Adaptive ECG interval extraction

ECG intervals such as QRS, QT and PR provide significant information and are widely used as clinical parameters for diagnosing cardiac diseases. This paper presents a novel QRS detection technique based on Curve Length Transform (CLT) and a refined delineation of P-wave and T-wave using Discrete Wavelet Transform (DWT). The proposed technique was verified using the PhysioNet database. The QRS detection achieved a sensitivity of 98.59% and a positive predictivity of 97.86%. The QRS duration, QT interval and PR interval had a mean error of -1.56± 28.8ms, -5.39± 42.4ms and 0.86± 40.3ms respectively. The proposed algorithm is computationally efficient and is simpler to implement in hardware, hence, will lead to a faster execution time, smaller design area and consequently low power consumption.