Processing of EMG signals in order to collect specific Features (specifically IEMG, RMS, WL, WAMP, ENERGY) in the Matlab environment, as shown in the attached paper. Signals must be drawn from datasets that already exist online. The code corresponding to each Feature already exists. There are two goals at work:
1. To create a dataset that will contain the processed EMG signals
2. a dataset that will contain the features.
The order is as follows: Raw EMG Signal -> Preprocessing and Data Segmentation -> Feature Extraction.
The ideal case would be to find data both from healthy individuals, when and from individuals with mobility problems or individuals with spinal cord injury. There is no limitation to a muscle unit, i.e. the signals can be from both hand and leg movements.

The data should concern muscle activity of people with and without a spinal cord problem. Data can be pulled from github, kaggle and other sources like researchgate. I am sending you indicative links:
1. https://www.kaggle.com/datasets/nccvector/electromyography-emg-dataset
2. https://github.com/Suguru55/Wearable_Sensor_Long-term_sEMG_Dataset
The data is not required to be from a specific muscle unit, i.e. one dataset could have data from arm muscles and another from thigh muscles. However, muscle activity data should also be found from people with motor/muscle problems and the same procedure as the rest of the data should be followed.

The data should be entered into matlab, preprocessing should be done [indicatively the signal was band pass filtered using 2nd order Butterworth filter with a cut off frequency of 20-500 Hz and further rectified before segmentation] and a dataset should be created with all processed signals.

Then the feature extraction will be performed.
I hope I helped you.
I am at your disposal for further instructions