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Pulse wave transit time (PWTT) method has been widely used in continuous blood pressure estimation by simultaneously measuring electrocardiogram and pulse signals in most researches [1]. Comparing with the morphological characteristic of photoplethysmograph (PPG) [2], the alternative sphygmogram (SPG) signal is much sharper and promising to improve the(More)
For purpose of detecting cardiovascular diseases (CVDs) hierarchically via hemodynamic parameters (HDPs) derived from sphygmogram, a hierarchical fuzzy neural networks (HFNNs) scheme is proposed, which provides a non-invasive way to detect CVDs. To deduce conclusion via HFNNs using HDPs as evidences, method of variance analysis is used to categorize and(More)
For the goal of cardiovascular disease risk detection, the statistic analysis is used to reduce the dimension of feature space and normalize each input feature; the modified Takagi-Sugeno model fuzzy neural networks are applied to realize the nonlinear mapping relationship between hemodynamic parameters and conclusions, which does not require predefining(More)
Pulse wave transmit time method has been used to estimate blood pressure by simultaneously measuring electrocardiogram & pulse signals [1]. Most researchers use photo reflective sensor to capture photoplethysmograph (PPG) signal by attaching sensor on finger tip. However, such a way would interfere hands in operating further the e-home healthcare system,(More)
A new approach to define and assign statistical parameters to Bayesian inference nodes derived from fuzzy logic technology is proposed. First to develop an intelligent medical diagnostic system, the individual membership function can be pre-defined by matching separately the adapted high-order polynomial, S-type or quasi-Gaussian function with plot of(More)
A method of using statistical analysis on site-sampled sphygmogram data sets and support vector machines classifier to diagnose coronary heart disease is proposed. The hemodynamic parameters derived from sphygmogram reflect the status of human cardiovascular system. Based on homodynamic parameters, the dimension reduction methods and a modified support(More)
After long-term exploration, it has been well established for the mechanisms of electrocardiogram (ECG) in health monitoring of cardiovascular system. Within the frame of an intelligent home healthcare system, our research group is devoted to researching/developing various mobile health monitoring systems, including the smart ECG interpreter. Hence, in this(More)
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