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mws_che_fft_phy_problem

# mws_che_fft_phy_problem - Chapter 11.00B Physical Problem...

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11.00C.1 Chapter 11.00B Physical Problem for Fast Fourier Transform Chemical Engineering Signal processing (Fast Fourier transforms (FFT), Power spectral density (PSD)) has emerged as an important tool to provide improved diagnosis of cardiovascular pathologies. Cardiovascular disorders are the leading causes of death in the United States, requiring an enhanced diagnosis to facilitate treatment at an early stage. An ECG (Electrocardiogram), which is a measure of the electrical conductivity of the heart, provides clinical information about the health of the heart. Parameter extraction from the ECG requires its preprocessing and analysis to obtain features that have prognostic value and provide a heart disease pattern. In the current problem, we will use FFT and PSD to differentiate ECG signals of normal subjects from those having ventricular arrhythmias, who eventually had sudden cardiac arrest. The ECG signals are obtained from the database collection provided by http://www.physionet.org/physiobank . The FFT of a signal ) ( n x is given by nw N i N n e n x w F 2 1 0 ) ( ) ( ; 1 ,..., 2 , 1 , 0 N w If the signal is not exactly periodic, which means that the start and end points of the signal do not lie at the same point of the cycle, the FFT can have non-zero values even at non-resonant frequencies. In such a case, sometimes the peaks of the FFT can become smeared. This is known as leakage and is a very common situation in any measurement. To improve the FFT resolution, the signal is multiplied by a window which forces the signal to become perfectly periodic. The power spectral density (PSD) of a signal indicates how the power of a signal is distributed in the frequency domain, i.e., it gives the energy spectrum of the signal. It is defined as the squared modulus of the FFT, scaled by the length of the signal.

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