An open source javascript-based web application for visualizing health data.
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An open source javascript-based web application for visualizing health data.


hGraph Demo:

hMixer Demo: hMixer Repo:

About the REPO

The hGraph is an open source project that is being developed and designed to provide an industry standard of presenting health care information to professionals and average citizens alike.


The HGraph class relies on d3.js, which is a very popular javascript library for manipulating SVG, specficically for graphs and data plotting.

Once you have downloaded the latest version, you will need to include in in your html above the HealthGraph source code:

    <script src="/path/to/your/d3.js" type="text/javascript"></script>
    <script src="/path/to/your/HealthGraph.js" type="text/javascript"></script>


During a window.onload or similar entry point, the health graph is constructed and intialized by:

    var graph;
    window.onload = function(){

            graph = new HGraph({
                    container : document.getElementById("graph_container"),
                    userdata  : {
                                                    overallScore : 90,
                                                    factors      :
                                                                    label : 'Family History',
                                                                    score : 80,
                                                                    label : 'Caloric Intake',
                                                                    score : 100



Want to Contribute? Here is how you can help

For designers and engineers:

  • What's version 2 of hGraph?
  • Design the population hGraph for your neighborhood, city, clinic, nation.
  • CSS refinement of hScore (making it beautiful).
  • CSS refinement of hGraph (making it beautiful).
  • JS help with hScore or hGraph
  • iOS development of hGraph
  • RHex tie-ins

For clinicians and researchers:

  • Make a hScore. Evolve the scoring algorithm
  • What are the top metrics to show (at the "global" hGraph level)? What are the correct groupings and sub metric groupings?
  • What are the chronic disease patterns (the outlines on hGraph) and how do we arrange the metrics to better see those conditions?
  • What are we missing from the everyday diagnostic tool clinicians use? How do we improve hGraph to rock your in-patient encounter experience? Population diagnostic experience?

Core Contributors

Founders/Designers: Involution Studios

Architects/Engineers: iMedia Solutions


hGraph and hMixer are licensed under the Apache-2.0 open source license. You can find more information on the Apache-2.0 license at