Smart Textile-integrated Thermochromic Display for Real-time Temperature Monitoring in Elderly Care

Smart Textile-integrated Thermochromic Display for Real-time Temperature Monitoring in Elderly Care | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Smart Textile-integrated Thermochromic Display for Real-time Temperature Monitoring in Elderly Care Ching Lee, Jeanne Tan, Hiu Ting Tang, Annie Yu, Jun Jong Tan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6366433/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract With the rapidly aging population, maintaining personalized thermal comfort and preventing heat loss for elderly individuals has become increasingly important. Heating textiles provide an effective solution for warmth; however, without proper monitoring, the risk of overheating in real-world applications remains a concern. To address this challenge, thermochromic textiles offer a visual, real-time temperature indication through colour change, enhancing both safety and usability. In this study, thermochromic electric heating textiles were developed in woven and knitted structures, each offering distinct hand feel and performance characteristics. Key parameters, including heating efficiency, thermochromic response, thermal insulation, and overall thermal comfort, were systematically analyzed and compared. Findings reveal that double-layer fabric structures exhibit superior heat distribution and heating efficiency compared to single-layer counterparts, with the double-layer woven fabric demonstrating a more pronounced thermochromic colour change upon heating. Based on these insights, a collection of thermochromic heating cushions was designed for elderly care applications. Additionally, as a proof of concept, a fully textile-based electronic control system was proposed, enabling caregivers to remotely monitor the surface temperature of the heating fabric in real time and adjust the heating levels accordingly. By bridging the fields of textile engineering, smart materials, and healthcare monitoring, this study introduces innovative design strategies that enhance both functionality and user experience in elderly-focused heating textiles. Smart textile heating textile thermochromic textile temperature monitoring elderly care Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Highlights A collection of thermochromic heating cushions for elderly care are developed in woven and knitted structures. Double-layer woven fabric shows the highest heating efficiency and colour change effect. A textile-based control system enables real-time temperature monitoring for elderly care. 1 Introduction The rapid advancement of smart textile technologies has opened new possibilities for healthcare monitoring, particularly in elderly care applications. Recent studies underscore the potential of smart textiles integrated with biosensors, which can monitor physiological parameters such as heart rate, body temperature, and pressure distribution, thereby enhancing elderly individuals' comfort, safety, and overall well-being[ 1 , 2 ]. These innovations have led to the development of textiles designed for fall detection, cardiovascular monitoring, and thermoregulation, offering valuable real-time health insights while ensuring wearer comfort[ 3 – 9 ]. Despite these advancements, a significant demand still exists for textiles that provide warmth while also incorporating real-time temperature monitoring, especially for elderly individuals with reduced thermoregulatory efficiency[ 10 – 12 ]. In elderly care, advanced textile technologies play a crucial role in providing thermal comfort. Heating textiles have been widely employed in products such as electric blankets, heating pads, and smart garments, helping elderly users maintain an optimal body temperature and prevent cold stress[ 13 , 14 ]. While these products are effective in delivering localized warmth, they pose significant overheating risks, particularly when continuous monitoring is unavailable[ 14 , 15 ]. In settings where caregivers are responsible for regulating the heating level, insufficient feedback on surface temperature changes and the elderly individual's skin condition can lead to undesirable thermal stress, discomfort, or potential burns[ 15 ]. Therefore, integrating intelligent monitoring systems into heating textiles is essential for promoting safe and efficient usage in elderly care settings. A promising approach to addressing this challenge is the incorporation of thermochromic textiles, which serve as visual indicators of temperature changes through colour variation. Unlike small display screens that may be difficult for elderly individuals to read, thermochromic textiles utilize a large, fabric-based visualization method, making temperature fluctuations easier to detect by both users and caregivers. A recent study demonstrated strong potential for thermochromic yarns as visual indicators in smart heating textiles, allowing real-time, intuitive, and non-intrusive thermal feedback[ 16 ]. However, despite these advantages, there remains a gap in understanding how fabric structure influences thermochromic performance and user comfort, particularly in elderly care applications. Given the importance of sensory perception in elderly textile applications, selecting the appropriate fabric structure is essential for ensuring user acceptance. Elderly users may have different preferences regarding surface texture and hand feel, which can significantly influence their comfort and willingness to adopt new technologies[ 17 – 19 ]. Woven and knitted textiles, the two most commonly used textile structures, offer distinct mechanical and tactile properties. Woven fabrics, with their tightly interlaced threads, provide high durability, dimensional stability, and uniform heat distribution, making them suitable for consistent thermal performance. In contrast, knitted fabrics are characterized by softness, flexibility, and stretchability, offering a comfortable and adaptive texture, which is often preferred in contact textiles for elderly users, including those with sensory sensitivities[ 20 , 21 ]. In this study, thermochromic heating textiles were fabricated in both woven and knitted structures, incorporating thermochromic yarns, silver-coated conductive heating yarns, and insulating yarns, including cotton, soybean and wool, in various combinations to optimize heating efficiency, mechanical properties, and colour-changing effects. Figure 1 a and 1 b illustrate the yarns used and the corresponding woven and knitted fabric structures, respectively. Experimental characterization revealed that double-layer structures outperformed single-layer fabrics in heat distribution and heating efficiency, with double-layer woven fabrics exhibiting the most pronounced thermochromic colour change upon heating. Figure 1 c demonstrates the heating performance and colour changes as power is supplied from 0 V (no heating) to 10 V (heating) for the double-layer knitted and woven samples, K-D2 and W-D2, respectively. Based on these findings, a collection of four thermochromic heating cushions was developed specifically for elderly care applications, as shown in Fig. 1 d and 1 e, allowing users to choose fabrics based on their preferred texture and thermal performance. Additionally, a fully textile-based electronic control system was proposed to enable caregivers to remotely monitor elderly users' skin temperature in real time and regulate the heating function accordingly. This research contributes to the advancement of thermochromic smart textiles by demonstrating their practical applications in elderly care and their potential for providing safer, more intuitive, and caregiver-friendly thermal regulation. 2 Experimental details 2.1 Electrical resistance heating theory The heating mechanism in e-textiles follows the Joule heating effect, as described by Ohm’s Law[ 21 – 23 ]. When an electric current flows through a resistance—such as metallic yarns serving as bus bars and low-resistance silver- or copper-coated polymeric yarns acting as heating elements—heat is generated, resulting in a warming effect. Ohm's law could be calculated as: P = VI = I 2 R (1) where P is the power consumption (watt), V is the voltage applied (volt), I is current (A) and R is the resistance (ohm). Figure 2 a highlights the equivalent circuit diagram of the heating fabric in both woven and knitted structures, where variables R1, R2, …, Rn represent the resistances of parallel conductive yarn strips. Additionally, variables r1, r2, …, rn and r’1, r’2, …, r’n denote pairs of contact resistances (electrodes) at left and right crossing points, respectively. Figure 2 b illustrates the electrical resistance heating process, in which connecting a power supply to the thermochromic electric heating fabric induces a colour change from pink to purple on the surface when the temperature exceeds 30°C. The power generated is directly proportional to the square of the current (I) and the resistance (R). In such systems, the amount of heat generated depends on the magnitude of the current, which in turn is governed by the resistance (R) and the applied voltage (V). This principle forms the fundamental operating mechanism of electric heating textiles, which typically regulate heating intensity using either direct current (DC) voltage regulation or pulse duty ratio regulation methods. 2.2 Fabric weaving and structure characteristics The thermochromic heating fabric in a woven structure developed for this study was based on previous study increasing the number of conductive heating yarns enhances heating efficiency[ 16 , 24 ]. The double cloth structure with a diamond pattern was chosen for its symmetry along both the vertical and horizontal axes, ensuring uniform heat distribution across each small repeat section of the fabric. The fabrication process involved weaving silver-coated heating yarn (40D, 17% silver, 83% nylon) and thermochromic yarn (150D/2) in the weft direction, while insulating passive cotton yarn (40/2s, 100% cotton) was used in the warp direction. Embroidery was applied after the weaving process to shorten the preparation time needed to replace the warp yarn with conductive yarn as a pair of electrodes. Therefore, after weaving, silver-coated yarn (200D, 18% silver, 82% nylon) was embroidered onto the fabric as electrodes, in accordance with Ohm’s Law. The weaving process was carried out using a rapier sample loom (CCI/SL7900) with dobby shedding motion at a speed of 25 rpm (as shown in Fig. 2 c), and the embroidery of the electrodes was done using a TAJIMA-SAI embroidery machine. Figure 2 d illustrates the woven structure of the e-textile, which was fabricated using a double-sided diamond twill pattern. Table 1 summarizes the characteristics of the thermochromic heating fabric specimens. The fabric thickness was measured using a digital thickness gauge. Microscopic views were taken by stereo microscope (model Leica M165 C). W-D1 utilizes thermochromic yarns that changes colour from grey to white, whereas W-D2 applies thermochromic yarns that changes colour from pink to purple when the fabric is heated to 30°C. Table 2 lists the specifications of the silver-coated conductive yarn. Table 3 provides the specifications of the conventional yarns used in the fabric specimens. 2.3 Fabric knitting and structure characteristics Seven knitted samples of thermochromic heating fabric were fabricated. To align with the double-woven cloth, the knitted fabrics were fabricated in a double jersey structure. The fabric structure consists of two electrodes positioned along the left and right edges with a main heating area in the middle. Intarsia knitting was applied to organize the heating and electrode sections. The electrodes were knitted in a double jersey using one end of silver-coated heating yarn (800D, 17% silver, 83% nylon) with a lower resistance of 0.75Ω/cm. One end of silver-coated heating yarn (70D, 17% silver, 83% nylon) with a higher resistance of 10.7Ω/cm, along with one end of 150D/2 thermochromic yarn, were used to knit front stitches simultaneously in both the heating area and electrodes, forming the heating rows. Between each heating row, an interval of eight knitting rows was inserted in the heating section using textile-based yarn. Figure 2 f illustrates the knitted structure of the e-textiles. K-S1 to K-S4 were knitted with single jersey for the intervals, while K-D1 to K-D3 used double jersey. Four ends of soybean yarn (40/2s, 50% cotton, 50% soybean) were used for the interval sections in K-S1 and K-D1. For K-S2 to K-S4 and K-D2 to K-D3, the textile-based yarn used for the intervals was wool yarn (Nm 48/2, 100% extrafine merino wool), with two ends for K-S2, K-S3, and K-D2, and three ends for K-S4 and K-D3. The knitting process was performed on a computerized flat-knitting machine (Shima Seiki SWG091N2) with a gauge of 7 at a speed of 0.5 (m/s), as shown in Fig. 2 e. The knitting programs were prepared using the incorporated computer-aided design system (SDS-ONE APEX). Table 1 Characteristics of the fabric specimens *Yarn density was measured on conditioned samples by using a magnifying glass to count the number of yarns in each wale and course. EPI (Ends Per Inch) refers to the yarns in the machine direction, while PPI (Picks Per Inch) represents those in the cross-direction. Table 2 Silver-coated conductive yarn specification Yarn Fabrication Embedded Area Yarn Resistance (Ω/cm) Yarn Count End (s) Yarn Content A Weaving Main body (Heating) 32 40D 1 17% Silver, 83% Nylon B Embroidery (on woven fabric) Electrode 2.54 200D 1 18% Silver, 82% Nylon C Knitting Main body (Heating) 10.7 70D 1 17% Silver, 83% Nylon D Knitting Electrode 0.75 800D 1 17% Silver, 83% Nylon Table 3 Conventional yarn specification of the fabric specimens Yarn Fabric Sample Yarn Count End(s) Yarn Content Cotton W-D1 W-D2 40/2s 1 100% Cotton Soybean K-S1 K-D1 32s/1 4 50% Cotton 50% Soybean Wool K-S2 K-D2 NM 1/34000 2 100% Merino wool Wool K-S3 48/2 Nm 2 100% Merino wool Wool K-S4 K-D3 48/2 Nm 3 100% Merino wool 2.4 Testing Methods Heating efficiency. The average surface temperature of the thermochromic electric heating fabrics was monitored using a FLUKE Ti32 infrared camera (Fig. 3 a) and a DC power supply (GPS3010D-30V/10A). Temperature readings were recorded at varying voltages and times, then analyzed through the Fluke Connect data analysis software. A multimeter was used to measure the fabric's resistance under different power inputs (5V, 7.5V, 10V, and 12V) to evaluate heating efficiency. Additionally, A thermometer (model: YET-610) equipped with thermocouples was attached at four evenly spaced points on the fabric surface to measure the surface temperature during the heating process. Colour measurement. A Datacolor 600™ Colour-Eye Spectrophotometer was used to analyze the reflectance of the thermochromic electric heating fabrics at 0V and 10V power supplies, in order to study the colour change of the thermochromic yarns. Fabric samples were arranged in parallel and compressed in a container with optical glass until opaque to ensure accurate and consistent colour measurements. 