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Search Results (24)

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Keywords = textile-based stretch sensors

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14 pages, 4291 KiB  
Article
Assessing the Role of Yarn Placement in Plated Knit Strain Sensors: A Detailed Study of Their Electromechanical Properties and Applicability in Bending Cycle Monitoring
by Youn-Hee Kim, Juwon Jun, You-Kyung Oh, Hee-Ji Choi, Mi-Jung Lee, Kyeong-Sik Min, Sung-Hyon Kim, Hyunseung Lee, Ho-Seok Nam, Son Singh, Byoung-Joon Kim and Jaegab Lee
Sensors 2024, 24(5), 1690; https://doi.org/10.3390/s24051690 - 6 Mar 2024
Viewed by 1030
Abstract
In this study, we explore how the strategic positioning of conductive yarns influences the performance of plated knit strain sensors fabricated using commercial knitting machines with both conductive and non-conductive yarns. Our study reveals that sensors with conductive yarns located at the rear, [...] Read more.
In this study, we explore how the strategic positioning of conductive yarns influences the performance of plated knit strain sensors fabricated using commercial knitting machines with both conductive and non-conductive yarns. Our study reveals that sensors with conductive yarns located at the rear, referred to as ‘purl plated sensors’, exhibit superior performance in comparison to those with conductive yarns at the front, or ‘knit plated sensors’. Specifically, purl plated sensors demonstrate a higher sensitivity, evidenced by a gauge factor ranging from 3 to 18, and a minimized strain delay, indicated by a 1% strain in their electromechanical response. To elucidate the mechanisms behind these observations, we developed an equivalent circuit model. This model examines the role of contact resistance within varying yarn configurations on the sensors’ sensitivity, highlighting the critical influence of contact resistance in conductive yarns subjected to wale-wise stretching on sensor responsiveness. Furthermore, our findings illustrate that the purl plated sensors benefit from the vertical movement of non-conductive yarns, which promotes enhanced contact between adjacent conductive yarns, thereby improving both the stability and sensitivity of the sensors. The practicality of these sensors is confirmed through bending cycle tests with an in situ monitoring system, showcasing the purl plated sensors’ exceptional reproducibility, with a standard deviation of 0.015 across 1000 cycles, and their superior sensitivity, making them ideal for wearable devices designed for real-time joint movement monitoring. This research highlights the critical importance of conductive yarn placement in sensor efficacy, providing valuable guidance for crafting advanced textile-based strain sensors. Full article
(This article belongs to the Section Wearables)
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Figure 1

Figure 1
<p>Illustration of machine-knitted textiles incorporating strain sensors, utilizing conductive yarns (light blue) and non-conductive yarns (dark blue). The figure demonstrates (<b>a</b>) the purl stitch pattern, (<b>b</b>) the knit stitch pattern, and (<b>c</b>) the plated knitting technique used for integrating the strain sensor. For parts (<b>a</b>,<b>b</b>), both the textile’s appearance and a schematic of the front side are shown.</p>
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<p>The experimental setup used to measure the dynamic bending resistance of the sample: (<b>a</b>) E-textile flexing tester; (<b>b</b>) wireless fabric sensor system consisting of a purl stitch plated sensor, an MCU module, and an interconnection module, and the inset (on the right side) shows a schematic of a fabric sensor system; and (<b>c</b>) a schematic of the voltage divider in the sensor system that shows the calculation of the voltage drop (Vout) across the sensor.</p>
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<p>Circuit of unit loop and plated fabric network: (<b>a</b>) a schematic structure of the plated knit fabric; (<b>b</b>) a unit loop and its related resistances, (<b>c</b>) an equivalent resistance network circuit corresponding to the loop structure of 1 course × 2 wale, and (<b>d</b>) a simplified circuit.</p>
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<p>Resistance variations of the purl and knit plated sensors plotted as a function of applied force.</p>
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<p>Simulated and experimental values of the plated sensors’ resistances plotted as a function of applied force.</p>
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<p>Variations in the vertical and horizontal resistances with forces applied to knit plated sensor and purl plated sensor, respectively.</p>
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<p>Optical microscopy images (<b>a</b>) of the purl plated strain sensor in the relaxed state, at a strain of 10% and at a strain of 20%, respectively; (<b>b</b>) corresponding images of the knit plated strain sensor in the relaxed state, at a strain of 10% and at a strain of 20%, respectively.</p>
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<p>The variation in the gauge factor of the purl and knit plated sensors as a function of strain.</p>
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<p>Output voltage changes of a 20 mm × 40 mm fabric sensor during the repetitive bending processes at 50 cpm.</p>
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14 pages, 16625 KiB  
Article
Seamless Weft Knit Vest with Integrated Needle Sensing Zone for Monitoring Shoulder Movement: A First Methodological Study
by Fei Sun, Zhijia Dong, Yuqin Din, Honglian Cong and Pibo Ma
Materials 2023, 16(16), 5563; https://doi.org/10.3390/ma16165563 - 10 Aug 2023
Cited by 1 | Viewed by 1231
Abstract
The integration of textile-based flexible sensors and electronic devices has accelerated the development of wearable textiles for posture monitoring. The complexity of the processes required to create a complete monitoring product is currently reflected in three main areas. The first is the sensor [...] Read more.
The integration of textile-based flexible sensors and electronic devices has accelerated the development of wearable textiles for posture monitoring. The complexity of the processes required to create a complete monitoring product is currently reflected in three main areas. The first is the sensor production process, which is complex. Second, the integration of the sensor into the garment requires gluing or stitching. Finally, the production of the base garment requires cutting and sewing. These processes deteriorate the user experience and hinder the commercial mass production of wearable textiles. In this paper, we knitted a one-piece seamless knitted vest (OSKV) utilizing the one-piece seamless knitting technique and positioned an embedded needle sensing zone (EHSZ) with good textile properties and electrical performance for monitoring human shoulder activity. The EHSZ was knitted together with the OSKV, eliminating the need for an integration process. The EHSZ exhibited good sensitivity (GF = 2.23), low hysteresis (0.29 s), a large stretch range (200%), and excellent stability (over 300 cycles), satisfying the requirement to capture a wide range of deformation signals caused by human shoulder movements. The OSKV described the common vest process structure without the stitching process. Furthermore, OSKV fulfilled the demand for seamless and trace-free monitoring while effortlessly and aesthetically satisfying the knitting efficiency of commercial garments. Full article
(This article belongs to the Section Advanced Composites)
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<p>Three types of weft-knitted vest construction (from <b>left</b> to <b>right</b>, style a, style b, style c).</p>
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<p>The OSKV straps transformation principle and knitting. (<b>a</b>) The direction of the vest straps has been changed from vertical to horizontal. (<b>b</b>) Illustration of the horizontal knitted shoulder strap pull up. (<b>c</b>) Functional partitioning of 3D vests and 2D templates. (<b>d</b>) Fabric structure in different areas.</p>
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<p>Yarn and tissue construction tests.</p>
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<p>(<b>a</b>) Photograph of a one-piece knitted no-integration seamless vest. (<b>b</b>) The embedded knitting principle of the ENSZ.</p>
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<p>Physical view of the flexible sensor. (<b>a</b>) Silver−plated conductive yarn resistance curve with length, (<b>b</b>) electron microscope image of a silver−plated nylon conductive yarn. EHSZ clipping processing, (<b>c</b>) photographs of EHSZ at increasing starting strain levels of 70% and 133%, respectively, showing its good tensile strain. (<b>d</b>) EHSZ’s craftsmanship is front and back, bent and twisted, showcasing its remarkable softness. (<b>e</b>) EHSZ clipping processing.</p>
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<p>The knitting of OSKV. (<b>a</b>) Knitting equipment environment. (<b>b</b>) Product Handling Process Flow. (<b>c</b>) Wireless transmission of external devices.</p>
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<p>The strain sensing performance of the fabric sensor. The Δ<span class="html-italic">R</span>/<span class="html-italic">R</span><sub>0</sub> of the sensor under cyclic stretching. (<b>a</b>) Photograph of the testing instrument system. (<b>b</b>) Resistance change as a function of strain at a stretching rate of 100 mm/min. (<b>c</b>) Relative resistance changes of the EHSZ strain sensor as a function of the applied strain in the longitudinal and transverse directions, respectively. (<b>d</b>) Dynamic responses under a repeated strain of 20%, 40%, 60%, 80%, and 100% (100 mm/min) for 8 cycles. (<b>e</b>) The real-time Δ<span class="html-italic">R</span>/<span class="html-italic">R</span><sub>0</sub> of the sensor subjected to a fast-speed (500 mm/min) stretching and releasing at 5% strain. (<b>f</b>) Stability testing under 80% strain at 200 mm/min for 300 cycles. (<b>g</b>) Cyclic resistance changes under 80% strain at a speed of 50, 100, 150, and 200 mm/min.</p>
