Flexible multi-mode hydrogel sensing patch as well as preparation method and application thereof

Abstract

The invention discloses a flexible multi-mode hydrogel sensing patch as well as a preparation method and application thereof. The flexible multi-mode hydrogel sensing patch is composed of a bottom hydrogel-based bimodal pressure-temperature sensing layer and a top electrostatic spinning nanofiber-based non-contact detection layer. The hydrogel serves as a core base material and has high toughness and water-retaining property, multi-mode sensing of temperature, pressure and non-contact proximity is achieved through different sensing mechanisms, and crosstalk interference does not exist. In a simulated real scene, the feasibility of the multi-mode sensing function of the robot hand is verified by grabbing an object through the robot hand. A plurality of multi-mode sensing patches integrated at different positions of the pillow are used for intelligent sleep monitoring, and a one-dimensional convolutional neural network is used for acquiring and analyzing various human pillow interaction information and time-dependent evolution thereof, so that tracking of head movement and recognition of wrong postures possibly causing poor sleep are realized; and a promising method is provided for sleep monitoring.

Description

Technical Field

[0001] The present invention relates to the field of wearable sensors, and particularly to a flexible multimodal hydrogel sensing patch, a preparation method thereof, and an application thereof. Background Art

[0002] With the rapid development of the economic level and living standard, people's attention to their own health conditions has been continuously increasing. Among all aspects of health management, sleep monitoring is particularly important because a person spends about one-third of their time sleeping, and the quality of sleep is crucial for the recovery of human health. Although traditional sleep monitoring methods (such as polysomnography PSG and portable devices) can provide detailed sleep data, these methods need to be carried out in a fixed test environment and require complex wire connections to bulky and complex devices, which severely limits their application and popularization in daily life. In contrast, wearable sensors have become an alternative for sleep monitoring due to their capabilities in physiological signal detection and posture recognition, as well as their miniaturized and flexible characteristics. However, these devices still need to be closely attached to multiple parts of the human body and require wire connections or transmission antennas to obtain sensing information, which inevitably interferes with the quiet sleep experience. Therefore, it is of great significance to develop an effective method for sleep monitoring in a comfortable and unconstrained manner.

[0003] In recent years, wearable sensors have made remarkable progress in disease perception, posture detection, and physiological signal monitoring. Among the existing available polymer materials, hydrogels have become ideal substrates for constructing flexible sensors due to their unique properties (such as self-adhesion, adjustable conductivity, modulus similar to biological tissues, and good biocompatibility), enabling close attachment to the human body to achieve a close-fitting wearing mode. However, the practical application of hydrogel sensors still faces major challenges. Due to their high water content, hydrogels usually exhibit limited mechanical properties, such as low strength and toughness, and are difficult to adapt to some demanding flexible conditions. In addition, after long-term use, the water content of hydrogels will significantly decrease, resulting in poor durability. Water evaporation not only affects the mechanical strength but also reduces the sensing ability. In addition, most hydrogel sensors only provide a single sensing function (such as pressure or temperature), making it difficult to meet the diverse needs of simultaneous monitoring of multiple human parameters in complex environments. In addition, most sensing signals (such as pressure and temperature) mainly come from the biological information of the human skin. To expand the functions of flexible sensors, it is also necessary to obtain the interaction information of non-contact behaviors between objects and the human body in the near range, so proximity sensors are required. In summary, developing hydrogel sensors with high mechanical toughness, long-lasting water retention, and multimodal sensing capabilities is of great significance for promoting personal health monitoring technology to a higher level. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a flexible multimodal hydrogel sensing patch and a preparation method and application thereof.

[0005] In a first aspect, the present invention provides a preparation method of a flexible multimodal hydrogel sensing patch, which is achieved through the following technical solutions.

[0006] A preparation method of a flexible multimodal hydrogel sensing patch includes the following steps:

[0007] S1. Preparation of M-PPT organic hydrogel with spherical microstructures

[0008] a. Add acrylamide powder and polyvinyl alcohol particles into water and stir evenly; wherein, the mass ratio of acrylamide to polyvinyl alcohol is (6 - 8):1.

[0009] b. Add (5 - 7)wt% MXene aqueous solution and PEDOT:PSS solution to the above mixture and stir evenly; wherein, the volume ratio of MXene aqueous solution, PEDOT:PSS solution and polyvinyl alcohol is 1:(17 - 20):(11 - 13).

[0010] c. Add 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide salt to the above mixture and stir evenly; wherein, the volume ratio of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide salt to PEDOT:PSS solution is (1.1 - 1.3):1.

[0011] d. Sequentially add ammonium persulfate initiator and N,N'-methylenebisacrylamide to the above mixture, the mass ratio of ammonium persulfate to N,N'-methylenebisacrylamide is (17 - 19):1, and the addition amount of ammonium persulfate is 1 - 2wt% of the total mass of the reaction system.

[0012] e. Pour the mixed solution obtained in step d into a container containing a mold with spherical microstructures.

[0013] f. After degassing, heat at (60 - 70)°C for 20 - 30 minutes to obtain M-PPT hydrogel with spherical microstructures.

[0014] g. Immerse the M-PPT hydrogel in a mixed solution of water and glycerol to obtain M-PPT organic hydrogel.