3-dimensional spectral reflectance data were recorded across the 400–700 nm range in 10 nm intervals, including the specular reflection component. To minimize errors, the largest aperture (30 mm) was selected, and measurements were taken randomly at four different positions and orientations on the sample surface. The average of these measurements was used as the true colour data. Optical glass correction was applied to eliminate any influence from the glass during the measurement process. Testing for thermal conductivity, Q-max and thermal insulation. The thermal conductivity, Q-max (a measurement of warm/cool feeling) and thermal insulation of the samples were assessed using the KES-F7 Thermo Labo II thermal property measurement instrument (Kato Tech. Co., Ltd, Japan). Prior to testing, all thermochromic electric heating fabrics were conditioned for 24 hours under standard conditions of 21.1°C ± 2°C and 65% ± 5% relative humidity (RH). The samples were placed between the Water box (cold plate – constant temperature box) and BT-box (hot plate; area: 5 × 5 cm²; weight: 150 g), maintained at temperatures of 30°C ± 0.3°C and 20°C ± 0.3°C, respectively. The heat flow loss W (watts) from the BT-box was recorded once a constant value was achieved. Q-max is a measurement to evaluate the instantaneous heat transfer between a fabric and the skin, indicating the warmth or coolness a material feels upon first contact. It quantifies the maximum heat flux that occurs when two surfaces at different temperatures come into contact. It can be calculated using Fourier’s Law. A higher Q-max value indicates that the fabric feels cooler to the touch because it transfers heat away from the skin more quickly, while a lower Q-max value suggests the fabric retains heat, making it feel warmer. For thermal insulation, a dry contact method was applied. Data are corrected to the value per 1°C and 1m 2 (The area of BT-plate is 100cm 2 ). The thermal conductivity (k), Q-max value, and keeping warmth ratio (%) could be determined using the following equations: \(\:\text{k}=\frac{W‧D}{A‧\varDelta\:T}\) (2) \(\:{Q}_{max}=-\text{k}‧A‧\frac{\varDelta\:T}{\varDelta\:D}\) (3) \(\:{\alpha\:}=\frac{\left({W}_{0}-W\right)}{{W}_{0}}\times\:100\) (4) where k is the thermal conductivity, Q_maxis the maximum heat flux (W/m 2 ), W (watt) is the heat flow loss, D is the thickness of the fabric, A is the fabric area and ΔT is the temperature difference of two sides of sample, W0 is the heat loss without sample and W is the heat loss with sample. Tensile and Shear test. The tensile and shear properties were measured using the KES-FB1 Tensile and Shear Tester within a measurement area of 610 × 535 × 320 mm, simulating mechanical stretching and in-plane displacement to evaluate fabric performance. Before tensile, shear, compression, bending, friction, and air permeability tests, all fabric samples were cut to a standard size of 20 × 20 cm and conditioned for 24 hours under 21.1°C ± 2°C and 65% ± 5% RH. During tensile testing, the fabric is clamped and stretched to determine tensile rigidity (LT), with values closer to 1 indicating greater firmness. For shear testing, horizontal forces simulate in-plane deformation, measuring shear rigidity (G), where higher values signal increased resistance to shearing, and elasticity for minute shear (2HG), where higher values denote poorer recoverability from initial shear deformation. Compression test. The KES-FB3-A Compression Tester (Kato Tech. Co., Ltd, Japan) was applied to measure the compression properties of fabric samples. Using a two-plate system, with one fixed and one movable plate applying a controlled vertical force, the tester evaluates how fabrics respond to compression and their ability to recover. Key metrics include compressional energy (WC), expressed in Load (gf/cm²), where higher values indicate greater susceptibility to compression. The ratio WC/W reflects the relationship between compressional energy and weight per unit area, with higher values indicating that the textile fibers compress more, resulting in a softer feel. Similarly, WC/T represents the ratio of compressional energy to thickness, where larger values indicate more compression and enhanced softness. By recording changes in fabric thickness during the compression and recovery process, the device offers insights into the material's cushioning, softness, and structural resilience. Bending test. KES-FB2 Pure Bending Tester was applied in measuring the bending properties of fabrics, assessing the stiffness, flexibility, and drapability by applying pure bending forces without shear or tension. Key measurements include bending rigidity (B) and hysteresis (2HB), which reflect stiffness and recovery after bending. The B/W ratio indicates the relationship between a fabric's stiffness and weight, with higher values leading to a stiffer appearance and poor drape. The 2HB/W ratio correlates with shape instability, where a higher value means less lively movement, and 2HB/B and 2HG/G represent the balance between elastic and hysteresis components in bending and shear deformation, respectively. Friction test. Frictional properties and surface roughness (SR) of fabrics was measured by KES-FB4-A Friction Tester which provides key insights into surface texture and tactile feel. It evaluates the coefficient of friction (MMD) and surface roughness (SMD) by passing a sensor over the fabric's surface under controlled pressure. The SR can be expressed as MMD/SMD, where the ratio of MMD (fluctuation in friction) to SMD (surface roughness) reflects the relationship between surface friction and texture. A smaller ratio indicates a smoother surface, which directly correlates to how soft or smooth the fabric feels to the touch. Air permeability test. The KES-F8 Air Permeability Tester (Kato Tech. Co., Ltd, Japan) was used to assess the air permeability of the fabric samples by measuring their ventilation resistance. The dimensions of the test area were approximately 330 (w) × 495 (d) × 430 (h) mm. The ventilation resistance R (kPa·s/m) was recorded, with smaller values indicating higher breathability and permeability. Each sample group was tested four times, and the results were averaged to determine the fabric's overall air permeability. 3 Results and discussion 3.1 Heating efficiency Figure 3 presents the thermal images captured by a FLUKE Ti32 infrared camera with a rectangular selection within a specified area in thermal pixels, showing a temperature range from 25 to 70°C. The images were taken after 20 minutes of heating with a 10V power supply applied to the thermochromic heating fabrics. The average surface temperatures for the woven heating fabrics W-D1 and W-D2, which possess the same double cloth weaving structure, were 56.5°C and 54.95°C, respectively, both exhibiting uniform heat distribution in the thermal images (Fig. 3 b). In contrast, Fig. 3 c shows the thermal images for single jersey fabrics (K-S1 to K-S4) with a knitted structure, displaying several random hot spots along the conductive heating yarn. This unevenness is attributed to the inconsistent silver coating on the yarn during fabrication. When comparing the yarn materials used in the knitted structures, K-S1 and K-D1 show a relatively even heating distribution. This suggests that the soybean/cotton blended yarn provides a more stable heating distribution compared to wool. For woven heating fabrics, the tight interlacing of the structure minimizes such irregular spots, resulting in more even heat distribution. Compared to single jersey fabrics (K-S1 to K-S4), the double jersey fabrics (K-D1 to K-D3) shown in Fig. 3 d exhibited improved heat distribution along the rows, with more courses being heated due to the increased number of silver-coated conductive yarns. However, the looped knitted structure led to loose contact between the electrodes and the heating area, causing uneven heat extraction at the intersection of the electrodes and the heating regions, particularly in K-D2, leading to extremely high temperature at 93.4°C. The difference between the maximum temperature and the average surface temperature was significantly higher in the knitted samples compared to the woven samples. This is attributed to the presence of extremely high-temperature spots on the knitted samples. Overall, woven structures provide more stable and even heat distribution than knitted structures in the fabrication of electric heating fabrics. Figure 4 a presents the electric heating performance of the thermochromic heating fabrics. A thermometer (model: YET-610) equipped with thermocouples was used to measure the surface temperature of the fabric during the heating process. During the 60-minute test, both woven and double jersey fabrics reached a relatively high temperature of 60°C, while single jersey fabrics remained below 45°C. This suggests that the double structure accommodates a greater number of conductive heating yarns, which enhances the heating performance. The increase in conductive yarns, functioning as part of the equivalent circuit, leads to higher surface temperatures in the heating fabrics. While, the single jersey fabric’s heating stabilized more quickly, reaching a constant temperature after 30 minutes, compared to 40 minutes for the double structure fabric. Figure 4 b shows the relationship between electric resistance and current under a 12V power supply. Knitted samples K-S2, K-S3, and K-S4 exhibited relatively high resistance and low current, while the woven samples showed the highest current and lowest resistance. These findings suggest that higher resistance and lower current result in a lower average surface temperature, as seen in Fig. 4 a. Figure 4 c illustrates the current-voltage graph for the samples at power supplies of 5V, 7.5V, 10V, and 12V. In all samples, current gradually increased as voltage increased from 5V to 12V. Single jersey knits exhibited relatively low current, peaking around 1.25A, while double jersey structures rose by approximately to 1.7A, and woven structures saw an increase of roughly to 2A or above. At all tested voltages, woven samples (W-D1 and W-D2) provided the highest current among all fabric samples. Figure 4 d and Fig. 4 e show the power density corresponding to the average surface temperature and the average surface temperature with standard deviation, visualized through error bars. These measurements were obtained using IR imaging and analyzed with Fluke Connect data analysis software. In Fig. 4 d, the power consumption of the heating fabric was evaluated at applied voltages of 5V, 7.5V, 10V, and 12V, respectively. A linear curve was plotted for each fabric sample, demonstrating the correlation between power density and average surface temperature at 5V, 7.5V, 10V, and 12V. All curves displayed a positive slope, indicating that higher power density corresponds to a higher average surface temperature. Among the samples, W-D2 (woven structure) showed the steepest slope, followed by W-D1 and the double jersey sample K-D1, showing the highest power density and average surface temperature among the fabric samples. Single-jersey knitted samples exhibited similar surface heating temperatures to the double jersey samples (except for K-D1) but demonstrated the lowest power density. Figure 4 e illustrates the average surface temperature with standard deviation, visualized through error bars, measured and analyzed using IR images. At 5V and 7.5V, all samples maintained average surface temperatures of 30–35°C and 35–40°C, respectively, with minimal error. At 10V and 12V, woven fabric samples, particularly W-D2, reached the highest average surface temperatures of 63.81°C and 68.10°C, which were approximately 10°C higher than the other samples. This indicates that woven structures respond with relatively higher temperatures as voltage increases beyond 10V. When focusing on the knitted samples, K-D1 exhibited a relatively high temperature in the IR images (Fig. 4 e) compared to measurements taken by the thermometer at four specific points on the fabric (Fig. 4 a). This discrepancy could be due to the uniform distribution of the thermocouples, which may not account for the uneven heating distribution across the fabric, potentially introducing bias in the temperature recording. In Fig. 4 e, the IR images show large error bars for K-D2, and small error bars for K-S1 and K-D2 at 10V and 12V (similar to the double-woven structure), suggesting that using the soybean-cotton-blend yarn as the insulating yarn provides more even heating distribution and stability than wool. 3.2 Colorimetric effect Figure 5 shows the microscopic view of the electric heating samples with power supplies of 0V and 10V, respectively, to study the colour changes on the fabric surface with and without heating. Except for W-D1, where the thermochromic yarns changed from grey to white upon heating to 30°C, the thermochromic yarns in all other samples changed from purple to pink when heated above 30°C. In Fig. 5 a, the long floats of thermochromic yarns are woven on the technical face, resulting in a more noticeable colour change compared to the technical back. However, due to the structure of single-jersey knits, the long floats of thermochromic yarns appear on the technical back of the fabric (Fig. 5 b). To enhance the dual-sided functionality, where the technical face provides colour indication based on temperature changes and the technical back ensures comfort against the skin, double jersey fabrics were developed to conceal the thermochromic yarns from the fabric surface (Fig. 5 c). Figure 5 d and 5 e present the spectral reflectance curves for the technical face and back of the thermochromic heating fabric samples. The solid line represents fabric samples connected to 0V (with power), while the dotted line represents samples at 10V (without power). In Fig. 5 d, which shows the technical face, the solid and dotted lines are similar in shape for all samples except W-D1, W-D2, K-S1, and K-D1. Notably, W-D2, K-S1, and K-D1 exhibit a clear reflectance gap between 600 and 700nm (yellow, orange, and red wavelengths) due to the thermochromic yarns colour change from purple to pink on the fabric surface. Additionally, W-D1 shows a distinct reflectance gap between 400 and 650nm, indicating a shift in thermochromic yarns colour from grey to white in brighter tones. In contrast, Fig. 5 e shows that the reflectance gaps on the technical back side are much narrower, except for K-S1. These results indicate the potential of applying thermochromic yarns in woven and knitted structures for colour indication. The effectiveness of thermochromic yarn's colour change is influenced not only by the weaving or knitting structure but also by the insulating material. Soybean yarn (used in K-S1 and K-D1) exhibits a more noticeable colour change compared to the other knitted samples, potentially due to (1) differences in base colour—yellow in soybean yarn (K-S1 and K-D1) vs. blue or deep blue in wool (K-S2, K-S3, K-S4, K-D2, and K-D3)—or (2) material differences between soybean yarn and wool. Further evaluations are needed to ensure consistent material colour across samples for a more standardized comparison. 