We propose an image processing based technique for automatic identification of sleep stages from EEG signals. We generate two dimensional image representations ...

PDF | On Sep 1, 2019, Saira Kanwal and others published An Image Based Prediction Model for Sleep Stage Identification | Find, read and cite all the ...

In this paper, we propose an image processing based approach for automatic sleep stage identification from EEG signals. Our technique represents 30 seconds ...

Feb 27, 2024 · Here we present SlumberNet, a novel deep learning model based on residual network (ResNet) architecture, designed to classify sleep states in ...

Nov 1, 2021 · We developed a novel program called GI-SleepNet, generative adversarial network (GAN)-assisted image-based sleep staging for mice that is accurate, versatile, ...

Jan 14, 2022 · We developed an auto-annotation algorithm based on polysomnographic records and a deep learning architecture that predicts sleep stages at the millisecond ...

The EEG-based sleep phase method proposed in this paper provides an effective method for the diagnosis and treatment of sleep disorders.

As a result, sleep study analysis has undergone a significant transformation with the widespread adoption of AI for predicting sleep stages and identifying.

Mar 16, 2022 · To classify sleep stages using the CNN model, the biosignals are extracted from the SleepEDFx dataset, preprocessed, and converted into images.

It is shown that classification results can be improved by using multi-channel EEG instead of single-channel EEG data.