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作者机构:Ibn Zohr Univ ENSA Lab Syst Engn & Informat Technol Agadir Morocco Paris Saclay Univ Digiteo Labs SATIE Orsay France
出 版 物:《INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS》 (Intl. J. Adv. Comput. Sci. Appl.)
年 卷 期:2021年第12卷第5期
页 面:361-369页
核心收录:
基 金:National Centre for Scientific and Technical Research (CNRST) of Morocco [588UIZ2017]
主 题:ECG signal denoising ADTF algorithm OpenMP programming embedded architectures
摘 要:Medical applications increasingly require complex calculations with constraints of accelerated processing time. These applications are therefore oriented towards the integration of high-performance embedded architectures. In this context, the detection of cardiac abnormalities is a task that remains a high priority in emergency medicine. ECG analysis is a complex task that requires significant computing time since a large amount of information must be analyzed in parallel with high frequencies. Real-time processing is the biggest challenge for researchers, when talking about applications that require time constraints like that of cardiac activity monitoring. This work evaluates the Adaptive Dual Threshold Filter (ADTF) algorithm dedicated to ECG signal filtering using various embedded architectures: A Raspberry 3B+ and Odroid XU4. The implementation has been based on C/C++ and OpenMP to exploit the parallelism in the used architectures. The evaluation was validated using several ECG signals proposed in MIT-BIH Arrhythmia database with a sampling frequency of 360 Hz. Based on an algorithmic complexity study and a parallelization of the functional blocks which present significant workloads, the evaluation results show a mean execution time of 7.5 ms on the Raspberry 3B+ and 0.34 ms on the Odroid XU4. With an efficient parallelization on the Odroid XU4 architecture, real-time performance can be achieved.