3.3 Thermal insulation and Thermal comfort In evaluating the physical properties under static condition without heating, since W-D1 and W-D2 share the same woven structure, only W-D2 was tested for the KES analysis. Table 4 summarizes the thermal conductivity, Q-max value, and insulation (warmth retention) ratio for one woven sample and seven knitted samples, including both single jersey and double jersey structures. The results showed that W-D2 exhibited extremely high thermal conductivity and Q-max values, but the lowest insulation ratio. Within the knitted samples, the single jersey structure demonstrated lower thermal conductivity and Q-max values when compared to the double jersey structure. Figure 6 a further illustrates the thermal conductivity and insulation values. K-S1, K-D2, and K-D3 exhibited the highest insulation values, while K-S4 had the lowest. The thermal conductivity of K-S4 and K-D3 was slightly higher than the other knitted samples, and their insulation values were correspondingly lower. These findings suggest that the warmth retention effect can be optimized by increasing the density and thickness of the fabric from single jersey to double jersey, which enhances the air-trapping ability. Additionally, soybean yarn showed higher insulation values in both single jersey and double jersey structures compared to wool. These results indicate that woven structures are superior for e-textile products that require quick heat response or efficient heat transfer, such as heated blankets, battery-powered jackets, or seat warmers where the fabric needs to heat up and cool down rapidly. Conversely, knitted fabrics are better suited for thermo-insulated garments like sweaters, socks, or base layers, where consistent warmth and comfort are critical. Table 4 Result in thermal conductivity, Q-max and keeping warmth ratio Fabric Sample Thermal Conductivity (k) (W/cm‧°C) Q-max value (W/cm 2 ) Keeping Warmth Ratio (α) (%) Average Heating Temperature under 10V (°C) W-D2 0.135 0.087 47 54.95 K-S1 0.009 0.032 71 49.77 K-S2 0.007 0.029 66 50.43 K-S3 0.009 0.032 60 42.32 K-S4 0.015 0.029 56 47.25 K-D1 0.021 0.035 71 59.69 K-D2 0.024 0.034 72 59.96 K-D3 0.039 0.037 64 52.67 Figure 6 b shows the tensile and shear properties of the fabric samples. The woven sample (W-D2) exhibits the highest values in both LT (1.93) and G (1.14 g/cm.deg), indicating the greatest tensile and shear rigidity among the fabric samples. In contrast, LT values for all knitted samples are relatively similar, all below 0.1. However, K-S4 and K-D3 have relatively high G values, at 0.64 g/cm.deg and 0.70 g/cm.deg, respectively, compared to other knitted samples, which range from 0.25 to 0.32 g/cm.deg. This suggests that knitted wool with 3-end knitting, in both single and double structures, provides satisfactory heat retention properties. Figure 6 c presents the compression results in terms of WC/W and WC/T for all fabric samples. K-D1 has the highest values, with WC/W at 0.067 and WC/T at 1.76, followed by K-S1 (0.043, 1.57) and K-S2 (0.050, 1.58). In contrast, W-D2 has the lowest values, with WC/W at 0.015 and WC/T at 0.59. Among the wool samples, the double jersey sample (K-D3) has a slightly higher WC/W value but a lower WC/T value than the single jersey samples (K-S3 and K-S4). These results suggest that the soybean yarn with a double jersey structure performs best in the compression test, indicating its potential for fabricating insulating fabrics, as higher compressibility implies better air trapping and enhanced thermal retention. Figure 6 d illustrates the thickness of the fabrics under compression (at 50 gf/cm²). W-D2 shows the lowest thickness (0.55), while K-S2 has the highest (1.51), highlighting that double jersey structures are generally softer than woven ones. Figure 6 e demonstrates the bending properties of the fabric samples. W-D2 exhibits the highest values for B/W (0.0067) and 2HB/W (0.0189), indicating the greatest stiffness, while K-S1 shows the lowest values for B/W (0.0004) and 2HB/W (0.0023). Additionally, single-knit fabric samples tend to have lower values than double jersey ones, showing that woven structures are stiffer and less drapable, while single jersey knits offer superior flexibility. Considering shape instability, K-S4 and K-D3 exhibit the highest values for 2HG/G (5.86 and 5.71) and the lowest for 2HB/B (2.2 and 1.86), meaning they are more prone to losing shape and wrinkling during bending but have better performance in shearing. In contrast, woven fabrics, such as W-D2, with balanced values for 2HG/G (3.18) and 2HB/B (2.82), demonstrate satisfactory dimensional stability. Figure 6 f displays the surface friction and air permeability characteristics of the fabric samples. Only the technical back side was tested, as the design of the thermochromic heating fabric features a face side for colour indication and a back side for contact with the skin to ensure thermal comfort. K-D1 shows the highest MMD/SMD ratio (0.0084), nearly double that of other samples, which range from 0.0027 to 0.0039. A lower ratio indicates a smoother surface, so K-D1 has a rougher surface, affecting tactile comfort. In terms of breathability, K-D3 has the highest value (0.186 kPa.s/m), while K-S1 and K-S2 have the lowest values (0.017 kPa.s/m and 0.008 kPa.s/m, respectively). Smaller values indicate better breathability and permeability, so K-S2 shows poor ventilation. Figure 6 Thermal insulation and thermal comfort characteristics of the thermochromic electric heating fabrics: (a) thermal conductivity and heat retention ratio, (b) tensile and shear properties, (c) compression energy, (d) loading properties, (e) bending properties, and (f) friction and air permeability of fabric samples. 3.4 Prototypes fabrication A collection of thermochromic heating cushions was developed using fabrics in both woven (W-D2) and knitted structures (K-D1, K-D2, and K-D3), as shown in Fig. 6 a and Fig. 6 b, respectively. The thermochromic yarns exhibited a distinct colour change from purple to pink when heated above 30°C, with the woven fabric demonstrating the most prominent visual transformation. The cushions were designed in a practical size of 30 × 50 cm—large enough for comfort but compact enough to suit the needs of elderly users for everyday use, such as hugging or holding. A conceptual temperature monitoring system with Bluetooth connectivity was proposed to enable remote control of the cushion’s heating function (Fig. 6 c). The system integrates a thermocouple as a temperature sensor, which continuously measures the fabric’s surface temperature in real time. The heating fabric and thermocouple were connected to a custom-designed printed circuit board (PCB) powered by a battery and an ESP32 microcontroller, which provides Bluetooth communication capabilities. Figure 6 d illustrates the operational flow: Users adjust the desired heating level via a mobile application connected through Bluetooth. The control signal is sent to the PCB, which regulates the power supplied to the thermochromic heating fabric by adjusting the output voltage. The thermocouple simultaneously monitors the actual surface temperature. Any detected changes are transmitted to the ESP32 microcontroller. The system uses Pulse Width Modulation (PWM)—a method for controlling the amount of electrical power delivered by rapidly switching the voltage on and off—to fine-tune the heating level based on the sensed temperature. This enables real-time feedback control, ensuring the fabric stays within a safe and comfortable temperature range for the user. This temperature controlled based smart heating textile allows caregivers to monitor and adjust the cushion’s heating level via Bluetooth, providing a safe and user-friendly interface tailored to elderly care settings. 4 Conclusion This study presents the design, fabrication, and evaluation of thermochromic electric heating textiles integrated into woven and knitted fabric structures for elderly care applications. Through a comparative analysis, the thermal, colorimetric, and mechanical properties of various fabric designs were systematically assessed. The results demonstrate that double-layer woven and knitted fabrics achieve more uniform heat distribution and improved heating efficiency, with double-layer woven structures exhibiting superior heating performance, greater tensile strength, and clearer thermochromic colour change. Among the insulating yarns tested, soybean–cotton blends provided more stable and uniform heating than wool-based alternatives. These findings support the tailored use of fabric structures in different applications: woven fabrics are more suitable for fast-response heating products such as blankets and seat warmers, while knitted structures are well-suited for thermo-insulated garments requiring flexibility and softness. The development of thermochromic cushions, coupled with a textile-based electronic control system for real-time monitoring, highlights the potential of smart textiles in enhancing user safety, comfort, and caregiver convenience in elderly care. Looking ahead, future research will explore the integration of voice recognition technology, supported by artificial intelligence (AI), to enable hands-free, user-friendly control of heating settings. This advancement aims to further enhance accessibility for elderly users by allowing intuitive and personalized temperature regulation through simple voice commands. Such user-centric innovations mark an important step toward the next generation of intelligent, responsive, and inclusive textile-based healthcare solutions. Declarations Acknowledgements The authors appreciate the valuable technical support and advice from Siu Wing Ng and Lee Cheng Hao at the School of Fashion and Textiles, The Hong Kong Polytechnic University, on the specimen weaving process and the operation of the spectrophotometer and spectrofluorometer. The authors would also like to thank Mr. Shingo Sawai of the Kyoto Design Lab, Kyoto Institute of Technology, for his help with the knitting process. Author contributions Conceptualization: Ching Lee, Jeanne Tan Investigation: Ching Lee, Jun Jong Tan Background research: Ching Lee, Ka Wing Tse Methodology: Ching Lee, Hiu Ting Tang, Annie Yu, Ngan Yi Kitty Lam Supervision: Jeanne Tan Writing – original draft: Jeanne Tan, Ching Lee Writing – review & editing: Jeanne Tan, Ching Lee, Hiu Ting Tang Funding This research is funded by the Laboratory for Artificial Intelligence in Design (Project Code: RP3-5) under InnoHK Research Clusters, Hong Kong Special Administrative Region. Data availability Data sets generated during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate Not applicable. Competing interests The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article. References Ma B, Zhou Y, Tan J, Li Y, Wang X, Liu C, et al. Artificial intelligence in elderly healthcare: A scoping review. Ageing Res Rev. 2023;83:101808. https://doi.org/10.1016/j.arr.2022.101808 SeyedAlinaghi S, Shokoohi M, Sahab-Negah S, Karami C, Tabatabaei A, Haghpanah S, et al. New technologies for elderly healthcare: A review of recent evidence. Public Health Environ. 2024;1(1):1–19. https://doi.org/10.70737/6t5s6w76 Fan W, He J, Cai J, Li Z, Yao K, Zhang Y, et al. Machine-knitted washable sensor array textile for precise epidermal physiological signal monitoring. Sci Adv. 2020;6(11):eaay2840. https://doi.org/10.1126/sciadv.aay2840 Yu A, Wang W, Li Z, Liu X, Zhang Y, Zhai J. Large-scale smart carpet for self-powered fall detection. Adv Mater Technol. 2020;5(2):1900978. https://doi.org/10.1002/admt.201900978 Wicaksono I, Tucker CI, Sun T, Shi Y, Pang C, Leber KN, et al. A tailored, electronic textile conformable suit for large-scale spatiotemporal physiological sensing in vivo. NPJ Flex Electron. 2020;4(1):1–13. https://doi.org/10.1038/s41528-020-0068-y Zhou Z, Deng Y, He Q, Yu J, Tan P, Lu B, et al. Single-layered ultra-soft washable smart textiles for all-around ballistocardiograph, respiration, and posture monitoring during sleep. Biosens Bioelectron. 2020;155:112064. https://doi.org/10.1016/j.bios.2020.112064 Fang Y, Wang J, Xu Z, Pan C, Wu H. Ambulatory cardiovascular monitoring via a machine-learning-assisted textile triboelectric sensor. Adv Mater. 2021;33(41):2104178. https://doi.org/10.1002/adma.202104178 Meng K, Zhao S, Zhou Y, Wu Y, Zhang S, He Q, et al. A wireless textile-based sensor system for self-powered personalized health care. Matter. 2020;2(4):896–907. https://doi.org/10.1016/j.matt.2020.02.001 Rahemtulla Z, Turner A, Oliveira C, Kaner J, Dias T, Hughes-Riley T. The design and engineering of a fall and near-fall detection electronic textile. Materials. 