Feature subset selection for blood pressure classification using orthogonal forward selection

S. Colak, C. Isik

Research output: Contribution to journalConference articlepeer-review

15 Scopus citations

Abstract

Systolic and diastolic pressures are used to define cardiac related health in general medicine. In our present work1, we investigate blood pressure classification based on pressure waveforms using a relatively large non-invasively collected database. Feature selection is required to reduce redundant features in the data set for a better classification. Therefore, a selection method based on an orthogonal transform is used.

Original languageEnglish (US)
Pages (from-to)122-123
Number of pages2
JournalProceedings of the IEEE Annual Northeast Bioengineering Conference, NEBEC
StatePublished - 2003
EventProceedings of the IEEE 29th Annual Northeast Bioengineering Conference - Newark, NJ, United States
Duration: Mar 22 2003Mar 23 2003

Keywords

  • Blood pressure classification
  • Feature selection
  • Orthogonal decomposition

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Bioengineering

Fingerprint

Dive into the research topics of 'Feature subset selection for blood pressure classification using orthogonal forward selection'. Together they form a unique fingerprint.

Cite this