Abstract
Real-time monitoring of foot pressure and humidity in diabetic patients is crucial for preventing diabetic foot ulcers. However, existing flexible wearable devices face challenges in achieving both accurate decoupling of multiple physiological signals and wearer comfort. Herein, a graphical textile electrode design is proposed to integrate sensing materials with selective responses to pressure and humidity onto a single substrate, resulting in an all-textile pressure-humidity bimodal sensor array. The sensor array demonstrates a pressure sensitivity of 0.7235 kPa−1 over 0–500 kPa and exhibits an excellent response consistency of 93.62 %. Furthermore, the combination of the fabric's unique porous architecture and the nanofiber membrane's high specific surface area endows the sensor array with a humidity sensitivity of 0.0216 % RH−1. By integrating the sensor array with a development board, a neural network-based diabetic foot ulcer early warning system is developed. The system effectively distinguishes nine common gait patterns with an accuracy of up to 99.56 % and integrates humidity baseline fluctuations for comprehensive analysis, enabling early warning of diabetic foot ulcers. This work offers new insights into achieving multi-signal responses and developing intelligent flexible electronic device designs based on textile substrates.
| Original language | English |
|---|---|
| Article number | 167905 |
| Journal | Chemical Engineering Journal |
| Volume | 522 |
| DOIs | |
| State | Published - 15 Oct 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Bimodal sensor
- Diabetic foot
- Electrospun nanofibers
- Machine learning
- Wearing comfort
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