| Autor: |
Buron Leo, Erbslöh Andreas, Ur-Rehman Zia, Klaes Christian, Seidl Karsten, Schiele Gregor |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Current Directions in Biomedical Engineering, Vol 9, Iss 1, Pp 471-474 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2364-5504 |
| DOI: |
10.1515/cdbme-2023-1118 |
| Popis: |
This paper presents a software-based Python framework for developing future AI-enhanced end-to-end Brain-Computer-Interfaces (BCI). This framework contains modules from the emulated analogue front-end and from neural signal pre-processing for invasive neural applications. These modules can be assembled into several pipeline versions for evaluation and benchmarking. The aim of this framework is to accelerate the development of BCIs due to system-wide optimizations in order to set the requirements for hardware development without prior knowledge on the basis of accuracy (recall and precision) and latency. In the next step, the pipeline can be optimised for on-chip and embedded execution. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
