PERFORMANCE EVALUATION OF SMART OSA DETECTION: ARTIFICIAL INTELLIGENCE AND NEURAL NETWORK WITH ECG

Sleep-apnea has been related to breathe and sleep associated with respirational illness. The prolonged Sleep apnea (SA) can lead to serious cardiovascular and neurological diseases. The SA has been diagnosed by the patient with Polysomnography (PSG). But there have been many complications and the test has been only possible with the hospitalized patient with one or two nights. There have been much research has been carried out for an alternative for the PSG. One of the most interesting research with a single-lead ECG test by the wearable device. In this paper review the various research for the detection of SA with ECG. Numerous works issued in the widespread journals between 2016 and 2020 are reviewed in this paper to accomplish these requirements. The reviewed articles are compared concerning algorithms' simplicity, the type they belong, and the performance metrics the work assumed that the movement in the application of elementary methods to detect SA is better than the recommendations that custom some artificial-intelligence techniques