High-Performance Flexible Strain Sensor Enhanced by Functionally Partitioned Conductive Network for Intelligent Monitoring of Human Activities

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Authors: Guanjun Zhu, Baojia Zhao, Gailian Zhang, Honglai Yan, Jia Liu, T. LI, Shengkui Yuan, Fang Ren, Penggang Ren, Qinghua Sun, Hongliang Du
Cited by: 2
References: 34

Abstract

Flexible strain sensors have attracted much attention for their immense application potential in fields such as health monitoring, human–machine interaction, and sports science. However, the inherent coupling constraints between core sensing parameters (sensitivity, working range, and stability) lead to severe challenges in multiperformance collaborative improvement, which seriously restricts the large-scale promotion of sensors in various scenarios. Herein, a design strategy of heterogeneous conductive network structure with functional partition is proposed to resolve the challenges. The flexible strain sensor with linear and multiring carbon-based (C) conductive networks in series is prepared on thermoplastic polyurethane (TPU) substrate by screen printing. The linear pathways function as a sensitive unit to achieve strain concentration and rapid crack response, while the interconnected multiring pathways act as a buffer unit dissipating strain energy through elastic deformation. This structurally engineered C/TPU sensor successfully reconciles the performance trade-off, demonstrating an ultrawide sensing range (up to 128% strain), high sensitivity (GF up to 56857) and excellent stability (over 8000 cycles). The flexible C/TPU sensor with outstanding comprehensive performance can capture and quantify full-range human biomechanical signals with high fidelity. Moreover, high-precision recognition of complex knee joint motion patterns (average accuracy up to 98%) is achieved with the support of artificial intelligence. The theoretical and ingenious structure engineering design strategy proposed in this study provides a feasible approach for performance synergistic optimization of flexible strain sensors, which is of great significance for advancing the development in smart wearable devices.

Fields of Study & Subjects

Advanced Sensor and Energy Harvesting Materials Smart Materials for Construction Prosthetics and Rehabilitation Robotics

Publication details

Journal / source
ACS Applied Electronic Materials
Publisher
American Chemical Society (ACS)
Volume
8
Issue
3
Pages
1264–1273
Publication date
30 January 2026
Language
EN