Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.16471 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917963443994624 |
|---|---|
| author | Wang, Yifan Jiang, Cheng Li, Chenzhong |
| author_facet | Wang, Yifan Jiang, Cheng Li, Chenzhong |
| contents | Brain-Computer Interface (BCI) technology facilitates direct communication between the human brain and external devices, representing a substantial advancement in human-machine interaction. This review provides an in-depth analysis of various BCI paradigms, including classic paradigms, current classifications, and hybrid paradigms, each with distinct characteristics and applications. Additionally, we explore a range of signal acquisition methods, classified into non-implantation, intervention, and implantation techniques, elaborating on their principles and recent advancements. By examining the interdependence between paradigms and signal acquisition technologies, this review offers a comprehensive perspective on how innovations in one domain propel progress in the other. The goal is to present insights into the future development of more efficient, user-friendly, and versatile BCI systems, emphasizing the synergy between paradigm design and signal acquisition techniques and their potential to transform the field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_16471 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Review of Brain-Computer Interface Technologies: Signal Acquisition Methods and Interaction Paradigms Wang, Yifan Jiang, Cheng Li, Chenzhong Human-Computer Interaction Artificial Intelligence J.3 Brain-Computer Interface (BCI) technology facilitates direct communication between the human brain and external devices, representing a substantial advancement in human-machine interaction. This review provides an in-depth analysis of various BCI paradigms, including classic paradigms, current classifications, and hybrid paradigms, each with distinct characteristics and applications. Additionally, we explore a range of signal acquisition methods, classified into non-implantation, intervention, and implantation techniques, elaborating on their principles and recent advancements. By examining the interdependence between paradigms and signal acquisition technologies, this review offers a comprehensive perspective on how innovations in one domain propel progress in the other. The goal is to present insights into the future development of more efficient, user-friendly, and versatile BCI systems, emphasizing the synergy between paradigm design and signal acquisition techniques and their potential to transform the field. |
| title | A Review of Brain-Computer Interface Technologies: Signal Acquisition Methods and Interaction Paradigms |
| topic | Human-Computer Interaction Artificial Intelligence J.3 |
| url | https://arxiv.org/abs/2503.16471 |