[0015] S2. Preparation of Ag / PVDF / Ti 3 C 2 Tx nanofibers for interdigital electrodes

[0016] Ⅰ. Completely dissolve polyvinylidene fluoride in DMF solvent, and the mass-volume ratio of polyvinylidene fluoride to DMF is (0.25 - 0.27) g / ml.

[0017] II. Add MXene powder to the above solution and stir until the MXene powder is uniformly dispersed; the mass ratio of MXene powder to polyvinylidene fluoride is 1:(38 - 40);

[0018] III. Use a syringe to take the mixed solution for electrospinning, and dry the obtained electrospun membrane to obtain a PVDF / Ti 3 C 2 Tx thin film;

[0019] IV. Place the mask of the interdigital electrode with a pattern on the PVDF / Ti 3 C 2 Tx thin film and fix it on the magnetron sputtering substrate; use the DC magnetron sputtering technique to sputter a silver target, and finally obtain an Ag / PVDF / Ti 3 C 2 Tx nanofiber membrane with a patterned interdigital silver electrode;

[0020] S3. Stack the M-PPT organic hydrogel prepared in step S1 with the Ag / PVDF / Ti 3 C 2 Tx nanofiber membrane to form a complete flexible multimodal hydrogel sensing patch.

[0021] Furthermore, the preparation method of MXene is as follows: Add 75% concentrated hydrochloric acid and lithium fluoride to water and stir to mix evenly; under stirring conditions, add Ti 3 AlC 2 , heat in a water bath at (40 - 50) °C and stir at (1000 - 1200) r / min for (22 - 24) hours to obtain an MXene etching solution; centrifuge the MXene etching solution to obtain a multi-layer MXene precipitate, then mix it with deionized water, and freeze-dry to obtain multi-layer MXene powder; among them, the mass ratio of concentrated hydrochloric acid, lithium fluoride, and Ti 3 AlC 2 is (19 - 20):(1.8 - 1.7):(1.3 - 1.4).

[0022] Furthermore, the preparation method of the spherical microstructure mold is as follows: Design a rectangular column with dimensions of 1.8 cm × 1.5 cm × 0.5 cm, and arrange multiple spheres with a radius of 250 μm on the top surface of the rectangular column; use an ultraviolet photosensitive resin material for 3D printing to make the mold, clean the mold surface and then cure it with ultraviolet light; prepare polydimethylsiloxane, and fully mix the curing agent and the base monomer according to a mass ratio of 10:1; pour the mixture into the printed mold, vacuum degas at room temperature for 15 - 20 minutes, and then completely cure at (70 - 80) °C for 2 - 3 hours, and peel to obtain a mold with a concave spherical microstructure.

[0023] Furthermore, the extrusion speed of the electrospinning setup is (0.6 - 0.7) mm / min, the collection distance is (80 - 85) mm, the spinning time is (2 - 2.5) hours, and the spinning voltage is (18 - 20) kV.

[0024] Furthermore, the experimental conditions for DC magnetron sputtering are as follows: the oxygen flow rate is 20 - 22 L / min, the pressure is (2 - 3) Pa, the power is (80 - 82) W, and the sputtering time is (15 - 17) minutes.

[0025] In a second aspect, the present invention provides a flexible multimodal hydrogel sensing patch, which is achieved through the following technical solutions.

[0026] A flexible multimodal hydrogel sensing patch prepared by the above preparation method.

[0027] In a third aspect, the present invention provides a use of the flexible multimodal hydrogel sensing patch, which is achieved through the following technical solutions.

[0028] An application of the above flexible multimodal hydrogel sensing patch in sleep monitoring.

[0029] This application has the following beneficial effects.

[0030] The present invention has developed a flexible integrated multimodal proximity - pressure - temperature sensing patch (M - PPT) based on a highly tough and water - retaining hydrogel and applied it to unconstrained sleep monitoring. The sensing patch is designed to consist of a bottom hydrogel - based bimodal pressure - temperature sensing layer and a top electrospun nanofiber - based non - contact detection layer, forming an integrated device. The hydrogel as the core substrate exhibits excellent mechanical properties, with its strength, toughness, and deformation recovery not decreasing after repeated use, while also showing excellent water retention, with no mass loss after 8 days. The internal structure effectively locks in moisture and prevents water evaporation, ensuring that the hydrogel sensor maintains its original sensing performance during long - term use. In terms of multimodal sensing capabilities, the temperature sensing based on the conductive polymer PEDOT:PSS exhibits a high sensitivity of 0.5℃ -1 and has a good linear relationship, suitable for body temperature monitoring; the pressure sensing based on the ion - capacitance sensing mechanism shows a high sensitivity of 30.6 kPa -1 in the low - pressure range of 1 kPa and 26.3 kPa -1The sensitivity is such that the response time is only 5.6 ms, suitable for head touch detection; the non-contact sensing based on MXene-doped electrospun PVDF nanofibers has an ultra-wide non-contact detection range (exceeding 2 meters) and stable durability, enabling proximity interaction perception. To verify the practicality of M-PPT, the feasibility of its multimodal sensing function was verified through a simulated scenario of a robotic hand grasping an object. Finally, multiple multimodal sensing patches were seamlessly integrated at different positions of the pillow for intelligent sleep monitoring. Human-pillow interaction information including temperature, pressure, and proximity signals and its evolution with head movement were obtained in real time, and one-dimensional convolutional neural network (1D-CNN) was used to analyze the multi-dimensional sensing data to achieve tracking of head movement and identification of bad postures that may lead to a decline in sleep quality. In this way, sleep quality can be monitored in a comfortable and unrestrained manner, and personalized sleep management can be achieved to prevent potential health risks. Brief Description of the Drawings