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<p>Demonstration of the working principle of the EHSZ. (<b>a</b>) The structural process of the EHSZ. (<b>b</b>) Contact resistance. (<b>c</b>) Equivalent resistance model for a flat pin structure. The blue color in the image represents the conductive top yarn, the yellow color represents the normal bottom yarn, and the red color represents long loops. (<b>d</b>) Equivalent resistance model of the hanger pin structure.</p>
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<p>Real−time monitoring of human physiological activities using OSKV. (<b>a</b>) The basic movements of the human shoulder in three anatomical planes. Electrical signal output from the same joint at different swing angles: (<b>b</b>) 30° in the coronal plane, (<b>c</b>) 90° in the coronal plane, (<b>d</b>) 180° in the coronal plane, wave patterns of signals picked up by sensors during. (<b>e</b>) Inward to 130° in the horizontal plane, (<b>f</b>) outward to 50° in the horizontal plane, (<b>g</b>) 90° in the sagittal plane, (<b>h</b>) 40° in the sagittal plane.</p>
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<p>(<b>a</b>) EDR algorithm for edit distance fitting, Blue: Dataset H, Red: Dataset K. (<b>b</b>) GUI interface for the digital shoulder movement recognition system.</p>
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<p>Decision trees for shoulder movements.</p>
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16 pages, 2430 KiB  
Article
The Use of Wearable Inertial Sensors and Workplace-Based Exercises to Reduce Lateral Epicondylitis in the Workstation of a Textile Logistics Center
by Florian Michaud, Roberto Pazos, Urbano Lugrís and Javier Cuadrado
Sensors 2023, 23(11), 5116; https://doi.org/10.3390/s23115116 - 27 May 2023
Cited by 3 | Viewed by 2340
Abstract
People whose jobs involve repetitive motions of the wrist and forearm can suffer from lateral epicondylitis, which is a significant burden on both the individual and the employer due to treatment costs, reduced productivity, and work absenteeism. This paper describes an ergonomic intervention [...] Read more.
People whose jobs involve repetitive motions of the wrist and forearm can suffer from lateral epicondylitis, which is a significant burden on both the individual and the employer due to treatment costs, reduced productivity, and work absenteeism. This paper describes an ergonomic intervention to reduce lateral epicondylitis in the workstation of a textile logistics center. The intervention includes workplace-based exercise programs, evaluation of risk factors, and movement correction. An injury- and subject-specific score was calculated from the motion captured with wearable inertial sensors at the workplace to evaluate the risk factors of 93 workers. Then, a new working movement was adapted to the workplace, which limited the observed risk factors and took into account the subject-specific physical abilities. The movement was taught to the workers during personalized sessions. The risk factors of 27 workers were evaluated again after the intervention to validate the effectiveness of the movement correction. In addition, active warm-up and stretching programs were introduced as part of the workday to promote muscle endurance and improve resistance to repetitive stress. The present strategy offered good results at low cost, without any physical modification of the workplace and without any detriment to productivity. Full article
(This article belongs to the Special Issue Wearable Sensors for Human Movement)
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<p>Workplace and task illustration.</p>
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<p>Working movement correction intervention.</p>
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<p>Wearable system for motion capture at the workplace (sensors numbered in green).</p>
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<p>Corrected task illustration.</p>
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<p>Recorded training instructions.</p>
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<p>Workers with previous pathologies in wrist or elbow according to gender: (<b>a</b>) men; (<b>b</b>) women.</p>
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13 pages, 3897 KiB  
Article
3D Stitching Double Weave Fabric-Based Elastic Triboelectric Nanogenerator for Energy Harvesting and Self-Powered Sensing
by Lijun Chen, Yixi Zhao, Yunchu Shen, Kai Wang, Pibo Ma, Fumei Wang and Chaoyu Chen
Energies 2023, 16(5), 2284; https://doi.org/10.3390/en16052284 - 27 Feb 2023
Cited by 2 | Viewed by 1601
Abstract
With the start of the intelligent age, textiles are no longer limited to safety protection, warmth, and aesthetic purposes. They have become intelligent textiles, which combine functionality, intelligence, and information technology to adapt to the era and enrich our lives, such as wearable [...] Read more.
With the start of the intelligent age, textiles are no longer limited to safety protection, warmth, and aesthetic purposes. They have become intelligent textiles, which combine functionality, intelligence, and information technology to adapt to the era and enrich our lives, such as wearable textiles and energy harvesting electronics. However, the limited stretchable smart textiles and complex fabrication methods have largely hindered their development. Here, a mass-manufactured 3D stitching double weave fabric-based elastic triboelectric nanogenerator (3DWE-TENG) is developed. Based on its stable electrical output performances and rapid response to external tensile strain, it can be used for energy harvesting and self-powered sensing simultaneously through both the lining layer and the exterior layer. With an advanced 3D structural design and using the improved woven method, 3DWE-TENG can be stretched to 300% and achieves a stable mechanical structure, breathability, and excellent flexibility. Furthermore, it also has low costs, wearable comfortability, and high fabricating efficiency due to the mature woven technique and the common yarns used in the fabric. This work provides more opportunities for stretchable power sources and self-powered sensors with applications in wearable electronics. Full article
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<p>(<b>a</b>) Scanning electron microscopy (SEM) photograph of PET multifilament; (<b>b</b>) SEM of PA conductive yarn; (<b>c</b>) tensile property of the PAconductive yarn.</p>
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<p>(<b>a</b>) Photographs of 3DWE-TENG before the stretch; (<b>b</b>) Photographs of 3DWE-TENG before and after stretch; (<b>c</b>) Stitching double weave diagram.</p>
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<p>The working mechanism of the 3DWE-TENG with a stitching double weave, (<b>i</b>) In the original state without stretch; (<b>ii</b>) The 3DWE-TENG is gradually stretched; (<b>iii</b>) The 3DWE-TENG is stretched to the largest deformation; (<b>iv</b>) The 3DWE-TENG is recovering to the original state.</p>
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<p>(<b>a</b>,<b>b</b>) Electrical output performances of the 3DWE-TENG fabricated with 280D PA conductive yarn; (<b>c</b>,<b>d</b>) Electrical output performances of the 3DWE-TENG fabricated with 140D PA conductive yarn; (<b>e</b>,<b>f</b>) Electrical output performance comparison between two 3DWE-TENGs fabricated with 280D and 140D PA conductive yarn.</p>
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<p>(<b>a</b>,<b>b</b>) The electrical output performances of the 3DWE-TENG with warp yarn density 417 ends/10 cm; (<b>c</b>,<b>d</b>) The electrical output performances comparison between two 3DWE-TENGs with different warp yarn densities, including five ends per dent and three ends per dent.</p>
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<p>(<b>a</b>) The face view of the 3DWE-TENG with the electrode as the weft yarn; (<b>b</b>) The back view of the 3DWE-TENG with the electrode as the weft yarn; (<b>c</b>) The side view of the 3DWE-TENG with the electrode as the weft yarn; (<b>d</b>) 3DWE-TENGs with a warp yarn density of 417 ends/10 cm in a stretch state; (<b>e</b>) 3DWE-TENGs with a warp yarn density of 533 ends/10 cm in a stretch state; (<b>f</b>) The stitching double weave diagram of the 3DWE-TENG with the electrode as the weft yarn.</p>
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<p>(<b>a</b>) The working mechanism of the 3DWE-TENG with the electrode as the weft yarn, (<b>i</b>) In the original state without stretch; (<b>ii</b>) The 3DWE-TENG is gradually stretched; (<b>iii</b>) The 3DWE-TENG is stretched to the largest deformation; (<b>iv</b>) The 3DWE-TENG is gradually recovering to the original state; (<b>b</b>) The V<sub>OC</sub> of 3DWE-TENG with a warp yarn density of 417 ends/10cm in a stretch state; (<b>c</b>) The V<sub>OC</sub> of 3DWE-TENG with a warp yarn density of 533 ends/10 cm in a stretch state; (<b>d</b>) The V<sub>OC</sub> comparison of two 3DWE-TENGs with different warp yarn densities, including five ends per dent and three ends per dent; (<b>e</b>) The V<sub>OC</sub> comparison of two 3DWE-TENGs with the weft yarn and the warp yarn as the electrode, respectively.</p>
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<p>(<b>a</b>) Photograph comparison of the 3DWE-TENG (with warp yarn as the electrode) at 0% tensile strain and 300% tensile strain, (<b>b</b>) photograph comparison of the 3DWE-TENG (with weft yarn as the electrode) at 0% tensile strain and 300% tensile strain.</p>
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<p>(<b>a</b>–<b>c</b>) The Voc, Isc, and Q<sub>SC</sub> of the 3DWE−TENG when it comes into contact with and separates from the PTFE fabric, (<b>d</b>) the 3DWE−TENG can be used to light up 87 LEDs, (<b>e</b>) photograph of the 3DWE−TENG as a bend-stretch sensor, (<b>f</b>) output voltages of 3DWE−TENG as a bend-stretch sensor at different bend angles (including 15°, 45°, 90°, and 120°).</p>
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14 pages, 3568 KiB  
Article
Stretchable Woven Fabric-Based Triboelectric Nanogenerator for Energy Harvesting and Self-Powered Sensing
by Lijun Chen, Tairan Wang, Yunchu Shen, Fumei Wang and Chaoyu Chen
Nanomaterials 2023, 13(5), 863; https://doi.org/10.3390/nano13050863 - 25 Feb 2023
Cited by 8 | Viewed by 2129
Abstract
With the triboelectric nanogenerator developing in recent years, it has gradually become a promising alternative to fossil energy and batteries. Its rapid advancements also promote the combination of triboelectric nanogenerators and textiles. However, the limited stretchability of fabric-based triboelectric nanogenerators hindered their development [...] Read more.
