Wearable sensing multi-component sweat sensing patch, preparation method thereof and intelligent detection system

Abstract

The present application relates to the technical field of sensing detection, and particularly relates to a wearable sensing type multi-component sweat sensing patch, a preparation method thereof and an intelligent detection system. The wearable sensing type multi-component sweat sensing patch comprises an epidermal contact layer, a thermal stimulation layer, a microfluidic channel, a sensing layer and a breathable packaging layer. The sensing layer is arranged at one end of the microfluidic channel and comprises four independent chambers, which respectively load different signal probes for color reaction with target substances in sweat. The present application drives directional transmission of sweat through capillary action and realizes synchronous detection of four target substances in sweat. Different signal probes are used to selectively bind calcium ions, potassium ions, uric acid and glucose. Molecular binding is converted into color signals through nanoparticle aggregation or indicator displacement. The thermal stimulation layer is used to optimize sweat generation and collection, improve calibration and signal stability of the sweat sensing patch, adapt to real-time monitoring requirements and have high sensitivity.

Description

Technical Field

[0001] This invention relates to the field of sensor technology, and in particular to a wearable multi-component sweat sensor patch, its preparation method, and an intelligent detection system. Background Technology

[0002] Currently, commercial wearable devices (such as smartwatches and health bracelets) integrate high-precision micro sensors to achieve continuous dynamic monitoring of physiological parameters such as body temperature, heart rate, and blood oxygen saturation. They then use algorithmic models to transform these physical signals into a visual representation of health status. These devices, through non-invasive detection methods, have successfully built a real-time monitoring network for basic human physiological indicators, providing crucial technical support for cardiovascular health assessment, motor function analysis, and other scenarios.

[0003] Due to the complexity and multidimensionality of various diseases, deeper, multi-dimensional information at the molecular level is needed before using wearable sensors for disease monitoring. Sweat, as a biofluid rich in multidimensional molecular information such as electrolytes, metabolites, hormones, and proteins, provides a unique window for non-invasive, continuous monitoring of human biochemical dynamics. However, current wearable sensing technologies for sweat analysis still face several bottlenecks: First, sweat molecular signals exhibit high individual variability and dynamic fluctuations (such as changes in pH and ion concentration gradients), making it difficult to adapt sensor calibration and signal stability to real-time monitoring requirements; second, the precise capture of low-abundance target molecules (such as picomolar cortisol and micromolar glucose) places extremely high demands on sensor sensitivity and selectivity, and existing electrochemical and optical sensing materials are easily interfered with by the complex matrix of sweat; third, the contradiction between device miniaturization and comfort is prominent, and the integration of high-precision multi-channel detection modules often sacrifices breathability and long-term fit, limiting the continuous acquisition of clinical-grade data.

[0004] Therefore, existing technologies still need to be improved and developed. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a wearable multi-component sweat sensor patch and its preparation method and intelligent detection system, which aims to solve the problems that the calibration and signal stability of existing sweat sensor patches are difficult to adapt to the real-time monitoring requirements and that the sensitivity is low.

[0006] The technical solution of the present invention is as follows:

[0007] A wearable, multi-component sweat-sensing patch includes:

[0008] The epidermal contact layer is used for contact with the skin surface;

[0009] A heat-stimulating layer is disposed on one side of the epidermal contact layer;

[0010] Microfluidic channels are disposed on one side of the epidermal contact layer and are in the same layer as the thermal stimulation layer;

[0011] A sensing layer is disposed at one end of the microfluidic channel; the sensing layer includes four independent chambers, each of which is loaded with a different signal probe for colorimetric reaction with a target in sweat.

[0012] A breathable encapsulation layer is bonded to the epidermal contact layer; the thermal stimulation layer, the microfluidic channel, and the sensing layer are sandwiched between the epidermal contact layer and the breathable encapsulation layer.

[0013] The wearable, multi-component sweat-sensing patch includes calcium ions, potassium ions, uric acid, and glucose as its target components.

[0014] The wearable, multi-component sweat-sensing patch includes a calcium ion recognition probe, a potassium ion recognition probe, a uric acid recognition probe, and a glucose recognition probe. The calcium ion recognition probe is a naphthalimide modified with azacrown ether. The potassium ion recognition probe is gold nanoparticles modified with 4'-aminodibenzo-18-crown-6. The uric acid recognition probe is a complex of a water-soluble naphthyltetralactam macrocyclic compound and a phenolazine dye halogen. The glucose recognition probe is a chitosan composite material loaded with silver nanoparticles.

[0015] The wearable multi-component sweat sensor patch, wherein the material of the epidermal contact layer and the breathable encapsulation layer is selected from polyethylene terephthalate, thermoplastic polyurethane, and polydimethylsiloxane; the epidermal contact layer and the breathable encapsulation layer are provided with through holes with a pore size of 1.0mm-1.4mm.

[0016] The wearable, multi-component sweat-sensing patch includes a thermal stimulation layer comprising a first arc-shaped thermal stimulation chamber and a second arc-shaped thermal stimulation chamber arranged symmetrically; the microfluidic channel and the sensing layer are located between the first arc-shaped thermal stimulation chamber and the second arc-shaped thermal stimulation chamber.

[0017] The wearable multi-component sweat sensor patch, wherein the microfluidic channel has a trapezoidal cross-section in the thickness direction of the wearable multi-component sweat sensor patch.

[0018] A method for preparing a wearable, multi-component sweat-sensing patch includes the following steps:

[0019] The epidermal contact film is subjected to plasma treatment to obtain the epidermal contact layer;

[0020] A heat-stimulating material is injected into a mold on one side of the epidermal contact layer to obtain a heat-stimulating layer;

[0021] A tree-like fractal channel network is formed on the skin contact layer using printing and demolding processes to obtain microfluidic channels;

[0022] A signal probe is synthesized in situ at one end of the microfluidic channel to form a sensing layer with four independent chambers;

[0023] A wearable, multi-component sweat-sensing patch is prepared by covering the heat-stimulating layer, the microfluidic channel, and the sensing layer with a breathable encapsulation film and bonding it to the epidermal contact layer.

[0024] The method for preparing the wearable sensing multi-component sweat sensing patch, wherein the signal probes include calcium ion recognition probes, potassium ion recognition probes, uric acid recognition probes, and glucose recognition probes;

[0025] The preparation steps of the calcium ion recognition probe include: mixing and grinding dibromo-substituted naphthalimide and azacrown ether under the catalysis of anhydrous potassium carbonate and copper sulfate, and then heating the mixture under solvent-free conditions to obtain the calcium ion recognition probe.

