Paper Info
Title
An Ssvep-Bci In Augmented Reality
Abstract
Steady-State Visual Evoked Potentials (SSVEP) based Brain-Computer Interface (BCI) has achieved very high information transmission rate (ITR), but its portability and fundamental interactions with the surrounding environment were limited. The combination of Augmented Reality (AR) and BCI is expected to solve these problems. In this paper, we combined AR with the SSVEP-BCI to build a more portable and natural BCI system in Microsoft HoloLens. We designed the AR-BCI system and studied the influence of different algorithms on the system performance. The analysis of SSVEP signals collected in AR environment shows that the extended filter bank canonical correlation analysis was better than task-related component analysis. The average recognition accuracy and ITR obtained by using Electroencephalography (EEC) data of 1s, 1.5s, and 2s length were 87.7%, 95.4%, 97.6% and 64.6 bit/min, 62.9 bit/min, 55.6 bit/min, respectively. Compared with the existing AR-BCI studies, the ITR has been greatly improved in this study.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8857859
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Computer vision,Computer science,Canonical correlation,Filter bank,Brain–computer interface,Information transmission,Augmented reality,Software portability,Artificial intelligence,Component analysis
Conference
2019
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Pengxiao Liu101.01
Yufeng Ke200.68
Jiale Du301.01
Wentao Liu400.34
Linghan Kong501.01
Ningci Wang601.01
Xingwei An72111.88
Dong Ming810551.47