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.
EKG synchronized ensemble averaging of the impedance cardiogram tends to blur or suppress signal events due to signal jitter or event latency variability. Although ensemble averaging provides some improvement in the stability of the signal and signal to noise ratio under conditions of nonperiodic influences of respiration and motion, coherent averaging techniques were developed to determine whether further enhancement of the impedance cardiogram could be obtained. Physiological signals were obtained from sixteen male and female subjects during resting conditions. while delivering a speech and while undergoing submaximal bicycle exercise. Results indicated that improved resolution of dZ'dt signal events could be obtained using coherent ensemble averaging. Although some improvement in precision of event location was obtained, most enhancement of the impedance cardiogram occurred in measurement of the amplitude of the dZldt maximum (ejection velocity) during speaking and exercise conditions. Validated increases in dZldt maximum exceeding 20% were obtained in some subjects with coherent averaging. suggesting that the diagnostic utility of impedance cardiography can be improved by using this technique. (Supported by NHLBI research grants. HlA 1335 and HL36588.)
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