A Review on Flexible Electronic Sensors for Brain Monitoring

Yiwei Chen

doi:10.54254/2753-8818/2025.AU28732

Theoretical and Natural ScienceOpen access

A Review on Flexible Electronic Sensors for Brain Monitoring

Research Article

Open Access

A Review on Flexible Electronic Sensors for Brain Monitoring

Yiwei Chen ^1*

¹ Tianjin University

^*Corresponding author: liam_tchen@tju.edu.cn

Published on 28 October 2025

TNS Vol.147

ISSN (Print): 2753-8826

ISSN (Online): 2753-8818

ISBN (Print): 978-1-80590-489-2

ISBN (Online): 978-1-80590-490-8

Download Cover

Abstract

Flexible electronic sensors, due to their mechanical compliance with soft tissues and excellent biocompatibility, have demonstrated unique advantages in neuroscience research and clinical applications in recent years. Compared with traditional rigid electrodes, flexible sensors show greater potential in long-term stability, large-area coverage, and multimodal integration, thereby meeting the diverse needs of neural signal acquisition and functional monitoring. This review summarizes the latest advances in the application of flexible electronics for brain monitoring, covering electrophysiological signal acquisition, neurotransmitter detection, multimodal and region-synchronized recording, and clinical rehabilitation applications. It further discusses critical aspects influencing performance and applications, including material selection, device design, circuit integration, energy supply, and mechanical modeling. On this basis, the challenges and prospects regarding long-term stability, data processing, multimodal integration, and clinical translation are analyzed. Overall, flexible brain sensors are gradually progressing from laboratory validation to systematic applications, and their development is expected to exert profound impacts on neuroscience research, disease diagnosis and treatment, and intelligent rehabilitation in the future.

Keywords:

Flexible electronic sensors, Brain monitoring, Electrophysiological recording, Neurotransmitter detection, Multimodal integrated sensors

View PDF

References

[1]. Das, R., Tiwari, A., Prakash, S., & Kumar, S. (2020). Biointegrated and wirelessly powered implantable brain devices: A review. IEEE Transactions on Biomedical Circuits and Systems, 14(2), 343–358.

[2]. Pimenta, S., Ribeiro, F., & Silva, C. (2024). Flexible neural probes: A review of the current advantages, drawbacks, and future demands. Journal of Zhejiang University–SCIENCE B, 25(7), 571–595.

[3]. Chen, Y., Liu, Y., Zhang, Y., & Wang, H. (2021). How is flexible electronics advancing neuroscience research? Biomaterials, 268, 120559.

[4]. Zhou, N., Liu, X., & Hu, Y. (2020). Recent advances in the construction of flexible sensors for biomedical applications. Biotechnology Journal, 15(12), e2000094.

[5]. Vargo, S., Dyer, A., & Hwang, S. (2023). Smart Dura: A monolithic optoelectrical surface array for neural interfacing with primate cortex. Proceedings of the IEEE/EMBS Conference on Neural Engineering (NER).

[6]. Park, H., Lee, J., & Kim, D. (2022). A miniaturized 256-channel neural recording interface with area-efficient hybrid integration of flexible probes. IEEE Transactions on Biomedical Engineering, 69(1), 334–346.

[7]. Zeng, N., Yang, Y., & Xie, L. (2023). A wireless, mechanically flexible, 25 μm-thick, 65, 536-channel subdural surface recording and stimulation array. IEEE Symposium on VLSI Technology & Circuits (Proceedings).

[8]. Huang, Z., Zhang, Q., & Wang, J. (2022). Actively multiplexed μECoG brain implant system with incremental-ΔΣ ADCs employing bulk-DACs. IEEE Transactions on Biomedical Circuits and Systems, 16(2), 233–246.

[9]. Carlino, G., Min, H., & Kwon, Y. (2023). Highly-digital 0.0018-mm²/channel multiplexed neural frontend with time-based incremental ADC for implantable brain interfaces. IEEE Journal of Solid-State Circuits, 58(4), 1021–1034.

[10]. Ling, W., Wang, X., & Yang, J. (2024). Miniaturized implantable fluorescence probes integrated with metal–organic frameworks for deep brain neurotransmitter detection. ACS Nano, 18(15), 10596–10608.

[11]. Ling, W., Zhang, Q., & Chen, H. (2020). Flexible electronics and materials for synchronized stimulation and monitoring in multi-encephalic regions. Advanced Functional Materials, 30(32), 2002644.

[12]. Ren, X., Li, Y., & Zhao, H. (2025). Flexible tactile sensors with self-assembled cilia based on magnetoelectric composites. ACS Applied Materials & Interfaces, 17(4), 6936–6947.

[13]. Vinoj, P. G., Menon, S., & Das, R. (2019). Brain-controlled adaptive lower limb exoskeleton for rehabilitation of post-stroke paralyzed patients. IEEE Access, 7, 132628–132648.

[14]. Amri, M. M. (2022). Recent trends in the reconfigurable intelligent surfaces (RIS): Active RIS to brain-controlled RIS. In Proc. 2022 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT) (pp. 299–304).

[15]. Agarwal, K., Sharma, R., & Gupta, P. (2017). Wireless power transfer strategies for implantable bioelectronics. IEEE Reviews in Biomedical Engineering, 10, 136–161.

References

[3]. Chen, Y., Liu, Y., Zhang, Y., & Wang, H. (2021). How is flexible electronics advancing neuroscience research? Biomaterials, 268, 120559.

[4]. Zhou, N., Liu, X., & Hu, Y. (2020). Recent advances in the construction of flexible sensors for biomedical applications. Biotechnology Journal, 15(12), e2000094.

[12]. Ren, X., Li, Y., & Zhao, H. (2025). Flexible tactile sensors with self-assembled cilia based on magnetoelectric composites. ACS Applied Materials & Interfaces, 17(4), 6936–6947.

[13]. Vinoj, P. G., Menon, S., & Das, R. (2019). Brain-controlled adaptive lower limb exoskeleton for rehabilitation of post-stroke paralyzed patients. IEEE Access, 7, 132628–132648.

[15]. Agarwal, K., Sharma, R., & Gupta, P. (2017). Wireless power transfer strategies for implantable bioelectronics. IEEE Reviews in Biomedical Engineering, 10, 136–161.

Cite this article

Chen,Y. (2025). A Review on Flexible Electronic Sensors for Brain Monitoring. Theoretical and Natural Science,147,27-32.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICBioMed 2025 Symposium: AI for Healthcare: Advanced Medical Data Analytics and Smart Rehabilitation

ISBN: 978-1-80590-489-2(Print) / 978-1-80590-490-8(Online)

Editor: Alan Wang

Conference website: https://2025.icbiomed.org/auckland.html

Conference date: 17 October 2025

Series: Theoretical and Natural Science

Volume number: Vol.147

ISSN: 2753-8818(Print) / 2753-8826(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).