Phase-rectified signal averaging detects quasi-periodicities in non-stationary data

Bauer, Axel; Kantelhardt, Jan W.; Bunde, Armin; Barthel, Petra; Schneider, Raphaël; Malík, Marek; Schmidt, Georg

doi:10.1016/j.physa.2005.08.080

Cited by 203 publications

(243 citation statements)

References 16 publications

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“…PRSA is a mathematical procedure that allows the extraction of periodicities from complex time series that might include non-stationarities, noise and artefacts. 25 PRSA has been originally used to detect deceleration-related (deceleration capacity; DC) and acceleration-related (acceleration capacity; AC) modulations of heart rate. DC has been shown to yield strong and independent prognostic information in survivors of acute MI.…”

Section: Alternative Quantification Of Periodic Repolarisation Dynamimentioning

confidence: 99%

Periodic Repolarisation Dynamics: A Natural Probe of the Ventricular Response to Sympathetic Activation

Rizas¹,

Hamm²,

Kääb³

et al. 2016

Arrhythmia &Amp; Electrophysiology Review

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Experimental and clinical studies have demonstrated that enhanced sympathetic autonomic nervous system (SANS) activity can destabilise myocardial repolarisation, 1-4 increasing vulnerability to developing fatal cardiac arrhythmias. [5][6][7][8] Accordingly, assessment of SANS activity has always been a major goal for cardiac risk stratification methods.Various non-invasive methods including assessment of heart rate variability (HRV) and baroreflex sensitivity have been employed to study the activity of the SANS under routine clinical conditions. 9 These methods are based on two principles. First, activation of the SANS evokes physiological effects on the cardiovascular system, such as acceleration of heart rate, increased vasomotor tone or systolic contractility.4 Second, as SANS activity is clustered in low-frequency bursts, SANS-induced physiological responses are likely to exhibit low-frequency dynamics. [10][11][12][13][14] Previous studies have shown that SANS assessment based on HRV and baroreflex sensitivity is a marker of increased vulnerability to fatal cardiac arrhythmias. 15,16 However, both methods are limited by the fact that they only provide an indirect probe of the sympathetic effect on cardiac repolarisation, as they reflect influences on the sinoatrial node and blood vessels and not on the ventricular myocardium. In addition, both HRV and baroreflex sensitivity are confounded by the concomitant action of other systems exhibiting periodic dynamics, such as the parasympathetic nervous system and the renin-angiotensinaldosterone system, respectively.We proposed a novel approach to SANS assessment that substantially differs from previous methods.17 So-called periodic repolarisation dynamics (PRD) evaluates sympathetic activity-associated lowfrequency periodic changes of cardiac repolarisation instability and opens new perspectives for identifying high-risk patients, who would potentially benefit from prophylactic interventions. The first section of this review briefly depicts the methodology of PRD assessments.The second section focuses on potential mechanisms of PRD. In the third section, the clinical application of PRD as risk predictor after myocardial infarction (MI) is presented. In the fourth section, we present an alternative method for PRD assessment, which provides some technical advantages over the standard method. The final sections are dedicated to ongoing and future projects aimed at developing individualised treatment strategies. Methodology of Periodic Repolarisation Dynamics AssessmentPRD is typically assessed using a high-resolution ECG recorded in or converted to the three orthogonal axes X, Y and Z ('Frank lead configuration'). As low-frequency patterns are of interest, the recording AbstractPeriodic repolarisation dynamics (PRD) refers to low-frequency (≤0.1Hz) modulations of cardiac repolarisation instability. Spontaneous PRD can be assessed non-invasively from 3D high-resolution resting ECGs. Physiological and experimental studies have indicated that PRD correlates with effere...

