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

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

Conference

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

Fingerprint

Statistical tests
Parameterization
Support vector machines
Brain
Classifiers

Keywords

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

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.
Dietl, H. ; Weiss, S. / 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.8 p.
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abstract = "In this paper we compare the effect of the parameterisation on the automatic detection of diseases based on biomedical data. Exemplarily, we study theanalysis 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",
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author = "H. Dietl and S. Weiss",
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note = "2nd International Conference on Advances in Medical Signal and Information Processing, MEDSIP 2004 ; Conference date: 05-09-2004 Through 09-09-2004",

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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, 5/09/04 - 9/09/04, .

Parameterisation comparison for the detection of panic disorder using time-frequency transforms and support vector machines. / Dietl, H.; Weiss, S.

2004. Paper presented at 2nd International Conference on Advances in Medical Signal and Information Processing, Sliema, Malta.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Parameterisation comparison for the detection of panic disorder using time-frequency transforms and support vector machines

AU - Dietl, H.

AU - Weiss, S.

PY - 2004

Y1 - 2004

N2 - In this paper we compare the effect of the parameterisation on the automatic detection of diseases based on biomedical data. Exemplarily, we study theanalysis 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

AB - In this paper we compare the effect of the parameterisation on the automatic detection of diseases based on biomedical data. Exemplarily, we study theanalysis 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

KW - transient

KW - emissions

KW - otoacoustic

KW - evoked

KW - parameterisation comparison

KW - detection

KW - panic disorder

KW - time-frequency

KW - transforms

KW - support vector machines

M3 - Paper

ER -

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