The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Sicong Zhang - One of the best experts on this subject based on the ideXlab platform.
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highly interactive brain computer interface based on flicker free steady state motion Visual Evoked Potential
Scientific Reports, 2018Co-Authors: Guanghua Xu, Chaoyang Chen, Sicong ZhangAbstract:Visual Evoked Potential-based brain–computer interfaces (BCIs) have been widely investigated because of their easy system configuration and high information transfer rate (ITR). However, the uncomfortable flicker or brightness modulation of existing methods restricts the practical interactivity of BCI applications. In our study, a flicker-free steady-state motion Visual Evoked Potential (FF-SSMVEP)-based BCI was proposed. Ring-shaped motion checkerboard patterns with oscillating expansion and contraction motions were presented by a high-refresh-rate display for Visual stimuli, and the brightness of the stimuli was kept constant. Compared with SSVEPs, few harmonic responses were elicited by FF-SSMVEPs, and the frequency energy of SSMVEPs was concentrative. These FF-SSMVEPs Evoked “single fundamental peak” responses after signal processing without harmonic and subharmonic peaks. More stimulation frequencies could thus be selected to elicit more responding fundamental peaks without overlap with harmonic peaks. A 40-target online SSMVEP-based BCI system was achieved that provided an ITR up to 1.52 bits per second (91.2 bits/min), and user training was not required to use this system. This study also demonstrated that the FF-SSMVEP-based BCI system has low contrast and low Visual fatigue, offering a better alternative to conventional SSVEP-based BCIs.
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the role of Visual noise in influencing mental load and fatigue in a steady state motion Visual Evoked Potential based brain computer interface
Sensors, 2017Co-Authors: Guanghua Xu, Min Li, Sicong ZhangAbstract:As a spatial selective attention-based brain-computer interface (BCI) paradigm, steady-state Visual Evoked Potential (SSVEP) BCI has the advantages of high information transfer rate, high tolerance to artifacts, and robust performance across users. However, its benefits come at the cost of mental load and fatigue occurring in the concentration on the Visual stimuli. Noise, as a ubiquitous random perturbation with the power of randomness, may be exploited by the human Visual system to enhance higher-level brain functions. In this study, a novel steady-state motion Visual Evoked Potential (SSMVEP, i.e., one kind of SSVEP)-based BCI paradigm with spatiotemporal Visual noise was used to investigate the influence of noise on the compensation of mental load and fatigue deterioration during prolonged attention tasks. Changes in α, θ, θ + α powers, θ/α ratio, and electroencephalography (EEG) properties of amplitude, signal-to-noise ratio (SNR), and online accuracy, were used to evaluate mental load and fatigue. We showed that presenting a moderate Visual noise to participants could reliably alleviate the mental load and fatigue during online operation of Visual BCI that places demands on the attentional processes. This demonstrated that noise could provide a superior solution to the implementation of Visual attention controlling-based BCI applications.
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steady state motion Visual Evoked Potential ssmvep based on equal luminance colored enhancement
PLOS ONE, 2017Co-Authors: Wenqiang Yan, Jun Xie, Chengcheng Han, Sicong Zhang, Ailing Luo, Chaoyang ChenAbstract:Steady-state Visual Evoked Potential (SSVEP) is one of the typical stimulation paradigms of brain-computer interface (BCI). It has become a research approach to improve the performance of human-computer interaction, because of its advantages including multiple objectives, less recording electrodes for electroencephalogram (EEG) signals, and strong anti-interference capacity. Traditional SSVEP using light flicker stimulation may cause Visual fatigue with a consequent reduction of recognition accuracy. To avoid the negative impacts on the brain response caused by prolonged strong Visual stimulation for SSVEP, steady-state motion Visual Evoked Potential (SSMVEP) stimulation method was used in this study by an equal-luminance colored ring-shaped checkerboard paradigm. The movement patterns of the checkerboard included contraction and expansion, which produced less discomfort to subjects. Feature recognition algorithms based on power spectrum density (PSD) peak was used to identify the peak frequency on PSD in response to Visual stimuli. Results demonstrated that the equal-luminance red-green stimulating paradigm within the low frequency spectrum (lower than 15 Hz) produced higher power of SSMVEP and recognition accuracy than black-white stimulating paradigm. PSD-based SSMVEP recognition accuracy was 88.15±6.56%. There was no statistical difference between canonical correlation analysis (CCA) (86.57±5.37%) and PSD on recognition accuracy. This study demonstrated that equal-luminance colored ring-shaped checkerboard Visual stimulation Evoked SSMVEP with better SNR on low frequency spectrum of power density and improved the interactive performance of BCI.
