Durable and Flexible Magnetoelastic Sensing for Plantar Distributions of Normal and Shear Loads
Tri-axial reaction forces (TRF), which support body mass and provide dynamic propulsion, are critical to improve motion stability, gait transitions, and energy efficiency in legged motions of both humans and robots. The accurate and robust sensing of TRF presents significant challenges due to the cyclic and high-impact loads. Existing commercial sensors with rigid encapsulation have a heavy weight and poor wearability, while flexible sensors with conformal capability are susceptible to damage under cyclic impacts due to complex structure and stress concentration between flexible and hard interfaces. This article proposes a flexible magnetoelastic sensing method that couples three-dimensional elastomer deformations with magnetic flux intensities to capture tri-axial load distributions. The locally-stiffened design mitigates stress concentration at the interfaces among soft elastomer, flexible substrate, and rigid chips. The plantar load sensing array is developed to measure loads up to 116, 113, and 433 kPa in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x-</i>, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">y-</i>, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">z-</i>axes, respectively, with durability validated by the 150 000-cycle compression test and 9-month clinical gait monitoring. The proposed method is illustrated with an immediate application to gait pattern identification, and it is anticipated to contribute to tri-axial force sensing in various scenarios, including but not limited to rehabilitation gait monitoring, legged robot navigation, and human–robot interaction.
Authors
- Zijie Liu (ORCID: https://orcid.org/0009-0000-6987-2649)
- Yuchao Liu (ORCID: https://orcid.org/0009-0006-6575-6572)
- Xuan Wu (ORCID: https://orcid.org/0000-0002-6906-1587)
- Jiajie Guo (ORCID: https://orcid.org/0000-0002-7740-6792)
- Shabei Xu (ORCID: https://orcid.org/0000-0001-5409-2092)
- Zhuo Li (ORCID: https://orcid.org/0000-0003-1067-4191)
- Lei Li (ORCID: https://orcid.org/0000-0003-2854-4555)
- Chuxuan Guo (ORCID: https://orcid.org/0009-0005-8466-5978)
- Weipeng Li (ORCID: https://orcid.org/0000-0002-4686-116X)
- Yibin Chen (ORCID: https://orcid.org/0009-0004-0423-5218)
- Xiang Luo (ORCID: https://orcid.org/0000-0001-8362-8079)
Institutions
- Fudan University (CN)
- China Academy of Information and Communications Technology (CN)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- IEEE/ASME Transactions on Mechatronics
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1109/tmech.2025.3574948
- Citations
- 2
- Primary Topic
- Structural Health Monitoring Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.91
Funders
- National Natural Science Foundation of China