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In this paper, we present a novel feature-based neural network (NN) approach for estimation of blood pressure (BP) from wrist oscillometric measurements. Unlike previous methods that use the raw oscillometric waveform envelope (OMWE) as input to the NN, in this paper, we propose to use features extracted from the envelope. The OMWE is mathematically modeled as a sum of two Gaussian functions. The...
This paper presents a novel approach using principal component analysis (PCA) and adaptive neuro-fuzzy inference system (ANFIS) for estimation of blood pressure (BP) from oscillometric waveforms. The proposed method consists of three stages. In the first stage, the oscillation amplitudes (OAs) of the oscillometric waveforms are represented as a function of the cuff pressure. In the second stage, the...
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