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Mechanical Manifestation of Human Hemodynamics: Insights from Multivariate Time Series Analysis

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30 diapositives · 428 Views · Jul 13, 2014

This study examines human hemodynamics through a mechanical lens, utilizing force plate measurements and ECG signals to analyze the multidimensional time series data of healthy adults. By capturing the ground reaction forces during cardiac cycles, we investigate how internal mass motions within the body link to cardiovascular dynamics. The research explores geometrical properties of curves derived from these measurements and their relation to physiological events, providing insights into the impact of arterial elasticity and pressure waves on hemodynamic measurements.

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  1. Mechanical manifestation of human hemodynamics J.Kříž, P.Šeba Department of physics,University Hradec Kralove and K.Martiník Faculty of Medicine, Charles University arXiv: physics/0507135 15. konference českých a slovenských fyziků 7.9.2005

  2. Force plate Measured are the three force and three moment components , i.e. a six dimensional multivariate time series

  3. Typical data

  4. Force plate Measured are the three force and three moment components , i.e. a six dimensional multivariate time series only five independent channels Usual choice: three force components + point of application of the force: COP

  5. Typical data: COP (120 s)

  6. Our equipment

  7. Measurements Using the force plate and a special bed we measured the force plate output and the ECG signal on 17 healthy adult males. In three cases we measured also the heart sounds. In such a way we obtained a 7 or 8 dimensional time series. The used sampling rate was 1000 Hz.

  8. Typical data: COP (10 s)

  9. For a reclining subject the motion of the internal masses within the body has a crucial effect. Measured ground reaction forces contain information on the blood mass transient flow at each heartbeat and on the movement of the heart itself. (There are also other sources of the internal mass motion that cannot be suppressed, like the stomach activity etc, but they are much slower and do not display a periodic-like pattern.) Starting point of the cardiac cycle: the R wave of the ECG signal. Length of the cycle: 1000 ms

  10. Multivariate signal: process multidimensional time-parameterized curve. Measured channel: projection of the curve to a given axis Changing the position of an electrode within EEG measurement changes the measured voltage. The measured process remains unchanged. Characterizing the curve: geometrical invariants: c: [a,b]n… Cn([a,b]) – mapping, such that examples of geometrical invariants: length of a curve Curvatures

  11. Frenet frame A Frenet frame is a moving reference frame of northonormal vectors e_i(t) which are used to describe a curve locally at each point γ(t). The main message of the differential geometry: it is more natural to describe local properties of the curve in terms of a local reference system than using a global one like the euclidean coordinates.

  12. Assume that are linearly independent • The Frenet Frame is the family of orthonormal vectors • called Frenet vectors. They are constructed from the derivates of c(t) using the Gram-Schmidt orthogonalization algorithm with • The real valued functions are called generalized curvatures and are defined as

  13. Special cases 2 – dimensional curve …tangent, normal …curvature 3 – dimensional curve …curvature …torsion

  14. Frenet-Serret Formulas Relation between the local reference frame and its changes Curvatures are invariant under reparametrization and Eucleidian transformations! Therefore they are geometric properties of the curve. Main theorem of curve theory

  15. The 5 curvatures were evaluated at each cycle and the mean over cycles was taken. The measurement lasted 8 minutes

  16. The results are reproducible

  17. What does it mean? Are the curvature peaks linked to some physiological events?

  18. On branching places of large arteries the pulse wave is scattered and the subsequent elastic recoil contribute to the force changes measured by the plate. A similar recoil is expected also when the artery changes its direction (like for instance in the aortal arc).

  19. Pressure wave oscillations

  20. Pathology: abdominal aneurism

  21. volunteer pacient

  22. Scattering of the pressure wave on the artery branchings / bendings leads to forces and moments measured by the force plate. Pressure wave velocity: Depends on the elasticity of the arterial wall and on the arterial pressure.

  23. Pulse wave velocity on large arteries is not directly accessible.

  24. Timing and consistency Pulse wave velocity: c=L/T; L=0.7 m

  25. Magnetic resonace measurements

  26. What is it good for? • Measuring the pressure wave velocity in large arteries • Observing pathological reflections (recoils) • Testing the effect of medicaments on the aortal wall properties • etc. and all this fully noninvasively. Cooperation of the patient is not needed