Use of the fast Fourier transform in the frequency analysis of the second heart sound in normal man

1976 ◽  
Vol 14 (4) ◽  
pp. 455-460 ◽  
Author(s):  
Ajit P. Yoganathan ◽  
Ramesh Gupta ◽  
William H. Corcoran ◽  
Firdaus E. Udwadia ◽  
Radha Sarma ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Frequency Analysis ◽  
Heart Sound ◽  
Normal Man ◽  
Second Heart Sound

Use of the fast fourier transform for frequency analysis of the first heart sound in normal man

1976 ◽  
Vol 14 (1) ◽  
pp. 69-73 ◽  
Author(s):  
Ajit P. Yoganathan ◽  
Ramesh Gupta ◽  
Firdaus E. Udwadia ◽  
J. Wayen Miller ◽  
William H. Corcoran ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Frequency Analysis ◽  
Heart Sound ◽  
First Heart Sound ◽  
Normal Man

scholarly journals Sparse Time-Frequency Decomposition for Multiple Signals with Same Frequencies

2017 ◽  
Vol 09 (04) ◽  
pp. 1750010
Author(s):  
Thomas Y. Hou ◽  
Zuoqiang Shi
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Frequency Analysis ◽  
Special Structure ◽  
Data Driven ◽  
Multiple Signals ◽  
Time Frequency ◽  
Frequency Decomposition ◽  
Engineering Problems ◽  
Instantaneous Frequencies

In this paper, we consider multiple signals sharing the same instantaneous frequencies. This kind of data is very common in scientific and engineering problems. To take advantage of this special structure, we modify our data-driven time-frequency analysis by updating the instantaneous frequencies simultaneously. Moreover, based on the simultaneous sparsity approximation and the Fast Fourier Transform, we develop several efficient algorithms to solve this problem. Since the information of multiple signals is used, this method is very robust to the perturbation of noise and it is applicable to the general nonperiodic signals even with missing samples or outliers. Several synthetic and real signals are used to demonstrate the robustness of this method. The performances of this method seems quite promising.

An Introduction to EMG Signal Processing Using MatLab and Microsoft Excel

2014 ◽  
pp. 95-112
Author(s):  
Daniel Robbins
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Frequency Analysis ◽  
Mean Square ◽  
Microsoft Excel ◽  
Signal Filtering ◽  
Emg Signal ◽  
Low Pass ◽  
High Pass

This chapter provides the reader with an introduction to the fundamentals of biological signal analysis and processing, using EMG signals to illustrate the process. The areas covered within the chapter include: frequency analysis using the Fast Fourier Transform, identifying noise within a signal, signal smoothing via root mean square (RMS) processing and signal filtering with both low-pass and high-pass filters. Guidelines for the application of the processes covered are included in conjunction with step by step examples using both MathWorks MatLab and Microsoft Excel software. Following the examples therefore allows the reader to practice the processes described to promote and reinforce their learning.

Time–Frequency Analysis of The Second Heart Sound to Assess Pulmonary Artery Pressure

2020 ◽  
Vol 66 (5) ◽  
pp. 542-547
Author(s):  
V. G. Andreev ◽  
V. V. Gramovich ◽  
M. V. Krasikova ◽  
A. I. Korolkov ◽  
O. N. Vyborov ◽  
...  
Keyword(s):  
Pulmonary Artery ◽  
Pulmonary Artery Pressure ◽  
Frequency Analysis ◽  
Heart Sound ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Artery Pressure ◽  
Second Heart Sound

A Four-Year Follow-Up of Mitral Bioprostheses by Fast Fourier Transform Monitoring of the First Heart Sound

1994 ◽  
Vol 8 (1) ◽  
pp. 7-10
Author(s):  
Enrico Baracca ◽  
Maria Brunazzi Brunazzi ◽  
Paolo Sgobino ◽  
Marco Vaccari ◽  
Mario Pasqualini ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Heart Sound ◽  
First Heart Sound
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