this study evaluates the discriminative power of sequential spectrum analysis of the short-term electrocardiogram (ecg) time series in separating normal and subjects with life threatening arrhythmias like, ventricular tachycardia/fibrillation (vt/vf). the raw ecg time series is transformed into a series of binary symbols and the binary occupancy or relative distribution of mono-sequences (i.e. ...

Often multiple observations are required to achieve acceptable diagnostic certainty. We present a spectrum-based sequential diagnosis approach coined SEQUOIA, that greedily selects tests out of a suite of tests to narrow down the set of diagnostic candidates with a minimum number of tests. SEQUOIA handles multiple faults, that can be intermittent, at polynomial time and space complexity. This i...

BACKGROUND Analysis of signals by means of symbolic methods consists in calculating a measure of signal complexity, for example informational entropy or Lempel-Ziv algorithmic complexity. For construction of these entropic measures one uses distributions of symbols representing the analyzed signal. RESULTS We introduce a new signal characteristic named sequential spectrum that is suitable for...

This study evaluates the discriminative power of sequential spectrum analysis of the short-term electrocardiogram (ECG) time series in separating normal and subjects with life threatening arrhythmias like, ventricular tachycardia/fibrillation (VT/VF). The raw ECG time series is transformed into a series of binary symbols and the binary occupancy or relative distribution of mono-sequences (i.e. ...

This study evaluates the discriminative power of sequential spectrum analysis of the short-term electrocardiogram (ECG) time series in separating normal and subjects with life threatening arrhythmias like, ventricular tachycardia/fibrillation (VT/VF). The raw ECG time series is transformed into a series of binary symbols and the binary occupancy or relative distribution of mono-sequences (i.e. ...