A method of manufacturing a strain-pressure sensor, a monitoring device and a monitoring method

Abstract

The application relates to the technical field of sensors, and provides a preparation method of a strain-pressure sensor, a monitoring device and a monitoring method. The monitoring device based on the strain-pressure sensor comprises at least one strain-pressure sensor and a signal acquisition circuit module and a signal processing module which are uniformly distributed, the strain-pressure sensor generates a first resistance signal and a second resistance signal according to different physiological states, the signal acquisition circuit module outputs corresponding first digital signals and second digital signals based on the first resistance signal and the second resistance signal, the signals are transmitted to the signal processing module in a wireless transmission mode, and the signal processing module calculates and outputs continuous physiological information and analysis results of a user through a "double band-pass-peak value detection" algorithm and a "fetal movement monitoring" algorithm. Through the monitoring device, the problems of single function, insufficient sensitivity, difficulty in adapting to the slight deformation or jumping of human skin, lack of continuous monitoring capacity and the like of the existing health monitoring devices can be solved.

Description

Technical Field

[0001] This invention relates to the field of sensor technology, and specifically to a method for preparing a strain-pressure sensor, a monitoring device, and a monitoring method. Background Technology

[0002] With the increasing demand for health monitoring, wearable physiological monitoring devices are gradually becoming important tools for health management, chronic disease tracking, and monitoring of special populations (such as pregnant women and the elderly). In the existing technology, common health monitoring devices mainly include wristband devices based on photoplethysmography, patch monitors based on electrocardiogram signals, and devices such as chest straps and breathing belts based on traditional pressure or strain sensors.

[0003] In recent years, the rapid development of flexible strain and pressure sensors has provided new possibilities for flexible wearable health monitoring. Flexible strain sensors can sense surface tension through changes in resistance caused by material deformation, while flexible pressure sensors can sense surface pressure through changes in interfacial resistance. Their advantages include high sensitivity, fast response, and adaptability to different skin surface shapes. However, the application of existing flexible sensors in wearable health monitoring still faces some challenges, such as limited sensor functionality, insufficient sensitivity, difficulty in adapting to minute deformations / jumps of human skin, and lack of continuous monitoring capabilities. To address these issues, a new wearable health monitoring solution is needed. Summary of the Invention

[0004] The purpose of this invention is to solve the problems of existing health monitoring devices, such as limited functionality, insufficient sensitivity, inability to adapt to minute deformations or pulsations of human skin, and lack of continuous monitoring capability, and to provide a monitoring device based on a strain-pressure sensor and a method for preparing the sensor.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A monitoring device based on a strain-pressure sensor includes a signal acquisition module and a signal processing module. The signal acquisition module is used in contact with the area to be monitored on the user's skin, and the signal acquisition module and the signal processing module are wirelessly connected.

[0007] The signal acquisition module includes at least one uniformly distributed strain-pressure sensor and at least one signal acquisition circuit module. The strain-pressure sensor is electrically connected to the signal acquisition module. The signal acquisition circuit module outputs corresponding first digital signal and second digital signal based on a first resistance signal and a second resistance signal. The first resistance signal is the resistance change value generated by the strain-pressure sensor according to the stretching and contraction of the skin in the user's monitoring area. The second resistance signal is the resistance change value generated by the strain-pressure sensor according to the pressure change of the strain-pressure sensor when the skin in the user's monitoring area jumps.

[0008] The materials of the detection end of the strain-pressure sensor are strain-sensitive carbon paste material and paper-based pressure-sensitive carbon paste material;

[0009] The signal processing module has either a "dual bandpass-peak detection" algorithm or a "fetal movement monitoring" algorithm. The "dual bandpass-peak detection" algorithm is used to obtain the user's continuous respiratory rate information and continuous heart rate information in real time based on the first digital signal and the second digital signal. The signal processing module matches the continuous respiratory rate information and continuous heart rate information with the database and outputs the user's respiratory-heartbeat joint monitoring results, deep and shallow respiratory rates, blood oxygen assessment, or sleep apnea analysis and other information results. The "fetal movement monitoring" algorithm is used to obtain fetal movement information in real time based on the first digital signal and the second digital signal. The signal processing module matches the fetal movement information with the database and outputs the physiological state of the fetus in the uterus.

[0010] This invention provides a monitoring device based on a strain-pressure sensor. The strain-pressure sensor uses strain-sensitive carbon paste material and paper-based pressure-sensitive carbon paste material to make the detection end, enabling it to monitor minute stress and pressure changes. Therefore, the strain-pressure sensor can continuously and in real-time generate corresponding resistance changes with the stretching and contraction of human skin and pressure changes. The signal acquisition circuit module and the signal processing module analyze the resistance changes into data such as respiratory rate, heart rate, and fetal movement, thereby improving the real-time and continuous nature of monitoring. Applying the signal acquisition module to the skin surface of the area to be monitored effectively reduces interference and improves the accuracy and reliability of the measurement.

[0011] When the user is an infant, child, or adult, the user monitoring site is the skin near the user's heart; when the user is a pregnant woman and the monitoring is used to monitor the physiological state of the fetus, the user monitoring site is the skin near the fetus in the pregnant woman's uterus.

[0012] As a preferred embodiment of the present invention, the strain-pressure sensor is composed of a flexible substrate layer, a strain sensing layer, a pressure sensing layer, a flexible circuit board, and a flexible encapsulation layer stacked sequentially. The monitoring end of the strain sensing layer is an open hollow polygon, and the monitoring end of the pressure sensing layer is a solid structure. The monitoring end of the pressure sensing layer is nested within the hollow region of the monitoring end of the strain sensing layer.

[0013] As a preferred embodiment of the present invention, the monitoring end of the strain sensing layer is a hollow octagonal structure with one side not closed; the monitoring end of the pressure sensing layer is a solid circle.

