by Keyword: Pulse wave

Rodriguez, J, Schulz, S, Voss, A, Giraldo, BF, (2021). Classification of ischemic and dilated cardiomyopathy patients based on the analysis of the pulse transit time Conference Proceedings : ... Annual International Conference Of The Ieee Engineering In Medicine And Biology Society. Ieee Engineering In Medicine And Biology Society. Conference , 5527-5530

Cardiomyopathies diseases affects a great number of the elderly population. An adequate identification of the etiology of a cardiomyopathy patient is still a challenge. The aim of this study was to classify patients by their etiology in function of indexes extracted from the characterization of the pulse transit time (PTT). This time series represents the time taken by the pulse pressure to propagate through the length of the arterial tree and corresponding to the time between R peak of ECG and the mid-point of the diastolic to systolic slope in the blood pressure signal. For each patient, the PTT time series was extracted. Thirty cardiomyopathy patients (CMP) classified as ischemic (ICM - 15 patients) and dilated (DCM - 15 patients) were analyzed. Forty-three healthy subjects (CON) were used as a reference. The PTT time series was characterized through statistical descriptive indices and the joint symbolic dynamics method. The best indices were used to build support vector machine models. The optimal model to classify ICM versus DCM patients achieved 89.6% accuracy, 78.5% sensitivity, and 100% specificity. When comparing CMP patients and CON subjects, the best model achieved 91.3% accuracy, 91.3% sensitivity, and 88.3% specificity. Our results suggests a significantly lower pulse transit time in ischemic patients.Clinical relevance - This study analyzed the suitability of the pulse transit time for the classification of ICM and DCM patients. © 2021 IEEE.

JTD Keywords: Aged, Blood pressure, Cardiomyopathies, Cardiomyopathy, Cardiomyopathy, dilated, Congestive cardiomyopathy, Human, Humans, Pulse wave, Pulse wave analysis, Support vector machine