Packets wavelets and stockwell transform analysis of femoral Doppler ultrasound signals

4Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

Ultrasonic Doppler signals are widely used in the detection of cardiovascular pathologies or the evaluation of the degree of stenosis in the femoral arteries. The presence of stenosis can be indicated by disturbing the blood flow in the femoral arteries, causing spectral broadening of the Doppler signal. To analyze these types of signals and determine stenosis index, a number of time-frequency methods have been developed, such as the short-time Fourier transform, the continuous wavelets transform, the wavelet packet transform, and the S-transform

References Powered by Scopus

Analysis and simplification of three-dimensional space vector PWM for three-phase four-leg inverters

181Citations
N/AReaders
Get full text

A new optimized Stockwell transform applied on synthetic and real non-stationary signals

91Citations
N/AReaders
Get full text

Selection of the order of autoregressive models for spectral analysis of doppler ultrasound signals

50Citations
N/AReaders
Get full text

Cited by Powered by Scopus

A review on sparse Fast Fourier Transform applications in image processing

26Citations
N/AReaders
Get full text

Modified spiht algorithm for quincunx wavelet image coding

4Citations
N/AReaders
Get full text

Selection of compression test images using variance-based statistical method

3Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Latfaoui, M., & Bereksi Reguig, F. (2018). Packets wavelets and stockwell transform analysis of femoral Doppler ultrasound signals. International Journal of Electrical and Computer Engineering, 8(6), 4212–4220. https://doi.org/10.11591/ijece.v8i6.pp4212-4220

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 3

60%

Lecturer / Post doc 2

40%

Readers' Discipline

Tooltip

Engineering 3

60%

Computer Science 1

20%

Social Sciences 1

20%

Save time finding and organizing research with Mendeley

Sign up for free