With the triboelectric nanogenerator developing in recent years, it has gradually become a promising alternative to fossil energy and batteries. Its rapid advancements also promote the combination of triboelectric nanogenerators and textiles. However, the limited stretchability of fabric-based triboelectric nanogenerators hindered their development in wearable electronic devices. Here, in combination with the polyamide (PA) conductive yarn, polyester multifilament, and polyurethane yarn, a highly stretchable woven fabric-based triboelectric nanogenerator (SWF-TENG) with the three elementary weaves is developed. Different from the normal woven fabric without elasticity, the loom tension of the elastic warp yarn is much larger than non-elastic warp yarn in the weaving process, which results in the high elasticity of the woven fabric coming from the loom. Based on the unique and creative woven method, SWF-TENGs are qualified with excellent stretchability (up to 300%), flexibility, comfortability, and excellent mechanical stability. It also exhibits good sensitivity and fast responsibility to the external tensile strain, which can be used as a bend–stretch sensor to detect and identify human gait. Its collected power under pressure mode is capable of lighting up 34 light-emitting diodes (LEDs) by only hand-tapping the fabric. SWF-TENG can be mass-manufactured by using the weaving machine, which decreases fabricating costs and accelerates industrialization. Based on these merits, this work provides a promising direction toward stretchable fabric-based TENGs with wide applications in wearable electronics, including energy harvesting and self-powered sensing. Full article
(This article belongs to the Section Energy and Catalysis)
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Figure 1
<p>(<b>a</b>) Scanning electron microscopy (SEM) photograph of the PA conductive yarn; (<b>b</b>) Scanning electron microscopy (SEM) photograph of the Ag coating on the surface of the PA conductive yarn; PET multifilament; (<b>c</b>) The tensile property of the PA conductive yarn; (<b>d</b>) The digital photograph of the PET multifilament; (<b>e</b>) Optical microscopy (OM) photograph of the PET multifilament; (<b>f</b>) Scanning electron microscopy (SEM) photograph of the PET multifilament.</p>
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<p>(<b>a</b>) SWF-TENG with satin weave before stretch; (<b>b</b>,<b>c</b>) SWF-TENG with satin weave after stretch; (<b>d</b>,<b>e</b>) The side view of SWF-TENG with satin weave; (<b>f</b>) Satin weave diagram; (<b>g</b>) SWF-TENG with satin weave before stretch; (<b>h</b>,<b>i</b>) SWF-TENG with satin weave after stretch.</p>
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<p>(<b>a</b>) The working mechanism of SWF-TENG with a satin weave, (<b>i</b>) In the original state without stretch; (<b>ii</b>) The SWF-TENG is gradually stretched; (<b>iii</b>) The SWF-TENG is stretched to the largest deformation; (<b>iv</b>) The SWF-TENG is recovering to the original state; (<b>b</b>,<b>c</b>) Electrical output performances of SWF-TENG with satin structure.</p>
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<p>(<b>a</b>) The digital photograph of SWF-TENG with twill weave before stretch; (<b>b</b>,<b>c</b>) SWF-TENG with twill weave after stretch; (<b>d</b>) The side view of SWF-TENG with twill weave; (<b>e</b>) The back side of SWF-TENG with twill weave; (<b>f</b>) The weave diagram.</p>
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<p>(<b>a</b>) The working mechanism of SWF-TENG with twill weave, (<b>i</b>) In the original state without stretch; (<b>ii</b>) The SWF-TENG is gradually stretched; (<b>iii</b>) The SWF-TENG is stretched to the largest deformation; (<b>iv</b>) The SWF-TENG is recovering to the original state; (<b>b</b>,<b>c</b>) Electrical output performances of SWF-TENG with twill structure.</p>
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<p>(<b>a</b>,<b>b</b>) Digital photographs of SWF-TENG with plain weave before and after stretch; (<b>c</b>) The weave diagram of plain structure; (<b>d</b>) The working mechanism of SWF-TENG with plain structure, (<b>i</b>) The SWF-TENG is stretched at the largest deformation state; (<b>ii</b>) The SWF-TENG is gradually recovering; (<b>iii</b>) The SWF-TENG recovers to the original state; (<b>iv</b>) The SWF-TENG is gradually stretched. (<b>e</b>,<b>f</b>) Electrical output performances of SWF-TENG with plain structure; (<b>g</b>) The tensile property of the SWF-TENG with different structures.</p>
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<p>(<b>a</b>) The outputs comparison of satin, twill, and plain structures; The electrical output performances comparison between different SWF-TENGs; (<b>b</b>) Twill structure fabricated by the PA conductive yarn, including 280D and 140D; (<b>c</b>) Satin structure fabricated by the PA conductive yarn, including 280D and 140D; (<b>d</b>) SWF-TENGs with different weft yarn densities.</p>
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<p>(<b>a</b>) The electrical output performances of SWF-TENG under press mode with different frequencies; (<b>b</b>) The working mechanism of SWF-TENG under press mode, (<b>i</b>) In the original state with pressure between the PTFE film and the fabric; (<b>ii</b>) The SWF-TENG and the PTFE film are gradually separating; (<b>iii</b>) The PTFE film is moving quite far away from the SWF-TENG; (<b>iv</b>) The PTFE film is contacting the SWF-TENG gradually; (<b>c</b>) Simulated electric field distribution of SWF-TENG under press mode; (<b>d</b>) Demonstration of lighting up 34 LEDs marked as alphabets “KTC” by only hand tapping the fabric TENG; (<b>e</b>) The testing interface of the SWY-TENG as a real-time bend–stretch sensor; (<b>f</b>) V<sub>OC</sub> of the SWY-TENG as a real-time bend–stretch sensor.</p>
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23 pages, 2650 KiB  
Article
Creation and Analysis of a Respiratory Sensor Using the Screen-Printing Method and the Arduino Platform
by Jarosław Wojciechowski and Ewa Skrzetuska
Sensors 2023, 23(4), 2315; https://doi.org/10.3390/s23042315 - 19 Feb 2023
Cited by 2 | Viewed by 3237
Abstract
The aim of this paper is to present novel highly sensitive and stretchable strain sensors using data analysis to report on human live parameters using the Arduino embedded system as a proof of concept in developing new and innovative solutions for health care. [...] Read more.
