Materials and microsystems for stable and high-efficiency brain-computer interfaces in signal recording

npj Biosensing 2026 Open access

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Authors: Qi Chen, Ningge Huang, Chuanjie Tong, Pengchuan Liu, Shaojun Que, Huize Xue, Xiao Xiao, Enming Song
DOI: 10.1038/s44328-026-00109-7
Cited by: 1
References: 275

Abstract

Brain–computer interfaces enable high-resolution neural recording, yet chronic performance is constrained by interacting factors across materials, electrode and array architectures, and microsystem integration. This review examines how these cross-level design layers collectively shape recording stability, efficiency, and scalability. We summarize representative degradation patterns, strategies for improving long-term performance, and recent advances in integrated systems, and outline design principles for clinically scalable and reliable neural interfaces.

Fields of Study & Subjects

Neuroscience and Neural Engineering Neural dynamics and brain function EEG and Brain-Computer Interfaces

Publication details

Journal / source
npj Biosensing
Publisher
Springer Science and Business Media LLC
Volume
3
Issue
1
Publication date
29 June 2026
Language
EN