PHZLAB: A MATLAB toolbox for analyzing physiological data.

PHZLAB is a MATLAB Toolbox for analyzing physiological data, both peripheral (e.g., EDA, EMG) and neural (i.e., ABR). Really, it is good for any multiple-trial time-series data. It has been designed with the following goals in mind:

• make it easy and fast to try different analyses
• easy presentation-ready figures and stats-ready data frames
• be simple enough to act as an introduction to MATLAB
• be hackable enough so as not to be a hindrance, while still adding value

See the wiki for a proper introduction, quickstart guide, documentation, and example scripts.

Installation in Three Steps

1. System Requirements

PHZLAB requires MATLAB to run. Since PHZLAB uses the table and categorical variable types, it will only run on MATLAB versions R2014a and later. Also for this reason, it won't run in Octave.

Some PHZLAB functions depend on MATLAB Toolboxes. Details about the dependencies can be found in the help section of the functions themselves.

• phzBiopac_readJournalMarkers requires the Statistics and Machine Learning Toolbox.

• phz_filter requires the Signal Processing Toolbox.

2. Download

Manual download. Use the download link in the upper-right corner of this webpage (https://github.com/gabenespoli/phzlab). Unzip the file and put it somewhere where you can easily add it to your MATLAB path (like ~/Documents/MATLAB).

Install using git. From a terminal, move to the directory where you want to put PHZLAB (like ~/Documents/MATLAB) and clone the git repository there. You may need to install git first (e.g., on a Mac you'll need the XCode Command Line Tools, which you can obtain by running xcode-select install in a terminal).

cd ~/Documents/MATLAB
git clone https://github.com/gabenespoli/phzlab

This makes it easy to update PHZLAB:

cd ~/Documents/MATLAB/phzlab
git pull

3. Add to the MATLAB path

Use the MATLAB menu to add the phzlab folder to your path, or type the following in the command window or your scripts:

addpath('~/Documents/MATLAB/phzlab')

Acknowledgements

I would like to thank the SMART Lab (especially Frank Russo, Ella Dubinsky, and Fran Copelli), Alex Andrews, and Carson Pun for their invaluable thoughts, suggestions, inspiration, and feedback.

PHZLAB contains an adapted version of sigstar.

License

This software is covered by the GNU General Public Licence v3.

Contributing

If you are interested in contributing to this project please get in touch! You can email me at gabenespoli@gmail.com