478 Hits in 9.2 sec

Quality control and assurance in functional near infrared spectroscopy (fNIRS) experimentation

F Orihuela-Espina, D R Leff, D R C James, A W Darzi, G Z Yang
2010 Physics in Medicine and Biology  
Functional near infrared spectroscopy (fNIRS) is a rapidly developing neuroimaging modality for exploring cortical brain behaviour.  ...  For each factor, a detailed description is provided, and previous solutions are reviewed.  ...  Journal of Biomedical Optics 9 Functional optical signal analysis: a software tool for near-infrared spectroscopy data processing incorporating statistical parametric mapping Journal of Biomedical  ... 
doi:10.1088/0031-9155/55/13/009 pmid:20530852 fatcat:ljy3gecy4fb2zkxqrsfzhvstpa

Removing Artifacts From Eeg Signal Using Wavelet Transform and Conventional Filters

Meryem Felja, Asmae Bencheqroune, Mohammed Karim, Ghita Bennis
2021 North atlantic university union: International Journal of Circuits, Systems and Signal Processing  
In literature, there are different techniques for removing artifacts.  ...  This paper proposes and discusses a new EEG de-noising technique, based on a combination of wavelet transforms and conventional filters.  ...  resonance imaging (FMRI ) and functional spectroscopy near infrared spectroscopy (fNIRS) for changes in blood oxygenation level resulting from neural activity [4] . however the most used technique and  ... 
doi:10.46300/9106.2021.15.19 fatcat:x2txmdqvqbawfmtprp7auyur3y

Best practices for fNIRS publications

Meryem A. Yücel, Alexander v. Lühmann, Felix Scholkmann, Judit Gervain, Ippeita Dan, Hasan Ayaz, David Boas, Robert J. Cooper, Joseph Culver, Clare E. Elwell, Adam Eggebrecht, Maria A. Franceschini (+10 others)
2021 Neurophotonics  
The Society for Functional Near-Infrared Spectroscopy has thus been motivated to organize a representative (but not exhaustive) group of leaders in the field to build a consensus on the best practices  ...  The application of functional near-infrared spectroscopy (fNIRS) in the neurosciences has been expanding over the last 40 years.  ...  Motivation Functional near-infrared spectroscopy (fNIRS) is a noninvasive, easy-to-use, and portable brain imaging technology that enables studies of normal brain function and alterations that arise in  ... 
doi:10.1117/1.nph.8.1.012101 pmid:33442557 pmcid:PMC7793571 fatcat:hkcjeyob3fc5vnnetpas4z7aqq

Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis

Alexander von Lühmann, Xinge Li, Klaus-Robert Müller, David A. Boas, Meryem A. Yücel
2019 NeuroImage  
We have recently introduced a new methodological framework for the unsupervised multivariate analysis of fNIRS signals using Blind Source Separation (BSS) methods.  ...  For the robust estimation of evoked brain activity from functional Near Infrared Spectroscopy (fNIRS) signals, it is crucial to reduce nuisance signals from systemic physiology and motion.  ...  To tackle these challenges outside of the GLM, we have recently introduced a new methodological framework for the multivariate analysis of fNIRS signals using Blind Source Separation (BSS), and its application  ... 
doi:10.1016/j.neuroimage.2019.116472 pmid:31870944 pmcid:PMC7703677 fatcat:57enh7uxerdrljetoxwie6xtc4

Removal of Artifacts from EEG Signals: A Review

Xiao Jiang, Gui-Bin Bian, Zean Tian
2019 Sensors  
However, the recorded electrical activity always be contaminated with artifacts and then affect the analysis of EEG signal.  ...  Lastly, a comparative analysis is provided for choosing a suitable methods according to particular application.  ...  More recently, a modified joint blind source separation (JBSS) approach and quadrature regression IVA (q-IVA) provide a more effective artifact removal technique in both time and frequency domain, paving  ... 
doi:10.3390/s19050987 fatcat:aaj7kldei5clrl7j7g7xi66ih4

