Signal Labeling

Manual and automated labeling of signal attributes, regions of interest, and points

Use deep learning to accelerate and automate feature labeling.

Apps

Label signal attributes, regions, and points of interest, and extract features

`edfheader`	Create header structure for EDF or EDF+ file (Since R2021a)
`edfinfo`	Get information about EDF/EDF+ file (Since R2020b)
`edfread`	Read data from EDF/EDF+ file (Since R2020b)
`edfwrite`	Create or modify EDF or EDF+ file (Since R2021a)
`paddata`	Pad data by adding elements (Since R2023b)
`resize`	Resize data by adding or removing elements (Since R2023b)
`trimdata`	Trim data by removing elements (Since R2023b)
`signalDatastore`	Datastore for collection of signals (Since R2020a)

`labeledSignalSet`	Create labeled signal set
`signalLabelDefinition`	Create signal label definition
`signalMask`	Modify and convert signal masks and extract signal regions of interest (Since R2020b)
`sigrangebinmask`	Label signal samples with values within a specified range (Since R2023a)
`countlabels`	Count number of unique labels (Since R2021a)
`filenames2labels`	Get list of labels from filenames (Since R2022b)
`folders2labels`	Get list of labels from folder names (Since R2021a)
`splitlabels`	Find indices to split labels according to specified proportions (Since R2021a)

Automate Signal Labeling with Custom Functions (Signal Processing Toolbox)
Use Signal Labeler to locate and label QRS complexes and R peaks of ECG signals.
Label Signal Attributes, Regions of Interest, and Points (Signal Processing Toolbox)
Use Signal Labeler to label attributes, regions, and points of interest in a set of whale songs.
Create Labeled Signal Sets Iteratively with Reduced Human Effort (Signal Processing Toolbox)
Use deep learning to decrease the human effort required to label signals.

Label signals and export data using Signal Labeler to train a deep learning classifier.