26 April 2018 Detection of different states of sleep in the rodents by the means of artificial neural networks
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Abstract
This paper considers the possibility of classification of electroencephalogram (EEG) and electromyogram (EMG) signals corresponding to different phases of sleep and wakefulness of mice by the means of artificial neural networks. A feed-forward artificial neural network based on multilayer perceptron was created and trained on the data of one of the rodents. The trained network was used to read and classify the EEG and EMG data corresponding to different phases of sleep and wakefulness of the same mouse and other mouse. The results show a good recognition quality of all phases for the rodent on which the training was conducted (80–99%) and acceptable recognition quality for the data collected from the same mouse after a stroke.
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Viacheslav Musatov, Viacheslav Musatov, Viacheslav Dykin, Viacheslav Dykin, Elena Pitsik, Elena Pitsik, Alexander Pisarchik, Alexander Pisarchik, } "Detection of different states of sleep in the rodents by the means of artificial neural networks", Proc. SPIE 10717, Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV, 107171N (26 April 2018); doi: 10.1117/12.2314957; https://doi.org/10.1117/12.2314957
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