This paper will purpose a beat recognition algorithm using discrete wavelet coefficients and fuzzy hybrid neural network. Cardiac beats have been detected from differential of compressed wavelet coefficients by Linear Approximation Data Transfer (LADT) algorithm and adaptive thresholds. The variance and sum of the squared wavelet coefficients and the R-R ratio of successive beats have been applied to the self organizing subnetwork connected in cascade with a multi layer perceptron as final classifier.The c-means and Gustafson-Kessel algorithms have been applied for the self-organizing layer. Potential of the method was examined using MIT_BIH arrhythmia database. Results show high detection (99.43%) and high sensitivity (99.65%) on 59864 detected beats and 100% sensitivity and specificity on premature beat recognition.

The paper addresses a new QRS complex geometrical feature extraction technique as well as its application for electrocardiogram (ECG) supervised hybrid (fusion) beat-type classification. To this end, after detection and delineation of the major events of ECG signal via a robust algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of three Multi Layer Perceptron-Back Propagation (MLP-BP) neural networks with different topologies and one Adaptive Network Fuzzy Inference System (ANFIS) were designed and implemented. To show the merit of the new proposed algorithm, it was applied to all MIT-BIH Arrhythmia Database records and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.27% was obtained. Also, the proposed method was applied to 8 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, VE, PB, VF) belonging to 19 number of the aforementioned database and the average value of Acc=98.08% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer-reviewed studies in this area.

Background: Non-stress test is the most widely used test to assess fetal status. The presence of beat-to-beat variability is reassuring while its absence is not reassuring.Methods: In this single-blind clinical trial, 213 pregnant women with gestational age of 37 - 41 weeks were randomly allocated into three groups (auditory intervention for mother, auditory intervention for fetus, and control), each containing 71 subjects. The data were analyzed using one-way ANOVA followed by Tukey HSD test and Kruskal-Wallis test. In addition, paired t-test was used to compare each group before and after the intervention.Results: The results showed a significant difference among the three groups regarding beat-to-beat variability of fetal heart rate in the second 10 minutes of the test (P=0.006). Besides, the results of Tukey HSD test indicated that this difference was significant between the control group and auditory intervention for mother group (P=0.004). Moreover, the results of t-test showed a significant difference in beat-to-beat variability of fetal heart rate between the first and the second 10 minutes of the test in both groups of auditory intervention for mother (P<0.001) and for fetus (P<0.001).Conclusions: Since beat-to-beat variability of the fetal heart rate is indicator of fetal health, music intervention can be used to increase the number of accelerations and reduce false positive results in NST.

Introduction: Autonomic changes play an essential role in the genesis of neurally mediated syncope (NMS). The aim of this study was to compare the changes of the autonomic nervous system (ANS) by measuring spectral indices of beat-to-beat systolic blood pressure and heart rate variability (SBPV and HRV) in ranges of low frequency (LF), high frequency (HF), and the LF/HF ratio during head-up tilt test (HUTT) in patients with and without a syncope response. Methods: In this case-control study of 46 patients with a suspected history of unexplained syncope, data were recorded separately during the typical three phases of HUTT. Patients who developed syncope were designated as the case group and the rest as the control group. Results: Thirty one patients experienced syncope during HUTT. Resting HRV and SBPV indices were significantly lower in cases than controls. After tilting in the syncope group, both HF and LF powers of SBPV showed a significant and gradual decrease. LF/HF in HRV increased in both groups similarly during the test but in SBPV, mainly driven by oscilations in its LF power, it increased significantly more during the first two phases of the test in syncope patients only to paradoxically decrease during active tilt (P< 0. 001). Conclusion: Our findings show an abnormal autonomic function in patients with syncope, both at rest and tilting. Fluctuations of spectral indices of beat-to-beat SBPV, a potential noval index of pure sympathetic activity, show an exaggerated response during tilt and its withdrawal before syncope.