A new design of a system for preliminary detection of defective hearts is proposed which is composed of two subsystems, in which one is based on the relationship between the electrocardiogram (ECG) and phonocardiogram (PCG) signals. The relationship between both signals is determined as an impulse response (h(n)) of a system, where the decision is made based on the linear predictive coding coefficients of a heart’s impulse response. The other subsystem uses a phase space approach, in which the mean squared error between the distance vectors of the phase space of the normal heart and abnormal heart is judged by the likelihood ratio test (Λ) value, on which the decision is made. The advantage of the proposed system is that a heart’s diagnosis system based on the ECG and EPCG signals can lead to high performance heart diagnostics.
In this paper a simple low cost measurement system of electrocardiogram (ECG) is presented. It is implemented by digitizing the measured ECG signal and then wireless (infrared) transmitting to be displayed the result on the computer screen. The analog-to-digital converter of the proposed method is based on a simple sigma-delta modulator. The main advantage of this circuit is that it has noise-shaping property. In addition, the employed sigma-delta modulator has an inherent clock signal. The external clock signal is therefore not required. The obtained sigma-delta output is sent to the receiver by the infrared driver circuit. The infrared wave received at the receiver is converted into an electrical signal and then passed through the low pass filter to recover the ECG signal. The reconstructed ECG signal is fed to the computer soundcard to be displayed on the screen. The experimental results show that the proposed system is fairly effective where the total harmonic distortion (THD) of system is lower than 0.08%.
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In this paper, a new automated early-stage detection of heart defect is introduced. Based on the proposed technique, human heart is modeled as a pump system where ECG signal and PCG signal are defined to be command (input) and response (output) of the system, respectively. The ratio of discrete Fourier transform of both signals is employed to determine the transfer function ( ) p H k of a patient's heart system. The early-stage heart defect detection is fundamentally based on the correlation between the standard transfer function ( ) s H k and the patient heart transfer function ( ) p H k . The obtained correlation measurement is fed to be the input of neural network to make decision whether or not patient's heart is normal. The proposed method provides satisfying results where negative and positive false rates approximately are 12.50% and 11.11%, respectively.
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