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In this study, a simple mathematical-statistical based metric called Multiple Higher Order Moments (MHOM) is introduced enabling the electrocardiogram (ECG) detection-delineation algorithm to yield acceptable results in the cases of ambulatory holter ECG including strong noise, motion artifacts, and severe arrhythmia(s). In the MHOM measure, important geometric characteristics such as maximum value to minimum value ratio, area, extent of smoothness or being impulsive and distribution skewness degree (asymmetry), occult. In the proposed method, first three leads of high resolution 24-h holter data are extracted and preprocessed using Discrete Wavelet Transform (DWT). Next, a sample to sample sliding window is applied to preprocessed sequence and in each slid, mean value, variance, skewness, and kurtosis of the excerpted segment are superimposed called MHOM. The MHOM metric is then used as decision statistic to detect and delineate ECG events. To show advantages of the presented method, it is applied to MIT-BIH Arrhythmia Database, QT Database, and T-Wave Alternans Database and as a result, the average values of sensitivity and positive predictivity Se = 99.95% and P+ = 99.94% are obtained for the detection of QRS complexes, with the average maximum delineation error of 6.1, 4.1, and 6.5 ms for P-wave, QRS complex, and T-wave, respectively showing marginal improvement of detectiondelineation performance. In the next step, the proposed method is applied to DAY hospital high resolution holter data (more than 1,500,000 beats including Bundle Branch Blocks-BBB, Premature Ventricular Complex-PVC, and Premature Atrial Complex-PAC) and average values of Se = 99.97% and P+ = 99.95% are obtained for QRS detection. In summary, marginal performance improvement of ECG events detection-delineation process, reliable robustness against strong noise, artifacts, and probable severe arrhythmia(s) of high resolution holter data can be mentioned as important merits and capabilities of the proposed algorithm.

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This paper presents a new method to detect and to delineate phonocardiogram (PCG) sounds. Toward this objective, after preprocessing the PCG signal, two windows were moved on the preprocessed signal, and in each analysis window, two frequency-and amplitude-based features were calculated from the excerpted segment. Then, a synthetic decision making basis was devised by combining these two features for being used as an efficient detection-delineation decision statistic, (DS). Next, local extremums and locations of minimum slopes of the DS were determined by conducting forward-backward local investigations with the purpose of detecting sound incidences and their boundaries. In order to recognize the delineated PCG sounds, first, S1 and S2 were detected. Then, a new DS was regenerated from the signal whose S1 and S2 were eliminated to detect occasional S3 and S4 sounds. Finally, probable murmurs and souffles were spotted. The proposed algorithm was applied to 52 min PCG signals gathered from patients with different valve diseases. The provided database was annotated by some cardiology experts equipped by echocardiography and appropriate computer interfaces. The acquisition landmarks were in 2R (aortic), 2L (pulmonic), 4R (apex) and 4L (tricuspid) positions. The acquisition sensor was an electronic stethoscope (3 M Littmann® 3200, 4 kHz sampling frequency). The operating characteristics of the proposed method have an average sensitivity Se = 99.00% and positive predictive value PPV = 98.60% for sound type recognition (i.e., S1, S2, S3 or S4).

In this article, the problem of third-order consensus of homogeneous traffic flow formed by cooperative vehicular platoons is studied. This article is presented in two main parts. Inter-platoon stability analysis and intra-platoon stability analysis. For inter-platoon stability analysis, due to great length of traffic flow, it is assumed that lead vehicle is not available. Therefore, a new consensus algorithm based on bidirectional virtual leader-following strategy is introduced. Both communication and parasitic delays are involved in control design and stability analysis. By decoupling the closed-loop dynamics of cooperative leaders and employing the cluster treatment characteristic root method, necessary conditions on control parameters and stable regions of time delay satisfying internal stability of leaders' network are derived. In continuance of this part, inter-platoon string stability is studied. In the second part, it is assumed that the communication topology of each platoon is generic. Therefore, some of the eigenvalues of network matrix are complex which complicates the intra-platoon stability analysis. After decoupling the closed-loop dynamics of each platoon, a new consensus algorithm is presented. It will be shown that by this algorithm, the control parameters are independent of eigenvalues of network matrix which simplifies the controller design and stability analysis. Several simulation results are provided to show the effectiveness of the proposed approaches.

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In this paper the problem of centralized control of a platoon of non-identical vehicles under constant time headway strategy (CTHS) is investigated for multi predecessors following (MPF) topology. A centralized neighbor based linear control law using relative position and velocity is considered for each vehicle. Due to communication and parasitic delays and time-varying network topology, the closed-loop dynamics of platoon is in the form of a multiple delayed switched linear system. New approaches are developed to perform the internal stability analysis of one-dimensional heterogeneous vehicular platoons. Afterwards, sufficient conditions assuring the string stability of a platoon under MPF topology are obtained by presenting a new theorem. In continuance of the paper, some conditions on control parameters guaranteeing safety of the platoon in an emergency braking maneuver are presented through a new theorem. Several simulation results are provided to show the effectiveness of the proposed methods.