[0026] The preparation steps of the potassium ion recognition probe include: preparing gold nanoparticles by sodium citrate reduction, and then modifying the gold nanoparticles with 4'-aminodibenzo-18-crown-6 to obtain the potassium ion recognition probe.

[0027] The method for preparing the wearable, multi-component sweat-sensing patch, wherein the uric acid recognition probe is a complex of a water-soluble naphthyltetralactam macrocyclic compound and a phenolic dye halogen; the preparation method of the complex of the water-soluble naphthyltetralactam macrocyclic compound and the phenolic dye halogen includes the following steps:

[0028] 2,6-Dihydroxynaphthalene and trimesic acid were mixed and an intermediate was constructed by bromoethane substitution, paraformaldehyde bridging and amination reactions.

[0029] Using the intermediate, a pseudo-high dilution method was employed to achieve a cyclization reaction between the diester and the diamine in dichloromethane, forming a rigid framework with 2,6-diethoxynaphthalene as hydrophobic sidewalls and four lactam bonds as polar sites.

[0030] The rigid skeleton was hydrolyzed with trifluoroacetic acid and alkalized to introduce a hydrophilic group from sodium carboxylate, yielding a water-soluble naphthyltetralactam macrocyclic compound.

[0031] The water-soluble naphthyltetralactam macrocyclic compound was subjected to an indicator displacement reaction with the phenolazine dye halogen to obtain a complex.

[0032] A wearable, sensor-based, multi-component sweat intelligent detection system includes:

[0033] Wearable multi-component sweat sensor patch;

[0034] The signal acquisition unit is used to acquire the color spectrum of the sensing layer on the wearable multi-component sweat sensing patch to form a basic dataset.

[0035] The data augmentation unit is used to augment the basic dataset to form an augmented dataset;

[0036] The machine learning analysis unit is used to train the system using the augmented dataset and output sweat detection results based on the color spectrum acquired by the signal acquisition unit.

[0037] Beneficial Effects: This invention provides a wearable multi-component sweat sensor patch and its preparation method, as well as an intelligent detection system. The wearable multi-component sweat sensor patch includes: an epidermal contact layer for contact with the skin surface; a thermal stimulation layer disposed on one side of the epidermal contact layer; a microfluidic channel disposed on one side of the epidermal contact layer and in the same layer as the thermal stimulation layer; a sensing layer disposed at one end of the microfluidic channel; the sensing layer includes four independent chambers, each of which is loaded with a different signal probe for colorimetric reaction with a target in sweat; and a breathable encapsulation layer adhered to the epidermal contact layer; the thermal stimulation layer, the microfluidic channel, and the sensing layer are sandwiched between the epidermal contact layer and the breathable encapsulation layer. This invention utilizes capillary action to drive the directional transport of sweat and achieve simultaneous detection of four target substances in sweat. The sensing layer employs different signal probes to selectively bind to calcium ions, potassium ions, uric acid, and glucose. This molecular binding is converted into color signals through nanoparticle aggregation or indicator displacement. Simultaneously, a thermal stimulation layer optimizes sweat generation and collection, improving the calibration and signal stability of the sweat sensing patch, making it suitable for real-time monitoring and exhibiting high sensitivity. Furthermore, this sweat sensing patch can combine signal acquisition, data amplification, and machine learning to achieve electronically component-free, highly selective multi-index analysis of sweat. This sweat sensing patch is suitable for metabolic monitoring, sports medicine, and chronic disease management. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the overall structure of a wearable multi-component sweat sensing patch according to the present invention.

[0039] Figure 2 This is an exploded structural diagram of a wearable multi-component sweat sensing patch according to the present invention.

[0040] Figure 3 This is a schematic diagram illustrating the principle of a calcium ion recognition probe.

[0041] Figure 4 This is a schematic diagram illustrating the principle of a potassium ion recognition probe.

[0042] Figure 5 This is a schematic diagram illustrating the principle of a uric acid recognition probe.

[0043] Figure 6 The image shows the sensing effect of the calcium ion sensor, potassium ion sensor, and uric acid sensor in Example 1.

[0044] Figure 7 These are scanning electron microscope images of the analyte before and after it is combined with body 1, body 2 and body 3 in Example 1;

[0045] Figure 8 A schematic diagram for calculating non-covalent interaction forces between the subject and object using DFT;

[0046] Figure 9 This image shows the effect of a wearable, multi-component sweat sensor patch in the detection of sweat biomarkers.

[0047] Figure 10 A diagram showing the confusion matrix results when integrated with the K-NN classification algorithm;

[0048] Figure 11 Synthetic pathway diagram for water-soluble naphthyltetralactam macrocyclic compounds;

[0049] Figure 12 This is a graph showing the results of selective validation.

[0050] Explanation of reference numerals in the attached diagram: Epidermal contact layer 10, thermal stimulation layer 20, microfluidic channel 30, sensing layer 40, breathable encapsulation layer 50, skin surface 100. Detailed Implementation

[0051] This invention provides a wearable, multi-component sweat sensor patch, its preparation method, and an intelligent detection system. To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention is further described in detail below. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0052] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0053] like Figure 1and Figure 2 As shown, the present invention provides a wearable multi-component sweat sensing patch, comprising:

[0054] Epidermal contact layer 10, for contact with skin surface 100;

[0055] A heat stimulation layer 20 is disposed on one side of the epidermal contact layer 10;

[0056] The microfluidic channel 30 is disposed on one side of the epidermal contact layer 10 and is in the same layer as the thermal stimulation layer 20;

[0057] A sensing layer 40 is disposed at one end of the microfluidic channel 30; the sensing layer 40 includes four independent chambers, each of which is loaded with a different signal probe for colorimetric reaction with a target in sweat.

[0058] A breathable encapsulation layer 50 is attached to the epidermal contact layer; the thermal stimulation layer, the microfluidic channel, and the sensing layer are sandwiched between the epidermal contact layer and the breathable encapsulation layer.

[0059] In this embodiment, capillary action drives the directional transmission of sweat and enables the simultaneous detection of four target substances in sweat. The sensing layer employs different signal probes to selectively bind to calcium ions, potassium ions, uric acid (UA), and glucose (Glu). This molecular binding is converted into color signals through nanoparticle aggregation or indicator displacement. Simultaneously, a thermal stimulation layer optimizes sweat generation and collection, improving the calibration and signal stability of the sweat sensing patch, making it suitable for real-time monitoring and exhibiting high sensitivity. Furthermore, this sweat sensing patch can combine signal acquisition, data amplification, and machine learning to achieve electronically component-free, highly selective multi-index analysis of sweat. This sweat sensing patch is suitable for metabolic monitoring, sports medicine, and chronic disease management.

