Arrhythmia ECG signal analysis using non parametric time-frequency technique

2015 ◽  
Author(s):  
Elmehdi Benmalek ◽  
Jamal Elmhamdi
Keyword(s):  
Signal Analysis ◽  
Ecg Signal ◽  
Time Frequency ◽  
Non Parametric

scholarly journals Arrhythmia ECG Signal Analysis using Non Parametric Time-Frequency Techniques

2012 ◽  
Vol 41 (4) ◽  
pp. 25-30 ◽  
Author(s):  
A. Dliou ◽  
R. Latif ◽  
M. Laaboubi ◽  
F. M. R. Maoulainine
Keyword(s):  
Signal Analysis ◽  
Ecg Signal ◽  
Time Frequency ◽  
Non Parametric

scholarly journals Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis

2017 ◽  
Vol 42 (1) ◽  
Author(s):  
Ahmed Faeq Hussein ◽  
Shaiful Jahari Hashim ◽  
Ahmad Fazli Abdul Aziz ◽  
Fakhrul Zaman Rokhani ◽  
Wan Azizun Wan Adnan
Keyword(s):  
Performance Evaluation ◽  
Signal Analysis ◽  
Ecg Signal ◽  
Frequency Distributions ◽  
Time Frequency

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Extending Acoustic Microscopy for Comprehensive Failure Analysis Applications

2010 ◽  
Author(s):  
Sebastian Brand ◽  
Matthias Petzold ◽  
Peter Czurratis ◽  
Peter Hoffrogge
Keyword(s):  
Image Processing ◽  
Failure Analysis ◽  
Signal Analysis ◽  
Flip Chip ◽  
Fault Isolation ◽  
Acoustic Microscopy ◽  
Specific Information ◽  
Full Potential ◽  
Time Frequency ◽  
Non Destructive

Abstract In industrial manufacturing of microelectronic components, non-destructive failure analysis methods are required for either quality control or for providing a rapid fault isolation and defect localization prior to detailed investigations requiring target preparation. Scanning acoustic microscopy (SAM) is a powerful tool enabling the inspection of internal structures in optically opaque materials non-destructively. In addition, depth specific information can be employed for two- and three-dimensional internal imaging without the need of time consuming tomographic scan procedures. The resolution achievable by acoustic microscopy is depending on parameters of both the test equipment and the sample under investigation. However, if applying acoustic microscopy for pure intensity imaging most of its potential remains unused. The aim of the current work was the development of a comprehensive analysis toolbox for extending the application of SAM by employing its full potential. Thus, typical case examples representing different fields of application were considered ranging from high density interconnect flip-chip devices over wafer-bonded components to solder tape connectors of a photovoltaic (PV) solar panel. The progress achieved during this work can be split into three categories: Signal Analysis and Parametric Imaging (SA-PI), Signal Analysis and Defect Evaluation (SA-DE) and Image Processing and Resolution Enhancement (IP-RE). Data acquisition was performed using a commercially available scanning acoustic microscope equipped with several ultrasonic transducers covering the frequency range from 15 MHz to 175 MHz. The acoustic data recorded were subjected to sophisticated algorithms operating in time-, frequency- and spatial domain for performing signal- and image analysis. In all three of the presented applications acoustic microscopy combined with signal- and image processing algorithms proved to be a powerful tool for non-destructive inspection.

A novel feature extraction-based ECG signal analysis

2021 ◽  
Author(s):  
Varun Gupta ◽  
Monika Mittal ◽  
Vikas Mittal ◽  
Arvind Kumar Sharma ◽  
Nitin Kumar Saxena
Keyword(s):  
Feature Extraction ◽  
Signal Analysis ◽  
Ecg Signal

ECG Signal Analysis for Classification of Congenital Heart Defects

2020 ◽  
Author(s):  
Muhammad Umar Khan ◽  
Sumair Aziz ◽  
Mumtaz Ch. Javeria ◽  
Anber Shahjehan ◽  
Zohaib Mushtaq ◽  
...  
Keyword(s):  
Congenital Heart Defects ◽  
Signal Analysis ◽  
Congenital Heart ◽  
Heart Defects ◽  
Ecg Signal

Three-Point Bending Test Evaluation of Concrete Specimens by Non-Traditional Analysis of Acoustic Emission Method

2016 ◽  
Vol 837 ◽  
pp. 198-202
Author(s):  
Luboš Pazdera ◽  
Libor Topolář ◽  
Tomáš Vymazal ◽  
Petr Daněk ◽  
Jaroslav Smutny
Keyword(s):  
Acoustic Emission ◽  
Signal Analysis ◽  
Measurement Data ◽  
Bending Test ◽  
Test Evaluation ◽  
Acoustic Emission Method ◽  
Emission Method ◽  
Three Point Bending ◽  
Time Frequency ◽  
Emission Signal

The aim of the paper is focused on the analysis of the mechanical properties of the concrete specimens with plasticizer at three point bending test by the signal analysis of the acoustic emission signal. The evaluations were compared the measurement and the results obtained with theoretical presumptions. The Joint Time Frequency Analysis applied on measurement data and its evaluation is described. It is well known that the Acoustic Emission Method is a very sensitive method to determine active cracks into structure. However, evaluation of acoustic emission signals is very difficult. A non-traditional method was used to signal analysis of burst acoustic emission signals recorded during three point bending test.

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