  Quality sleep is very important for a healthy life. Nowadays, many people
around the world are not getting enough sleep which is having negative impacts
on their lifestyles. Studies are being conducted for sleep monitoring and have
now become an important tool for understanding sleep behavior. The gold
standard method for sleep analysis is polysomnography (PSG) conducted in a
clinical environment but this method is both expensive and complex for
long-term use. With the advancements in the field of sensors and the
introduction of off-the-shelf technologies, unobtrusive solutions are becoming
common as alternatives for in-home sleep monitoring. Various solutions have
been proposed using both wearable and non-wearable methods which are cheap and
easy to use for in-home sleep monitoring. In this paper, we present a
comprehensive survey of the latest research works (2015 and after) conducted in
various categories of sleep monitoring including sleep stage classification,
sleep posture recognition, sleep disorders detection, and vital signs
monitoring. We review the latest works done using the non-invasive approach and
cover both wearable and non-wearable methods. We discuss the design approaches
and key attributes of the work presented and provide an extensive analysis
based on 10 key factors, to give a comprehensive overview of the recent
developments and trends in all four categories of sleep monitoring. We also
present some publicly available datasets for different categories of sleep
monitoring. In the end, we discuss several open issues and provide future
research directions in the area of sleep monitoring.
