Flexible wearable sweat bio-component real-time monitoring bracelet and its detection method

Abstract

This invention provides a flexible wearable wristband for real-time monitoring of sweat bio-components and its detection method, comprising a flexible wristband, a microfluidic sweat collection module, a multi-channel sensing unit, and a data processing system. The microfluidic sweat collection module is disposed in the inner layer of the flexible wristband and adheres to the skin through a biomimetic sweat micropore array, utilizing capillary action and material synergy to guide sweat to the microfluidic channels. The multi-channel sensing unit is used to detect sodium ion concentration, potassium ion concentration, lactic acid concentration, sweat volume, and basic electrochemical parameters in sweat, including an ion-selective electrode, an enzyme-modified sensor, a capacitance detection circuit, and an impedance detection circuit. The data processing system includes a signal amplification circuit, an analog-to-digital conversion circuit, and a wireless communication module, used for signal processing and generating a health assessment report to be fed back to the user terminal.

Description

Technical Field

[0001] This invention relates to the field of wearable electronic device technology, specifically to a flexible wearable wristband for real-time monitoring of sweat bio-components and its detection method. Background Technology

[0002] In the field of life and health monitoring, sweat has become a research hotspot in recent years due to its non-invasive acquisition method and rich physiological information. Sweat contains various biological components such as electrolytes, metabolites, and hormones, which are closely related to the body's dehydration status, muscle fatigue levels, and early signs of certain diseases. Therefore, sweat analysis has significant application value in clinical early warning, sports health management, and chronic disease monitoring. Compared with traditional blood testing methods, sweat testing has significant advantages in terms of safety, comfort, and convenience, and has thus attracted widespread attention.

[0003] In the existing technology, various detection schemes for sweat components have emerged. Patent CN202510058796.4 proposes an in-situ sweat detection sensor based on composite nanofibers, utilizing a gradient wettability structure and liquid metal electrodes to achieve unidirectional sweat flow and efficient signal transmission. Patent CN202411637008.9 discloses a press-type sweat component detection sensor, which improves the accuracy and specificity of detection through a five-finger synchronous detection structure and electrochemical technology. Patent CN202211065764.X employs a flexible hydrogel-based electrochemiluminescence sensor, integrating physical behavior and biochemical index monitoring, enhancing the adaptability and sensitivity of the device. Furthermore, patent CN202111371360.9 achieves high-precision detection of mixed sweat components through an array-type non-enzymatic electrochemical sensor, effectively improving the specificity problem of traditional sensors.

[0004] Despite advancements in material selection, structural design, and detection mechanisms in existing sweat detection technologies, several key issues remain unresolved. For instance, most devices employ rigid electrode structures, which are not easily adapted to dynamic body movements, potentially causing discomfort and affecting measurement accuracy. Furthermore, sweat collection and composition analysis are typically separate processes, resulting in long overall testing cycles and hindering continuous, real-time monitoring of physiological indicators. Additionally, the stability and durability of some devices in complex environments still require verification, limiting their application in long-term health monitoring.

[0005] In summary, current sweat bio-component detection technologies still have significant room for improvement in terms of flexibility, integration, real-time performance, and user experience. There is an urgent need for collaborative innovation in new materials, structural design, and detection methods to enhance the overall performance and practicality of detection systems. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this invention is to provide a flexible wearable wristband for real-time monitoring of sweat bio-components and its detection method.

