keyword
https://read.qxmd.com/read/35450498/the-clinical-effects-of-brain-computer-interface-with-robot-on-upper-limb-function-for-post-stroke-rehabilitation-a-meta-analysis-and-systematic-review
#21
JOURNAL ARTICLE
Hao Qu, Feixiang Zeng, Yongbin Tang, Bin Shi, Zhijun Wang, Xiaokai Chen, Jing Wang
PURPOSE: Many recent clinical studies have suggested that the combination of brain-computer interfaces (BCIs) can induce neurological recovery and improvement in motor function. In this review, we performed a systematic review and meta-analysis to evaluate the clinical effects of BCI-robot systems. METHODS: The articles published from January 2010 to December 2020 have been searched by using the databases (EMBASE, PubMed, CINAHL, EBSCO, Web of Science and manual search)...
January 2024: Disability and Rehabilitation. Assistive Technology
https://read.qxmd.com/read/34956344/a-review-of-eeg-and-fmri-measuring-aesthetic-processing-in-visual-user-experience-research
#22
REVIEW
Zhepeng Rui, Zhenyu Gu
In human-computer interaction, the visual interaction of user experience (UX) and user interface (UI) plays an important role in enriching the quality of daily life. The purpose of our study analyzes the use of brain-computer interface (BCI), wearable technology, and functional magnetic resonance imaging (fMRI) to explore the aesthetic processing of visual neural response to UI and UX designs. Specifically, this review aims to understand neuroaesthetic processing knowledge, aesthetic appreciation models, and the ways in which visual brain studies can improve the quality of current and future UI and UX designs...
2021: Computational Intelligence and Neuroscience
https://read.qxmd.com/read/34790157/research-on-the-emotions-based-on-brain-computer-technology-a-bibliometric-analysis-and-research-agenda
#23
REVIEW
Wei Yan, Xiaoju Liu, Biaoan Shan, Xiangxian Zhang, Yi Pu
This study conducts a scientific analysis of 249 literature on the application of brain-computer technology in emotion research. We find that existing researches mainly focus on engineering, computer science, neurosciences neurology and psychology. PR China, United States, and Germany have the largest number of publications. Authors can be divided into four groups: real-time functional magnetic resonance imaging (rtfMRI) research group, brain-computer interface (BCI) impact factors analysis group, brain-computer music interfacing (BCMI) group, and user status research group...
2021: Frontiers in Psychology
https://read.qxmd.com/read/34710584/extremely-fast-prf-mapping-for-real-time-applications
#24
JOURNAL ARTICLE
Salil Bhat, Michael Lührs, Rainer Goebel, Mario Senden
Population receptive field (pRF) mapping is a popular tool in computational neuroimaging that allows for the investigation of receptive field properties, their topography and interrelations in health and disease. Furthermore, the possibility to invert population receptive fields provides a decoding model for constructing stimuli from observed cortical activation patterns. This has been suggested to pave the road towards pRF-based brain-computer interface (BCI) communication systems, which would be able to directly decode internally visualized letters from topographically organized brain activity...
October 25, 2021: NeuroImage
https://read.qxmd.com/read/34646112/brain-computer-interface-training-with-functional-electrical-stimulation-facilitating-changes-in-interhemispheric-functional-connectivity-and-motor-outcomes-post-stroke
#25
JOURNAL ARTICLE
Anita M Sinha, Veena A Nair, Vivek Prabhakaran
While most survivors of stroke experience some spontaneous recovery and receive treatment in the subacute setting, they are often left with persistent impairments in upper limb sensorimotor function which impact autonomy in daily life. Brain-Computer Interface (BCI) technology has shown promise as a form of rehabilitation that can facilitate motor recovery after stroke, however, we have a limited understanding of the changes in functional connectivity and behavioral outcomes associated with its use. Here, we investigate the effects of EEG-based BCI intervention with functional electrical stimulation (FES) on resting-state functional connectivity (rsFC) and motor outcomes in stroke recovery...
