A novel method for detecting ventricular premature contraction (VPC) from the Holter system is proposed using wavelet transform (WT) and fuzzy neural network (FNN). The basic ideal and major advantage of this method is to reuse information that is used during QRS detection, a necessary step for most ECG classification algorithm, for VPC detection. To reduce the influence of different artifacts, the filter bank property of quadratic spline WT is explored. The QRS duration in scale three and the area under the QRS complex in scale four are selected as the characteristic features. It is found that the R wave amplitude has a marked influence on the computation of proposed characteristic features. Thus, it is necessary to normalize these features. This normalization process can reduce the effect of alternating R wave amplitude and achieve reliable VPC detection. After normalization and excluding the left bundle branch block beats, the accuracies for VPC classification using FNN is 99.79%. Features that are extracted using quadratic spline wavelet were used successfully by previous investigators for QRS detection. In this study, using the same wavelet, it is demonstrated that the proposed feature extraction method from different WT scales can effectively eliminate the influence of high and low-frequency noise and achieve reliable VPC classification. The two primary advantages of using same wavelet for QRS detection and VPC classification are less computation and less complexity during actual implementation.
In this study, the EEG, ECG and blood-pressure-pulse recorder were employed to evaluate heart rate variability, pulse rate variability, and EEG of 10 adults after scalp (experimental test I) at Sishencong scalp acupoint and auricular (experimental test II) acupuncture at Shenmen auricular acupoint for about 10 min. Comparison of the results between the experimental tests and a control with no stimulation test showed that both the heart rate and pulse rate were decreased, and the blood pressure fell. The high and low frequency power of FFT analysis of heart rate was increased and decreased, respectively; indicating that the parasympathetic nerves were activated and the sympathetic nerves were inhibited. The analysis of the power spectrum of EEG showed that the number of low frequency waves was increased after acupuncture stimulation. Therefore, acupuncture on either Sishencong or Shenmen might calm the mind, slow down the heart rate, and activate the parasympathetic nerves.
Dilated LA with global hypokinesia was noted in AF patients. Improved LA transport function was demonstrated in patients without any recurrence after ablation. However, the anatomic and functional reverse remodeling was not significant in patients with AF recurrence.
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