DocumentCode :
2716322
Title :
Optimized R peak detection algorithm for ultra low power ECG systems
Author :
Shrestha, Sachin ; Torfs, Tom ; Kim, Hyejung ; Yazicioglu, Refet Firat ; Romero, Inaki ; Buxi, Dilpreet ; Berset, Torfinn ; Altini, Marco
Author_Institution :
Heterogeneous Integrated Microsyst. Dept., imec, Leuven, Belgium
fYear :
2011
fDate :
10-12 Nov. 2011
Firstpage :
225
Lastpage :
228
Abstract :
In this paper, an optimized R peak detection algorithm with a high level of accuracy that can be implemented using very low power consumption is proposed. The accuracy of the algorithm is evaluated against the MIT-BIH arrhythmia database, giving an average sensitivity of 99.22% and positive predictivity of 99.86%, as well as against imec´s database with ambulatory data, giving an average sensitivity of 99.77% and positive predictivity of 99.82%. The power consumption of the algorithm is estimated by implementation in a commercial low power microcontroller (TI MSP430) to 71.42 μW. The algorithm has been tested in a hardware system using applied signals at varying signal to noise ratio as well as on human volunteers.
Keywords :
electrocardiography; medical image processing; medical signal processing; microcontrollers; optimisation; power consumption; MIT-BIH arrhythmia database; ambulatory data; hardware system; imec database; microcontroller; optimized R peak detection algorithm; power 71.42 muW; power consumption; ultralow power ECG systems; Application specific integrated circuits; Continuous wavelet transforms; Databases; Detection algorithms; Electrocardiography; Power demand; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2011 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4577-1469-6
Type :
conf
DOI :
10.1109/BioCAS.2011.6107768
Filename :
6107768
Link To Document :
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