Key result
The Complex Phase Space Difference algorithm successfully distinguished atrial fibrillation and ventricular fibrillation with a sensitivity of 97.9% and specificity of 98.4%.
Why the study?
Does the Complex Phase Space Difference (CPSD) algorithm accurately differentiate between normal sinus rhythm, atrial fibrillation, and ventricular fibrillation?
Does the Complex Phase Space Difference (CPSD) algorithm accurately differentiate between normal sinus rhythm, atrial fibrillation, and ventricular fibrillation?
Answers are grounded in this paper and cite their sources.
The CPSD algorithm provides a highly sensitive and specific real-time method for differentiating AF and VF from normal sinus rhythm, with potential applications in tele-healthcare and implantable devices.
The advances in electrocardiographic (ECG) technology have facilitated the development of numerous successful clinical applications and commercial monitoring products for diagnosing disease and monitoring health. All of these demand the development of smart algorithms and computational resources for the real-time, early indication of critical cardiac conditions. This study presents the development of a Complex Phase Space Difference (CPSD) algorithm with differential method to analyze spatial and temporal changes in reconstructed phase space matrix, and derives an index for real-time monitoring. We used total of 5306 data segments from MIT-BIH, CU, and SCDH databases and clinical trial data to determine the optimal working parameters and verified the classification capability by using a quantitative index of this algorithm. With threshold values set to 2.0 and 6.0, this method can successfully differentiate normal sinus rhythm (NSR) signals (1.48+/-0.21), low risk of atrial fibrillation (AF) signals (3.71+/-0.99) and high risk of ventricular fibrillation (VF) signals (9.38+/-2.22). It is the first real-time algorithm that reports the best performance to distinguish AF and VF with sensitivity of 97.9% and specificity of 98.4%. With self-normalization, the algorithm is not subjected to the inter-variability or sampling size effects. Its computational scheme only requires matrices addition and subtraction, and thus significantly reduces the complexity for real-time implementation. It will be able to adopt in different scenarios of tele-healthcare and implantable applications.
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Liu et al. (2010) studied Atrial fibrillation and ventricular fibrillation (n=5,306). Complex Phase Space Difference (CPSD) algorithm vs. Normal sinus rhythm was evaluated on AF and VF discrimination. The Complex Phase Space Difference algorithm successfully distinguished atrial fibrillation and ventricular fibrillation with a sensitivity of 97.9% and specificity of 98.4%.
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