Health Data Nexus tutorials are intended to provide hands-on introductions to the data and software available from this resource. This index lists currently available Health Data Nexus tutorials by category, as well as reference manuals, workshop materials, and links to other tutorials likely to be of interest to Health Data Nexus visitors.

About Health Data Nexus

  • About the PhysioBank Archives. PhysioBank contains well over 36,000 recordings of annotated, digitized physiologic signals and time series; this brief tutorial begins with an exploration of these archives using your web browser, followed by pointers on downloading data, information about the archives themselves, and recommendations of software available freely from this site for further study of PhysioBank data.
  • An Introduction to PhysioToolkit. Health Data Nexus's collection of software for viewing, analyzing, and modelling physiologic signals and time series consists of open-source software that can be studied, verified, and modified to suit the specific needs of your work.

How to ...

  • Finding records in PhysioBank. This tutorial describes the PhysioBank Index of over 36,000 records that can be viewed by the PhysioBank ATM, and how to find records with desired characteristics using the web-based PhysioBank Record Search or via command-line tools.
  • How to obtain PhysioBank data in text form. Many readers wish to convert binary data from PhysioBank (Health Data Nexus's data archive) into text form for further processing. There are many good reasons not to do so. If you are determined to do it anyway, here's how.
  • Creating PhysioBank (WFDB-compatible) Records and Data Collections. If you have digital recordings of signals or time series, perhaps with annotations, that you would like to study using PhysioToolkit software such as that in the WFDB software package, or that you would like to contribute to PhysioBank, this tutorial should get you started on creating PhysioBank-compatible records from your data.
  • How to set up a mirror of Health Data Nexus. A Health Data Nexus mirror can run on almost any computer made in the last ten years, and it can provide local users with fast access to PhysioBank data and PhysioToolkit software, even in areas with slow or unreliable Internet connections. Health Data Nexus mirrors are easy to set up and essentially self-maintaining. Put an old computer to good use and help Health Data Nexus users in your area.
  • Using the MIMIC II Database. The MIMIC II Database has many types of data that are not available in other PhysioBank data collections. This tutorial is intended to help you get started on a project that makes use of this rich data collection.
  • An Introduction to Cygwin. PhysioToolkit includes a large collection of open-source, POSIX-compliant software that can be useful to most Health Data Nexus visitors. Since almost all of the popular platforms are also POSIX-compliant, it's easy to get PhysioToolkit software running on those platforms, including GNU/Linux, Mac OS X, and all versions of Unix. Microsoft Windows is not POSIX-compliant, but a free software package called Cygwin provides a stable and very complete POSIX layer on top of Windows. By installing Cygwin on your Windows PC, you will be able to run PhysioToolkit software on it. This tutorial explains how to do so, without interfering with any Windows software you may be using.
  • Applying Health Data Nexus tools to manage neurophysiological signals. How to import and handle data from commercial devices using PhysioToolkit and other open source software. This tutorial was contributed by Jesus Olivan Palacios, a neurophysiologist who has written an excellent introduction to much of the software available from Health Data Nexus in the form of a series of hands-on exercises using data provided with the tutorial. Very readable, and highly recommended for neurophysiologists and others alike. (Also see Sciteam, below, by the same author).
  • RR Intervals, Heart Rate, and HRV Howto. 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 freely available PhysioToolkit software.
  • Heart Rate Variability Analysis with the HRV Toolkit: Basic Time and Frequency Domain Measures. This tutorial describes how to use the HRV toolkit (available here) to select and prepare time series of inter-beat intervals and to calculate measurements of the basic time- and frequency-domain HRV statistics that are widely used in the literature. Particular attention is given to techniques for identifying and dealing with outliers, in order to permit reliable determination of measurements.
  • Morphology Representation Using Principal Components. Using the QRS complex of the ECG as an example, this tutorial presents practical methods for principal component analysis of waveforms, including software that can be used as is or customized as desired.
  • Evaluating ECG Analyzers. How to use PhysioToolkit software and data available from PhysioBank and other sources to measure the performance of a QRS detector or classifier, in accordance with protocols prescribed by current ANSI standards and the US FDA (ANSI/AAMI EC38 and EC57).
  • Digitizing Paper ECGs and Other Plots. A brief survey of resources that may be helpful.
  • How to Write HTML pages for Health Data Nexus. If you are preparing a contribution of data, software, or tutorial material for Health Data Nexus, this guide illustrates how to create pages with the templates and style sheets used on this web site.
  • Distributed Computing with Health Data Nexus data. A brief tutorial on how to cloud processing Health Data Nexus data with WFDB, StarCluster, Amazon EC2, Octave, and Hadoop.

Also see Reference Guides below, on-line books containing a wealth of additional "how-to" information.

