Evidence map›Paper›PMID 40710074›Full record

ReviewBiosensors2025

Recent Advances in Flexible Sensors for Neural Interfaces: Multimodal Sensing, Signal Integration, and Closed-Loop Feedback.

Siyi Yang, Xiujuan Qiao, Junlong Ma, Zhihao Yang, Xiliang Luo, Zhanhong Du

Abstract readReview
In one paragraph

Review in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Siyi YangThe Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Xiujuan QiaoKey Laboratory of Optic-Electric Sensing and Analytical Chemistry for Life Science, Ministry of Education, College of Chemistry and Molecular Engineering, Qingdao University of Science and Technology, Qingdao 266042, China.
Junlong MaThe Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Zhihao YangThe Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Xiliang LuoKey Laboratory of Optic-Electric Sensing and Analytical Chemistry for Life Science, Ministry of Education, College of Chemistry and Molecular Engineering, Qingdao University of Science and Technology, Qingdao 266042, China.ORCID 0000-0001-6075-7089
Zhanhong DuThe Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.ORCID 0000-0001-6535-1424

Funding

Key-Area Research and Development Program of Guangdong Province 2018B030331001 and 2018B030338001National Key R&D Pro gram of China 2020YFC2008503National Special Support Grant W02020453Natural Science Foundation of China Grants 31930047NSFC-Guangdong Joint Fund U20A6005Scientific and Technological Innovation 2030 Key Project 2022ZD0209800Shenzhen Infrastructure for Brain Analysis and Modeling ZDKJ20190204002the Strategic Priority Research Program of Chinese Academy of Science XDB32030103
6 · The paper itself

Abstract

The rapid advancement of flexible sensor technology has profoundly transformed neural interface research, enabling multimodal information acquisition, real-time neurochemical and electrophysiological signal monitoring, and adaptive closed-loop regulation. This review systematically summarizes recent developments in flexible materials and microstructural designs optimized for enhanced biocompatibility, mechanical compliance, and sensing performance. We highlight the progress in integrated sensing systems capable of simultaneously capturing electrophysiological, mechanical, and neurochemical signals. The integration of carbon-based nanomaterials, metallic composites, and conductive polymers with innovative structural engineering is analyzed, emphasizing their potential in overcoming traditional rigid interface limitations. Furthermore, strategies for multimodal signal fusion, including electrochemical, optical, and mechanical co-sensing, are discussed in depth. Finally, we explore future perspectives involving the convergence of machine learning, miniaturized power systems, and intelligent responsive materials, aiming at the translation of flexible neural interfaces from laboratory research to practical clinical interventions and therapeutic applications.

Indexed as

Biosensing TechniquesFeedbackHumansNanostructuresclosed-loop systemselectrochemical detectionflexible sensorsmultimodal sensingnanomaterialsneural interfaces

Identifiers

PMID40710074
PMCPMC12293567

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.