.png){kind=icon}
Return
TrustBCI: A Trustworthy Platform for Collaborative Brain-Computer Interface Data Exchange
.png){kind=icon}
PRE
AI
DOI：10.14778/3827998.3828139.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
High-quality brain-computer interface (BCI) datasets are essential for developing accurate and generalizable BCI models, but in practice they are often isolated across institutions, heterogeneous in format, and difficult to share under privacy constraints. Existing BCI data platforms address only part of this problem, and do not provide unified support for data contribution, privacy-preserving computation, and downstream use. To this end, we present TrustBCI, a trustworthy platform for collaborative BCI data exchange. TrustBCI combines three key components: assetization tools for preparing raw BCI datasets, incentive mechanisms for sustained data contribution, and privacy-aware services for using protected data without exposing raw records. Our demonstration focuses on two representative workflows: controllable data synthesis and privacy-preserving data query. These workflows show how TrustBCI supports both dataset-level and query-level access to protected BCI data through a functional web prototype. More broadly, TrustBCI illustrates how protected domain data can be turned into usable data services through a unified data platform.
Journal
P
IF:
3.3
Papers:
563
Citations:
1.2W
Organization
No organization information available
Cited Papers
No cited papers available