Residential College | false |
Status | 已發表Published |
Ultra-low power QRS detection using adaptive thresholding based on forward search interval technique | |
Ruping Xiao1; Mingzhong Li1; Man-Kay Law1; Pui-In Mak1; Rui P. Martin1 | |
2017-12-01 | |
Conference Name | International Conference on Electron Devices and Solid-State Circuits (EDSSC) |
Source Publication | EDSSC 2017 - 13th IEEE International Conference on Electron Devices and Solid-State Circuits |
Volume | 2017-January |
Pages | 1-2 |
Conference Date | OCT 18-20, 2017 |
Conference Place | Hsinchu, TAIWAN |
Abstract | We present an energy efficient QRS detector for real-time ECG signal processing implemented in ASIC. An adaptive thresholding scheme based on forward search interval (FSI) algorithm together with simple preprocessing is proposed to accurately detect QRS peaks. The Verilog HDL codes with improved hardware utilization efficiency are validated using FPGA, achieving 99.59% sensitivity (Se) and 99.63% positive prediction (Pr) using the MIT-BIH Arrhythmia database. A chip prototype is also implemented in a standard 0.18-μm CMOS process. Synthesized with a customized subthreshold digital library for minimum energy operation, the proposed QRS detector occupies an active area of 0.13 mm and consumes merely 93nW. |
DOI | 10.1109/EDSSC.2017.8126486 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Engineering |
WOS Subject | Engineering, Electrical & Electronic |
WOS ID | WOS:000426985900088 |
Scopus ID | 2-s2.0-85043571325 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING Faculty of Science and Technology THE STATE KEY LABORATORY OF ANALOG AND MIXED-SIGNAL VLSI (UNIVERSITY OF MACAU) INSTITUTE OF MICROELECTRONICS |
Affiliation | 1.Universidade de Macau 2.Instituto Superior Técnico |
First Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Ruping Xiao,Mingzhong Li,Man-Kay Law,et al. Ultra-low power QRS detection using adaptive thresholding based on forward search interval technique[C], 2017, 1-2. |
APA | Ruping Xiao., Mingzhong Li., Man-Kay Law., Pui-In Mak., & Rui P. Martin (2017). Ultra-low power QRS detection using adaptive thresholding based on forward search interval technique. EDSSC 2017 - 13th IEEE International Conference on Electron Devices and Solid-State Circuits, 2017-January, 1-2. |
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