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Section: Alternative Quantification Of Periodic Repolarisation Dynamimentioning

confidence: 99%

Periodic Repolarisation Dynamics: A Natural Probe of the Ventricular Response to Sympathetic Activation

Rizas¹,

Hamm²,

Kääb³

et al. 2016

Arrhythmia &Amp; Electrophysiology Review

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“…The PRSA method offers the possibility to study causal relationships between accelerations or decelerations of the heart [6]. The standard algorithm is based on anchor points, i.e., points in time series that correspond to either moderate acceleration or moderate deceleration.…”

Section: Matrices Of Network Representation Of Rr-incrementsmentioning

confidence: 99%

“…The standard algorithm is based on anchor points, i.e., points in time series that correspond to either moderate acceleration or moderate deceleration. The deceleration capacity (DC) represents the average of the special combination of RR-intervals directly preceding and following such a deceleration [6]. One can observe that this combination can be transcribed into RR-increments as follows:…”

Section: Matrices Of Network Representation Of Rr-incrementsmentioning

confidence: 99%

“…The first method explores tools arising from a network representation of a time series [4,5]. The adjacency matrix of the network of RR-increments is used to obtain an approximation of the deceleration capacity, the measure that results from the phase-rectified signal averaging (PRSA) method [6] and that has been successful in predicting mortality in post-infraction patients [7]. The transition matrix of this network leads to the Markov characterization of the dynamics, and hence, it provides the entropy rate as an estimator of the total complexity of the time series.…”

Section: Introductionmentioning

confidence: 99%

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Entropic Measures of Complexity of Short-Term Dynamics of Nocturnal Heartbeats in an Aging Population

Makowiec

Kaczkowska

Wejer

et al. 2015

Entropy

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Two entropy-based approaches are investigated to study patterns describing differences in time intervals between consecutive heartbeats. The first method explores matrices arising from networks of transitions constructed following events represented by a time series. The second method considers distributions of ordinal patterns of length three, whereby patterns with repeated values are counted as different patterns. Both methods provide estimators of dynamical aspects of short-term heartbeat signals obtained from nocturnal Holter electrocardiogram (ECG) recordings of healthy people of different ages and genders. The deceleration capacity, arising from the adjacency matrix of the network, and the entropy rate, resulting from the transition matrix of the network, are also calculated, and both significantly decay with aging. As people age, the permutation entropy grows, due to the increase in patterns with repeated values. All of these estimators describe in a consistent way changes in the beat-to-beat heart period dynamics caused by aging. An overall slowing Entropy 2015, 17 1254 down of heart period changes is observed, and an increase of permutation entropy results from the progressive increase of patterns with repeated values. This result points to the sympathetic drive becoming dominant in cardiac regulation of nocturnal heart rate with age.

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“…DC is an advanced measure of heart rate variability, thus basically analyzing autonomic innervation at the level of the sinus node. To obtain DC, the sequence of beat-to-beat (RR)-intervals is transformed into a new condensed signal, preserving deceleration-related oscillations of heart rate [7]. Figure 1 visualizes these oscillations for a low-risk (A) and a high-risk patient (B).…”

Section: Measures Of Cardiac Autonomic Dysfunctionmentioning

confidence: 99%

Biosignal-guided personalized therapy

Stülpnagel

Wolf

Bauer

2017

Current Directions in Biomedical Engineering

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Sudden cardiac death (SCD) is the leading single cause of death in the industrialized world. Current guidelines recommend a prophylactic implantation of an implantable cardioverter-defibrillator (ICD) in patients with reduced leftventricular ejection fraction (LVEF ≤ 35%). However, most deaths after myocardial infarction (MI) occur in patients with normal or moderately reduced LVEF (>35%). There is a large body of evidence that cardiac autonomic dysfunction after MI is linked to increased susceptibility to malignant arrhythmias. Deceleration capacity of heart rate (DC) and periodic repolarization dynamics (PRD) are novel ECGbased risk markers, which capture different facets of cardiac autonomic dysfunction. Both parameters are strong and independent predictors of mortality and SCD after MI. Previous studies indicated that combined assessment of DC and PRD allows identification of a new high-risk group among post-infarction patients that is not addressed by current guidelines, thus opening new perspectives for biosignal-guided personalized therapies.

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Phase-rectified signal averaging detects quasi-periodicities in non-stationary data

Cited by 203 publications

References 16 publications

Periodic Repolarisation Dynamics: A Natural Probe of the Ventricular Response to Sympathetic Activation

Periodic Repolarisation Dynamics: A Natural Probe of the Ventricular Response to Sympathetic Activation

Entropic Measures of Complexity of Short-Term Dynamics of Nocturnal Heartbeats in an Aging Population

Biosignal-guided personalized therapy

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