Rehabilitation training is believed to be an effectual strategy that canreduce the risk of dysfunction caused by spasticity.However,achieving visualizationrehabilitation training for patients remains clinically challe...Rehabilitation training is believed to be an effectual strategy that canreduce the risk of dysfunction caused by spasticity.However,achieving visualizationrehabilitation training for patients remains clinically challenging.Herein,wepropose visual rehabilitation training system including iontronic meta-fabrics withskin-friendly and large matrix features,as well as high-resolution image modules fordistribution of human muscle tension.Attributed to the dynamic connection and dissociationof 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 garmentsand 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 allowthis visualization training strategy extendable to various common disease monitoring.Therefore,we believe that our study overcomes theconstraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.展开更多
基金supported by the National Key Research and Development Program(2022YFB3805800)National Natural Science Foundation of China(52473307,22208178,62301290)+9 种基金Taishan Scholar Program of Shandong Province in China(tsqn202211116)Shandong Provincial Universities Youth Innovation Technology Plan Team(2023KJ223)Natural Science Foundation of Shandong Province of China(ZR2023YQ037,ZR2020QE074,ZR2023QE043,ZR2022QE174)Shandong Province Science and Technology Small and Medium sized Enterprise Innovation Ability Enhancement Project(2023TSGC0344,2023TSGC1006)Natural Science Foundation of Qingdao(23-2-1-249-zyyd-jch,24-4-4-zrjj-56-jch)Anhui Province Postdoctoral Researcher Research Activity Funding Project(2023B706)Qingdao Key Technology Research and Industrialization Demonstration Projects(23-1-7-zdfn-2-hz)Qingdao Shinan District Science and Technology Plan Project(2022-3-005-DZ)Suqian Key Research and Development Plan(H202310)Jinan City-School Integration Development Strategy Project for the Year 2023 under Grant(JNSX2023088).
文摘Rehabilitation training is believed to be an effectual strategy that canreduce the risk of dysfunction caused by spasticity.However,achieving visualizationrehabilitation training for patients remains clinically challenging.Herein,wepropose visual rehabilitation training system including iontronic meta-fabrics withskin-friendly and large matrix features,as well as high-resolution image modules fordistribution of human muscle tension.Attributed to the dynamic connection and dissociationof 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 garmentsand 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 allowthis visualization training strategy extendable to various common disease monitoring.Therefore,we believe that our study overcomes theconstraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.
