journal article·2026-05-13Open access

Soft, Skin-Conformal Electronic Interfaces for Multimodal Biosignal Monitoring and Transcutaneous Stimulation

Md Saifur Rahman, Ziyu Zhu, Nicholas B. Abadie, Kailash Pillai, Adam Reyes, Luke McKinley, Creed G. Bielss, Salina Teng, Jie Zhao, Dimitry G. Sayenko, Limei Tian

ACS Applied Materials & Interfaces· Volume 18· Issue 18

Abstract

Soft, stable, and high-performance skin-electrode interfaces are essential for continuous electrophysiological recording and transcutaneous electrical stimulation. Conventional gel electrodes suffer from dehydration, unstable skin-electrode contact, reduced recording quality, and limited stimulation efficiency during prolonged use. This paper reports a soft, mixed-conducting nanocomposite electrode composed of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) integrated with hygroscopic and ionic dopants. The synergistic formulation enhances mixed ionic-electronic conduction, mechanical softness, and long-term hydration stability. A simple micromolding process enables scalable fabrication of conformal, freestanding electrodes that adhere seamlessly to the skin. The optimized composition achieves an excellent balance between conductivity and softness, exhibiting approximately a 20-fold lower interfacial impedance and a 2.6-fold higher charge injection capacity compared to gel electrodes. As a result, these nanocomposite electrodes deliver higher signal-to-noise ratios in electrocardiography and electromyography recordings and enhanced bioimpedance sensitivity and achieve a 2-fold expansion of the stimulation window. This nanocomposite design establishes a versatile materials platform for soft, durable, and high-fidelity bioelectronic interfaces, enabling advances in wearable sensing and neuromodulation technologies.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Neuroscience and Neural Engineering · Muscle activation and electromyography studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Biomedical Engineering, Center for Remote Health Technologies and Systems

Texas A&M University

Department of Electrical and Computer Engineering

Department of Neurosurgery, Center for Neuroregeneration

Houston Methodist Research Institute

Funding

Division of Engineering Education and Centers · National Institute of General Medical Sciences

References (46)

Show source-provided references
1. 10.1021/acs.chemrev.8b0057310.1021/acs.chemrev.8b00573 ↗
2. 10.1039/C7LC00914C10.1039/C7LC00914C ↗
3. 10.1002/adsr.20220004910.1002/adsr.202200049 ↗
4. 10.1161/CIRCULATIONAHA.106.18020010.1161/CIRCULATIONAHA.106.180200 ↗
5. 10.1002/9781119082934.ch0210.1002/9781119082934.ch02 ↗
6. Teplan M. · Meas. Sci. Rev. · 2002 · 2 · 1
7. 10.1016/j.nut.2024.11260110.1016/j.nut.2024.112601 ↗
8. 10.1073/pnas.250427812210.1073/pnas.2504278122 ↗
9. 10.1002/adma.20150415510.1002/adma.201504155 ↗
10. 10.1126/scirobotics.aap977010.1126/scirobotics.aap9770 ↗
11. 10.1002/adma.20150415010.1002/adma.201504150 ↗
12. 10.1126/science.118238310.1126/science.1182383 ↗
13. 10.1038/s41467-022-28027-y10.1038/s41467-022-28027-y ↗
14. 10.1016/j.device.2024.10067610.1016/j.device.2024.100676 ↗
15. 10.1021/acsnano.4c1553010.1021/acsnano.4c15530 ↗
16. 10.1126/science.120615710.1126/science.1206157 ↗
17. 10.1038/nnano.2017.12510.1038/nnano.2017.125 ↗
18. 10.1002/adma.20190192410.1002/adma.201901924 ↗
19. 10.1038/s41467-020-18503-810.1038/s41467-020-18503-8 ↗
20. 10.1002/adfm.20230268110.1002/adfm.202302681 ↗
21. 10.1038/s41551-019-0347-x10.1038/s41551-019-0347-x ↗
22. 10.1038/s41528-022-00170-y10.1038/s41528-022-00170-y ↗
23. 10.1002/advs.20190081310.1002/advs.201900813 ↗
24. 10.20517/ss.2022.0710.20517/ss.2022.07 ↗
25. 10.1016/j.device.2025.10078110.1016/j.device.2025.100781 ↗
26. 10.1038/s41467-021-25152-y10.1038/s41467-021-25152-y ↗
27. 10.1126/sciadv.ads441510.1126/sciadv.ads4415 ↗
28. 10.1021/acsami.1c0053710.1021/acsami.1c00537 ↗
29. 10.1016/j.polymer.2004.10.00110.1016/j.polymer.2004.10.001 ↗
30. 10.1023/A:101898412141510.1023/A:1018984121415 ↗
31. 10.1016/j.matt.2025.10240910.1016/j.matt.2025.102409 ↗
32. 10.70401/bmeh.2025.000410.70401/bmeh.2025.0004 ↗
33. 10.1109/10.8359110.1109/10.83591 ↗
34. 10.1002/adma.20130192110.1002/adma.201301921 ↗
35. 10.1002/admt.20230015810.1002/admt.202300158 ↗
36. 10.1002/admt.20230140710.1002/admt.202301407 ↗
37. Sodolski T. · Cardiol. J. · 2007 · 14 · 115
38. 10.1016/j.amjhyper.2004.10.00910.1016/j.amjhyper.2004.10.009 ↗
39. 10.1038/hr.2008.2010.1038/hr.2008.20 ↗
40. 10.1111/j.1469-7793.2000.t01-1-00263.x10.1111/j.1469-7793.2000.t01-1-00263.x ↗
41. 10.1016/j.neurot.2024.e0033010.1016/j.neurot.2024.e00330 ↗
42. 10.2147/MDER.S12346410.2147/MDER.S123464 ↗
43. 10.1101/2023.12.22.57311910.1101/2023.12.22.573119 ↗
44. 10.3389/fpsyg.2016.0146610.3389/fpsyg.2016.01466 ↗
45. Grimnes S. · 2008
46. 10.1016/j.jpain.2023.06.01510.1016/j.jpain.2023.06.015 ↗