The apnea-ECG database
By T. Penzel, G. Moody, R. Mark, Ary L. Goldberger, J. Peter. Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163), 2000
558 citations recorded by the source corpus.
Subfields: Cardiology and Cardiovascular Medicine, Physiology, Surgery
View Paper: https://www.semanticscholar.org/paper/9afa9c1c650d915c1b6f56b458ff3759bc26bf09
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cardiology and Cardiovascular Medicine
- Richard B. Reilly
- Philip de Chazal
- S. Van Huffel
- Farid Melgani
- Yakoub Bazi
- Serkan Kiranyaz
- Moncef Gabbouj
- Turker Ince
Citations in the corpus
- Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review (2017, unknown): “Dataset Ref No Subjs Age ECG PPG Resp Sigs Type of Breathing Level of Illness Datasets containing breath annotations BIDMC [31] 53 adult Y Y ImP spont, vent critical CapnoBase [8] 42 paed, adult Y Y CO2 spont, vent surgery, anaesthesia Datasets without breath annotations MIMIC-II [234] 23,180 paed, ”
- Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea (2003, methodology): “[4], [5] to determine the efficacy of ECG-based methods for apnoea detection using a large, well-characterized and representative database.”
- A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG (2015, methodology): “The first one is the Apnea-ECG database [4], [8], publicly available on Phy-”