APPLICATION OF THE DISCRETE WAVELET TRANSFORM FOR THE ROBUST DETECTION OF THE IMPULSIVE INCIDENCES: APPLICATION TO ARTERIAL BLOOD PRESSURE CHARACTERISTIC EVENTS DETECTION–DELINEATION

2011 ◽  
Vol 09 (05) ◽  
pp. 813-842 ◽  
Author(s):  
MOHAMMAD R. HOMAEINEZHAD ◽  
MOHAMMAD AGHAEE ◽  
HAMID NAJJARAN TOOSI ◽  
ALI GHAFFARI ◽  
REZA RAHMANI
Keyword(s):  
Blood Pressure ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Arterial Blood Pressure ◽  
False Alarm Probability ◽  
Discrete Wavelet ◽  
Robust Detection ◽  
Dicrotic Notch ◽  
Arterial Blood ◽  
Events Detection

The major focus of this study is to describe the structure of a solution designed for robustly detecting and delineating the arterial blood pressure (ABP) signal events. To meet this end, first, the original ABP signal is pre-processed by application of à trous discrete wavelet transform (DWT) for extracting several dyadic scales. Then, a fixed sample size sliding window is moved on the appropriately selected scale and in each slid, six features namely as summation of the nonlinearly amplified Hilbert transform, summation of absolute first-order differentiation, summation of absolute second-order differentiation, curve length, area and variance of the excerpted segment are calculated. Then, all feature trends are normalized and utilized to construct a newly proposed principal components analyzed geometric index (PCAGI) (to be used as the segmentation decision statistic (DS)) by application of a linear orthonormal projection. After application of an adaptive-nonlinear transformation for making the DS baseline stationary, the histogram parameters of the enhanced DS are used to regulate the α-level Neyman–Pearson classifier for false alarm probability (FAP)-bounded delineation of the ABP events. In order to illustrate the capabilities of the presented algorithm, it was applied to all 18 subjects of the MIT-BIH Polysomnographic Database (359,000 beats) and the end-systolic and end-diastolic locations of the ABP signal as well as dicrotic notch pressure were extracted and values of sensitivity and positive predictivity Se = 99.86% and P+ = 99.95% were obtained for the detection of all ABP events. High robustness against measurement noises, acceptable detection-delineation accuracy of the ABP events in the presence of severe heart valvular and arrhythmic dysfunctions within a tolerable computational burden (processing time) and having no parameters dependency to the acquisition sampling frequency can be mentioned as the important merits and capabilities of the proposed PCAGI-based ABP events detection-segmentation algorithm.

CLASSIFICATION OF CARDIAC ARRHYTHMIAS USING ARTERIAL BLOOD PRESSURE BASED ON DISCRETE WAVELET TRANSFORM

2017 ◽  
Vol 29 (05) ◽  
pp. 1750034 ◽  
Author(s):  
Roghayyeh Arvanaghi ◽  
Sabalan Daneshvar ◽  
Hadi Seyedarabi ◽  
Atefeh Goshvarpour
Keyword(s):  
Blood Pressure ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Arterial Blood Pressure ◽  
Cardiac Arrhythmias ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Ecg Signal ◽  
Arterial Blood

Early and correct diagnosis of cardiac arrhythmias is an important step in the treatment of patients. In the recent decades, a wide area of bio-signal processing is allocated to cardiac arrhythmia classification. Unlike other studies, which have employed Electrocardiogram (ECG) signal as a main signal to classify the arrhythmia and sometimes they have used other vital signals as an auxiliary signal to fill missing data and robust detections. In this study, the Arterial Blood Pressure (ABP) is used to classify six types of heart arrhythmias. In other words, in this study for first time, the arrhythmias are classified according ABP signal information. Discrete Wavelet Transform (DWT) is used to de-noise and decompose ABP signal. On feature extraction stage, three types of features including frequency, power, and entropy are extracted. In classification stage, Least Square Support Vector Machine (LS-SVM) is employed as a classifier. The accuracy, sensitivity, and specificity rates of 95.75%, 96.77%, and 96.32% are achieved, respectively. Currently, the classification of cardiac arrhythmias is based on the ABP signal which has some advantages. The recording of ABP signal is done by means of one electrode and therefore it has resulted in lower costs compared with the ECG signal. Finally, it has been shown that ABP has very important and valuable information about the heart performance and can be used in arrhythmia classification.

scholarly journals Detection of Onset, Systolic Peak and Dicrotic Notch in Arterial Blood Pressure Pulses

