Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space
Objective. This review paper provides an integrated perspective of Explainable Artificial
Intelligence (XAI) techniques applied to Brain-Computer Interfaces (BCIs). BCIs use …
Intelligence (XAI) techniques applied to Brain-Computer Interfaces (BCIs). BCIs use …
A review on signal processing approaches to reduce calibration time in EEG-based brain–computer interface
In an electroencephalogram-(EEG-) based brain–computer interface (BCI), a subject can
directly communicate with an electronic device using his EEG signals in a safe and …
directly communicate with an electronic device using his EEG signals in a safe and …
Single-trial motor imagery electroencephalogram intention recognition by optimal discriminant hyperplane and interpretable discriminative rectangle mixture model
R Fu, D Xu, W Li, P Shi - Cognitive Neurodynamics, 2022 - Springer
Spatial filtering is widely used in brain-computer interface (BCI) systems to augmented
signal characteristics of electroencephalogram (EEG) signals. In this study, a spatial domain …
signal characteristics of electroencephalogram (EEG) signals. In this study, a spatial domain …
NeurCAM: Interpretable Neural Clustering via Additive Models
Interpretable clustering algorithms aim to group similar data points while explaining the
obtained groups to support knowledge discovery and pattern recognition tasks. While most …
obtained groups to support knowledge discovery and pattern recognition tasks. While most …
Execution, assessment and improvement methods of motor imagery for brain-computer interface
G Tian, J Chen, P Ding, A Gong, F Wang… - Sheng wu yi xue …, 2021 - europepmc.org
运动想象 (MI) 是驱动脑机接口 (BCI) 的一种重要范式, 但 MI 心理活动不易控制或**得, MI-BCI
的性能严重依赖被试 MI 的表现. 因此 MI 心理活动的**确执行以及能力的评估和提高对 MI-BCI …
的性能严重依赖被试 MI 的表现. 因此 MI 心理活动的**确执行以及能力的评估和提高对 MI-BCI …
An evidence accumulation based block diagonal cluster model for intent recognition from EEG
R Fu, Z Li - Biomedical Signal Processing and Control, 2022 - Elsevier
Most of the probabilistic mixture models perform clustering by observing the eigenvectors of
the data sample and these models rely on the layout of features. Clustering ensemble based …
the data sample and these models rely on the layout of features. Clustering ensemble based …
[HTML][HTML] 脑机接口中运动想象的执行与能力的评估和提高方法
贵鑫田， 俊杰陈， 鹏丁， 安民龚， 帆王… - Sheng Wu Yi Xue …, 2021 - ncbi.nlm.nih.gov
运动想象（ MI） 是驱动脑机接口（ BCI） 的一种重要范式， 但MI 心理活动不易控制或**得， MI-
BCI 的性能严重依赖被试MI 的表现。 因此MI 心理活动的**确执行以及能力的评估和提高对MI …
BCI 的性能严重依赖被试MI 的表现。 因此MI 心理活动的**确执行以及能力的评估和提高对MI …
An Adaptive EEG Classification Algorithm Based on CSSD and ELM_Kernel for Small Training Samples
L Wang, Z Lan, Q Wang, X Bai… - Journal of Healthcare …, 2022 - Wiley Online Library
Rehabilitation technologies based on brain‐computer interface (BCI) have become a
promising approach for patients with dyskinesia to regain movement. In BCI experiment …
promising approach for patients with dyskinesia to regain movement. In BCI experiment …
An optimized GMM algorithm and its application in single-trial motor imagination recognition
R Fu, Z Li, J Wang - Biomedical Signal Processing and Control, 2022 - Elsevier
The Gaussian mixture model (GMM) is utilized to illustrate the possibility of applying
probabilistic models to data clustering and provide an efficient method for processing EEG …
probabilistic models to data clustering and provide an efficient method for processing EEG …
[PDF][PDF] Smart Drowsiness Detector to Alert Surgeons at Times of Operating
J Lenin, XSA Shiny, K Vanisree… - Renewable Energy with IoT … - researchgate.net
This article discusses a physical wireless device called Electroencephalogram (EEG) based
Drowsiness detection system. A dizziness monitor can effectively deter such casualties from …
Drowsiness detection system. A dizziness monitor can effectively deter such casualties from …