Receiver-Operating-Characteristic Analysis Reveals Superiority of Scale-Dependent Wavelet and Spectral Measures for Assessing Cardiac Dysfunction
Receiver-operating-characteristic (ROC) analysis was used to assess the suitability of various heart rate variability (HRV) measures for correctly classifying electrocardiogram records of varying lengths as normal or revealing the presence of heart failure. Scale-dependent HRV measures were found to...
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| Veröffentlicht in: | arXiv.org 1999-01 |
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| creator | Thurner, Stefan Feurstein, Markus C Lowen, Steven B Teich, Malvin C |
| description | Receiver-operating-characteristic (ROC) analysis was used to assess the suitability of various heart rate variability (HRV) measures for correctly classifying electrocardiogram records of varying lengths as normal or revealing the presence of heart failure. Scale-dependent HRV measures were found to be substantially superior to scale-independent measures (scaling exponents) for discriminating the two classes of data over a broad range of record lengths. The wavelet-coefficient standard deviation at a scale near 32 heartbeat intervals, and its spectral counterpart near 1/32 cycles per interval, provide reliable results using record lengths just minutes long. A jittered integrate-and-fire model built around a fractal Gaussian-noise kernel provides a realistic, though not perfect, simulation of heartbeat sequences. |
| doi_str_mv | 10.48550/arxiv.9901007 |
| format | Article |
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| source | Free E- Journals |
| subjects | Computer simulation Electrocardiography Fractal models Heart rate Wavelet analysis |
| title | Receiver-Operating-Characteristic Analysis Reveals Superiority of Scale-Dependent Wavelet and Spectral Measures for Assessing Cardiac Dysfunction |
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