[0007] According to one aspect of the present invention, a flexible wearable sweat bio-component real-time monitoring wristband is characterized in that it includes a flexible wristband, a microfluidic sweat collection module, a multi-channel sensing unit, and a data processing system; the microfluidic sweat collection module is disposed in the inner layer of the flexible wristband, and the microfluidic sweat collection module is in contact with the wearer's skin through a biomimetic sweat micropore array; the micropore array utilizes capillary action and the synergistic properties of hydrophobic and hydrophilic materials in the module to directionally introduce and guide sweat into the microfluidic channels; The multi-channel sensing unit is used to detect the concentration of sodium ions, potassium ions, lactic acid, sweat volume, and basic electrochemical parameters of sweat. The multi-channel sensing unit includes an ion-selective electrode, an enzyme-modified sensor, a capacitance detection circuit, and an impedance detection circuit. The data processing system includes a signal amplification circuit, an analog-to-digital conversion circuit, and a wireless communication module, which are used to process the signals output by the multi-channel sensing unit, generate a health assessment report based on a cloud algorithm, and feed it back to the user terminal.

[0008] Preferably, the microfluidic sweat collection module includes an upper hydrophobic guiding layer, a middle hydrophilic microchannel layer, and a bottom sweat storage layer; the surface of the hydrophobic guiding layer is provided with gradient wettability micropores, and the hydrophobic guiding layer forms a gradient wettability structure through local plasma modification; the hydrophilic microchannel layer adopts a serpentine zigzag microchannel configuration, and the inner wall of the hydrophilic microchannel layer is coated with an anti-protein adsorption coating; the sweat storage layer is provided with a liquid storage chamber, and the liquid storage chamber is connected to a multi-channel sensing unit through a microvalve. The microvalve opens periodically according to a preset detection cycle to quantitatively release sweat to the sensor interface for detection.

[0009] Preferably, the pore size of the micropores ranges from 500 to 1000 μm.

[0010] Preferably, the ion-selective electrode is used to detect inorganic ion components in sweat. The ion-selective electrode includes a valine-modified solid ion-selective electrode for sodium ion detection and a crown ether sensitive membrane electrode for potassium ion detection. The ion-selective electrode obtains the corresponding ion concentration by measuring the change in electrode interface potential. Preferably, the enzyme-modified sensor is used to detect organic metabolite components in sweat. The enzyme-modified sensor uses a lactate oxidase-Prussian blue nanowire composite material as the sensitive layer. The enzyme-modified sensor performs quantitative analysis of lactate concentration through electrochemical signals generated by enzymatic reactions. Preferably, the capacitance detection circuit is used to detect changes in sweat volume. The capacitance detection circuit includes a flexible interdigital electrode array, the interdigital electrodes covering the surface of the microfluidic reservoir. The capacitance detection circuit calculates the volume of sweat by monitoring changes in capacitance before and after sweat filling. The impedance detection circuit is used to measure the basic electrochemical parameters of sweat. The impedance detection circuit is integrated with the interdigitated electrode array and obtains the conductivity and pH-related impedance information of sweat based on the multi-frequency scanning method, and is used to cross-correct the ion detection results.

[0011] Preferably, the data processing system uses a SoC as the main control chip, and the main control chip has a built-in adaptive filtering algorithm to eliminate artifact interference generated during the wearer's movement; the main control chip uses a convolutional neural network model to fuse and analyze multi-source sensor data to identify abnormal physiological patterns.

[0012] Preferably, the wireless communication module is used to: transmit the processed data to an application on a mobile terminal based on Bluetooth 5.0 technology, wherein the application combines user historical data and a cloud database to generate personalized health suggestions and provide feedback to the user.

[0013] Preferably, the flexible wristband is made of TPU / PDMS composite material, and its inner layer is embedded with copper wires arranged in a serpentine pattern to achieve flexible interconnection of circuits; the overall thickness of the wristband is less than 2 mm, and it has an elongation rate of not less than 200% to meet the requirements of long-term wear and dynamic deformation conditions; the wristband also includes a micro air pump and a temperature control module.

