TY - GEN
T1 - Quantifying Heartbeat Dynamics by Magnitude and Sign Correlations
AU - Ivanov, Plamen Ch
AU - Ashkenazy, Yosef
AU - Kantelhardt, Jan W.
AU - Stanley, H. Eugene
N1 - Funding Information:
We thank A. Bunde, A.L. Goldberger, S. Havlin, C.-K. Peng, and T. Penzel for discussions and major contributions to the results reviewed here which represent collaborative research efforts. We thank the NIH/National Center for Research Resources (P41 RR13622), the Israel-U.S.A Binational Science Foundation and the Deutscher Akademischer Austauschdienst (DAAD) for support. The healthy volunteers were recorded as part of the SIESTA project funded by the European Union grant no. Biomed-2-BMH4-CT97-2040.
Publisher Copyright:
© 2003 American Institute of Physics.
PY - 2003/5/28
Y1 - 2003/5/28
N2 - We review a recently developed approach for analyzing time series with long-range correlations by decomposing the signal increment series into magnitude and sign series and analyzing their scaling properties. We show that time series with identical long-range correlations can exhibit different time organization for the magnitude and sign. We apply our approach to series of time intervals between consecutive heartbeats. Using the detrended fluctuation analysis method we find that the magnitude series is long-range correlated, while the sign series is anticorrelated and that both magnitude and sign series may have clinical applications. Further, we study the heartbeat magnitude and sign series during different sleep stages-light sleep, deep sleep, and REM sleep. For the heartbeat sign time series we find short-range anticorrelations, which are strong during deep sleep, weaker during light sleep and even weaker during REM sleep. In contrast, for the heartbeat magnitude time series we find long-range positive correlations, which are strong during REM sleep and weaker during light sleep. Thus, the sign and the magnitude series provide information which is also useful for distinguishing between different sleep stages.
AB - We review a recently developed approach for analyzing time series with long-range correlations by decomposing the signal increment series into magnitude and sign series and analyzing their scaling properties. We show that time series with identical long-range correlations can exhibit different time organization for the magnitude and sign. We apply our approach to series of time intervals between consecutive heartbeats. Using the detrended fluctuation analysis method we find that the magnitude series is long-range correlated, while the sign series is anticorrelated and that both magnitude and sign series may have clinical applications. Further, we study the heartbeat magnitude and sign series during different sleep stages-light sleep, deep sleep, and REM sleep. For the heartbeat sign time series we find short-range anticorrelations, which are strong during deep sleep, weaker during light sleep and even weaker during REM sleep. In contrast, for the heartbeat magnitude time series we find long-range positive correlations, which are strong during REM sleep and weaker during light sleep. Thus, the sign and the magnitude series provide information which is also useful for distinguishing between different sleep stages.
UR - http://www.scopus.com/inward/record.url?scp=85050095685&partnerID=8YFLogxK
U2 - 10.1063/1.1584912
DO - 10.1063/1.1584912
M3 - Conference contribution
AN - SCOPUS:85050095685
T3 - AIP Conference Proceedings
SP - 383
EP - 391
BT - Unsolved Problems of Noise and Fluctuations, UPoN 2002
A2 - Bezrukov, Sergey M.
PB - American Institute of Physics Inc.
T2 - 3rd International Conference on Unsolved Problems of Noise and Fluctuations in Physics, Biology, and High Technology, UPoN 2002
Y2 - 3 September 2002 through 6 September 2002
ER -