2023;16(5):1920. https://doi.org/10.3390/ma16051920 Zhou S, Ouyang L, Li B, Hodder S, Yao R. A thermoregulation model based on the physical and physiological characteristics of Chinese elderly. Comput Biol Med. 2024;172:108262. https://doi.org/10.1016/j.compbiomed.2024.108262 Lv T, Lu Y, Zhu G. Research and analysis of user needs for smart clothing for the elderly. Wearable Technol. 2021;2:101. https://doi.org/10.54517/wt.v2i2.1653 Millyard A, Layden JD, Pyne DB, Edwards AM, Bloxham SR. Impairments to thermoregulation in the elderly during heat exposure events. Gerontol Geriatr Med. 2020;6:2333721420932432. https://doi.org/10.1177/2333721420932432 Fitriani D, Pratiwi RD, Ayuningtyas G, Murtiningsih S, Poddar S. The differences in the effectiveness of providing thick blankets and electric blankets in reducing shivering incidence on postoperative patients in surgical installations Dr. Sitanala Hospital Tangerang, Indonesia in 2019. Malays J Med Res. 2021;5(4):28–35. https://doi.org/10.31674/mjmr.2021.v05i04.007 Liu S, Wu J. Development of user interaction (UI)-based electrically heated clothing incorporating knitted jacquard pattern for the elderly. J Ind Text. 2024;54:15280837241287938. https://doi.org/10.1177/15280837241287938 Ş Marius D, P Rareș, B Gabriella, D Liliana, F Lucian, R Georgiana Lavinia. Thermographic study on textile treatment equipment. Ann Univ Oradea Fac Text Leatherwork. 2024;25(2):87. Lee C, Tan J, Tan JJ, Tang HT, Yu WS, Lam NYK. Intelligent thermochromic heating e-textile for personalized temperature control in healthcare. ACS Appl Mater Interfaces. 2025; 17(3): 5515–5526. https://doi.org/10.1021/acsami.4c19174 Puspitosari A, Nurhidayah N. Sensory stimulation activities improving quality of life of elderly people in elderly communities. J Penelit Pendidik IPA. 2023;9(12):11038–44. https://doi.org/10.29303/jppipa.v9i12.5572 Alibakshi H, Eslami J, Shahrokhi S, Mirzabeigi H, Naimi E, Mirshoja MS. Effects of perceptual-motor exercises based on multi-sensory therapy on sensory processing of older adults. Iran J Ageing. 2024;19(3):410–23. http://dx.doi.org/10.32598/sija.2023.2789.6 Koo J, Hwang H. Effect of sensory stimulation type on brain activity in elderly persons with mild cognitive impairment. J Int Acad Phys Ther Res. 2019;10(1):1700–05. https://doi.org/10.20540/JIAPTR.2019.10.1.1700 Jurabayev N, Shogofurov S, Kholikov K, Meliboev U. Study of the fabric structure influence on the physical-mechanical and technological properties of knitted products. E3S Web Conf. 2021;304:03030. https://doi.org/10.1051/e3sconf/202130403030 Phoophat P, Soontrunnarudrungsri A, Chollakup R. Investigation of fabric tactile characteristics for different clothing based on elderly perspectives. Suranaree J Sci Technol. 2023; 30(4):030120(1–9). https://doi.org/10.55766/sujst-2023-04-e02413 Xue P, Tao X, Leung MY, Zhang H. Electromechanical properties of conductive fibres, yarns and fabrics. In: Wearable electronics and photonics. Amsterdam: Elsevier; 2005. p. 81–104. https://doi.org/10.1533/9781845690441.81 McBrearty D. Electronics calculations data handbook. Oxford: Elsevier; 1998. Lee C, Tan J, Tan JJ, Tang HT, Yu WS, Lam NYK. Integrating artificial intelligence for optimal thermal comfort: A design approach for electric heating textiles aligned with user preferences. Text Res J. 2025;95(5–6):513–30. https://doi.org/10.1177/00405175221148064 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 13 Jun, 2025 Reviews received at journal 26 May, 2025 Reviews received at journal 21 May, 2025 Reviewers agreed at journal 17 May, 2025 Reviews received at journal 15 May, 2025 Reviewers agreed at journal 14 May, 2025 Reviewers agreed at journal 14 May, 2025 Reviewers agreed at journal 12 May, 2025 Reviewers agreed at journal 12 May, 2025 Reviewers invited by journal 12 May, 2025 Editor assigned by journal 06 May, 2025 Submission checks completed at journal 06 May, 2025 First submitted to journal 03 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6366433","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":457240095,"identity":"3f63d335-8631-4977-872a-fa681a84c867","order_by":0,"name":"Ching Lee","email":"","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Ching","middleName":"","lastName":"Lee","suffix":""},{"id":457240096,"identity":"b01be2a6-a0c0-467e-b097-393a8f8e5787","order_by":1,"name":"Jeanne Tan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBACxgY4k/kAA0MBmGUAFE4gqEWCgYEtAaSYsBYYAGrhMSBOC3N787PHBRUMdfyze749+GBwOLGBvXmbBOOONNwO6zlmbjzjDIOExJ2z2w1ngLTwHCuTYDyTg1vLjAQzad42oMNu5G6T5gFpkcgxk2Bsq8CtZf7zb9K8/xgk5G/kPINokX9DQMsMHqAtDQwSBjdy2KC28IC04HFYT06ZNM8xCcmNN9LMgX5JN27jSSu2SGzD7X3D9uNAL9TY8MvdSH724EOFtWw/++GNNz62JePW0gCmJEAEGxA3g0mGBJwaGBjkkdggxXV41I6CUTAKRsFIBQAfvk7c3hUfnQAAAABJRU5ErkJggg==","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":true,"prefix":"","firstName":"Jeanne","middleName":"","lastName":"Tan","suffix":""},{"id":457240097,"identity":"b92be115-73b2-46be-ab16-2fe4a64bb603","order_by":2,"name":"Hiu Ting Tang","email":"","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Hiu","middleName":"Ting","lastName":"Tang","suffix":""},{"id":457240098,"identity":"b09cd091-1954-4861-8063-3544c0a57561","order_by":3,"name":"Annie Yu","email":"","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Annie","middleName":"","lastName":"Yu","suffix":""},{"id":457240099,"identity":"8765996f-ffd4-4599-a4f8-e33bba3b4ded","order_by":4,"name":"Jun Jong Tan","email":"","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"Jong","lastName":"Tan","suffix":""},{"id":457240100,"identity":"a6a5cc76-686b-4923-8c5a-834706b92c56","order_by":5,"name":"Ngan Yi Kitty Lam","email":"","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Ngan","middleName":"Yi Kitty","lastName":"Lam","suffix":""},{"id":457240101,"identity":"6f941dac-16eb-4c05-8eff-842379cc7e28","order_by":6,"name":"Ka Wing Tse","email":"","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Ka","middleName":"Wing","lastName":"Tse","suffix":""}],"badges":[],"createdAt":"2025-04-03 06:23:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6366433/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6366433/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82896244,"identity":"43f0868a-1f61-45e3-a244-28169c747ca7","added_by":"auto","created_at":"2025-05-16 12:54:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":199901,"visible":true,"origin":"","legend":"\u003cp\u003eDesign and development of a collection of thermochromic heating cushions using: (a) conductive yarns for heating and thermochromic yarns for temperature visualization; (b) fabrication into woven and knitted structures; (c) evaluation of heating performance and colour-changing effect in double-layer woven and knitted fabrics; (d) photos of four fabricated cushions; and (e) demonstration in elderly care applications.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6366433/v1/d63131b7a8fa889e823c5cfb.jpg"},{"id":82895057,"identity":"0fbc834f-b086-4321-b869-76452d51d7b4","added_by":"auto","created_at":"2025-05-16 12:38:50","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":378708,"visible":true,"origin":"","legend":"\u003cp\u003eFabrication of thermochromic electric heating fabrics: Illustration of electrical resistance heating and Ohm’s Law in (a) equivalent circuit diagram and (b) colour change in thermochromic yarns when heating below and above 30°C. (c) Weaving machine and (d) Double cloth weaving structure applied. (e) Knitting machine and, (f) knitting structure of (i) double jersey, (ii) cross-miss single jersey and (iii) single jersey applied in this study.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6366433/v1/3722a92ea9813b188ebae362.jpg"},{"id":82895460,"identity":"9a00c7f7-135f-43c3-8419-1073d9618332","added_by":"auto","created_at":"2025-05-16 12:46:51","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":265980,"visible":true,"origin":"","legend":"\u003cp\u003eInfrared (IR) tool and images of the thermochromic electric heating fabrics: (a) Thermal camera used for IR measurement. IR images of (b) woven heating fabrics (W-D1 and W-D2), (c) knitted heating fabrics structured in single jersey (K-S1 to K-S4), and (d) knitted heating fabrics structured in double jersey (K-D1 to K-D2).\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6366433/v1/0717248b57bcb44ef438c9b6.jpg"},{"id":82895467,"identity":"2549a86f-da6f-4d60-92a0-145032ba54ad","added_by":"auto","created_at":"2025-05-16 12:46:51","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":383555,"visible":true,"origin":"","legend":"\u003cp\u003eElectric heating performance of the thermochromic electric heating fabrics: (a) 60-minute heating test, (b) electric resistance and current under a 12V power supply, (c) current-voltage graph, (d) power density vs. average surface temperature curve, and (e) voltage vs. average surface temperature for all heating fabrics under 5V, 7.5V, 10V, and 12V power supplies, respectively.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6366433/v1/38503fafc1b122da65732e05.jpg"},{"id":82896245,"identity":"c7a570df-b1b6-4f19-a941-0088385dfd92","added_by":"auto","created_at":"2025-05-16 12:54:51","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":398869,"visible":true,"origin":"","legend":"\u003cp\u003eColorimetric properties of the thermochromic electric heating fabrics: Microscopic views at 2.0X magnification of the thermochromic heating fabric in (a) woven structure, (b) single jersey knit, and (c) double jersey structure. Spectral reflectance curves for the (d) technical face and (e) technical back sides of the thermochromic heating fabric samples.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6366433/v1/e5d665dc088a16a4a5514bc1.jpg"},{"id":82895061,"identity":"081e3729-d42d-49a5-888d-bd79df45aa3e","added_by":"auto","created_at":"2025-05-16 12:38:51","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":291066,"visible":true,"origin":"","legend":"\u003cp\u003eThermal insulation and thermal comfort characteristics of the thermochromic electric heating fabrics: (a) thermal conductivity and heat retention ratio, (b) tensile and shear properties, (c) compression energy, (d) loading properties, (e) bending properties, and (f) friction and air permeability of fabric samples.\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6366433/v1/22ede890cccb89414e48af43.jpg"},{"id":82895468,"identity":"8fe347f0-09eb-459e-92be-deed8c9f1edf","added_by":"auto","created_at":"2025-05-16 12:46:51","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":293692,"visible":true,"origin":"","legend":"\u003cp\u003eFabrication of a collection of thermochromic heating cushions: Photos of cushions with heating sections in (a) woven and (b) knitted structures; (c) conceptual diagram; and (d) block diagram of the textile-based electronic temperature control system.\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6366433/v1/040157d51b471bed253ea7ed.jpg"},{"id":82898414,"identity":"f3488588-e71f-4c6a-a56a-d8b87d102c20","added_by":"auto","created_at":"2025-05-16 13:10:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3482669,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6366433/v1/f2fd1b52-c3df-4c3b-82b4-fe99d64bc4cc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Smart Textile-integrated Thermochromic Display for Real-time Temperature Monitoring in Elderly Care","fulltext":[{"header":"Highlights","content":"\u003cul start=\"50\"\u003e\n \u003cli\u003eA collection of thermochromic heating cushions for elderly care are developed in woven and knitted structures.\u003c/li\u003e\n \u003cli\u003eDouble-layer woven fabric shows the highest heating efficiency and colour change effect.\u003c/li\u003e\n \u003cli\u003eA textile-based control system enables real-time temperature monitoring for elderly care.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1 Introduction","content":"\u003cp\u003eThe rapid advancement of smart textile technologies has opened new possibilities for healthcare monitoring, particularly in elderly care applications. Recent studies underscore the potential of smart textiles integrated with biosensors, which can monitor physiological parameters such as heart rate, body temperature, and pressure distribution, thereby enhancing elderly individuals' comfort, safety, and overall well-being[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These innovations have led to the development of textiles designed for fall detection, cardiovascular monitoring, and thermoregulation, offering valuable real-time health insights while ensuring wearer comfort[\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7 CR8\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Despite these advancements, a significant demand still exists for textiles that provide warmth while also incorporating real-time temperature monitoring, especially for elderly individuals with reduced thermoregulatory efficiency[\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In elderly care, advanced textile technologies play a crucial role in providing thermal comfort. Heating textiles have been widely employed in products such as electric blankets, heating pads, and smart garments, helping elderly users maintain an optimal body temperature and prevent cold stress[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. While these products are effective in delivering localized warmth, they pose significant overheating risks, particularly when continuous monitoring is unavailable[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In settings where caregivers are responsible for regulating the heating level, insufficient feedback on surface temperature changes and the elderly individual's skin condition can lead to undesirable thermal stress, discomfort, or potential burns[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, integrating intelligent monitoring systems into heating textiles is essential for promoting safe and efficient usage in elderly care settings.\u003c/p\u003e \u003cp\u003eA promising approach to addressing this challenge is the incorporation of thermochromic textiles, which serve as visual indicators of temperature changes through colour variation. Unlike small display screens that may be difficult for elderly individuals to read, thermochromic textiles utilize a large, fabric-based visualization method, making temperature fluctuations easier to detect by both users and caregivers. A recent study demonstrated strong potential for thermochromic yarns as visual indicators in smart heating textiles, allowing real-time, intuitive, and non-intrusive thermal feedback[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, despite these advantages, there remains a gap in understanding how fabric structure influences thermochromic performance and user comfort, particularly in elderly care applications.