- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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The Effects of Global Signal Regression on Estimates of Resting-State Blood Oxygen-Level-Dependent Functional Magnetic Resonance Imaging and Electroencephalogram Vigilance Correlations
摘要： Global signal regression (GSR) is a commonly used although controversial preprocessing approach in the analysis of resting-state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data. Although the effects of GSR on resting-state functional connectivity measures have received much attention, there has been relatively little attention devoted to its effects on studies looking at the relationship between resting-state BOLD measures and independent measures of brain activity. In this study, we used simultaneously acquired electroencephalogram (EEG)–fMRI data in humans to examine the effects of GSR on the correlation between resting-state BOLD fluctuations and EEG vigilance measures. We show that GSR leads to a positive shift in the correlation between the BOLD and vigilance measures. This shift leads to a reduction in the spatial extent of negative correlations in widespread brain areas, including the visual cortex, but leads to the appearance of positive correlations in other areas, such as the cingulate gyrus. The results obtained using GSR are consistent with those of a temporal censoring process in which the correlation is computed using a temporal subset of the data. Since the data from these retained time points are unaffected by the censoring process, this finding suggests that the positive correlations in cingulate gyrus are not simply an artifact of GSR.
关键词： resting-state fMRI,vigilance,global signal regression,simultaneous EEG–fMRI
更新于2025-09-23 15:23:52
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[IEEE 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR) - Bangalore, India (2017.12.27-2017.12.30)] 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR) - A Novel Hybrid Brain-Computer Interface for Robot Arm manipulation using Visual Evoked Potential
摘要： This paper attempts to solve a major problem of rigorous subject training in BCI based robotics. A hybrid Brain computer interface has been established here to mentally guide a robot arm without any motor commands generated in mind. Spontaneous N200 response of human brain as a part of motion onset visual evoked potential (mVEP) is used here to detect the desired object in the environment and use of Steady state visual evoked potential (SSVEP) provides the guidance to a bedside robotic arm to reach that target object. Electroencephalographic response of ten such subjects has been used here to evaluate the efficacy of the proposed system. Recorded EEG response goes through a sequential operation of preprocessing, feature extraction and classification. For detecting N200 response of the brain, a novel EKF-Particle filter induced Neural Network classifier is also proposed which essentially outperforms the other existing classifier for N200 detection. Performance analysis of other classifiers has been given here for comparison.
关键词： Particle Filter,BCI,Elman NN,Robot,EKF,EEG
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA) - Rome, Italy (2018.6.11-2018.6.13)] 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA) - Extracting Features from Optical Coherence Tomography for Measuring Optical Nerve Thickness
摘要： Neurological pathologies, especially optical neuropathologies, can be studied by means of OCT (optical coherence tomography). Tomography generally allows to investigate inner structures of a tissue such as mass, and profiles of liquid flow. OCT is intended as an interferometry-based imaging technique that provides cross-sectional views of substrates. It allows to measure micro-scale cross-sectional imaging of biological tissue. While ultrasound uses sound waves, it acts like it but with a low coherence light. Optical nerve thickness has an impact on different neurological pathologies, and in particular as an indicator of epilepsy. We propose a dedicated technique for measuring optical nerve thickness and identifying its quality by means of processing front eye image in nanoscale. Experimental measurements have been performed, and a database of 10 teenagers has been used for that.
关键词： Micro and Nanotechnology,Optical nerve thickness measurement,Optical coherence Tomography,Neuro-disorders,Epilepsy,Atomic Force Microscopy,EEG
更新于2025-09-23 15:22:29
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Electrophysiology Meets Printed Electronics: The Beginning of a Beautiful Friendship
摘要： Electroencephalography (EEG) and surface electromyography (sEMG) are notoriously cumbersome technologies. A typical setup may involve bulky electrodes, dangling wires, and a large amplifier unit. Adapting these technologies to numerous applications has been accordingly fairly limited. Thanks to the availability of printed electronics, it is now possible to effectively simplify these techniques. Elegant electrode arrays with unprecedented performances can be readily produced, eliminating the need to handle multiple electrodes and wires. Specifically, in this Perspective paper, we focus on the advantages of electrodes printed on soft films as manifested in signal transmission at the electrode-skin interface, electrode-skin stability, and user convenience during electrode placement while achieving prolonged use. Customizing electrode array designs and implementing blind source separation methods can also improve recording resolution, reduce variability between individuals and minimize signal cross-talk between nearby electrodes. Finally, we outline several important applications in the field of neuroscience and how each can benefit from the convergence of electrophysiology and printed electronics.
关键词： wearable sensors,EMG,printed electrodes,skin electronics,EEG
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) - Miyazaki, Japan (2018.10.7-2018.10.10)] 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) - Monitoring Pilot's Cognitive Fatigue with Engagement Features in Simulated and Actual Flight Conditions Using an Hybrid fNIRS-EEG Passive BCI
摘要： There is growing interest for implementing tools to monitor cognitive performance in naturalistic environments. Recent technological progress has allowed the development of new generations of brain imaging systems such as dry electrodes electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) to investigate cortical activity in a variety of human tasks out of the laboratory. These highly portable brain imaging devices offer interesting prospects to implement passive brain computer interfaces (pBCI) and neuroadaptive technology. We developed a fNIRS-EEG based pBCI to monitor cognitive fatigue using engagement related features (EEG engagement ratio and wavelet coherence fNIRS based metrics). This mental state is known to impair cognitive performance and can jeopardize flight safety. In this preliminary study, four participants were asked to perform four identical traffic patterns along with a secondary auditory task in a flight simulator and in an actual light aircraft. The two first traffic patterns were considered as the low cognitive fatigue class, whereas the two last traffic patterns were considered as the high cognitive fatigue class. As expected, the pilots missed more auditory targets in the second part than in the first part of the experiment. Classification accuracy reached 87.2% in the flight simulator condition and 87.6% in the actual flight conditions when combining the two modalities. This study demonstrates that fNIRS and EEG-based pBCIs can monitor mental states in operational and noisy environments.
