Results 31 to 40 of about 76,961 (216)

A Brain-Computer Interface based on Colour Dependent Visual Attention [PDF]

, 2022
In this thesis we designed a specific visual protocol for a new application in the brain-computer interface field.
Bon, Alvise
core  

Analogue mouse pointer control via an online steady state visual evoked potential (SSVEP) brain-computer interface [PDF]

, 2011
The steady state visual evoked protocol has recently become a popular paradigm in brain–computer interface (BCI) applications. Typically (regardless of function) these applications offer the user a binary selection of targets that perform correspondingly
Ramaswamy Palaniappan, John J Wilson, Wilson, John J., Palaniappan, Ramaswamy   +3 more
core   +1 more source

An EEG-based attention recognition method: fusion of time domain, frequency domain, and non-linear dynamics features

Frontiers in Neuroscience, 2023
IntroductionAttention is a complex cognitive function of human brain that plays a vital role in our daily lives. Electroencephalogram (EEG) is used to measure and analyze attention due to its high temporal resolution.
Di Chen, Di Chen, Haiyun Huang, Haiyun Huang, Xiaoyu Bao, Xiaoyu Bao, Jiahui Pan, Jiahui Pan, Yuanqing Li, Yuanqing Li   +9 more
doaj   +1 more source

Multiresolution analysis over simple graphs for brain computer interfaces [PDF]

, 2013
Objective. Multiresolution analysis (MRA) offers a useful framework for signal analysis in the temporal and spectral domains, although commonly employed MRA methods may not be the best approach for brain computer interface (BCI) applications.
Palaniappan, R, Gan, J Q, Asensio-Cubero, J, Gan, JQ, Palaniappan, Ramaswamy   +4 more
core   +1 more source

Brain-Computer-Interface controlled robot via RaspberryPi and PiEEG. [PDF]

, 2022
This paper presents Open-source software and a developed shield board for the Raspberry Pi family of single-board computers that can be used to read EEG signals.
ildar Rakhmatulin (10287974)
core   +1 more source

The Influence of Different EEG References on Scalp EEG Functional Network Analysis During Hand Movement Tasks

Frontiers in Human Neuroscience, 2020
Although scalp EEG functional networks have been applied to the study of motor tasks using electroencephalography (EEG), the selection of a suitable reference electrode has not been sufficiently researched.
Lipeng Zhang, Lipeng Zhang, Peng Wang, Peng Wang, Rui Zhang, Rui Zhang, Mingming Chen, Mingming Chen, Li Shi, Li Shi, Jinfeng Gao, Jinfeng Gao, Yuxia Hu, Yuxia Hu   +13 more
doaj   +1 more source

Revisiting embodiment for brain–computer interfaces

Human–Computer Interaction, 2023
Researchers increasingly explore deploying brain-computer interfaces (BCIs) for able-bodied users, with the motivation of accessing mental states more directly than allowed by existing body-mediated interaction. This motivation seems to contradict the long-standing HCI emphasis on embodiment, namely the general claim that the body is crucial for ...
Serim, Barış, Spapé, Michiel, Jacucci, Giulio   +2 more
openaire   +2 more sources

Brain–computer interface game applications for combined neurofeedback and biofeedback treatment for children on the autism spectrum [PDF]

, 2014
Individuals with autism spectrum disorder (ASD) show deficits in social and communicative skills, including imitation, empathy, and shared attention, as well as restricted interests and repetitive patterns of behaviors.
Lim, Theodore; id_orcid, Sandy Louchart, Theodore Lim, Pineda, Jaime A, Neil Suttie, Elisabeth V. C. Friedrich, Jaime A. Pineda, Aparajithan Sivanathan, Friedrich, Elisabeth V. C., Louchart, Sandy, Friedrich, Elisabeth VC, Suttie, Neil, Louchart, Sandy Jean-Jacques, Sivanathan, Aparajithan, Pineda, Jaime A., Lim, Theodore   +15 more
core   +1 more source

Detecting mental states by machine learning techniques: The Berlin Brain-computer interface [PDF]

, 2022
S.113-135The Berlin Brain-Computer Interface (BBCI) uses a machine learning approach to extract user-specific patterns from high-dimensional EEG-features optimized for revealing the user's mental state. Classical BCI applications are brain actuated tools
Blankertz, B., Fazli, S., Sannelli, C., Popescu, F., Tangermann, M., Dickhaus, T., Curio, G., Vidaurre, C., Danóczy, M., Müller, K.-R.   +9 more
core   +1 more source

Real-time EEG-based brain-computer interface to a virtual avatar enhances cortical involvement in human treadmill walking

Scientific Reports, 2017
Recent advances in non-invasive brain-computer interface (BCI) technologies have shown the feasibility of neural decoding for both users’ gait intent and continuous kinematics. However, the dynamics of cortical involvement in human upright walking with a
Trieu Phat Luu, Sho Nakagome, Yongtian He, Jose L. Contreras-Vidal   +3 more
doaj   +1 more source