The aim of this paper is to present novel highly sensitive and stretchable strain sensors using data analysis to report on human live parameters using the Arduino embedded system as a proof of concept in developing new and innovative solutions for health care. The article introduces the solution of textile sensor origination with electrical resistance measurement using the mobile Arduino microcontroller in the designed/elaborated textile printed sensor. The textile sensor was developed by the screen printing technique based on the water dispersion of carbon nanotubes during printing composition. By stretching and squeezing the T-shirt during breathing, the electrical resistances of the printed sensor were changed. The measured resistance corresponded to the number of breaths of the person wearing the T-shirt. The microcontroller calculated the number of breaths as a number of electrical resistance peaks, which then led to monitoring human live parameters. Full article
(This article belongs to the Special Issue Sensors in Sleep Monitoring)
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<p>The microcontroller and textile sensor connection diagram (own elaboration).</p>
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<p>Photo of the Arduino microcontroller and cable connections to textile sensor.</p>
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<p>Block diagram of algorithm.</p>
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<p>Arduino serial plot peak recognition.</p>
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<p>Detection of breath in simulation of slow breathing—Bradypnea—eight breaths per min.</p>
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<p>Detection of breath in simulation of normal breathing—12 breaths per min.</p>
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<p>Detection of breath in simulation of increased breathing—Hyperpnea—20 breaths per min.</p>
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<p>Detection of breath in simulation of increased breathing—Tachypnea—24 breaths per min.</p>
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<p>Tensile displacement by load 0–700 N.</p>
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<p>Tensile displacement by load 0–1200 N.</p>
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<p>Tensile displacement by load 0–2000 N.</p>
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23 pages, 6497 KiB  
Article
Design and Fabrication of Embroidered Textile Strain Sensors: An Alternative to Stitch-Based Strain Sensors
by Jose Guillermo Colli Alfaro and Ana Luisa Trejos
Sensors 2023, 23(3), 1503; https://doi.org/10.3390/s23031503 - 29 Jan 2023
Cited by 9 | Viewed by 3773
Abstract
Smart textile sensors have been gaining popularity as alternative methods for the continuous monitoring of human motion. Multiple methods of fabrication for these textile sensors have been proposed, but the simpler ones include stitching or embroidering the conductive thread onto an elastic fabric [...] Read more.
Smart textile sensors have been gaining popularity as alternative methods for the continuous monitoring of human motion. Multiple methods of fabrication for these textile sensors have been proposed, but the simpler ones include stitching or embroidering the conductive thread onto an elastic fabric to create a strain sensor. Although multiple studies have demonstrated the efficacy of textile sensors using the stitching technique, there is almost little to no information regarding the fabrication of textile strain sensors using the embroidery method. In this paper, a design guide for the fabrication of an embroidered resistive textile strain sensor is presented. All of the required design steps are explained, as well as the different embroidery design parameters and their optimal values. Finally, three embroidered textile strain sensors were created using these design steps. These sensors are based on the principle of superposition and were fabricated using a stainless-steel conductive thread embroidered onto a polyester–rubber elastic knit structure. The three sensors demonstrated an average gauge factor of 1.88±0.51 over a 26% working range, low hysteresis (8.54±2.66%), and good repeatability after being pre-stretched over a certain number of stretching cycles. Full article
(This article belongs to the Section Intelligent Sensors)
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<p>Stitching and embroidery examples. (<b>a</b>) A zigzag stitch formed by the interlock of a bobbin and needle thread. (<b>b</b>) An embroidery pattern formed by the combination of multiple stitches.</p>
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<p>(<b>a</b>) A zigzag stitch is observed on the upper side of the fabric. (<b>b</b>) The same zigzag stitch as observed on the bottom side of the fabric. The dashed red line shows the bobbin thread.</p>
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<p>Design process of the embroidered textile strain sensor. First, a CAD model of the sensor is created. Then, the CAD model is digitized to produce an embroidery compatible file that will be read by an embroidery machine. Finally, the sensor is embroidered based on a set of specifications defined during the digitization phase.</p>
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<p>Examples of textile structures. (<b>a</b>) A close up view of a weaved structure. (<b>b</b>) A close up view of a knitted structure.</p>
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<p>Digital representation of the embroidered textile strain sensor. The red lines represent the running stitch direction and the blue lines show the underpath that will be followed by the needle when embroidering. Changes in resistance happen when the running stitch contacts the underpath.</p>
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<p>The embroidered textile strain sensor with dimensions of 90 by 25 mm. Wires are attached to each end of the sensor using grommets.</p>
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<p>Typical response of a strain sensor when stretched. Here, several properties are shown, including hysteresis, sensor drift, and working range. Note that no scale is provided for the <span class="html-italic">x</span> and <span class="html-italic">y</span> axis, as no real data were used in this example.</p>
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<p>Testing setup used for collecting data from the embroidered textile strain sensors.</p>
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<p>Sensor S1 strain data over the 1st, 11th, 40th, and 100th stretching cycle.</p>
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<p>Sensor S2 strain data over the 1st, 11th, 40th, and 100th stretching cycle.</p>
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<p>Sensor S3 strain data over the 1st, 11th, 40th, and 100th stretching cycle.</p>
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<p>Linearity results for Sensor S1. Linearity data from Cycle 1 are shown over a 7.5–66% working range, whereas linearity data from Cycles 50 and 100 are shown over a 40–66% working range.</p>
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<p>Linearity results for Sensor S2. Linearity data from Cycle 1 are shown over a 7.5–66% working range, whereas linearity data from Cycles 50 and 100 are shown over a 40–66% working range.</p>
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<p>Linearity results for Sensor S3. Linearity data from Cycle 1 is shown over a 7.5–66% working range, whereas linearity data from Cycles 50 and 100 are shown over a 40–66% working range.</p>
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<p>Sensor drift over the course of 100 stretching cycles. For each of the three sensor samples, the drift stabilizes around the 40th cycle. The black stars on each plot indicate the maximum strain applied (66%), which was measured halfway through the stretching cycle.</p>
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<p>Average DTW cost across the three sensor samples for Cycles 10 to 100. The cost function was computed using the squared euclidean distance for each sensor pair combination. The highest average cost function (<math display="inline"><semantics> <mrow> <mn>2.752</mn> <mo>±</mo> <mn>2.398</mn> </mrow> </semantics></math>) was for the 10th cycle (in red), whereas the lowest average cost function (<math display="inline"><semantics> <mrow> <mn>0.25</mn> <mo>±</mo> <mn>0.052</mn> </mrow> </semantics></math>) corresponded to the 40th cycle and is shown in green.</p>
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<p>Formation of loops (circled in yellow) underneath the fabric substrate. These loops are produced due to thread tension imbalances that affect the performance of the sensor over a continuous number of stretching cycles.</p>
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<p>Rearrangement of fibres within the conductive thread used. (<b>a</b>) Initial position of the fibres. Each blue dot represents a fibre that is not in contact with neighbouring ones. When the sensor is stretched, the cross-sectional area of the conductive thread decreases, which increases the total number of fibres that touch each other (red dots). (<b>b</b>) Position of the fibres within the conductive thread after unstretching the sensor. Some of these fibres remain in contact with their neighbouring ones, which decreases the overall resistance of the sensor and its working range. When stretching the sensor consecutive times, some of the fibres stop contacting each other, which affects the ability of the sensor to detect changes in resistance.</p>
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<p>Data similarities assessed by applying the DTW technique on the resistance data of each sensor pair for Cycle 10. The <span class="html-italic">y</span> axis on each plot represent the normalized resistance data; and the <span class="html-italic">x</span> axis on each plot represents the resistance sample number compared during the computation of the warping path of the DTW algorithm.</p>
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<p>Data similarities are assessed by applying the DTW technique on the resistance data of each sensor pair for Cycle 40. The <span class="html-italic">y</span> axis on each plot represent the normalized resistance data; and the <span class="html-italic">x</span> axis on each plot represents the resistance sample number compared during the computation of the warping path of the DTW algorithm.</p>
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34 pages, 60201 KiB  
Article
Textile Knitted Stretch Sensors for Wearable Health Monitoring: Design and Performance Evaluation
by Md Abdullah al Rumon, Gozde Cay, Vignesh Ravichandran, Afnan Altekreeti, Anna Gitelson-Kahn, Nicholas Constant, Dhaval Solanki and Kunal Mankodiya
Biosensors 2023, 13(1), 34; https://doi.org/10.3390/bios13010034 - 27 Dec 2022
Cited by 6 | Viewed by 4587
Abstract
The advancement of smart textiles has led to significant interest in developing wearable textile sensors (WTS) and offering new modalities to sense vital signs and activity monitoring in daily life settings. For this, textile fabrication methods such as knitting, weaving, embroidery, and braiding [...] Read more.
