DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.
Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have devel...
Enregistré dans:
Auteurs principaux: | Vernon Lawhern, W David Hairston, Kay Robbins |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Public Library of Science (PLoS)
2013
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/0f14a9067d7b4a639589b0d82c992d23 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Detection of Mental Stress through EEG Signal in Virtual Reality Environment
par: Dorota Kamińska, et autres
Publié: (2021) -
Structural change detection in ordinal time series.
par: Fuxiao Li, et autres
Publié: (2021) -
A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
par: Devin O’Kelly, et autres
Publié: (2021) -
MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
par: Alessandro Montalto, et autres
Publié: (2014) -
Detecting Phase-Synchrony Connectivity Anomalies in EEG Signals. Application to Dyslexia Diagnosis
par: Marco A. Formoso, et autres
Publié: (2021)