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Efficient hemodynamic event detection utilizing relational databases and wavelet analysisDevelopment 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 large-scale time-oriented medical databases.
Document ID
20040087463
Document Type
Reprint (Version printed in journal)
Authors
Saeed, M. (Harvard-MIT Cambridge, United States)
Mark, R. G.
Date Acquired
August 21, 2013
Publication Date
January 1, 2001
Publication Information
Publication: Computers in cardiology
Volume: 28
ISSN: 0276-6574
Subject Category
Life Sciences (General)
Funding Number(s)
CONTRACT_GRANT: NCC9-58
Distribution Limits
Public
Copyright
Other
Keywords
NASA Discipline Cardiopulmonary
NASA Program Biomedical Research and Countermeasures
Non-NASA Center