Results 81 to 90 of about 90,513 (199)

RECOGNITION OF COGNITIVE POTENTIALS TO THE TARGET STIMULI IN THE BRAIN-COMPUTER INTERFACE ON THE BASIS OF THE ENSEMBLE OF CLASSIFIERS

Наука и инновации в медицине, 2016
Background. A number of studies have been done on detection of human visual attention focus by means of P300 brain-computer interfaces (BCI). However, the performance of interfaces on P300 is still low, since this technique requires the repeated ...
D A Kirjanov, A Y Kaplan
doaj   +1 more source

INTEGRAL ALGORITHM OF P300 RECOGNITION IN EEG FOR BCI APPLICATION

Наука и инновации в медицине, 2016
Aim - developing the integral algorithm of recognition of the evoked potential (ERP-response) to a target visual stimulus and testing of the proposed algorithm on the wireless 5-channel electroencephalograph Emotiv Insight with “dry” electrodes ...
S N Agapov, V A Bulanov, A V Zakharov, M S Sergeeva, V F Pyatin   +4 more
doaj   +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
core  

Airborne Ultrasonic Tactile Display BCI

, 2015
This chapter presents results of our project, which studied whether contactless and airborne ultrasonic tactile display (AUTD) stimuli delivered to a user's palms could serve as a platform for a brain computer interface (BCI) paradigm.
Hamada, Katsuhiko, Mori, Hiromu, Rutkowski, Tomasz M., Shinoda, Hiroyuki   +3 more
core   +1 more source

Caso de estudio del desarrollo de un videojuego basado en BCI

Lámpsakos, 2019
Este artículo describe la metodología de formación por proyectos del Servicio Nacional de Aprendizaje–SENA y su integración con un proyecto de investigación aplicada.
Erika Juliett Restrepo Zapata, Alejandro Díaz Jaramillo, Isabel Margarita Vega Rodríguez, Sandra Milena Velásquez Restrepo   +3 more
doaj   +1 more source

Cross-BCI, A Cross-BCI-Paradigm Classifica-tion Model Towards Universal BCI Applications

Classification models used in brain-computer interface (BCI) are usually designed for a single BCI paradigm. This requires the redevelopment of the model when applying it to a new BCI paradigm, resulting in repeated costs and effort. Moreover, less complex deep learning models are desired for practical usage, as well as for deployment on portable ...
Zhou, Gaojie, Li, Junhua
openaire   +2 more sources

MagCPP: A C++ toolbox for Combining Neurofeedback with Magstim transcranial magnetic stimulators

Current Directions in Biomedical Engineering, 2020
Transcranial magnetic stimulation (TMS) is an established method to treat various neurological diseases, such as depression, Alzheimer’s disease, and tinnitus.
Oppermann Hannes, Wichum Felix, Haueisen Jens, Klemm Matthias, Esch Lorenz   +4 more
doaj   +1 more source

The Strathclyde Brain Computer Interface (S-BCI) : the road to clinical translation [PDF]

, 2011
In this paper, we summarise the state of development of the Strathclyde Brain Computer Interface (S-BCI) and what has been so far achieved. We also briefly discuss our next steps for translation to spinal cord injured patients and the challenges we ...
Allan, David B., Conway, Bernard A, Lakany, Heba   +2 more
core  

Review on the Use of Brain Computer Interface Rehabilitation Methods for Treating Mental and Neurological Conditions

Journal of Integrative Neuroscience
This review provides a comprehensive examination of recent developments in both neurofeedback and brain-computer interface (BCI) within the medical field and rehabilitation.
Vladimir Khorev, Semen Kurkin, Artem Badarin, Vladimir Antipov, Elena Pitsik, Andrey Andreev, Vadim Grubov, Oxana Drapkina, Anton Kiselev, Alexander Hramov   +9 more
doaj   +1 more source

EEG signal ANFIS classification for motor imagery for different joints of the same limb

Vojnotehnički Glasnik
Introduction: The experimental area of brain-computer interfaces (BCIs) is expanding to include movement actions, which play a crucial part in deciphering cognitive processes.
Ihab A. Satam
doaj   +1 more source