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High performance dynamic threshold calibration for RR interval detection in a QRS complex using a parallel programing

  • These days computer analysis of ECG (Electrocardiograms) signals is common. There are many real-time QRS recognition algorithms; one of these algorithms is Pan-Tompkins Algorithm. Which the Pan-Tompkins Algorithm can detect QRS complexes of ECG signals. The proposed algorithm is analysed the data stream of the heartbeat based on the digital analysis of the amplitude, the bandwidth, and the slope. In addition to that, the stress algorithm compares whether the current heartbeat is similar or different to the last heartbeat after detecting the ECG signals. This algorithm determines the stress detection for the patient on the real-time. In order to implement the new algorithm with higher performance, the parallel programming language CUDA is used. The algorithm determines stress at the same time by determining the RR interval. The algorithm uses a different function as beat detector and a beat classifier of stress.

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Metadaten
Author:Mohammed RajabORCiD, Ralf SeepoldORCiDGND
DOI:https://doi.org/10.1007/978-3-319-39700-9_16
ISBN:978-3-319-39698-9
ISBN:978-3-319-39700-9
Parent Title (English):Mobile Networks for Biometric Data Analysis (Lecture notes in electrical engineering ; Vol. 392)
Publisher:Springer
Place of publication:Cham
Document Type:Conference Proceeding
Language:English
Year of Publication:2016
Opac ID:Im Katalog der Hochschule Konstanz ansehen
Release Date:2018/11/20
First Page:205
Last Page:213
Open Access?:Nein