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Robbins, Kay A.
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overview My research focuses on modeling, visualization, analysis, and management of multimedia data sets in three major application areas: neuroinformatics, bioinformatics, and medical informatics. Our group is currently developing algorithms and tools for automated annotation and retrieval of EEG and other signals based on content, as well as tools to detect enrichment of co-occurrences of events and signal patterns. This problem domain shares many characteristics with problems in bioinformatics and in the mining of medical information in general --- the significant variation among and within individuals, the variety and non-uniformity of information available for an individual under any particular conditions, and the unique and complex mosaic of environmental factors that might contribute to a particular response. We seek to design approaches that are applicable and accessible to researchers in a variety of areas.
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Concept Electroencephalography
Academic Article DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.
Academic Article Detection and classification of subject-generated artifacts in EEG signals using autoregressive models.
Academic Article Characterization and robust classification of EEG signal from image RSVP events with independent time-frequency features.
Academic Article Classification of imperfectly time-locked image RSVP events with EEG device.
Academic Article Detecting alpha spindle events in EEG time series using adaptive autoregressive models.
Academic Article A Framework for Content-based Retrieval of EEG with Applications to Neuroscience and Beyond.
Academic Article The PREP pipeline: standardized preprocessing for large-scale EEG analysis.
Academic Article Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach.
Academic Article Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG.
Academic Article PWC-ICA: A Method for Stationary Ordered Blind Source Separation with Application to EEG.
Academic Article BLASST: Band Limited Atomic Sampling With Spectral Tuning With Applications to Utility Line Noise Filtering.
Academic Article BLINKER: Automated Extraction of Ocular Indices from EEG Enabling Large-Scale Analysis.
Academic Article EEG-Annotate: Automated identification and labeling of events in continuous signals with applications to EEG.
Academic Article An 18-subject EEG data collection using a visual-oddball task, designed for benchmarking algorithms and headset performance comparisons.
Academic Article Automated EEG mega-analysis II: Cognitive aspects of event related features.
Academic Article How Sensitive Are EEG Results to Preprocessing Methods: A Benchmarking Study.
Academic Article Capturing the nature of events and event context using hierarchical event descriptors (HED).
Academic Article Propagating waves mediate information transfer in the motor cortex.
Academic Article Automated EEG mega-analysis I: Spectral and amplitude characteristics across studies.
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  • Electroencephalography
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