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ORIGINAL RESEARCH article

Front. Bioeng. Biotechnol.

Sec. Nanobiotechnology

Volume 13 - 2025 | doi: 10.3389/fbioe.2025.1639630

This article is part of the Research TopicAdvanced Biocompatible Piezoelectrics: Synthesis, Characterization, and ApplicationsView all 5 articles

Application of Artificial Muscle e-Rubber for Healthcare Sensing: Verification of Measurement Properties as a Smart Insole

Provisionally accepted
Hidemasa  YonedaHidemasa Yoneda1*Takashi  YamagaTakashi Yamaga2Takeshi  FujiwaraTakeshi Fujiwara3Yoko  KomoriYoko Komori3Masatoshi  ShimadaMasatoshi Shimada3Yuki  KatoYuki Kato4Shintaro  OyamaShintaro Oyama5Shingo  ShimodaShingo Shimoda5Michiro  YamamotoMichiro Yamamoto6Hirata  HitoshiHirata Hitoshi5
  • 1Nagoya University Hospital, Nagoya, Japan
  • 2Tsushima municipal hospital, Tsuhima, Japan
  • 3Toyoda Gosei Kabushiki Kaisha, Kiyosu, Japan
  • 4Chunichi Hospital, Nagoya, Japan
  • 5Nagoya Daigaku, Nagoya, Japan
  • 6Nagoya Daigaku Igakubu Fuzoku Byoin, Nagoya, Japan

The final, formatted version of the article will be published soon.

Electroactive polymer (EAP) artificial muscles are gaining attention in robotic control technologies. Among them, the development of self-sensing actuators that integrate sensing mechanisms within artificial muscles is highly anticipated. This study aimed to evaluate the accuracy and precision of the sensing capabilities of the e-Rubber (eR), an artificial muscle developed by Toyoda Gosei Co., Ltd., and to investigate its potential for healthcare sensing applications such as smart insoles. The objective was to transform the eR into a thin capacitor and estimate the applied load by sensing minute changes in the capacitance. The changes in the EAP dielectric constant, electrode area, and inter-electrode distance, all of which define the capacitance, are non-linear functions. The relationship with the external force also exhibits nonlinearity. To address this issue, we experimentally plotted the load and capacitance changes and derived a regression equation. We evaluated the sensing characteristics of both a stand-alone sensor and a sensor embedded in a smart insole, followed by a precision verification of the load estimation using the derived regression equation. Load-capacitance changes were measured up to 400 N at three conditions: 23°C and 50% humidity, 40°C and 50% humidity, and 40°C and 80% humidity. For the standalone sensor, the coefficient of variation was less than 1.25% and the confidence interval was 0.25%, indicating high precision. However, for the sensor embedded within the insole housing, the coefficient of variation increased to less than 8%, and the confidence interval was 1.5%, likely owing to the influence of gaps within the insole structure. Regarding the load estimation equation, a 5th-order polynomial approximation (R² > 0.999) demonstrated the best fit, indicating that it is sufficiently accurate for healthcare sensing applications. Although capacitance-based sensors are increasingly being used in biomedical monitoring for pressure and load measurements owing to their durability and high sensitivity, their primary challenge lies in the nonlinearity of the sensing results. Although this challenge also exists for capacitance sensors utilizing artificial muscles, our study shows that developing a regression equation based on the experimental relationship between the load and capacitance changes can yield sufficient precision for practical healthcare applications.

Keywords: e-Rubber, Artificial muscle, Capacitance sensor, Dielectric Elastomer, Smart insole, Sensing for Healthcare

Received: 02 Jun 2025; Accepted: 07 Aug 2025.

Copyright: © 2025 Yoneda, Yamaga, Fujiwara, Komori, Shimada, Kato, Oyama, Shimoda, Yamamoto and Hitoshi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Hidemasa Yoneda, Nagoya University Hospital, Nagoya, Japan

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