A comfortable, FDM 3D-printed triboelectric insole for motion recognition and energy harvesting

Smart insoles show great potential for gait analysis and rehabilitation training. However, existing triboelectric nanogenerator (TENG)-based insoles often rely on complex fabrication processes or rigid components to achieve high performance. This compromises wearability and comfort. Here, we report a comfortable, highly elastic, and customizable triboelectric insole. It is fabricated using fused deposition modeling 3D printing with a commercial thermoplastic elastomer filament. The design integrates two independent TENG units at the forefoot and heel. This enables dual-zone plantar pressure sensing while enhancing overall elasticity. Through structural optimization guided by numerical simulations, a TENG unit configuration with an 80° slant angle and 2.0 mm wall thickness was established to balance electrical output, mechanical stability, and wearing comfort. The TENG units exhibit a linear open-circuit voltage response ranging from 3.35 to 45.83 V under applied forces of 10–200 N. They maintain stable performance after 10 000 loading cycles. The insole efficiently harvests biomechanical energy during natural walking. It can power 73 LEDs in a single step. Moreover, it effectively captures plantar pressure signals during human locomotion. By extracting multi-dimensional feature vectors and employing an optimized Gaussian-kernel Support Vector Machine, the system achieves a robust motion recognition accuracy of 96.12% even under varying environmental conditions. Overall, this work demonstrates strong application potential for human motion monitoring and biomechanical energy harvesting.

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Publication Details

Journal
AIP Advances
Published
2026-01-01
DOI
https://doi.org/10.1063/5.0312715
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
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article

A comfortable, FDM 3D-printed triboelectric insole for motion recognition and energy harvesting

Sha Xue, Yun Feng Yang, Tingting Cai, Zhibang Zhang et al.
AIP Advances
Advanced Sensor and Energy Harvesting Materials
article

A comfortable, FDM 3D-printed triboelectric insole for motion recognition and energy harvesting

Sha Xue, Yun Feng Yang, Tingting Cai, Zhibang Zhang, Yao Sun
article en

Abstract

Smart insoles show great potential for gait analysis and rehabilitation training. However, existing triboelectric nanogenerator (TENG)-based insoles often rely on complex fabrication processes or rigid components to achieve high performance. This compromises wearability and comfort. Here, we report a comfortable, highly elastic, and customizable triboelectric insole. It is fabricated using fused deposition modeling 3D printing with a commercial thermoplastic elastomer filament. The design integrates two independent TENG units at the forefoot and heel. This enables dual-zone plantar pressure sensing while enhancing overall elasticity. Through structural optimization guided by numerical simulations, a TENG unit configuration with an 80° slant angle and 2.0 mm wall thickness was established to balance electrical output, mechanical stability, and wearing comfort. The TENG units exhibit a linear open-circuit voltage response ranging from 3.35 to 45.83 V under applied forces of 10–200 N. They maintain stable performance after 10 000 loading cycles. The insole efficiently harvests biomechanical energy during natural walking. It can power 73 LEDs in a single step. Moreover, it effectively captures plantar pressure signals during human locomotion. By extracting multi-dimensional feature vectors and employing an optimized Gaussian-kernel Support Vector Machine, the system achieves a robust motion recognition accuracy of 96.12% even under varying environmental conditions. Overall, this work demonstrates strong application potential for human motion monitoring and biomechanical energy harvesting.

AIP AdvancesVol. 16(1)
Luliang University (CN)
Affordable and clean energy
Openalex Percentile: Top 95%
Advanced Sensor and Energy Harvesting Materials
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