Heart ECG waveforms fitness check techniques for cardiac at-risk stratification
There is increasing concern in preventive cardiovascular health care to detect apparently healthy people who could be at risk of sudden cardiac death (SCD). This concern is more meaningful when considering the young with a high cardiac performance demanding physical activity such as sports, exercising or at work. Accurate statistics are not available but experts believe at least 8 young (under 35) people die suddenly every week in the UK due to SCD. Although difficult to diagnose accurately after death, SCD syndrome is a potentially preventable condition that can often be detected by effective screening. The presence of late potentials in a high definition recorded ECG, is widely accepted to have prognostic significance in patients at risk of SCD and Brugada syndrome. A reliable parameter for quantifying late potential activity is by measuring the fractal dimension of their 3D attractor. Such a device provides a method of analysis of ventricular late potential (VLP) measurements in a high definition electrocardiographic (HD-ECG) recording. VLPs are located at the end section of every heart beat in the HD-ECG. The proposed VLP analysis determines a parameter related to the complexity of VLP waveforms as the parameter for clinical evaluation. This is done by computing the fractal dimension of the 3-dimensional VLP curve drawn in a high definition voltage scale (microvolts); the voltage being measured on three perpendicular (X,Y,Z) ECG signals. Several clinical studies have confirmed that a fractal dimension above 1.3, can be selected as the threshold value indicating risk of SCD in the subject being checked for heart fitness. The fractal dimension result may be provided as a numerical display or just as a simple SCD risk warning lamp (green-red) in the device. The basic algorithm was tested using off-line processing on an unpractical PC-based system. Therefore, research and development is required for a suitable and novel embedded system that implements the real-time fractal analysis in a portable handheld clinical device. References [1] - “Analog implementation of the single fiducial point alignment technique for real-time high resolution ECG analysis in the P-R interval”. O.J. Escalona. Computers in Cardiology 1998, vol. 25, IEEE, ISBN 0-7803-5200-9, 1998. [2] - “Discriminating at-risk post-MI patients by fractal dimension analysis of the late potential attractor”. R.H. Mitchell and O. Escalona. Proceedings of the 20th Annual International Conference, IEEE/EMBS, pp. 1573-1575, 1998. [3] - “Dynamic behavior of ventricular late potentials: estimation of 3-dimensional fractal dimension as an index of basic order chaotic features in post-MI patients at risk and in healthy subjects”. Escalona O.J., Mitchell R.H. Innovation et Technologie en Biologie et Medecine (ITBM), 20(3); pp. 169-180, 1999.
[4] - “Prognostic value of electrocardiograms, ventricular late potentials, ventricular arrhythmias, and left ventricular systolic dysfunction in patients with Duchenne muscular dystrophy”. Corrado G, Lissoni A, Beretta S, Terenghi L, Tadeo G, Foglia-Manzillo G, Tagliagambe LM, Spata M, Santarone M. American Journal of Cardiology; 89(7): 838-841, 2002. [5] - Escalona OJ, Mendoza M, Villegas G, et al, “Real-time system for high-resolution ECG diagnosis based on 3D late potentials fractal dimension estimation”. Computing in Cardiology; 38:789-792, 2011. [6] - Mizobuchi M, et al. “Ventricular late potential in patients with apparently normal electrocardiogram; predictor of Brugada syndrome”. PACE; 33 (3): 266-273, 2010.
[8] - Zipes DP, Camm AJ, et al. “ACC/AHA/ESC 2006 Guidelines for Management of Patients With Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death”, J Am Coll Cardiol; 48:247-346, 2006.
[9] - Corrado D, Schmied C, Basso C, Borjesson M, Schiavon M, et al. “Risk of sports: do we need a pre-participation screening for competitive and leisure athletes?”. Eur Heart J; 32(8):934-44, 2011.
[7] - Goldberger J, Cain ME, et al. “American Heart Association/American College of Cardiology Foundation/Heart Rhythm Society Scientific Statement on Noninvasive Risk Stratification Techniques for Identifying Patients at Risk for Sudden Cardiac Death”. Circulation. 118:1497-1518, 2008.
A handy, cost effective, reliable device, with a simple output indicator (green-red lamp), for screening young athletes or school aged at risk of SCD, would provide an important support for today’s clinical needs of sports cardiology and point-of-care cardiovascular healthcare solutions.
Personnel Involved
First Supervisor: Escalona, OJ Prof
Second Supervisor: Boyd, AR Dr
Collaborator: Dr David McEneaney
Collaboration: Craigavon Area Hospital
Synopsis:
The project will research and develop a suitable embedded system for a clinical device which implements real-time, fractal dimension caracterisation of 3D ventricular late potentials in the high-definition ECG, for screening the young and risk stratification of sudden cardiac death and Brugada syndrome. The targeted helthcare device is within the framework of inteligent sensor systems for point-of-care applications.