Guanghua Xu - One of the best experts on this subject based on the ideXlab platform.
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highly interactive brain computer interface based on flicker free steady state motion Visual Evoked Potential
Scientific Reports, 2018Co-Authors: Guanghua Xu, Chaoyang Chen, Sicong ZhangAbstract:Visual Evoked Potential-based brain–computer interfaces (BCIs) have been widely investigated because of their easy system configuration and high information transfer rate (ITR). However, the uncomfortable flicker or brightness modulation of existing methods restricts the practical interactivity of BCI applications. In our study, a flicker-free steady-state motion Visual Evoked Potential (FF-SSMVEP)-based BCI was proposed. Ring-shaped motion checkerboard patterns with oscillating expansion and contraction motions were presented by a high-refresh-rate display for Visual stimuli, and the brightness of the stimuli was kept constant. Compared with SSVEPs, few harmonic responses were elicited by FF-SSMVEPs, and the frequency energy of SSMVEPs was concentrative. These FF-SSMVEPs Evoked “single fundamental peak” responses after signal processing without harmonic and subharmonic peaks. More stimulation frequencies could thus be selected to elicit more responding fundamental peaks without overlap with harmonic peaks. A 40-target online SSMVEP-based BCI system was achieved that provided an ITR up to 1.52 bits per second (91.2 bits/min), and user training was not required to use this system. This study also demonstrated that the FF-SSMVEP-based BCI system has low contrast and low Visual fatigue, offering a better alternative to conventional SSVEP-based BCIs.
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the role of Visual noise in influencing mental load and fatigue in a steady state motion Visual Evoked Potential based brain computer interface
Sensors, 2017Co-Authors: Guanghua Xu, Min Li, Sicong ZhangAbstract:As a spatial selective attention-based brain-computer interface (BCI) paradigm, steady-state Visual Evoked Potential (SSVEP) BCI has the advantages of high information transfer rate, high tolerance to artifacts, and robust performance across users. However, its benefits come at the cost of mental load and fatigue occurring in the concentration on the Visual stimuli. Noise, as a ubiquitous random perturbation with the power of randomness, may be exploited by the human Visual system to enhance higher-level brain functions. In this study, a novel steady-state motion Visual Evoked Potential (SSMVEP, i.e., one kind of SSVEP)-based BCI paradigm with spatiotemporal Visual noise was used to investigate the influence of noise on the compensation of mental load and fatigue deterioration during prolonged attention tasks. Changes in α, θ, θ + α powers, θ/α ratio, and electroencephalography (EEG) properties of amplitude, signal-to-noise ratio (SNR), and online accuracy, were used to evaluate mental load and fatigue. We showed that presenting a moderate Visual noise to participants could reliably alleviate the mental load and fatigue during online operation of Visual BCI that places demands on the attentional processes. This demonstrated that noise could provide a superior solution to the implementation of Visual attention controlling-based BCI applications.
Chaoyang Chen - One of the best experts on this subject based on the ideXlab platform.
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highly interactive brain computer interface based on flicker free steady state motion Visual Evoked Potential
Scientific Reports, 2018Co-Authors: Guanghua Xu, Chaoyang Chen, Sicong ZhangAbstract:Visual Evoked Potential-based brain–computer interfaces (BCIs) have been widely investigated because of their easy system configuration and high information transfer rate (ITR). However, the uncomfortable flicker or brightness modulation of existing methods restricts the practical interactivity of BCI applications. In our study, a flicker-free steady-state motion Visual Evoked Potential (FF-SSMVEP)-based BCI was proposed. Ring-shaped motion checkerboard patterns with oscillating expansion and contraction motions were presented by a high-refresh-rate display for Visual stimuli, and the brightness of the stimuli was kept constant. Compared with SSVEPs, few harmonic responses were elicited by FF-SSMVEPs, and the frequency energy of SSMVEPs was concentrative. These FF-SSMVEPs Evoked “single fundamental peak” responses after signal processing without harmonic and subharmonic peaks. More stimulation frequencies could thus be selected to elicit more responding fundamental peaks without overlap with harmonic peaks. A 40-target online SSMVEP-based BCI system was achieved that provided an ITR up to 1.52 bits per second (91.2 bits/min), and user training was not required to use this system. This study also demonstrated that the FF-SSMVEP-based BCI system has low contrast and low Visual fatigue, offering a better alternative to conventional SSVEP-based BCIs.
