Towards a Brain-Computer Interface Framework for Multi-Party Robot Applications

被引：0

作者：

Lewis, Myles ^{[1
]}

Junkins, Wesley ^{[1
]}

Setty, Chanakya ^{[1
]}

Crawford, Chris ^{[1
]}

机构：

[1] Univ Alabama, Tuscaloosa, AL 35487 USA

来源：

PROCEEDINGS OF THE 2024 ACM SOUTHEAST CONFERENCE, ACMSE 2024 | 2024年

关键词：

Brain-Robot Interaction; Brain-Computer Interface; Competitive BCI;

D O I：

10.1145/3603287.3656157

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Studies featuring electroencephalography (EEG)-based robotic systems controlled by the brain have predominantly concentrated on single-user applications. However, there is a growing interest in exploring novel ways to engage users with Brain-Computer Interfaces (BCIs). This research contributes an EEG-Based multi-party closedloop architecture built using the NeurosityT SDK. Furthermore, this work extends knowledge regarding how to use consumer-grade EEG tools to implement a multi-party BCI application. Our observations suggest that while new SDKs may enhance our ability to create novel BCI applications, additional research is needed to validate this approach further.

引用

页码：309 / 310

页数：2