Published on Feb 12, 2016


An adequate blood flow supply is necessary for all organs of the body. Analysis of the blood flow finds its importance in the diagnoses of diseases. There are many techniques for analyzing the blood flow. These techniques are not affordable by the poor people because of their high expense. So we have implemented a technique called Zoom-FFT. This technique is simple and affordable to detect the blood clots and other diseases.Human with his potential tries to get whichever is unexplored, explored, and till now we are managing and succeeding using some technical ways.

In the same way this is one of the explorations made for scanning the intra details of some specific objects using ultrasound named SONOGRAPHY, which is used as an alternative to x-ray photography. In this paper, the method to zoom the image or the scanned data-using zoom FFT has been discussed. It also explains the algorithm to get ZOOM FFT and how it can be obtained via simulation. Real time experimentation and its applications, with basics of ultrasound scanning are also explained. Here a specific application will be dealt i.e., ultrasonic blood flow analyzer using ZOOM FFT.

Description of Implementation Of Zoom FFT

Blood flow analysis is done by passing a high frequency ultrasonic wave in the blood vessels through a transducer (transmitter) .The reflected signal; from the receiver transducer has a different frequency due to the Doppler principle. This signal is passed to a DSP processor to find the frequency spectrum. Because of the high frequency of the ultrasonic wave, the resolution of the frequency spectrum output will not be good. Therefore we go for advanced Zoom FFT technique, wherein a very small frequency change due to the clot formation can be obtained with a good resolution. It can be used to locate the initial presence of a blood clot. All of these tasks must be achieved with a single DSP chip in order for the system to be both cost-effective and power efficient and thus widely accepted.

The Fast Fourier Transform (FFT) is one of the most commonly used algorithms in digital signal processing and is widely used in applications such as image processing and spectral analysis.

The purpose of this application note is to investigate efficient partitioning/parallelization schemes for one-dimensional (1-D) FFTs on the TMS320C40 parallel processing DSP. Partitioning of the FFT algorithm is important in two special cases:

For computation of large FFTs in which input data doesn’t fit in the available processor’s on-chip RAM. In this case, execution must be performed with the data off-chip, resulting in performance degradation. As a consequence, execution time grows exponentially with the FFT size.


1. Increased frequency domain resolution
2.Reduced hardware cost and complexity


The Zoom-FFT is a process where an input signal is mixed down to baseband and then decimated, prior to passing it into a standard FFT. The advantage is for example that if you have a sample rate of 10 MHz and require at least 10Hz resolution over a small frequency band (say 1 KHz) then you do not need a 1 Mega point FFT, just decimate by a factor of 4096 and use a 256 point FFT which is obviously quicker.