The interpretation and estimation of the QT interval in the ECG can help to detect the risky malignant ventricular arrhythmia and prevent the sudden death caused by the unusual QT segment. In an ECG signal, a QT interval in one cardiac cycle is defined as a segment before the beginning of Q-wave to the end of T-wave. The proposed technique consists of a pre-processing stage followed by baseline identification for better R-peak detection. Thereafter, QRS is detected by implementing a decision based rule on the root mean square value of the signal. A RR interval was used to detect T-wave and T-wave offset points after the S-wave. Similarly, P-onset points were detected prior to the Q-wave. After that, the corrected QTc and QT interval were calculated between Q and T-waves. The proposed method is applied to the standard QT-database, and examines the short and prolonged QT intervals using Bazett, Fridericia, Framingham, and Hodges formulae to explore QT-RR co-variability for the stratification of cardiac diseases. Among the four different formulas, the Bazett method yields an overall average QT interval of 517 ms, which is consistent and accurate with different heart rates.