Sleep scoring plays a pivotal role both in sleep research and in clinical practice.
Traditionally, this process has relied on manual scoring by human experts, but it is marred …

Abstract Study Objectives Sleep is an important biological process that is perturbed in
numerous diseases, and assessment of its substages currently requires implantation of …

Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate
the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which …

Understanding human sleep requires appropriate animal models. Sleep has been
extensively studied in rodents, although rodent sleep differs substantially from human sleep …

Research into sleep–wake behaviors relies on scoring sleep states, normally done by
manual inspection of electroencephalogram (EEG) and electromyogram (EMG) recordings …

Background Sleep physiology plays a critical role in brain development and aging. Accurate
sleep staging, which categorizes different sleep states, is fundamental for sleep physiology …

Electroencephalogram (EEG) and electromyogram (EMG) are fundamental tools in sleep
research. However, investigations into the statistical properties of rodent EEG/EMG signals …

The objective and automatic detection of the sleep–wake cycle (SWC) stages is essential for
the investigation of its physiology and dysfunction. Here, we propose a machine learning …

We study the type of distributions that restricted Boltzmann machines (RBMs) with different
activation functions can express by investigating the effect of the activation function of the …

Background Recent advancement in deep learning provides a pivotal opportunity to
potentially supplement or supplant the limiting step of manual sleep scoring. New method In …