Optimisation of an epileptiform activity detector for ambulatory use

  • E. M. Thomas
  • , D. Kelleher
  • , G. Lightbody
  • , D. Nash
  • , B. McNamara
  • , W. P. Mamane

Research output: Chapter in Book/Report/Conference proceedingsConference proceedingpeer-review

Abstract

A detector originally designed for seizure detection is modified to detect epileptiform activity in adults. The detector is intended for ambulatory use, and as such an emphasis is placed on the computational load of the detector. A framework is proposed making use of genetic algorithms in order to select the features for a Gaussian mixture classifier. Feature subset selection was performed by incorporating the computational load of each feature. This resulted in an improvement in classification results (larger area under both the ROC and PR curves), while reducing the runtime of the algorithm by up to 2000 fold with respect to a detector using the full feature set.

Original languageEnglish
Title of host publicationITAB 2010 - 10th International Conference on Information Technology and Applications in Biomedicine
Subtitle of host publicationEmerging Technologies for Patient Specific Healthcare
DOIs
Publication statusPublished - 2010
Event10th International Conference on Information Technology and Applications in Biomedicine: Emerging Technologies for Patient Specific Healthcare, ITAB 2010 - Corfu, Greece
Duration: 2 Nov 20105 Nov 2010

Publication series

NameProceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB

Conference

Conference10th International Conference on Information Technology and Applications in Biomedicine: Emerging Technologies for Patient Specific Healthcare, ITAB 2010
Country/TerritoryGreece
CityCorfu
Period2/11/105/11/10

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