Online Classification of Motor Imagery Using EEG and fNIRS: A Hybrid
Approach with Real Time HumanComputer Interaction
G Hirsch, M Dirodi, R Xu, P Reitner, C Guger International Conference on …, 2020 Springer
… For data acquisition the g.NAUTILUS FNIRS from g.tec was used a hybrid system … F., et al.: A
review on continuous wave functional nearinfrared spectroscopy and imaging instrumentation
and … of braincomputer interfaces that combine EEG and fNIRS for motor imagery tasks …
Motor Imagery Experiment Using BCI: An Educational Technology Approach
CAO Daza, FB Garrido, D Burgos Radical Solutions and Learning …, 2020 Springer
… Zhang, Yan, Hu, & Hong, 2017), since to develop MI “(…) the participants must learn to modulate
their mental rhythms to … The Nautilus g.tec 32 BCI equipped with elements such as 32electrode
headset, two modules (one to transmit and one to … 6.2.2.1 Motor Imagination Practice …
A novel deep learning approach with data augmentation to classify motor imagery signals
Z Zhang, F Duan, J SoleCasals… IEEE …, 2019 ieeexplore.ieee.org
… All EEG data are acquired by using a g.tec device (g.tec medical engineering GmbH … Morlet
wavelets transformation of the EEG signals has been proved effective in recent motor imagery
studies, including … First of all, we validated our algorithms on our experi mental dataset …
Adaptive Riemannian BCI for Enhanced Motor Imagery Training Protocols
D Freer, F Deligianni, GZ Yang 2019 IEEE 16th International …, 2019 ieeexplore.ieee.org
… II. METHODS A. Datasets 1) Data Collection: For this study, we collected data from 3 healthy
volunteers, undergoing 4class BCI motor imagery training sessions … 12], and the protocol can
be seen in Figure 1. Data was recorded using a 32channel wet g.Nautilus (g.tec) EEG cap …
A BCI System with Motor Imagery Based on Bidirectional LongShort Term
Memory
JS Lin, BH She IOP Conference Series: Materials Science and …, 2020 iopscience.iop.org
… Being one of a topic in the research field of BCI, motor imagery (MI) emulates a given mental
activity, eg … 6. Experimental Results The EEG signals were extracted on locations C3, Cz and C4
in this paper and Emotiv EPOC chip, g.tec dry electrode and Ultracortex …
An EEG BrainComputer Interface to Classify Motor Imagery Signals
MK Andrade, MA de Santana, G Moreno… Biomedical Signal …, 2020 Springer
… In this chapter, the performance of an Imagery EEGbased BCI engine was accessed by applying
Wavelet transform to … Motor imagery combined to artificial intelligence techniques to control
interfaces … EEG was recorded using a g.tec g.Hiamp amplifier at a sampling rate of 256 Hz …
Review on motor imagery based BCI systems for upper limb poststroke
neurorehabilitation: From designing to application
MA Khan, R Das, HK Iversen… Computers in Biology and …, 2020 Elsevier
… Computers in Biology and Medicine. Review on motor imagery based BCI systems
for upper limb poststroke neurorehabilitation: From designing to application. Author
links open overlay panelMuhammad AhmedKhan a Rig …
The effects of handedness on sensorimotor rhythm desynchronization and
motor imagery BCI control
D Zapała, E ZabielskaMendyk, P Augustynowicz… Scientific reports, 2020 nature.com
… 26 , participants with a similar temporal profile, obtained in the mental chronometry task, showed
both higher BCI abilities and stronger lateralization of sensorimotor rhythms during motor imagery.
In fact, SMR lateralization is a major issue in the area of motor cognition research …
An advanced bispectrum features for EEGbased motor imagery classification
L Sun, Z Feng, N Lu, B Wang, W Zhang Expert Systems with Applications, 2019 Elsevier
… AlvarezMeza, VelasquezMartinez, and CastellanosDominguez (2015) makes use of CSP and
motor imagery discrimination using feature relevance analysis (MIDFR) to improve … G.tec (Guger
Technologies OEG Austria) BCI device was utilized to collect MIrelated EEG signals …
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