[0014] According to another aspect of the present invention, a method for detecting real-time sweat bio-components using a flexible wearable wristband is provided, characterized in that it employs the monitoring wristband described in any one of claims 1-9, and the method comprises: Step S1: Collect sweat from the wearer's skin surface in real time using a microfluidic module and guide it into the reservoir. Step S2: The filling status of the liquid storage chamber is monitored in real time by the capacitance detection unit. When the capacitance value reaches the set threshold, the micro valve opening signal is triggered. Step S3: Open the micro valve according to the preset timing sequence to release the sweat in the storage chamber to the sensing interface of the multi-channel sensing unit, and simultaneously start the electrochemical detection process. Step S4: The conductivity and related impedance parameters of sweat are measured by the impedance detection unit to correct the cross-interference generated during ion detection and to obtain the impedance spectrum of characteristic frequencies. Step S5: The data output from each sensor channel is processed by Kalman filtering to suppress noise, and then the filtered multidimensional data is input into the LSTM model to predict the concentration change trend of the target component in sweat. Step S6: If the concentration trend shows a concentration exceeding a preset threshold, it is determined that the wearer's body is abnormal, triggering a local alarm and uploading relevant data to the cloud platform for further clinical correlation analysis.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention dynamically correlates the multidimensional biological components (such as sodium ions, potassium ions, and lactic acid) in sweat with the amount of secretion. Through multidimensional data detection and analysis of "sweat volume-biological components-rate", it comprehensively assesses the hydration status and metabolic load of the human body, which helps to comprehensively examine and monitor human movement and health status in real time, and builds an overall assessment system.

[0016] 2. The capacitance detection unit and impedance cross-correction technology in this invention can reduce the measurement error of sweat volume to 1 / 3 of that of traditional methods, and the sensitivity of component detection reaches the nm level.

[0017] 3. This invention adopts a fully flexible structure and adaptive microfluidic design, making the device thickness less than 2mm and the weight less than 15g. The wristband design further improves wearability and convenience, providing good comfort and safety. It supports long-term wear under high-intensity exercise while ensuring the wearer's comfort and the accuracy of bio-information detection. 4. This invention utilizes an edge-cloud collaborative algorithm to achieve a leap from "passive detection" to "proactive health intervention," systematically processing and analyzing the collected and detected biological information for user health level assessment, and providing a closed-loop solution for sports medicine and chronic disease management. Attached Figure Description

[0018] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of a flexible wearable sweat bio-component real-time monitoring wristband device provided in Embodiment 3; Figure 2 This is a schematic diagram of the layered structure of a sweat detection sensor module for a flexible wearable sweat bio-component real-time monitoring wristband provided in Embodiment 3; In the figure, 1 is the flexible wristband, 2 is the real-time monitoring sensor for sweat bio-components, 21 is the hydrophobic guiding layer, 22 is the serpentine zigzag hydrophilic microchannel layer, 23 is the sweat storage layer, 24 is the interdigital electrode layer, 25 is the multi-channel detection circuit, 26 is the bottom sweat storage layer, and 3 is the data processing system. Detailed Implementation

[0019] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0020] Example 1: This embodiment provides a flexible wearable wristband for real-time monitoring of sweat bio-components. The wristband achieves continuous monitoring of sweat composition and secretion dynamics through four core processes: sweat collection, multi-channel detection, data processing, and health analysis. The microfluidic sweat collection module inside the wristband adheres to the skin. The gradient wetting micropores formed by the hydrophobic and hydrophilic structures rapidly guide sweat into the serpentine microchannels, where it is temporarily stored in a reservoir. This reservoir is connected to a microvalve, which opens periodically to allow sweat to flow quantitatively and controllably to the multi-channel sensing unit, thus standardizing and stabilizing the detection conditions.

[0021] Once sweat enters the sensing area, different detection modules work together: ion-selective electrodes generate potential signals related to the concentrations of sodium and potassium ions in the sweat; enzyme-modified sensors generate current signals for lactic acid monitoring through lactate oxidase catalysis; the capacitance detection circuit uses flexible interdigitated electrodes to sense changes in the dielectric constant of the reservoir to calculate the sweat volume; and the impedance detection circuit obtains the conductivity and pH-related impedance characteristics of the sweat through frequency scanning, which is used to correct for interference from ion detection and supplement basic electrochemical parameters.