2017 ◽  
Vol 50 (7-8) ◽  
pp. 170-176 ◽  
Author(s):  
Omkar Singh ◽  
Ramesh Kumar Sunkaria
Keyword(s):  
Blood Pressure ◽  
Wavelet Transform ◽  
Arterial Blood Pressure ◽  
Pressure Pulse ◽  
Data Set ◽  
Dicrotic Notch ◽  
Arterial Blood ◽  
Comparison Results ◽  
Empirical Wavelet Transform ◽  
Pressure Pulses

In this paper, we proposed an effective method for detecting fiducial points in arterial blood pressure pulses. An arterial blood pressure pulse normally consists of onset, systolic peak and dicrotic notch. Detection of fiducial points in blood pressure pulses is a critical task and has many potential applications. The proposed method employs empirical wavelet transform for locating the systolic peak and onset of blood pressure pulse. The proposed method first estimates the fundamental frequency of blood pressure pulse using empirical wavelet transform and utilizes the combination of the blood pressure pulse and the estimated frequency for locating onset and systolic peak. For dicrotic notch detection, it utilizes the first-order difference of blood pressure pulse. The algorithm was validated on various open-source databases and was tested on a data set containing 12,230 beats. Two benchmark parameters such as sensitivity and positive predictivity were used for the performance evaluation. The comparison results for accuracy of the detection of systolic peak, onset and dicrotic notch are reported. The proposed method attained a sensitivity and positive predictivity of 99.95% and 99.97%, respectively, for systolic peaks. For onsets, it attained a sensitivity and predictivity of 99.88% and 99.92%, respectively. For dicrotic notches, a sensitivity and positive predictivity of 98.98% and 98.81% were achieved, respectively.

Dicrotic Notch Identification: a Generalizable Hybrid Approach under Arterial Blood Pressure (ABP) Curve Deformations

2021 ◽  
Author(s):  
Mahya Saffarpour ◽  
Debraj Basu ◽  
Fatemeh Radaei ◽  
Kourosh Vali ◽  
Jason Y. Adams ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Arterial Blood Pressure ◽  
Hybrid Approach ◽  
Dicrotic Notch ◽  
Arterial Blood

scholarly journals Age-Related Changes in Spontaneous Oscillations Assessed by Wavelet Transform of Cerebral Oxygenation and Arterial Blood Pressure Signals

2013 ◽  
Vol 33 (5) ◽  
pp. 692-699 ◽  
Author(s):  
Zengyong Li ◽  
Ming Zhang ◽  
Qing Xin ◽  
Site Luo ◽  
Ruofei Cui ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Wavelet Transform ◽  
Arterial Blood Pressure ◽  
Cerebral Oxygenation ◽  
Oxygenation Index ◽  
Elderly Subjects ◽  
Arterial Blood ◽  
Age Related ◽  
Spontaneous Oscillations ◽  
Young Subjects

The study aims to assess the spontaneous oscillations in elderly subjects based on the wavelet transform of cerebral oxygenation (CO) and arterial blood pressure (ABP) signals. Continuous recordings of near-infrared spectroscopy (NIRS) and ABP signals were obtained from simultaneous measurements in 20 young subjects (age: 27.3 ± 7.1 years) and 15 elderly subjects (age: 70.8 ± 5.1 years) at rest. Using spectral analysis based on wavelet transform, five frequency intervals were identified (I, 0.005 to 0.02 Hz; II, 0.02 to 0.06 Hz; III, 0.06 to 0.15 Hz; IV, 0.15 to 0.40 Hz; and V, 0.40 to 2.0 Hz). The average amplitudes of the Δ[HbO2] and tissue oxygenation index in intervals I to V and the relative amplitudes in intervals IV and V were significantly lower in elderly subjects than in young subjects ( P < 0.05). In addition, the relative amplitudes of the ABP in interval I were significantly lower in elderly subjects than in young subjects ( P = 0.016). The present findings suggest the presence of a cerebrovascular degenerative process caused by aging. Spontaneous oscillations in the CO could be used as an indicator of cerebrovascular changes and could be used to identify the risk for cerebrovascular degenerative processes.

Robust Detection of Systolic Peaks in Arterial Blood Pressure Signal

2017 ◽  
pp. 700-709
Author(s):  
Tomasz Pander ◽  
Robert Czabański ◽  
Tomasz Przybyła ◽  
Stanisław Pietraszek ◽  
Michał Jeżewski
Keyword(s):  
Blood Pressure ◽  
Arterial Blood Pressure ◽  
Robust Detection ◽  
Pressure Signal ◽  
Arterial Blood
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