VLSI design of ECG QRS complex detection using Multiscale Mathematical Morphology

Author

Vishnu Gopeka, S. ; Murali, L. ; Manigandan, T.

Author_Institution

P.A. Coll. of Eng. & Technol., Coimbatore, India

fYear

2014

fDate

8-10 May 2014

Firstpage

478

Lastpage

482

Abstract

This study presents the very large scale integration (VLSI) based electrocardiogram (ECG) QRS complex detector for wearable devices in body sensor networks. Multiscale Mathematical Morphology (MMM) is a method used to suppress background noise and baseline wandering from original ECG signal. The major advantage of this method is that it does not require any prior knowledge of frequency spectrum. Hence Multiscale Mathematical Morphology is very attractive for noise reduction. An efficient VLSI architecture in is designed and simulated for the same method. This algorithm is applied to ECG signal from MIT - BIH database and its performance is measured in terms of sensitivity (Se) and positive predictivity (+P) as 97.8% and 97.8% respectively.

Keywords

VLSI; body sensor networks; electrocardiography; mathematical morphology; medical signal detection; ECG QRS complex detection; MMM; VLSI architecture; background noise suppression; body sensor networks; multiscale mathematical morphology; very large scale integration based electrocardiogram; Morphology; Noise measurement; Body Sensor Networks; Electrocardiogram (ECG); Mathematical Morphology; Multiscale filtering; QRS Detection; Very Large Scale Integration (VLSI);

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on

Conference_Location

Ramanathapuram

Print_ISBN

978-1-4799-3913-8

Type

conf

DOI

10.1109/ICACCCT.2014.7019489

Filename

7019489