[0060] Specifically, the wearable multi-component sweat sensor patch achieves a color reaction of target substances in sweat through the synergistic effect of microfluidic design, thermal stimulation of sweating, and supramolecular precise recognition. By utilizing the color signals generated by the reaction between different signal probes loaded on four independent chambers on the sensing layer and the target substances, the concentration of target substances in sweat can be monitored in real time with high sensitivity. It exhibits advantages of high sensitivity, strong anti-interference, and multi-mode detection compatibility in fields such as environmental pollutant monitoring and biomarker sensing.

[0061] In some embodiments, the target substances include calcium ions, potassium ions, uric acid, and glucose. Calcium ions, potassium ions, uric acid, and glucose are important indicators of metabolites. Real-time monitoring of calcium ions, potassium ions, uric acid, and glucose in sweat via a sweat sensor patch can improve the monitoring of target substances.

[0062] In some embodiments, the signal probes include calcium ion recognition probes, potassium ion recognition probes, uric acid recognition probes, and glucose recognition probes; the calcium ion recognition probe is a naphthalimide modified with azacrown ether; the potassium ion recognition probe is gold nanoparticles modified with 4'-aminodibenzo-18-crown-6; the uric acid recognition probe is a mixture of a water-soluble naphthyltetralactam macrocyclic compound and the phenolazine dye halogen; and the glucose recognition probe is a chitosan composite material loaded with silver nanoparticles.

[0063] Specifically, each of the four independent chambers carries a different macrocyclic host. The supramolecular macrocyclic host, with its pre-organized cavity structure and multiple non-covalent bond synergies (including hydrogen bonds, hydrophobic effects, and ion-dipole interactions), can achieve highly selective recognition and binding of target ions / molecules. Furthermore, through the entropy-enthalpy synergy effect in the host-guest complexation process, it enriches the target in sweat, significantly increasing the local concentration of the target and thus overcoming the sensitivity bottleneck of traditional detection methods. Based on this, by modularly modifying the molecular framework and constructing composite systems with functional nanomaterials (such as gold nanoparticles) and signal probe molecules (such as fluorescent dyes and electroactive molecules), the coupling efficiency of molecular recognition and signal transduction can be directionally controlled, triggering visual / spectral detection signal output based on colorimetric reactions, fluorescence quenching / enhancement, or localized surface plasmon resonance effects.

[0064] In some embodiments, the target may include, but is not limited to, cortisol and creatinine, in which case the signal probe is replaced by a cortisol recognition probe and a creatinine recognition probe; the cortisol recognition probe and the creatinine recognition probe are respectively cucurbituril or sulfonated calixarene.

[0065] In some embodiments, the material of the epidermal contact layer and the breathable encapsulation layer is selected from polyethylene terephthalate (PET), thermoplastic polyurethane (TPU), and polydimethylsiloxane (PDMS); the epidermal contact layer and the breathable encapsulation layer are provided with through holes with a pore size of 1.0 mm-1.4 mm. The material selection of the epidermal contact layer and the breathable encapsulation layer takes into account biocompatibility, flexibility, breathability, and compatibility with microfluidic structures. Similar materials include hydrogel composite materials, polylactic acid (PLA) modified materials, etc. Preferably, the pore size of the through holes is 1.2 mm ± 10%.

[0066] In some embodiments, the thermal stimulation layer includes a first arc-shaped thermal stimulation chamber and a second arc-shaped thermal stimulation chamber arranged symmetrically; the microfluidic channel and the sensing layer are located between the first arc-shaped thermal stimulation chamber and the second arc-shaped thermal stimulation chamber.

[0067] Specifically, the concave portions of the first and second arc-shaped thermal stimulation chambers are positioned opposite each other, forming an asymmetric thermal field (40-45℃ gradient) through the difference in curvature, which both directionally activates sweat glands and inhibits edge heat diffusion.

[0068] In some embodiments, the heat-stimulated layer is prepared by mixing 60-85 wt% iron powder, 10-30 wt% activated carbon, and 2-15 wt% sodium chloride to form an iron-based composite by weight percentage; preferably, the particle size of the iron powder is between 200-400 mesh. The iron-based composite obtained by mixing the components by weight percentage is continuously oxidized in an air environment (RH=60%), with the temperature rising to 38±2℃ within 30 minutes and maintained for more than 6 hours.

[0069] Specifically, the heat stimulation layer adjusts the reaction rate by adjusting the NaCl content, controlling the temperature between 30-45℃; and the double-arc layout of the heat stimulation layer can ensure uniform heat distribution (epidermal temperature difference less than 1.5℃), avoiding localized burns.

[0070] In some implementations, various inorganic composite materials based on redox exothermic reactions can be used as alternative heat sources for iron-based micro powder mixtures in the construction of self-heating material systems; specifically, calcium compounds (such as calcium oxide and calcium hydroxide), magnesium-iron composite metal powders, aluminum-activated quicklime mixtures, and transition metal oxide composite systems (such as the MnO2-CuO-Fe3O4 ternary system) can be selected.

[0071] In some embodiments, the microfluidic channel has a trapezoidal cross-section in the thickness direction of the wearable, multi-component sweat-sensing patch. Using a trapezoidal microfluidic channel optimizes capillary flow rate.

[0072] In a preferred embodiment, the microfluidic channel has a trapezoidal cross-section with a top width of 0.1 mm, a bottom width of 0.15 mm, and a depth of 0.6 mm. This size of microfluidic channel has a fast capillary flow rate, driving sweat to complete directional transmission to the sensing layer within 6 minutes.

[0073] In some embodiments, the epidermal contact layer 10 is provided with a sweat inlet 11 corresponding to the independent chamber, for delivering sweat from the skin surface to each independent chamber; the breathable sealing layer 50 is provided with a sweat outlet 51 for discharging the remaining sweat after detection in the independent chamber; specifically, sweat from the skin surface enters the independent chamber through the sweat inlet 11, and the remaining sweat is discharged from the sweat outlet 51 through the microfluidic channel.

[0074] In addition, the present invention also provides a method for preparing a wearable, multi-component sweat-sensing patch, comprising the following steps:

[0075] Step S10: Perform plasma treatment on the epidermal contact film to obtain the epidermal contact layer;

[0076] Step S20: Inject the heat-stimulating material into the mold on one side of the epidermal contact layer to obtain the heat-stimulating layer;

[0077] Step S30: A tree-like fractal channel network is formed on the skin contact layer using a printing and demolding process to obtain microfluidic channels;

[0078] Step S40: Synthesize a signal probe in situ at one end of the microfluidic channel to form a sensing layer with four independent chambers;

[0079] Step S50: Cover the heat stimulation layer, the microfluidic channel and the sensing layer with a breathable encapsulation film and attach it to the epidermal contact layer to obtain a wearable sensing multi-component sweat sensing patch.

