  Sleep apnea is a breathing disorder where a person repeatedly stops breathing
in sleep. Early detection is crucial for infants because it might bring long
term adversities. The existing accurate detection mechanism (pulse oximetry) is
a skin contact measurement. The existing non-contact mechanisms (acoustics,
video processing) are not accurate enough. This paper presents a novel
algorithm for the detection of sleep apnea with video processing. The solution
is non-contact, accurate and lightweight enough to run on a single board
computer. The paper discusses the accuracy of the algorithm on real data,
advantages of the new algorithm, its limitations and suggests future
improvements.

Signal Processing;Computer Vision and Pattern Recognition