Multiplexed Sensing Textiles Enabled by Reconfigurable Weaving Meso-Structures for Intricate Kinematic Posture Recognition and Thermal Therapy Healthcare

Wearable sensing textiles with multimodal mechanical stimulation detection capabilities have broad applications, such as sports guidance and rehabilitation training. However, current mainstream multimodal sensing textiles typically rely on combining discrete sensors with single functions intensively through sewing or adhesion to detect various mechanical stimuli. Herein, an all-in-one multiplexed sensing textile (MPST) capable of simultaneously detecting pressure and tensile strain is achieved by engineering an innovative hierarchical architecture of textiles. The functionality of MPST is directly derived from the reconfigurable sensing pathways of the woven meso-structures, enabling it to exhibit excellent pressure sensitivity (0.1 kPa<sup>-1</sup>), wide strain detection range (0-100%), superior durability, and desirable wearability. With the assistance of the Long Short-Term Memory (LSTM) algorithm, the MPST wearable system achieves a recognition accuracy of 97.5% in human kinematic postures of the elbow, knee, and foot. In addition, MPST demonstrates outstanding joule heating performance, which reaches 57.1 °C at a 2.5 V applied voltage. With its excellent multimodal sensing performance and joule heating ability, MPST holds great potential for applications in sports training guidance, assistive rehabilitation training, and soft robotics.

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Publication Details

Journal
ACS Sensors
Published
2025-04-03
DOI
https://doi.org/10.1021/acssensors.5c00133
Citations
6
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
4.04

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article

Multiplexed Sensing Textiles Enabled by Reconfigurable Weaving Meso-Structures for Intricate Kinematic Posture Recognition and Thermal Therapy Healthcare

Ruru Pan, Fengxin Sun, Yangyang Peng
6 citations
ACS Sensors
Advanced Sensor and Energy Harvesting Materials
4.04
article

Multiplexed Sensing Textiles Enabled by Reconfigurable Weaving Meso-Structures for Intricate Kinematic Posture Recognition and Thermal Therapy Healthcare

Ruru Pan, Fengxin Sun, Yangyang Peng
article en
6 citations

Abstract

Wearable sensing textiles with multimodal mechanical stimulation detection capabilities have broad applications, such as sports guidance and rehabilitation training. However, current mainstream multimodal sensing textiles typically rely on combining discrete sensors with single functions intensively through sewing or adhesion to detect various mechanical stimuli. Herein, an all-in-one multiplexed sensing textile (MPST) capable of simultaneously detecting pressure and tensile strain is achieved by engineering an innovative hierarchical architecture of textiles. The functionality of MPST is directly derived from the reconfigurable sensing pathways of the woven meso-structures, enabling it to exhibit excellent pressure sensitivity (0.1 kPa<sup>-1</sup>), wide strain detection range (0-100%), superior durability, and desirable wearability. With the assistance of the Long Short-Term Memory (LSTM) algorithm, the MPST wearable system achieves a recognition accuracy of 97.5% in human kinematic postures of the elbow, knee, and foot. In addition, MPST demonstrates outstanding joule heating performance, which reaches 57.1 °C at a 2.5 V applied voltage. With its excellent multimodal sensing performance and joule heating ability, MPST holds great potential for applications in sports training guidance, assistive rehabilitation training, and soft robotics.

ACS SensorsVol. 10(4)
Jiangnan University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, China National Textile and Apparel Council, Graduate Research and Innovation Projects of Jiangsu Province
Openalex Percentile: Top 7%
Advanced Sensor and Energy Harvesting Materials
4.04
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Multiplexed Sensing Textiles Enabled by Reconfigurable Weaving Meso-Structures for Intricate Kinematic Posture Recognition and Thermal Therapy Healthcare — Ruru Pan, Fengxin Sun, et al. · ACS Sensors (2025) | TGRS Research Map | TGRS