Heart Rate Variability: Measures and Models

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# Heart Rate Variability: Measures and Models - PowerPoint PPT Presentation

Heart Rate Variability: Measures and Models. 指導教授：鄭仁亮 學生：曹雅婷. Outline. Introduction Methods Conventional Point Process Fractal Point Process Measure Standard Measures Novel Measures. Introduction. ECG a recording of the cardiac-induced skin potentials at the body ’ s surface HRV

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## Heart Rate Variability: Measures and Models

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### Heart Rate Variability: Measures and Models

Outline
• Introduction
• Methods
• Conventional Point Process
• Fractal Point Process
• Measure
• Standard Measures
• Novel Measures
Introduction
• ECG

a recording of the cardiac-induced skin potentials at the body’s surface

• HRV

called heart rate variability, the variability of the RR-interval sequence

Methods
• The heartbeat sequence as a point process.
• The sequence of heartbeats can be studied by replacing the complex waveform of an individual heartbeat recorded in the ECG.
• The sequence of heartbeats is represented by
Conventional Point Process
• Simplest
• homogeneous Poisson point process
• Related point process
• nonparalyzable fixed-dead-time modified Poisson point process
• gamma-γ renewal process
Homogeneous Poisson point process
• The interevent-interval probability density function

where λ is the mean number of events per unit time.

• interevent-interval mean=1/λ
• interevent-interval variance=1/λ2
• The interevent-interval probability density function

Here τd is the dead time and λ is the rate of the process before dead time is imposed.

0

Fractal Point Process
• Fractal stochastic processes exhibit scaling in their statistics.
• Suppose changing the scale by any factor a effectively scales the statistic by some other factor g(a), related to the factor but independent of the original scale:

w(ax) = g(a)w(x).

Fractal Point Process
• The only nontrivial solution of this scaling equation, for real functions and arguments, that is independent of a and x is

w(x) = bg(x) with g(x) = xc

• The particular case of fixed a admits a more general solution

g(x; a) = xc cos[2πln(x)/ ln(a)]

Standard Frequency-Domain Measures
• A rate-based power spectral density
• Units of sec-1
• An interval-based power spectral density
• Units of cycles/interval
• To convert the interval-based frequency to the time-based frequency using
Estimate the spectral density
• Divided data into K non-overlapping blocks of L samples
• Hanning window
• Discrete Fourier transform of each block
Measures in HRV
• VLF.The power in the very-low-frequency range: 0.003–0.04 cycles/interval.
• LF.The power in the low-frequency range: 0.04–0.15 cycles/interval.
• HF.The power in the high-frequency range: 0.15–0.4 cycles/interval.
• LF/HF.The ratio of the low-frequency-range power to that in the high-frequency range.
Standard Time-Domain Measures
• pNN50.proportion of successive NN intervals
• SDANN.Standard Deviation of the Average NN interval
• SDNN.Standard Deviation of the NN interval
Other Standard Measures
• The event-number histogram
• The Fano factor
Novel Scale-Dependent Measures
• Allen Factor [A(T)]
• The Allan factor is the ratio of the event-number Allan variance to twice the mean: