Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
BMEI '08 Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02
MEMEA '09 Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications
FPGA-oriented HW/SW implementation of ECG beat detection and classification algorithm
Digital Signal Processing
An ECG-on-Chip for Wearable Cardiac Monitoring Devices
DELTA '10 Proceedings of the 2010 Fifth IEEE International Symposium on Electronic Design, Test & Applications
Journal of Signal Processing Systems
A New QRS Detection Method Using Wavelets and Artificial Neural Networks
Journal of Medical Systems
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Healthcare issues arose from population aging. Meanwhile, electrocardiogram (ECG) is a powerful measurement tool. The first step of ECG is to detect QRS complexes. A state-of-the-art QRS detection algorithm was modified and implemented to an application-specific integrated circuit (ASIC). By the dedicated architecture design, the novel ASIC is proposed with 0.68mm2 core area and 2.21 µW power consumption. It is the smallest QRS detection ASIC based on 0.18 µm technology. In addition, the sensitivity is 95.65% and the positive prediction of the ASIC is 99.36% based on the MIT/BIH arrhythmia database certification.