The advancement of smart textiles has led to significant interest in developing wearable textile sensors (WTS) and offering new modalities to sense vital signs and activity monitoring in daily life settings. For this, textile fabrication methods such as knitting, weaving, embroidery, and braiding offer promising pathways toward unobtrusive and seamless sensing for WTS applications. Specifically, the knitted sensor has a unique intermeshing loop structure which is currently used to monitor repetitive body movements such as breathing (microscale motion) and walking (macroscale motion). However, the practical sensing application of knit structure demands a comprehensive study of knit structures as a sensor. In this work, we present a detailed performance evaluation of six knitted sensors and sensing variation caused by design, sensor size, stretching percentages % (10, 15, 20, 25), cyclic stretching (1000), and external factors such as sweat (salt-fog test). We also present regulated respiration (inhale–exhale) testing data from 15 healthy human participants; the testing protocol includes three respiration rates; slow (10 breaths/min), normal (15 breaths/min), and fast (30 breaths/min). The test carried out with statistical analysis includes the breathing time and breathing rate variability. These testing results offer an empirically derived guideline for future WTS research, present aggregated information to understand the sensor behavior when it experiences a different range of motion, and highlight the constraints of the silver-based conductive yarn when exposed to the real environment. Full article
(This article belongs to the Special Issue Devices and Wearable Devices toward Innovative Applications)
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<p>Technical notations for the knitted structures: 1 × 1-one conductive and one non-conductive yarn, 1 × 2-one conductive and two non-conductive yarns. All the yarn is conductive and solid.</p>
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<p>Simulation of plain knit structure composed of conductive yarn and 100% polyester yarn (non-conductive).</p>
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<p>Knitted sensors. Sensor-1 (1 × 1), Sensor-2 (solid), Sensor-3 (solid), Sensor-4 (solid), Sensor-5 (1 × 2), and Sensor-6 (hybrid solid).</p>
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<p>Plain knit structures and components.</p>
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<p>Simulation of the knitted sensor’s sensing mechanism. Contact points between the top arc and bottom arc before stretching and after stretching.</p>
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<p>The in-lab designed electromechanical setup for cyclic tests.</p>
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<p>Resistance difference of all the sensors after different stretching.</p>
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<p>Continuous stretching (0–25%) test results.</p>
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<p>Durability-test error chart. Changes in resistance (before and after stretching 25%) in 1 cycle and 1000 cycles.</p>
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<p>Durability test of sensor-6 (1000 cycle).</p>
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<p>Salt-fog test error chart. Change in resistance before and after interaction with salt water.</p>
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<p>Resistance changes (sensor-6) during interaction with salt and water.</p>
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<p>Electrochemical changes of silver-based conductive yarn after the interaction with salt water.</p>
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<p>SEM images and elemental EDS analysis of the silver-coated fiber before salt-fog test (<b>a</b>,<b>b</b>) and after salt fog test (<b>c</b>,<b>d</b>).</p>
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<p>Hysteresis of the knitted sensor (sensor-6) for different stretching %.</p>
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<p>Human testing and data acquisition system.</p>
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<p>Respiration data analysis (Participant-9). Left-raw and filtered data, right-peak detection for inhale and exhale.</p>
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<p>Breathing−time variability of 15 participants during the breathing test (slow, normal, and fast). Rf refers to the referenced breathing time—Slow (60 s), Normal (40 s), Fast (20 s).</p>
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<p>Breathing−rate (BR) variability and error analysis for 15 participants.</p>
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<p>Durability Result (Sensor-1).</p>
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<p>Durability Result (Sensor-2).</p>
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<p>Durability Result (Sensor-3).</p>
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<p>Durability Result (Sensor-4).</p>
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<p>Durability Result (Sensor-5).</p>
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<p>Salt-fog test data of (sensor-1).</p>
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<p>Salt-fog test data of (sensor-2).</p>
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<p>Salt-fog test data of (sensor-3).</p>
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<p>Salt-fog test data of (sensor-4).</p>
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<p>Salt-fog test data of (sensor-5).</p>
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<p>Hysteresis (sensor-1).</p>
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<p>Hysteresis (sensor-2).</p>
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<p>Hysteresis (sensor-3).</p>
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<p>Hysteresis (sensor-4).</p>
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<p>Hysteresis (sensor-5).</p>
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<p>Breathing Test data of Participant number-1.</p>
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<p>Breathing Test data of Participant number-2.</p>
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<p>Breathing Test data of Participant number-3.</p>
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<p>Breathing Test data of Participant number-4.</p>
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<p>Breathing Test data of Participant number-5.</p>
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<p>Breathing Test data of Participant number-6.</p>
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<p>Breathing Test data of Participant number-7.</p>
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<p>Breathing Test data of Participant number-8.</p>
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<p>Breathing Test data of Participant number-9.</p>
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<p>Breathing Test data of Participant number-10.</p>
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<p>Breathing Test data of Participant number-11.</p>
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<p>Breathing Test data of Participant number-12.</p>
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<p>Breathing Test data of Participant number-13.</p>
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<p>Breathing Test data of Participant number-14.</p>
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<p>Breathing Test data of Participant number-15.</p>
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11 pages, 3478 KiB  
Article
Wireless Communication Platform Based on an Embroidered Antenna-Sensor for Real-Time Breathing Detection
by Mariam El Gharbi, Raúl Fernández-García and Ignacio Gil
Sensors 2022, 22(22), 8667; https://doi.org/10.3390/s22228667 - 10 Nov 2022
Cited by 6 | Viewed by 1907
Abstract
Wearable technology has been getting more attention for monitoring vital signs in various medical fields, particularly in breathing monitoring. To monitor respiratory patterns, there is a current set of challenges related to the lack of user comfort, reliability, and rigidity of the systems, [...] Read more.
Wearable technology has been getting more attention for monitoring vital signs in various medical fields, particularly in breathing monitoring. To monitor respiratory patterns, there is a current set of challenges related to the lack of user comfort, reliability, and rigidity of the systems, as well as challenges related to processing data. Therefore, the need to develop user-friendly and reliable wireless approaches to address these problems is required. In this paper, a novel, full, compact textile breathing sensor is investigated. Specifically, an embroidered meander dipole antenna sensor integrated into an e-textile T-shirt with a Bluetooth transmitter for real-time breathing monitoring was developed and tested. The proposed antenna-based sensor is designed to transmit data over wireless communication networks at 2.4 GHz and is made of a silver-coated nylon thread. The sensing mechanism of the proposed system is based on the detection of a received signal strength indicator (RSSI) transmitted wirelessly by the antenna-based sensor, which is found to be sensitive to stretch. The respiratory system is placed on the middle of the human chest; the area of the proposed system is 4.5 × 0.48 cm2, with 2.36 × 3.17 cm2 covered by the transmitter module. The respiratory signal is extracted from the variation of the RSSI signal emitted at 2.4 GHz from the detuned embroidered antenna-based sensor embedded into a commercial T-shirt and detected using a laptop. The experimental results demonstrated that breathing signals can be acquired wirelessly by the RSSI via Bluetooth. The RSSI range change was from −80 dBm to −72 dBm, −88 dBm to −79 dBm and −85 dBm to −80 dBm during inspiration and expiration for normal breathing, speaking and movement, respectively. We tested the feasibility assessment for breathing monitoring and we demonstrated experimentally that the standard wireless networks, which measure the RSSI signal via standard Bluetooth protocol, can be used to detect human respiratory status and patterns in real time. Full article
(This article belongs to the Special Issue Wearable Antennas and Sensors for Microwave Applications)
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<p>Schematic representation of the ventral body cavity: (<b>a</b>) expiration, (<b>b</b>) inspiration and (<b>c</b>) chest movement during inhalation and exhalation.</p>
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<p>Main steps for the fabrication of the embroidered antenna-based sensor. (<b>a</b>) Measurement setup of the dielectric properties of material, (<b>b</b>) Antenna design model, (<b>c</b>) Digitization and (<b>d</b>) Embroidered prototype.</p>
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<p>Block diagram of breathing monitoring.</p>
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<p>Procedure to detect human breathing status.</p>
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<p>Person under test wearing the e-textile for breathing monitoring: (<b>a</b>) experimental setup configuration and (<b>b</b>) photograph of experimental setup.</p>
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<p>Examples of eupnea breathing signals: (<b>a</b>) normal breathing in stable position, (<b>b</b>) normal breathing while speaking and (<b>c</b>) normal breathing while moving.</p>
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<p>Example of abnormal breathing status.</p>
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<p>Breathing detection systems embedded into textile T-shirt: (<b>a</b>) system 1 (our previous work) based on the resonant frequency shift using VNA, (<b>b</b>) proposed system based on the RSSI detected wirelessly using a base station.</p>
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13 pages, 5200 KiB  
Article
Weft-Knitted Spacer Fabric for Highly Stretchable–Compressible Strain Sensor, Supercapacitor, and Joule Heater
by Lu Dou, Zhen Zeng, Deshan Cheng, Shengyu Li, Wei Ke and Guangming Cai
Nanomaterials 2022, 12(20), 3684; https://doi.org/10.3390/nano12203684 - 20 Oct 2022
Cited by 7 | Viewed by 2225
Abstract
The development of wearable electronic devices has greatly stimulated the research interest of textile-based strain sensors, which can effectively combine functionality with wearability. In this work, the fabrication of highly stretchable and compressible strain sensors from weft-knitted spacer fabric was reported. Carbon nanotubes [...] Read more.