[0080] In this embodiment, the wearable multi-component sweat sensor patch prepared by this method can drive the directional transmission of sweat through capillary action and achieve simultaneous detection of four target substances in sweat. The sensing layer uses different signal probes to selectively bind calcium ions, potassium ions, uric acid, and glucose. The molecular binding is converted into color signals through nanoparticle aggregation or indicator replacement. At the same time, the thermal stimulation layer optimizes sweat generation and collection, improves the calibration and signal stability of the sweat sensor patch, and makes it suitable for real-time monitoring needs with high sensitivity.

[0081] In some embodiments, the plasma treatment has a power of 30W and a duration of 30s; after plasma treatment, the contact angle of the epidermal contact membrane can be reduced from 110° to less than 10°, promoting capillary absorption of sweat.

[0082] In some embodiments, in step S30, a tree-like fractal channel network is formed by 3D printing a resin mold, then filling it with PDMS, and finally demolding to obtain a microfluidic channel.

[0083] This invention employs precision surface projection micro-stereolithography (PμSL) 3D printing technology to prepare a high-resolution resin master mold, combined with a polydimethylsiloxane (PDMS) casting process to construct microfluidic channels with precise microstructures. Specific steps include: preparing a master mold using biocompatible polymethyl methacrylate (PMA) resin via 3D printing; mixing a PDMS matrix and a curing agent in a specific ratio, degassing under vacuum, and then pouring the mixture onto the surface of the master mold; curing by heating to form a PDMS layer; and finally, demolding to obtain a clearly structured microfluidic channel. This method offers a simple, low-cost, and highly reproducible fabrication process, making it suitable for the rapid manufacturing and personalized design of flexible wearable devices.

[0084] In some embodiments, the signal probe includes a calcium ion recognition probe, a potassium ion recognition probe, a uric acid recognition probe, and a glucose recognition probe.

[0085] In some embodiments, the preparation steps of the calcium ion recognition probe include: mixing and grinding dibromo-substituted naphthalimide and azacrown ether under the catalysis of anhydrous potassium carbonate and copper sulfate, followed by heating reaction under solvent-free conditions to obtain the calcium ion recognition probe.

[0086] Specifically, the schematic diagram of the calcium ion recognition probe is as follows: Figure 3 As shown, it affects Ca 2+ The selectively recognized macrocyclic host is an azacrown ether (host 1), which interacts with Ca 2+ The binding constant K a It is 9.1×10 6 M -1 The macrocyclic body is readily available for purchase; CAS number 33941-15-0, manufacturer: Aladdin, product number: A151566. The macrocyclic body alone is colorless; it is modified by adding Ca... 2+ No color change was subsequently observed; this invention synthesizes Ca via a copper-catalyzed nucleophilic aromatic substitution (SNAr) reaction. 2+ The sensing system specifically includes the following steps: heating dibromonaphthalene diimide (Br2-cNDI), 1-aza-18-crown-6-ether, anhydrous K2CO3, and CuSO4 powder at 100-120℃ for 6 hours under solvent-free conditions, utilizing Cu... + The nucleophilicity of the activated crown ether amino group selectively substitutes the dibromo site of the naphthalimide. K₂CO₃ acts as a base to capture HBr to drive the reaction equilibrium. The crude product is purified by silica gel column chromatography (dichloromethane to methanol, volume ratio 98:2) to give a blue solid (yield 31.9%). This probe exhibits activity towards Ca. 2+ Specific "turn-on" fluorescence response: addition of Ca 2+ Subsequently, the ultraviolet absorption peak shifted 60 nm from 580 nm to 520 nm, and the color changed from purple to reddish-brown.

[0087] In some embodiments, the preparation steps of the potassium ion recognition probe include: preparing gold nanoparticles by sodium citrate reduction, and then modifying the gold nanoparticles with 4'-aminodibenzo-18-crown-6 to obtain the potassium ion recognition probe.

[0088] Specifically, the schematic diagram of the potassium ion recognition probe is as follows: Figure 4 As shown, it is related to K + The selectively recognized macrocyclic host is 4'-aminodibenzo-18-crown-6 (host 2), which interacts with K + The binding constant K aIt is 5.1×10 3 M -1 The macrocyclic main body is readily available for purchase; CAS number 126531-26-8, manufacturer: Shanghai Mairui, catalog number: M62601. This potassium ion recognition probe is synthesized into approximately 18 nm gold nanoparticles (AuNPs) via sodium citrate reduction. Individual AuNPs are then added to K... + It does not produce a color change; the color remains wine-red. However, it utilizes the amino group of 4-aminobenzo-18-crown-6 to modify the surface of AuNPs via Au-N bonds. When K + In the presence of K, the crown ether cavity of 4'-aminodibenzo-18-crown-6 interacts with K + The specific binding forms a 2:1 sandwich complex, which triggers AuNP aggregation, causing the solution color to change from wine red to grayish blue, accompanied by a red shift of the surface plasmon resonance absorption peak from 520 nm to 630 nm.

[0089] In some embodiments, the uric acid recognition probe is a mixture of a water-soluble naphthyltetralactam macrocyclic compound and a phenolazine dye, halogen; the preparation method of the water-soluble naphthyltetralactam macrocyclic compound includes the following steps:

[0090] Step S1: Mix 2,6-dihydroxynaphthalene and trimesic acid, and construct an intermediate through bromoethane substitution, paraformaldehyde bridging and amination reactions;

[0091] Step S2: Using the intermediate, a pseudo-high dilution method is used to realize the cyclization reaction between the diester and the diamine in dichloromethane, forming a rigid framework with 2,6-diethoxynaphthalene as hydrophobic sidewalls and four lactam bonds as polar sites.

[0092] Step S3: The rigid skeleton is hydrolyzed with trifluoroacetic acid to introduce a hydrophilic group of sodium carboxylate and alkalized to obtain a water-soluble naphthyltetralactam macrocyclic compound;

[0093] Step S4: The water-soluble naphthyltetralactam macrocyclic compound is subjected to an indicator displacement reaction with the phenolazine dye halogen to obtain a complex.

