Quantitative Electromyography and Time Series Analysis (QEMG)
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There are a number of software tools available through this lab. We are happy to share software with researchers around the world. In order to track who is using the software, we ask you to contact us by email: dqemg@qemg.org

Depending on the software, it is provided in either Python source form, C/C++ form, or as an executable file for Windows. Source code is compatible with all of the following operating systems: Linux, Mac OSX, Free BSD, Microsoft Windows.

Pattern Analysis Software

The most recent version of the pattern discovery association mining algorithm described in this 2007 paper is available (C/C++). This algorithm searches a data set for patterns that are statistically unlikely to be produced by random association, according the Haberman (1975) residual. It operates on tabular data in text (CSV) files and can provide a confidence of association for each classification made on the resulting data.

Electromyographic Analysis

A muscle simulator that produces EMG signals of the sort observed at indwelling electrodes is available (C/C++). This software produces signals as waveform files in several formats, which can then be analyzed to exercise decomposition algorithms or similar tools. A “gold standard” decomposition based on the modelled muscle physiology is included with each signal.

A muscle visualization program (Python) allows inspection of the layout and connectivity of the muscles produced by the simulator.

The DQEMG (Decomposition based Quantative Electromyograph) program is available. This is suitable for decomposing contractions obtained from real muscles, and provides significant insight into muscle structure and function. The likely audience for this are interested clinicians, neurophysiologists, and related researchers.