A real-time QRS detection algorithm using topological mapping and modified spatial velocity achieved a 99.58% detection rate, 99.57% sensitivity, and 99.87% positive predictivity.
Does a simple real-time QRS detection algorithm using topological mapping accurately detect QRS complexes in ECG signals from the MIT/BIH arrhythmia database?
A novel real-time QRS detection algorithm using topological mapping demonstrates high sensitivity and positive predictivity on the MIT/BIH arrhythmia database.
A simple algorithm using topological mapping has been developed for a real-time detection of the QRS complexes of ECG signals. As a measure of QRS complex energy, the authors used topological mapping from one dimensional sampled ECG signals to two dimensional vectors. To describe a change of curvature, the authors derive modified spatial velocity (MSV), from MSV the authors can locate QRS complexes more easily. The proposed algorithm consists of very small C-language procedures which reliably recognize the QRS complexes. For evaluation the authors used the MIT/BIH arrhythmia database. The proposed algorithm provides a good performance, a 99.58% detection rate of QRS complexes, a 99.57% sensitivity and 99.87% positive predictivity, respectively.
Lee et al. (Tue,) conducted a other in Arrhythmia. QRS detection algorithm using topological mapping and modified spatial velocity was evaluated on QRS complex detection rate, sensitivity, and positive predictivity. A real-time QRS detection algorithm using topological mapping and modified spatial velocity achieved a 99.58% detection rate, 99.57% sensitivity, and 99.87% positive predictivity.