Data‐Driven Design of Self‐Adhesive Epidermal Electrodes and Sensors
Xuan Li, Shilei Wang, Milad Razbin, Danish Tahir, Chen Sang, Shuhua Peng, Markus Müllner, Wenlong Cheng, Wei Chen, Chun Hui Wang, Shuying Wu · 2026
Read Data‐Driven Design of Self‐Adhesive Epidermal Electrodes and Sensors by Xuan Li, Shilei Wang, Milad Razbin, Danish Tahir, Chen Sang, Shuhua Peng, Markus Müllner, Wenlong Cheng, Wei Chen, Chun Hui Wang, Shuying Wu (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13426098.txt.
Description
Li and colleagues reported in 2026 on a data-driven way to design skin-worn electrodes and sensors that stick on by themselves and stretch with the body. Such devices mix several materials, each adding electrical or mechanical traits, and design has long relied on slow trial and error. The team used a neural network model, a form of machine learning, plus a genetic search method to pick better material mixes for set goals.
Li's tuned electrode stretched to about 177 percent of its length, held firm grip on skin, and kept contact resistance low. It recorded muscle, heart, and brain signals more steadily over time than standard gel electrodes sold for clinical use. A second mix, tuned for pressure sensing, stretched to about 153 percent and sensed strain well enough for motion tracking and a human-machine control demo. The method suits application-specific wearable design.
Catalog record
| CREATOR | Xuan Li, Shilei Wang, Milad Razbin, Danish Tahir, Chen Sang, Shuhua Peng, Markus Müllner, Wenlong Cheng, Wei Chen, Chun Hui Wang, Shuying Wu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |