Hello, researchers, students, and other signal hobbyists! FeatureFinder is a free MATLAB tool that lets you organize your signals, visually review them with speed and ease, apply filters and normalization, and export meaningful signal features in a ready-to-analyze format.
FEATURE PREVIEW The feature value for the selected file is instantly updated as settings are changed.
FFT VIEWER Quickly and easily view the frequency spectrum of any data file.
PROFILES Store the filenames and settings for each of your experiments.
FILE FINDER Unique file-finding algorithm finds all of your data files in seconds.
CUSTOMIZE Add your own filters in just a few lines of MATLAB code.
CUSTOMIZE Add your own features in just a few lines of MATLAB code.
PROCESS Processing your data differently is as easy as revising the settings and clicking "Process."
EASY BROWSING Scroll through files one-by-one, or hone in using the drop-down menus.
EXPORT DATA Not interested in signal features? Use FeatureFinder solely as a filtering tool with the export buttons.
What makes FeatureFinder really stand out is the option for you to code your own features and filters, allowing unlimited flexibility—you can literally extract any feature that you like from your data. Did we mention that it's free? Check out The Story to find out more!
Are you interested in using FeatureFinder, but aren’t sure if your data is in the right format? Well, FeatureFinder looks for text files that each comprise a single trial of data. If that’s not the case with your data files, then you can use our new step-by-step guides to convert them into this format!
For example, say that you collected data from ten responses to a stimulus for three different subjects. Your data files should look something like this: Sub1Trial1.txt, Sub1Trial2.txt, and so on, all the way to Sub3Trial10.txt.
If your data files aren’t in a text format (e.g., you have “.acq” file extensions), then you’ll need to convert them to text files. Take a look at “Exporting your data” here.
If your data files each contain multiple trials—maybe they contain all trials for each subject (e.g., Sub1.txt, Sub2.txt, and so on)—then you’ll need to split them up. Check out “Splitting your data” here for a step-by-step tutorial.
…And as always, feel free to get it touch if you have any questions.
