ISA Interchange

Welcome to the official blog of the International Society of Automation (ISA).

This blog covers numerous topics on industrial automation such as operations & management, continuous & batch processing, connectivity, manufacturing & machine control, and Industry 4.0.

The material and information contained on this website is for general information purposes only. ISA blog posts may be authored by ISA staff and guest authors from the automation community. Views and opinions expressed by a guest author are solely their own, and do not necessarily represent those of ISA. Posts made by guest authors have been subject to peer review.

All Posts

Summary of “QRS Detection Using Adaptive Filters: A Comparative Study”

The following is a summary review of “QRS detection using adaptive filters: A comparative study” from Volume 66 of ISA Transactions (January 2017). If you would like to learn more about ISA Transactions, please visit this link.

See Samuel Ko Tak Shun's other summary on Design of minimum multiplier fractional order differentiator based on lattice wave digital filterhere.

Electrocardiogram (ECG) is the electrical activity of the heart, measured by placing electrodes at several positions on the human body. The ECG signal is a quasi-periodic wave that comprises of a few individual characteristic waves, given as P, Q, R, S, and T. These waves initiate with P wave that originates from the atrial depolarization of heart muscles; the Q, E, and S waves originate from the ventricular depolarization, and are together interpreted as the QRS complex. The T wave is due to the re-polarization of the heart, and this cycle repeats itself with the next P wave. 

ECG signal monitoring and analysis is widely used to explore and identify various heart diseases such as atrial and ventricular premature contractions, atrial fibrillations, bradycardia, tachycardia, etc. Variations from a normal sinus rhythm (standard heart cycle) are the symptoms of arrhythmia that represents some form of cardiovascular disease (CVD). CVD has been identified as one of the dominant causes of death by the World Health Organization (WHO). CVD is a primary health concern in most countries, with large expenditures on research and development of CVD monitoring and control equipment. 

Such equipment and devices rely on digital ECG signal processing methods. Digital ECG also plays an important role in compressing the ECG signal for teleporting to tertiary healthcare centers under low bandwidth requirements. To enhance ECG monitoring for easy identification of abnormalities, automated and adaptive computerized methods have been developed and adopted. 

The process of QRS detection starts with the mean subtraction of ECG signals, after which adaptive filtering, also known as adaptive linear prediction, is applied to get the instantaneous prediction error (PE). This then undergoes Savitzky-Golay (SG) filtering for peak enhancement and noise suppression. 

The mathematical equations of variants consist of the following least mean square (LMS) variants: 

  • Basic LMS
  • Variable step size LMS
  • Leaky LMS
  • Variable leaky LMS
  • Fractional LMS
  • Normalized least mean square (NLMS)
  • Sign error LMS
  • Sign-sign LMS
  • Recursive least square (RLS) 

The mathematical equations of the above variants can be found on page 364 of this research article. 

The performance of the proposed QRS detection algorithm is evaluated on the standard MIT-BIH Arrhythmia Database for a data length of 60 seconds (21,600 samples). Its results are as follows: 

  • Optimized initialization of predictor-coefficients
  • Optimized initialization of parameters of predictor variants
  • Detection performance 

Its discussions are divided into four sections: 

  • LMS variants versus fidelity parameters
  • LMS variants versus time complexity
  • LMS variants versus averaged weights
  • Proposed improved algorithm versus state-of-the-art algorithms 

The above discussions can be found in more detail on pages 368-374 in the research article. 

In conclusion, the improvement of the QRS detection system is done by utilizing new variants of LMS algorithms; a novel combination of a few variants have been tested and analyzed. The performance of all variants are compared to find out the best variant to be used in adaptive filtering-based QRS detection systems. The performance of LMS variants gets degraded when either the ECG signal is highly corrupted with noises due to EMG and motion artifacts resulting in false positive (FP) beat detection, or it incorporates extraneously wide fusion (F) beats that generally result in false negative (FN) beat detection.


Jain, S., Ahirwal, M. K., Kumar, A., Bajaj, V., & Singh, G. K. (2017). QRS detection using adaptive filters: A comparative study. ISA transactions, 66, 362-375.

Samuel Ko Tak Shun
Samuel Ko Tak Shun
Samuel Ko Tak Shun is a member of ISA and Works Supervisor I & II (Instrumentation) for the HKSARG Water Supplies Department, Shatin Water Treatment Work Instrumentation Division. He is responsible for supervising subcontractors and junior staff on the installation, troubleshooting, repair, and operations of the instruments and equipment of the water plant. Samuel graduated from British Columbia Institute of Technology with a diploma of Technology in Electronics: Process Automation and Instrumentation Option in January 1991 with a bursary received. He then obtained an MBA degree in International Business from the Hong Kong Campus of European University (now known as EU Business School, in Switzerland), in 2014.

Related Posts

IoT Solutions World Congress: Why Barcelona is the Place to Be in May

A century ago, automation solutions arrived to transform manual industrial tasks. This century, the digit...
Renee Bassett Apr 2, 2024 7:00:00 AM

3 Ways Industry 4.0 Can Upgrade Industrial Water Treatment Methods

Industrial water treatment methods must evolve to remain relevant and efficient. Many decision-makers hav...
Emily Newton Mar 12, 2024 7:38:26 PM

ISA Business Academy: A Mini-MBA For Automation Industry Leaders

The ISA Business Academy is a 10-week fully digital program beginning 28 March for both current and aspir...
Ashley Ragan Mar 11, 2024 10:08:24 AM