[0031] Figure 1 It is a design concept and synthesis strategy diagram of the hydrogel-based M-PPT of this application in sleep monitoring. Among them, (A) is the preparation flow chart of the hydrogel with an ionic cross-linked structure. (B) is a schematic diagram of the structure, function, and application of M-PPT. (C) is the FTIR spectral analysis of the hydrogel. (D) is the Raman spectral analysis of the hydrogel. (E) is a photo display of the hydrogel being shaped into various shapes and its excellent tensile properties;

[0032] Figure 2 It is a diagram of the mechanism and performance of the temperature sensing mode of this application. Among them, (A) is a schematic diagram showing the working principle of the hydrogel transferring heat from the skin; (B) is the moisture release process of PEDOT and PSS molecules; (C) is the sensitivity of the sensor; (D) is the cycling performance of the sensor; (E) is the sensitivity of the sensor at different carrier concentrations; (F) is the performance change of the sensor under different stretching and temperature conditions; (G) is the stability of the sensor at different temperatures; (H) is the signal linear fitting of the sensor during heating and cooling cycles; (I) is the detection of water at different temperatures; (J) is the response recovery time;

[0033] Figure 3 It is the mechanism and performance of the pressure sensing mode of this application. Among them, (A) is the SEM image of the surface microstructure of the hydrogel layer; (B) is the COMSOL simulation of the pressure sensing process; (C) is the sensitivity curve of sensors with different compositions; (D) is the response and recovery time of the sensor; (E) is the minimum detection limit; (F) is the dynamic response signal of the sensor at different frequencies; (G) is the influence of temperature on the pressure sensing mode; (H) is the influence of pressure on the temperature sensing mode; (I) is the performance comparison of the sensor with previously reported works; (J) is the detection result when holding a cup with different amounts of water.

[0034] Figure 4It is the mechanism and performance of the proximity sensing mode of this application. Among them, (A) the schematic diagram shows the working principle of vertical-mode proximity sensing based on the triboelectric effect; (B) the schematic diagram shows the collision and friction test device between the proximity sensor and various comparison materials; (C) the response voltage between the proximity sensor and different comparison materials; (D) the current between the proximity sensor and nylon material; (E) charge; (F) voltage; (G) the influence of temperature on the voltage of the proximity sensor; (H) as the separation distance increases, the voltage gradually decreases; (I) the COMSOL simulation of the proximity sensor; (J) the peak power under different load conditions; (K) the voltage change at different frequencies;

[0035] Figure 5 It is the simulation of multimodal sensing ability by the robotic hand in the actual scenario of this application. Among them, (A) the schematic diagram shows the multimodal sensing process in which the robot simulates human perception through neural signals via electromechanical signals; (B) the characteristic waveforms of the three sensing modes; (C) four steps of simulating the robotic hand touching a hot object: the initial stage, the approaching stage, the contact stage, and the leaving stage, and (D) the corresponding waveforms of the three sensing modes; (E) the combined test and multiple cycle test results of multimodal proximity-pressure-temperature sensing;

[0036] Figure 6 It is the appearance photo of the sensing patch of this invention;

[0037] Figure 7 It is the result graph of the tensile performance of the hydrogel of this invention;

[0038] Figure 8 It is the water retention performance result of the hydrogel of this invention Figure 1 ;

[0039] Figure 9 It is the water retention performance result of the hydrogel of this invention Figure 2 ;

[0040] Figure 10 It is the verification graph of the multi-water structure inside the hydrogel of this invention;

[0041] Figure 11 It is the working principle diagram of the pressure sensor of this invention;

[0042] Figure 12 It is the result graph of the cyclic stability of the hydrogel pressure sensor of this invention;

[0043] Figure 13 It is the result graph of the temperature stability of the hydrogel pressure sensor of this invention;

[0044] Figure 14 It is the pressure change graph of the hydrogel pressure sensor of this invention at different wrist bending angles;

[0045] Figure 15 It is the pulse detection result diagram of the hydrogel pressure sensor of the present invention;

[0046] Figure 16 It is for the preparation of Ag / PVDF / Ti 3 C 2 The result diagram of the Tx nanofiber membrane;

[0047] Figure 17 It is the XRD diagram of the proximity sensing layer thin film of the present invention;

[0048] Figure 18 It is the cyclic stability result diagram of the proximity sensing layer of the present invention. Detailed implementation manners

[0049] The invention will be further described below in conjunction with the drawings and embodiments.

[0050] 1 Experimental part

[0051] 1.1 Materials

[0052] Polyvinylidene fluoride (PVDF), 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][TFSI]) were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd.; acrylamide (AM, AR, 99.0%), titanium aluminum carbide powder (Ti 3 AlC 2 )), poly(3,4-ethylenedioxythiophene)-polystyrenesulfonate (PEDOT:PSS) (solid content in water 1.5%), N,N'-methylenebisacrylamide (MBA, AR), ammonium persulfate (APS, AR, 98.5%), lithium fluoride and glycerol (AR, 99%) were all purchased from Macklin Biochemical Technology Co., Ltd. (Shanghai, China).

