@inbook{a5806f97c73045ea905e1ec2f1a91b2d,
title = "The effect of lossy ECG compression on QRS and HRV feature extraction",
abstract = "This paper describes the performance of beat detection and heart rate variability (HRV) feature extraction on electrocardiogram signals which have been compressed and reconstructed with a lossy compression algorithm. The set partitioning in hierarchical trees (SPIHT) compression algorithm was used with sixteen compression ratios (CR) between 2 and 50 over the records of the MIT/BIH arrhythmia database. Sensitivities and specificities between 99% and 85% were computed for each CR utilised. The extracted HRV features were between 99% and 82% similar to the features extracted from the annotated records. A notable accuracy drop over all features extracted was noted beyond a CR of 30, with falls of 10% accuracy beyond this compression ratio.",
keywords = "Sensitivity and Specificity, Artifacts, Signal Processing, Computer-Assisted, Reproducibility of Results, Humans, Diagnosis, Computer-Assisted, Algorithms, Artificial Intelligence, Electrocardiography, Sample Size, Pattern Recognition, Automated, Data Compression, Arrhythmias, Cardiac",
author = "Niall Twomey and Noel Walsh and Orla Doyle and Brian McGinley and Martin Glavin and Edward Jones and Marnane, {W P}",
year = "2010",
doi = "10.1109/IEMBS.2010.5627261",
language = "English",
isbn = "978-1-4244-4123-5",
volume = "2010",
series = "IEEE Engineering in Medicine and Biology Society",
publisher = "IEEE",
pages = "634--7",
booktitle = "2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)",
}