TY - GEN
T1 - Time frequency analysis of heart rate variability with chaos theory
AU - Chuduc, Hoang
AU - Stein, Phyllis K.
PY - 2013/1/1
Y1 - 2013/1/1
N2 - Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval. HRV parameters providing information about the scaling behavior or the complexity of the cardiac system were included. In addition, Chaos theory is a field of study in mathematics, with applications in several disciplines including physics, engineering, economics, biology, and philosophy. Chaos theory studies the behavior of dynamical systems that are highly sensitive to initial conditions, an effect which is popularly referred to as the butterfly effect. The goal was to investigate the influence of gender, age and day-night variation on these nonlinear HRV parameters. Numerical titration yielded similar information as other nonlinear HRV parameters do. However, it does not require long and cleaned data and therefore applicable on short (9 minutes) noisy time series. A higher nonlinear behavior was observed during the night while nonlinear heart rate fluctuations decline with increasing age. Our results support the involvement of the autonomic nervous system in the generation of nonlinear and complex heart rate dynamics.
AB - Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval. HRV parameters providing information about the scaling behavior or the complexity of the cardiac system were included. In addition, Chaos theory is a field of study in mathematics, with applications in several disciplines including physics, engineering, economics, biology, and philosophy. Chaos theory studies the behavior of dynamical systems that are highly sensitive to initial conditions, an effect which is popularly referred to as the butterfly effect. The goal was to investigate the influence of gender, age and day-night variation on these nonlinear HRV parameters. Numerical titration yielded similar information as other nonlinear HRV parameters do. However, it does not require long and cleaned data and therefore applicable on short (9 minutes) noisy time series. A higher nonlinear behavior was observed during the night while nonlinear heart rate fluctuations decline with increasing age. Our results support the involvement of the autonomic nervous system in the generation of nonlinear and complex heart rate dynamics.
KW - Chaos theory
KW - Circadian variations
KW - Heart rate variability
UR - http://www.scopus.com/inward/record.url?scp=84893326085&partnerID=8YFLogxK
U2 - 10.1109/ICCSA.2013.35
DO - 10.1109/ICCSA.2013.35
M3 - Conference contribution
AN - SCOPUS:84893326085
SN - 9780769550459
T3 - Proceedings of the 2013 13th International Conference on Computational Science and Its Applications, ICCSA 2013
SP - 174
EP - 177
BT - Proceedings of the 2013 13th International Conference on Computational Science and Its Applications, ICCSA 2013
PB - IEEE Computer Society
T2 - 2013 13th International Conference on Computational Science and Its Applications, ICCSA 2013
Y2 - 24 June 2013 through 27 June 2013
ER -