[0053] 1.2 Preparation of the sensing patch

[0054] 1.2.1 Preparation of MXene (Ti 3 C 2 Tx) nanosheets

[0055] (1) Add 20 ml of 75% concentrated hydrochloric acid and 1.7 g of lithium fluoride to 10 ml of deionized water, and stir with a magnetic stirrer at 1200 r / min for 10 minutes until lithium fluoride is completely dissolved in the hydrochloric acid solution. (2) Stir the mixed solution with a magnetic stirrer at 600 r / min, and slowly add 1.3 g of titanium aluminum carbide to the etching solution at the same time. Heat in a 40 °C water bath and stir at 1000 r / min for 24 hours to remove aluminum elements, obtaining an MXene etching solution. (3) Centrifuge the etching solution at 8000 r / min for 5 minutes to obtain a multi-layer MXene precipitate. Mix it with deionized water and place it in a freeze dryer for 24 hours to obtain multi-layer MXene powder.

[0056] 1.2.2 Preparation of Spherical Microstructure Molds

[0057] (1) Use 3ds Max 2024 software to design a rectangular column with dimensions of 1.8 cm × 1.5 cm × 0.5 cm, and arrange multiple spheres with a radius of 250 μm on the top surface of the rectangular column. (2) Use ultraviolet photosensitive resin material for 3D printing to make the mold. Slowly clean the mold surface with anhydrous ethanol to remove impurities, and then cure it with ultraviolet light. (3) Prepare polydimethylsiloxane (PDMS), and fully mix the curing agent and the base monomer (Dow Corning Sylgard 184) at a mass ratio of 10:1. (4) Pour the PDMS mixture into the printed mold, degas it under vacuum at room temperature for 20 minutes to remove air bubbles, then cure it completely at 80 °C for 2 hours, and finally peel it off to obtain a mold with a concave spherical microstructure.

[0058] 1.2.3 Preparation of M-PPT Organic Hydrogel Containing Spherical Microstructure

[0059] (1) Add 4.2 g of AM powder and 0.6 g of PVA particles to 8 ml of deionized water, and stir at 1000 r / min with a magnetic stirrer at 85 °C for 3 hours. (2) Add 1 ml of 5% MXene aqueous solution and 1 ml of PEDOT:PSS solution to the above solution, and stir at 600 r / min with a magnetic stirrer at room temperature for 2 hours. (3) Slowly add 1.2 ml of [EMIM][TFSI] to the solution, and stir at 600 r / min with a magnetic stirrer for 30 minutes. (4) Add 0.42 ml of 20% APS initiator solution and 0.23 ml of 2% MBA solution to the mixture in sequence. (5) Place the prepared spherical microstructure mold in a glass petri dish that has been treated with plasma cleaning. (6) After thoroughly mixing the mixed solution, pour it into the spherical microstructure mold. (7) After degassing, place the petri dish in an oven at 60 °C and heat for 20 minutes to prepare the M-PPT hydrogel containing spherical microstructures. (8) Finally, soak the prepared M-PPT hydrogel in a water / glycerol mixed solution with a mass ratio of 1:1 for 10 minutes to obtain the final M-PPT organic hydrogel.

[0060] 1.2.4 PVDF / Ti for the triboelectric proximity sensing layer 3 C 2 Preparation of Tx nanofibers

[0061] (1) Dissolve 2 g of PVDF powder in 8 ml of DMF solvent. (2) Heat the solution in an 80 °C water bath and stir at 800 r / min for 3 hours to ensure complete dissolution. (3) Add 0.05 g of Ti 3 C 2 Tx powder, and stir at 600 r / min with a magnetic stirrer for 1 hour to ensure the uniform dispersion of Ti 3 C 2 Tx powder. (4) Use a 10 ml disposable syringe to take 8 ml of the mixed solution for electrospinning, set the extrusion speed to 0.6 mm / min, the collection distance to 80 mm, the spinning time to 2 hours, and the spinning voltage to 18 kV. (5) Vacuum dry the electrospun membrane at 40 °C for 12 hours to remove surface moisture.

[0062] 1.2.5 Ag / PVDF / Ti for the interdigital electrodes 3 C 2 Preparation of Tx nanofibers

[0063] Place the patterned interdigital electrode mask on PVDF / Ti 3 C 2On the Tx thin film, it was fixed on the magnetron sputtering substrate with clips (the interdigital electrode mask was purchased from JLCPCB). The commercial silver target was sputtered using DC magnetron sputtering technology under the conditions of an oxygen flow rate of 20 L / min, a pressure of 2 Pa, a power of 80 W, and a sputtering time of 15 minutes, and finally an Ag / PVDF / Ti with patterned interdigital silver electrodes was obtained. 3 C 2 Tx nanofiber membrane.

[0064] 2 Results and Discussion

[0065] 2.1 Design Concept and Synthesis Strategy of M-PPT

[0066] As an intrinsically flexible material, hydrogel has become an ideal choice for sensor design due to its unique physical and chemical properties. Figure 1 A shows the preparation process of the hydrogel-based bimodal pressure-temperature sensor and its ionic cross-linked structure. During the preparation process, the successful initiation of the structural ionic cross-linking is crucial, which not only enhances its internal mechanical strength but also provides sensitivity to external pressure and temperature stimuli. Figure 1 B illustrates the overall structure, function, and application of the proposed multimodal proximity-pressure-temperature sensing patch (M-PPT). The appearance photo of the sensing patch is shown in Figure 6 .

