About this Research Topic
Insufficient sleep increases the risk of developing serious medical conditions and shortened lifespan. Furthermore, sleep disorders affect hundreds of millions of people worldwide causing a major burden to the affected individuals, society, and economy. While sleep disorders are treatable, a majority of cases remain undiagnosed. This is mainly because current best-practices in sleep medicine are laborious and expensive, and do not take full advantage of today's technological possibilities.
The current diagnostic methods are technologically complex and cumbersome for diagnosing and treating ever-increasing numbers of patients and are particularly unsuitable for personalized early risk prediction, prevention, and intervention. However, recent advances in wearable sensor technology, digital signal processing, artificial intelligence, and big data technologies now provide exciting opportunities to develop new solutions, which can monitor sleep quality and detect a broader range of sleep disorders, better quantify disease severity, and better identify individuals at higher risk for severe health consequences.
We welcome submissions from the fields of physics, telemedicine, biomedical engineering, digital signal processing, artificial intelligence, sleep medicine, sleep disorders, wearable sensor technology, sleep trackers, biomedical devices, diagnostic systems, and health economics. Possible themes can include but are not limited to:
· Artificial intelligence in analyzing sleep recordings
· Artificial intelligence in the estimation of sleep quality
· Artificial intelligence in predicting poor sleep/sleep disorders-related adverse health consequences
· Wearable sensors in sleep medicine
· Novel electrode materials and manufacturing technologies in wearable sensors
· Consumer-grade sleep trackers in sleep monitoring and their implementation into clinical practice the estimation of sleep quality
· Sleep and its linkage to general well-being, novel methods to enhance sleep quality
All manuscript types will be considered, however, the highest priority will be given to original research, all types of reviews, and methods articles.
Dr. Massimiliano de Zambotti has received research funding from Ebb Therapeutics Inc., Fitbit Inc., International Flavors & Fragrances Inc., and Noctrix Health, Inc. All other Topic Editors declare no conflict of interest.
Keywords: Deep Learning, Artificial Intelligence, Wearable Sensors, Ambulatory Monitoring, Personalized Health Technology, Sleep Medicine, Sleep
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.