The development of wearable electronic devices has greatly stimulated the research interest of textile-based strain sensors, which can effectively combine functionality with wearability. In this work, the fabrication of highly stretchable and compressible strain sensors from weft-knitted spacer fabric was reported. Carbon nanotubes and polypyrrole were deposited on the surface of fabric via an in situ polymerization approach to reduce the electrical resistance. The as-fabricated WSP-CNT-PPy strain sensor exhibits high electrical conductivity and stable strain-sensing performance under different stretching deformations. The WSP-CNT-PPy strain sensor can be stretched up to 450% and compressed to 60% with a pressure of less than 50 KPa, which can be attributed to the unique loop and interval filament structures. The distinguishing response efficiency of WSP-CNT-PPy can effectively detect faint and strenuous body movements. In addition, the electrochemical behavior of WSP-CNT-PPy was also characterized to study the comprehensive properties. The electro-heating performance was also evaluated for feasible Joule heater applications. This work demonstrates the practicability of WSP-CNT-PPy strain sensor fabric for real-time monitoring in promising wearable garments. Full article
(This article belongs to the Section Nanoelectronics, Nanosensors and Devices)
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<p>Diagram of the fabrication process of the WSP-CNT-PPy strain sensor.</p>
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<p>(<b>a</b>) Optical images of the WSP strain sensor under different elongation conditions and (<b>b</b>) inclination angle of interval filament under different compression conditions.</p>
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<p>SEM images of pristine weft-knitted spacer fabric (<b>a</b>–<b>c</b>) surface and cross section (<b>d</b>–<b>f</b>) at different magnifications and SEM images of the WSP-CNT-PPy strain sensor (<b>g</b>–<b>i</b>) surface and cross section (<b>j</b>–<b>l</b>) at different magnifications.</p>
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<p>(<b>a</b>,<b>b</b>) Mechanical strength of WSP, WSP-CNT, and WSP-CNT-PPy; (<b>c</b>) cyclic stress–strain curves; (<b>d</b>) pressure under different strains of WSP, WSP-CNT, and WSP-CNT-PPy; (<b>e</b>) cyclic pressure–strain curves; and (<b>f</b>) electrical resistance of WSP-CNT dipped into 0.15 wt % CNT solutions for 1 to 3 times (denoted as WSP-CNT1, WSP-CNT2, and WSP-CNT3, respectively) and WSP-CNT-PPy.</p>
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<p>(<b>a</b>) I–V curves of elongation; (<b>b</b>) resistance of different strain conditions; (<b>c</b>–<b>f</b>) ΔR/R0 vs. cyclic strains of 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 80%, 100%, 200%, 300%, and 400%; (<b>g</b>) function of relative resistance charge (ΔR/R<sub>0</sub>); (<b>h</b>) ΔR/R<sub>0</sub> with 10% cyclic strain at various loading conditions; and (<b>i</b>) stability of the WSP-CNT-PPy strain sensor under a cyclic strain of 5%.</p>
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<p>Detection of various human body movements including: (<b>a</b>) shallow-deep breath, (<b>b</b>) finger up-down, and (<b>c</b>) wrist up-down.</p>
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<p>(<b>a</b>) Pressure-strain curve; (<b>b</b>) cyclic pressure-strain curve under the compression strain of 20%, 30%, 40%, and 50%; (<b>c</b>) relative resistance change (ΔR/R0) as a function of pressure; (<b>d</b>,<b>e</b>) ΔR/R<sub>0</sub> under a cyclic pressure of 36 Pa, 72 Pa, 108 Pa, and 180 Pa, and 0.5 KPa, 5 KPa, and 20 KPa; (<b>f</b>) ΔR/R0 change with the cyclic pressure of 0.5 KPa under 1 mm/min, 5 mm/min, 20 mm/min, and 60 mm/min loading speed; (<b>g</b>) durability of WSP-CNT-PPy under 180 KPa pressure; (<b>h</b>) I-V curves with various pressure; and (<b>i</b>) resistance with different pressure.</p>
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<p>Detection of various compression movements including (<b>a</b>) finger press, (<b>b</b>) foot press, and (<b>c</b>) counterweight press.</p>
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<p>(<b>a</b>) I-V curves of WSP-CNT-PPy under various rates; (<b>b</b>) GCD curves with different areal currents; (<b>c</b>) Nyquist plot under the amplitude of 50 mV/s; (<b>d</b>) cycle stability curve; (<b>e</b>) CV curves of various strain pressure; (<b>f</b>) GCD curves of different strain conditions; (<b>g</b>) the efficiency of CV and GCD curves is maintained with the strain ranging from 0 to 40%; (<b>h</b>) CV curves under different pressure conditions; (<b>i</b>) GCD curves of different pressure conditions; (<b>j</b>) capacitance maintain of CV and GCD curves with the pressure of 0 to 30%; and (<b>k</b>) single electrode, and electrodes connected in series and parallel.</p>
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<p>(<b>a</b>) The heating process of WSP-CNT-PPy under different applied voltage; (<b>b</b>) the increase in temperature with the increasing voltage; (<b>c</b>) experimental value and fitted linear curve between temperature and square of voltage; (<b>d</b>) heating process under cyclic voltage of 3 V, 4 V, 5 V, and 6 V; (<b>e</b>) heating process under different cycles; and (<b>f</b>) heat-imaging of the WSP-CNT-PPy fabric.</p>
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19 pages, 6993 KiB  
Article
Textile Strain Sensor Enhancement by Coating Metal Yarns with Carbon-Filled Silicone
by Rike Brendgen, Ramona Nolden, Jasmin Simon, Theresa Junge, Kerstin Zöll and Anne Schwarz-Pfeiffer
Polymers 2022, 14(13), 2525; https://doi.org/10.3390/polym14132525 - 21 Jun 2022
Cited by 4 | Viewed by 2457
Abstract
Flexible and stretchable strain sensors are an important development for measuring various movements and forces and are increasingly used in a wide range of smart textiles. For example, strain sensors can be used to measure the movements of arms, legs or individual joints. [...] Read more.
