A method for sleep quality analysis based on CNN ensemble with implementation in a portable wireless device

The quality of sleep can be affected by the occurrence of a sleep related disorder and, among these disorders, obstructive sleep apnea is commonly undiagnosed. Polysomnography is considered to be the gold standard for sleep analysis. However, it is an expensive and labor-intensive exam that is unavailable to a large group of the world population. To address these issues, the main goal of this work was to develop an automatic scoring algorithm to analyze the single-lead electrocardiogram signal, performing a minute-by-minute and an overall estimation of both quality of sleep and obstructive sleep apnea. The method employs a cross-spectral coherence technique which produces a spectrographic image that fed three one-dimensional convolutional neural networks for the classification ensemble. The predicted quality of sleep was based on the electroencephalogram cyclic alternating pattern rate, a sleep stability metric. Two methods were developed to indirectly evaluate this metric, creating two sleep quality predictions that were combined with the sleep apnea diagnosis to achieve the final global sleep quality estimation. It was verified that the quality of sleep of the nineteen tested subjects was correctly identified by the proposed model, advocating the significance of clinical analysis. The model was implemented in a non-invasive and simple to self-assemble device, producing a tool that can estimate the quality of sleep and diagnose the obstructive sleep apnea at the patient’s home without requiring the attendance of a specialized technician. Therefore, increasing the accessibility of the population to sleep analysis.info:eu-repo/semantics/publishedVersio

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field