Automated Scoring of Respiratory Events in Sleep With a Single Effort Belt and Deep Neural Networks

Abstract

The current gold standard of diagnosing sleep-disordered breathing, using polysomnography and manual analysis, is time-consuming, expensive, and only applicable in dedicated clinical environments. Automated analysis using a single effort belt signal overcomes these limitations.