@inbook{1bf209bb43844ef791a6eb5f160c0b7e,
title = "Stream computing for biomedical signal processing: A QRS complex detection case-study",
abstract = "Recent developments in 'Big Data' have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data.",
author = "Murphy, \{B. M.\} and C. O'Driscoll and Boylan, \{G. B.\} and G. Lightbody and Marnane, \{W. P.\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 ; Conference date: 25-08-2015 Through 29-08-2015",
year = "2015",
month = nov,
day = "4",
doi = "10.1109/EMBC.2015.7319741",
language = "English",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5928--5931",
booktitle = "2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015",
address = "United States",
}