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Recent research indicates a significant relationship between the severity of depression and heart rate variability (HRV). This paper presents a neuro-fuzzy approach-based classification algorithm, which distinguishes patients with depression from controls by a neuro-fuzzy network with a weighted fuzzy membership function (NEWFM) using the two time domain and four frequency domain features of HRV....
This paper presents a real-time algorithm for a mobile cardiac monitoring system to detect life-threatening arrhythmias. This detection algorithm focuses on two life-threatening arrhythmias ventricular tachycardia and fibrillation (VT/VF), which are detected through the application of pre-detection processing and main detection processing. In pre-detection processing, applies a statistical method...
This paper compares the forecasting performance of the feature extraction using the principal component analysis (PCA) that is one of the oldest and best known techniques in multivariate analysis with the feature selection using the non overlap area distribution measurement method based on the neural network with weighted fuzzy membership functions (NEWFM). This paper proposes CPPn,m (current price...
The ventricular arrhythmias including ventricular tachycardia (VT) and ventricular fibrillation (VF) are life-threatening heart diseases. This paper presents an approach to detect normal sinus rhythm (NSR) and VF/VT using the neural network with weighted fuzzy membership functions (NEWFM). NEWFM classifies NSR and VF/VT beats by the trained bounded sum of weighted fuzzy membership functions (BSWFMs)...
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