[0014] As a preferred embodiment of the present invention, the signal acquisition circuit module includes a power supply, a voltage regulator module, an FPC connector, several voltage divider resistors, and a control transmission unit. The power supply provides power to the circuit after modulation by the voltage regulator module. The strain-pressure sensor is connected to the circuit of the signal acquisition circuit module through the FPC connector. Each strain-pressure sensor in the circuit can form a strain detection loop and a pressure transformer detection loop in parallel with the signal acquisition circuit module. The strain detection loop is a closed loop formed by the voltage divider resistor and the strain sensing layer connected in series. The pressure transformer detection loop is a closed loop formed by the voltage divider resistor and the pressure sensing layer connected in series. The control transmission unit is used to convert the first voltage signal and the second voltage signal into corresponding first digital signal and second digital signal and wirelessly transmit them to the signal processing module.

[0015] As a preferred embodiment of the present invention, the strain-pressure sensor is detachably electrically connected to the FPC connector.

[0016] The detachable electrical connection between the strain-pressure sensor and the FPC connector includes a plug-in interface connection. This detachable electrical connection improves the reusability of the signal acquisition module and reduces the risk of infection from repeated or cross-use of the strain-pressure sensor.

[0017] As a preferred embodiment of the present invention, the control transmission unit includes an analog-to-digital conversion module and a wireless transmission module.

[0018] The wireless transmission module includes a Bluetooth transmission module or a Wi-Fi transmission module.

[0019] As a preferred embodiment of the present invention, the "dual bandpass-peak detection" algorithm includes a first fourth-order Butterworth bandpass filtering algorithm, a second fourth-order Butterworth bandpass filtering algorithm, a peak detection algorithm, and a result analysis algorithm. The first fourth-order Butterworth bandpass filtering algorithm and the second fourth-order Butterworth bandpass filtering algorithm have different filtering bands. The first fourth-order Butterworth bandpass filtering algorithm is used to perform zero-phase filtering on the first digital signal, and the second fourth-order Butterworth bandpass filtering algorithm is used to perform zero-phase filtering on the second digital signal. The peak detection algorithm is used to perform peak detection on the first digital signal and the second digital signal after zero-phase filtering to obtain respiratory rate monitoring value and heart rate monitoring value, respectively. The result analysis algorithm is used to match the respiratory rate monitoring value and the heart rate monitoring value with the database and output information results such as the user's deep and shallow respiratory rates, blood oxygen assessment, and sleep apnea analysis.

[0020] As a preferred embodiment of the present invention, the "fetal movement monitoring" algorithm includes an eighth-order Butterworth low-pass digital filtering algorithm and a result analysis algorithm. The eighth-order Butterworth low-pass digital filtering algorithm is used to perform zero-phase filtering on the first digital signal and the second digital signal. The result analysis algorithm is used to process the data based on the filtered first digital signal and the second digital signal to obtain fetal movement information, and to match the fetal movement information with the database to output the physiological state of the fetus in the uterus.

[0021] A monitoring method based on a strain-pressure sensor includes using a strain-pressure sensor-based monitoring device as described above, with the following steps:

[0022] S1. Place the signal acquisition module onto the area to be monitored on the user's skin;

[0023] S2. Turn on the power. The strain-pressure sensor generates a first resistance signal and a second resistance signal according to different physiological states. The signal acquisition circuit module outputs a corresponding first digital signal and a second digital signal based on the first resistance signal and the second resistance signal. The first digital signal and the second digital signal monitored in real time are transmitted to the signal processing module through wireless transmission.

[0024] S3. The first digital signal is subjected to zero-phase filtering using the first fourth-order Butterworth bandpass filtering algorithm in the signal processing module, and the second digital signal is subjected to zero-phase filtering using the second fourth-order Butterworth bandpass filtering algorithm in the signal processing module. The peak detection algorithm continuously counts the number of peaks in the first and second digital signals after zero-phase filtering within 30 seconds, and multiplies the number of peaks by 2 to obtain the respiratory rate monitoring value and the heart rate monitoring value, respectively. The result analysis algorithm matches the respiratory rate monitoring value and the heart rate monitoring value with the database.

[0025] S4. The signal processing module outputs the user's physiological information results.

[0026] This invention provides a monitoring method based on a strain-pressure sensor. By using a single strain-pressure sensor to couple changes in skin strain and pressure caused by various physiological activities, and by analyzing characteristic parameters such as respiration, heart rate, and fetal movement through the signal processing module, this invention simplifies the system structure, reduces hardware costs, and achieves multi-parameter collaborative monitoring. This helps to more comprehensively reflect the user's physiological state and significantly improves the real-time performance, continuity, comfort, and integration of physiological parameter monitoring while ensuring the accuracy and reliability of the monitoring data.

[0027] As a preferred embodiment of the present invention, step S3 is replaced with: S3, the first digital signal and the second digital signal are subjected to zero-phase filtering processing by the eighth-order Butterworth low-pass digital filtering algorithm in the signal processing module, and the first digital signal and the second digital signal are subjected to band-limited interpolation resampling, multi-scale moving average normalization processing, fixed window segmentation, dataset balancing processing and machine learning processing in sequence to obtain fetal movement information, and the fetal movement information is matched with the database.

[0028] A method for fabricating a strain-pressure sensor includes preparing a strain-pressure sensor for use in a monitoring device based on a strain-pressure sensor as described above, comprising the following steps:

[0029] Step 1: Pour the Ecoflex solution into a groove mold and cure it to obtain a flexible substrate;

[0030] Step 2: Multi-walled carbon nanotube powder, ethyl acetate solution, and Ecoflex solution were prepared in different proportions and by different preparation methods to obtain a first carbon paste, a second carbon paste, and a conductive binder;

[0031] Step 3: The first carbon paste is printed onto the top surface of the flexible substrate using a stencil printing method to prepare a strain sensing layer;

[0032] Step 4: Immerse the model paper in the second carbon paste, remove it and cure it to obtain the pressure sensing layer;

[0033] Step 5: Fix the pressure sensing layer to one side of the interdigitated electrode of the flexible circuit board. The flexible circuit board is fixed and connected to the electrode of the strain sensing layer by the conductive adhesive.