\u003c/p\u003e \u003cp\u003eGiven the importance of sensory perception in elderly textile applications, selecting the appropriate fabric structure is essential for ensuring user acceptance. Elderly users may have different preferences regarding surface texture and hand feel, which can significantly influence their comfort and willingness to adopt new technologies[\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Woven and knitted textiles, the two most commonly used textile structures, offer distinct mechanical and tactile properties. Woven fabrics, with their tightly interlaced threads, provide high durability, dimensional stability, and uniform heat distribution, making them suitable for consistent thermal performance. In contrast, knitted fabrics are characterized by softness, flexibility, and stretchability, offering a comfortable and adaptive texture, which is often preferred in contact textiles for elderly users, including those with sensory sensitivities[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, thermochromic heating textiles were fabricated in both woven and knitted structures, incorporating thermochromic yarns, silver-coated conductive heating yarns, and insulating yarns, including cotton, soybean and wool, in various combinations to optimize heating efficiency, mechanical properties, and colour-changing effects. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb illustrate the yarns used and the corresponding woven and knitted fabric structures, respectively. Experimental characterization revealed that double-layer structures outperformed single-layer fabrics in heat distribution and heating efficiency, with double-layer woven fabrics exhibiting the most pronounced thermochromic colour change upon heating. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec demonstrates the heating performance and colour changes as power is supplied from 0 V (no heating) to 10 V (heating) for the double-layer knitted and woven samples, K-D2 and W-D2, respectively. Based on these findings, a collection of four thermochromic heating cushions was developed specifically for elderly care applications, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, allowing users to choose fabrics based on their preferred texture and thermal performance. Additionally, a fully textile-based electronic control system was proposed to enable caregivers to remotely monitor elderly users' skin temperature in real time and regulate the heating function accordingly. This research contributes to the advancement of thermochromic smart textiles by demonstrating their practical applications in elderly care and their potential for providing safer, more intuitive, and caregiver-friendly thermal regulation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2 Experimental details","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Electrical resistance heating theory\u003c/h2\u003e\n \u003cp\u003eThe heating mechanism in e-textiles follows the Joule heating effect, as described by Ohm\u0026rsquo;s Law[\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. When an electric current flows through a resistance\u0026mdash;such as metallic yarns serving as bus bars and low-resistance silver- or copper-coated polymeric yarns acting as heating elements\u0026mdash;heat is generated, resulting in a warming effect. Ohm\u0026apos;s law could be calculated as:\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP\u0026thinsp;=\u0026thinsp;VI\u0026thinsp;=\u0026thinsp;\u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere P is the power consumption (watt), V is the voltage applied (volt), I is current (A) and R is the resistance (ohm).\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea highlights the equivalent circuit diagram of the heating fabric in both woven and knitted structures, where variables R1, R2, \u0026hellip;, Rn represent the resistances of parallel conductive yarn strips. Additionally, variables r1, r2, \u0026hellip;, rn and r\u0026rsquo;1, r\u0026rsquo;2, \u0026hellip;, r\u0026rsquo;n denote pairs of contact resistances (electrodes) at left and right crossing points, respectively. Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb illustrates the electrical resistance heating process, in which connecting a power supply to the thermochromic electric heating fabric induces a colour change from pink to purple on the surface when the temperature exceeds 30\u0026deg;C. The power generated is directly proportional to the square of the current (I) and the resistance (R). In such systems, the amount of heat generated depends on the magnitude of the current, which in turn is governed by the resistance (R) and the applied voltage (V). This principle forms the fundamental operating mechanism of electric heating textiles, which typically regulate heating intensity using either direct current (DC) voltage regulation or pulse duty ratio regulation methods.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Fabric weaving and structure characteristics\u003c/h2\u003e\n \u003cp\u003eThe thermochromic heating fabric in a woven structure developed for this study was based on previous study increasing the number of conductive heating yarns enhances heating efficiency[\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. The double cloth structure with a diamond pattern was chosen for its symmetry along both the vertical and horizontal axes, ensuring uniform heat distribution across each small repeat section of the fabric. The fabrication process involved weaving silver-coated heating yarn (40D, 17% silver, 83% nylon) and thermochromic yarn (150D/2) in the weft direction, while insulating passive cotton yarn (40/2s, 100% cotton) was used in the warp direction. Embroidery was applied after the weaving process to shorten the preparation time needed to replace the warp yarn with conductive yarn as a pair of electrodes. Therefore, after weaving, silver-coated yarn (200D, 18% silver, 82% nylon) was embroidered onto the fabric as electrodes, in accordance with Ohm\u0026rsquo;s Law. The weaving process was carried out using a rapier sample loom (CCI/SL7900) with dobby shedding motion at a speed of 25 rpm (as shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec), and the embroidery of the electrodes was done using a TAJIMA-SAI embroidery machine. Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed illustrates the woven structure of the e-textile, which was fabricated using a double-sided diamond twill pattern. Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the characteristics of the thermochromic heating fabric specimens. The fabric thickness was measured using a digital thickness gauge. Microscopic views were taken by stereo microscope (model Leica M165 C). W-D1 utilizes thermochromic yarns that changes colour from grey to white, whereas W-D2 applies thermochromic yarns that changes colour from pink to purple when the fabric is heated to 30\u0026deg;C. Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e lists the specifications of the silver-coated conductive yarn. Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e provides the specifications of the conventional yarns used in the fabric specimens.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Fabric knitting and structure characteristics\u003c/h2\u003e\n \u003cp\u003eSeven knitted samples of thermochromic heating fabric were fabricated. To align with the double-woven cloth, the knitted fabrics were fabricated in a double jersey structure. The fabric structure consists of two electrodes positioned along the left and right edges with a main heating area in the middle. Intarsia knitting was applied to organize the heating and electrode sections. The electrodes were knitted in a double jersey using one end of silver-coated heating yarn (800D, 17% silver, 83% nylon) with a lower resistance of 0.75Ω/cm. One end of silver-coated heating yarn (70D, 17% silver, 83% nylon) with a higher resistance of 10.7Ω/cm, along with one end of 150D/2 thermochromic yarn, were used to knit front stitches simultaneously in both the heating area and electrodes, forming the heating rows. Between each heating row, an interval of eight knitting rows was inserted in the heating section using textile-based yarn. Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef illustrates the knitted structure of the e-textiles. K-S1 to K-S4 were knitted with single jersey for the intervals, while K-D1 to K-D3 used double jersey. Four ends of soybean yarn (40/2s, 50% cotton, 50% soybean) were used for the interval sections in K-S1 and K-D1. For K-S2 to K-S4 and K-D2 to K-D3, the textile-based yarn used for the intervals was wool yarn (Nm 48/2, 100% extrafine merino wool), with two ends for K-S2, K-S3, and K-D2, and three ends for K-S4 and K-D3. The knitting process was performed on a computerized flat-knitting machine (Shima Seiki SWG091N2) with a gauge of 7 at a speed of 0.5 (m/s), as shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ee. The knitting programs were prepared using the incorporated computer-aided design system (SDS-ONE APEX).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Characteristics of the fabric specimens\u003c/div\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/69519_bce2c0439cd956a6/69519_custom_files/img1747398589.png\"\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003e*Yarn density was measured on conditioned samples by using a magnifying glass to count the number of yarns in each wale and course. EPI (Ends Per Inch) refers to the yarns in the machine direction, while PPI (Picks Per Inch) represents those in the cross-direction.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSilver-coated conductive yarn specification\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYarn\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFabrication\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEmbedded Area\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYarn Resistance (Ω/cm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYarn Count\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEnd (s)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYarn Content\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeaving\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMain body\u003c/p\u003e\n \u003cp\u003e(Heating)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17% Silver,\u003c/p\u003e\n \u003cp\u003e83% Nylon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmbroidery\u003c/p\u003e\n \u003cp\u003e(on woven fabric)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElectrode\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18% Silver,\u003c/p\u003e\n \u003cp\u003e82% Nylon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKnitting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMain body\u003c/p\u003e\n \u003cp\u003e(Heating)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17% Silver,\u003c/p\u003e\n \u003cp\u003e83% Nylon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKnitting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElectrode\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e800D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17% Silver,\u003c/p\u003e\n \u003cp\u003e83% Nylon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eConventional yarn specification of the fabric specimens\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYarn\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFabric Sample\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYarn Count\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEnd(s)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYarn Content\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCotton\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eW-D1\u003c/p\u003e\n \u003cp\u003eW-D2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40/2s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100% Cotton\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoybean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK-S1\u003c/p\u003e\n \u003cp\u003eK-D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32s/1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50% Cotton\u003c/p\u003e\n \u003cp\u003e50% Soybean\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWool\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK-S2\u003c/p\u003e\n \u003cp\u003eK-D2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNM 1/34000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100% Merino wool\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWool\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK-S3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48/2 Nm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100% Merino wool\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWool\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK-S4\u003c/p\u003e\n \u003cp\u003eK-D3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48/2 Nm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100% Merino wool\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Testing Methods\u003c/h2\u003e\n \u003cp\u003e\u003cem\u003eHeating efficiency.\u003c/em\u003e The average surface temperature of the thermochromic electric heating fabrics was monitored using a FLUKE Ti32 infrared camera (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea) and a DC power supply (GPS3010D-30V/10A). Temperature readings were recorded at varying voltages and times, then analyzed through the Fluke Connect data analysis software. A multimeter was used to measure the fabric\u0026apos;s resistance under different power inputs (5V, 7.5V, 10V, and 12V) to evaluate heating efficiency. Additionally, A thermometer (model: YET-610) equipped with thermocouples was attached at four evenly spaced points on the fabric surface to measure the surface temperature during the heating process.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eColour measurement.