[0067] In terms of the internal device structure, the hydrogel-based bimodal pressure-temperature sensing layer serves as the bottom layer, the biocompatible adhesion layer for attaching to the human skin, and the triboelectric proximity sensing layer with interdigital silver electrodes is integrated on the top. For actual human health monitoring, the M-PPT can be seamlessly integrated at multiple positions of a commercial pillow, and continuously and real-time identify the head position of the sleeper through the intelligent recognition of multimodal sensing information of temperature, pressure, and proximity distribution. Such multifunctional data is of great significance for in-depth research on sleep in an unconstrained manner. The various signals obtained representing different physiological parameters show characteristic waveforms at different sleep stages, providing a scientific basis for sleep quality assessment and sleep disorder diagnosis.

[0068] To verify the chemical composition and structure of the hydrogel, Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy were used for analysis. The FTIR spectrum shows the characteristic absorption peaks of various functional groups, confirming the specific chemical bonds and molecular structure in the hydrogel matrix ( Figure 1 C). In the ordinary AM hydrogel (H hydrogel), the characteristic peak at 3185 cm -1 is attributed to the stretching vibration of N-H; the absorption peak at 1417 cm -1 is attributed to the stretching vibration of the carbonyl group; while the absorption peak at 1326 cm -1The peak is the result of the bending vibration of the amide N-H. When hydrogen bonds are formed between molecules, the stretching peak of -OH will vibrate. Compared with the H-P hydrogel (the hydrogel after adding PVA), the -OH characteristic peak of the H-P-M-P hydrogel (the hydrogel after adding PVA-MXene-PEDOT:PSS) shifts significantly from 3270 cm -1 to 3265 cm -1 , indicating the formation of hydrogen bonds between H-P-M-P. Raman spectroscopy further provides information on the molecular structure of the hydrogel ( Figure 1 D), in which a peak at 1451 cm -1 is observed in the H-P-M-P hydrogel due to the addition of PEDOT:PSS.

[0069] From a macroscopic perspective, the hydrogel exhibits excellent flexibility ( Figure 1 E), and can be molded into various shapes such as butterflies, puppies, and flamingos, ensuring its suitability as a substrate for flexible wearable sensors. The hydrogel also demonstrates excellent tensile properties and can be used under harsh flexible conditions ( Figure 7 ). By adding glycerol, the hydrogel exhibits excellent water retention performance, with almost no appearance shrinkage ( Figure 8 ) and no water loss ( Figure 9 ) over a period of up to 8 days. This indicates that the hydrogel can retain moisture for a long time, ensuring the excellent stability and reliability of the flexible sensor.

[0070] To verify the multi-water structure inside the hydrogel, the hydrogel sample was freeze-dried in this application. By freezing the water in the sample into a solid state and sublimating it under low-temperature and low-pressure conditions, the internal structure of the hydrogel changed significantly after removing the water, forming a porous structure ( Figure 10 ). This porous structure directly reflects the multi-water network in the hydrogel.

[0071] 2.2 Temperature sensing performance of M-PPT

[0072] Figure 2 Details show the working principle and several key performance of the hydrogel-based temperature sensor. First, Figure 2 A shows the working schematic diagram of the hydrogel temperature sensor, illustrating the process of the sensor's resistance decreasing and current increasing when the external temperature changes. Figure 2Figure B shows in detail the working principle of PEDOT:PSS molecules. PEDOT:PSS is a conductive polymer material commonly used in flexible electronic devices, which has a unique core-shell structure. The conductive PEDOT core is surrounded by an insulating PSS shell. When the temperature rises, water molecules in the hydrophilic PSS are released into the external environment, causing the PSS shell to shrink, thereby reducing the distance between adjacent PEDOT cores and enhancing the electron hopping effect. The results show that the resistance of PEDOT:PSS decreases with increasing temperature.

[0073] Figure 2 Figure C shows the sensitivity of the temperature sensor. The sensitivity curve of the sensor is plotted based on the average data from five experimental tests, showing a maximum sensitivity of 0.5 °C⁻¹. To verify the stability and reliability of the sensor under repeated temperature changes, a cyclic temperature change test was conducted. The results show that the sensor exhibits excellent cyclic stability in two temperature ranges. Figure 2 Figure D shows the cyclic performance of the sensor in two temperature ranges of 34 °C - 38 °C and 38 °C - 42 °C. The results show that the sensor has stable performance during long-term use and no obvious degradation.

[0074] This application further studied the influence of different carrier concentrations on the sensitivity of the sensor. Comparative analysis of experimental data shows that when the carrier concentration is 12 wt%, the sensor has the highest sensitivity (as shown in Figure 2 Figure E). Due to the excellent flexibility and stretchability of the hydrogel material, it is particularly important to study its temperature response under different stretching conditions. Figure 2 Figure F shows the performance changes of the sensor under different stretching and temperature conditions. The results show that the sensor still maintains high sensitivity and stability in various stretching states. In addition, under long-term constant temperature conditions, the sensor can maintain a stable signal output, which is crucial for continuous monitoring in practical applications.