[0034] Step 6: Use Ecoflex solution as a flexible encapsulation layer for encapsulation to prepare a strain-pressure sensor.

[0035] This invention provides a method for fabricating a strain-pressure sensor. By precisely controlling the composition ratio, thickness, and microstructure morphology of strain-sensitive carbon paste material and paper-based pressure-sensitive carbon paste material, the prepared strain-pressure sensor exhibits excellent and consistent comprehensive performance in terms of sensitivity, response linearity, repeatability, and hysteresis characteristics. This controllable manufacturing process effectively reduces the performance differences between individual strain-pressure sensors, improving the overall measurement reliability and data accuracy after integration into a monitoring device. This method can form an ultra-thin, stretchable sensitive functional layer and a flexible substrate structure, giving the strain-pressure sensor excellent mechanical flexibility and conformability. This characteristic allows it to seamlessly conform to the curved surface of human skin and maintain a stable electrical response under repeated stretching and bending.

[0036] In a preferred embodiment of the present invention, step 2 has the following formulation: the first carbon paste is prepared by mixing the carbon black powder and the multi-walled carbon nanotube powder at a mass ratio of 4:1, and then mixing it with the ethyl acetate solution at a ratio of 1g / 35mL, wherein the mass ratio of the Ecoflex solution to the carbon black powder and the multi-walled carbon nanotube powder in the solution is 100:5; the second carbon paste is prepared by mixing the carbon black powder and the multi-walled carbon nanotube powder at a mass ratio of 4:1, and then mixing it with the ethyl acetate solution at a ratio of 1g / 100mL, wherein the mass ratio of the Ecoflex solution to the carbon black powder and the multi-walled carbon nanotube powder in the solution is 100:3; and the conductive binder is prepared by mixing the multi-walled carbon nanotube powder and the ethyl acetate solution at a ratio of 1g / 20mL, wherein the mass ratio of the Ecoflex solution to the multi-walled carbon nanotube powder in the solution is 100:7.

[0037] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0038] 1. A monitoring device based on a strain-pressure sensor, wherein the strain-pressure sensor uses strain-sensitive carbon paste material and paper-based pressure-sensitive carbon paste material to make the detection end, which can detect minute stress and pressure changes. Therefore, the strain-pressure sensor can continuously and in real time generate corresponding resistance changes with the expansion and contraction of human skin and pressure changes. Through a signal acquisition circuit module and a signal processing module, the resistance changes are analyzed into data such as respiratory rate, heart rate, and fetal movement, thereby improving the real-time and continuous nature of monitoring. Applying the signal acquisition module to the skin surface of the area to be monitored can effectively reduce interference and improve the accuracy and reliability of the measurement.

[0039] 2. A monitoring method based on a strain-pressure sensor, which uses a single strain-pressure sensor to couple changes in skin strain and pressure caused by multiple physiological activities, and analyzes characteristic parameters such as respiration, heart rate, and fetal movement through a signal processing module. While simplifying the system structure and reducing hardware costs, it realizes multi-parameter collaborative monitoring, which helps to more comprehensively reflect the user's physiological state. Under the premise of ensuring the accuracy and reliability of monitoring data, it significantly improves the real-time performance, continuity, comfort, and integration of physiological parameter monitoring.

[0040] 3. A method for fabricating a strain-pressure sensor, by precisely controlling the composition ratio, thickness, and microstructure morphology of strain-sensitive carbon paste material and paper-based pressure-sensitive carbon paste material, the prepared strain-pressure sensor exhibits excellent and consistent comprehensive performance in terms of sensitivity, response linearity, repeatability, and hysteresis characteristics; this controllable manufacturing process effectively reduces the performance differences between individual strain-pressure sensors, and improves the overall measurement reliability and data accuracy after integration into a monitoring device; this method can form an ultra-thin, stretchable sensitive functional layer and a flexible substrate structure, giving the strain-pressure sensor excellent mechanical flexibility and conformability, which allows it to seamlessly conform to the curved surface of human skin and maintain a stable electrical response under repeated stretching and bending. Attached Figure Description

[0041] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0042] Figure 1 This is a schematic diagram of a monitoring device based on a strain-pressure sensor;

[0043] Figure 2 This is a schematic diagram of the structure of a strain-pressure sensor in a monitoring device based on a strain-pressure sensor;

[0044] Figure 3This is a schematic diagram of a resistor voltage divider circuit for a signal acquisition module in a monitoring device based on a strain-pressure sensor;

[0045] Figure 4 This is a schematic diagram of a monitoring device based on a strain-pressure sensor for monitoring fetal movement.

[0046] Figure 5 This is a schematic diagram of the monitoring signal processing flow when monitoring respiratory and heart rate using a monitoring method based on a strain-pressure sensor.

[0047] Figure 6 This is a schematic diagram of the monitoring signal processing flow during fetal movement monitoring, which is a monitoring method based on a strain-pressure sensor monitoring device.

[0048] Icons: 1-Signal acquisition module; 11-Strain-pressure sensor module; 111-Flexible substrate layer; 112-Strain sensing layer; 113-Pressure sensing layer; 114-Flexible circuit board; 115-Flexible encapsulation layer; 12-Signal acquisition circuit module; 121-Power supply; 122-Voltage divider resistor; 2-Signal processing module; 3-Pregnant woman's abdominal skin. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0050] Example 1:

[0051] like Figure 1 As shown, the monitoring device based on a strain-pressure sensor used in this invention includes a signal acquisition module 1 and a signal processing module 2. The signal acquisition module 1 is used to attach to the area to be monitored on the user's skin, and the signal acquisition module 1 and the signal processing module 2 are wirelessly connected.