[0094] Specifically, the schematic diagram of the uric acid recognition probe is as follows: Figure 5 As shown, the macrocyclic host for selective recognition of uric acid (UA) is a water-soluble naphthyltetralactam macrocyclic compound (host 3), and its binding constant with UA is K. a 1.7×10 5 M -1The synthesis of water-soluble naphthyltetralactam macrocyclic compounds begins with 2,6-dihydroxynaphthalene and trimesic acid as starting materials. Intermediates are constructed through bromoethane substitution, paraformaldehyde bridging, and amination reactions. A pseudo-high dilution method is used to achieve a [2+2] ring-closing reaction between the diester and the diamine in dichloromethane, forming a rigid framework with 2,6-dihydroxynaphthalene as the hydrophobic sidewall and four polar lactam bond sites. Subsequently, the ester group is hydrolyzed by trifluoroacetic acid and a hydrophilic sodium carboxylate group is introduced, ultimately yielding a biomimetic macrocycle with both deep hydrophobic cavities and water solubility, namely, a water-soluble naphthyltetralactam macrocyclic compound.

[0095] In this embodiment, the water-soluble naphthyltetralactam macrocyclic compound achieves the detection of UA through supramolecular non-covalent interactions. This water-soluble naphthyltetralactam macrocyclic compound can selectively bind to uric acid and form a complex (K) with the phenolazine dye halogen (RF) based on an indicator displacement mechanism. a 4.6×10 4 M -1 The solution color changes from pink to blue; when uric acid is present, it competitively displaces RF, causing the solution color to return to pink (40nm redshift).

[0096] In some embodiments, the chitosan composite material (CS / Ag NCs) loaded with silver nanoparticles is synthesized by a chemical reduction method, in which chitosan is used as both a reducing agent and a stabilizer. Silver nitrate is reduced to silver nanoparticles at 90°C and uniformly loaded onto the chitosan matrix to obtain the chitosan composite material (CS / Ag NCs) loaded with silver nanoparticles.

[0097] Specifically, the composite material CS / Ag NCs exhibits a typical surface plasmon resonance peak (429 nm) on the surface of silver nanoparticles. Its colorimetric sensing mechanism is based on the interaction between glucose molecules and silver nanoparticles: glucose adsorption leads to the aggregation of silver nanoparticles, causing a decrease in the SPR peak intensity and accompanied by a change in solution color from yellow to grayish-purple. This sensor can achieve visual detection of glucose without enzyme catalysis, demonstrating advantages such as low cost, simple operation, and non-enzyme dependence, providing a feasible solution for the development of novel enzyme-free glucose sensors.

[0098] In addition, the present invention also provides a wearable sensing multi-component sweat intelligent detection system, comprising:

[0099] Wearable multi-component sweat sensor patch;

[0100] The signal acquisition unit is used to acquire the color spectrum of the sensing layer on the wearable multi-component sweat sensing patch to form a basic dataset.

[0101] The data augmentation unit is used to augment the basic dataset to form an augmented dataset;

[0102] The machine learning analysis unit is used to train the system using the augmented dataset and output sweat detection results based on the color spectrum acquired by the signal acquisition unit.

[0103] In this embodiment, the color spectra of calcium ions, potassium ions, uric acid (UA), and glucose (Glu) after reacting with the sensing layer are obtained using a signal acquisition unit, forming the basic dataset for machine learning. Simultaneously, to mitigate the inherent overfitting risk of a limited sample size, a data augmentation unit amplifies the basic dataset to obtain an augmented dataset. This avoids the randomness defects of traditional noise injection and overcomes the limitations of SMOTE (Synthetic Minority Over-sampling Technique) for high-dimensional data, making it suitable for machine learning optimization of multi-channel optical signals in wearable devices. Finally, a machine learning analysis unit trains the augmented dataset to form a machine learning model, which then outputs sweat detection results based on the color spectra acquired by the signal acquisition unit. This intelligent detection system enables highly selective multi-index analysis of sweat without electronic components, and is suitable for metabolic monitoring, sports medicine, and chronic disease management.

[0104] In some implementations, after acquiring the color spectrum of the sensing layer on the wearable multi-component sweat sensing patch using a signal acquisition unit, the R / G / B values ​​of the color spectrum are extracted, and the RGB channel intensity of the color spectrum is normalized to percentage values ​​(R%, G%, B%) to construct a feature vector, thereby forming a basic dataset.

[0105] In some implementations, to mitigate the inherent risk of overfitting with a limited sample size, the base dataset is augmented by generating data through data variance, resulting in an augmented dataset that is 6-8 times larger.

[0106] In some implementations, after training the machine learning analysis unit using the augmented dataset, the KNN algorithm (k=10, Euclidean distance) is used for 5-fold cross-validation to optimize classification accuracy. Ultimately, the classification accuracy for calcium ions is 100% (0-10mM, 6 concentration gradients), potassium ions are 97.2% (0-15mM), uric acid is 87.2% (0-250μM), and glucose is 100% (0-250μM). Combined with the K-nearest neighbor algorithm to process smartphone RGB signals (87-98% classification accuracy), this enables highly selective, electronically-free analysis of multiple sweat indicators. This intelligent detection method is suitable for metabolic monitoring, sports medicine, and chronic disease management.

[0107] The following examples further illustrate the present invention in detail. It should also be understood that the following examples are only for further explanation of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-essential improvements and adjustments made by those skilled in the art based on the above description of the present invention are within the scope of protection of the present invention.

[0108] Example 1

[0109] This embodiment provides a wearable, sensor-based, multi-component sweat intelligent detection system, the preparation of which includes the following steps:

[0110] 1. Preparation of wearable multi-component sweat sensor patch

[0111] Epidermal contact layer: A 0.5mm thick PET film with a pore size of 1.2mm±10% is used. The contact angle is reduced from 110° to <10° by plasma treatment (50W, 30s), which promotes the capillary absorption of sweat.

[0112] Heat-stimulated layer: Iron powder (200-400 mesh, 70wt%), activated carbon (20wt%) and NaCl (10wt%) are mixed by mass percentage to form an iron-based composite, which is then injected into a mold to form a double-arc heat-stimulated layer.

[0113] Microfluidic channels: A resin mold is printed on the side of the epidermal contact layer near the heat stimulation layer using 3D printing, located between the two arcs of the double-arc heat stimulation layer. Then, PDMS is poured into the resin mold and the mold is demolded to form a tree-like fractal channel network. The channel cross-section is trapezoidal (top width 0.1mm, bottom width 0.15mm, depth 0.6mm).

