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of heart rate and respiration synchronize during poetry recitation. Am J Physiol Heart Circ Physiol 287: H579 -H587, 2004. First published April 8, 2004 10.1152/ajpheart.01131.2003.-The objective of this study was to investigate the synchronization between low-frequency breathing patterns and respiratory sinus arrhythmia (RSA) of heart rate during guided recitation of poetry, i.e., recitation of hexameter verse from ancient Greek literature performed in a therapeutic setting. Twenty healthy volunteers performed three different types of exercises with respect to a cross-sectional comparison: 1) recitation of hexameter verse, 2) controlled breathing, and 3) spontaneous breathing. Each exercise was divided into three successive measurements: a 15-min baseline measurement (S1), 20 min of exercise, and a 15-min effect measurement (S2). Breathing patterns and RSA were derived from respiratory traces and electrocardiograms, respectively, which were recorded simultaneously using an ambulatory device. The synchronization was then quantified by the index ␥, which has been adopted from the analysis of weakly coupled chaotic oscillators. During recitation of hexameter verse, ␥ was high, indicating prominent cardiorespiratory synchronization. The controlled breathing exercise showed cardiorespiratory synchronization to a lesser extent and all resting periods (S1 and S2) had even fewer cardiorespiratory synchronization. During spontaneous breathing, cardiorespiratory synchronization was minimal and hardly observable. The results were largely determined by the extent of a low-frequency component in the breathing oscillations that emerged from the design of hexameter recitation. In conclusion, recitation of hexameter verse exerts a strong influence on RSA by a prominent low-frequency component in the breathing pattern, generating a strong cardiorespiratory synchronization.creative arts therapy; cross-sectional study design; bivariate data analysis; heart rate variability

Dynamic aspects of R-R intervals have often been analyzed by means of linear and nonlinear measures. The goal of this study was to analyze binary sequences, in which only the dynamic information is retained, by means of two different aspects of regularity. R-R interval sequences derived from 24-h electrocardiogram (ECG) recordings of 118 healthy subjects were converted to symbolic binary sequences that coded the beat-to-beat increase or decrease in the R-R interval. Shannon entropy was used to quantify the occurrence of short binary patterns (length N = 5) in binary sequences derived from 10-min intervals. The regularity of the short binary patterns was analyzed on the basis of approximate entropy (ApEn). ApEn had a linear dependence on mean R-R interval length, with increasing irregularity occurring at longer R-R interval length. Shannon entropy of the same sequences showed that the increase in irregularity is accompanied by a decrease in occurrence of some patterns. Taken together, these data indicate that irregular binary patterns are more probable when the mean R-R interval increases. The use of surrogate data confirmed a nonlinear component in the binary sequence. Analysis of two consecutive 24-h ECG recordings for each subject demonstrated good intraindividual reproducibility of the results. In conclusion, quantification of binary sequences derived from ECG recordings reveals properties that cannot be found using the full information of R-R interval sequences.

It would often be desirable to obtain the respiratory rate during everyday conditions without obtaining an additional respiratory trace. This study investigates the agreement between respiratory rate assessed from the electrocardiogram (ECG) and the reference respiratory rate derived from a nasal/oral airflow (AF). Nasal/oral airflow and a Holter ECG were recorded in 52 healthy subjects (26 males, age range: 25.4-85.4 years) during everyday conditions for at least 10 h, including night-time sleep. The respiratory rate was assessed for each 5-min epoch (1) using respiratory sinus arrhythmia (RSA), (2) utilizing the respiration induced variations of the R-wave amplitude (ECG derived respiration (EDR)). The agreement with respect to AF was quantified using the average/std and the concordance correlation coefficient rho(c). For RSA and EDR the difference with respect to AF was 0.2 cpm (std: 0.6 cpm) during sleep and -0.2 cpm (std: 1.0 cpm) during wake time. During sleep the RSA-approach performed best for subjects < or =50 years (rho(c) = 0.79) and worst for subjects >50 years (rho(c) = 0.41). The correlation of the EDR-approach was rho(c) = 0.73 for both groups. In conclusion, the respiratory rate may be assessed with reasonable agreement by both methods in younger subjects, but EDR should be preferred in the elderly.