[0022] All sensor signals are amplified and converted from analog to digital before being input to the SoC main control chip. The main control chip uses an adaptive filtering algorithm to eliminate motion artifacts, and then uses a convolutional neural network model and an LSTM model to achieve multi-source data fusion and trend prediction. When abnormal physiological patterns are detected, the system can issue a local alarm and send the data to a mobile terminal or the cloud via Bluetooth, combining historical data to generate personalized health recommendations. This system achieves real-time, multi-dimensional, and intelligent monitoring of sweat composition, secretion volume, and electrochemical properties.

[0023] The bracelet includes a flexible wristband, a microfluidic sweat collection module, a multi-channel sensing unit, and a data processing system. The microfluidic sweat collection module is located in the inner layer of the flexible wristband and adheres to the wearer's skin through a biomimetic sweat micropore array. The micropore array utilizes capillary action and the synergistic properties of hydrophobic and hydrophilic materials in the module to directionally guide and channel sweat into the microfluidic channels. The multi-channel sensing unit is used to detect the concentration of sodium ions, potassium ions, lactic acid, sweat volume, and basic electrochemical parameters of sweat. The multi-channel sensing unit includes an ion-selective electrode, an enzyme-modified sensor, a capacitance detection circuit, and an impedance detection circuit. The data processing system includes a signal amplification circuit, an analog-to-digital conversion circuit, and a wireless communication module, which are used to process the signals output by the multi-channel sensing unit, generate a health assessment report based on a cloud algorithm, and feed it back to the user terminal.

[0024] Based on the above scheme, when worn, the microporous array in the inner layer of the bracelet fits tightly against the skin surface. Due to the gradient wettability of the micropores, driven by capillary action and the difference in hydrophobic / hydrophilic interfacial energy, sweat is rapidly drawn into the microfluidic channels in a unidirectional manner. After the sweat reaches the multi-channel sensing unit, the ion-selective electrode is used to monitor the potential changes of sodium and potassium electrolytes; the enzyme-modified sensor generates a current signal through the lactate oxidase reaction to detect lactate concentration; the capacitance detection circuit senses the change in dielectric constant of the reservoir through the interdigital electrode structure, thereby estimating the sweat volume; the impedance detection circuit obtains conductivity and pH-related impedance spectra through frequency scanning to correct ion detection and improve overall measurement accuracy. All detection signals are amplified and converted from analog to digital before being input to the SoC main control system. After filtering, fusion, and feature extraction, they are uploaded to the mobile terminal or cloud via the wireless communication module. The cloud algorithm combines historical data to generate personalized health assessments and exercise status analyses.

[0025] In this embodiment, the microfluidic sweat collection module includes an upper hydrophobic guiding layer, a middle hydrophilic microchannel layer, and a bottom sweat storage layer. The surface of the hydrophobic guiding layer is provided with gradient wettability micropores, and the hydrophobic guiding layer forms a gradient wettability structure through local plasma modification. The hydrophilic microchannel layer adopts a serpentine zigzag microchannel configuration, and the inner wall of the hydrophilic microchannel layer is coated with an anti-protein adsorption coating. The sweat storage layer is provided with a liquid storage chamber, which is connected to a multi-channel sensing unit through a microvalve. The microvalve opens periodically according to a preset detection cycle to quantitatively release sweat to the sensor interface for detection.

[0026] Based on the above scheme, sweat first contacts the hydrophobic guiding layer. The gradient wetting micropores on its surface, after plasma modification, form a wetting gradient that gradually increases from the outside in, rapidly attracting and guiding the sweat inward. Upon entering the hydrophilic microchannel layer, the serpentine microchannels extend the sweat path, allowing the sweat to enter the storage chamber in a stable flow state. The anti-protein adsorption coating on its inner wall prevents biocontamination and blockage caused by protein residues in the sweat. The sweat in the storage chamber is temporarily stored, and a microvalve is triggered to open at a set period, allowing the sweat to contact various electrochemical electrodes in a controlled manner. This ensures consistency in sweat renewal and quantification during detection, improving the accuracy of dynamic monitoring.

