Why the study?
How do realistic noises affect the sensitivity and specificity of three surface ECG fibrillation detection algorithms?
How do realistic noises affect the sensitivity and specificity of three surface ECG fibrillation detection algorithms?
This study evaluates the robustness of three ECG fibrillation detection algorithms against realistic noises encountered during resuscitation, which is critical for improving AED accuracy.
May warrant caution with current AED algorithms in noisy resuscitation; leaves open prospective validation before practice changes.
The widening application of automatic external defibrillators (AEDs) presents very strong requirements for external electrocardiogram (ECG) signal analysis. Highly accurate detection of shockable rhythms is required, aimed to approach the maximum of 100% sensitivity and specificity. In a previous study the performance of five well known detection algorithms was assessed by test signals from the ECG-signal databases of the American Heart Association (AHA) and the Massachusetts Institute of Technology (MIT). The results obtained were used as a basis for testing the noise sensitivity of three of these algorithms. Realistic noise was obtained by simulation and recording of signal disturbance by various motions during resuscitation and defibrillation episodes (body shudder convulsions and gasps, cable movement, car transportation). The sensitivity and specificity of the detection algorithms were evaluated using electrocardiogram signals mixed with these noises.
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Jekova et al. (2001) studied this question.
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