PHD Project Low-Power FPGA controlled ECG-acquisition System for detection of Cardiac Diseases

 

Module Description

Design of ECG data read Module

ü  In the proposed Design Multiple data sets can be extracted from different patients who is having cardiac disease and who appears normal in cardiac system can be takes as test.

ü  The data sets are nothing but the patient’s original electro-cardio gram peak voltage values taken as PQRST waves

ü  These data are further stored in a text file for file reading

ü  In the VHDL code we write a file read process which read the peak voltage values in decimal or binary format. Which is converted in a simple MATLAB code

Design of Signal analysis Module

ü  The information are further stored in a dedicated digital LUT designed in VHDL code.

ü  Signal Analysis Module is used to classify the signal information peak values and pick the best value to process.

ü  ECG information have lots of peak threshold levels, each levels conveys the disease related accurate check points

ü  We have a detailed data base of cardiac disease which are able to detect by the PQRST wave can be stored in separate Latched Flip flop based LUTS

ü  Example, If a patient is possibly have a mild attach his PQRST check points such as ELOW will be less threshold , NR enabled will be HIGH in state.These kind of threshold information are stored in a clock controlled LATCHES

Design of Classification Algorithm

ü  In the Classification Module we get the constant values of check points which are going to be considered.

ü  Input patient samples are also further multiplied with a fixed constant to make the measurement more accurate.

Design of integration module

ü  Integration module consists of port mapping algorithm, component declarations to enable the main module enclose the sub modules with the Top module.

ü  The architecture of the proposed was able to work with min of KHZ to High speed of MHZ for storing.

ü  Data are predicted with respect to the heart pulses. Various cardiac diseases can be detected by this method efficiently.

Advantages of Proposed Design

ü  Data acquisition accuracy is increased to 90%

ü  Multiple cardiac diseases can be detected

ü  Critical Points are measured in high resolution

 

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