Parameterisation comparison for the detection of panic disorder using time-frequency transforms and support vector machines

H. Dietl, S. Weiss

Research output: Contribution to conferencePaper

48 Downloads (Pure)

Abstract

In this paper we compare the effect of the parameterisation on the automatic detection of diseases based on biomedical data. Exemplarily, we study the
analysis of event related brain potentials in patients suffering from panic disorder, whereby the data comprises responses to neutral and panic causing stimuli. This data is parameterised by time-frequency (TF) transforms, from which features are selected by a statistical test. The selected features represent the input to a support vector machine classifier yielding a detection rate for the TF parametrised data. This is compared with detection rates obtained for unparameterised time domain data
Original languageEnglish
Number of pages8
Publication statusPublished - 2004
Event2nd International Conference on Advances in Medical Signal and Information Processing - Sliema, Malta
Duration: 5 Sep 20049 Sep 2004

Conference

Conference2nd International Conference on Advances in Medical Signal and Information Processing
Abbreviated titleMEDSIP 2004
CountryMalta
CitySliema
Period5/09/049/09/04

Keywords

  • transient
  • emissions
  • otoacoustic
  • evoked
  • parameterisation comparison
  • detection
  • panic disorder
  • time-frequency
  • transforms
  • support vector machines

Fingerprint Dive into the research topics of 'Parameterisation comparison for the detection of panic disorder using time-frequency transforms and support vector machines'. Together they form a unique fingerprint.

  • Cite this

    Dietl, H., & Weiss, S. (2004). Parameterisation comparison for the detection of panic disorder using time-frequency transforms and support vector machines. Paper presented at 2nd International Conference on Advances in Medical Signal and Information Processing, Sliema, Malta.