\u003c/em\u003e A Datacolor 600\u0026trade; Colour-Eye Spectrophotometer was used to analyze the reflectance of the thermochromic electric heating fabrics at 0V and 10V power supplies, in order to study the colour change of the thermochromic yarns. Fabric samples were arranged in parallel and compressed in a container with optical glass until opaque to ensure accurate and consistent colour measurements. 3-dimensional spectral reflectance data were recorded across the 400\u0026ndash;700 nm range in 10 nm intervals, including the specular reflection component. To minimize errors, the largest aperture (30 mm) was selected, and measurements were taken randomly at four different positions and orientations on the sample surface. The average of these measurements was used as the true colour data. Optical glass correction was applied to eliminate any influence from the glass during the measurement process.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTesting for thermal conductivity, Q-max and thermal insulation.\u003c/em\u003e The thermal conductivity, Q-max (a measurement of warm/cool feeling) and thermal insulation of the samples were assessed using the KES-F7 Thermo Labo II thermal property measurement instrument (Kato Tech. Co., Ltd, Japan). Prior to testing, all thermochromic electric heating fabrics were conditioned for 24 hours under standard conditions of 21.1\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and 65% \u0026plusmn; 5% relative humidity (RH). The samples were placed between the Water box (cold plate \u0026ndash; constant temperature box) and BT-box (hot plate; area: 5 \u0026times; 5 cm\u0026sup2;; weight: 150 g), maintained at temperatures of 30\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u0026deg;C and 20\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u0026deg;C, respectively. The heat flow loss W (watts) from the BT-box was recorded once a constant value was achieved. Q-max is a measurement to evaluate the instantaneous heat transfer between a fabric and the skin, indicating the warmth or coolness a material feels upon first contact. It quantifies the maximum heat flux that occurs when two surfaces at different temperatures come into contact. It can be calculated using Fourier\u0026rsquo;s Law. A higher Q-max value indicates that the fabric feels cooler to the touch because it transfers heat away from the skin more quickly, while a lower Q-max value suggests the fabric retains heat, making it feel warmer. For thermal insulation, a dry contact method was applied. Data are corrected to the value per 1\u0026deg;C and 1m\u003csup\u003e2\u003c/sup\u003e (The area of BT-plate is 100cm\u003csup\u003e2\u003c/sup\u003e). The thermal conductivity (k), Q-max value, and keeping warmth ratio (%) could be determined using the following equations:\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tabb\" border=\"1\"\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{k}=\\frac{W‧D}{A‧\\varDelta\\:T}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e(2)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Q}_{max}=-\\text{k}‧A‧\\frac{\\varDelta\\:T}{\\varDelta\\:D}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\alpha\\:}=\\frac{\\left({W}_{0}-W\\right)}{{W}_{0}}\\times\\:100\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere k is the thermal conductivity, Q_maxis the maximum heat flux (W/m\u003csup\u003e2\u003c/sup\u003e), W (watt) is the heat flow loss, D is the thickness of the fabric, A is the fabric area and \u0026Delta;T is the temperature difference of two sides of sample, W0 is the heat loss without sample and W is the heat loss with sample.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTensile and Shear test.\u003c/em\u003e The tensile and shear properties were measured using the KES-FB1 Tensile and Shear Tester within a measurement area of 610 \u0026times; 535 \u0026times; 320 mm, simulating mechanical stretching and in-plane displacement to evaluate fabric performance. Before tensile, shear, compression, bending, friction, and air permeability tests, all fabric samples were cut to a standard size of 20 \u0026times; 20 cm and conditioned for 24 hours under 21.1\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and 65% \u0026plusmn; 5% RH. During tensile testing, the fabric is clamped and stretched to determine tensile rigidity (LT), with values closer to 1 indicating greater firmness. For shear testing, horizontal forces simulate in-plane deformation, measuring shear rigidity (G), where higher values signal increased resistance to shearing, and elasticity for minute shear (2HG), where higher values denote poorer recoverability from initial shear deformation.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCompression test.\u003c/em\u003e The KES-FB3-A Compression Tester (Kato Tech. Co., Ltd, Japan) was applied to measure the compression properties of fabric samples. Using a two-plate system, with one fixed and one movable plate applying a controlled vertical force, the tester evaluates how fabrics respond to compression and their ability to recover. Key metrics include compressional energy (WC), expressed in Load (gf/cm\u0026sup2;), where higher values indicate greater susceptibility to compression. The ratio WC/W reflects the relationship between compressional energy and weight per unit area, with higher values indicating that the textile fibers compress more, resulting in a softer feel. Similarly, WC/T represents the ratio of compressional energy to thickness, where larger values indicate more compression and enhanced softness. By recording changes in fabric thickness during the compression and recovery process, the device offers insights into the material\u0026apos;s cushioning, softness, and structural resilience.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eBending test.\u003c/em\u003e KES-FB2 Pure Bending Tester was applied in measuring the bending properties of fabrics, assessing the stiffness, flexibility, and drapability by applying pure bending forces without shear or tension. Key measurements include bending rigidity (B) and hysteresis (2HB), which reflect stiffness and recovery after bending. The B/W ratio indicates the relationship between a fabric\u0026apos;s stiffness and weight, with higher values leading to a stiffer appearance and poor drape. The 2HB/W ratio correlates with shape instability, where a higher value means less lively movement, and 2HB/B and 2HG/G represent the balance between elastic and hysteresis components in bending and shear deformation, respectively.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eFriction test.\u003c/em\u003e Frictional properties and surface roughness (SR) of fabrics was measured by KES-FB4-A Friction Tester which provides key insights into surface texture and tactile feel. It evaluates the coefficient of friction (MMD) and surface roughness (SMD) by passing a sensor over the fabric\u0026apos;s surface under controlled pressure. The SR can be expressed as MMD/SMD, where the ratio of MMD (fluctuation in friction) to SMD (surface roughness) reflects the relationship between surface friction and texture. A smaller ratio indicates a smoother surface, which directly correlates to how soft or smooth the fabric feels to the touch.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eAir permeability test.\u003c/em\u003e The KES-F8 Air Permeability Tester (Kato Tech. Co., Ltd, Japan) was used to assess the air permeability of the fabric samples by measuring their ventilation resistance. The dimensions of the test area were approximately 330 (w) \u0026times; 495 (d) \u0026times; 430 (h) mm. The ventilation resistance R (kPa\u0026middot;s/m) was recorded, with smaller values indicating higher breathability and permeability. Each sample group was tested four times, and the results were averaged to determine the fabric\u0026apos;s overall air permeability.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Results and discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Heating efficiency\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the thermal images captured by a FLUKE Ti32 infrared camera with a rectangular selection within a specified area in thermal pixels, showing a temperature range from 25 to 70\u0026deg;C. The images were taken after 20 minutes of heating with a 10V power supply applied to the thermochromic heating fabrics. The average surface temperatures for the woven heating fabrics W-D1 and W-D2, which possess the same double cloth weaving structure, were 56.5\u0026deg;C and 54.95\u0026deg;C, respectively, both exhibiting uniform heat distribution in the thermal images (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). In contrast, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec shows the thermal images for single jersey fabrics (K-S1 to K-S4) with a knitted structure, displaying several random hot spots along the conductive heating yarn. This unevenness is attributed to the inconsistent silver coating on the yarn during fabrication. When comparing the yarn materials used in the knitted structures, K-S1 and K-D1 show a relatively even heating distribution. This suggests that the soybean/cotton blended yarn provides a more stable heating distribution compared to wool. For woven heating fabrics, the tight interlacing of the structure minimizes such irregular spots, resulting in more even heat distribution. Compared to single jersey fabrics (K-S1 to K-S4), the double jersey fabrics (K-D1 to K-D3) shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed exhibited improved heat distribution along the rows, with more courses being heated due to the increased number of silver-coated conductive yarns. However, the looped knitted structure led to loose contact between the electrodes and the heating area, causing uneven heat extraction at the intersection of the electrodes and the heating regions, particularly in K-D2, leading to extremely high temperature at 93.4\u0026deg;C. The difference between the maximum temperature and the average surface temperature was significantly higher in the knitted samples compared to the woven samples. This is attributed to the presence of extremely high-temperature spots on the knitted samples. Overall, woven structures provide more stable and even heat distribution than knitted structures in the fabrication of electric heating fabrics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea presents the electric heating performance of the thermochromic heating fabrics. A thermometer (model: YET-610) equipped with thermocouples was used to measure the surface temperature of the fabric during the heating process. During the 60-minute test, both woven and double jersey fabrics reached a relatively high temperature of 60\u0026deg;C, while single jersey fabrics remained below 45\u0026deg;C. This suggests that the double structure accommodates a greater number of conductive heating yarns, which enhances the heating performance. The increase in conductive yarns, functioning as part of the equivalent circuit, leads to higher surface temperatures in the heating fabrics. While, the single jersey fabric\u0026rsquo;s heating stabilized more quickly, reaching a constant temperature after 30 minutes, compared to 40 minutes for the double structure fabric. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb shows the relationship between electric resistance and current under a 12V power supply. Knitted samples K-S2, K-S3, and K-S4 exhibited relatively high resistance and low current, while the woven samples showed the highest current and lowest resistance. These findings suggest that higher resistance and lower current result in a lower average surface temperature, as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec illustrates the current-voltage graph for the samples at power supplies of 5V, 7.5V, 10V, and 12V. In all samples, current gradually increased as voltage increased from 5V to 12V. Single jersey knits exhibited relatively low current, peaking around 1.25A, while double jersey structures rose by approximately to 1.7A, and woven structures saw an increase of roughly to 2A or above. At all tested voltages, woven samples (W-D1 and W-D2) provided the highest current among all fabric samples.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee show the power density corresponding to the average surface temperature and the average surface temperature with standard deviation, visualized through error bars. These measurements were obtained using IR imaging and analyzed with Fluke Connect data analysis software. In Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, the power consumption of the heating fabric was evaluated at applied voltages of 5V, 7.5V, 10V, and 12V, respectively. A linear curve was plotted for each fabric sample, demonstrating the correlation between power density and average surface temperature at 5V, 7.5V, 10V, and 12V. All curves displayed a positive slope, indicating that higher power density corresponds to a higher average surface temperature. Among the samples, W-D2 (woven structure) showed the steepest slope, followed by W-D1 and the double jersey sample K-D1, showing the highest power density and average surface temperature among the fabric samples. Single-jersey knitted samples exhibited similar surface heating temperatures to the double jersey samples (except for K-D1) but demonstrated the lowest power density. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee illustrates the average surface temperature with standard deviation, visualized through error bars, measured and analyzed using IR images. At 5V and 7.5V, all samples maintained average surface temperatures of 30\u0026ndash;35\u0026deg;C and 35\u0026ndash;40\u0026deg;C, respectively, with minimal error. At 10V and 12V, woven fabric samples, particularly W-D2, reached the highest average surface temperatures of 63.81\u0026deg;C and 68.10\u0026deg;C, which were approximately 10\u0026deg;C higher than the other samples. This indicates that woven structures respond with relatively higher temperatures as voltage increases beyond 10V. When focusing on the knitted samples, K-D1 exhibited a relatively high temperature in the IR images (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee) compared to measurements taken by the thermometer at four specific points on the fabric (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). This discrepancy could be due to the uniform distribution of the thermocouples, which may not account for the uneven heating distribution across the fabric, potentially introducing bias in the temperature recording. In Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee, the IR images show large error bars for K-D2, and small error bars for K-S1 and K-D2 at 10V and 12V (similar to the double-woven structure), suggesting that using the soybean-cotton-blend yarn as the insulating yarn provides more even heating distribution and stability than wool.