[0075] Figure 2 Figure G shows the experimental results of the sensor maintaining stable performance at temperatures of 34 °C, 36 °C, 38 °C, 40 °C, and 42 °C, without obvious drift or noise, ensuring the reliability and accuracy of temperature data. Figure 2 Figure H shows the signal changes of the sensor during heating and cooling cycles. The experimental results show that there is a good linear relationship between the signal changes of the sensor, indicating that it can provide a stable and predictable electrical signal output during temperature changes. This linear characteristic helps in the calibration and data processing of the temperature sensor, simplifying the data conversion and analysis process in temperature measurement.

[0076] To verify the performance of the sensor in practical applications, it was attached to the outside of a beaker to detect water at different temperatures (as shown in Figure 2 Figure I). The sensor can accurately detect changes in water temperature.Figure 2 J shows that the time for the sensor to return to the stable state after a temperature change from 38 °C to 42 °C is 17 seconds. The rapid recovery time means that the sensor can quickly return to its initial state, thereby improving the real-time performance and accuracy of temperature measurement and meeting the requirements of real-time monitoring.

[0077] 2.3 M-PPT's pressure sensing performance

[0078] Figure 3 Demonstrates the performance characteristics and working mechanism of the hydrogel-based pressure sensor, and verifies its excellent performance and broad application potential through a series of experiments and simulations. To improve the sensitivity and response speed of the sensor, spherical microstructures are constructed on the hydrogel surface using the pattern transfer method. These microstructures play a key role in the sensing process by reducing the initial contact area. Figure 3 A shows the characterization of the spherical microstructures on the surface of the hydrogel pressure sensing layer using a scanning electron microscope (SEM), revealing the ordered arrangement of the spherical structures.

[0079] Figure 3 B demonstrates the simulation of the sensor behavior under the applied pressure conditions using COMSOL software, observing the internal structural changes and stress distribution when the pressure acts on the hydrogel surface. Due to its ion supercapacitor sensing mechanism and spherical microstructures, this electronic skin exhibits excellent sensing performance. Figure 11 Details the working principle of the pressure sensor.

[0080] Figure 3 C shows the relative capacitance change curves (sensitivity curves) of sensors with different ion contents. Sensitivity is a key parameter in pressure sensing and is defined as: S = δ(ΔC / C 0 ) / δP, where ΔC is the relative capacitance change, C 0 is the initial capacitance without pressure, and P is the applied pressure. Among the four different sensors, the sensor with spherical microstructures and an MXene:PEDOT:PSS:[EMIM][TFSI] ratio of 1:1:1.2 shows the highest pressure sensitivity, with a sensitivity of 30.6 kPa-1 at a low pressure of 1 kPa and 26.3 kPa-1 at a high pressure of 40 kPa.

[0081] Figure 3 D shows the dynamic response speed of the hydrogel-based pressure sensor under pressure changes. The results show that the sensor responds quickly to pressure changes and can quickly return to its initial state after the pressure is released, with both the response and recovery times being less than 5.6 ms. Figure 3 E demonstrates the minimum detection limit of the sensor, which can detect small pressures of 25 Pa and 50 Pa.

[0082] Figure 3Figure F shows the dynamic load test results under pressure changes at different frequencies (0.4 Hz, 1.33 Hz, 2 Hz). The sensor outputs stable signals at different frequencies, indicating its good frequency response characteristics. Figure 12 The cyclic stability of the hydrogel pressure sensor was further tested. After approximately 16,500 cycles, the sensor still maintained excellent stability.

[0083] Environmental temperature changes may affect the performance of the sensor. Therefore, it is crucial to study the influence of temperature on pressure sensing performance. Figure 3 Figure G explores the pressure performance of the sensor in different temperature ranges from 25 °C to 45 °C. The results show that the hydrogel pressure sensor maintains high sensitivity and stability in this temperature range, demonstrating good temperature stability ( Figure 13 ).

[0084] Since the pressure and temperature sensors are integrated in the same device, it is also important to study the influence of pressure on temperature sensing performance. Figure 3 Figure H shows the changes in temperature sensing performance under different pressures from 500 Pa to 7 kPa. The results show that the temperature response of the sensor remains stable under different pressure conditions, indicating that the interference between pressure and temperature measurements is minimal, ensuring reliable simultaneous measurement capabilities.

[0085] Figure 3 Figure I compares the performance of the hydrogel-based pressure sensor with other reported works. The designed sensor has significant advantages in terms of sensitivity, response and recovery time, working range, and stability.

[0086] To verify the feasibility and reliability of the sensor in practical applications, it was attached to cups containing different amounts of water (100 ml and 150 ml), and the pressure changes were tested by hand (as Figure 3 shown in Figure J). In addition, the hydrogel pressure sensor accurately sensed the pressure changes at different wrist bending angles (30°, 60°, 90°) ( Figure 14 ). The sensor also successfully achieved pulse detection, capturing subtle pulse fluctuations ( Figure 15 ), providing accurate physiological data.

[0087] 2.4 M - PPT Proximity Sensing Performance

[0088] The proximity sensor in this application is mainly based on the triboelectric principle. Figure 4A shows a schematic diagram of the vertical mode. In this mode, an electrical signal is generated through the charge transfer between the electrode and the ground. When the hand approaches the friction layer, the electric field is redistributed, and negative charges flow from the ground to the nanofiber electrode, generating an instantaneous current in the external circuit. When the hand remains stationary, the system reaches an electrostatic equilibrium state. When the hand leaves the friction layer, the negative charges flow back from the nanofiber electrode to the ground. Based on this principle of the charge transfer effect, it is possible to detect approaching and leaving movements.