[0052] The signal acquisition module 1 includes at least one uniformly distributed strain-pressure sensor 11 and at least one signal acquisition circuit module 12. The strain-pressure sensor 11 is electrically connected to the signal acquisition module 1. The signal acquisition circuit module 12 outputs corresponding first digital signal and second digital signal based on a first resistance signal and a second resistance signal. The first resistance signal is the resistance change value generated by the strain-pressure sensor 11 according to the skin expansion and contraction of the user's area to be monitored. The second resistance signal is the resistance change value generated by the strain-pressure sensor 11 according to the pressure change of the strain-pressure sensor 11 when the skin of the user's area to be monitored jumps.

[0053] The material of the detection end of the strain-pressure sensor 11 is strain-sensitive carbon paste material and paper-based pressure-sensitive carbon paste material;

[0054] The signal processing module 2 has a "dual bandpass-peak detection" algorithm or a "fetal movement monitoring" algorithm. The "dual bandpass-peak detection" algorithm is used to obtain the user's continuous respiratory rate information and continuous heart rate information in real time based on the first digital signal and the second digital signal. The signal processing module 2 matches the continuous respiratory rate information and continuous heart rate information with the database and outputs the user's respiratory-heartbeat joint monitoring results, deep and shallow respiratory rates, blood oxygen assessment or sleep apnea analysis and other information results. The "fetal movement monitoring" algorithm is used to obtain fetal movement information in real time based on the first digital signal and the second digital signal. The signal processing module 2 matches the fetal movement information with the database and outputs the physiological state of the fetus in the uterus.

[0055] Furthermore, such as Figure 2 As shown, the strain-pressure sensor 11 has a structure consisting of a flexible substrate layer 111, a strain sensing layer 112, a pressure sensing layer 113, a flexible circuit board 114, and a flexible encapsulation layer 115 stacked sequentially. The monitoring end of the strain sensing layer 112 is an open hollow polygon, and the monitoring end of the pressure sensing layer 113 is a solid structure. The monitoring end of the pressure sensing layer 113 is nested within the hollow region of the monitoring end of the strain sensing layer 112.

[0056] Furthermore, the monitoring end of the strain sensing layer 112 is a hollow octagonal structure with one side not closed; the monitoring end of the pressure sensing layer 113 is a solid circle.

[0057] Furthermore, such as Figure 1 and 3 As shown, the signal acquisition circuit module 12 includes a power supply 121, a voltage regulator module, an FPC connector, several voltage divider resistors 122, and a control transmission unit. The power supply 121 supplies power to the circuit after modulation by the voltage regulator module. The strain-pressure sensor 11 is connected to the circuit of the signal acquisition circuit module 12 through the FPC connector. Each strain-pressure sensor 11 in the circuit can form a strain detection loop and a pressure transformer detection loop in parallel with the signal acquisition circuit module 12. The strain detection loop is a closed loop formed by the voltage divider resistors 122 and the strain sensing layer 112 connected in series. The pressure transformer detection loop is a closed loop formed by the voltage divider resistors 122 and the pressure sensing layer 113 connected in series. The control transmission unit is used to convert the first voltage signal and the second voltage signal into corresponding first digital signals and second digital signals and wirelessly transmit them to the signal processing module 2.

[0058] Furthermore, the strain-pressure sensor 11 is detachably electrically connected to the FPC connector.

[0059] Furthermore, the control transmission unit includes an analog-to-digital conversion module and a wireless transmission module.

[0060] Furthermore, the "dual bandpass-peak detection" algorithm includes a first fourth-order Butterworth bandpass filtering algorithm, a second fourth-order Butterworth bandpass filtering algorithm, a peak detection algorithm, and a result analysis algorithm. The first and second fourth-order Butterworth bandpass filtering algorithms have different filtering bands. The first fourth-order Butterworth bandpass filtering algorithm is used to perform zero-phase filtering on the first digital signal, and the second fourth-order Butterworth bandpass filtering algorithm is used to perform zero-phase filtering on the second digital signal. The peak detection algorithm is used to perform peak detection on the first and second digital signals after zero-phase filtering to obtain respiratory rate monitoring values ​​and heart rate monitoring values, respectively. The result analysis algorithm is used to match the respiratory rate monitoring values ​​and heart rate monitoring values ​​with the database and output information such as the user's deep and shallow respiratory rates, blood oxygen assessment, and sleep apnea analysis results.

[0061] Furthermore, the "fetal movement monitoring" algorithm includes an eighth-order Butterworth low-pass digital filtering algorithm and a result analysis algorithm. The eighth-order Butterworth low-pass digital filtering algorithm is used to perform zero-phase filtering on the first digital signal and the second digital signal. The result analysis algorithm is used to process the data based on the filtered first digital signal and the second digital signal to obtain fetal movement information, and to match the fetal movement information with the database to output the physiological state of the fetus in the uterus.

[0062] In this embodiment, the signal processing module 2 is a computer. The filtering band range of the first fourth-order Butterworth bandpass filter algorithm is 0.1-1Hz, and the filtering band range of the second fourth-order Butterworth bandpass filter algorithm is 1-3Hz. The control transmission unit includes a 12-bit ADC and a microprocessor. The 12-bit ADC for the strain detection circuit is denoted as ADC1, and the 12-bit ADC for the pressure transformer detection circuit is denoted as ADC2.

[0063] The strain-pressure sensor 11 uses strain-sensitive carbon paste material and paper-based pressure-sensitive carbon paste material to make the detection end, enabling it to monitor minute stress and pressure changes. Therefore, the strain-pressure sensor 11 can continuously and in real time generate corresponding resistance changes according to the stretching and contraction of human skin and its movement. The signal acquisition circuit module 12 and the signal processing module 2 analyze the resistance changes into data such as respiratory rate, heart rate, and fetal movement, thereby improving the real-time and continuous nature of monitoring. Applying the signal acquisition module 1 to the skin surface of the area to be monitored effectively reduces interference and improves the accuracy and reliability of the measurement.

