An Automated Sleep Stages Classification Using BrainEEG Signal: A Machine Learning Approaches

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

doi:10.1007/978-981-16-2674-6_24

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An Automated Sleep Stages Classification Using BrainEEG Signal: A Machine Learning Approaches

Santosh Kumar Satapathy M. V. Sangameswar D. Loganathan

Year: 2021 Advances in intelligent systems and computing Pages: 311-327 Publisher: Springer Nature

DOI: 10.1007/978-981-16-2674-6_24

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Keywords:

Support vector machine Sleep (system call) Computer science Artificial intelligence Sleep Stages Feature extraction Machine learning Process (computing) Sleep disorder Electroencephalography Psychology Polysomnography Insomnia Psychiatry

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0.84

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0.73

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Topics

EEG and Brain-Computer Interfaces

Life Sciences → Neuroscience → Cognitive Neuroscience

Non-Invasive Vital Sign Monitoring

Physical Sciences → Engineering → Biomedical Engineering

Sleep and Work-Related Fatigue

Social Sciences → Psychology → Experimental and Cognitive Psychology

An Automated Sleep Stages Classification Using BrainEEG Signal: A Machine Learning Approaches

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Citation History

Topics

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