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Related Experiment Videos

Assessment of cerebral autoregulation using time-domain cross-correlation analysis.

C C Chiu1, S J Yeh

  • 1Institute of Automatic Control Engineering, Feng Chia University, ROC, Taichung, Taiwan. chiuc@auto.fcu.edu.tw

Computers in Biology and Medicine
|October 18, 2001
PubMed
Summary

Cross-correlation analysis of blood pressure and flow velocity effectively assesses cerebral autoregulation (CA). Changes in time lags between these signals indicate autoregulatory disturbances, offering a valuable diagnostic tool.

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Area of Science:

  • Neuroscience
  • Physiology
  • Biomedical Engineering

Background:

  • Cerebral autoregulation (CA) is crucial for maintaining stable brain blood flow.
  • Assessing CA dynamics is vital for understanding neurological health and disease.
  • Non-invasive methods are needed to evaluate CA in real-time.

Purpose of the Study:

  • To evaluate the utility of time-domain cross-correlation analysis for assessing cerebral autoregulation (CA).
  • To investigate the impact of different frequency bands on the assessment of CA dynamics.
  • To determine if cross-correlation functions (CCFs) of blood pressure and flow velocity can detect autoregulatory disturbances.

Main Methods:

  • Beat-to-beat time series of mean arterial blood pressure (MABP) and mean cerebral blood flow velocity (MCBFV) were recorded from 13 healthy volunteers.

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  • MABP and MCBFV signals were bandpass filtered into very low (VLF), low (LF), and high (HF) frequency ranges.
  • Cross-correlation functions (CCFs) were calculated using a moving window to analyze the time lags between MABP and MCBFV.

    • Main Results:

    • Significant increases in time lags of peak MABP-MCBFV CCFs were observed between the LF and HF frequency ranges (p < 0.001).
    • A left-shift (negative lag) in CCF peaks, indicating a phase-lead property, was noted.
    • Increasing time lags correlated with evidence of autoregulatory disturbance.

    Conclusions:

    • Time-domain cross-correlation analysis of pre-filtered MABP and MCBFV is a potentially valuable tool for estimating CA dynamic response.
    • Frequency-specific analysis of CCFs can reveal disturbances in cerebral autoregulation.
    • This method offers a promising approach for non-invasively assessing CA in clinical and research settings.