BCIJelly: An integrated ecosystem for brain-computer interface research
Brain-computer interface (BCI) research relies on multistage computational pipelines, yet progress remains constrained by fragmented data formats, heterogeneous decoder implementations and hardware-specific deployment toolchains, and researchers lack an integrated workflow. Here, we fill this gap with BCIJelly, a unified computational ecosystem that integrates 18 curated BCI datasets, 15 benchmark decoders and an algorithmic library of 80 reusable modules, an automated architecture search (AAS) procedure, and hardware-aware deployment through the toChip pipeline within a single Python framework. AAS constructs task-specific decoders without manual architecture design. It is further extend...
| Authors | Liyuan Han, Xinrui Yang, Tianyu Zheng et al. |
|---|---|
| Primary category | cs.HC |
| Published | 6 July 2026 |
| Last updated at source | 6 July 2026 |
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