Getting started with EMGFlow

Download

EMGFlow can be installed from PyPI:

pip install EMGFlow

Quick example

EMGFlow extracts a comprehensive set of 32 statistical features from sEMG signals, achieved with only a few lines of code:

import EMGFlow

# Get path dictionary
path_names = EMGFlow.make_paths()

# Load sample data
EMGFlow.make_sample_data(path_names)

# Preprocess signals
EMGFlow.clean_signals(path_names, sampling_rate=2000)

# Plot data on the "EMG_zyg" column
EMGFlow.plot_dashboard(path_names, 'EMG_zyg', 'mV')

# Extract features and save results in "Features.csv" in feature_path
df = EMGFlow.extract_features(path_names, sampling_rate=2000)

Input data format

EMGFlow accepts data in plaintext .CSV file format. Files should have the following format:

• Row 1 - Column headers
• Col 1 - Labelled Time, and contains the timestamps of sampled data
• Col 2:n - Assumed to be sEMG or related signal data.

Time	Data-1	...	Data-n
0	0	...	-.04
0.1	0.32	...	.9
...	...	...	...
20.0	-1.2	...	1.7

Note, the Time column can be omitted when the sample rate is known.

EMGFlow Pipeline Processing Steps