[0064] When the user is an infant, child, or adult, the user monitoring site is the skin near the user's heart; when the user is a pregnant woman and the monitoring is used to monitor the physiological state of the fetus, the user monitoring site is the skin near the fetus in the pregnant woman's uterus.

[0065] In this embodiment, as Figure 4 As shown, the user is a pregnant woman and the device is used to monitor the physiological state of the fetus. There are four strain-pressure sensors 11 and four signal acquisition circuit modules 12. The output of each strain-pressure sensor 11 is electrically connected to one signal acquisition circuit module 12. The four strain-pressure sensors 11 are radially and evenly attached to the pregnant woman's abdominal skin 3, with the detection end of each strain-pressure sensor 11 positioned close to the center. The upper strain-pressure sensor module is primarily responsible for monitoring fetal leg movements, such as kicking; the left and right strain-pressure sensor modules are primarily responsible for monitoring fetal hand movements, such as stretching and waving; and the lower strain-pressure sensor module is primarily responsible for monitoring fetal head movements, such as head turning.

[0066] When the power supply 121 is turned on, it supplies power to the circuit after being modulated by the voltage regulator module. The pregnant woman's abdominal skin 3 stretches and contracts with the movement of the fetus, causing the flexible base layer 111 to stretch and contract, which in turn causes the octagonal strain sensing layer 112 to stretch and contract, outputting the corresponding first resistance signal. The pressure change of the pregnant woman's abdominal skin 3 with the movement of the fetus is monitored, causing the flexible base layer 111 to be under pressure, which in turn causes the circular pressure sensing layer 113 to be under pressure, outputting the corresponding second resistance signal. The control transmission unit converts the first resistance signal and the second resistance signal into the corresponding first digital signal and the second digital signal and wirelessly transmits them to the signal processing module 2.

[0067] The signal processing module 2 calculates and outputs the user's continuous physiological information through the "fetal movement monitoring" algorithm. The eighth-order Butterworth low-pass digital filtering algorithm performs zero-phase filtering on the first digital signal and the second digital signal. The result analysis algorithm is used to process the data based on the filtered first digital signal and the second digital signal to obtain fetal movement information, and matches the fetal movement information with the database to output the physiological state of the fetus in the uterus.

[0068] Fetal movement information includes discontinuous kicking, flapping, swaying, or rolling. Fetal movement causes the pregnant woman's abdominal skin to stretch and pulsate. Therefore, the monitoring device based on a strain-pressure sensor provided in this embodiment can be used for objective and continuous monitoring of fetal movement in pregnant women. This not only compensates for the bias of the pregnant woman's subjective perception but also provides a basis for timely medical intervention. In addition, fetal movement also includes turning / rolling, hiccups, twitching, and startling.

[0069] In this embodiment, when the user is an infant, child, or adult, the number of the strain-pressure sensor 11 and the signal acquisition circuit module 12 is one. The output terminal of the strain-pressure sensor 11 is electrically connected to the signal acquisition circuit module 12. The signal acquisition module 1 is attached to the skin near the heart. The first fourth-order Butterworth bandpass filter algorithm performs zero-phase filtering on the first digital signal, and the second fourth-order Butterworth bandpass filter algorithm performs zero-phase filtering on the second digital signal. The peak detection algorithm performs peak detection on the first and second digital signals after zero-phase filtering to obtain respiratory rate monitoring values ​​and heart rate monitoring values, respectively. The result analysis algorithm matches the respiratory rate monitoring values ​​and heart rate monitoring values ​​with the database and outputs information such as the user's deep and shallow respiratory rates, blood oxygen assessment, and sleep apnea analysis.

[0070] Example 2

[0071] The monitoring method of the present invention, which uses a strain-pressure sensor-based monitoring device, includes the following steps: (See Example 1 for details on the steps described).

[0072] S1. Place the signal acquisition module 1 onto the area to be monitored on the user's skin;

[0073] S2. Power on 121. Strain-pressure sensor 11 generates first resistance signal and second resistance signal according to different physiological states. Signal acquisition circuit module 12 outputs corresponding first digital signal and second digital signal based on the first resistance signal and the second resistance signal. The first digital signal and the second digital signal monitored in real time are transmitted to signal processing module 2 through wireless transmission.

[0074] S3, such as Figure 5 As shown, the first digital signal is subjected to zero-phase filtering by the first fourth-order Butterworth bandpass filtering algorithm in the signal processing module 2, and the second digital signal is subjected to zero-phase filtering by the second fourth-order Butterworth bandpass filtering algorithm in the signal processing module 2. A peak detection algorithm continuously counts the number of peaks in the first and second digital signals after zero-phase filtering within 30 seconds, and multiplies the peak count by 2 to obtain the respiratory rate monitoring value and heart rate monitoring value, respectively. A result analysis algorithm matches the respiratory rate monitoring value and the heart rate monitoring value with a database.

[0075] S4. The signal processing module 2 outputs the user's physiological information results.

[0076] By using a single strain-pressure sensor 11 to couple changes in skin strain and pressure caused by various physiological activities, and by analyzing characteristic parameters such as respiration, heart rate, and fetal movement through the signal processing module 2, the system simplifies the system structure, reduces hardware costs, and achieves multi-parameter collaborative monitoring. This helps to more comprehensively reflect the user's physiological state and significantly improves the real-time performance, continuity, comfort, and integration of physiological parameter monitoring while ensuring the accuracy and reliability of the monitoring data.