关键词： Hybrid fNIRS-EEG BCI,Neuroergonomics,Real flight conditions,Cognitive fatigue
更新于2025-09-23 15:22:29
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Highly accelerated stress method for measuring water vapor transmission rate of PV backsheet
摘要： The increasing availability of network data is leading to a growing interest in processing of signals on graphs. One notable tool for extending conventional signal-processing operations to networks is the graph Fourier transform that can be obtained as the eigendecomposition of the graph Laplacian. In this letter, we used the graph Fourier transform to define a new method for generating surrogate graph signals. The approach is based on sign-randomization of the graph Fourier coefficients and, therefore, the correlation structure of the surrogate graph signals (i.e., smoothness on the graph topology) is imposed by the measured data. The proposed method of surrogate data generation can be widely applied for nonparametric statistical hypothesis testing. Here, we showed a proof-of-concept with a high-density electroencephalography dataset.
关键词： nonparametric hypothesis testing,Electroencephalography (EEG),graph Laplacian,surrogate data,phase randomization,graph signals
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) - Edmonton, AB, Canada (2019.5.5-2019.5.8)] 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) - Targets Illumination Region Effect on Laser RCS in Random Media for H-Wave Polarization
摘要： The classification accuracy of a brain–computer interface (BCI) frequently suffers from ill-posed and overfitting problems. To avoid and alleviate these problems, we propose a method of a multilinear discriminant analysis with constraints to augment parameter reduction, regularization, and additional prior information for event-related potential (ERP)-based BCIs. The method reduces the number of parameters by multilinearization, regularizes the ill-posedness via subspaces that constrain the parameter spaces, and incorporates a brain functional connectivity through the constraints. The experimental results show that the proposed method improved the classification accuracy rates in a single-trial ERP processing.
关键词： multilinear algebra,single-trial classification,linear discriminant analysis,Brain–computer/machine interface (BCI/BMI),event-related potentials,electroencephalogram (EEG)
更新于2025-09-23 15:21:01
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Modelling the brain response to arbitrary visual stimulation patterns for a flexible high-speed Brain-Computer Interface
摘要： Visual evoked potentials (VEPs) can be measured in the EEG as response to a visual stimulus. Commonly, VEPs are displayed by averaging multiple responses to a certain stimulus or a classifier is trained to identify the response to a certain stimulus. While the traditional approach is limited to a set of predefined stimulation patterns, we present a method that models the general process of VEP generation and thereby can be used to predict arbitrary visual stimulation patterns from EEG and predict how the brain responds to arbitrary stimulation patterns. We demonstrate how this method can be used to model single-flash VEPs, steady state VEPs (SSVEPs) or VEPs to complex stimulation patterns. It is further shown that this method can also be used for a high-speed BCI in an online scenario where it achieved an average information transfer rate (ITR) of 108.1 bit/min. Furthermore, in an off-line analysis, we show the flexibility of the method allowing to modulate a virtually unlimited amount of targets with any desired trial duration resulting in a theoretically possible ITR of more than 470 bit/min.
关键词： Visual evoked potentials,High-speed BCI,EEG,Information transfer rate,Brain-Computer Interface
更新于2025-09-23 15:21:01
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Photovoltaic String Sizing Using Site-Specific Modeling
摘要： This paper focuses on electroencephalogram (EEG) manifestations of mental states and actions, emulation of control and communication structures using EEG manifestations, and their application in brain-robot interactions. The paper introduces a mentally emulated demultiplexer, a device which uses mental actions to demultiplex a single EEG channel into multiple digital commands. The presented device is applicable in controlling several objects through a single EEG channel. The experimental proof of the concept is given by an obstacle-containing trajectory which should be negotiated by a robotic arm with two degrees of freedom, controlled by mental states of a human brain using a single EEG channel. The work is presented in the framework of Human-Robot interaction (HRI), speci?cally in the framework of brain–robot interaction (BRI). This work is a continuation of a previous work on developing mentally emulated digital devices, such as a mental action switch, and a mental states ?ip-?op.
关键词： Brain–robot interaction (BRI),mental action EEG switch,mentally emulated EEG demultiplexer,electroencephalogram (EEG) manifestations of mental states and actions,mental state CNV ?ip-?op
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Sputtered Aluminum Oxide and p <sup>+</sup> Amorphous Silicon Back-Contact for Improved Hole Extraction in Polycrystalline CdSe <sub/>x</sub> Te <sub/>1-x</sub> and CdTe Photovoltaics
摘要： Previous studies have attempted to investigate the peripheral neural mechanisms implicated in tactile perception, but the neurophysiological data in humans involved in tactile spatial location perception to help the brain orient the body and interact with its surroundings are not well understood. In this paper, we use single-trial electroencephalogram (EEG) measurements to explore the perception of tactile stimuli located on participants’ right forearm, which were approximately equally spaced centered on the body midline, 2 leftward and 2 rightward of midline. An EEG-based signal analysis approach to predict the location of the tactile stimuli is proposed. Offline classification suggests that tactile location can be detected from EEG signals in single trial (four-class classifier for location discriminate can achieve up to 96.76%) with a short response time (600 milliseconds after stimulus presentation). From a human-machine-interaction (HMI) point of view, this could be used to design a real-time reactive control machine for patients, e.g., suffering from hypoesthesia.
关键词： Electroencephalogram (EEG),prediction,tactile,spatial location perception
更新于2025-09-23 15:19:57