[0027] In this embodiment, the pore size of the micropores ranges from 500 to 1000 μm.

[0028] Based on the above scheme, micropores with a pore size of 500–1000 μm can maintain sufficient capillary suction while ensuring rapid sweat penetration and effectively inhibiting sweat evaporation. A larger pore size gradient can also enhance the conduction velocity, allowing sweat to enter the microchannel layer more quickly and improving real-time detection.

[0029] In this embodiment, the ion-selective electrode includes a valine-modified solid ion-selective electrode for sodium ion detection and a crown ether-sensitive membrane electrode for potassium ion detection. The ion-selective electrode obtains the corresponding ion concentration by measuring the change in electrode interface potential.

[0030] Based on the above scheme, valine can selectively bind to sodium ions, and this binding process leads to a change in membrane potential; crown ether molecules exhibit steric selectivity for potassium ions, also producing a potential response. The Nernst equation can then be used to convert the potential change into ion concentration, enabling real-time electrolyte monitoring.

[0031] In this embodiment, the enzyme-modified sensor uses a lactate oxidase-Prussian blue nanowire composite material as the sensitive layer, and quantitatively analyzes the lactate concentration through the electrochemical signal generated by the enzymatic reaction.

[0032] Based on the above scheme, lactate oxidase catalyzes the conversion of lactate to pyruvate, accompanied by the release of electrons. Prussian blue nanowires serve as an electron transport pathway, amplifying the current response. The sensor output current exhibits a linear relationship with lactate concentration, enabling highly sensitive and selective lactate detection.

[0033] In this embodiment, the capacitance detection circuit includes a flexible interdigital electrode array, which calculates the sweat volume by monitoring the change in capacitance value before and after sweat filling; the impedance detection circuit is integrated with the interdigital electrode array, which acquires sweat conductivity and pH-related impedance information based on multi-frequency scanning, and is used to cross-correct the ion detection results.

[0034] Based on the above scheme, after sweat fills the reservoir, the dielectric constant around the interdigitated electrodes changes, causing a change in capacitance; the sweat volume can be calculated using a preset calibration model. Impedance detection obtains conductivity and phase angle at different frequencies through frequency sweeping, which can be used to determine ionic strength and pH value, and further used to correct non-ideal responses of ion-selective electrodes.

[0035] In this embodiment, the data processing system uses a SoC main control chip with a built-in adaptive filtering algorithm to eliminate motion artifacts; the main control chip uses a convolutional neural network model to fuse and analyze multi-source sensor data to identify abnormal physiological patterns.

[0036] Based on the above scheme, the adaptive filter adjusts its filtering parameters according to the real-time motion state, effectively suppressing the interference of wearing vibration on the signal. CNN can extract the feature distribution of multi-sensor signals and identify data patterns. By training the model, it can identify physiological abnormalities such as dehydration risk and ion imbalance, thereby improving the system's intelligent detection capabilities.

[0037] In this embodiment, the wireless communication module transmits data to the mobile terminal application based on Bluetooth 5.0. The application combines the user's historical data and cloud database to generate personalized health recommendations.

[0038] Based on the above solution, Bluetooth 5.0, with its low power consumption and high bandwidth, ensures real-time data transmission. The app and cloud database synchronize bidirectionally, allowing for historical trend comparisons of current data to generate personalized exercise suggestions, health status assessments, or risk warnings.

[0039] In this embodiment, the flexible wristband is made of TPU / PDMS composite material, with serpentine copper wires embedded in the inner layer to achieve flexible circuit interconnection; the wristband thickness is less than 2 mm and the elongation is ≥200%; the wristband includes a micro air pump and a temperature control module.

