.png){kind=icon}
.png){kind=icon}
Return
Creating a Roadmap for Pediatric Implanted Brain-Computer Interfaces
.png){kind=icon}
PRE
AI
DOI：10.1177/15459683261481764.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Background:
Implanted brain-computer interfaces (iBCIs) can record signals directly from the brain and translate them into computer commands continuously, at high speed and fidelity. Over 150 people worldwide have been implanted with an iBCI, and this number is expected to increase rapidly as iBCIs become commercially available. Despite the progress that is being made in the development of safe, wireless, and highly effective iBCIs, none of these have been implemented in youth or adults with pediatric-onset conditions.
Objective:
Pediatric-onset conditions, such as Cerebral Palsy (CP), represent a large proportion of the global burden of complex and severe disability. Since affected individuals, particularly youth, will likely benefit significantly from iBCIs, they should not be left behind in technological progress that would be life-changing. We outlined the evidence gaps, steps required, and arguments for greater focus on this population in iBCI research and development.
Methods:
Here, we present the result of two years of cumulative effort, combining expert opinions and findings from multiple transdisciplinary engagement sessions, including the first International Virtual Summit on Implanted BCIs for Children with Complex Needs, follow-up themed workgroup sessions, and a final in-person workshop held at the 11th International BCI Society Meeting.
Results:
We established a world-first visionary, community-and-partner-engaged roadmap for the design, development, and implementation of iBCIs for youth with CP to meaningfully interact with the world.
Conclusions:
Developing iBCI systems for youth with CP requires a fundamental shift toward child‑centric neuroscience, engineering, and user‑driven design rather than adapting adult‑oriented technologies.
Journal
IF:
3.7
Papers:
2.0K
Citations:
6.9K