Editorial: Machine Learning and Wearable Technology in Sleep Medicine 

Introduction

The “Machine Learning and Wearable Technology in Sleep Medicine” Research Topic consists of research articles related to the utilization of artificial intelligence (AI) to analyze sleep recordings, estimate sleep quality, and identify sleep disorders-related adverse health consequences as well as articles related to wearable sleep sensors and systems. This Editorial summarizes some key points of the Research Topic.

Short and interrupted sleep is related to several health-threatening medical conditions. Nearly one billion people worldwide suffer from obstructive sleep apnea (OSA) that causes a major burden to the affected individuals but also to the society and economy. However, most of the affected individuals remain undiagnosed mainly due to the unawareness of the disease and lack of readily available screening tools. This is, the current diagnostic methods in clinical sleep medicine are laborious, expensive, and too complex for self-application, thus not optimally suited for diagnosing a vastly increasing number of patients.

Keywords: artificial intelligence, machine learning, wearable sensors, sleep medicine, sleep disorders, deep learning, digital health.


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