Accurate and computationally efficient means of electrocardiography (ECG) arrhythmia detec-tion has been the subject of considerable re-search efforts in recent years. Intelligent com-puting tools such as artificial n...Accurate and computationally efficient means of electrocardiography (ECG) arrhythmia detec-tion has been the subject of considerable re-search efforts in recent years. Intelligent com-puting tools such as artificial neural network (ANN) and fuzzy logic approaches are demon-strated to be competent when applied individu-ally to a variety of problems. Recently, there has been a growing interest in combining both of these approaches, and as a result, adaptive neural fuzzy filters (ANFF) [1] have been evolved. This study presents a comparative study of the classification accuracy of ECG signals using (MLP) with back propagation training algorithm, and a new adaptive neural fuzzy filter architec-ture (ANFF) for early diagnosis of ECG ar-rhythmia. ANFF is inherently a feed forward multilayered connectionist network which can learn by itself according to numerical training data or expert knowledge represented by fuzzy if-then rules [1]. In this paper we used an adap-tive neural fuzzy filter as an ECG beat classifier. We combined 3 famous wavelet transforms and used them mid 4 the order AR model coefficient as features. Our results suggest that a new proposed classifier (ANFF) with these features can generalize better than ordinary MLP archi-tecture and also learn better and faster. The results of proposed method show high accu-racy in ECG beat classification (97.6%) with 100% specificity and high sensitivity.展开更多
Objective:To evaluate the efficacy and safety of Wenxin Keli for premature beats in structurally normal heart systematically.Methods:Eight databases at home and abroad were searched to collect randomized controlled tr...Objective:To evaluate the efficacy and safety of Wenxin Keli for premature beats in structurally normal heart systematically.Methods:Eight databases at home and abroad were searched to collect randomized controlled trials of Wenxin Keli for premature beats without cardiac diseases.The included literatures were systematically evaluated with Cochrane Handbook 5.1 evaluation criteria and tools,and Meta analysis was performed with software RevMan5.3.Results:A total of 13 randomized controlled trials with 1278 subjects were included.The exprimental group used Wenxin Keli alone while the control group used antiarrhythmic medicine.The Meta analysis results showed that the total effective rate(RR=1.06,95%CI[0.97,1.16],P=0.23)and clinical symptom effective rate(RR=1.16,95%CI[0.94,1.44],P=0.18)of Wenxin Keli on idiopathic premature beats was not significantly different from western medicine group.The subgroup analysis of total effective rate showed that Wenxin Keli had no significant difference with metoprolol(RR=1.04,95%CI[0.95,1.15],P=0.41),bisoprolol(RR=1.32,95%CI[0.85,2.05],P=0.22)and propanone(RR=1.07,95%CI[0.90,1.26],P=0.44).ECG changes showed that the PR intervals(MD=-12.57,95%CI[-16.15,-8.99],P<0.00001)and QTc intervals(MD=-8.09,95%CI[-15.52,-0.65],P=0.03)in the western medicine group were prolonged significantly more than those of Wenxin Keli.In terms of safety,the incidence of adverse reactions of Wenxin Keli was significantly less than that of western medicine group(RR=0.32,95%CI[0.19,0.54],P<0.0001).Conclusion:The efficacy of Wenxin Keli in the treatment of premature beats with structurally normal heart is accurate,and there are no serious adverse reactions.However,because of the low quality of the included papers,which affected the reliability of the conclusions,high-quality clinical research is needed to further demonstrate.展开更多
文摘Accurate and computationally efficient means of electrocardiography (ECG) arrhythmia detec-tion has been the subject of considerable re-search efforts in recent years. Intelligent com-puting tools such as artificial neural network (ANN) and fuzzy logic approaches are demon-strated to be competent when applied individu-ally to a variety of problems. Recently, there has been a growing interest in combining both of these approaches, and as a result, adaptive neural fuzzy filters (ANFF) [1] have been evolved. This study presents a comparative study of the classification accuracy of ECG signals using (MLP) with back propagation training algorithm, and a new adaptive neural fuzzy filter architec-ture (ANFF) for early diagnosis of ECG ar-rhythmia. ANFF is inherently a feed forward multilayered connectionist network which can learn by itself according to numerical training data or expert knowledge represented by fuzzy if-then rules [1]. In this paper we used an adap-tive neural fuzzy filter as an ECG beat classifier. We combined 3 famous wavelet transforms and used them mid 4 the order AR model coefficient as features. Our results suggest that a new proposed classifier (ANFF) with these features can generalize better than ordinary MLP archi-tecture and also learn better and faster. The results of proposed method show high accu-racy in ECG beat classification (97.6%) with 100% specificity and high sensitivity.
基金National Natural Science Foundation of China(No.81774128)National key Research and development program(No.2019YFC1708404)。
文摘Objective:To evaluate the efficacy and safety of Wenxin Keli for premature beats in structurally normal heart systematically.Methods:Eight databases at home and abroad were searched to collect randomized controlled trials of Wenxin Keli for premature beats without cardiac diseases.The included literatures were systematically evaluated with Cochrane Handbook 5.1 evaluation criteria and tools,and Meta analysis was performed with software RevMan5.3.Results:A total of 13 randomized controlled trials with 1278 subjects were included.The exprimental group used Wenxin Keli alone while the control group used antiarrhythmic medicine.The Meta analysis results showed that the total effective rate(RR=1.06,95%CI[0.97,1.16],P=0.23)and clinical symptom effective rate(RR=1.16,95%CI[0.94,1.44],P=0.18)of Wenxin Keli on idiopathic premature beats was not significantly different from western medicine group.The subgroup analysis of total effective rate showed that Wenxin Keli had no significant difference with metoprolol(RR=1.04,95%CI[0.95,1.15],P=0.41),bisoprolol(RR=1.32,95%CI[0.85,2.05],P=0.22)and propanone(RR=1.07,95%CI[0.90,1.26],P=0.44).ECG changes showed that the PR intervals(MD=-12.57,95%CI[-16.15,-8.99],P<0.00001)and QTc intervals(MD=-8.09,95%CI[-15.52,-0.65],P=0.03)in the western medicine group were prolonged significantly more than those of Wenxin Keli.In terms of safety,the incidence of adverse reactions of Wenxin Keli was significantly less than that of western medicine group(RR=0.32,95%CI[0.19,0.54],P<0.0001).Conclusion:The efficacy of Wenxin Keli in the treatment of premature beats with structurally normal heart is accurate,and there are no serious adverse reactions.However,because of the low quality of the included papers,which affected the reliability of the conclusions,high-quality clinical research is needed to further demonstrate.
