DocumentCode :
2394074
Title :
Metadata and annotations for multi-scale electrophysiological data
Author :
Bower, Mark R. ; Stead, Matt ; Brinkmann, Benjamin H. ; Dufendach, Kevin ; Worrell, Gregory A.
Author_Institution :
Mayo Syst. Electrophysiology Lab., Rochester, MN, USA
fYear :
2009
fDate :
3-6 Sept. 2009
Firstpage :
2811
Lastpage :
2814
Abstract :
The increasing use of high-frequency (kHz), long-duration (days) intracranial monitoring from multiple electrodes during pre-surgical evaluation for epilepsy produces large amounts of data that are challenging to store and maintain. Descriptive metadata and clinical annotations of these large data sets also pose challenges to simple, often manual, methods of data analysis. The problems of reliable communication of metadata and annotations between programs, the maintenance of the meanings within that information over long time periods, and the flexibility to re-sort data for analysis place differing demands on data structures and algorithms. Solutions to these individual problem domains (communication, storage and analysis) can be configured to provide easy translation and clarity across the domains. The multiscale annotation format (MAF) provides an integrated metadata and annotation environment that maximizes code reuse, minimizes error probability and encourages future changes by reducing the tendency to over-fit information technology solutions to current problems. An example of a graphical utility for generating and evaluating metadata and annotations for ldquobig datardquo files is presented.
Keywords :
bioelectric phenomena; biology computing; data analysis; error statistics; meta data; clinical annotations; code reuse maximization; data algorithms; data analysis; data communication; data storage; data structures; epilepsy; error probability minimization; high-frequency long-duration intracranial monitoring; metadata; multiple electrodes; multiscale annotation format; multiscale electrophysiological data; over-fit information technology; pre-surgical evaluation; Algorithms; Automatic Data Processing; Automation; Biomedical Engineering; Data Compression; Data Interpretation, Statistical; Electroencephalography; Electrophysiology; Humans; Programming Languages; Signal Processing, Computer-Assisted; Software;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
ISSN :
1557-170X
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2009.5333570
Filename :
5333570
Link To Document :
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