Background:The univariate approaches used to analyze heart rate variability have recently been extended by several bivariate approaches with respect to cardiorespiratory coordination. Some approaches are explicitly based on mathematical models which investigate the synchronization between weakly coupled complex systems. Others use an heuristic approach, i.e. characteristic features of both time series, to develop appropriate bivariate methods.

The purpose of this study was to demonstrate that cardiorespiratory coordination can be unveiled by analyzing solely the heart period data from electrocardiogram (ECG). The analysis was done (1) on the basis of symbolic musical pattern analysis to detect intermittent cardiorespiratory phase coordination and (2) on the quantitative evaluation of respiratory sinus arrhythmia (RSA) to examine long-term frequency coordination between heartbeat and respiration. The methods were applied to 196 ECGs of 98 healthy subjects. The results showed that at night (1) intermittent phase coordination occurred reproducibly in individual subjects, and (2) longterm frequency ratios statistically approached 4 : 1 over all subjects to within an accuracy of 0.02, although individual values ranged from 2.5-6.0 with a high intraindividual reproducibility (r = 0.94, day A versus day B). Moreover, intermittent phase coordination ratios and long-term frequency ratios corresponded to each other with a remarkably high correlation (r = 0.95). In the light of clinical applications, the coordination analysis presented here has an enormous advantage over those techniques depending on respiratory flow measurements, because the pattern technique requires only ECG recordings, and it is thus applicable over a longer period of time under daily life conditions.

Leeuwen. Musical rhythms in heart period dynamics: a cross-cultural and interdisciplinary approach to cardiac rhythms. Am. J. Physiol. 277 (Heart Circ. Physiol. 46): H1762-H1770, 1999.-The purpose of this study was to expand classic heart period analysis methods by techniques from ethnomusicology that explicitly take complex musical rhythm principles into consideration. The methods used are based on the theory of African music, the theory of symbolic dynamics, and combinatorial theory. Heart period tachograms from 192 24-h electrocardiograms of 96 healthy subjects were transformed into binary symbol sequences that were interpretable as elementary rhythmic (percussive) patterns, the time lines in African music. Using a hierarchical rhythm pattern scheme closely related to the Derler Rhythm Classification (from jazz theory), we calculated the predominance and stability of pattern classes. The results show that during sleep certain classes, specific to individuals, occurred in a cyclically recurrent manner and many times more often than expected. Simultaneously, other classes disappeared more or less completely. Moreover, the most frequent classes obviously originate from phase-locking processes in autonomic regulation (e.g., between respiratory and cardiac cycles). In conclusion, the new interdisciplinary method presented here demonstrates that heart period patterns, in particular those occurring during night sleep, can be interpreted as musical rhythms. This method may be of great potential use in music therapy research.

Objective of this study was to evaluate cardiac autonomic function in female breast cancer patients on the basis of linear and non-linear heart rate variability (HRV) as well as on musical heart rate rhythmicity. The latter method has been recently developed and enables particularly the quantification of cardiorespiratory coordination solely on the basis of ECG recordings. To provide a broad basis of comparability, 37 breast cancer patients were compared with 37 age-matched healthy women and 40 age-matched female diabetic patients who serve as pathological controls. During night sleep, all parameters showed a tendency towards lower variability, complexity or rhythmicity of HRV in cancer patients. The most prominent alterations were found for the binary pattern predominance (PP) and for the ratio of heart rate and respiration. In particular, when comparing metastasized and non-metastasized cancer patients, the discriminatory power of binary heart rate rhythmicity emerges: the histograms of 1-h intervals during night sleep with a predominance of cyclically recurrent phase locking patterns unveiled a clear transition from higher to lower cardiorespiratory coordination ratios and to a loss of coordination capability in metastasized patients.