Sleep-Deep-Net learns sleep wake scoring from the end-user and completes each record in their style.

ABSTRACT: Sleep-wake scoring is a time-consuming, tedious but essential component of clinical and pre-clinical sleep research. Sleep scoring is even more laborious and challenging in rodents due to the smaller EEG amplitude differences between states and the rapid state transitions which necessitate scoring in shorter epochs. Although many automated rodent sleep scoring methods exist, they do not perform as well when scoring new data sets, especially those which involve changes in the EEG/EMG profile. Thus, manual scoring by expert scorers remains the gold-standard. Here we take a different approach to this problem by using a neural network to accelerate the scoring of expert scorers. Sleep-Deep-Net (SDN) creates a bespoke deep convolution neural network model for individual electroencephalographic

SUBMITTER: Katsuki F 

PROVIDER: S-EPMC10769368 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature