{"id":{"repo_id":"wvu","oai_identifier":"oai:researchrepository.wvu.edu:etd-1994"},"canonical_url":"https://search.dev.ndltd.org/etd/wvu/oai:researchrepository.wvu.edu:etd-1994","repository":{"repo_id":"wvu","name":"West Virginia University","base_url":"https://researchrepository.wvu.edu/do/oai/"},"display":{"title":"Study of the Kalman filter for arrhythmia detection with intracardiac electrograms","abstract":"Third generation implantable antitachycardia devices offer tiered-therapy to reverse ventricular fibrillation (VF) by defibrillation and ventricular tachycardia (VT) by low-energy cardioversion or antitachycardia pacing. The schemes for detecting cardiac arrhythmias often realize nonpathologic tachycardia as serious arrhythmias and deliver false shocks. In this study, an arrhythmia classification technique has been developed with the use of Kalman filter applied on cyclostationary autoregressive model. This new algorithm was developed with a training set of 24 arrhythmia passages and tested on a different data set of 29 arrhythmia passages. The algorithm provides 100% detection of VF on the test set. 77.8% of VTs were detected correctly while 16.7% of VTs were diagnosed as sinus rhythm and 5.5% of VTs were detected as VF.","abstract_html":"Third generation implantable antitachycardia devices offer tiered-therapy to reverse ventricular fibrillation (VF) by defibrillation and ventricular tachycardia (VT) by low-energy cardioversion or antitachycardia pacing. The schemes for detecting cardiac arrhythmias often realize nonpathologic tachycardia as serious arrhythmias and deliver false shocks. In this study, an arrhythmia classification technique has been developed with the use of Kalman filter applied on cyclostationary autoregressive model. This new algorithm was developed with a training set of 24 arrhythmia passages and tested on a different data set of 29 arrhythmia passages. 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The schemes for detecting cardiac arrhythmias often realize nonpathologic tachycardia as serious arrhythmias and deliver false shocks. In this study, an arrhythmia classification technique has been developed with the use of Kalman filter applied on cyclostationary autoregressive model. This new algorithm was developed with a training set of 24 arrhythmia passages and tested on a different data set of 29 arrhythmia passages. The algorithm provides 100% detection of VF on the test set. 77.8% of VTs were detected correctly while 16.7% of VTs were diagnosed as sinus rhythm and 5.5% of VTs were detected as VF."]},{"key":"dc:title","label":"Title","values":["Study of the Kalman filter for arrhythmia detection with intracardiac electrograms"]}]}],"canonical_facts":{"dc:contributor":["Stephanie A. 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