[0077] Furthermore, the content of step S3 is replaced as follows: S3, the first digital signal and the second digital signal are subjected to zero-phase filtering processing by the eighth-order Butterworth low-pass digital filtering algorithm in the signal processing module 2, and the first digital signal and the second digital signal are subjected to band-limited interpolation resampling, multi-scale moving average normalization processing, fixed window segmentation, dataset balancing processing and machine learning processing in sequence to obtain fetal movement information, and the fetal movement information is matched with the database.

[0078] In this embodiment, taking the example of a pregnant woman using the device in Example 1 to monitor the physiological state of the fetus, as shown below... Figure 6 As shown, the preprocessing procedure of the signal processing module 2 for the fetal movement monitoring signal is as follows: First, an 8th-order Butterworth low-pass digital filter with a cutoff frequency of 8Hz is used to perform low-pass filtering on the first digital signal and the second digital signal; the result analysis algorithm then resamples the signal to ensure that the sampling rate is consistently 50 Hz; the result analysis algorithm uses moving average normalization, and uses the values ​​calculated in the first 1, 3, and 5 seconds respectively to obtain the multi-scale Z-Score normalized features:

[0079] Z-Score normalized feature = (standardized sampling rate signal – local mean) / standard deviation, and the normalized results are concatenated into three-dimensional data; the result analysis algorithm uses a fixed window of 4 seconds to segment the three-dimensional data; finally, the result analysis algorithm counts the number of fetal movement samples N1 and the number of non-fetal movement samples N2. When the number of non-fetal movement samples N2 is much larger than the number of fetal movement samples N1, the cluster center downsampling method is used to select N1 representative samples from the non-fetal movement class to construct a class-balanced binary training dataset; the balanced dataset is input into a residual convolutional neural network for training and real-time analysis to obtain fetal movement information, and the fetal movement information is matched with the database to output the physiological state of the fetus in the uterus.

[0080] Example 3

[0081] The present invention provides a method for fabricating a strain-pressure sensor, comprising the following steps: fabricating a strain-pressure sensor 11 in a monitoring device based on a strain-pressure sensor as described in Example 1.

[0082] Step 1: Pour the Ecoflex solution into a groove mold and cure it to obtain a flexible substrate;

[0083] Step 2: Multi-walled carbon nanotube powder, ethyl acetate solution, and Ecoflex solution were prepared in different proportions and by different preparation methods to obtain a first carbon paste, a second carbon paste, and a conductive binder;

[0084] Step 3: The first carbon paste is printed onto the top surface of the flexible substrate using a template printing method to prepare the strain sensing layer 112;

[0085] Step 4: Immerse the model paper in the second carbon paste, remove it and cure it to obtain the pressure sensing layer 113;

[0086] Step 5: Fix the pressure sensing layer 113 to one side of the interdigitated electrode of the flexible circuit board 114. The flexible circuit board 114 is fixed and connected to the electrode of the strain sensing layer 112 by the conductive adhesive.

[0087] Step 6: Use Ecoflex solution as a flexible encapsulation layer 115 for encapsulation to prepare strain-pressure sensor 11.

[0088] Further, in step 2, the first carbon paste is prepared as follows: the carbon black powder and the multi-walled carbon nanotube powder are mixed at a mass ratio of 4:1, and then mixed with the ethyl acetate solution at a ratio of 1g / 35mL, wherein the mass ratio of the Ecoflex solution to the carbon black powder and the multi-walled carbon nanotube powder in the solution is 100:5; the second carbon paste is prepared as follows: the carbon black powder and the multi-walled carbon nanotube powder are mixed at a mass ratio of 4:1, and then mixed with the ethyl acetate solution at a ratio of 1g / 100mL, wherein the mass ratio of the Ecoflex solution to the carbon black powder and the multi-walled carbon nanotube powder in the solution is 100:3; the conductive binder is prepared as follows: the multi-walled carbon nanotube powder and the ethyl acetate solution are mixed at a ratio of 1g / 20mL, wherein the mass ratio of the Ecoflex solution to the multi-walled carbon nanotube powder in the solution is 100:7.

[0089] By precisely controlling the composition ratio, thickness, and microstructure morphology of strain-sensitive carbon paste and paper-based pressure-sensitive carbon paste, the prepared strain-pressure sensor 11 exhibits excellent and consistent comprehensive performance in terms of sensitivity, response linearity, repeatability, and hysteresis characteristics. This controllable manufacturing process effectively reduces the performance differences between individual strain-pressure sensors 11, improving the overall measurement reliability and data accuracy after integration into the monitoring device. This method can form an ultra-thin, stretchable sensitive functional layer and a flexible substrate structure, giving the strain-pressure sensor 11 excellent mechanical flexibility and conformability. This characteristic allows it to seamlessly conform to the curved surface of human skin and maintain a stable electrical response under repeated stretching and bending.

[0090] In this embodiment, the fabrication process of the strain-pressure sensor 11 module is as follows:

[0091] Step 1: Mix component A and component B of Ecoflex solution in a mass ratio of 1:1, stir magnetically for 15 minutes at a stirring speed of 500 rpm, degas in a vacuum chamber for 10 minutes at a vacuum degree of -80 kPa, then pour it into a 0.5 mm deep groove mold, pre-cur at room temperature for 30 minutes, and then place it in an oven at 80°C for 10 minutes to prepare the flexible substrate layer 111;

[0092] Step 2: Mix carbon black powder and multi-walled carbon nanotube powder at a mass ratio of 4:1, and then mix with ethyl acetate solution at a ratio of 1g / 35mL. First, magnetically stir for 30 minutes (500rpm) to allow the ethyl acetate solution to fully wet the multi-walled carbon nanotube powder. Then, sonicate in an ice-water bath for 30 minutes. Add Ecoflex solution, and mix components A and B of Ecoflex solution at a mass ratio of 1:1. The mass ratio of Ecoflex solution, carbon black powder and multi-walled carbon nanotube powder is 100:5. Sonicate again in an ice-water bath for 30 minutes to obtain the first carbon paste.

