Why the study?
Does the Phase Invariant Signature Algorithm (PISA) improve the detection of cardiac abnormalities on ECG in animal models?
Does the Phase Invariant Signature Algorithm (PISA) improve the detection of cardiac abnormalities on ECG in animal models?
The Phase Invariant Signature Algorithm (PISA) represents a novel, potentially highly sensitive computational method for detecting early ECG abnormalities without needing a reference standard.
PISA enables reference-free ECG analysis in animals; leaves open translation to clinical detection of cardiac abnormalities.
The present paper presents a simple and unambiguous computer-assisted method for the detection of cardiac disorders by processing the electrocardiogram. A new technique "Phase Invariant Signature Algorithm (PISA)", has been described, which is useful in the detection of cardiac abnormalities by investigating certain statistical properties of the measured waveform of ECG in a "phase-locked" fashion. This method of detection of abnormalities in the heart was used in the changes in the hypoxic action potential and in the ECG due to ionic changes and ischemia in the heart of cats and dogs. The signature of the normal ECG or action potential was straight-line. Any change in the waveform of ECG or action potential was detected as spikes in the signature. This method of detection of cardiac abnormalities does not require a priori reference to any standard ECG. The results indicate that this new method is capable of detecting cardiac disorders at an early stage and hence a higher sensitivity than the presently available type of ECG analysis. This method is in the developmental stage and further studies are being carried out.
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Prasad et al. (1978) studied this question.
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