2021: Frontiers in Neuroscience
https://read.qxmd.com/read/34587606/weighted-neurofeedback-facilitates-greater-self-regulation-of-functional-connectivity-between-the-primary-motor-area-and-cerebellum
#26
JOURNAL ARTICLE
Patricia Vargas, Ranganatha Sitaram, Pradyumna Sepúlveda, Cristian Montalba, Mohit Rana, Rafael Torres, Cristián Tejos, Sergio Ruiz
Objective. Brain-computer interface (BCI) is a tool that can be used to train brain self-regulation and influence specific activity patterns, including functional connectivity, through neurofeedback. The functional connectivity of the primary motor area (M1) and cerebellum play a critical role in motor recovery after a brain injury, such as stroke. The objective of this study was to determine the feasibility of achieving control of the functional connectivity between M1 and the cerebellum in healthy subjects...
October 14, 2021: Journal of Neural Engineering
https://read.qxmd.com/read/34507098/mri-magnetic-compatible-electrical-neural-interface-from-materials-to-application
#27
REVIEW
Yuan Zhang, Song Le, Hui Li, Bowen Ji, Ming-Hao Wang, Jin Tao, Jing-Qiu Liang, Xiao-Yong Zhang, Xiao-Yang Kang
Neural electrical interfaces are important tools for local neural stimulation and recording, which potentially have wide application in the diagnosis and treatment of neural diseases, as well as in the transmission of neural activity for brain-computer interface (BCI) systems. At the same time, magnetic resonance imaging (MRI) is one of the effective and non-invasive techniques for recording whole-brain signals, providing details of brain structures and also activation pattern maps. Simultaneous recording of extracellular neural signals and MRI combines two expressions of the same neural activity and is believed to be of great importance for the understanding of brain function...
September 1, 2021: Biosensors & Bioelectronics
https://read.qxmd.com/read/34358704/evoking-highly-focal-percepts-in-the-fingertips-through-targeted-stimulation-of-sulcal-regions-of-the-brain-for-sensory-restoration
#28
JOURNAL ARTICLE
Santosh Chandrasekaran, Stephan Bickel, Jose L Herrero, Joo-Won Kim, Noah Markowitz, Elizabeth Espinal, Nikunj A Bhagat, Richard Ramdeo, Junqian Xu, Matthew F Glasser, Chad E Bouton, Ashesh D Mehta
BACKGROUND: Paralysis and neuropathy, affecting millions of people worldwide, can be accompanied by significant loss of somatosensation. With tactile sensation being central to achieving dexterous movement, brain-computer interface (BCI) researchers have used intracortical and cortical surface electrical stimulation to restore somatotopically-relevant sensation to the hand. However, these approaches are restricted to stimulating the gyral areas of the brain. Since representation of distal regions of the hand extends into the sulcal regions of human primary somatosensory cortex (S1), it has been challenging to evoke sensory percepts localized to the fingertips...
August 3, 2021: Brain Stimulation
https://read.qxmd.com/read/34335210/brain-functional-changes-in-stroke-following-rehabilitation-using-brain-computer-interface-assisted-motor-imagery-with-and-without-tdcs-a-pilot-study
#29
JOURNAL ARTICLE
Mengjiao Hu, Hsiao-Ju Cheng, Fang Ji, Joanna Su Xian Chong, Zhongkang Lu, Weimin Huang, Kai Keng Ang, Kok Soon Phua, Kai-Hsiang Chuang, Xudong Jiang, Effie Chew, Cuntai Guan, Juan Helen Zhou
Brain-computer interface-assisted motor imagery (MI-BCI) or transcranial direct current stimulation (tDCS) has been proven effective in post-stroke motor function enhancement, yet whether the combination of MI-BCI and tDCS may further benefit the rehabilitation of motor functions remains unknown. This study investigated brain functional activity and connectivity changes after a 2 week MI-BCI and tDCS combined intervention in 19 chronic subcortical stroke patients. Patients were randomized into MI-BCI with tDCS group and MI-BCI only group who underwent 10 sessions of 20 min real or sham tDCS followed by 1 h MI-BCI training with robotic feedback...