[0089] The proximity sensing layer is made of electrospun PVDF nanofibers, and the electrode part is prepared with interdigital silver electrodes on the surface of the nanofibers through magnetron sputtering technology ( Figure 16 A). To improve the surface charge density and charge capture ability, two-dimensional MXene sheets are incorporated into PVDF. After electrospinning, a composite film with a spherical multi-physical network structure is prepared ( Figure 16 B-C). This spherical multi-physical network exhibits excellent chemical stability and a high specific surface area, which can effectively capture and accumulate more negative charges. In addition, highly conductive Ti 3 C 2 Tx is uniformly distributed within the microspheres, increasing the continuous conduction path.

[0090] The successful preparation of the proximity sensing layer film is confirmed by X-ray diffraction (XRD) ( Figure 17 ), and the interaction between PVDF and Ti 3 C 2 Tx sheets is studied. The diffraction peak of the (104) crystal plane of Ti 3 C 2 Tx is observed at 36°, and the enhancement of its peak is attributed to the binding of H and F atoms on the PVDF chain to the surface functional groups of Ti 3 C 2 Tx, ultimately forming polymer chains between the Ti 3 C 2 Tx layers. A similar trend is also observed at the β(110 / 200) crystal plane. When the addition amount of Ti 3 C 2 Tx is too high, the width of the diffraction peak decreases significantly, which may be due to the reduction of the crystallinity of the β-phase crystals in the composite film.

[0091] To verify the performance of the proximity sensing layer, a series of experiments are designed, involving the collision and friction tests of the sensing layer with various materials using a linear motor ( Figure 4 B). The test materials include nylon, mixed cellulose, knitted fabric, copper sheet, polyurethane, and thermoplastic polyurethane. Since there are significant differences in the triboelectric effect intensity of different materials, the voltage values generated by each material are also different ( Figure 4C). For example, the triboelectric effect between the nylon material and the sensing layer is significant, generating a test voltage as high as 133V. Figure 4 D shows the test current of the proximity sensing layer interacting with the nylon material. Figure 4 E shows that the test charge is 47 nC, indicating a high charge transfer efficiency. The voltage test results of the interaction between the nylon materials are as Figure 4 shown in F.

[0092] To evaluate the effect of temperature change on the performance of the sensing layer, voltage tests were conducted under different temperature conditions ( Figure 4 G). The results show that the sensing layer maintains high stability at various temperatures. To study the effect of distance change on the proximity sensing layer, the signal changes of the nylon material at different distances were tested ( Figure 4 H). As the distance increases, the voltage signal gradually decreases. Figure 4 I shows the COMSOL simulation of the proximity sensing test, visually displaying the electric field distribution and charge accumulation around the nylon material at different distances, further verifying the working principle and performance characteristics of the sensing layer.

[0093] Experimental measurements under different load conditions measured the peak power generated during the friction process ( Figure 4 J). The cyclic stability of the proximity sensing layer was tested through the collision-separation friction test. After 4000 cycles ( Figure 18 ), the sensing layer still maintained excellent stability. To verify the stable performance of the sensor under different dynamic conditions, collision-separation friction tests at different frequencies were conducted. Figure 4 K shows the voltage changes at different test frequencies. The results indicate that the sensing layer can output stable voltage signals at different test frequencies, demonstrating good frequency response characteristics.

[0094] 2.5 Multimodal Proximity-Pressure-Temperature Sensing Capability in Realistic Scenarios

[0095] Figure 5 The multimodal sensing performance and working mechanism in an actual scenario were explored through a robotic hand, and its excellent performance and broad application potential were verified through a series of experiments and simulations. Multimodal sensing integrates mechanical, electrical, and neural signals, as Figure 5 shown in A. Figure 5 B shows the characteristics of the three sensing modes, and the output characteristic curves of proximity, pressure, and temperature signals were plotted through experimental measurement and analysis.

[0096] The sensor was installed on the robotic finger to simulate the scenario of touching a glass bottle filled with warm water (to prevent humidity from affecting the sensor, the bottle mouth was sealed with a sealing film), as Figure 5As shown in C. By controlling the movement trajectory of the robotic hand, the perception process of a human finger approaching, contacting, and then moving away from an object can be accurately simulated (phases S1, S2, S3, and S4). Figure 5 D shows the changes in the sensor signals in the four phases and conducts a detailed analysis and comparison. Phase S1: The robotic finger remains stationary and all sensor signals remain stable. Phase S2: When the robotic hand approaches the thermos flask, the proximity sensor starts to respond and generates a downward voltage peak, while the pressure and temperature sensor signals remain stable. Phase S3: When the robotic hand touches the thermos flask, the pressure and temperature sensors start to respond, manifested as an increase in capacitance and a decrease in resistance. Phase S4: When the robotic hand moves away from the thermos flask, all three sensors respond. After generating a downward voltage peak, the proximity sensor gradually recovers, the capacitance of the pressure sensor decreases, and the resistance of the temperature sensor increases.

[0097] Figure 5 E shows the comprehensive changes in the proximity, pressure, and temperature signals, where the voltage change corresponds to proximity sensing, the capacitance change corresponds to pressure sensing, and the resistance change corresponds to temperature sensing.