Flexible and stretchable strain sensors are an important development for measuring various movements and forces and are increasingly used in a wide range of smart textiles. For example, strain sensors can be used to measure the movements of arms, legs or individual joints. Thereby, most strain sensors are capable of detecting large movements with a high sensitivity. Very few are able to measure small movements, i.e., strains of less than 5%, with a high sensitivity, which is necessary to carry out important health measurements, such as breathing, bending, heartbeat, and vibrations. This research deals with the development of strain sensors capable of detecting strain of 1% with a high sensitivity. For this purpose, a total of six commercially available metallic yarns were coated with a carbon-containing silicone coating. The process is based on a vertical dip-coating technology with a self-printed 3D coating bath. Afterwards, the finished yarns were interlooped and stretched by 1% while electrical resistance measurements were carried out. It was shown that, although the coating reduced the overall conductivity of the yarns, it also improved their sensitivity to stress. Conclusively, highly sensitive strain sensors, designed specially for small loads, were produced by a simple coating set-up and interlooping structure of the sensory yarns, which could easily be embedded in greater textile structures for wearable electronics. Full article
(This article belongs to the Special Issue Polymer-Based Materials for Sensors)
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<p>Schematic cross-section of carbon-filled, silicone-coated metal yarn and their deformation upon strain that causes the change in electrical resistance.</p>
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<p>Schematic drawing of coating set-up.</p>
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<p>Schematic drawing of four-point probe method carried out at the interlooped hybrid yarns.</p>
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<p>Image of the real measurement set-up of the interlooped sensory yarns.</p>
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<p>Light microscopic measurement of the layer thickness of the coating exemplarily here at the Silvertech substrate.</p>
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<p>Light microscopic images of coated yarns.</p>
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<p>Cross-sectional view of coated samples showing the sheathing of substrates with the coating film.</p>
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<p>Change of electrical resistance of various carbon-silicone coated substrates upon loading and unloading, showing the working principle of the sensory yarn as electrical resistance decreases upon 1% loading.</p>
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<p>Change of electrical resistance of uncoated substrates upon loading and unloading showing too few changes during load cycles.</p>
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<p>Single display of change of electrical resistance of coated substrates with standard deviation.</p>
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<p>Single display of change of electrical resistance of uncoated substrates with standard deviation.</p>
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<p>Factor of resistance change of the uncoated substrate as comparison to the coated substrates to illustrate the influence of the coating on the sensitivity of the yarns.</p>
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<p>Mean factor of resistance change of all cycles demonstrating the enhancement of sensory properties towards loading by coating.</p>
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5 pages, 2474 KiB  
Proceeding Paper
Textile Tactile Senor Based on Ferroelectret for Gesture Recognition
by Junjie Shi and Mahmoud Wagih
Eng. Proc. 2022, 15(1), 8; https://doi.org/10.3390/engproc2022015008 - 11 Mar 2022
Cited by 3 | Viewed by 1254
Abstract
Ferroelectret is a charged polymer with cellular void structures that create giant dipole moments across the material’s thickness. In this work, we present the first realization of a wearable textile substrate tactile sensor based on Polypropylene (PP) ferroelectret material for gesture recognition. As [...] Read more.
Ferroelectret is a charged polymer with cellular void structures that create giant dipole moments across the material’s thickness. In this work, we present the first realization of a wearable textile substrate tactile sensor based on Polypropylene (PP) ferroelectret material for gesture recognition. As a result, the sensitivity of the fabricated sensor is 0.21 V/kPa in the pressure range of 0–20 kPa. The ferroelectret tactile sensor adheres to a glove’s surface for detecting human movements such as bending or the relaxation motion of the palm and the bending or stretching motion of each finger, enabling the successful detection of small finger gestures around a 400 mV output. Full article
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<p>(<b>a</b>) The fabrication process for the ferroelectret tactile sensor; (<b>b</b>) the photo of the fabricated tactile sensor.</p>
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<p>(<b>a</b>) The schematic of diagram of the ferroelectret tactile sensor system for gesture recognition; (<b>b</b>) the image of ferroelectret tactile sensor for finger bending.</p>
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<p>The output voltage of the tactile sensor installed at fingers and palm during a fist gesture.</p>
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<p>(<b>a</b>) Output voltage of the ferroelectret tactile sensor under different states for a finger bending; (<b>b</b>) output voltage response under different pressure.</p>
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17 pages, 13441 KiB  
Article
Coating of Silicone Monofilaments with Elastic Carbon Black-Silver-Silicone Layers and Their Characterization Especially with Regard to the Change of the Electrical Resistance in Dependence on Strain
by Kristina Klinkhammer, Ramona Nolden, Rike Brendgen, Manuela Niemeyer, Kerstin Zöll and Anne Schwarz-Pfeiffer
Polymers 2022, 14(4), 806; https://doi.org/10.3390/polym14040806 - 19 Feb 2022
Cited by 3 | Viewed by 2263
Abstract
Smart textiles have properties that outperform the conventional protective and decorative function of textiles. By integrating special sensors into clothing, body functions and movements can be detected. Piezoresistive sensors measure a change in electrical resistance due to the application of force in the [...] Read more.
Smart textiles have properties that outperform the conventional protective and decorative function of textiles. By integrating special sensors into clothing, body functions and movements can be detected. Piezoresistive sensors measure a change in electrical resistance due to the application of force in the form of stretching, pressure or bending. In order to manufacture such sensors, conventional non-conductive textile materials need to be made conductive by finishing processes. Therefore, a non-conductive silicone monofilament was coated with a conductive carbon silicone and additional silver-containing components and investigated for its suitability as a strain sensor. The changes in electrical resistance and the gauge factor as a measure of the sensitivity of a sensor were measured and calculated. In this publication, the electrical properties of such a filament-based sensor in the context of particle composition and concentration are discussed. The electrical resistance was already significantly reduced in a first step by coating with conductive carbon silicone (145 kΩ). The addition of silver-containing components further reduced the electrical resistance in a second step. Thereby, flat flakes of silver proved to be much more effective than silver-containing particles (5 kΩ at 20% addition). The former was easier to integrate into the coating and formed contact surfaces with each other at higher concentrations. Stretching the samples increased the resistance by enlarging the distance between the conductive components. With 30% silver-coated glass flakes in the coating, the highest gauge factor of 0.33 was achieved. Consequently, the changes in electrical resistance during stretching can be exploited to detect motion and the gauge factor indicates that even small changes in strain can be detected, so the herein developed coated monofilaments are suggested for use as strain sensors. Future work includes matching the particle composition and concentration to the exact application and investigating the sensors in the field. Full article
(This article belongs to the Section Polymer Processing and Engineering)
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<p>Photographs of the monofilament; left: Light microscopy; size bar 1 mm, right: SEM; size bar 300 µm; (<b>a</b>,<b>b</b>) monofilament uncoated; (<b>c</b>,<b>d</b>) monofilament with carbon-silicone coating.</p>
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<p>SEM images of coated monofilaments each with 20% silver addition. (<b>a</b>) Ag352000, (<b>b</b>) AgVO180-4, (<b>c</b>) Ag1.53, (<b>d</b>) Ag1.36, (<b>e</b>) Ag F56T, (<b>f</b>) AgES4. Size bar = 500 µm.</p>
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<p>3D laser microscopy images of monofilament coated with carbon silicone and Ag352000, (<b>a</b>) 5%, (<b>b</b>) 10%, (<b>c</b>) 15%, (<b>d</b>) 20%, (<b>e</b>) 25%, (<b>f</b>) 30%, (<b>g</b>) 35%, (<b>h</b>) 40%.</p>
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<p>Detailed laser microscopy images of monofilament coated with carbon silicone and Ag352000, (<b>a</b>) 5%, (<b>b</b>) 25%, (<b>c</b>) 30%, (<b>d</b>) 40%; size bars 20 µm.</p>
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<p>EDX mapping of Ag32000_25%; (<b>a</b>) SEM image; (<b>b</b>) Ag; (<b>c</b>) superimposed image of all relevant elements and SEM image. Size bar 100 µm.</p>
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<p>Electrical Resistance R as function of elongation for carbon silicone coated monofilament (MF-CSi) (length in relaxed state 150 mm).</p>
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<p>Electrical Resistance R as function of elongation for different silver additives (20%). The lower curves belong to stress, the upper curves belong to relaxation of the monofilament.</p>
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<p>Electrical Resistance R as function of concentration of Ag352000 at 0% elongation.</p>
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<p>Electrical Resistance as function of elongation for different concentrations of Ag352000. The lower curve belongs to stress, the upper curve belongs to release of the monofilament.</p>
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<p>Gauge factors for different concentrations of Ag35200 flakes in dependency on elongation.</p>
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14 pages, 4283 KiB  
Article
Ultrasensitive Strain Sensor Based on Pre-Generated Crack Networks Using Ag Nanoparticles/Single-Walled Carbon Nanotube (SWCNT) Hybrid Fillers and a Polyester Woven Elastic Band
by Yelin Ko, Ji-seon Kim, Chi Cuong Vu and Jooyong Kim
Sensors 2021, 21(7), 2531; https://doi.org/10.3390/s21072531 - 4 Apr 2021
Cited by 27 | Viewed by 5182
Abstract
Flexible strain sensors are receiving a great deal of interest owing to their prospective applications in monitoring various human activities. Among various efforts to enhance the sensitivity of strain sensors, pre-crack generation has been well explored for elastic polymers but rarely on textile [...] Read more.
