Key Takeaways & Executive Findings
- •• The iontronic meta-fabric exhibits a "hitting three birds with one stone" property, breaking through the bottleneck that traditional film materials (PDMS) cannot balance comfort and durability. • The meta-fabrics can be integrated with garments and advanced data analysis systems to manufacture a series of large matrix structure (>40×40, 1600 sensing units) rehabilitation training devices, overcoming the bottleneck of low matrix integration of traditional iontronic devices (<10×10, 100 sensing units). • The fabric demonstrates outstanding tactile sensing properties, including a wide sensing range (0–300 kPa) and high-resolution tactile perception (50 Pa or 0.058%), enabling precise muscle tension mapping. • The tunability of piezo-ionic dynamics and programmability of high-resolution imaging modules make this visualization training strategy extendable to various common disease monitoring, paving the way for smart healthcare.
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.
1. Introduction
As a common sequel of central nervous system injuries such as stroke, traumatic brain injury (TBI) and cerebral palsy (CP), spasticity has now been a globally prevalent and disabling disease [1, 2]. It is estimated that over millions people worldwide suffer from spasticity to some degree [3]. Take the spasticity caused by stroke as an example, it occurs in 25% of patients within 2 weeks after a stroke, and increases up to 43%–50% and 38%–44% after 6 and 12 months, respectively [4–6]. Among them, severe or disabling spasticity occurs in approximately 15% of stroke patients, which is caused by increasing in muscle tone [7, 8]. Fortunately, rehabilitation training, which can improve muscle contraction, coordination, and control abilities, is seen as an effective strategy to avoid the risk of disability. To fulfill this effect, the assessment of muscle tone is of a significant importance.
Currently, mainstream strategies for muscle tension assessment, such as Modified Ashworth scale (MAS) and Modified Tardieu scales (MTS), are testing joint resistance of the patients during passive motion [2, 9–11]. Nevertheless, the above strategies rely heavily on the subjective perception of the physician, which may lead to potential misdiagnosis [12]. In addition, various quantitative assessment techniques, such as electrophysiological measures, gait analysis and neuroimaging, have emerged in clinical in recent years [13–15]. These techniques are dependent on various bulky and costly medical apparatus, which not only require professional operators but cause uncomfortable experience for patients [16, 17]. Thus, it is difficult for physician to obtain timely and continuous rehabilitation training data for patients, affecting the recovery of patients. To this end, portable muscle tension monitoring technologies with continuous monitoring and wearing comfort are highly demanded.
Thanks to the advent and development of flexible electronics, wearable tactile sensing devices (such as resistance, capacitance, triboelectric, and iontronic type) have provided a technological ca...
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Ruidong Xu, Tong Xu, Minghua She, Xinran Ji, Ganghua Li, Shijin Zhang, Xinwei Zhang, Hong Liu, Bin Sun, Guozhen Shen, Mingwei Tian (2024). Skin-Friendly Large Matrix Iontronic Sensing Meta-Fabric for Spasticity Visualization and Rehabilitation Training via Piezo-Ionic Dynamics. Nano-Micro Letters. https://doi.org/10.1007/s40820-024-01566-3
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Frequently Asked Questions
What is the main innovation of this iontronic meta-fabric?
The iontronic meta-fabric achieves a 'hitting three birds with one stone' property, balancing comfort, durability, and sensing performance, which traditional film materials like PDMS cannot achieve.
How does the meta-fabric overcome the bottleneck of low matrix integration in traditional iontronic devices?
The meta-fabric can be integrated into large matrix structures with over 40×40 (1600 sensing units), significantly surpassing the typical <10×10 (100 units) of traditional devices, enabling high-resolution spatial mapping.
What are the key sensing performance metrics of the meta-fabric?
The fabric exhibits a wide tactile sensing range of 0–300 kPa and high-resolution tactile perception of 50 Pa (0.058%), allowing precise detection of muscle tension distribution.
How does the visualization rehabilitation training system work?
The system integrates the iontronic meta-fabric with high-resolution imaging modules to map muscle tension distribution in real time, providing visual feedback for rehabilitation training.
What is the potential clinical impact of this technology?
This technology offers a portable, comfortable, and high-resolution solution for spasticity assessment and rehabilitation training, potentially improving patient outcomes and enabling remote monitoring.
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