Heart rate variability

From the physiological background given above, it is clear that our heart does not beat at a fixed rate. The rate at which our heart contracts is in fact determined and continuously modulated by complex interactions between the sympathetic and parasympathetic system in order to properly respond to the demands of our body. These changes in heart rhythm constitute the concept of heart rate variability (HRV). Its easy derivation from non-invasive recordings and its informative value on cardiac autonomic activity, has greatly popularized the study of HRV. Moreover, one of the most important findings of HRV analyses, is that a lack of variability in the HR is related to mortality in patients that

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Figure 1.6: Electrocardiogram (top panel) and its tachogram (lower panel). The black triangles indicate the detected R peaks, and the interval (in ms) between two consecutive R peaks is given below each arrow.

suffered from myocardial infarction [190]. Possibly, the decreased HRV is due to a prolonged increased sympathetic or decreased vagal tone [99].

To study HRV, first an ECG is recorded from which the R peaks of the QRS complexes are detected using specialized algorithms. Throughout this dissertation, a real-time QRS detection algorithm based on bandpass filtering, derivative, squaring and integration operations, adaptive thresholding and search procedures, known as the Pan-Tompkins algorithm, is used [136]. In order to deal with possible missing or spurious detections, the estimated R peak locations are additionally processed using an automated procedure that finds the most probable R peak location based on prior heart beats in case of a suspicious location [212]. The time between two consecutive heart beats is an RR interval. Note that an RR interval is related to the heart rate according to HR [bpm]= 60

RR [s]. When RR intervals are tracked in time, a tachogram is

formed, which constitutes the basic signal for the study of HRV. An example of a tachogram is given in Fig. 1.6. After preprocessing of the RR intervals, they are also called normal-to-normal (NN) intervals.

can be deduced [1,26,182]. An overview of the most important HRV measures is given in the next paragraph, followed by some important clinical applications of HRV.

Measures of heart rate variability

Linear measures of HRV have been standardized in a Task Force of The European Society of Cardiology and The North American Society of Pacing and Electrophysiology [182]. The most common time domain HRV measures include:

• meanNN [ms]: the mean NN interval;

• diffNN [ms]: the difference between the longest and shortest NN interval; • SDNN [ms]: the standard deviation of the NN intervals. SDNN reflects all cyclic components responsible for variability and is thus a general measure of HRV;

• RMSSD [ms]: the square root of the mean squared differences of successive NN intervals;

• pNN50 [%]: the percentage of interval differences of successive NN intervals greater than 50 ms;

• SDSD [ms]: the standard deviation of squared differences of successive NN intervals.

The latter three are strongly correlated and related to high frequency spectral power (cfr. infra). These measures are linked to cardiac parasympathetic activity of the ANS.

HRV measures are also commonly deduced from spectral analysis of the tachogram [112]. These frequency domain measures are based on the calculation of the power spectral density (PSD) of the tachogram. To this end, in this thesis, unevenly sampled tachograms are first resampled at 4 Hz using cubic splines [171]. The PSD is then obtained via Welch’s method using a 1024 point fast Fourier transform (FFT), a periodic Hamming window, and an overlap of 50%. We can distinguish four frequency bands:

• Ultra low frequencies (ULF): the ULF band is defined from 0 Hz to 0.003 Hz and is only considered in 24 h recordings.

PHYSIOLOGICAL BACKGROUND 15

• Very low frequencies (VLF): the VLF band goes from 0.003 Hz to 0.04 Hz.

• Low frequencies (LF): the LF band is defined from 0.04 Hz to 0.15 Hz. • High frequencies (HF): the HF band goes from 0.15 Hz to 0.40 Hz. In each frequency band, the power, expressed in ms2_{, is computed by integration}

of the PSD curves. Both LF and HF components are also often expressed in normalized units (nu). This is a relative description of the power in the LF or HF band with respect to the total power (TP). In short-term recordings, TP is determined as the sum of the power in the LF and HF band.

Peak frequencies in the ULF band are related to circadian rhythms, while the physiological meaning of the VLF band is not clear. Possibly, thermoregulation operates in the VLF band. Power in the LF band is reduced by either sympathetic or parasympathetic blockade, and therefore, LF power is believed to reflect both sympathetic and parasympathetic modulations, though this has been debated [66, 152]. Also Mayer waves, i.e. oscillations of arterial pressure with a period of 10 s, affect LF power [90]. The power in the HF band is almost fully eliminated during parasympathetic blockade by atropine, and is therefore often taken as an index of cardiac vagal control. Another commonly used measure is the ratio between LF and HF power (LF/HF), that is considered a measure of sympathovagal balance, though this is also not widely accepted [47,224].

An example of a PSD is given in Fig. 1.7.

Note that it is important to always compare HRV measures derived from recordings of equal length.

There are also geometric and nonlinear methods to characterize HRV. Although nonlinear methods may account better for the nonlinear processes that are responsible for HRV, their physiological interpretation is not yet clear. Nonlinear HRV measures can roughly be classified in four categories [200]: (1) fractal measures - they assess the self-affinity of heart rate fluctuations over multiple time scales; (2) entropy measures - they determine the (ir)regularity or randomness of heart beat fluctuations; (3) symbolic dynamic measures - they assess the coarse-grained dynamics of heart rate fluctuations based on symbolization; and (4) poincaré plot representations - they assess the heart beat dynamics based on a simplified phase-space embedding. We will not go further into detail in these methods. More information can be found in [113,166,192,200].

Figure 1.7: Power spectral density of tachogram of 30 minutes, with indication of VLF, LF and HF bands and their corresponding powers.

Clinical importance

As previously mentioned, HRV is related to mortality risk after myocardial infarction. In addition, also links with diseases, including diabetic neuropathy, renal failure and sudden cardiac death, were found [1, 176, 182]. Also in the field of psychophysiology, HRV is commonly used to study among others the influence of mental stress, panic disorders [64], anxiety and depression after myocardial infarction [5].