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parse emg recording and normalize the voltage

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Is a tool set to help to analyze ElectroMyoGraphy recorded via smart analyzer. For now it is able to normalize The voltage from an Electromyography recorded file (.emt file) and produce a new .emt file with the normalized voltage, this new file can be open in smart analyzer. The second script allow to generate new emt grouped by tracks.


emg_analyzer is not yet registered on PyPI so you need to install it from github. It need at least python 3.6.

For users

python3.6 -m pip install --user git+

For developers

It’s recommended to install emg_analyzer in a virtualenv

python3.6 -m venv emg_env
source emg_env/bin/activate

Then install the project in editable mode

pip install -e git+

quick start



To normalize tracks in emt file. There is to way to normalize tracks.

  • all tracks are considered together to normalize (default)

  • normalize tracks by tracks

emg_norm -v foo.emt

emg_norm -v --by-track foo.emt


emg_group_tracks take several emt files as input and groups tracks base on their names. Creates one .emt file by tracks. for instance:

emg_group_tracks exp{1,2,3}.emt

with inputs

  track_A track_B track_C track_D

  track_B track_A track_D track_D

  track_D track_C track_D track_C

create outputs

    exp1 exp2 exp3

    exp1 exp2 exp3

    exp1 exp2 exp3

    exp1 exp2 exp3

**Note:** you can pipe the 2 methods


    emg_group_tracks exp{1,2,3}.emt | emg_norm -v

create outputs:

track\_A.emt , track\_B.emt, track\_C.emt, track\_D.emt,
track\_A\_norm.emt , track\_B\_norm.emt, track\_C\_norm.emt,


We encourage contributions, bug report, enhancement …

But before to do that we encourage to read the contributing guide.

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emg_analyzer-0.1.tar.gz (18.3 kB view hashes)

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