Papers Brain Computer Interface
“Brain Computer Interface” 태그가 달린 논문 466편 · 필터 해제
Hybrid Template Canonical Correlation Analysis Method for Enhancing SSVEP Recognition under data-limited Condition
In this study, an advanced CCA-based algorithn called hybrid template canonical correlation analysis (HTCCA) was proposed to improve the performance of brain-computer interface (BCI) based on steady state visual evoked p…
Brain Computer InterfaceEEGElectroencephalogram (EEG)SSVEP+1Selection of Proper EEG Channels for Subject Intention Classification Using Deep Learning
Brain signals could be used to control devices to assist individuals with disabilities. Signals such as electroencephalograms are complicated and hard to interpret. A set of signals are collected and should be classified…
Brain Computer InterfaceEEGElectroencephalogram (EEG)General ClassificationGCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals
Towards developing effective and efficient brain-computer interface (BCI) systems, precise decoding of brain activity measured by electroencephalogram (EEG), is highly demanded. Traditional works classify EEG signals wit…
Brain Computer InterfaceEEGElectroencephalogram (EEG)Motor ImageryClassification and Recognition of Encrypted EEG Data Neural Network
With the rapid development of Machine Learning technology applied in electroencephalography (EEG) signals, Brain-Computer Interface (BCI) has emerged as a novel and convenient human-computer interaction for smart home, i…
Brain Computer InterfaceClassificationEEGElectroencephalogram (EEG)+1Constrained Variational Autoencoder for improving EEG based Speech Recognition Systems
In this paper we introduce a recurrent neural network (RNN) based variational autoencoder (VAE) model with a new constrained loss function that can generate more meaningful electroencephalography (EEG) features from raw …
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Brain Computer InterfaceEEG+3PhyAAt: Physiology of Auditory Attention to Speech Dataset
Auditory attention to natural speech is a complex brain process. Its quantification from physiological signals can be valuable to improving and widening the range of applications of current brain-computer-interface syste…
Attention Score PredictionBrain Computer InterfaceLWR ClassificationNoise Level Prediction+1Mu-suppression detection in motor imagery electroencephalographic signals using the generalized extreme value distribution
This paper deals with the detection of mu-suppression from electroencephalographic (EEG) signals in brain-computer interface (BCI). For this purpose, an efficient algorithm is proposed based on a statistical model and a …
Brain Computer InterfaceEEGElectroencephalogram (EEG)Motor ImageryAttention Patterns Detection using Brain Computer Interfaces
The human brain provides a range of functions such as expressing emotions, controlling the rate of breathing, etc., and its study has attracted the interest of scientists for many years. As machine learning models become…
Brain Computer InterfaceEEGElectroencephalogram (EEG)Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI
Decoding behavior, perception, or cognitive state directly from neural signals has applications in brain-computer interface research as well as implications for systems neuroscience. In the last decade, deep learning has…
Brain Computer InterfaceDeep LearningEEGElectroencephalogram (EEG)+4Decoding of Intuitive Visual Motion Imagery Using Convolutional Neural Network under 3D-BCI Training Environment
In this study, we adopted visual motion imagery, which is a more intuitive brain-computer interface (BCI) paradigm, for decoding the intuitive user intention. We developed a 3-dimensional BCI training platform and applie…
Brain Computer InterfaceFunctional ConnectivityGeneral ClassificationClassification of Visual Perception and Imagery based EEG Signals Using Convolutional Neural Networks
Recently, visual perception (VP) and visual imagery (VI) paradigms are investigated in several brain-computer interface (BCI) studies. VP and VI are defined as a changing of brain signals when perceiving and memorizing v…
Binary ClassificationBrain Computer InterfaceEEGElectroencephalogram (EEG)+1Gradual Relation Network: Decoding Intuitive Upper Extremity Movement Imaginations Based on Few-Shot EEG Learning
Brain-computer interface (BCI) is a communication tool that connects users and external devices. In a real-time BCI environment, a calibration procedure is particularly necessary for each user and each session. This proc…
Brain Computer InterfaceEEGElectroencephalogram (EEG)Few-Shot Learning+2Prediction of Memory Retrieval Performance Using Ear-EEG Signals
Many studies have explored brain signals during the performance of a memory task to predict later remembered items. However, prediction methods are still poorly used in real life and are not practical due to the use of e…
Brain Computer InterfaceEEGElectroencephalogram (EEG)RetrievalDeep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition
Recognition accuracy and response time are both critically essential ahead of building practical electroencephalography (EEG) based brain-computer interface (BCI). Recent approaches, however, have either compromised in t…
Brain Computer InterfaceEEGElectroencephalogram (EEG)Motor ImageryThe Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models
The Kalman filter provides a simple and efficient algorithm to compute the posterior distribution for state-space models where both the latent state and measurement models are linear and gaussian. Extensions to the Kalma…
Brain Computer InterfaceregressionSequential Bayesian InferenceState Estimation+1Brain-based control of car infotainment
Nowadays, the possibility to run advanced AI on embedded systems allows natural interaction between humans and machines, especially in the automotive field. We present a custom portable EEG-based Brain-Computer Interface…
Brain Computer InterfaceEEGElectroencephalogram (EEG)ERPDetecting Driver's Distraction using Long-term Recurrent Convolutional Network
In this study we demonstrate a novel Brain Computer Interface (BCI) approach to detect driver distraction events to improve road safety. We use a commercial wireless headset that generates EEG signals from the brain. We …
Brain Computer InterfaceEEGElectroencephalogram (EEG)Time Series+2Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016
A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common non-invasive BCI modality, electroencephalogram (EEG), is sensitive to noise/artifact and suffe…
Brain Computer InterfaceEEGElectroencephalogram (EEG)Motor Imagery+1Active recursive Bayesian inference using Rényi information measures
Recursive Bayesian inference (RBI) provides optimal Bayesian latent variable estimates in real-time settings with streaming noisy observations. Active RBI attempts to effectively select queries that lead to more informat…
Bayesian InferenceBrain Computer InterfaceDecision MakingHuman action recognition with a large-scale brain-inspired photonic computer
The recognition of human actions in video streams is a challenging task in computer vision, with cardinal applications in e.g. brain-computer interface and surveillance. Deep learning has shown remarkable results recentl…
Action RecognitionBrain Computer InterfaceTemporal Action Localization