ArticleRoyal Society open science2017
Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis.
Article in Royal Society open science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Noise-Assisted Multivariate EMD-Based Mean-Phase Coherence Analysis to Evaluate Phase-Synchrony Dynamics in Epilepsy Patients.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2018Article
- Survival and weak chaos.Royal Society open science · 2018Article
- Generalizability of High Frequency Oscillation Evaluations in the Ripple Band.Frontiers in neurology · 2018Article
- Progress and Remaining Challenges in the Application of High Frequency Oscillations as Biomarkers of Epileptic Brain.Current opinion in biomedical engineering · 2017Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high-frequency oscillations (HFOs) from a big database of rat electroencephalogram recordings. We find a striking phenomenon: HFOs exhibit on-off intermittency that can be quantified by algebraic scaling laws. Our framework can be generalized to big data-related problems in other fields such as large-scale sensor data and seismic data analysis.
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Registered trials
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