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Cardiovascular Coupling-Based Classification of Ischemic and Dilated Cardiomyopathy Patients

文献类型： 会议论文

第一作者： Javier Rodriguez

作者： Javier Rodriguez 1 ; Steffen Schulz 2 ; Andreas Voss 2 ; Beatriz F. Giraldo 3 ;

作者机构： 1.Institute for Bioengineering of Catalonia (IBEC), Automatic Control Dept. (ESAII), Universitat Politècnica de Catalunya (UPC), Spain

2.the Ernst-Abbe-Hochschule Jena, University of Applied Sciences Jena, Institute of Innovative Health Technologies, Carl-Zeiss- Promenade 2. 07745 Jena, Germany

3.Automatic Control Dept. (ESAII), the Barcelona East School of Engineering (EEBE), Universitat Politècnica de Catalunya (UPC), Institute for Bioengineering of Catalonia (IBEC) - The Barcelona Institute of Science and Technology, and CIBER de Bioengeniería, Biomateriales y Nanomedicina (CIBER-BBN), Av. Eduard Maristany, 16. 08019, Barcelona, Spain

关键词： Cardiovascular Coupling;Classification;Cardiomyopathy Patients

会议名称： International Conference of the IEEE Engineering in Medicine and Biology Society

主办单位：

页码： 2007-2010

摘要： Cardiovascular diseases are one of the most common causes of death in elderly patients. The etiology of cardiomyopathies is difficult to discern clinically. The objective of this study was to classify cardiomyopathy patients using coupling analysis, through their cardiovascular behavior and the baroreflex response. A total of thirty-eight cardiomyopathy patients (CMP) classified as ischemic (ICM, 25 patients) and dilated (DCM, 13 patients) were analyzed. Thirty elderly control subjects (CON) were used as reference. Their electrocardiographic (ECG) and blood pressure (BP) signals were studied. To characterize the cardiovascular activity, the following temporal series were extracted: beat-to-beat intervals (from the ECG signal), and end- systolic and diastolic blood pressure amplitudes (from the BP signal). Non-linear characterization techniques like high resolution joint symbolic dynamics, segmented Poincaré plot analysis, normalized short-time partial directed coherence, and dual sequence method were used to characterize these times series. The best indices were used to build support vector machine models for classification. The optimal model for ICM versus DCM patients achieved 84.2% accuracy, 76.9% sensitivity, and 88% specificity. When CMP patients and CON subjects were compared, the best model achieved 95.5% accuracy, 97.3% sensitivity, and 93.3% specificity. These results suggest a disfunction in the baroreflex mechanism in cardiomyopathies patients.

分类号： r318-532

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