Evaluation of feature selection in Brain Computer Interface

Aswinseshadri, K.; Bai, Thulasi

doi:10.1109/aeeicb.2016.7538404

Cited by 1 publication

(2 citation statements)

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“…Most BCI systems rely on three typical BCI paradigms: Motor Imagery (MI), P300, and steady-state visual-evoked potentials (SSVEP). At the same time, in the process of brain signal acquisition, we can collect electroencephalogram (EEG), near infrared spectroscopy (NIRS), and other signals through non-invasive devices, or use invasive devices to collect electrocartography (ECoG) [ 21 , 22 ] and local field potential(LFP) [ 23 ] signals. The personalized processing of brain signals includes preprocessing, feature extraction and selection, and classification.…”

Section: Personalized Bcimentioning

confidence: 99%

“…Because different BCI users have different needs, capability characteristics, and status characteristics, they will have corresponding preferences for brain signal acquisition methods. For example, some BCI users may prefer to choose wearable EEG earphones, while some BCI users may only use implantable BCIs to collect ECoG [ 21 , 22 ] or Spikes/LFP signals [ 23 ].…”

Section: Personalized Bci Design Research and Developmentmentioning

confidence: 99%

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Personalized Brain–Computer Interface and Its Applications

Gong

Nan

et al. 2022

JPM

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Brain–computer interfaces (BCIs) are a new technology that subverts traditional human–computer interaction, where the control signal source comes directly from the user’s brain. When a general BCI is used for practical applications, it is difficult for it to meet the needs of different individuals because of the differences among individual users in physiological and mental states, sensations, perceptions, imageries, cognitive thinking activities, and brain structures and functions. For this reason, it is necessary to customize personalized BCIs for specific users. So far, few studies have elaborated on the key scientific and technical issues involved in personalized BCIs. In this study, we will focus on personalized BCIs, give the definition of personalized BCIs, and detail their design, development, evaluation methods and applications. Finally, the challenges and future directions of personalized BCIs are discussed. It is expected that this study will provide some useful ideas for innovative studies and practical applications of personalized BCIs.

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Section: Personalized Bcimentioning

confidence: 99%