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Table · dataset · 2026

Deep Learning-Enhanced All-Nanofiber Sensors for Pressure–Temperature Sensing and Stimulus Discrimination

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Flexible sensors for elderly-assistive robots typically chase high sensitivity, while comfort and multisensory capabilities are largely ignored.

Description

Here, we break this pattern with a deep-learning decoupled sensor based on tunable all-nanofiber membranes. Unlike conventional sensors that rely on multiple complex signals, our device uses a single sensing mode and decouples the pressure–temperature signal.

The all-nanofiber sensors not only offer excellent pressure–temperature sensing performances but also demonstrate outstanding elderly-friendliness, including biocompatibility, breathability, and degradability. A deep learning algorithm decouples the mixed signals, enabling accurate recognition of liquid temperature and volume in a cup, as well as classification of 15 daily objects during robotic grasping with 97.78% accuracy.

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This work provides a simple, ecofriendly, and high-performance sensing solution for elderly-assistive robotics and smart home systems.

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Provenance · 3 source records, 17 field assertions
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HKU DataHub · removed upstreamoai:figshare.com:article/3400894513 d agoJSON v1
figshareoai:figshare.com:article/3400894513 d agoJSON v1
Loughborough Research Repository · removed upstreamoai:figshare.com:article/3400894512 d agoJSON v1
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