[0040] Based on the above scheme, the TPU / PDMS composite structure can maintain good fit under large deformation conditions. The serpentine copper wires can unfold and bend when stretched, thus keeping the circuit intact. A micro air pump applies local negative pressure at the bottom of the wristband to promote sweat secretion; the temperature control module further increases the sweat production rate through micro-heating, enabling the detection system to work stably even under low sweating conditions.

[0041] Example 2: This embodiment provides a detection method for a flexible wearable sweat bio-component real-time monitoring bracelet, using the monitoring bracelet from Embodiment 1. The method includes: Step S1: Collect sweat from the wearer's skin surface in real time using a microfluidic module and guide it into the reservoir. Step S2: The filling status of the liquid storage chamber is monitored in real time by the capacitance detection unit. When the capacitance value reaches the set threshold, the micro valve opening signal is triggered. Step S3: Open the micro valve according to the preset timing sequence to release the sweat in the storage chamber to the sensing interface of the multi-channel sensing unit, and simultaneously start the electrochemical detection process. Step S4: The conductivity and related impedance parameters of sweat are measured by the impedance detection unit to correct the cross-interference generated during ion detection and to obtain the impedance spectrum of characteristic frequencies. Step S5: The data output from each sensor channel is processed by Kalman filtering to suppress noise, and then the filtered multidimensional data is input into the LSTM model to predict the concentration change trend of the target component in sweat. Based on the above scheme, the LSTM model uses a modular hierarchical structure of "input preprocessing - double-layer stacked LSTM - linear regression output" to predict sweat concentration: the preprocessing module standardizes and performs sliding window segmentation on the multidimensional sensor data sequence; the core prediction module uses a 64→32 unit double-layer stacked LSTM to output 32-dimensional hidden states; and the regression module directly outputs the target component concentration through a fully linearly connected layer. The model is trained using the Adam optimizer, an initial learning rate of 0.001, and a batch size of 64. The optimal model is then used for practical data prediction applications.

[0042] Step S6: If the concentration trend shows a concentration exceeding a preset threshold, it is determined that the wearer's body is abnormal, triggering a local alarm and uploading relevant data to the cloud platform for further clinical correlation analysis.

[0043] Example 3: like Figure 1 , 2 A schematic diagram of a flexible wearable wristband for real-time monitoring of sweat bio-components. Figure 1 The diagram shows the overall device, which includes: a flexible wristband 1, a real-time monitoring sensor for liquid biological components 2, and a data processing system 3. The sensor module further includes a microfluidic sweat collection module and a multi-channel sensing unit. Figure 2 This is a schematic diagram of the layered structure of the sweat detection sensor module of a flexible wearable sweat bio-component real-time monitoring wristband. From top to bottom, it consists of a hydrophobic guiding layer 21, a serpentine zigzag hydrophilic microchannel layer 22, a sweat storage layer 23, an interdigital electrode layer 24, a multi-channel detection circuit 25, and a bottom sweat storage layer 26.

[0044] Regarding the multidimensional bio-component detection, the main components include: Sodium ion detection employs a valine-modified solid-state ion-selective electrode. Valine is an ion carrier that selectively binds sodium ions to form a stable complex. When sodium ions bind to valine, the potential on the electrode surface changes, and the concentration of sodium ions can be quantitatively analyzed by measuring this change in potential. Potassium ion detection utilizes a crown ether compound sensitive membrane electrode. Crown ethers are cyclic compounds that selectively bind potassium ions. When potassium ions bind to crown ethers, the potential on the electrode surface changes, and the concentration of potassium ions can be quantitatively analyzed by measuring this change in potential. Lactic acid detection is based on a lactate oxidase-Prussian blue nanowire composite electrode. Lactic acid oxidase catalyzes the oxidation of lactate to pyruvate and reduced nicotinamide adenine dinucleotide (NADH). Prussian blue nanowires possess excellent electrochemical properties, enhancing the sensitivity and stability of the electrode. The concentration of lactate can be quantitatively analyzed by measuring the change in current on the electrode surface.

