DocumentCode :
1768124
Title :
65-nm ASIC implementation of QRS detector based on Pan and Tompkins algorithm
Author :
Bayasi, Nourhan ; Saleh, Hani ; Mohammad, Baker ; Ismail, Mahamod
Author_Institution :
Dept. of Electr. & Comput. Eng., Khalifa Univ. of Sci., Technol., & Res., Abu Dhabi, United Arab Emirates
fYear :
2014
fDate :
9-11 Nov. 2014
Firstpage :
84
Lastpage :
87
Abstract :
Electrocardiogram analysis is an important tool in the management of cardiac diseases and the QRS complex is the main reference in such analysis. The paper presents a new adaptive ECG QRS detection ASIC based on Pan and Tompkins algorithm. The algorithm has been modified to detect a large number of different QRS complex morphologies using two adaptive thresholds. The dedicated ASIC design architecture is based on the state-of-the-art 65-nm CMOS technology and has achieved 0.073426 mm2 total core area and 0.55105 μW power consumption. The QRS detector is tested on ECG records obtained from Physionet MIT-BIH database and obtained a sensitivity of Se =99.83% and a positive predictivity of P+= 98.65%.
Keywords :
CMOS integrated circuits; adaptive signal detection; adaptive signal processing; application specific integrated circuits; biomedical electronics; diseases; electrocardiography; feature extraction; low-power electronics; medical signal detection; medical signal processing; ASIC implementation; CMOS technology; Pan-Tompkins algorithm modification; Physionet MIT-BIH database; QRS complex detector; QRS complex morphology; QRS detector positive predictivity; QRS detector sensitivity; QRS detector testing; adaptive ECG QRS detection ASIC; adaptive threshold; cardiac disease management; dedicated ASIC design architecture; electrocardiogram analysis; power 0.55105 muW; power consumption; size 0.073426 mm; size 65 nm; total core area; Algorithm design and analysis; Application specific integrated circuits; Detection algorithms; Detectors; Electrocardiography; Hardware; Real-time systems; ASIC design; Electrocardiogram signal; QRS detection; automated diagnosis; peak detection; real-time adaptation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovations in Information Technology (INNOVATIONS), 2014 10th International Conference on
Conference_Location :
Al Ain
Print_ISBN :
978-1-4799-7210-4
Type :
conf
DOI :
10.1109/INNOVATIONS.2014.6987567
Filename :
6987567
Link To Document :
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