Cargando…

Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks

Non-invasive Brain-Computer Interfaces (BCI) have demonstrated great promise for neuroprosthetics and assistive devices. Here we aim to investigate methods to combine Electroencephalography (EEG) and functional Near-Infrared Spectroscopy (fNIRS) in an asynchronous Sensory Motor rhythm (SMR)-based BC...

Descripción completa

Detalles Bibliográficos
Autores principales:	Buccino, Alessio Paolo, Keles, Hasan Onur, Omurtag, Ahmet
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2016
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4701662/ https://www.ncbi.nlm.nih.gov/pubmed/26730580 http://dx.doi.org/10.1371/journal.pone.0146610

Ejemplares similares

Measuring Mental Workload with EEG+fNIRS
por: Aghajani, Haleh, et al.
Publicado: (2017)

fNIRS improves seizure detection in multimodal EEG-fNIRS recordings
por: Sirpal, Parikshat, et al.
Publicado: (2019)

Feature Extraction and Classification Methods for Hybrid fNIRS-EEG Brain-Computer Interfaces
por: Hong, Keum-Shik, et al.
Publicado: (2018)

OptEF-BCI: An Optimization-Based Hybrid EEG and fNIRS–Brain Computer Interface
por: Ali, Muhammad Umair, et al.
Publicado: (2023)

Open access dataset integrating EEG and fNIRS during Stroop tasks
por: Chen, Zemeng, et al.
Publicado: (2023)

EEG-fNIRS-based hybrid image construction and classification using CNN-LSTM
por: Mughal, Nabeeha Ehsan, et al.
Publicado: (2022)

Early-stage fusion of EEG and fNIRS improves classification of motor imagery
por: Li, Yang, et al.
Publicado: (2023)

Amplitude of fNIRS Resting-State Global Signal Is Related to EEG Vigilance Measures: A Simultaneous fNIRS and EEG Study
por: Chen, Yuxuan, et al.
Publicado: (2020)

A Computationally Efficient Method for Hybrid EEG-fNIRS BCI Based on the Pearson Correlation
por: Hasan, Mustafa A. H., et al.
Publicado: (2020)

Hybrid fNIRS-EEG based classification of auditory and visual perception processes
por: Putze, Felix, et al.
Publicado: (2014)

Early Detection of Hemodynamic Responses Using EEG: A Hybrid EEG-fNIRS Study
por: Khan, M. Jawad, et al.
Publicado: (2018)

fNIRS Complexity Analysis for the Assessment of Motor Imagery and Mental Arithmetic Tasks
por: Ghouse, Ameer, et al.
Publicado: (2020)

Observation and motor imagery balance tasks evaluation: An fNIRS feasibility study
por: Almulla, Latifah, et al.
Publicado: (2022)

Hybrid EEG-fNIRS BCI Fusion Using Multi-Resolution Singular Value Decomposition (MSVD)
por: Khan, Muhammad Umer, et al.
Publicado: (2020)

fNIRS-based Neurorobotic Interface for gait rehabilitation
por: Khan, Rayyan Azam, et al.
Publicado: (2018)

Wearable, Integrated EEG–fNIRS Technologies: A Review
por: Uchitel, Julie, et al.
Publicado: (2021)

Mutual interaction between motor cortex activation and pain in fibromyalgia: EEG-fNIRS study
por: Gentile, Eleonora, et al.
Publicado: (2020)

Hybrid EEG–fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control
por: Khan, Muhammad Jawad, et al.
Publicado: (2017)

Toward a Hybrid Passive BCI for the Modulation of Sustained Attention Using EEG and fNIRS
por: Karran, Alexander J., et al.
Publicado: (2019)

Multi-Modal Integration of EEG-fNIRS for Brain-Computer Interfaces – Current Limitations and Future Directions
por: Ahn, Sangtae, et al.
Publicado: (2017)

Multimodal assessment of the spatial correspondence between fNIRS and fMRI hemodynamic responses in motor tasks
por: Pereira, João, et al.
Publicado: (2023)

Multimodal Affective State Assessment Using fNIRS + EEG and Spontaneous Facial Expression
por: Sun, Yanjia, et al.
Publicado: (2020)

fNIRS-based brain-computer interfaces: a review
por: Naseer, Noman, et al.
Publicado: (2015)

Comparison of Brain Activation during Motor Imagery and Motor Movement Using fNIRS
por: Batula, Alyssa M., et al.
Publicado: (2017)

Mental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces
por: Banville, Hubert, et al.
Publicado: (2017)

Multiscale Entropy as a New Feature for EEG and fNIRS Analysis
por: Angsuwatanakul, Thanate, et al.
Publicado: (2020)

Editorial: Techniques Advances and Clinical Applications in Fused EEG-fNIRS
por: Yuan, Zhen, et al.
Publicado: (2019)

Development of an Integrated EEG/fNIRS Brain Function Monitoring System
por: Mohamed, Manal, et al.
Publicado: (2021)

An fNIRS Study of Brain Lateralization During Observation and Execution of a Fine Motor Task
por: Khaksari, Kosar, et al.
Publicado: (2022)

Corrigendum: Multi-Modal Integration of EEG-fNIRS for Brain-Computer Interfaces – Current Limitations and Future Directions
por: Ahn, Sangtae, et al.
Publicado: (2021)

An effective classification framework for brain-computer interface system design based on combining of fNIRS and EEG signals
por: Alhudhaif, Adi
Publicado: (2021)

Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review
por: Khan, Haroon, et al.
Publicado: (2021)

The Relationship between Motor Coordination and Imitation: An fNIRS Study
por: Zhao, Wenrui, et al.
Publicado: (2021)

Multisubject “Learning” for Mental Workload Classification Using Concurrent EEG, fNIRS, and Physiological Measures
por: Liu, Yichuan, et al.
Publicado: (2017)

Toward a compact hybrid brain-computer interface (BCI): Performance evaluation of multi-class hybrid EEG-fNIRS BCIs with limited number of channels
por: Kwon, Jinuk, et al.
Publicado: (2020)

fMRI Validation of fNIRS Measurements During a Naturalistic Task
por: Noah, J. Adam, et al.
Publicado: (2015)

Best practices for fNIRS publications
por: Yücel, Meryem A., et al.
Publicado: (2021)

Corrigendum “fNIRS-based brain-computer interfaces: a review”
por: Naseer, Noman, et al.
Publicado: (2015)

Neuronal correlates of spider phobia in a combined fNIRS-EEG study
por: Rosenbaum, David, et al.
Publicado: (2020)

Multimodal Autoencoder Predicts fNIRS Resting State From EEG Signals
por: Sirpal, Parikshat, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_413r0k4gcd3vi9sho8468e2mvr