Flexible strain sensors are receiving a great deal of interest owing to their prospective applications in monitoring various human activities. Among various efforts to enhance the sensitivity of strain sensors, pre-crack generation has been well explored for elastic polymers but rarely on textile substrates. Herein, a highly sensitive textile-based strain sensor was fabricated via a dip-coat-stretch approach: a polyester woven elastic band was dipped into ink containing single-walled carbon nanotubes coated with silver paste and pre-stretched to generate prebuilt cracks on the surface. Our sensor demonstrated outstanding sensitivity (a gauge factor of up to 3550 within a strain range of 1.5–5%), high stability and durability, and low hysteresis. The high performance of this sensor is attributable to the excellent elasticity and woven structure of the fabric substrate, effectively generating and propagating the prebuilt cracks. The strain sensor integrated into firefighting gloves detected detailed finger angles and cyclic finger motions, demonstrating its capability for subtle human motion monitoring. It is also noteworthy that this novel strategy is a very quick, straightforward, and scalable method of fabricating strain sensors, which is extremely beneficial for practical applications. Full article
(This article belongs to the Special Issue Textile-Based Sensors: E-textiles, Devices, and Integrated Systems)
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<p>The manufacturing process for strain sensors based on polyester woven elastic band (PEB): (<b>a</b>) ultrasonication of single-walled carbon nanotube (SWCNT) ink; (<b>b</b>) dipping PEB into SWCNT ink; (<b>c</b>) squeezing SWCNT/PEB; (<b>d</b>) drying SWCNT/PEB; (<b>e</b>) screen printing for silver-paste coating; (<b>f</b>) drying Ag/SWCNT/PEB; (<b>g</b>) pre-crack formation by pre-stretching to make pre-cracked Ag/SWCNT/PEB.</p>
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<p>Top-view SEM images of pristine PEB at 300 um (<b>a</b>); 80 um (<b>b</b>); 20 um (<b>c</b>); SWCNT/PEB at 300 um (<b>d</b>); 80 um (<b>e</b>); 20 um (<b>f</b>); Ag/SWCNT/PEB at 300 um (<b>g</b>); 80 um (<b>h</b>); 20 um (<b>i</b>); Pre-cracked Ag/SWCNT/PEB at 300 um (<b>j</b>); 80 um (<b>k</b>); 20 um (<b>l</b>); Cross-sectional SEM images of pre-cracked Ag/SWCNT/PEB at 125 um (<b>m</b>); 50 um (<b>n</b>); 20 um (<b>o</b>).</p>
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<p>(<b>a</b>) Schematic structure of the pre-cracked strain sensor; (<b>b</b>) Pre-crack morphology of the pre-cracked strain sensor; (<b>c</b>) Flexibility of the pre-cracked strain sensor; (<b>d</b>) Customized Universal Testing Machine (UTM); (<b>e</b>) Relative changes in resistance versus strain of non-cracked SWCNT, pre-cracked SWCNT, non-cracked Ag/SWCNT, and pre-cracked Ag/SWCNT sensors.</p>
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<p>(<b>a</b>) Strain sensing mechanism of the pre-cracked strain sensor: the dark gray layer represents PEB dipped into SWCNT inks; the light gray layer shows the silver coating on SWCNT/PEB; (<b>b</b>) Resistance model of the crack structure; (<b>c</b>) Fabric structure of the polyester woven elastic band utilized in the present study.</p>
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<p>(<b>a</b>) Crack images for the pre-cracked strain sensors according to pre-stretching strains of 0%, 100%, 150%, and 200%; (<b>b</b>) Relative changes in resistance versus strain of samples pre-stretched at 0%, 100%, 150%, and 200% strain.</p>
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<p>Strain sensing properties of the pre-cracked Ag/SWCNT sensor including (<b>a</b>) Hysteresis; (<b>b</b>) Gauge factors; (<b>c</b>) Signals at different loading strains; (<b>d</b>) Responses at different loading frequencies; (<b>e</b>) Durability after 5000 stretching–releasing cycles.</p>
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<p>(<b>a</b>) Construction of the polyester woven elastic band utilized as the stretchable substrate; (<b>b</b>) Schematic diagram of an example knitted fabric in initial and stretched states; (<b>c</b>) Dimensional changes of polyester woven elastic band and knitted stretchable fabric examples under 50% applied strain.</p>
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<p>(<b>a</b>) Structure of the sensor integrated into the firefighters’ glove; (<b>b</b>) Prototype of the finger-motion-sensing firefighter’s glove; (<b>c</b>) Relative resistance changes of finger bending at different angles; (<b>d</b>) Relative resistance changes of cyclic finger motions of extending and bending.</p>
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13 pages, 1287 KiB  
Article
A Fabric-Based Textile Stretch Sensor for Optimized Measurement of Strain in Clothing
by Yetanawork Teyeme, Benny Malengier, Tamrat Tesfaye and Lieva Van Langenhove
Sensors 2020, 20(24), 7323; https://doi.org/10.3390/s20247323 - 20 Dec 2020
Cited by 13 | Viewed by 5202
Abstract
Fabric stretch sensors are available as planar fabrics, but their reliability and reproducibility are low. To find a good working setup for use in an elastic sports garment, the design of such sensors must be optimized. The main purpose of this study was [...] Read more.
Fabric stretch sensors are available as planar fabrics, but their reliability and reproducibility are low. To find a good working setup for use in an elastic sports garment, the design of such sensors must be optimized. The main purpose of this study was to develop resistive strain sensors from stretchable conductive fabric and investigating the influence of stretchability on conductivity/resistivity. The influence of using the sensor in a sweat rich environment was also determined, in order to evaluate the potential use of the sensor in sporting garments. The sensor resistivity performance was analyzed for its sensitivity, working range, and repeatability and it was determined what makes the sensitivity when elongated or stretched. The resistivity was found to decrease with elongation if no sweat is present, this can be due to molecular rearrangement and a higher degree of orientation that improves the conductivity of a material. The result from this finding also shows that for wearable applications the commercial EeonTexTM conductive stretchable fabric did not show a considerable resistivity increase, nor a good sensitivity. The sensitivity of the sensor was between 0.97 and 1.28 and varies with different elongation %. This may be due to the mechanical deformation characteristics of knitted samples that lead to changes in conductivity. We advise that the testing performed in this paper is done by default on new stretch sensitive textile materials, so practical use of the material can be correctly estimated. Full article
(This article belongs to the Section Physical Sensors)
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<p>List of material used for sensor development: (<b>a</b>) conductive stretchable fabric, (<b>b</b>) silver-plated conductive thread, (<b>c</b>) nylon/spandex knitted fabric.</p>
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<p>Assembled test specimen on the base fabric of 25 cm (C + A + C).</p>
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<p>A test for identifying the warp and course direction of conductive stretchable fabric.</p>
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<p>Test specimens with dimension.</p>
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<p>Experimental setup for the measurement of resistivity.</p>
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<p>Average resistance response of the sensor to a given elongation and SEM.</p>
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<p>Sensitivity (%) the sensor to a sample under cyclic testing.</p>
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<p>Response to a given extension with time (30 s interval) [type III].</p>
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<p>Resistance values of the sensor at 0% stretch after a pre-stretch of 15%.</p>
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<p>Sensitivity between sensor with and without sweat.</p>
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<p>The resistivity for a given waiting time over elongation after sweat was applied.</p>
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<p>Average resistance value for a given elongation on repeat measurement at different waiting time.</p>
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<p>Resistivity response of sweated sensor vs non-sweated.</p>
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