[0114] The sensing layer includes the following:

[0115] 1) Synthesis of a calcium ion sensor (containing a chamber with a calcium ion recognition probe): Dibromo-substituted naphthalenediimide (Br2-cNDI) was mixed and ground with excess 1-aza-18-crown-6 ether under the catalysis of anhydrous potassium carbonate (K2CO3) and copper sulfate (CuSO4). The mixture was heated at 120°C for 6 hours without solvent. After the reaction, the product was purified by column chromatography (CH2Cl2:MeOH=98:2) to obtain a purple solid product with a yield of approximately 30%. This reaction introduces two aza-crown ether groups into the core of the naphthalenediimide through nucleophilic substitution, forming a bisubstituted structure, namely aza-crown ether-modified naphthalenediimide, in which the macrocyclic host is aza-crown ether (host 1).

[0116] Signaling mechanism: Azacrown ether modified naphthalimide on Ca 2+ The sensing mechanism is based on the suppression of the photoinduced electron transfer (PET) effect. When Ca 2+When it binds to the azacrown ether acceptor in the probe, the lone pair electrons of the crown ether are converted by Ca. 2+ Coordination binding blocks the electron transfer process from the crown ether to the naphthalimide (NDI) fluorophore, thereby relieving fluorescence quenching (PET-OFF) and inducing a significant fluorescence enhancement ("turn-on" effect). DFT calculations show that Ca... 2+ It forms a 1:2 complex with azacrown ether, and cyclic voltammetry shows that Ca 2+ The combination of these factors resulted in a positive shift in the NDI reduction potential, confirming the alteration of the electronic structure. This process exhibits high selectivity and reversibility, enabling naked-eye detection of calcium ions through synergistic crown ether coordination with the optical response of the NDI fluorophore.

[0117] Selective validation results as follows Figure 12 As shown: In the presence of interfering ions at 10 times the concentration or other small molecules in sweat, Ca 2+ Response signal deviation <5%.

[0118] 2) Synthesis of a potassium ion sensor (containing a chamber with a potassium ion recognition probe): Gold nanoparticles (Au NPs) of approximately 18 nm were prepared via sodium citrate reduction. Subsequently, the Au NPs were modified by binding the amino group of 4'-aminodibenzo-18-crown-6 (body 2) to gold atoms on the surface via Au-N bonds, forming a well-dispersed functionalized nanoprobe. A solution of 4'-aminodibenzo-18-crown-6 modified Au NPs was finally obtained for subsequent K... + Colorimetric detection (H2 concentration 50 μM, modification time 2 h).

[0119] Signaling mechanism: Based on the ABC crown ether cavity in 4'-aminodibenzo-18-crown-6 and K + Size matching characteristics, K + Two ABC molecules can be specifically bound together through a "sandwich" structure (2:1 complex), leading to the aggregation of Au NPs. Aggregation causes a change in the localized surface plasmon resonance (SPR) absorption peak, manifested as a change in solution color from wine red to blue-gray, and a red shift of the LSPR peak of 120 nm (520→640 nm), enabling naked-eye colorimetric detection of potassium ions.

[0120] Selective validation results as follows Figure 12 As shown: In the presence of interfering ions at a concentration of 10 times or other small molecules in sweat, K + Response signal deviation <5%.

[0121] 3) Synthesis of a uric acid sensor (containing a chamber with a uric acid recognition probe): 2,6-dihydroxynaphthalene and trimesic acid were mixed, and an intermediate was constructed through bromoethane substitution, paraformaldehyde bridging, and amination. Using the intermediate, a diester and a diamine were cyclically closed in dichloromethane using a pseudo-high dilution method to form a rigid framework with 2,6-diethoxynaphthalene as hydrophobic sidewalls and four lactam bonds as polar sites. The rigid framework was hydrolyzed with trifluoroacetic acid and alkalized to introduce hydrophilic groups from sodium carboxylate, yielding a water-soluble naphthyltetralactam macrocyclic compound (body 3). The water-soluble naphthyltetralactam macrocyclic compound was subjected to an indicator substitution reaction with phenolazine dye halogen (RF) to obtain a complex.

[0122] Specifically, the synthesis steps are as follows: Figure 11 As shown:

[0123] (1) Compounds S1, S2 and S3 were prepared according to existing methods.

[0124] (2) Synthesis of compound S4: 2,6-dihydroxynaphthalene (16.0 g, 100 mmol), bromoethane (43.2 g, 400 mmol), potassium carbonate (69.0 g, 500 mmol), and N,N-dimethylformamide (DMF, 600 mL) were added to a 1 L three-necked round-bottom flask. The oil bath temperature was set at 80 °C, and the mixture was stirred for 10 hours under argon protection. After the reaction was completed, the mixture was cooled to room temperature, and most of the solvent was removed by rotary evaporation. The mixture was then poured into 400 mL of pure water and extracted multiple times with dichloromethane solvent. The organic phase was collected, dried with anhydrous sodium sulfate, and filtered. The dichloromethane solvent was removed by rotary evaporation, and the white solid S4 was finally obtained.

[0125] (3) Synthesis of compound S5: S4 (6.9 g, 32 mmol) and paraformaldehyde (5.7 g, 170 mmol) were added to a 250 mL three-necked round-bottom flask. 100 mL of hydrobromic acid / acetic acid solution (33 wt%) was drawn into the flask using a syringe and injected. The oil bath temperature was set to 50 °C, and the reaction was stirred for 5 hours under argon protection. The formation of a large amount of light purple solid indicated the end of the reaction. After the reaction system cooled to room temperature, it was filtered. The filter cake was washed repeatedly with a large amount of methanol to obtain the crude product. The crude product was dissolved in a small amount of dichloromethane and then added dropwise to 50 mL of methanol while sonicating. The precipitate formed was filtered and dried to obtain the white dibenzyl bromide compound S5.

[0126] (4) Synthesis of compound S6: S5 (4.1 g, 2.7 mmol), hexamethylenetetramine (HMTA, 4.0 g, 28 mmol), and chloroform (CHCl3, 150 mL) were added to a 250 mL three-necked round-bottom flask and refluxed for 48 hours under argon protection. After the reaction was completed, the reaction system was cooled to room temperature and the precipitate was collected by filtration. The dried filter cake was added to a 1 L round-bottom flask, 500 mL of ethanol solvent and 100 mL of concentrated hydrochloric acid were added, and the reaction was refluxed for 48 hours under argon protection. After the reaction was completed, the reaction system was cooled to 0 °C, filtered, and the filter cake was washed several times with cold ethanol solvent. The solid was added to sodium bicarbonate solution (2 M, 250 mL) and sonicated to form a suspension. The suspension was extracted with chloroform (600 mL) to obtain benzylamine; a small amount of chloroform was added to extract the remaining amine in the aqueous phase. The concentrated organic phase was collected and dried with anhydrous sodium sulfate. After filtration, the solvent was removed by rotary evaporation to obtain white dibenzylamine compound S6.

