- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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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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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
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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) - Novel optical approach for concentrating light in micro-CPV
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2025-09-19 17:13:59
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[IEEE 2019 Device Research Conference (DRC) - Ann Arbor, MI, USA (2019.6.23-2019.6.26)] 2019 Device Research Conference (DRC) - III-V Lasers and Integrated Components Directly Grown on Silicon: Options for Integration
摘要： Electroencephalogram (EEG) is a technique for recording the asynchronous activation of neuronal firing inside the brain with non-invasive scalp electrodes. Artifacts, such as eye blink activities, can corrupt these neuronal signals. While ocular artifact (OA) removal is well investigated for multiple channel EEG systems, in alignment with the recent momentum toward minimalistic EEG systems for use in natural environments, we investigate unsupervised and effective removal of OA from single-channel streaming raw EEG data. In this paper, the unsupervised wavelet transform (WT) decomposition technique was systematically evaluated for the effectiveness of OA removal for a single-channel EEG system. A set of seven raw EEG data set was analyzed. Two commonly used WT methods, Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT), were applied. Four WT basis functions, namely, haar, coif3, sym3, and bior4.4, were considered for OA removal with universal threshold and statistical threshold (ST). To quantify OA removal efficacy from single-channel EEG, five performance metrics were utilized: correlation coefficients, mutual information, signal-to-artifact ratio, normalized mean square error, and time-frequency analysis. The temporal and spectral analysis shows that the optimal combination could be DWT with ST with coif3 or bior4.4 to remove OA among 16 combinations. This paper demonstrates that the WT can be an effective tool for unsupervised OA removal from single-channel EEG data for real-time applications.
关键词： ocular artifact,wavelet transform,electroencephalogram (EEG),single channel EEG,Artifact removal
更新于2025-09-19 17:13:59
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[IEEE 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM) - Dubai, United Arab Emirates (2020.1.9-2020.1.10)] 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM) - Compact UWB Monopole antenna with WLAN and X-Band satellite filtering Characteristics
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： single-trial classification,Brain–computer/machine interface (BCI/BMI),electroencephalogram (EEG),event-related potentials,linear discriminant analysis,multilinear algebra
更新于2025-09-19 17:13:59
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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) - Ways of Producing Perovskite Light Absorbing Layer on Periodically Patterned Silicon Texture and Evaluating Method
摘要： A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing (BCI). The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g., electrooculogram signals). Evaluation of FORCe is performed of?ine on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged Auto-Mutual Information Clustering (LAMIC) and Fully Automated Statistical Thresholding for EEG artifact Rejection (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.
关键词： independent component analysis,wavelets,brain-computer interface (BCI),electroencephalogram (EEG),Automated online artifact removal
更新于2025-09-19 17:13:59