2021: Frontiers in Human Neuroscience
https://read.qxmd.com/read/34155480/guiding-functional-near-infrared-spectroscopy-optode-layout-design-using-individual-f-mri-data-effects-on-signal-strength
#30
JOURNAL ARTICLE
Amaia Benitez-Andonegui, Michael Lührs, Laurien Nagels-Coune, Dimo Ivanov, Rainer Goebel, Bettina Sorger
Significance: Designing optode layouts is an essential step for functional near-infrared spectroscopy (fNIRS) experiments as the quality of the measured signal and the sensitivity to cortical regions-of-interest depend on how optodes are arranged on the scalp. This becomes particularly relevant for fNIRS-based brain-computer interfaces (BCIs), where developing robust systems with few optodes is crucial for clinical applications. Aim: Available resources often dictate the approach researchers use for optode-layout design...
April 2021: Neurophotonics
https://read.qxmd.com/read/34039029/can-children-with-perinatal-stroke-use-a-simple-brain-computer-interface
#31
JOURNAL ARTICLE
Zeanna Jadavji, Jack Zhang, Brett Paffrath, Ephrem Zewdie, Adam Kirton
BACKGROUND AND PURPOSE: Perinatal stroke is the leading cause of hemiparetic cerebral palsy resulting in lifelong disability for millions of people worldwide. Options for motor rehabilitation are limited, especially for the most severely affected children. Brain computer interfaces (BCIs) sample brain activity to allow users to control external devices. Functional electrical stimulation enhances motor recovery after stroke, and BCI-activated functional electrical stimulation was recently shown to improve upper extremity function in adult stroke...
May 27, 2021: Stroke; a Journal of Cerebral Circulation
https://read.qxmd.com/read/34007777/improved-mild-closed-head-traumatic-brain-injury-outcomes-with-a-brain-computer-interface-amplified-cognitive-remediation-training
#32
JOURNAL ARTICLE
Curtis T Cripe, Rebecca Cooper, Peter Mikulecky, Jason H Huang, Dallas C Hack
This study is a retrospective chart review of 200 clients who participated in a non-verbal restorative cognitive remediation training (rCRT) program between 2012 and 2020. Each client participated in the program for about 16 weeks, and the study as a whole occurred over a five-year period. The program was applied to effect proper neural functional remodeling needed to support resilient, flexible, and adaptable behaviors after encountering a mild closed head traumatic brain injury (mTBI). The rCRT program focused on improving functional performance in executive cognitive control networks as defined by fMRI studies...
May 12, 2021: Curēus
https://read.qxmd.com/read/33956845/combined-real-time-fmri-and-real-time-fnirs-brain-computer-interface-bci-training-of-volitional-wrist-extension-after-stroke-a-case-series-pilot-study
#33
JOURNAL ARTICLE
Avi K Matarasso, Jake D Rieke, Keith White, M Minhal Yusufali, Janis J Daly
OBJECTIVE: Pilot testing of real time functional magnetic resonance imaging (rt-fMRI) and real time functional near infrared spectroscopy (rt-fNIRS) as brain computer interface (BCI) neural feedback systems combined with motor learning for motor recovery in chronic severely impaired stroke survivors. APPROACH: We enrolled a four-case series and administered three sequential rt-fMRI and ten rt-fNIRS neural feedback sessions interleaved with motor learning sessions...
2021: PloS One
https://read.qxmd.com/read/33780916/decoding-of-semantic-categories-of-imagined-concepts-of-animals-and-tools-in-fnirs
#34
JOURNAL ARTICLE
Milan Rybář, Riccardo Poli, Ian Daly
OBJECTIVE: Semantic decoding refers to the identification of semantic concepts from recordings of an individual's brain activity. It has been previously reported in fMRI and EEG. We investigate whether semantic decoding is possible with functional near-infrared spectroscopy (fNIRS). Specifically, we attempt to differentiate between the semantic categories of animals and tools. We also identify suitable mental tasks for potential brain-computer interface (BCI) applications. APPROACH: We explore the feasibility of a silent naming task, for the first time in fNIRS, and propose three novel intuitive mental tasks based on imagining concepts using three sensory modalities: visual, auditory, and tactile...
