ScottCare Cardiac Resources

A Statistical Approach for Accurate Detection of Atrial Fibrillation and Flutter

We recently interviewed Snehraj Merchant, Vice President of Engineering, to gain insight on the development of ScottCare’s proprietary algorithm for real-time detection of Atrial Fibrillation and Flutter. 

Click to download: A Statistical Approach for Accurate Detection of Atrial Fibrillation and FlutterQ: What was the initial purpose of entering into the development of this algorithm?

A: Atrial Fibrillation (AF or A-Fib) is the most commonly encountered arrhythmia in the clinical practice that affects more than 2.2 million Americans and more than 4.5 million people in Europe. The prevalence of AF has not only caused a 66% increase in the number of hospitalizations in the past twenty years, but has been a substantial cost burden to the healthcare community worldwide. With the steady increase of this particular arrhythmia came the need for the development of a brand new algorithm for real-time detection of atrial fibrillation (AF) and flutter (AFL).

Q: Were there existing methods or algorithms out there that called for improvement or prompted the development of ScottCare’s algorithm?

­­­A: Generating a successful automatic detection algorithm took multiple attempts. Previous efforts at automatic detection of AF include Moody & Mark(1983), Murgatroyd et al(1995), Duverney et al(2001), Tateno & Glass (2001), etc. using mechanisms such as Markov models, Wavelet transforms of RR intervals, coefficient of variation of RR and delta RR and utilization of RMSSD. Most utilized the MIT-BIH AF database for representing the accuracy of detection. In order to address high rate of false positive detections in an ambulatory environment, ScottCare committed to develop an algorithm with higher degree of sensitivity and specificity on not only the MIT-BIH AF database but also on 76 real life ambulatory Holter data patients with varying degrees of Paroxymal Atrial Fibrillation.

Q: What sets this algorithm apart from any other?

A: Our enhanced algorithm is unlike past algorithms used in cardiovascular devices due to its use of multiple calculations namely Root Mean Square Successive Difference, Turning Point Ratio and Shannon Entropy for detection of Afib. This quantification of nonlinear dynamics produces a much more accurate detection of AF with very high sensitivity and specificity.

Q: How has ScottCare incorporated this algorithm into its products?

A: ScottCare advanced two cardiovascular diagnostic products with the development of the new and improved algorithm, including the Chroma™ Holter Monitor and Telesentry™ Live Ambulatory Telemetry Monitor by incorporating the algorithm into their development. With a low computation time of 0.781ms, it is effective in its utilization on real-time devices as well as retrospective analysis systems. ScottCare has utilized it in both capacities.

Q: How does this make ScottCare product(s) better/different?

A: This algorithm sets our products apart from other similar cardiovascular diagnostic devices by contributing to better accuracy results and higher degree of detection in clinical application, increasing productivity and ultimately improving patient care. 

To learn more about ScottCare’s proprietary A-Fib algorithm, access the publication here.

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