ArticlePloS one2013
DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- ICA-SFrontiers in neuroscience · 2026Article
- Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities.NeuroImage · 2023Review
- Methods for motion artifact reduction in online brain-computer interface experiments: a systematic review.Frontiers in human neuroscience · 2023Review
- Pre-Work for the Birth of Driver-Less Scraper (LHD) in the Underground Mine: The Path Tracking Control Based on an LQR Controller and Algorithms Comparison.Sensors (Basel, Switzerland) · 2021Article
- Signaleeg : A practical tool for EEG signal data mining.Neuroinformatics · 2021Article
- Artifact rejection and missing data imputation in cerebral blood flow velocity signals via trace norm minimization.Physiological measurement · 2020Article
- Independent Low-Rank Matrix Analysis-Based Automatic Artifact Reduction Technique Applied to Three BCI Paradigms.Frontiers in human neuroscience · 2020Article
- Improved EOG Artifact Removal Using Wavelet Enhanced Independent Component Analysis.Brain sciences · 2019Article
- An Unsupervised Method for Artefact Removal in EEG Signals.Sensors (Basel, Switzerland) · 2019Article
- Evaluation of an automated pipeline for large-scale EEG spectral analysis: the National Sleep Research Resource.Sleep medicine · 2018Article
- Multi-User Low Intrusive Occupancy Detection.Sensors (Basel, Switzerland) · 2018Article
- Automatic bad channel detection in intracranial electroencephalographic recordings using ensemble machine learning.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2018Article
- Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow.Neuroinformatics · 2017Article
- Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application.Sensors (Basel, Switzerland) · 2016Article
- The PREP pipeline: standardized preprocessing for large-scale EEG analysis.Frontiers in neuroinformatics · 2015Article
- Detecting alpha spindle events in EEG time series using adaptive autoregressive models.BMC neuroscience · 2013Article
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3 authors.
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Abstract
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 developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration.
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