Software for advanced HRV analysis
Introduction
Heart rate variability (HRV) describes the variations between consecutive heartbeats. The regulation mechanisms of HRV originate from the sympathetic and parasympathetic nervous systems and, thus, HRV can be used as a quantitative marker of the autonomic nervous system [1]. Stress, certain cardiac diseases, and other pathologic states affect the HRV. A good review of physiological origins and mechanisms of HRV can be found in [2].
In HRV analysis, either the heart rate as a function of time or the intervals between successive QRS complexes need to be determined. In this paper, when we talk about HRV we actually mean the variability of RR intervals (i.e. intervals between consecutive R peaks).
The analysis methods of HRV can be divided into time-domain and frequency-domain methods. The guidelines for these methods are given in [1]. In addition, there are several nonlinear methods such as the so-called Poincaré plot.
In this study, we present a computer program for advanced HRV analysis for Microsoft® Windows® operating systems. The program calculates all the commonly used time- and frequency-domain parameters of HRV as well as the nonlinear Poincaré plot. The spectrum estimates in frequency-domain are calculated by using both parametric and nonparametric methods. The program also features advanced detrending options for RR series and an informative printable report sheet which can be exported to various file formats including the portable document format (PDF). Combined with a modern heart rate monitor capable of recording RR intervals this freely distributed program forms a complete low-cost HRV measuring and analysis system.
Section snippets
Background
We have been developing a Matlab1 based software package for event-related biosignal analysis in collaboration with the Kuopio University Hospital and the Brain@Work-Laboratory of the Finnish Institute of Occupational Health. The software package consists of a main browser for different biosignals and of various analysis tools. The presented HRV analysis software for Windows® has originated from the HRV analysis
Computational methods
The analysis methods of HRV can be divided into time-domain, frequency-domain, and nonlinear methods. In the following, these methods are discussed shortly. The denotions and definitions for HRV parameters in this paper and in the developed software follow the guidelines given in [1].
Program description
The program was originally developed using Matlab 6.1 (Release 12.1). The final version of the program has been compiled to a standalone C-language application using the Matlab Compiler Suite 2.3 and the free Borland C-Builder 5.5 compiler. Thus, the program is now independent from Matlab and does not require a Matlab installation to run.
The presented HRV analysis software calculates all the commonly used time- and frequency-domain measures of heart rate variability. All the calculated
Sample runs
As a test case we measured HRV from a healthy young female at rest in lying position. As a measuring device a POLAR S810 heart rate monitor was used. It is capable of automatically storing consecutive RR intervals and it is very inexpensive compared to other commercial ECG or RR interval measuring devices. The resolution of a POLAR Vantage NV heart rate monitor, which is analogous to the S810 but with lower memory capacity, was studied in [11]. The inaccuracy of the RR interval measurements was
Discussions and future plans
We have presented a computer program for advanced HRV analysis for Windows® operating systems. The program calculates all the commonly used time- and frequency-domain parameters and the nonlinear Poincaré plot. Advanced spectrum estimation methods and detrending options are included as well. The program generates an informative and easy to interpret printable one-page report sheet that can be exported to various different file formats including the portable document format (PDF). The results of
Mode of availability
The HRV analysis software for Windows is available free of charge upon request. If you are interested in downloading and using the software please visit http://it.uku.fi/biosignal or email to [email protected] for further instructions.
Acknowledgements
This work has been done in collaboration with the Kuopio University Hospital and the Brain@Work-Laboratory of the Finnish Institute of Occupational Health.
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