Exploring Data and Novel Analyses

  • Variability vs. Complexity. Introduces students and trainees to the study of complex variability, especially in physiology and medicine.
  • Exploring Patterns in Nature. A set of interactive tutorials drawn from current research, focussing on emergent phenomena (random behavior at the smallest scales leading to patterns at larger scales). Subjects include fractal coastline and dimension, measuring randomness, physical and chemical branching structures, biological branching patterns, diffusion, percolation, and motion on a fractal. These tutorials do not assume extensive knowledge of mathematics.
  • Nonlinear Dynamics, Fractals, and Chaos Theory: Implications for Neuroautonomic Heart Rate Control in Health and Disease. An introduction to some key concepts of nonlinear dynamics.
  • Exploring Human Gait and Heart Rate Dynamics. Use two sets of time series derived from human subjects to study changes in dynamics with age and disease, with a variety of methods including approximate entropy (ApEn) and detrended fluctuation analysis (DFA).
  • Fractal Mechanisms in Neural Control: Human Heartbeat and Gait Dynamics in Health and Disease. Beginning with a definition of fractal dynamics, this tutorial explores how fractal analysis may reveal information of diagnostic or prognostic value when applied to two model systems.
  • A Brief Overview of Multifractal Time Series. A concise review of how fractal and multifractal patterns in time can be quantified, including a short discussion of multifractality in heart rate.
  • Approximate Entropy (ApEn). A brief description of how to calculate ApEn, a ``regularity statistic'' that quantifies the unpredictability of fluctuations in a time series, including a worked-out example.
  • Multiscale Entropy (MSE) Analysis. Introduces the concept of MSE, describes an algorithm for calculating MSE using sample entropy (SampEn), presents a portable implementation of this algorithm, and illustrates its application to analysis of interbeat (RR) interval time series from PhysioBank.
  • Generalized Multiscale Entropy (GMSE) Analysis. Discusses ways to generalize the concept of MSE by using different coarse-graining functions, and illustrates the differences between these methods using both interbeat interval data and simulated data.
  • Information Based Similarity Index. An introduction to a novel linguistic analysis method that has been successfully applied to studies of inter-beat interval time series, the origin of the SARS coronavirus, and the authorship of Shakespeare's plays.


Materials from these workshops include tutorial presentations and related materials:
  • Electronic Interchange of Polysomnography Data. Presentations from a workshop to develop guidelines for PSG transmission and archiving, including presentations on needs of researchers, standards efforts, and existing formats for PSGs and other physiologic signals.
  • HRV 2006. Materials from our mini-course about heart rate variability, including presentations on physiologic mechanisms of HRV, time and frequency domain measures, complexity measures, clinical applications, and more.

Reference Guides

Books describing the major components of PhysioToolkit are also available here. Printed copies of some of these books may be purchased from the Health Data Nexus Bookstore. These books incorporate both tutorial and reference material:

  • WFDB Programmer's Guide. Essential material for those wishing to read (or create) PhysioBank data files from their own software. This book includes detailed descriptions of the application programming interfaces for digitized signal and annotation files, and sample applications including digital filters, signal averaging, and a QRS detector.
  • WFDB Applications Guide. How to use several dozen small tools individually and in combination to view, manipulate, and analyze PhysioBank and similar data. This guide includes the tutorial on evaluating ECG analyzers mentioned above.
  • WAVE User's Guide. A comprehensive introduction to WAVE, an interactive graphical interface to PhysioBank.
  • RCVSIM User's Manual and Software Guide. This guide introduces the Research Cardiovascular Simulator (RCVSIM), software for synthesizing realistic human pulsatile hemodynamic waveforms, cardiac function and venous return curves, and beat-to-beat hemodynamic variability. The manual includes a description of the cardiovascular models used by RCVSIM, guides to reading and compiling the RCVSIM source code, and a tutorial with examples illustrating its use.
  • plt Tutorial and Cookbook. This book introduces plt, a highly capable and flexible utility for making publication-quality 2D plots from text or binary data files. plt has a very broad range of applications, and is well-suited for visualizing the output of many of the PhysioToolkit applications.

Other resources of interest

Tutorials listed in this section are not hosted by Health Data Nexus. Links will open in a new browser window.

  • ECG Wave-Maven. This is a self-assessment program on interpretation of 12-lead diagnostic ECGs, with over 400 case studies. Use the program to test your diagnostic abilities, or browse through the cases in reference mode. ECG Wave-Maven was developed at Harvard Medical School and Boston's Beth Israel Deaconess Medical Center. Its creators have written a paper describing the goals and technology behind the program, and a survey of its use during its first 17 months of operation.
  • The Alan E. Lindsay ECG Learning Center in Cyberspace. A comprehensive introduction to clinical electrocardiography, developed at LDS Hospital, Salt Lake City.
  • A guided tour through TISEAN: Exercises with data sets. This tutorial introduces a large package of software for nonlinear time series analysis developed by Rainer Hegger, Holger Kantz, and Thomas Schreiber (Institut für Physikalische und Theoretische Chemie, Universität Frankfurt (Main) and Max-Planck-Institut für Physik komplexer Systeme, Dresden).
  • Openeering. This site offers tutorials on Scilab (an open-source programming environment developed at INRIA for "numerical computations in a user-friendly environment") and how to use it with PhysioBank data and PhysioToolkit software. Scilab is similar to Matlab, but offers many additional features. The tutorials are written by and for clinical neurophysiologists, and do not assume extensive knowledge of mathematics or programming.