Multimodal Sleep Apnea Detection with Missing or Noisy Modalities

arXiv:2402.17788v1 Announce Type: cross
Abstract: Polysomnography (PSG) is a type of sleep study that records multimodal physiological signals and is widely used for purposes such as sleep staging and respiratory event detection. Conventional machine learning methods assume that each sleep study is associated with a fixed set of observed modalities and that all modalities are available for each sample. However, noisy and missing modalities are a common issue in real-world clinical settings. In this study, we propose a comprehensive pipeline …

abstract arxiv cs.lg detection eess.sp event machine machine learning multimodal records set sleep staging study type