Abstract
Symbolic dynamics derived from heart rate variability (HRV) is able to reflect changes of cardiac autonomic modulations on short time scales in spite of the considerable reduction of information involved. However, the link between the appearance of specific symbolic patterns and the activity of the autonomic nervous system has not yet been elucidated. In this study, we investigate the symbolic dynamics that reflect acceleration (='1') and deceleration (='0') of the instantaneous heart rate. The resulting binary series is analyzed with respect to the regularity of binary patterns of length 8 using Approximate Entropy (ApEn). Binary patterns were grouped according to the level of their regularity as assessed by ApEn. ECG recordings were obtained from 17 healthy subjects during graded head-up tilt (0, 15, 30, 45, 60, 75, and 90°). The linear correlation (Spearman correlation coefficient) between tilt angle and the occurrence of binary patterns was evaluated. The results show that regular binary patterns occurred more often with increasing tilt angle whereas the occurrence of some irregular patterns decreased. Some binary patterns did not show a change of occurrence during tilt. When compared to the results of spectral analysis, regular binary patterns reflect sympathetic modulations whereas irregular binary patterns reflect parasympathetic modulations. The parameters derived from binary symbolic dynamics reflect changes of autonomic modulations during graded head-up tilt and are not fully correlated to the spectral markers of HRV.
| Original language | English |
|---|---|
| Pages (from-to) | 313-318 |
| Number of pages | 6 |
| Journal | Computers in Biology and Medicine |
| Volume | 42 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Mar 2012 |
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Keywords
- Autonomic nervous system
- Graded head-up tilt
- Heart rate variability
- Symbolic dynamics
ASJC Scopus subject areas
- Computer Science Applications
- Health Informatics
Cite this
Binary symbolic dynamics classifies heart rate variability patterns linked to autonomic modulations. / Cysarz, D.; Van Leeuwen, P.; Edelhäuser, F.; Montano, N.; Porta, A.
In: Computers in Biology and Medicine, Vol. 42, No. 3, 03.2012, p. 313-318.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Binary symbolic dynamics classifies heart rate variability patterns linked to autonomic modulations
AU - Cysarz, D.
AU - Van Leeuwen, P.
AU - Edelhäuser, F.
AU - Montano, N.
AU - Porta, A.
PY - 2012/3
Y1 - 2012/3
N2 - Symbolic dynamics derived from heart rate variability (HRV) is able to reflect changes of cardiac autonomic modulations on short time scales in spite of the considerable reduction of information involved. However, the link between the appearance of specific symbolic patterns and the activity of the autonomic nervous system has not yet been elucidated. In this study, we investigate the symbolic dynamics that reflect acceleration (='1') and deceleration (='0') of the instantaneous heart rate. The resulting binary series is analyzed with respect to the regularity of binary patterns of length 8 using Approximate Entropy (ApEn). Binary patterns were grouped according to the level of their regularity as assessed by ApEn. ECG recordings were obtained from 17 healthy subjects during graded head-up tilt (0, 15, 30, 45, 60, 75, and 90°). The linear correlation (Spearman correlation coefficient) between tilt angle and the occurrence of binary patterns was evaluated. The results show that regular binary patterns occurred more often with increasing tilt angle whereas the occurrence of some irregular patterns decreased. Some binary patterns did not show a change of occurrence during tilt. When compared to the results of spectral analysis, regular binary patterns reflect sympathetic modulations whereas irregular binary patterns reflect parasympathetic modulations. The parameters derived from binary symbolic dynamics reflect changes of autonomic modulations during graded head-up tilt and are not fully correlated to the spectral markers of HRV.
AB - Symbolic dynamics derived from heart rate variability (HRV) is able to reflect changes of cardiac autonomic modulations on short time scales in spite of the considerable reduction of information involved. However, the link between the appearance of specific symbolic patterns and the activity of the autonomic nervous system has not yet been elucidated. In this study, we investigate the symbolic dynamics that reflect acceleration (='1') and deceleration (='0') of the instantaneous heart rate. The resulting binary series is analyzed with respect to the regularity of binary patterns of length 8 using Approximate Entropy (ApEn). Binary patterns were grouped according to the level of their regularity as assessed by ApEn. ECG recordings were obtained from 17 healthy subjects during graded head-up tilt (0, 15, 30, 45, 60, 75, and 90°). The linear correlation (Spearman correlation coefficient) between tilt angle and the occurrence of binary patterns was evaluated. The results show that regular binary patterns occurred more often with increasing tilt angle whereas the occurrence of some irregular patterns decreased. Some binary patterns did not show a change of occurrence during tilt. When compared to the results of spectral analysis, regular binary patterns reflect sympathetic modulations whereas irregular binary patterns reflect parasympathetic modulations. The parameters derived from binary symbolic dynamics reflect changes of autonomic modulations during graded head-up tilt and are not fully correlated to the spectral markers of HRV.
KW - Autonomic nervous system
KW - Graded head-up tilt
KW - Heart rate variability
KW - Symbolic dynamics
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U2 - 10.1016/j.compbiomed.2011.04.013
DO - 10.1016/j.compbiomed.2011.04.013
M3 - Article
C2 - 21570680
AN - SCOPUS:84857053590
VL - 42
SP - 313
EP - 318
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
SN - 0010-4825
IS - 3
ER -