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steady state motion Visual Evoked Potential ssmvep based on equal luminance colored enhancement
PLOS ONE, 2017Co-Authors: Wenqiang Yan, Jun Xie, Chengcheng Han, Sicong Zhang, Ailing Luo, Chaoyang ChenAbstract:Steady-state Visual Evoked Potential (SSVEP) is one of the typical stimulation paradigms of brain-computer interface (BCI). It has become a research approach to improve the performance of human-computer interaction, because of its advantages including multiple objectives, less recording electrodes for electroencephalogram (EEG) signals, and strong anti-interference capacity. Traditional SSVEP using light flicker stimulation may cause Visual fatigue with a consequent reduction of recognition accuracy. To avoid the negative impacts on the brain response caused by prolonged strong Visual stimulation for SSVEP, steady-state motion Visual Evoked Potential (SSMVEP) stimulation method was used in this study by an equal-luminance colored ring-shaped checkerboard paradigm. The movement patterns of the checkerboard included contraction and expansion, which produced less discomfort to subjects. Feature recognition algorithms based on power spectrum density (PSD) peak was used to identify the peak frequency on PSD in response to Visual stimuli. Results demonstrated that the equal-luminance red-green stimulating paradigm within the low frequency spectrum (lower than 15 Hz) produced higher power of SSMVEP and recognition accuracy than black-white stimulating paradigm. PSD-based SSMVEP recognition accuracy was 88.15±6.56%. There was no statistical difference between canonical correlation analysis (CCA) (86.57±5.37%) and PSD on recognition accuracy. This study demonstrated that equal-luminance colored ring-shaped checkerboard Visual stimulation Evoked SSMVEP with better SNR on low frequency spectrum of power density and improved the interactive performance of BCI.
Kathleen M. Fitzgerald - One of the best experts on this subject based on the ideXlab platform.
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Amblyopia in unilateral congenital ptosis: early detection by sweep Visual Evoked Potential
Graefe's Archive for Clinical and Experimental Ophthalmology, 1995Co-Authors: Gerhard W. Cibis, Kathleen M. FitzgeraldAbstract:•Background: Fixation preference assessment is a clinical tool widely used to determine amblyopia in young infants and children. It is our clinical experience that this tool underestimates amblyopia. The purpose of this study was to compare the results of sweep Visual Evoked Potentials to fixation preference assessment in cases of unilateral ptosis. • Methods: Sweep Visual Evoked Potentials were performed in 17 children with unilateral ptosis thought to have equal acuity by fixation preference asessment. Binocular and monocular sweep Visual Evoked Potentials were recorded to square-wave gratings of 80% contrast counterphase modulated at 6 Hz. A range of spatial frequencies from 1 to 30 cycles per degree were presented over a 10-s period. Resolution acuity was determined as the zero-microvolt intercept of linear regression analysis on the Visual Evoked Potential amplitude versus spatial frequency. • Results: Nine of the 17 children had interocular resolution acuity differences ranging from 0.8 to 2 octaves by sweep Visual Evoked Potential testing. This correlates to a Snellen equivalent interocular difference of 2 to 7 lines and clinical amblyopia. • Conclusion: This study confirms our clinical impression that children who are unable to preform recognition acuity tasks and are thought to have equal vision by fixation preference assessment often have 2 or more lines of Snellen acuity difference (amblyopia) when they are finally old enough to be tested by Snellen methods. It also implies that amblyopia precedes refractive errors and strabismus in unilateral ptosis cases. Clinical methods to determine amblyopia other than fixation preference assessment need to be explored with a view to earlier detection, better definition and treatment of amblyopia.
Charles A Nelson - One of the best experts on this subject based on the ideXlab platform.
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deletion and duplication of 16p11 2 are associated with opposing effects on Visual Evoked Potential amplitude
Molecular Autism, 2016Co-Authors: Jocelyn Leblanc, Charles A NelsonAbstract:Background Duplication and deletion of the chromosomal region 16p11.2 cause a broad range of impairments, including intellectual disability, language disorders, and sensory symptoms. However, it is unclear how changes in 16p11.2 dosage affect cortical circuitry during development. The aim of this study was to investigate whether the Visual Evoked Potential (VEP) could be used as a noninvasive quantitative measure of cortical processing in children with 16p11.2 copy number variation.
