FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2982640928> ?p ?o ?g. }

• W2982640928 endingPage "158880" @default.
• W2982640928 startingPage "158872" @default.
• W2982640928 abstract "Electroencephalogram (EEG) is a common tool for medical diagnosis, cognitive research, and managing neurological disorders. However, EEG is usually contaminated with various artifacts, making it difficult to interpret EEG data. In this study, a recursive least square (RLS) notch filter was developed to effectively suppress electrocardiogram (ECG) artifacts from EEG recordings. ECG artifacts were estimated and modeled using the instantaneous frequency of the cardiac cycle. Then it was adaptively estimated using a RLS filter and directly subtracted from contaminated EEG data. Based on the validation measures of improvement of normalized power spectrum (INPS), mean square error (MSE) and information quantity (IQ), the performance of ECG artifacts suppression was compared among the proposed RLS approach, independent component analysis (ICA) and blind deconvolution method under information maximization (Infomax) on simulated and animal experimental data. Simulation data demonstrated that INPS of RLS method (19.75(18.37,20.95) dB) was significantly higher than that of ICA (4.35(3.35,5.41) dB) and Infomax (5.76(4.60,6.88) dB). Meanwhile, MSE of RLS method (0.20(0.08,0.53) μV <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> ) was considerably lower than that of ICA (5.59(2.35,19.79) μV <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> ) and Infomax (3.21(1.01,10.69) μV <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> ). Animal experimental data showed that INPS was 1.76(0.42,9.40) dB for RLS method, which was dramatically higher than that of ICA (0.02(0.00,0.14) dB) and Infomax (0.57(0.08,2.45) dB). The calculated IQ for RLS method (0.331(0.021,0.584)) was relatively lower than that of raw EEG (0.350(0.070,0.586)), ICA (0.350(0.069,0.581)) and Infomax (0.341(0.050,0.585)). The RLS notch filter can effectively eliminate ECG artifacts from EEG and preserve the majority of EEG information with little loss." @default.
• W2982640928 created "2019-11-08" @default.
• W2982640928 creator A5000807319 @default.
• W2982640928 creator A5006126349 @default.
• W2982640928 creator A5046621948 @default.
• W2982640928 creator A5066851632 @default.
• W2982640928 creator A5068741802 @default.
• W2982640928 creator A5078176560 @default.
• W2982640928 date "2019-01-01" @default.
• W2982640928 modified "2023-10-17" @default.
• W2982640928 title "Removal of ECG Artifacts From EEG Using an Effective Recursive Least Square Notch Filter" @default.
• W2982640928 cites W1968076224 @default.
• W2982640928 cites W1969673219 @default.
• W2982640928 cites W1971073682 @default.
• W2982640928 cites W1986711076 @default.
• W2982640928 cites W1988611597 @default.
• W2982640928 cites W1999390833 @default.
• W2982640928 cites W1999542175 @default.
• W2982640928 cites W2002027021 @default.
• W2982640928 cites W2007198984 @default.
• W2982640928 cites W2011957681 @default.
• W2982640928 cites W2033632093 @default.
• W2982640928 cites W2069017697 @default.
• W2982640928 cites W2078637998 @default.
• W2982640928 cites W2110075977 @default.
• W2982640928 cites W2110793950 @default.
• W2982640928 cites W2115300327 @default.
• W2982640928 cites W2125659977 @default.
• W2982640928 cites W2125927307 @default.
• W2982640928 cites W2127950112 @default.
• W2982640928 cites W2128688146 @default.
• W2982640928 cites W2141905629 @default.
• W2982640928 cites W2143815478 @default.
• W2982640928 cites W2145444715 @default.
• W2982640928 cites W2149350404 @default.
• W2982640928 cites W2154821931 @default.
• W2982640928 cites W2161541421 @default.
• W2982640928 cites W2162273778 @default.
• W2982640928 cites W2166306684 @default.
• W2982640928 cites W2170096293 @default.
• W2982640928 cites W2170397555 @default.
• W2982640928 cites W2532428827 @default.
• W2982640928 cites W2546159266 @default.
• W2982640928 cites W2565837874 @default.
• W2982640928 cites W2612143655 @default.
• W2982640928 cites W2799751818 @default.
• W2982640928 cites W4297900197 @default.
• W2982640928 cites W86723067 @default.
• W2982640928 doi "https://doi.org/10.1109/access.2019.2949842" @default.
• W2982640928 hasPublicationYear "2019" @default.
• W2982640928 type Work @default.
• W2982640928 sameAs 2982640928 @default.
• W2982640928 citedByCount "12" @default.
• W2982640928 countsByYear W29826409282021 @default.
• W2982640928 countsByYear W29826409282022 @default.
• W2982640928 countsByYear W29826409282023 @default.
• W2982640928 crossrefType "journal-article" @default.
• W2982640928 hasAuthorship W2982640928A5000807319 @default.
• W2982640928 hasAuthorship W2982640928A5006126349 @default.
• W2982640928 hasAuthorship W2982640928A5046621948 @default.
• W2982640928 hasAuthorship W2982640928A5066851632 @default.
• W2982640928 hasAuthorship W2982640928A5068741802 @default.
• W2982640928 hasAuthorship W2982640928A5078176560 @default.
• W2982640928 hasBestOaLocation W29826409281 @default.
• W2982640928 hasConcept C105795698 @default.
• W2982640928 hasConcept C106131492 @default.
• W2982640928 hasConcept C120317606 @default.
• W2982640928 hasConcept C127162648 @default.
• W2982640928 hasConcept C139945424 @default.
• W2982640928 hasConcept C153180895 @default.
• W2982640928 hasConcept C153402090 @default.
• W2982640928 hasConcept C154945302 @default.
• W2982640928 hasConcept C15744967 @default.
• W2982640928 hasConcept C169760540 @default.
• W2982640928 hasConcept C28490314 @default.
• W2982640928 hasConcept C31972630 @default.
• W2982640928 hasConcept C33923547 @default.
• W2982640928 hasConcept C41008148 @default.
• W2982640928 hasConcept C51432778 @default.
• W2982640928 hasConcept C522805319 @default.
• W2982640928 hasConcept C76155785 @default.
• W2982640928 hasConceptScore W2982640928C105795698 @default.
• W2982640928 hasConceptScore W2982640928C106131492 @default.
• W2982640928 hasConceptScore W2982640928C120317606 @default.
• W2982640928 hasConceptScore W2982640928C127162648 @default.
• W2982640928 hasConceptScore W2982640928C139945424 @default.
• W2982640928 hasConceptScore W2982640928C153180895 @default.
• W2982640928 hasConceptScore W2982640928C153402090 @default.
• W2982640928 hasConceptScore W2982640928C154945302 @default.
• W2982640928 hasConceptScore W2982640928C15744967 @default.
• W2982640928 hasConceptScore W2982640928C169760540 @default.
• W2982640928 hasConceptScore W2982640928C28490314 @default.
• W2982640928 hasConceptScore W2982640928C31972630 @default.
• W2982640928 hasConceptScore W2982640928C33923547 @default.
• W2982640928 hasConceptScore W2982640928C41008148 @default.
• W2982640928 hasConceptScore W2982640928C51432778 @default.
• W2982640928 hasConceptScore W2982640928C522805319 @default.
• W2982640928 hasConceptScore W2982640928C76155785 @default.

• next