[0045] The hydrophobic guiding layer is fabricated using a 100μm thick PDMS film as the substrate, with hydrophilic regions formed on its surface through oxygen plasma treatment. A gradient micropore array with a pore size of 500-1000μm is then fabricated on its surface to ensure efficient sweat collection. The hydrophilic microchannel layer is fabricated using laser engraving to etch serpentine microchannels (500μm wide, 100μm deep, and 75mm long) onto a PET substrate. The intermediate layer also employs a serpentine microchannel design, with a 1.5mm wide and 1.5mm deep serpentine microchannel and a 1mm diameter outlet. The inner walls of the channels are coated with an anti-protein adsorption coating to prevent biocontamination. Sweat flows into the channel from the inlet and out from the outlet. The storage chamber is formed using 3D printing technology (material: photocurable resin), with a 1mm diameter microvalve interface pre-installed at the top. The capacitance detection unit uses an interdigital capacitor structure, with interdigital electrodes formed using dispensing printed silver paste. The electrodes are 1mm wide, 1mm spaced, and have an effective area of ​​10mm × 20mm.

[0046] After the wearer completes wearing the sweat bio-component detection wristband, the system is powered on and ready to work. The sweat collection inlet is in close contact with the skin without any pressure. Since there is no sweat in the channel at the beginning, the multi-channel sensing unit does not output a detection signal and performs self-calibration. The capacitance detection unit verifies the empty state of the liquid storage chamber and completes the baseline calibration.

[0047] When sweat enters the collection channel and then the sensing unit, each sensor outputs multi-dimensional bio-component information, including sodium ion concentration, potassium ion concentration, and lactic acid concentration. The capacitance testing module outputs the current capacitance value and, based on calibration data, obtains sweat volume data. The impedance detection module displays the sweat conductivity. The edge computing model LSTM receives the detected data and, by combining sweat volume, bio-component data, and ambient temperature and humidity, comprehensively assesses the wearer's current activity and health status. It triggers alarms for potential risks such as dehydration and sends alerts to the online platform. The test data is stored in the cloud platform for analysis and evaluation of long-term users' health and activity status, in conjunction with historical data.

[0048] This embodiment can be seen as a practical application of Embodiment 1.

[0049] It should be noted that the parts of this invention not described in detail are well-known technologies in the field.

[0050] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0051] In the description of this application, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0052] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A flexible wearable wristband for real-time monitoring of sweat bio-components, characterized in that, The device includes a flexible wristband, a microfluidic sweat collection module, a multi-channel sensing unit, and a data processing system. The microfluidic sweat collection module is located in the inner layer of the flexible wristband and fits the wearer's skin through a biomimetic sweat micropore array. The micropore array utilizes capillary action and the synergistic properties of hydrophobic and hydrophilic materials in the module to directionally guide and channel sweat into the microfluidic channels. The multi-channel sensing unit is used to detect the concentration of sodium ions, potassium ions, lactic acid, sweat volume, and basic electrochemical parameters of sweat. The multi-channel sensing unit includes an ion-selective electrode, an enzyme-modified sensor, a capacitance detection circuit, and an impedance detection circuit. The data processing system includes a signal amplification circuit, an analog-to-digital conversion circuit, and a wireless communication module, which are used to process the signals output by the multi-channel sensing unit, generate a health assessment report based on a cloud algorithm, and feed it back to the user terminal.

2. The wristband according to claim 1, characterized in that, The microfluidic sweat collection module includes an upper hydrophobic guiding layer, a middle hydrophilic microchannel layer, and a bottom sweat storage layer. The surface of the hydrophobic guiding layer is provided with gradient wettability micropores, and the hydrophobic guiding layer forms a gradient wettability structure through local plasma modification. The hydrophilic microchannel layer adopts a serpentine zigzag microchannel configuration, and the inner wall of the hydrophilic microchannel layer is coated with an anti-protein adsorption coating. The sweat storage layer is provided with a liquid storage chamber, which is connected to a multi-channel sensing unit through a microvalve. The microvalve opens periodically according to a preset detection cycle to quantitatively release sweat to the sensor interface for detection.

