Detecting and Quantifying Apnea Based on the ECG: The PhysioNet/Computing in Cardiology Challenge 2000

Description

Obstructive sleep apnea (intermittent cessation of breathing) is a common problem with major health implications, ranging from excessive daytime drowsiness to serious cardiac arrhythmias. Obstructive sleep apnea is associated with increased risks of high blood pressure, myocardial infarction, and stroke, and with increased mortality rates. Standard methods for detecting and quantifying sleep apnea are based on respiration monitoring, which often disturbs or interferes with sleep and is generally expensive. A number of studies during the past 15 years have hinted at the possibility of detecting sleep apnea using features of the electrocardiogram. Such approaches are minimally intrusive, inexpensive, and may be particularly well-suited for screening. The major obstacle to use of such methods is that careful quantitative comparisons of their accuracy against that of conventional techniques for apnea detection have not been published. We therefore offer a challenge to the biomedical research community: demonstrate the efficacy of ECG-based methods for apnea detection using a large, well-characterized, and representative set of data. The goal of the contest is to stimulate effort and advance the state of the art in this clinically significant problem, and to foster both friendly competition and wide-ranging collaborations. We will award prizes of US$500 to the most successful entrant in each of two events.1

Update Frequency

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License

Open Data Commons Attribution License v1.0

Documentation

https://physionet.org/content/challenge-2000/

Managed By

PhysioNet

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Contact

https://physionet.org/about/#contact_us

How to Cite

Detecting and Quantifying Apnea Based on the ECG: The PhysioNet/Computing in Cardiology Challenge 2000 was accessed on DATE from https://registry.opendata.aws/challenge-2000.