PhysioToolkit Software Index

As for PhysioBank data, we describe the software available here in terms of three classes:

• Class 1 (fully supported, extensively and rigorously tested software)
• Class 2 (archival copies of software that supports published research, contributed by authors, together with corrections and improvements submitted by authors and users)
• Class 3 (contributed code that may need further testing or development)

We make class 2 and class 3 software available via PhysioNet as a service to the research community. Contributed code is placed in classes 2 and 3 on acceptance, and may be admitted to class 1 after review and a public comment period.

Software for use with PhysioBank

The WFDB Software Package [Class 1] is a GPLed successor to the DB Software Package from the creators of the MIT-BIH databases of physiologic signals at the Massachusetts Institute of Technology, one of the core laboratories contributing to PhysioNet. The WFDB Software Package incorporates the WAVE interactive visualization, analysis, and annotation editing tool for GNU/Linux, Mac OS/X, and Unix. A version of WAVE that uses the portable GTK+ GUI toolkit, GTKWave [Class 3], is now available in a beta version for Linux and MS-Windows.

If you are interested in developing your own software to work with PhysioBank and other physiologic data, the WFDB library (included in the WFDB Software Package) provides functions (subroutines) for reading and writing PhysioBank data files from programs written in C, C++, or Fortran. When compiled together with the W3C's libwww libraries, the WFDB library provides HTTP client code that permits applications to read data directly from PhysioBank and other web and FTP servers as well as from local disk files. All of these capabilities are also available to users of Matlab R13 via the WFDB_tools package, which provides an interface between the WFDB library and Matlab.

Also available is a collection of m-files [Class 3] for reading and writing PhysioBank data files from Matlab or Octave (an open-source environment similar to Matlab), and a Matlab viewer [Class 3] for PhysioBank signals and annotations. A growing collection of contributed software for Matlab and Octave includes these and other applications.

Simulation

The Research Cardiovascular Simulator, RCVSIM [Class 1], is software for synthesizing realistic human pulsatile hemodynamic waveforms, cardiac function and venous return curves, and beat-to-beat hemodynamic variability. RCVSIM generates simulations in the formats used for PhysioBank data, so that WFDB applications can be used to analyze and view RCVSIM output. The RCVSIM package includes binaries for GNU/Linux and sources for other platforms (Matlab and its compiler are required to compile RCVSIM sources), as well as a tutorial and reference guide.

ECGSYN [Class 2] generates a realistic ECG signal with user-settable mean heart rate, number of beats, sampling frequency, waveform morphology (P, Q, R, S, and T timing, amplitude, and duration), standard deviation of the RR interval, and LF/HF ratio. ECGSYN can reproduce many of the features of the human ECG, including beat-to-beat variation in morphology and timing, respiratory sinus arrhythmia, QT dependence on heart rate, and R-peak amplitude modulation. Implementations of ECGSYN in C, Java, and Matlab/Octave m-code are available.

ECGwaveGen [Class 3] is a Matlab/Octave program for generating a synthetic ECG with user-settable heart rate, signal duration, sampling frequency, QRS amplitude and duration, and T-wave amplitude. Unlike the signals generated by ECGSYN, the output of ECGwaveGen is not intended to be highly realistic; the primary application for this program is testing the fidelity of analog signal-processing components of cardiac monitors and similar instruments, using an ECG-like signal with well-defined characteristics.

Also see the collections of synthetic time series with known characteristics in PhysioBank.

Graphics

Physiologic signal processing

ecgpuwave [Class 2] is software for locating waveform boundaries in the ECG (i.e., the beginnings, peaks, and ends of P, QRS, and T waves). The software can be used to analyze either annotated or unannotated recordings (it includes an implementation of the Pan-Tompkins QRS detection algorithm). Sources for ecgpuwave are available here; a reference guide can be read here or downloaded in Unix man page format; also available is a paper in which ecgpuwave is evaluated using the QT Database.

Software for deriving a respiration signal [Class 2] from one or two ECG signals using the EDR technique, the original paper that describes this technique, and a second paper describing applications of the EDR, are available here.

Software for assessing physical activity from a heart rate time series [Class 2], and a paper that describes the development and evaluation of this algorithm, are available here.

The apdet [Class 2] software package provides automated detection of obstructive sleep apnea by analysis of interbeat intervals in the ECG. The paper that introduced this algorithm is also available.

The heartprints [Class 2] software package provides a novel way to visualize the dynamics of ventricular ectopic activity.

Analysis of heart rate variability (HRV)

The pNNx [Class 2] software package offers a novel method for characterizing HRV with a family of time-domain statistics of which pNN50 is the best known.

The WFDB Software Package (see above) includes several applications useful for HRV studies, including programs for extracting RR interval time series from annotation files, reconstructing NN interval series with missing data, deriving instantaneous heart rate time series, and deriving power spectra from uniform and non-uniform time series.

The nonlinear analysis software described below, in particular DFA, has been usefully applied to studies of HRV.

A brief tutorial, RR Intervals, Heart Rate, and HRV Howto, offers a brief overview of how to obtain inter-beat (RR) interval and heart rate time series, and of some basic methods for characterizing heart rate variability, using PhysioToolkit software.

Nonlinear analysis of time series

Software for detrended fluctuation analysis (DFA) [Class 1] is available here, together with notes on the method.

Software for calculating sample entropy (SampEn) [Class 1] can be used to characterize the unpredictability of fluctuations in a time series. SampEn has advantages over the earlier and closely related approximate entropy (ApEn) statistic. The SampEn software includes both C and Matlab implementations.

Software for multiscale entropy (MSE) analysis [Class 1] is useful for study of time series that have correlations at multiple scales. A tutorial illustrating the application of the MSE method to analysis of interbeat (RR) interval time series accompanies the software.

Software for calculating Lyapunov exponents [Class 2] from small data sets is available together with an article describing it.

Other free software

Open-source software useful for the study of physiologic signals and time series is available from other sources. Information about several such software packages is available here.

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Updated Wednesday, 04-Aug-2004 17:42:07 EDT