An Improved Method of Measurement of ECG Parameters for Online Medical Diagnosis

The accuracy in the online measurement of ECG parameters has a decisive role in the better diagnosis and effective treatment of the diseases. The present paper describes a Lab-VIEW based programming using Pan Tompkins method to extract out QRS complex whereas QT interval measurements were carried out using Mat-lab based math-script module. Hilbert transform has been applied on the ECG signal to convert it into an analytical signal for better peak detection. Peak detection and other parameters like RR interval, HR and several time domain measures of heart rate variability such as RR mean and standard deviations, HR mean and standard deviations, RMSSSD, NN50 count, pNN50 etc were calculated for several other clinical applications apart from online disease diagnosis.