T Wave Alternans Features for Automated Detection

  • Authors:

  • Tomas Kulvičius;Minija Tamošiūnaitė;Rimas Vaišnys

  • Affiliations:

  • Department of Applied Informatics, Vytautas Magnus University, Vileikos 8, 44404 Kaunas, Lithuania, e-mail: m.tamosiunaite@if.vdu.lt;Department of Applied Informatics, Vytautas Magnus University, Vileikos 8, 44404 Kaunas, Lithuania, e-mail: m.tamosiunaite@if.vdu.lt;Department of Electrical Engineering, Yale University, Becton Center, P.O. Box 208284, New Haven, CT 06520-8284, USA, e-mail: rimas.vaisnys@yale.edu

  • Venue:
  • Informatica
  • Year:
  • 2005

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Abstract

T wave features suitable for automatic T wave alternans detection in low signal-to-noise ratio electrocardiograms are explored using a correlation-to-template-based algorithm for detecting T waves of variable duration. Amplitude and area features of T waves are found to be notably less sensitive to template selection than are duration features. T wave alternans features and measures which can be determined more stably provide better classification accuracy of patients with and without coronary artery lesions.