[0098] To verify the stability and reliability of the multimodal sensing system, multiple cycle tests were conducted, and the changes in the proximity, pressure, and temperature signals under different cycle conditions were measured. The results show that all three signals exhibit good stability and consistency in multiple cycle tests, indicating that the multimodal sensing system has high repeatability and reliability and can provide stable and reliable sensing data in practical applications.

[0099] The embodiments of this specific implementation manner are all preferred embodiments of the present invention, and do not limit the protection scope of the present invention accordingly. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for preparing a flexible multimodal hydrogel sensor patch, characterized in that: The following steps are involved: S1. Preparation of M-PPT organohydrogel containing spherical microstructures a. Add acrylamide powder and polyvinyl alcohol particles to water and stir to mix; wherein the mass ratio of acrylamide and polyvinyl alcohol is (6-8): 1; b. Add (5-7) wt% MXene aqueous solution and PEDOT:PSS solution to the above mixture and stir to mix; wherein the volume ratio of MXene aqueous solution, PEDOT:PSS solution and polyvinyl alcohol is 1:(17-20):(11-13); c. Add 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl imide) salt to the above mixture and stir to mix; wherein the volume ratio of 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl imide) salt to PEDOT:PSS solution is (1.1-1.3):1; d. Sequentially, ammonium persulfate initiator and N, N'-methylenebisacrylamide were added to the above mixture, the mass ratio of ammonium persulfate and N, N'-methylenebisacrylamide was (17-19): 1, and the amount of ammonium persulfate added was 1-2wt% of the total mass of the reaction system; e. The mixed solution obtained in step d is poured into a container containing a spherical microstructure mold; f. After degassing, heating at (60-70) ° C for 20-30 minutes to obtain an M-PPT hydrogel containing spherical microstructures; g. The M-PPT hydrogel was immersed in a mixed solution of water and glycerol to obtain the M-PPT organic hydrogel. S2. Preparation of Ag / PVDF / Ti3C2Tx Nanofibers for Interdigitated Electrodes Ⅰ. Dissolve polyvinylidene fluoride completely in DMF solvent, the mass volume ratio of polyvinylidene fluoride to DMF is (0.25-0.27) g / ml; II. Add MXene powder to the above solution and stir until the MXene powder is evenly dispersed; the mass ratio of MXene powder to polyvinylidene fluoride is 1:(38-40); III. Using a syringe to take the mixed solution for electrospinning, and drying the obtained electrospun membrane to obtain a PVDF / Ti3C2Tx film; IV. Placing a patterned interdigital electrode mask on a PVDF / Ti3C2Tx film and fixing it on a magnetron sputtering substrate; sputtering a silver target using a DC magnetron sputtering technique to ultimately obtain an Ag / PVDF / Ti3C2Tx nanofiber film with patterned interdigital silver electrodes; S3. The M-PPT organic hydrogel prepared in step S1 is stacked with the Ag / PVDF / Ti3C2Tx nanofiber membrane to form a complete flexible multimodal hydrogel sensing patch.

2. The method for preparing a flexible multimodal hydrogel sensor patch according to claim 1, characterized in that: The preparation method of MXene is as follows: Add 75% concentrated hydrochloric acid and lithium fluoride to water and stir to mix; add Ti3AlC2 under stirring, heat in a (40-50)°C water bath, and stir at (1000-1200) r / min for (22-24) hours to obtain a MXene etching solution; centrifuge the MXene etching solution to obtain a multilayer MXene precipitate, mix it with deionized water, and freeze-dry to obtain a multilayer MXene powder; wherein the mass ratio of concentrated hydrochloric acid, lithium fluoride, and Ti3AlC2 is (19-20):(1.8-1.7):(1.3-1.4).

3. The method for preparing a flexible multimodal hydrogel sensor patch according to claim 1, characterized in that: The preparation method of the spherical microstructure mold is as follows: A rectangular column with a size of 1.8 cm × 1.5 cm × 0.5 cm was designed, and multiple spheres with a radius of 250 μm were arranged on the top surface of the rectangular column; A mold is made by 3D printing using an ultraviolet photosensitive resin material, and the mold surface is cleaned and then cured using ultraviolet light; polydimethylsiloxane is prepared, and a curing agent and a base monomer are fully mixed in a mass ratio of 10:1; the mixture is poured into the printed mold, vacuum degassed at room temperature for 15-20 minutes, and then completely cured at (70-80)°C for 2-3 hours, and peeled off to obtain a mold with a recessed spherical microstructure.

4. The method for preparing a flexible multimodal hydrogel sensor patch according to claim 1, characterized in that: The electrospinning was set with an extrusion speed of (0.6-0.7) mm / min, a collection distance of (80-85) mm, a spinning time of (2-2.5) hours, and a spinning voltage of (18-20) kV.

5. The method for preparing a flexible multimodal hydrogel sensor patch according to claim 1, characterized in that: The experimental conditions of DC magnetron sputtering are: oxygen flow rate of 20-22 L / min, pressure of (2-3) Pa, power of (80-82) W, and sputtering time of (15-17) minutes.

6. A flexible multimodal hydrogel sensor patch prepared by the preparation method according to any one of claims 1 to 5.

7. Use of the flexible multimodal hydrogel sensor patch according to claim 6 in sleep monitoring.

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