Signal processing problems of neurocardiological fluctuations

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Signal processing problems of neurocardiological
fluctuations

• Z. Gingl, L. Rudas and P. Makra
• Department of Experimental Physics
• Medical Intensive Care Unit, Cardiology Centre,
  Faculty of Medicine
• University of Szeged
• www.noise.physx.u-szeged.hu/med

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Measured signals ECG, blood pressure
RRi
SBPi
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Typical heart rate waveform
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Measurement and analysis

• Heart rate (HR) and blood pressure (BP)
• sensitive to external and internal stimuli
• Mechanism of this influence is complex
• We try to measure, characterize and analyse these
  mechanisms continuous in time
• Measurement data
• heart rate (RR, inherently discrete)
• blood pressure (inherently continuous in time)

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HR modulation mechanism
Stimuli
Complex sensing and control mechanisms
Change in heart rate (measured)
continuous in time, interested in it
discrete, measure it
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RR measurements

• ECG amplitude and shape is neglected (time
  instants only)
• Information is in the modulation of ECG frequency
  (HR(t), RR(t))
• Inherently discrete and unevenly sampled(at
  R-wave locations)
• Digital sampling measurement (dt2ms typical)
• Peak detection, RR calculation (signal
  processing)
• Compensation for artifacts (measurement,
  extrasyst.)
• Time domain and frequency domain analysis
• Problems of methods, information extraction

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Blood pressure measurements

• Information both in amplitude and rate
• Inherently continuous in time and amplitude
• Digital sampling measurement (dt2ms)
• SBP peak detection
• creates discrete unevenly sampled signal (like
  RR)
• Compensation for artifacts
• Time domain and frequency domain analysis
• Problems of methods, information extraction

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Typically resampling is used(sample rate
conversion)

• Aim produce evenly sampled signal
• Reason fast Fourier transformation (FFT)
• Theoretical problems
• New points created by linear/spline interpolation
• Same signal?
• Resampling methods theoretically well
  established?
• RR resampling
• No new peaks created
• the continuous modulation determined in new time
  instants
• Alternatives direct methods for unevenly sampled
  signals(e.g. Lomb, they are fast enough)

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Illustration of resampling

• Theoretically both linear and spline are inexact
• Sampling theorem says
• there is exact method of resampling (fsgt2fmax)
• no loss of information due to discrete
  representation
• However linear and spline resampling methods
  provide enough precision

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Blood pressure analysis

• Information in the amplitude
• We recommend
• Fourier analysis of the whole signal(without
  peak detection and resampling)
• Advantages
• Inherently evenly sampled (typical dt2 ms)
• No peak detection
• No resampling required (no associated
  theoretical, practical problems)
• Less sensitive to artifacts (e.g. extrasystole)
• Contains the most of info (about heart rate also)

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How is it related to the SBP spectrum?
S(f)SSBP(f)S0(f)
SSBP(f)
S0(f)
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SBP and blood pressure spectra
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Blood pressure waveforms and spectra
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Spectral analysis benchmarks(length120 s, on a
typical PC)
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Conclusion and problems

• Resampling is performed on the modulation rather
  than on RR or SBP it is OK.
• Reason is FFT and some time-frequency analysis
  methods (like STFFT, Wigner-Ville distr., etc.)
• Alternative methods preferred (developed for
  unevenly sampled discrete signals, fast enough on
  todays PCs no reason for FFT)

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Conclusion and problems

• For BP spectrum of the whole signal
• No peak detection, no resampling
• Inherently evenly sampled (easy analysis FFT
  and time-frequency methods)
• More info than SBP
• Practically no RR measurement required
• Any better measurement of the HR and BP
  modulation?
• Nonlinear methods of analysis, time dependent
  spectral analysis (too many ways, too complex) ?
• Are some statistical parameters (variance,
  correlation) of fluctuations enough for practical
  diagnosis?

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Lomb normalized periodogram(for unevenly sampled
signal)
Lomb, N.R., 1976, Astrophysics and Space Science,
39, 447-462 Laguna P, Moody GB, Mark RG, IEEE
TRANSACTIONS ON BIOMEDICAL ENGINEERING, 45 (6)
698-715 JUN 1998