FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2952560166> ?p ?o ?g. }

• W2952560166 endingPage "88" @default.
• W2952560166 startingPage "72" @default.
• W2952560166 abstract "In the analysis of functional Near-Infrared Spectroscopy (fNIRS) signals from real-world scenarios, artifact rejection is essential. However, currently there exists no gold-standard. Although a plenitude of methodological approaches implicitly assume the presence of latent processes in the signals, elaborate Blind-Source-Separation methods have rarely been applied. A reason are challenging characteristics such as Non-instantaneous and non-constant coupling, correlated noise and statistical dependencies between signal components. We present a novel suitable BSS framework that tackles these issues by incorporating A) Independent Component Analysis methods that exploit both higher order statistics and sample dependency, B) multimodality, i.e., fNIRS with accelerometer signals, and C) Canonical-Correlation Analysis with temporal embedding. This enables analysis of signal components and rejection of motion-induced physiological hemodynamic artifacts that would otherwise be hard to identify. We implement a method for Blind Source Separation and Accelerometer based Artifact Rejection and Detection (BLISSA2RD). It allows the analysis of a novel n-back based cognitive workload paradigm in freely moving subjects, that is also presented in this manuscript. We evaluate on the corresponding data set and simulated ground truth data, making use of metrics based on 1st and 2nd order statistics and SNR and compare with three established methods: PCA, Spline and Wavelet-based artifact removal. Across 17 subjects, the method is shown to reduce movement induced artifacts by up to two orders of magnitude, improves the SNR of continuous hemodynamic signals in single channels by up to 10dB, and significantly outperforms conventional methods in the extraction of simulated Hemodynamic Response Functions from strongly contaminated data. The framework and methods presented can serve as an introduction to a new type of multivariate methods for the analysis of fNIRS signals and as a blueprint for artifact rejection in complex environments beyond the applied paradigm." @default.
• W2952560166 created "2019-06-27" @default.
• W2952560166 creator A5006915006 @default.
• W2952560166 creator A5060798483 @default.
• W2952560166 creator A5063086487 @default.
• W2952560166 creator A5082698816 @default.
• W2952560166 date "2019-10-01" @default.
• W2952560166 modified "2023-10-16" @default.
• W2952560166 title "A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy" @default.
• W2952560166 cites W1513100438 @default.
• W2952560166 cites W1555603176 @default.
• W2952560166 cites W1822143055 @default.
• W2952560166 cites W1967419852 @default.
• W2952560166 cites W1980786684 @default.
• W2952560166 cites W1988567261 @default.
• W2952560166 cites W1989053419 @default.
• W2952560166 cites W1989784044 @default.
• W2952560166 cites W1991410152 @default.
• W2952560166 cites W1996548734 @default.
• W2952560166 cites W1996776986 @default.
• W2952560166 cites W1999340799 @default.
• W2952560166 cites W2002994039 @default.
• W2952560166 cites W2004995977 @default.
• W2952560166 cites W2007884967 @default.
• W2952560166 cites W2009070933 @default.
• W2952560166 cites W2009118090 @default.
• W2952560166 cites W2011402106 @default.
• W2952560166 cites W2020157147 @default.
• W2952560166 cites W2025564775 @default.
• W2952560166 cites W2029802912 @default.
• W2952560166 cites W2034291876 @default.
• W2952560166 cites W2047401359 @default.
• W2952560166 cites W2065346482 @default.
• W2952560166 cites W2069767403 @default.
• W2952560166 cites W2075606751 @default.
• W2952560166 cites W2082207932 @default.
• W2952560166 cites W2087538899 @default.
• W2952560166 cites W2092890379 @default.
• W2952560166 cites W2099051993 @default.
• W2952560166 cites W2099119042 @default.
• W2952560166 cites W2102771656 @default.
• W2952560166 cites W2103386389 @default.
• W2952560166 cites W2108384452 @default.
• W2952560166 cites W2108489616 @default.
• W2952560166 cites W2111692383 @default.
• W2952560166 cites W2120720467 @default.
• W2952560166 cites W2125628414 @default.
• W2952560166 cites W2130603606 @default.
• W2952560166 cites W2136284422 @default.
• W2952560166 cites W2137523819 @default.
• W2952560166 cites W2138023925 @default.
• W2952560166 cites W2141224535 @default.
• W2952560166 cites W2141250485 @default.
• W2952560166 cites W2143221170 @default.
• W2952560166 cites W2147700873 @default.
• W2952560166 cites W2148640263 @default.
• W2952560166 cites W2148895235 @default.
• W2952560166 cites W2160339809 @default.
• W2952560166 cites W2169264770 @default.
• W2952560166 cites W2172808202 @default.
• W2952560166 cites W2292302374 @default.
• W2952560166 cites W2552578398 @default.
• W2952560166 cites W2606574754 @default.
• W2952560166 cites W2735317774 @default.
• W2952560166 cites W2737346303 @default.
• W2952560166 cites W2745914289 @default.
• W2952560166 cites W4237723258 @default.
• W2952560166 cites W4297832436 @default.
• W2952560166 doi "https://doi.org/10.1016/j.neuroimage.2019.06.021" @default.
• W2952560166 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31203024" @default.
• W2952560166 hasPublicationYear "2019" @default.
• W2952560166 type Work @default.
• W2952560166 sameAs 2952560166 @default.
• W2952560166 citedByCount "34" @default.
• W2952560166 countsByYear W29525601662020 @default.
• W2952560166 countsByYear W29525601662021 @default.
• W2952560166 countsByYear W29525601662022 @default.
• W2952560166 countsByYear W29525601662023 @default.
• W2952560166 crossrefType "journal-article" @default.
• W2952560166 hasAuthorship W2952560166A5006915006 @default.
• W2952560166 hasAuthorship W2952560166A5060798483 @default.
• W2952560166 hasAuthorship W2952560166A5063086487 @default.
• W2952560166 hasAuthorship W2952560166A5082698816 @default.
• W2952560166 hasBestOaLocation W29525601661 @default.
• W2952560166 hasConcept C104267543 @default.
• W2952560166 hasConcept C120317606 @default.
• W2952560166 hasConcept C127162648 @default.
• W2952560166 hasConcept C130796691 @default.
• W2952560166 hasConcept C153180895 @default.
• W2952560166 hasConcept C154945302 @default.
• W2952560166 hasConcept C169760540 @default.
• W2952560166 hasConcept C169900460 @default.
• W2952560166 hasConcept C199360897 @default.
• W2952560166 hasConcept C2779010991 @default.
• W2952560166 hasConcept C2779843651 @default.
• W2952560166 hasConcept C2781195155 @default.
• W2952560166 hasConcept C28490314 @default.
• W2952560166 hasConcept C31258907 @default.

• next