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Colorimetric effect\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the microscopic view of the electric heating samples with power supplies of 0V and 10V, respectively, to study the colour changes on the fabric surface with and without heating. Except for W-D1, where the thermochromic yarns changed from grey to white upon heating to 30\u0026deg;C, the thermochromic yarns in all other samples changed from purple to pink when heated above 30\u0026deg;C. In Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, the long floats of thermochromic yarns are woven on the technical face, resulting in a more noticeable colour change compared to the technical back. However, due to the structure of single-jersey knits, the long floats of thermochromic yarns appear on the technical back of the fabric (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). To enhance the dual-sided functionality, where the technical face provides colour indication based on temperature changes and the technical back ensures comfort against the skin, double jersey fabrics were developed to conceal the thermochromic yarns from the fabric surface (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee present the spectral reflectance curves for the technical face and back of the thermochromic heating fabric samples. The solid line represents fabric samples connected to 0V (with power), while the dotted line represents samples at 10V (without power). In Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed, which shows the technical face, the solid and dotted lines are similar in shape for all samples except W-D1, W-D2, K-S1, and K-D1. Notably, W-D2, K-S1, and K-D1 exhibit a clear reflectance gap between 600 and 700nm (yellow, orange, and red wavelengths) due to the thermochromic yarns colour change from purple to pink on the fabric surface. Additionally, W-D1 shows a distinct reflectance gap between 400 and 650nm, indicating a shift in thermochromic yarns colour from grey to white in brighter tones. In contrast, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee shows that the reflectance gaps on the technical back side are much narrower, except for K-S1. These results indicate the potential of applying thermochromic yarns in woven and knitted structures for colour indication. The effectiveness of thermochromic yarn's colour change is influenced not only by the weaving or knitting structure but also by the insulating material. Soybean yarn (used in K-S1 and K-D1) exhibits a more noticeable colour change compared to the other knitted samples, potentially due to (1) differences in base colour\u0026mdash;yellow in soybean yarn (K-S1 and K-D1) vs. blue or deep blue in wool (K-S2, K-S3, K-S4, K-D2, and K-D3)\u0026mdash;or (2) material differences between soybean yarn and wool. Further evaluations are needed to ensure consistent material colour across samples for a more standardized comparison.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Thermal insulation and Thermal comfort\u003c/h2\u003e \u003cp\u003eIn evaluating the physical properties under static condition without heating, since W-D1 and W-D2 share the same woven structure, only W-D2 was tested for the KES analysis. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the thermal conductivity, Q-max value, and insulation (warmth retention) ratio for one woven sample and seven knitted samples, including both single jersey and double jersey structures. The results showed that W-D2 exhibited extremely high thermal conductivity and Q-max values, but the lowest insulation ratio. Within the knitted samples, the single jersey structure demonstrated lower thermal conductivity and Q-max values when compared to the double jersey structure. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea further illustrates the thermal conductivity and insulation values. K-S1, K-D2, and K-D3 exhibited the highest insulation values, while K-S4 had the lowest. The thermal conductivity of K-S4 and K-D3 was slightly higher than the other knitted samples, and their insulation values were correspondingly lower. These findings suggest that the warmth retention effect can be optimized by increasing the density and thickness of the fabric from single jersey to double jersey, which enhances the air-trapping ability. Additionally, soybean yarn showed higher insulation values in both single jersey and double jersey structures compared to wool. These results indicate that woven structures are superior for e-textile products that require quick heat response or efficient heat transfer, such as heated blankets, battery-powered jackets, or seat warmers where the fabric needs to heat up and cool down rapidly. Conversely, knitted fabrics are better suited for thermo-insulated garments like sweaters, socks, or base layers, where consistent warmth and comfort are critical.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResult in thermal conductivity, Q-max and keeping warmth ratio\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFabric Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThermal Conductivity (k)\u003c/p\u003e \u003cp\u003e(W/cm‧\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ-max value\u003c/p\u003e \u003cp\u003e(W/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKeeping Warmth Ratio (α)\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAverage Heating Temperature under 10V\u003c/p\u003e \u003cp\u003e(\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW-D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK-S1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK-S2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK-S3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK-S4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK-D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK-D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK-D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb shows the tensile and shear properties of the fabric samples. The woven sample (W-D2) exhibits the highest values in both LT (1.93) and G (1.14 g/cm.deg), indicating the greatest tensile and shear rigidity among the fabric samples. In contrast, LT values for all knitted samples are relatively similar, all below 0.1. However, K-S4 and K-D3 have relatively high G values, at 0.64 g/cm.deg and 0.70 g/cm.deg, respectively, compared to other knitted samples, which range from 0.25 to 0.32 g/cm.deg. This suggests that knitted wool with 3-end knitting, in both single and double structures, provides satisfactory heat retention properties. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec presents the compression results in terms of WC/W and WC/T for all fabric samples. K-D1 has the highest values, with WC/W at 0.067 and WC/T at 1.76, followed by K-S1 (0.043, 1.57) and K-S2 (0.050, 1.58). In contrast, W-D2 has the lowest values, with WC/W at 0.015 and WC/T at 0.59. Among the wool samples, the double jersey sample (K-D3) has a slightly higher WC/W value but a lower WC/T value than the single jersey samples (K-S3 and K-S4). These results suggest that the soybean yarn with a double jersey structure performs best in the compression test, indicating its potential for fabricating insulating fabrics, as higher compressibility implies better air trapping and enhanced thermal retention. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed illustrates the thickness of the fabrics under compression (at 50 gf/cm\u0026sup2;). W-D2 shows the lowest thickness (0.55), while K-S2 has the highest (1.51), highlighting that double jersey structures are generally softer than woven ones. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee demonstrates the bending properties of the fabric samples. W-D2 exhibits the highest values for B/W (0.0067) and 2HB/W (0.0189), indicating the greatest stiffness, while K-S1 shows the lowest values for B/W (0.0004) and 2HB/W (0.0023). Additionally, single-knit fabric samples tend to have lower values than double jersey ones, showing that woven structures are stiffer and less drapable, while single jersey knits offer superior flexibility. Considering shape instability, K-S4 and K-D3 exhibit the highest values for 2HG/G (5.86 and 5.71) and the lowest for 2HB/B (2.2 and 1.86), meaning they are more prone to losing shape and wrinkling during bending but have better performance in shearing. In contrast, woven fabrics, such as W-D2, with balanced values for 2HG/G (3.18) and 2HB/B (2.82), demonstrate satisfactory dimensional stability. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ef displays the surface friction and air permeability characteristics of the fabric samples. Only the technical back side was tested, as the design of the thermochromic heating fabric features a face side for colour indication and a back side for contact with the skin to ensure thermal comfort. K-D1 shows the highest MMD/SMD ratio (0.0084), nearly double that of other samples, which range from 0.0027 to 0.0039. A lower ratio indicates a smoother surface, so K-D1 has a rougher surface, affecting tactile comfort. In terms of breathability, K-D3 has the highest value (0.186 kPa.s/m), while K-S1 and K-S2 have the lowest values (0.017 kPa.s/m and 0.008 kPa.s/m, respectively). Smaller values indicate better breathability and permeability, so K-S2 shows poor ventilation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e Thermal insulation and thermal comfort characteristics of the thermochromic electric heating fabrics: (a) thermal conductivity and heat retention ratio, (b) tensile and shear properties, (c) compression energy, (d) loading properties, (e) bending properties, and (f) friction and air permeability of fabric samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Prototypes fabrication\u003c/h2\u003e \u003cp\u003eA collection of thermochromic heating cushions was developed using fabrics in both woven (W-D2) and knitted structures (K-D1, K-D2, and K-D3), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb, respectively. The thermochromic yarns exhibited a distinct colour change from purple to pink when heated above 30\u0026deg;C, with the woven fabric demonstrating the most prominent visual transformation. The cushions were designed in a practical size of 30 \u0026times; 50 cm\u0026mdash;large enough for comfort but compact enough to suit the needs of elderly users for everyday use, such as hugging or holding.\u003c/p\u003e \u003cp\u003eA conceptual temperature monitoring system with Bluetooth connectivity was proposed to enable remote control of the cushion\u0026rsquo;s heating function (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). The system integrates a thermocouple as a temperature sensor, which continuously measures the fabric\u0026rsquo;s surface temperature in real time. The heating fabric and thermocouple were connected to a custom-designed printed circuit board (PCB) powered by a battery and an ESP32 microcontroller, which provides Bluetooth communication capabilities. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed illustrates the operational flow: Users adjust the desired heating level via a mobile application connected through Bluetooth. The control signal is sent to the PCB, which regulates the power supplied to the thermochromic heating fabric by adjusting the output voltage. The thermocouple simultaneously monitors the actual surface temperature. Any detected changes are transmitted to the ESP32 microcontroller. The system uses Pulse Width Modulation (PWM)\u0026mdash;a method for controlling the amount of electrical power delivered by rapidly switching the voltage on and off\u0026mdash;to fine-tune the heating level based on the sensed temperature. This enables real-time feedback control, ensuring the fabric stays within a safe and comfortable temperature range for the user. This temperature controlled based smart heating textile allows caregivers to monitor and adjust the cushion\u0026rsquo;s heating level via Bluetooth, providing a safe and user-friendly interface tailored to elderly care settings.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Conclusion","content":"\u003cp\u003eThis study presents the design, fabrication, and evaluation of thermochromic electric heating textiles integrated into woven and knitted fabric structures for elderly care applications. Through a comparative analysis, the thermal, colorimetric, and mechanical properties of various fabric designs were systematically assessed. The results demonstrate that double-layer woven and knitted fabrics achieve more uniform heat distribution and improved heating efficiency, with double-layer woven structures exhibiting superior heating performance, greater tensile strength, and clearer thermochromic colour change. Among the insulating yarns tested, soybean\u0026ndash;cotton blends provided more stable and uniform heating than wool-based alternatives. These findings support the tailored use of fabric structures in different applications: woven fabrics are more suitable for fast-response heating products such as blankets and seat warmers, while knitted structures are well-suited for thermo-insulated garments requiring flexibility and softness. The development of thermochromic cushions, coupled with a textile-based electronic control system for real-time monitoring, highlights the potential of smart textiles in enhancing user safety, comfort, and caregiver convenience in elderly care. Looking ahead, future research will explore the integration of voice recognition technology, supported by artificial intelligence (AI), to enable hands-free, user-friendly control of heating settings. This advancement aims to further enhance accessibility for elderly users by allowing intuitive and personalized temperature regulation through simple voice commands. Such user-centric innovations mark an important step toward the next generation of intelligent, responsive, and inclusive textile-based healthcare solutions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors appreciate the valuable technical support and advice from Siu Wing Ng and Lee Cheng Hao at the School of Fashion and Textiles, The Hong Kong Polytechnic University, on the specimen weaving process and the operation of the spectrophotometer and spectrofluorometer. The authors would also like to thank Mr. Shingo Sawai of the Kyoto Design Lab, Kyoto Institute of Technology, for his help with the knitting process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Ching Lee, Jeanne Tan\u003c/p\u003e\n\u003cp\u003eInvestigation: Ching Lee, Jun Jong Tan\u003c/p\u003e\n\u003cp\u003eBackground research: Ching Lee, Ka Wing Tse\u003c/p\u003e\n\u003cp\u003eMethodology: Ching Lee, Hiu Ting Tang, Annie Yu, Ngan Yi Kitty Lam\u003c/p\u003e\n\u003cp\u003eSupervision: Jeanne Tan\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; original draft: Jeanne Tan, Ching Lee\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; review \u0026amp; editing: Jeanne Tan, Ching Lee, Hiu Ting Tang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research is funded by the Laboratory for Artificial Intelligence in Design (Project Code: RP3-5) under InnoHK Research Clusters, Hong Kong Special Administrative Region.