Distinction Between Phases of Human Sleep Cycle Using Neural Networks Based on Bio-signals

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Emerging Technologies in Data Mining and Information Security

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 755))

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Abstract

Sleep disorders can be monitored by analyzing the various stages of sleep. The stages of human sleep cycle can be broadly classified into three types Awake, rapid eye movement (REM) sleep and non-REM sleep stages. In this work a neural network based method is proposed to distinguish between Awake, REM sleep and non-REM sleep stages. Various types of bio-signals such as electro-occulogram (EOG), electromyogram (EMG), and electroencephalogram (EEG) are used as input to the neural network based method. Accuracy of the proposed neural network based method is found to be 100%. The results of the method are promising, hence can be used to monitor sleep disorders.

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Correspondence to Aleena Swetapadma .

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Trishita, Bhatia, S.K., Kumar, G., Swetapadma, A. (2019). Distinction Between Phases of Human Sleep Cycle Using Neural Networks Based on Bio-signals. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-13-1951-8_12

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