[0127] (5) Synthesis of compound S7: Bisbenzylamine compound S6 (274 mg, 1.5 mmol) and N,N-diisopropylethylamine (DIEA, mL) were added to a 1 L two-necked round-bottom flask. 500 mL of anhydrous dichloromethane was added to the round-bottom flask, stirred to dissolve, and the air in the flask was replaced with argon gas to ensure the entire system was under argon protection. Pentafluorophenol ester S3 (1.0 g, 1.0 mmol) was dissolved in 50 mL of anhydrous dichloromethane and slowly and uniformly injected into the round-bottom flask using a syringe pump. The entire injection process lasted for 30 hours. After the injection was completed, the reaction was allowed to continue for 24 hours. Most of the solvent was removed by rotary evaporation, and 100 mL of dichloromethane was added to dissolve the product. The product was washed several times with pure water and brine. The organic phase was collected and dried over anhydrous sodium sulfate. After filtration, most of the solvent in the filtrate was removed by rotary evaporation to obtain the crude product. The crude product was purified by column chromatography (dichloromethane:methanol = 100:1) to obtain the white solid product S7.

[0128] 6) Synthesis of host3: S7 (100 mg, 0.05 mmol) was added to a 50 mL three-necked round-bottom flask, followed by the addition of 50 mL anhydrous dichloromethane to dissolve it. 5 mL of trifluoroacetic acid was slowly added dropwise to the flask under ice bath conditions, and the reaction was then brought to room temperature for 3 hours. After the reaction was complete, the solvent was removed by rotary evaporation, and the solid was collected by filtration. The pH of the ultrapure water was adjusted to 5-6 with dilute hydrochloric acid, and the resulting solid was washed. The solid was then lyophilized to obtain a dry solid (100 mg, 0.05 mmol). The solid was dissolved in sodium hydroxide solution (100 mg, 0.05 mmol) and then lyophilized to obtain the tetralactam macrocyclic host3.

[0129] Signaling mechanism: Based on the indicator substitution effect (IDA), the binding affinity of UA to water-soluble naphthyltetralactam macrocyclic compounds (K...a =1.7×10 5 M -1 Significantly stronger than RF (K) a =4.08×10 4 M -1 When UA is present, it competitively displaces RF from the complex, causing the charge transfer (CT) effect to disappear and the solution color to revert from blue to pink (the absorption peak shifts from 600 nm to 571 nm). This signal change enables specific detection of UA through colorimetric analysis.

[0130] Selective validation results as follows Figure 12 As shown: In the presence of 10 times the concentration of interfering ions or other small molecules in sweat, the UA response signal deviation is <5%.

[0131] 4) Synthesis of glucose sensor (chamber containing glucose recognition probe): Using chitosan as both a reducing agent and a stabilizer, silver nitrate was reduced to silver nanoparticles at 90°C and uniformly loaded onto the chitosan matrix to obtain a chitosan composite material (CS / Ag NCs) loaded with silver nanoparticles.

[0132] Selective validation results as follows Figure 12 As shown: In the presence of 10 times the concentration of interfering ions or other small molecules in sweat, the glucose response signal deviation is <5%.

[0133] The sensing effects of calcium ion sensors, potassium ion sensors, and uric acid sensors are as follows: Figure 6 As shown, the original Br2-CNDI solution is colorless and reacts with Ca. 2+ No response. After grinding it together with host 1 (azacrown ether), a covalent complex was formed, yielding a blue-purple material. When Ca was added to it... 2+ At the saturation concentration (15 mM), the color gradually changes from purple to red. Similarly, when K... + After being conjugated with gold nanoparticles (AuNPs), the hybrid system retained its original reddish-brown color in the colloidal suspension, indicating that no significant plasmonic coupling occurred in the unconjugated state. However, when host 2 was introduced into the AuNP system, K... + The presence of K causes a noticeable color shift from red to blue. This response is likely due to the ability of subject 2 to selectively bind K. +Ions induce partial aggregation of AuNPs, leading to plasmonic resonant shift. Direct introduction of uric acid (UA) into a halogen (RF) dye solution failed to induce a detectable color change; the mixture retained its initial pink color. To overcome this limitation, an indicator displacement analysis (IDA) strategy was employed, utilizing a pre-assembled host-guest complex of host 3 and RF. This complex exhibits a stable blue color due to charge transfer interactions within the host cavity. Upon addition of UA, its competitive binding displaces RF from the macrocycle, restoring the pink color of the free dye.

[0134] Figure 7 The images show scanning electron microscope (SEM) images of the analyte before and after binding with host 1, host 2, and host 3. It can be seen that after the analyte binds with the macrocycle, it enters the cavity of the macrocycle, and the distance between ions or small molecules decreases, thus achieving the enrichment of the analyte.

[0135] To elucidate the supramolecular recognition mechanism, density functional theory (DFT) calculations were systematically performed (e.g., Figure 8 As shown in the figure, the geometric configurations of three subject-object systems were analyzed. Geometric optimization revealed different interaction modes: Ca 2+ K coordinates with the oxygen atom of the aza-crown ether (host 1) through ion-dipole interactions. + Encapsulated within an 18-corona-6-cavity (body 2) (also an ion-dipole interaction), uric acid (UA) binds to the tetralactam macrocycle (body 3) via synergistic π-π superposition and hydrogen bonding (NH···O; CH···O).

[0136] 2. Based on the wearable multi-component sweat sensor patch obtained in step 1, a wearable multi-component sweat intelligent detection system is prepared, specifically including:

[0137] A calibrated imaging system (ColorGrab) was used as the signal acquisition unit, and Ca was obtained. 2+ K + Color spectra of six concentration layers (UA, glucose, and alpha), with five replicates per layer (n=30 initial datasets). RGB channel intensities were normalized to percentage values ​​(R%, G%, B%) to construct feature vectors, forming the foundational dataset for machine learning (e.g., alpha, alpha, alpha, glucose). Figure 9 (As shown).

[0138] The data augmentation unit is used to generate data from the basic dataset (n=30) through data variance, and the basic dataset is augmented by 6 times (n=180) to form the augmented dataset.

[0139] The machine learning analysis unit was trained using an augmented dataset, and 5-fold cross-validation was performed using the KNN algorithm (k=10, Euclidean distance) to obtain the optimized classification accuracy. The results are as follows: Figure 10 As shown; it can be seen that Ca 2+ : 100% (0-10mM, 6 concentration gradient), K + : 97.2% (0-15mM), UA: 87.2% (0-250μM), Glu: 100% (0-250μM).