Assessing Brain–Muscle Connectivity in Human Locomotion through Mobile Brain/Body Imaging: Opportunities, Pitfalls, and Future Directions

Federico Gennaro, Eling D. de Bruin
2018 Frontiers in Public Health  
Recently, statistical methods based on blind source separation revealed potential for resolving this issue, by segregating non-cerebral/artifactual from cerebral sources of activity.  ...  This step marked a new opportunity for the investigation of the brains' role while moving and was tagged mobile brain/body imaging (MoBI).  ...  The interest in the supraspinal behavior during human locomotion has grown in the previous few decades and several studies started using functional near infrared spectroscopy (fNIRS) for the assessment  ... 
doi:10.3389/fpubh.2018.00039 pmid:29535995 pmcid:PMC5834479 fatcat:4paaarsr2jfqxkycj6tpffmduu

Optical imaging and spectroscopy for the study of the human brain: status report

Hasan Ayaz, Wesley B. Baker, Giles Blaney, David A. Boas, Heather Bortfeld, Kenneth Brady, Joshua Brake, Sabrina Brigadoi, Erin M. Buckley, Stefan A. Carp, Robert J. Cooper, Kyle R. Cowdrick (+48 others)
2022 Neurophotonics  
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function.  ...  is needed, and provide an outlook for the future directions.  ...  The Shared Near-Infrared Spectroscopy Format (SNIRF) provides a specification for storing fNIRS measurements.  ... 
doi:10.1117/1.nph.9.s2.s24001 pmid:36052058 pmcid:PMC9424749 fatcat:hxxrydfuzbbbhejblka5fmyw7e

Using the General Linear Model to Improve Performance in fNIRS Single Trial Analysis and Classification: A Perspective

Alexander von Lühmann, Antonio Ortega-Martinez, David A. Boas, Meryem Ayşe Yücel
2020 Frontiers in Human Neuroscience  
Within a decade, single trial analysis of functional Near Infrared Spectroscopy (fNIRS) signals has gained significant momentum, and fNIRS joined the set of modalities frequently used for active and passive  ...  When correctly applied in single trial analysis, e.g., in BCI, this approach can significantly enhance contrast to noise ratio of the brain signal, improve feature separability and ultimately lead to better  ...  Within a decade, single trial analysis of functional Near Infrared Spectroscopy (fNIRS) signals has gained significant momentum, and fNIRS joined the set of modalities frequently used for active and passive  ... 
doi:10.3389/fnhum.2020.00030 pmid:32132909 pmcid:PMC7040364 fatcat:t67jpwxhmbhkjnkmgxcwn5hrqm

Noninvasive BCIs: Multiway Signal-Processing Array Decompositions

A. Cichocki, Y. Washizawa, T. Rutkowski, H. Bakardjian, Anh-Huy Phan, Seungjin Choi, Hyekyoung Lee, Qibin Zhao, Liqing Zhang, Yuanqing Li
2008 Computer  
imaging (fMRI), and near infrared spectroscopy (NIRS).  ...  While BCI research endeavors to create new communication channels for severely handicapped people using their brain signals, recent efforts also have been focused on developing potential applications in  ...  imaging (fMRI), and near infrared spectroscopy (NIRS).  ... 
doi:10.1109/mc.2008.431 fatcat:auvhydbdcnagdehqhjbmxxgnnm

An Intelligent Spelling Framework Based on Brain-Computer Interface

Yosra Abdula, S Abdel-Mageid, R. Ramadan, Afaf Nada, Marwa Elshahed, Sarah Abdulkader
2018 Journal of Scientific Research in Science  
Such framework uses Independent Component Analysis (ICA) and Auto Regressive (AR) for preprocessing and feature extraction respectively.  ...  In this paper, A BCI speller framework based on converting mental activity is presented.  ...  There are many non-invasive techniques for measuring brain responses such as Magnetoencephalogram (MEG), Functional Near Infrared Spectroscopy (FNIRS), Electrocorticogram (ECoG), Functional Magnetic Resonance  ... 
doi:10.21608/jsrs.2018.14043 fatcat:ognrxuzshjdjdddlnt3iaxsadm