March 29, 2021: Journal of Neural Engineering
https://read.qxmd.com/read/33545580/optical-brain-imaging-and-its-application-to-neurofeedback
#35
JOURNAL ARTICLE
Surjo R Soekadar, Simon H Kohl, Masahito Mihara, Alexander von Lühmann
Besides passive recording of brain electric or magnetic activity, also non-ionizing electromagnetic or optical radiation can be used for real-time brain imaging. Here, changes in the radiation's absorption or scattering allow for continuous in vivo assessment of regional neurometabolic and neurovascular activity. Besides magnetic resonance imaging (MRI), over the last years, also functional near-infrared spectroscopy (fNIRS) was successfully established in real-time metabolic brain imaging. In contrast to MRI, fNIRS is portable and can be applied at bedside or in everyday life environments, e...
January 26, 2021: NeuroImage: Clinical
https://read.qxmd.com/read/33418846/bci-training-effects-on-chronic-stroke-correlate-with-functional-reorganization-in-motor-related-regions-a-concurrent-eeg-and-fmri-study
#36
JOURNAL ARTICLE
Kai Yuan, Cheng Chen, Xin Wang, Winnie Chiu-Wing Chu, Raymond Kai-Yu Tong
Brain-computer interface (BCI)-guided robot-assisted training strategy has been increasingly applied to stroke rehabilitation, while few studies have investigated the neuroplasticity change and functional reorganization after intervention from multimodality neuroimaging perspective. The present study aims to investigate the hemodynamic and electrophysical changes induced by BCI training using functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) respectively, as well as the relationship between the neurological changes and motor function improvement...
January 6, 2021: Brain Sciences
https://read.qxmd.com/read/33418549/functional-mri-based-simulations-of-ecog-grid-configurations-for-optimal-measurement-of-spatially-distributed-hand-gesture-information
#37
JOURNAL ARTICLE
Max Alexander van den Boom, Kai Miller, Nick Ramsey, Dora Hermes
Objective In electrocorticography (ECoG), the physical characteristics of the electrode grid determine which aspect of the neurophysiology is measured. For particular cases, the ECoG grid may be tailored to capture specific features, such as in the development and use of brain-computer-interfaces (BCI). Neural representations of hand movement are increasingly used to control ECoG based BCIs. However, it remains unclear which grid configurations are the most optimal to capture the dynamics of hand gesture information...
January 8, 2021: Journal of Neural Engineering
https://read.qxmd.com/read/33386032/robotic-treatment-of-the-upper-limb-in-chronic-stroke-and-cerebral-neuroplasticity-a-systematic-review
#38
F Bressi, M Bravi, B Campagnola, D Bruno, A Marzolla, F Santacaterina, S Miccinilli, S Sterzi
Stroke is the second cause of mortality and the third cause of long-term disability worldwide. Deficits in upper limb (UL) capacity persist at 6 months post-stroke in 30-66% of hemiplegic stroke patients with major limitations in activity of daily living (ADL), thus making the recovery of paretic UL function the main rehabilitation goal. Robotic rehabilitation plays a crucial role since it allows to perform a repetitive, intensive, and task-oriented treatment, adaptable to the patients' residual abilities, necessary to facilitate recovery and the rehabilitation of the paretic UL...
September 2020: Journal of Biological Regulators and Homeostatic Agents
https://read.qxmd.com/read/33281590/editorial-towards-expanded-utility-of-real-time-fmri-neurofeedback-in-clinical-applications
#39
EDITORIAL
Javier Gonzalez-Castillo, Michal Ramot, Reza Momenan
No abstract text is available yet for this article.
2020: Frontiers in Human Neuroscience
https://read.qxmd.com/read/32799771/changes-in-electroencephalography-complexity-and-functional-magnetic-resonance-imaging-connectivity-following-robotic-hand-training-in-chronic-stroke
#40
JOURNAL ARTICLE
Ahsan Khan, Cheng Chen, Kai Yuan, Xin Wang, Prabhav Mehra, Yunmeng Liu, Kai-Yu Tong
In recent years, robotic training has been utilized for recovery of motor control in patients with motor deficits. Along with clinical assessment, electrical patterns in the brain have emerged as a marker for studying changes in the brain associated with brain injury and rehabilitation. These changes mainly involve an imbalance between the two hemispheres. We aimed to study the effect of brain computer interface (BCI)-based robotic hand training on stroke subjects using clinical assessment, electroencephalographic (EEG) complexity analysis, and functional magnetic resonance imaging (fMRI) connectivity analysis...
August 17, 2020: Topics in Stroke Rehabilitation
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