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Adaptive Integration of the Compressed Algorithm of CS and NPC for the ECG Signal Compressed Algorithm in VLSI Implementation

Sensors. 2017;17(10):2288 DOI 10.3390/s17102288


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Journal Title: Sensors

ISSN: 1424-8220 (Online)

Publisher: MDPI AG

LCC Subject Category: Technology: Chemical technology

Country of publisher: Switzerland

Language of fulltext: English

Full-text formats available: PDF, HTML, ePUB, XML



Yun-Hua Tseng (Department of Engineering and System Science, National Tsing Hua University, Hsinchu 300, Taiwan)

Yuan-Ho Chen (Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan)

Chih-Wen Lu (Department of Engineering and System Science, National Tsing Hua University, Hsinchu 300, Taiwan)


Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 11 weeks


Abstract | Full Text

Compressed sensing (CS) is a promising approach to the compression and reconstruction of electrocardiogram (ECG) signals. It has been shown that following reconstruction, most of the changes between the original and reconstructed signals are distributed in the Q, R, and S waves (QRS) region. Furthermore, any increase in the compression ratio tends to increase the magnitude of the change. This paper presents a novel approach integrating the near-precise compressed (NPC) and CS algorithms. The simulation results presented notable improvements in signal-to-noise ratio (SNR) and compression ratio (CR). The efficacy of this approach was verified by fabricating a highly efficient low-cost chip using the Taiwan Semiconductor Manufacturing Company’s (TSMC) 0.18-μm Complementary Metal-Oxide-Semiconductor (CMOS) technology. The proposed core has an operating frequency of 60 MHz and gate counts of 2.69 K.