192 related articles for article (PubMed ID: 24111305)
1. Method for removing motion artifacts from fNIRS data using ICA and an acceleration sensor.
Hiroyasu T; Nakamura Y; Yokouchi H
Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():6800-3. PubMed ID: 24111305
[TBL] [Abstract][Full Text] [Related]
2. Motion artifacts in functional near-infrared spectroscopy: a comparison of motion correction techniques applied to real cognitive data.
Brigadoi S; Ceccherini L; Cutini S; Scarpa F; Scatturin P; Selb J; Gagnon L; Boas DA; Cooper RJ
Neuroimage; 2014 Jan; 85 Pt 1(0 1):181-91. PubMed ID: 23639260
[TBL] [Abstract][Full Text] [Related]
3. A kurtosis-based wavelet algorithm for motion artifact correction of fNIRS data.
Chiarelli AM; Maclin EL; Fabiani M; Gratton G
Neuroimage; 2015 May; 112():128-137. PubMed ID: 25747916
[TBL] [Abstract][Full Text] [Related]
4. Wavelet based motion artifact removal for Functional Near Infrared Spectroscopy.
Molavi B; Dumont GA
Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():5-8. PubMed ID: 21096093
[TBL] [Abstract][Full Text] [Related]
5. Wavelet-based motion artifact removal for functional near-infrared spectroscopy.
Molavi B; Dumont GA
Physiol Meas; 2012 Feb; 33(2):259-70. PubMed ID: 22273765
[TBL] [Abstract][Full Text] [Related]
6. Comparison of motion correction techniques applied to functional near-infrared spectroscopy data from children.
Hu XS; Arredondo MM; Gomba M; Confer N; DaSilva AF; Johnson TD; Shalinsky M; Kovelman I
J Biomed Opt; 2015; 20(12):126003. PubMed ID: 26662300
[TBL] [Abstract][Full Text] [Related]
7. Hybrid motion artifact detection and correction approach for functional near-infrared spectroscopy measurements.
Gao L; Wei Y; Wang Y; Wang G; Zhang Q; Zhang J; Chen X; Yan X
J Biomed Opt; 2022 Feb; 27(2):. PubMed ID: 35212200
[TBL] [Abstract][Full Text] [Related]
8. Functional connectivity as revealed by independent component analysis of resting-state fNIRS measurements.
Zhang H; Zhang YJ; Lu CM; Ma SY; Zang YF; Zhu CZ
Neuroimage; 2010 Jul; 51(3):1150-61. PubMed ID: 20211741
[TBL] [Abstract][Full Text] [Related]
9. A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy.
von Lühmann A; Boukouvalas Z; Müller KR; Adalı T
Neuroimage; 2019 Oct; 200():72-88. PubMed ID: 31203024
[TBL] [Abstract][Full Text] [Related]
10. Motion artifact removal for functional near infrared spectroscopy: a comparison of methods.
Robertson FC; Douglas TS; Meintjes EM
IEEE Trans Biomed Eng; 2010 Jun; 57(6):1377-87. PubMed ID: 20172809
[TBL] [Abstract][Full Text] [Related]
11. Improved Motion Artifact Correction in fNIRS Data by Combining Wavelet and Correlation-Based Signal Improvement.
Al-Omairi HR; Fudickar S; Hein A; Rieger JW
Sensors (Basel); 2023 Apr; 23(8):. PubMed ID: 37112320
[TBL] [Abstract][Full Text] [Related]
12. Motion Artifacts Correction from Single-Channel EEG and fNIRS Signals Using Novel Wavelet Packet Decomposition in Combination with Canonical Correlation Analysis.
Hossain MS; Chowdhury MEH; Reaz MBI; Ali SHM; Bakar AAA; Kiranyaz S; Khandakar A; Alhatou M; Habib R; Hossain MM
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590859
[TBL] [Abstract][Full Text] [Related]
13. A methodology for validating artifact removal techniques for fNIRS.
Sweeney KT; Ayaz H; Ward TE; Izzetoglu M; McLoone SF; Onaral B
Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():4943-6. PubMed ID: 22255447
[TBL] [Abstract][Full Text] [Related]
14. Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI.
Pruim RHR; Mennes M; Buitelaar JK; Beckmann CF
Neuroimage; 2015 May; 112():278-287. PubMed ID: 25770990
[TBL] [Abstract][Full Text] [Related]
15. Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis.
Funane T; Atsumori H; Katura T; Obata AN; Sato H; Tanikawa Y; Okada E; Kiguchi M
Neuroimage; 2014 Jan; 85 Pt 1():150-65. PubMed ID: 23439443
[TBL] [Abstract][Full Text] [Related]
16. A Motion Artifact Correction Procedure for fNIRS Signals Based on Wavelet Transform and Infrared Thermography Video Tracking.
Perpetuini D; Cardone D; Filippini C; Chiarelli AM; Merla A
Sensors (Basel); 2021 Jul; 21(15):. PubMed ID: 34372353
[TBL] [Abstract][Full Text] [Related]
17. Statistical analysis of fNIRS data: a comprehensive review.
Tak S; Ye JC
Neuroimage; 2014 Jan; 85 Pt 1():72-91. PubMed ID: 23774396
[TBL] [Abstract][Full Text] [Related]
18. ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data.
Pruim RHR; Mennes M; van Rooij D; Llera A; Buitelaar JK; Beckmann CF
Neuroimage; 2015 May; 112():267-277. PubMed ID: 25770991
[TBL] [Abstract][Full Text] [Related]
19. Hammerstein-Wiener Motion Artifact Correction for Functional Near-Infrared Spectroscopy: A Novel Inertial Measurement Unit-Based Technique.
Al-Omairi HR; Al-Zubaidi A; Fudickar S; Hein A; Rieger JW
Sensors (Basel); 2024 May; 24(10):. PubMed ID: 38794026
[TBL] [Abstract][Full Text] [Related]
20. Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals.
Bauernfeind G; Wriessnegger SC; Daly I; Müller-Putz GR
J Neural Eng; 2014 Oct; 11(5):056010. PubMed ID: 25111822
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
