parse emg recording and normalize the voltage
Project description
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.
Installation
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+https://github.com/freeh4cker/emg_analyzer.git#egg=emg_analyzer
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+https://github.com/freeh4cker/emg_analyzer.git#egg=emg_analyzer
quick start
- construction:
emg_norm
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
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
exp1.emt track_A track_B track_C track_D exp2.emt track_B track_A track_D track_D exp3.emt track_D track_C track_D track_C
create outputs
track_A.emt exp1 exp2 exp3 track_B.emt exp1 exp2 exp3 track_C.emt exp1 exp2 exp3 track_D.emt 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, track\_D\_norm.emt
Contributing
We encourage contributions, bug report, enhancement …
But before to do that we encourage to read the contributing guide.
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