Detection of Sharp Wave Activity in Biological Signals using Differentiation between Consecutive Samples

A number of signal processing techniques make use of first-derivative-based approaches for detecting regions of interest in biological signals. For instance, central and five-point derivative-based algorithms are employed for emphasizing and identification of the QRS complex in the ECG signal. Signal differentiation approaches are also used for detection and removal of high-frequency components associated to artefacts in the EEG signal. This paper aims to present a first-derivative approach based upon differentiation of consecutive samples – signal slope adaption (SSD) – for detecting regions of sharp wave activity in biological signals. A case study is analysed whereby SSD is used to mark and select the sharp wave activity associated to the QRS complex in the electrocardiogram. Evaluation of our methodology reveals that SSD shows to be effective for identification of QRS samples and, thereby, could be also employed to detect samples associated to sharp wave activity regions of other biological signals which possess similar signal