Automatic identification and recording of cardiac arrhythmia

M. Small, D. J. Yu, N. Grubb, J. Simonotto, K. A A Fox, R. G. Harrison

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

ECG waveform data showing the spontaneous evolution of ventricular fibrillation (VF) together with its precursors in humans is rare. When such data has been obtained, the resolution is often poor, or the length of pre-onset recording is limited. We describe a new automatic data collection facility that is capable of recording such data. We designed computer software that, in conjunction with Hewlett-Packard proprietary hardware, allows continuous monitoring of physiological waveforms from up to 24 separate hospital beds. Episodes of cardiac arrhythmia (including ventricular tachycardia and ventricular fibrillation) are identified online by either power spectral analysis or nonlinear complexity algorithm. Each episode is automatically recorded for 20 minutes with 10 minutes both before and after onset of the arrhythmia. When monitoring a 6-bed coronary care unit this facility will typically collect around 10-50 recordings per week. The majority of these will be artifacts. However, 2-8 genuine VF episodes will also be recorded per month.

Original languageEnglish
Pages (from-to)355-358
Number of pages4
JournalComputers in Cardiology
Publication statusPublished - 2000
Event1989 IEEE International Conference on Systems, Man, and Cybernetics - Cambridge, MA, United States
Duration: 14 Nov 198917 Nov 1989

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    Small, M., Yu, D. J., Grubb, N., Simonotto, J., Fox, K. A. A., & Harrison, R. G. (2000). Automatic identification and recording of cardiac arrhythmia. Computers in Cardiology, 355-358.