[0140] In summary, the present invention provides a wearable multi-component sweat sensor patch and its preparation method, as well as an intelligent detection system. The wearable multi-component sweat sensor patch includes: an epidermal contact layer for contact with the skin surface; a thermal stimulation layer disposed on one side of the epidermal contact layer; a microfluidic channel disposed on one side of the epidermal contact layer and in the same layer as the thermal stimulation layer; a sensing layer disposed at one end of the microfluidic channel; the sensing layer includes four independent chambers, each of which is loaded with a different signal probe for colorimetric reaction with a target in sweat; and a breathable encapsulation layer adhered to the epidermal contact layer; the thermal stimulation layer, the microfluidic channel, and the sensing layer are sandwiched between the epidermal contact layer and the breathable encapsulation layer. This invention utilizes capillary action to drive the directional transport of sweat and achieve simultaneous detection of four target substances in sweat. The sensing layer employs different signal probes to selectively bind to calcium ions, potassium ions, uric acid, and glucose. This molecular binding is converted into color signals through nanoparticle aggregation or indicator displacement. Simultaneously, a thermal stimulation layer optimizes sweat generation and collection, improving the calibration and signal stability of the sweat sensing patch, making it suitable for real-time monitoring and exhibiting high sensitivity. Furthermore, this sweat sensing patch can combine signal acquisition, data amplification, and machine learning to achieve electronically component-free, highly selective multi-index analysis of sweat. This sweat sensing patch is suitable for metabolic monitoring, sports medicine, and chronic disease management.

[0141] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A wearable, multi-component sweat-sensing patch, characterized in that, include: The epidermal contact layer is used for contact with the skin surface; A heat-stimulating layer is disposed on one side of the epidermal contact layer; Microfluidic channels are disposed on one side of the epidermal contact layer and are in the same layer as the thermal stimulation layer; A sensing layer is disposed at one end of the microfluidic channel; the sensing layer includes four independent chambers, each of which is loaded with a different signal probe for colorimetric reaction with a target in sweat. A breathable encapsulation layer is bonded to the epidermal contact layer; the thermal stimulation layer, the microfluidic channel, and the sensing layer are sandwiched between the epidermal contact layer and the breathable encapsulation layer; The targets include calcium ions, potassium ions, uric acid, and glucose; the signal probes include calcium ion recognition probes, potassium ion recognition probes, uric acid recognition probes, and glucose recognition probes; the calcium ion recognition probe is a naphthalimide modified with azacrown ether; the potassium ion recognition probe is gold nanoparticles modified with 4'-aminodibenzo-18-crown-6; the uric acid recognition probe is a complex of a water-soluble naphthyltetralactam macrocyclic compound and the phenolazine dye halogen; and the glucose recognition probe is a chitosan composite material loaded with silver nanoparticles.

2. The wearable multi-component sweat sensing patch according to claim 1, characterized in that, The material of the skin contact layer and the breathable sealing layer is selected from one of polyethylene terephthalate, thermoplastic polyurethane, and polydimethylsiloxane; the skin contact layer and the breathable sealing layer are provided with through holes with a diameter of 1.0mm-1.4mm.

3. The wearable multi-component sweat sensing patch according to claim 1, characterized in that, The thermal stimulation layer includes a first arc-shaped thermal stimulation chamber and a second arc-shaped thermal stimulation chamber arranged symmetrically; the microfluidic channel and the sensing layer are located between the first arc-shaped thermal stimulation chamber and the second arc-shaped thermal stimulation chamber.

4. The wearable multi-component sweat sensing patch according to claim 1, characterized in that, The microfluidic channel has a trapezoidal cross-section in the thickness direction of the wearable multi-component sweat sensor patch.

5. A method for preparing a wearable, multi-component sweat-sensing patch as described in any one of claims 1-4, characterized in that, Including the following steps: The epidermal contact film is subjected to plasma treatment to obtain the epidermal contact layer; A heat-stimulating material is injected into a mold on one side of the epidermal contact layer to obtain a heat-stimulating layer; A tree-like fractal channel network is formed on the skin contact layer using printing and demolding processes to obtain microfluidic channels; A signal probe is synthesized in situ at one end of the microfluidic channel to form a sensing layer with four independent chambers; A wearable, multi-component sweat-sensing patch is prepared by covering the heat-stimulating layer, the microfluidic channel, and the sensing layer with a breathable encapsulation film and bonding it to the epidermal contact layer.

6. The method for preparing the wearable multi-component sweat sensing patch according to claim 5, characterized in that, The signal probes include calcium ion recognition probes, potassium ion recognition probes, uric acid recognition probes, and glucose recognition probes; The preparation steps of the calcium ion recognition probe include: mixing and grinding dibromo-substituted naphthalimide and azacrown ether under the catalysis of anhydrous potassium carbonate and copper sulfate, and then heating the mixture under solvent-free conditions to obtain the calcium ion recognition probe. The preparation steps of the potassium ion recognition probe include: preparing gold nanoparticles by sodium citrate reduction, and then modifying the gold nanoparticles with 4'-aminodibenzo-18-crown-6 to obtain the potassium ion recognition probe.

7. The method for preparing the wearable sensing multi-component sweat sensing patch according to claim 6, characterized in that, The uric acid recognition probe is a complex of a water-soluble naphthyltetralactam macrocyclic compound and a phenolic dye halogen; the preparation method of the complex of the water-soluble naphthyltetralactam macrocyclic compound and the phenolic dye halogen includes the following steps: 2,6-Dihydroxynaphthalene and trimesic acid were mixed and an intermediate was constructed by bromoethane substitution, paraformaldehyde bridging and amination reactions. Using the intermediate, a pseudo-high dilution method was employed to achieve a cyclization reaction between the diester and the diamine in dichloromethane, forming a rigid framework with 2,6-diethoxynaphthalene as hydrophobic sidewalls and four lactam bonds as polar sites. The rigid skeleton was hydrolyzed with trifluoroacetic acid and alkalized to introduce a hydrophilic group from sodium carboxylate, yielding a water-soluble naphthyltetralactam macrocyclic compound. The water-soluble naphthyltetralactam macrocyclic compound was subjected to an indicator displacement reaction with the phenolazine dye halogen to obtain a complex.

8. A wearable, sensor-based, multi-component intelligent sweat detection system, characterized in that, include: The wearable sensing multi-component sweat sensing patch as described in any one of claims 1-4; The signal acquisition unit is used to acquire the color spectrum of the sensing layer on the wearable multi-component sweat sensing patch to form a basic dataset. The data augmentation unit is used to augment the basic dataset to form an augmented dataset; The machine learning analysis unit is used to train the system using the augmented dataset and output sweat detection results based on the color spectrum acquired by the signal acquisition unit.

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