TEAP is a Matlab/Octave toolbox for emotion analysis using physiological signals.
Unlike others, TEAP is
free,
comprehensive and
easy to setup.
No need to buy complex software any more. TEAP is free, and works on Matlab and Octave. Now, physiological signal analysis is at the reach of everybody. TEAP provides simple functions for signal analysis thus making it easy to use; no need to know which type of filter to apply to an EEG signal: by default TEAP will provide one.
Need to analyse emotions from signals acquired from physiological signals ?.
TEAP makes that easy for you by providing an all-in-one toolbox you can
simply use to compute your results.
Currently, TEAP supports the following signals:
In general, TEAP's algorithms are documented and were inspired from
published and reviewed algorithms. No need to worry about which
arguments to give to a zerophase FIR filter
: TEAP does
that for you.
1 %Before all, load TEAP 2 addpath(genpath('../../../')) 3 4 %Then, we load some data: 5 data = csvread('GSR_example.csv'); 6 data = data'; %put in horizontal form 7 8 9 %Create the signal, the sampling freq of the signal we have is 1024Hz 10 signal = GSR_aqn_variable(data, 1024); 11 12 %Clean the signal a bit 13 signal = GSR_filter_basic(signal); 14 15 %And compute the features: 16 [nbPeaks ampPeaks riseTime posPeaks] = GSR_feat_peaks(signal);
18 %Show the signal 19 Signal_plot(signal); 20 21 %As now the axis are in seconds, we have to use this function to plot the points 22 rawSig = Signal__get_raw(signal); 23 Signal_plot_pts(signal, posPeaks, rawSig(posPeaks), 'r*'); 24 %Note that we didn't had to 'hold on': the function does-it itself.
27 %Take a part of a signal, between 41 and 85 seconds 28 figure; 29 truncated = Signal__get_window(signal, 41, 85); 30 Signal_plot(truncated); 31 32 [nbPeaks ampPeaks riseTime posPeaks] = GSR_feat_peaks(truncated); 33 rawSig = Signal__get_raw(truncated); 34 Signal_plot_pts(truncated, posPeaks, rawSig(posPeaks), 'r*');
If you know git, you can simply:
git clone https://github.com/Gijom/TEAP.git
You can also simply go to:
https://github.com/Gijom/TEAP/archive/master.zip
TEAP's documentation is simply and freely available here. It is generated using Doxygen and can thus be obtained from the source code.