Deep learning for classifing sEMG signals

Requirements

The following packages must be installed:

• python3.5 or greater
• gcc
• Python headers (python3-dev for debian and python3-devel for RedHat)

Installation

Cloning repository

git clone https://github.com/jonDel/emg_mc.git

Installing environment

cd emg_mc
bash install_environ.sh

Activating environment

source emg_mc_venv/bin/activate

Downloading the datasets (takes a while, 22 Gb)

python scripts/datasets_download.py

Checking results from pre-trained sessions

Evaluating model with a test set from a subject

#subject 3, database 3
python scripts/load_results.py 4 database_3
#subject 14, database 1
python scripts/load_results.py 14 database_1

Ploting results for database 1

#subject 10, database 1
python scripts/plot_data.py 10

Running training sessions

Launching tensorboard for visualizing the training process (optional)

tensorboard --logdir=results/logs/ &

Running training for all datasets in all databases

python deepconvlstm/session_run.py

Running training for one entire database

python
>>>from deepconvlstm import session_run
>>>session_run.run_dbtraining('database_1')

Running training for one subject only

python
>>>from deepconvlstm import DeepConvLstm
>>>subject = 10
>>>database = 'database_1'
>>>dcl = DeepConvLstm(subject, database)
>>>dcl.run_training()

Using jupyter notebooks

Launch jupyter

jupyter notebook notebooks/