Wavelet design by means of multi-objective GAs for motor imagery EEG analysis [PDF]
, 2011 Wavelet-based analysis has been broadly used in the study of brain-computer interfaces (BCI), but in most cases these wavelet functions have not been designed taking into account the requirements of this field.
Asensio-Cubero, J +3 more
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Integrating EEG and MEG signals to improve motor imagery classification in brain-computer interfaces
, 2018 We propose a fusion approach that combines features from simultaneously recorded electroencephalographic (EEG) and magnetoencephalographic (MEG) signals to improve classification performances in motor imagery-based brain-computer interfaces (BCIs).
Bassett, Danielle S. +6 more
core +3 more sources
Brain-Computer Interfaces for Internet of Things
Proceedings, 2018 A brain-computer interface for controlling elements commonly used at home is presented in this paper. It includes the electroencephalography device needed to acquire signals associated to the brain activity, the algorithms for artefact reduction and ...
Francisco Laport +3 more
doaj +1 more source
Annals of Translational Medicine, 2020 Brain-computer interfaces (BCIs) have shown great prospects as real-time bidirectional links between living brains and actuators. Artificial intelligence (AI), which can advance the analysis and decoding of neural activity, has turbocharged the field of ...
Xiayin Zhang +10 more
semanticscholar +1 more source
Advanced Functional Materials, EarlyView.This study demonstrated single‐crystalline PbTiO3‐based memristors with atomically sharp interfaces, well‐ordered lattices, and minimal lattice mismatch. The devices exhibited an ON/OFF ratio exceeding 105, high stability, and rich resistance‐state modulation.
Haining Li +7 more
wiley +1 more source
Comparing EEG patterns of actual and imaginary wrist movements - a machine learning approach [PDF]
, 2005 Our goal is to develop an algorithm for feature extraction and classification to be used in building brain-computer interfaces. In this paper, we present preliminary results for classifying EEG data of imaginary wrist movements.
Conway, B.A., Lakany, H.
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Enheduanna – A Manifesto of Falling: first demonstration of a live brain-computer cinema performance with multi-brain BCI interaction for one performer and two audience members [PDF]
, 2016 The new commercial-grade Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) have led to a phenomenal development of applications across health, entertainment and the arts, while an increasing interest in multi-brain interaction has ...
Adorno T. W. +16 more
core +2 more sources
Using Multiple Decomposition Methods and Cluster Analysis to Find and Categorize Typical Patterns of EEG Activity in Motor Imagery Brain–Computer Interface Experiments [PDF]
, 2020 Alexander Frolov +6 more
openalex +1 more source
Advanced Functional Materials, EarlyView.This study presents the BioCLEAR system, a highly transparent and conductive neural electrode array composed of silver nanowires (AgNWs) and doped PEDOT:PSS, enabling neural recordings with minimal optical artifacts. When integrated with a GRIN lens, this cost‐effective neural implant allows simultaneous electrophysiological recording and GCaMP6‐based ...
Dongjun Han +17 more
wiley +1 more source
Multi-objective particle swarm optimization for channel selection in brain-computer interfaces [PDF]
, 2009 This paper presents a novel application of a multi-objective particle swarm optimization (MOPSO) method to solve the problem of effective channel selection for Brain-Computer Interface (BCI) systems.
Gan, JQ, Hasan, BAS
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