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData sets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMa B, Zhou Y, Tan J, Li Y, Wang X, Liu C, et al. Artificial intelligence in elderly healthcare: A scoping review. Ageing Res Rev. 2023;83:101808. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.arr.2022.101808\u003c/span\u003e\u003cspan address=\"10.1016/j.arr.2022.101808\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeyedAlinaghi S, Shokoohi M, Sahab-Negah S, Karami C, Tabatabaei A, Haghpanah S, et al. New technologies for elderly healthcare: A review of recent evidence. Public Health Environ. 2024;1(1):1\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.70737/6t5s6w76\u003c/span\u003e\u003cspan address=\"10.70737/6t5s6w76\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFan W, He J, Cai J, Li Z, Yao K, Zhang Y, et al. Machine-knitted washable sensor array textile for precise epidermal physiological signal monitoring. Sci Adv. 2020;6(11):eaay2840. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/sciadv.aay2840\u003c/span\u003e\u003cspan address=\"10.1126/sciadv.aay2840\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu A, Wang W, Li Z, Liu X, Zhang Y, Zhai J. Large-scale smart carpet for self-powered fall detection. Adv Mater Technol. 2020;5(2):1900978. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/admt.201900978\u003c/span\u003e\u003cspan address=\"10.1002/admt.201900978\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWicaksono I, Tucker CI, Sun T, Shi Y, Pang C, Leber KN, et al. A tailored, electronic textile conformable suit for large-scale spatiotemporal physiological sensing in vivo. NPJ Flex Electron. 2020;4(1):1\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41528-020-0068-y\u003c/span\u003e\u003cspan address=\"10.1038/s41528-020-0068-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou Z, Deng Y, He Q, Yu J, Tan P, Lu B, et al. Single-layered ultra-soft washable smart textiles for all-around ballistocardiograph, respiration, and posture monitoring during sleep. Biosens Bioelectron. 2020;155:112064. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bios.2020.112064\u003c/span\u003e\u003cspan address=\"10.1016/j.bios.2020.112064\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFang Y, Wang J, Xu Z, Pan C, Wu H. Ambulatory cardiovascular monitoring via a machine-learning-assisted textile triboelectric sensor. Adv Mater. 2021;33(41):2104178. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/adma.202104178\u003c/span\u003e\u003cspan address=\"10.1002/adma.202104178\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeng K, Zhao S, Zhou Y, Wu Y, Zhang S, He Q, et al. A wireless textile-based sensor system for self-powered personalized health care. Matter. 2020;2(4):896\u0026ndash;907. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.matt.2020.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.matt.2020.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahemtulla Z, Turner A, Oliveira C, Kaner J, Dias T, Hughes-Riley T. The design and engineering of a fall and near-fall detection electronic textile. Materials. 2023;16(5):1920. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ma16051920\u003c/span\u003e\u003cspan address=\"10.3390/ma16051920\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou S, Ouyang L, Li B, Hodder S, Yao R. A thermoregulation model based on the physical and physiological characteristics of Chinese elderly. Comput Biol Med. 2024;172:108262. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.compbiomed.2024.108262\u003c/span\u003e\u003cspan address=\"10.1016/j.compbiomed.2024.108262\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLv T, Lu Y, Zhu G. Research and analysis of user needs for smart clothing for the elderly. Wearable Technol. 2021;2:101. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54517/wt.v2i2.1653\u003c/span\u003e\u003cspan address=\"10.54517/wt.v2i2.1653\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMillyard A, Layden JD, Pyne DB, Edwards AM, Bloxham SR. Impairments to thermoregulation in the elderly during heat exposure events. Gerontol Geriatr Med. 2020;6:2333721420932432. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/2333721420932432\u003c/span\u003e\u003cspan address=\"10.1177/2333721420932432\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFitriani D, Pratiwi RD, Ayuningtyas G, Murtiningsih S, Poddar S. The differences in the effectiveness of providing thick blankets and electric blankets in reducing shivering incidence on postoperative patients in surgical installations Dr. Sitanala Hospital Tangerang, Indonesia in 2019. Malays J Med Res. 2021;5(4):28\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.31674/mjmr.2021.v05i04.007\u003c/span\u003e\u003cspan address=\"10.31674/mjmr.2021.v05i04.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu S, Wu J. Development of user interaction (UI)-based electrically heated clothing incorporating knitted jacquard pattern for the elderly. J Ind Text. 2024;54:15280837241287938. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/15280837241287938\u003c/span\u003e\u003cspan address=\"10.1177/15280837241287938\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eŞ Marius D, P Rareș, B Gabriella, D Liliana, F Lucian, R Georgiana Lavinia. Thermographic study on textile treatment equipment. Ann Univ Oradea Fac Text Leatherwork. 2024;25(2):87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee C, Tan J, Tan JJ, Tang HT, Yu WS, Lam NYK. Intelligent thermochromic heating e-textile for personalized temperature control in healthcare. ACS Appl Mater Interfaces. 2025; 17(3): 5515\u0026ndash;5526. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acsami.4c19174\u003c/span\u003e\u003cspan address=\"10.1021/acsami.4c19174\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePuspitosari A, Nurhidayah N. Sensory stimulation activities improving quality of life of elderly people in elderly communities. J Penelit Pendidik IPA. 2023;9(12):11038\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.29303/jppipa.v9i12.5572\u003c/span\u003e\u003cspan address=\"10.29303/jppipa.v9i12.5572\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlibakshi H, Eslami J, Shahrokhi S, Mirzabeigi H, Naimi E, Mirshoja MS. Effects of perceptual-motor exercises based on multi-sensory therapy on sensory processing of older adults. Iran J Ageing. 2024;19(3):410\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.32598/sija.2023.2789.6\u003c/span\u003e\u003cspan address=\"10.32598/sija.2023.2789.6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoo J, Hwang H. Effect of sensory stimulation type on brain activity in elderly persons with mild cognitive impairment. J Int Acad Phys Ther Res. 2019;10(1):1700\u0026ndash;05. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.20540/JIAPTR.2019.10.1.1700\u003c/span\u003e\u003cspan address=\"10.20540/JIAPTR.2019.10.1.1700\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJurabayev N, Shogofurov S, Kholikov K, Meliboev U. Study of the fabric structure influence on the physical-mechanical and technological properties of knitted products. E3S Web Conf. 2021;304:03030. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1051/e3sconf/202130403030\u003c/span\u003e\u003cspan address=\"10.1051/e3sconf/202130403030\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhoophat P, Soontrunnarudrungsri A, Chollakup R. Investigation of fabric tactile characteristics for different clothing based on elderly perspectives. Suranaree J Sci Technol. 2023; 30(4):030120(1\u0026ndash;9). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.55766/sujst-2023-04-e02413\u003c/span\u003e\u003cspan address=\"10.55766/sujst-2023-04-e02413\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue P, Tao X, Leung MY, Zhang H. Electromechanical properties of conductive fibres, yarns and fabrics. In: Wearable electronics and photonics. Amsterdam: Elsevier; 2005. p. 81\u0026ndash;104. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1533/9781845690441.81\u003c/span\u003e\u003cspan address=\"10.1533/9781845690441.81\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcBrearty D. Electronics calculations data handbook. Oxford: Elsevier; 1998.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee C, Tan J, Tan JJ, Tang HT, Yu WS, Lam NYK. Integrating artificial intelligence for optimal thermal comfort: A design approach for electric heating textiles aligned with user preferences. Text Res J. 2025;95(5\u0026ndash;6):513\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/00405175221148064\u003c/span\u003e\u003cspan address=\"10.1177/00405175221148064\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-applied-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Applied Sciences](https://link.springer.com/journal/42452)","snPcode":"42452","submissionUrl":"https://submission.springernature.com/new-submission/42452/3","title":"Discover Applied Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Smart textile, heating textile, thermochromic textile, temperature monitoring, elderly care","lastPublishedDoi":"10.21203/rs.3.rs-6366433/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6366433/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWith the rapidly aging population, maintaining personalized thermal comfort and preventing heat loss for elderly individuals has become increasingly important. Heating textiles provide an effective solution for warmth; however, without proper monitoring, the risk of overheating in real-world applications remains a concern. To address this challenge, thermochromic textiles offer a visual, real-time temperature indication through colour change, enhancing both safety and usability. In this study, thermochromic electric heating textiles were developed in woven and knitted structures, each offering distinct hand feel and performance characteristics. Key parameters, including heating efficiency, thermochromic response, thermal insulation, and overall thermal comfort, were systematically analyzed and compared. Findings reveal that double-layer fabric structures exhibit superior heat distribution and heating efficiency compared to single-layer counterparts, with the double-layer woven fabric demonstrating a more pronounced thermochromic colour change upon heating. Based on these insights, a collection of thermochromic heating cushions was designed for elderly care applications. Additionally, as a proof of concept, a fully textile-based electronic control system was proposed, enabling caregivers to remotely monitor the surface temperature of the heating fabric in real time and adjust the heating levels accordingly. By bridging the fields of textile engineering, smart materials, and healthcare monitoring, this study introduces innovative design strategies that enhance both functionality and user experience in elderly-focused heating textiles.\u003c/p\u003e","manuscriptTitle":"Smart Textile-integrated Thermochromic Display for Real-time Temperature Monitoring in Elderly Care","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 12:38:46","doi":"10.21203/rs.3.rs-6366433/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-13T16:46:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-27T03:22:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-21T12:20:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46854265266363589077809392205840585837","date":"2025-05-17T18:25:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-15T17:24:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18720880033124457455730225040341706191","date":"2025-05-14T18:43:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286394773419278636701624321238387179557","date":"2025-05-14T17:40:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20007534956651378363288856368500486850","date":"2025-05-12T21:54:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"322646407624233616663213422580636311621","date":"2025-05-12T17:39:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-12T17:30:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-06T11:55:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-06T11:53:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Applied Sciences","date":"2025-04-03T06:21:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-applied-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Applied Sciences](https://link.springer.com/journal/42452)","snPcode":"42452","submissionUrl":"https://submission.springernature.com/new-submission/42452/3","title":"Discover Applied Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e5e40ee4-c997-4624-b52e-eb8cf8f953e2","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-07-21T08:08:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-16 12:38:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6366433","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6366433","identity":"rs-6366433","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}