3. The wristband according to claim 1, characterized in that, The pore size of the micropores ranges from 500 to 1000 μm.

4. The wristband according to claim 1, characterized in that, The ion-selective electrode is used to detect inorganic ion components in sweat. The ion-selective electrode includes a valine-modified solid ion-selective electrode for sodium ion detection and a crown ether sensitive membrane electrode for potassium ion detection. The ion-selective electrode obtains the corresponding ion concentration by measuring the change in electrode interface potential.

5. The bracelet according to claim 1, characterized in that, The enzyme-modified sensor is used to detect organic metabolites in sweat. The enzyme-modified sensor uses a lactate oxidase-Prussian blue nanowire composite material as the sensitive layer. The enzyme-modified sensor performs quantitative analysis of lactate concentration through electrochemical signals generated by enzymatic reactions.

6. The wristband according to claim 1, characterized in that, The capacitance detection circuit is used to detect changes in the volume of sweat. The capacitance detection circuit includes a flexible interdigital electrode array. The interdigital electrodes cover the surface of the microfluidic reservoir. The capacitance detection circuit calculates the volume of sweat by monitoring the change in capacitance value before and after the sweat is filled. The impedance detection circuit is used to measure the basic electrochemical parameters of sweat. The impedance detection circuit is integrated with the interdigitated electrode array and obtains the conductivity and pH-related impedance information of sweat based on the multi-frequency scanning method, and is used to cross-correct the ion detection results.

7. The wristband according to claim 1, characterized in that, The data processing system uses a SoC as the main control chip, which has a built-in adaptive filtering algorithm to eliminate artifact interference generated during the wearer's movement. The main control chip uses a convolutional neural network model to fuse and analyze multi-source sensor data to identify abnormal physiological patterns.

8. The wristband according to claim 1, characterized in that, The wireless communication module is used to transmit the processed data to the application on the mobile terminal based on Bluetooth 5.0 technology. The application combines the user's historical data and cloud database to generate personalized health suggestions and provide feedback to the user.

9. The bracelet according to claim 1, characterized in that, The flexible wristband is made of TPU / PDMS composite material, with copper wires embedded in its inner layer in a serpentine pattern for flexible interconnection of circuits; the overall thickness of the wristband is less than 2 mm, and it has an elongation rate of not less than 200% to meet the requirements of long-term wear and dynamic deformation conditions; the wristband also includes a micro air pump and a temperature control module.

10. A method for detecting the real-time biocomposition of sweat on a flexible wearable wristband, characterized in that, The method, using the monitoring wristband according to any one of claims 1-9, comprises: Step S1: Collect sweat from the wearer's skin surface in real time using a microfluidic module and guide it into the reservoir. Step S2: The filling status of the liquid storage chamber is monitored in real time by the capacitance detection unit. When the capacitance value reaches the set threshold, the micro valve opening signal is triggered. Step S3: Open the micro valve according to the preset timing sequence to release the sweat in the storage chamber to the sensing interface of the multi-channel sensing unit, and simultaneously start the electrochemical detection process. Step S4: The conductivity and related impedance parameters of sweat are measured by the impedance detection unit to correct the cross-interference generated during ion detection and to obtain the impedance spectrum of characteristic frequencies. Step S5: The data output from each sensor channel is processed by Kalman filtering to suppress noise, and then the filtered multidimensional data is input into the LSTM model to predict the concentration change trend of the target component in sweat. Step S6: If the concentration trend shows a concentration exceeding a preset threshold, it is determined that the wearer's body is abnormal, triggering a local alarm and uploading relevant data to the cloud platform for further clinical correlation analysis.

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