder Psychology Insomnia Neuroscience Psychiatry

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EEG and Brain-Computer Interfaces

Life Sciences → Neuroscience → Cognitive Neuroscience

Sleep and Wakefulness Research

Life Sciences → Neuroscience → Cognitive Neuroscience

Blind Source Separation Techniques

Physical Sciences → Computer Science → Signal Processing

Automated Classification of Sleep Stages Based on Electroencephalogram Signal Using Machine Learning Techniques

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