[0093] Step 3: Place a stainless steel mold with an octagonal pattern and a thickness of 0.2 mm on the prepared flexible substrate layer 111. Drop the first carbon paste onto the mold and use a scraper to scrape the carbon paste through the pores of the stainless steel mold onto the flexible substrate layer 111. The angle between the scraper and the mold is 45°. Then, place it in an oven at 80°C for curing for 12 hours. Remove it and peel the stainless steel mold off the flexible substrate layer 111 to prepare the strain sensing layer 112.

[0094] Step 4: Mix carbon black powder and multi-walled carbon nanotube powder at a mass ratio of 4:1, and then mix with ethyl acetate solution at a ratio of 1g / 100mL. First, magnetically stir for 30 minutes (500rpm) to allow the ethyl acetate solution to fully wet the multi-walled carbon nanotube powder. Then, sonicate in an ice-water bath for 30 minutes. Add Ecoflex solution, with a mass ratio of Ecoflex solution, carbon black powder and multi-walled carbon nanotube powder of 100:3. Sonicate again in an ice-water bath for 30 minutes to obtain the second carbon paste.

[0095] Step 5: Cut the model paper into circular pieces with a diameter of 1 cm, immerse the model paper in the second carbon paste, take it out after 1 minute, and put it in an oven at 80°C to cure for 12 hours to prepare the pressure sensing layer 113.

[0096] Step 6: Mix multi-walled carbon nanotube powder and ethyl acetate solution at a ratio of 1g / 20mL, stir magnetically for 30 minutes (500rpm), then add Ecoflex solution with a mass ratio of Ecoflex solution to multi-walled carbon nanotube powder of 100:7, and stir magnetically for another 15 minutes (1000rpm) to obtain the conductive binder.

[0097] Step 7: Place the pressure sensing layer 113 at the center of the strain sensing layer 112, place the flexible circuit board 114 with interdigitated electrodes on the pressure sensing layer 113, fix the exposed side of the interdigitated electrodes to the pressure sensing layer 113, use the conductive adhesive to bond the electrodes of the strain sensing layer 112 to the corresponding electrodes of the flexible circuit board 114, and place it in an oven at 80°C for 1 hour to cure.

[0098] Step 8: Mix components A and B of the Ecoflex solution in a 1:1 mass ratio, stir magnetically for 15 minutes at a stirring speed of 500 rpm, degas in a vacuum chamber for 10 minutes at a vacuum degree of -80 kPa, and then coat it onto the strain sensing layer 112, the pressure sensing layer 113, and the flexible circuit board 114 stacked on the flexible substrate layer 111 with a thickness of 0.5 mm. Place it in an oven at 80°C for 10 minutes to cure, thus preparing the strain-pressure sensor 11 module.

[0099] The specific embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the scope of protection of the present invention is not limited to the specific contents disclosed in the embodiments. Any simple variations based on the technical concept of the present invention should fall within the scope of protection of the present invention. Furthermore, the above-mentioned specific technical features can be combined in any suitable manner without conflict. To avoid redundancy, all combinations will not be listed here.

Claims

1. A monitoring device based on a strain-pressure sensor, characterized in that, It includes a signal acquisition module and a signal processing module. The signal acquisition module is attached to the area to be monitored on the user's skin, and the signal acquisition module and the signal processing module are wirelessly connected. The signal acquisition module includes at least one uniformly distributed strain-pressure sensor and at least one signal acquisition circuit module. The strain-pressure sensor is electrically connected to the signal acquisition module. The signal acquisition circuit module outputs corresponding first digital signal and second digital signal based on a first resistance signal and a second resistance signal. The first resistance signal is the resistance change value generated by the strain-pressure sensor according to the stretching and contraction of the skin in the user's monitoring area. The second resistance signal is the resistance change value generated by the strain-pressure sensor according to the pressure change of the strain-pressure sensor when the skin in the user's monitoring area jumps. The materials of the detection end of the strain-pressure sensor are strain-sensitive carbon paste material and paper-based pressure-sensitive carbon paste material; The signal processing module has either a "dual bandpass-peak detection" algorithm or a "fetal movement monitoring" algorithm. The "dual bandpass-peak detection" algorithm is used to obtain the user's continuous respiratory rate information and continuous heart rate information in real time based on the first digital signal and the second digital signal. The signal processing module matches the continuous respiratory rate information and continuous heart rate information with the database and outputs the user's respiratory-heartbeat joint monitoring results, deep and shallow respiratory rates, blood oxygen assessment, or sleep apnea analysis and other information results. The "fetal movement monitoring" algorithm is used to obtain fetal movement information in real time based on the first digital signal and the second digital signal. The signal processing module matches the fetal movement information with the database and outputs the physiological state of the fetus in the uterus.

2. The monitoring device based on a strain-pressure sensor according to claim 1, characterized in that, The strain-pressure sensor is composed of a flexible substrate layer, a strain sensing layer, a pressure sensing layer, a flexible circuit board, and a flexible encapsulation layer stacked sequentially. The monitoring end of the strain sensing layer is an open hollow polygon, and the monitoring end of the pressure sensing layer is a solid structure. The monitoring end of the pressure sensing layer is nested within the hollow region of the monitoring end of the strain sensing layer.

3. The monitoring device based on a strain-pressure sensor according to claim 2, characterized in that, The monitoring end of the strain sensing layer is a hollow octagonal structure with one side open; the monitoring end of the pressure sensing layer is a solid circle.

4. A monitoring device based on a strain-pressure sensor according to claim 2, characterized in that, The signal acquisition circuit module includes a power supply, a voltage regulator module, an FPC connector, several voltage divider resistors, and a control transmission unit. The power supply provides power to the circuit after modulation by the voltage regulator module. The strain-pressure sensor is connected to the circuit of the signal acquisition circuit module through the FPC connector. Each strain-pressure sensor in the circuit can form a strain detection loop and a pressure-transformer detection loop in parallel with the signal acquisition circuit module. The pressure-transformer detection loop is a closed loop formed by the voltage divider resistor and the pressure sensing layer connected in series. The control transmission unit is used to convert the first voltage signal and the second voltage signal into corresponding first digital signal and second digital signal and wirelessly transmit them to the signal processing module.

