Pattern recognition: statistical, structural and neural approaches
Pattern recognition: statistical, structural and neural approaches
Argus, a clinical computer system for monitoring electrocardiographic rhythms
Argus, a clinical computer system for monitoring electrocardiographic rhythms
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Investigation of heart rate variability is of considerable interest in physiology, clinical medicine and drug development. HRV analysis requires accurate rhythm classification. The well-known ARGUS system defines the useful method of rhythm classification. The original set of features used in this method contains 4 parameters: QRS duration, QRS height, QRS offset and QRS area. Zhou at al. showed, that the spatial features: T wave amplitude in lead V2, QRS and T axes angles in frontal plane, and QRS-T spatial angle are of utmost value for diagnostic classification of ventricular conduction defects. We studied usefulness of spatial features instead of original ones in the ARGUS system classification method. The spatial features were computed using SPART method developed by the authors. Classification results for spatial and original features are similar and close to those obtained by the original ARGUS system. The study results confirm usefulness of spatial features for automatic rhythm analysis.