NDLI: Efficient hemodynamic event detection utilizing relational databases and wavelet analysis

Content Provider	IEEE Xplore Digital Library
Author	Saeed, M. Mark, R.G.
Copyright Year	2001
Description	Author affiliation: Harvard-MIT, Cambridge, MA, USA (Saeed, M.)
Abstract	Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on largescale time-oriented medical databases.
Starting Page	153
Ending Page	156
File Size	333503
Page Count	4
File Format	PDF
ISBN	0780372662
ISSN	02766547
DOI	10.1109/CIC.2001.977614
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-09-23
Publisher Place	Netherlands
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hemodynamics Event detection Relational databases Wavelet analysis Data analysis Heart rate Data models Search engines Time series analysis Data structures
Content Type	Text
Resource Type	Article

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