2008
DOI: 10.1109/icpr.2008.4761083
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Multifractality in arterial pulse

Abstract: Extensive research has been done to show that heartbeats are composed of the interaction of many physiological components operating on different time scales, with nonlinear and self-regulating nature. The more direct, and easily accessible manifestation of the heartbeat is the pulse; however, it has not been studied anywhere near as extensively.In this paper, we establish the relevance of the multifractal formalism for the arterial pulse, which has long been used as a fundamental tool for diagnosis in the Trad… Show more

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Cited by 7 publications
(4 citation statements)
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“…The reproducibility, accuracy and precision of the instrument has been studied and the results were found to be consistent across multiple recordings at different times [18] . The studies on pulse rate variability [19] , beat-to-beat alterations [20] , and spectral analysis [21] using Nadi Tarangini have shown significant results.…”
Section: Introductionmentioning
confidence: 99%
“…The reproducibility, accuracy and precision of the instrument has been studied and the results were found to be consistent across multiple recordings at different times [18] . The studies on pulse rate variability [19] , beat-to-beat alterations [20] , and spectral analysis [21] using Nadi Tarangini have shown significant results.…”
Section: Introductionmentioning
confidence: 99%
“…It is observed that, pulse duration increases and pulse rate decrease with the age [13]. Multifractality analysis explored self-similarity in arterial pulse and is used for diagnosis of skin disorder, aging and diabetes [14]. Kalange et al proposed a system in which a transducer based on piezoelectric properties was used for detecting the human pulse.…”
Section: Piezoelectric Sensorsmentioning
confidence: 99%
“…Recently the arterial pulse signals have had a minor renaissance and quantified; results on the shape of the arterial pulse signals show variations with age in [8] (through the shift of multifractal spectrum), with gender in [2] (through variations in augmentation index), and variability analysis in [7] (through various time domain, frequency domain and nonlinear Poincaré-based parameters).…”
Section: Time Domain Parametersmentioning
confidence: 99%