Abstract
We demonstrate the use of artificial neural networks (ANN) to automatically detect arousal states during sleep. In this approach we model the attractor of the underlying process from time series and we show how the hidden control neural networks can be extended to model instationary behavior, by means of mutual control neural networks (MCNN). A verification of the model, based on polysomnographic recordings of 5 patients suffering from obstructive sleep apnea hypopnoea syndrome (OSAHS) is given.
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Assimakopoulos, T., Dingli, K., Douglas, N.J. (2000). Mutual Control Neural Networks for Sleep Arousal Detection. In: Malmgren, H., Borga, M., Niklasson, L. (eds) Artificial Neural Networks in Medicine and Biology. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0513-8_16
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DOI: https://doi.org/10.1007/978-1-4471-0513-8_16
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