Dynamic cortical connectivity alterations associated with Alzheimer's disease: An EEG and fNIRS integration study

Rihui Li, Thinh Nguyen, Thomas Potter, Yingchun Zhang
2019 NeuroImage: Clinical  
This study employs an integrative functional near-infrared spectroscopy (fNIRS) - electroencephalography (EEG) analysis approach to explore dynamic, regional alterations in the AD-linked brain network.  ...  FNIRS-based spatial constraints were used as priors for EEG source localization.  ...  Acknowledgments This work was supported in part by the University of Houston.  ... 
doi:10.1016/j.nicl.2018.101622 pmid:30527906 pmcid:PMC6411655 fatcat:5anknj4flrdpba2i3k37wpuedq

Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis [article]

Pranali Kokate, Sidharth Pancholi, Amit M. Joshi
2021 arXiv   pre-print
Therefore, a novel approach was approached to remove the artifacts using Independent Components Analysis which boosted the performance.  ...  Results were compared with the deep learning framework. In addition to accuracy, Precision, F1-Score, and recall was considered as the performance metrics.  ...  Functional Near-Infrared Spectroscopy (fNIRS) The fNIRS is a noninvasive brain wave collection method that uses near-infrared light to quantify alterations in localised cerebral metabolism while performing  ... 
arXiv:2107.08514v1 fatcat:4aijbhssk5dejehq2uuvx4527e

Line-by-line velocity measurements, an outlier-resistant method for precision velocimetry [article]

Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-Françcois Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons (+5 others)
2022 arXiv   pre-print
In the near-infrared, the LBL provides a framework for m/s-level accuracy in pRV measurements despite the challenges associated with telluric absorption and sky emission lines.  ...  We present a new algorithm for precision radial velocity (pRV) measurements, a line-by-line (LBL) approach designed to handle outlying spectral information in a simple but efficient manner.  ...  Precision spectroscopy in the near-infrared (nIR) is significantly more challenging than in the optical domain for a number of reasons.  ... 
arXiv:2207.13524v1 fatcat:rsgfzqb6s5gk7grkkrqwo2fx7e

Noninvasive Monitoring of Blood Glucose with Raman Spectroscopy

Rishikesh Pandey, Santosh Kumar Paidi, Tulio A. Valdez, Chi Zhang, Nicolas Spegazzini, Ramachandra Rao Dasari, Ishan Barman
2017 Accounts of Chemical Research  
In this Account, we discuss the newly developed array of methodologies that address the key challenges in measuring blood glucose accurately using Raman spectroscopy and unlock new  ...  CONSPECTUS The successful development of a noninvasive blood glucose sensor that can operate reliably over sustained periods of time has been a much sought after but elusive goal in diabetes management  ...  , and Samsung.  ... 
doi:10.1021/acs.accounts.6b00472 pmid:28071894 pmcid:PMC5896772 fatcat:75o5kmolojbm5j64s3ulefftz4

Motion Artifacts Correction from Single-Channel EEG and fNIRS Signals using Novel Wavelet Packet Decomposition in Combination with Canonical Correlation Analysis [article]

Md Shafayet Hossain, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz, Sawal H. M. Ali, Ahmad Ashrif A. Bakar, Serkan Kiranyaz, Amith Khandakar, Mohammed Alhatou, Rumana Habib, Muhammad Maqsud Hossain
2022 arXiv   pre-print
The electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals, highly non-stationary in nature, greatly suffers from motion artifacts while recorded using wearable sensors.  ...  signal to noise ratio (ΔSNR) and ii) Percentage reduction in motion artifacts (η).  ...  Acknowledgments The dataset used in this experiment is kindly shared in the PhysioNet database by Sweeney et al. [32, 33, 63] .  ... 
arXiv:2204.04533v1 fatcat:hxao26ixxfflldyc4aralr6onq
« Previous Showing results 1 — 15 out of 478 results