Skin-Friendly Large Matrix Iontronic Sensing Meta-Fabric for Spasticity Visualization and Rehabilitation Training via Piezo-Ionic Dynamics

Rehabilitation training is believed to be an effectual strategy that can reduce the risk of dysfunction caused by spasticity. However, achieving visualization rehabilitation training for patients remains clinically challenging. Herein, we propose visual rehabilitation training system including iontronic meta-fabrics with skin-friendly and large matrix features, as well as high-resolution image modules for distribution of human muscle tension. Attributed to the dynamic connection and dissociation of the meta-fabric, the fabric exhibits outstanding tactile sensing properties, such as wide tactile sensing range (0 ~ 300 kPa) and high-resolution tactile perception (50 Pa or 0.058%). Meanwhile, thanks to the differential capillary effect, the meta-fabric exhibits a "hitting three birds with one stone" property (dryness wearing experience, long working time and cooling sensing). Based on this, the fabrics can be integrated with garments and advanced data analysis systems to manufacture a series of large matrix structure (40 × 40, 1600 sensing units) training devices. Significantly, the tunability of piezo-ionic dynamics of the meta-fabric and the programmability of high-resolution imaging modules allow this visualization training strategy extendable to various common disease monitoring. Therefore, we believe that our study overcomes the constraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.

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Publication Details

Journal
Nano-Micro Letters
Published
2024-12-18
DOI
https://doi.org/10.1007/s40820-024-01566-3
Citations
14
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
2.58

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article

Skin-Friendly Large Matrix Iontronic Sensing Meta-Fabric for Spasticity Visualization and Rehabilitation Training via Piezo-Ionic Dynamics

Guozhen Shen, Xinran Ji, Minghua She, Mingwei Tian et al.
14 citations
Nano-Micro Letters
Advanced Sensor and Energy Harvesting Materials
2.58
article

Skin-Friendly Large Matrix Iontronic Sensing Meta-Fabric for Spasticity Visualization and Rehabilitation Training via Piezo-Ionic Dynamics

Guozhen Shen, Xinran Ji, Minghua She, Mingwei Tian, Xinwei Zhang, Hong Liu, Ruidong Xu, Ganghua Li, Shijin Zhang, Tong Xu, Bing Sun
article en
14 citations

Abstract

Rehabilitation training is believed to be an effectual strategy that can reduce the risk of dysfunction caused by spasticity. However, achieving visualization rehabilitation training for patients remains clinically challenging. Herein, we propose visual rehabilitation training system including iontronic meta-fabrics with skin-friendly and large matrix features, as well as high-resolution image modules for distribution of human muscle tension. Attributed to the dynamic connection and dissociation of the meta-fabric, the fabric exhibits outstanding tactile sensing properties, such as wide tactile sensing range (0 ~ 300 kPa) and high-resolution tactile perception (50 Pa or 0.058%). Meanwhile, thanks to the differential capillary effect, the meta-fabric exhibits a "hitting three birds with one stone" property (dryness wearing experience, long working time and cooling sensing). Based on this, the fabrics can be integrated with garments and advanced data analysis systems to manufacture a series of large matrix structure (40 × 40, 1600 sensing units) training devices. Significantly, the tunability of piezo-ionic dynamics of the meta-fabric and the programmability of high-resolution imaging modules allow this visualization training strategy extendable to various common disease monitoring. Therefore, we believe that our study overcomes the constraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.

Nano-Micro LettersVol. 17(1)
Qingdao University (CN), Beijing Institute of Technology (CN), Qingdao University of Science and Technology (CN)
Texas Space Grant Consortium, National Natural Science Foundation of China, Natural Science Foundation of Shandong Province, Natural Science Foundation of Qingdao, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 10%
Advanced Sensor and Energy Harvesting Materials
2.58
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