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Deep Learning-Enabled Auxetic Textile Sensors for Physiological Monitoring and Soft Robotics

Authors: ZHU Wei-bin; KAMRUL Hasan; KUANG Chengzhao; MO Xiaojuan; ZHANG Xiaohui; AO Kelong; WANG Zhen; HU Hong; SHOU Dahua

DOI: 10.1007/s40843-026-4350-4Status: Verified Translated Edition
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Key Findings in This Report

• • Achieves a gauge factor (sensitivity) of 11.2 across a 0–100% strain range, enabling precise detection of both subtle physiological signals and large joint movements; this sensitivity is critical for applications requiring high resolution over a broad dynamic range. • • Exhibits a linear sensing response with R² = 0.998, ensuring predictable and reliable signal transduction; this linearity simplifies calibration and enhances accuracy in real-time monitoring systems. • • Demonstrates an ultra-low detection limit of 0.5% strain, allowing the sensor to capture minute deformations such as pulse or micro-movements, which is essential for high-fidelity physiological monitoring. • • Possesses a negative Poisson's ratio of -0.25 and moisture permeability of 32.7 g m⁻² h⁻¹, providing enhanced conformability to curved surfaces and breathability for comfortable long-term wear; these properties are vital for wearable integration and user compliance.