Feature fusion for improving performance of motor imagery brain-computer interface system
出版年份 2021 全文链接
标题
Feature fusion for improving performance of motor imagery brain-computer interface system
作者
关键词
Feature fusion, Motor imagery, Brain-computer interface, Feature selection, Constant-Q filter
出版物
Biomedical Signal Processing and Control
Volume 68, Issue -, Pages 102763
出版商
Elsevier BV
发表日期
2021-05-15
DOI
10.1016/j.bspc.2021.102763
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Adaptation of Common Spatial Patterns based on mental fatigue for motor-imagery BCI
- (2020) Upasana Talukdar et al. Biomedical Signal Processing and Control
- Motor imagery EEG classification based on ensemble support vector learning
- (2020) Jing Luo et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- A new multi-objective wrapper method for feature selection – Accuracy and stability analysis for BCI
- (2019) Jesús González et al. NEUROCOMPUTING
- Filtering techniques for channel selection in motor imagery EEG applications: a survey
- (2019) Muhammad Zeeshan Baig et al. ARTIFICIAL INTELLIGENCE REVIEW
- Transfer learning in imagined speech EEG-based BCIs
- (2019) Jesús S. García-Salinas et al. Biomedical Signal Processing and Control
- Feature selection using regularized neighbourhood component analysis to enhance the classification performance of motor imagery signals
- (2019) Nitesh Singh Malan et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Common spatial patterns combined with phase synchronization information for classification of EEG signals
- (2019) X. Li et al. Biomedical Signal Processing and Control
- Classification of multiclass motor imagery EEG signal using sparsity approach
- (2019) S. R. Sreeja et al. NEUROCOMPUTING
- Comparative analysis of features extracted from EEG spatial, spectral and temporal domains for binary and multiclass motor imagery classification
- (2019) Seung-Bo Lee et al. INFORMATION SCIENCES
- Automatic and tunable algorithm for EEG artifact removal using wavelet decomposition with applications in predictive modeling during auditory tasks
- (2019) Nikesh Bajaj et al. Biomedical Signal Processing and Control
- FastEMD–CCA algorithm for unsupervised and fast removal of eyeblink artifacts from electroencephalogram
- (2019) Ashvaany Egambaram et al. Biomedical Signal Processing and Control
- A review of feature extraction and performance evaluation in epileptic seizure detection using EEG
- (2019) Poomipat Boonyakitanont et al. Biomedical Signal Processing and Control
- Improved EOG Artifact Removal Using Wavelet Enhanced Independent Component Analysis
- (2019) Mohamed F. Issa et al. Brain Sciences
- BCI oriented EEG analysis using log energy entropy of wavelet packets
- (2018) Hüseyin Göksu Biomedical Signal Processing and Control
- Robust Support Matrix Machine for Single Trial EEG Classification
- (2018) Qingqing Zheng et al. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
- Brain–machine interfaces for controlling lower-limb powered robotic systems
- (2018) Yongtian He et al. Journal of Neural Engineering
- Spatio-temporal discrepancy feature for classification of motor imageries
- (2018) Jing Luo et al. Biomedical Signal Processing and Control
- Emotion classification using EEG signals based on tunable-Q wavelet transform
- (2018) Anala Hari Krishna et al. IET Science Measurement & Technology
- Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review
- (2017) L R Quitadamo et al. Journal of Neural Engineering
- EEG-based BCI and video games: a progress report
- (2017) Bojan Kerous et al. VIRTUAL REALITY
- Dynamic frequency feature selection based approach for classification of motor imageries
- (2016) Jing Luo et al. COMPUTERS IN BIOLOGY AND MEDICINE
- A novel deep learning approach for classification of EEG motor imagery signals
- (2016) Yousef Rezaei Tabar et al. Journal of Neural Engineering
- Adaptive learning with covariate shift-detection for motor imagery-based brain–computer interface
- (2015) Haider Raza et al. SOFT COMPUTING
- Exploring dimensionality reduction of EEG features in motor imagery task classification
- (2014) Pedro J. García-Laencina et al. EXPERT SYSTEMS WITH APPLICATIONS
- Extracting optimal tempo-spatial features using local discriminant bases and common spatial patterns for brain computer interfacing
- (2013) Javier Asensio-Cubero et al. Biomedical Signal Processing and Control
- Classification of brain hemodynamic signals arising from visual action observation tasks for brain–computer interfaces: A functional near-infrared spectroscopy study
- (2013) Berdakh Abibullaev et al. MEASUREMENT
- Analysis the effect of PCA for feature reduction in non-stationary EEG based motor imagery of BCI system
- (2013) Xinyang Yu et al. OPTIK
- Simultaneous Design of FIR Filter Banks and Spatial Patterns for EEG Signal Classification
- (2012) H. Higashi et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- A latent discriminative model-based approach for classification of imaginary motor tasks from EEG data
- (2012) Jaime F Delgado Saa et al. Journal of Neural Engineering
- Multiple classifier system for EEG signal classification with application to brain–computer interfaces
- (2012) Amir Ahangi et al. NEURAL COMPUTING & APPLICATIONS
- Bispectrum-based feature extraction technique for devising a practical brain–computer interface
- (2011) Shahjahan Shahid et al. Journal of Neural Engineering
- Regularizing Common Spatial Patterns to Improve BCI Designs: Unified Theory and New Algorithms
- (2010) Fabien Lotte et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Feature selection on movement imagery discrimination and attention detection
- (2010) N. S. Dias et al. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
- Optimizing Spatial filters for Robust EEG Single-Trial Analysis
- (2008) Benjamin Blankertz et al. IEEE SIGNAL PROCESSING MAGAZINE
- Classifying mental tasks based on features of higher-order statistics from EEG signals in brain–computer interface
- (2007) Shang-Ming Zhou et al. INFORMATION SCIENCES
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now