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.
Author: | Mohammed RajabORCiD, Ralf SeepoldORCiDGND |
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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 |
Identifier: | Im Katalog der Hochschule Konstanz ansehen |
Release Date: | 2018/11/20 |
First Page: | 205 |
Last Page: | 213 |
Open Access?: | Nein |