165
Views
0
CrossRef citations to date
0
Altmetric
Medical Electronics

Swarm Intelligence-based Optimized Adaptive Filtering Technique for ECG Data Analysis System

, , &
Pages 4894-4908 | Published online: 23 Feb 2022
 

Abstract

The ECG (Electrocardiogram) signal is the most important signal in the biomedical signal processing, because it is used to diagnose the wellness of heart’s activity. Now a days the ECG signal processing devices have become more compact and smaller in size. Implementing the algorithms in devices is a complex task. Various blocks like preprocessing, extraction and diagnosis have to be implemented in hardware. The ECG signal will be corrupted by different types of noises. The filter to be implemented should be efficient in removal of the noise and extraction of medical information. In this paper, implementation of adaptive filtering using Swarm-based optimization techniques for biomedical system on chip architecture is presented. The proposed algorithm was implemented in different hardware and the performance is compared. The filters show linear phase and high rejection ratio. Field programmable gate arrays were used for implementation. These adaptive filters form the part of filter circuits for preprocessing and extraction of ECG signals. Implementation was done using Intel Altera innovative Programmable Power Technology tool Quartus.

Additional information

Notes on contributors

Manoharan Tamilselvi

M Tamilselvi obtained her BE degree in electronics and communication engineering from Paavai Engineering College-Anna University in 2005, MTech degree in communication systems Prist University, Thanjavur in 2012. She has 14 years of teaching experience. Currently working as an assistant professor in the Department of Electronics and Communication Engineering at Cheran College of Engineering, Karur. Her teaching and research areas include signal processing, filters, electronics circuits,wireless networks, image processing, etc.

J. Senthilkumar

J Senthilkumar obtained his BE and ME degrees from Bharathiar University and Anna University, Chennai, respectively, in 2002 and 2004 and PhD from Anna University, Chennai in 2012. He has 21 years of teaching experience. Currently, he is working as a professor in the Department of Information Technology at Sona College of Technology, Salem. His research interest includes computer networks, wireless sensor networks, image processing, neural networks, etc. Email: [email protected]

V. Mohanraj

V Mohanraj obtained his BE degree in computer science and engineering from Madras University in 1999, ME degree in computer science and engineering from Anna University, Chennai in 2004 and PhD degree in information and communication engineering from the Anna University, Chennai in 2013. He has 22 years of teaching experience. Currently, he is working as a professor in the Department of Information Technology at Sona College of Technology, Salem, India. Email: [email protected]

Y. Suresh

Y Suresh obtained his BE degree in electrical and electronics engineering from Madras University in 1998, ME degree in applied electronics with distinction from Anna University, Chennai in 2004 and PhD in the faculty of Information and Communication Engineering from Anna University, Chennai in 2012. He has 23 years of teaching experience. Currently, he is working as professor in the Department of Information Technology at Sona College of Technology, Salem. His research interest includes computer networks, wireless sensor networks, image processing, neural networks, etc. Email: [email protected]

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 100.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.