5. A monitoring device based on a strain-pressure sensor according to any one of claims 1 to 4, characterized in that, The "dual bandpass-peak detection" algorithm includes a first fourth-order Butterworth bandpass filtering algorithm, a second fourth-order Butterworth bandpass filtering algorithm, a peak detection algorithm, and a result analysis algorithm. The first and second fourth-order Butterworth bandpass filtering algorithms have different filtering bands. The first fourth-order Butterworth bandpass filtering algorithm is used to perform zero-phase filtering on the first digital signal, and the second fourth-order Butterworth bandpass filtering algorithm is used to perform zero-phase filtering on the second digital signal. The peak detection algorithm is used to perform peak detection on the first and second digital signals after zero-phase filtering to obtain respiratory rate monitoring values ​​and heart rate monitoring values, respectively. The result analysis algorithm is used to match the respiratory rate monitoring values ​​and heart rate monitoring values ​​with the database and output information such as the user's deep and shallow respiratory rates, blood oxygen assessment, and sleep apnea analysis results.

6. A monitoring device based on a strain-pressure sensor according to any one of claims 1 to 4, characterized in that, The "fetal movement monitoring" algorithm includes an eighth-order Butterworth low-pass digital filtering algorithm and a result analysis algorithm. The eighth-order Butterworth low-pass digital filtering algorithm is used to perform zero-phase filtering on the first digital signal and the second digital signal. The result analysis algorithm is used to process the data based on the filtered first digital signal and the second digital signal to obtain fetal movement information, and to match the fetal movement information with the database to output the physiological state of the fetus in the uterus.

7. A monitoring method for a monitoring device based on a strain-pressure sensor, characterized in that, The method includes a monitoring device based on a strain-pressure sensor as described in any one of claims 1 to 6, comprising the following steps: S1. Place the signal acquisition module onto the area to be monitored on the user's skin; S2. Turn on the power. The strain-pressure sensor generates a first resistance signal and a second resistance signal according to different physiological states. The signal acquisition circuit module outputs a corresponding first digital signal and a second digital signal based on the first resistance signal and the second resistance signal. The first digital signal and the second digital signal monitored in real time are transmitted to the signal processing module through wireless transmission. S3. The first digital signal is subjected to zero-phase filtering using the first fourth-order Butterworth bandpass filtering algorithm in the signal processing module, and the second digital signal is subjected to zero-phase filtering using the second fourth-order Butterworth bandpass filtering algorithm in the signal processing module. The peak detection algorithm continuously counts the number of peaks in the first and second digital signals after zero-phase filtering within 30 seconds, and multiplies the number of peaks by 2 to obtain the respiratory rate monitoring value and the heart rate monitoring value, respectively. The result analysis algorithm matches the respiratory rate monitoring value and the heart rate monitoring value with the database. S4. The signal processing module outputs the user's physiological information results.

8. The monitoring method of the monitoring device based on a strain-pressure sensor according to claim 7, characterized in that, Replace the content of step S3 with: S3, perform zero-phase filtering on the first digital signal and the second digital signal respectively using the eighth-order Butterworth low-pass digital filtering algorithm in the signal processing module, and perform band-limited interpolation resampling, multi-scale moving average normalization, fixed window segmentation, dataset balancing and machine learning processing on the filtered first digital signal and the second digital signal respectively to obtain fetal movement information, and match the fetal movement information with the database.

9. A method for manufacturing a strain-pressure sensor, characterized in that, The steps for preparing a strain-pressure sensor in a monitoring device based on a strain-pressure sensor as described in any one of claims 1 to 6 are as follows: Step 1: Pour the Ecoflex solution into a groove mold and cure it to obtain a flexible substrate; Step 2: Carbon black powder, multi-walled carbon nanotube powder, ethyl acetate solution, and Ecoflex solution are prepared in different proportions and by different preparation methods to obtain the first carbon paste, the second carbon paste, and the conductive binder. Step 3: The first carbon paste is printed onto the top surface of the flexible substrate using a stencil printing method to prepare a strain sensing layer; Step 4: Immerse the model paper in the second carbon paste, remove it and cure it to obtain the pressure sensing layer; Step 5: Fix the pressure sensing layer to one side of the interdigitated electrode of the flexible circuit board. The flexible circuit board is fixed and connected to the electrode of the strain sensing layer by the conductive adhesive. Step 6: Use Ecoflex solution as a flexible encapsulation layer for encapsulation to prepare a strain-pressure sensor.

10. A method for manufacturing a strain-pressure sensor according to claim 9, characterized in that, In step 2, the first carbon paste is prepared as follows: the carbon black powder and the multi-walled carbon nanotube powder are mixed at a mass ratio of 4:1, and then mixed with the ethyl acetate solution at a ratio of 1g / 35mL, wherein the mass ratio of the Ecoflex solution to the carbon black powder and the multi-walled carbon nanotube powder in the solution is 100:5; the second carbon paste is prepared as follows: the carbon black powder and the multi-walled carbon nanotube powder are mixed at a mass ratio of 4:1, and then mixed with the ethyl acetate solution at a ratio of 1g / 100mL, wherein the mass ratio of the Ecoflex solution to the carbon black powder and the multi-walled carbon nanotube powder in the solution is 100:3; the conductive binder is prepared as follows: the multi-walled carbon nanotube powder and the ethyl acetate solution are mixed at a ratio of 1g / 20mL, wherein the mass ratio of the Ecoflex solution to the multi-walled carbon nanotube powder in the solution is 100:7.

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