Control method and control system for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion

Abstract

This invention discloses a control method and control system for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion, relating to the fields of medical and nursing intelligent monitoring technology. The method uses the user's deep stillness state as the activation signal for acquiring biochemical parameter electrical signals for incontinence risk assessment. Specifically, when the user is determined to be in a deep stillness state, the third sensor unit is activated by combining the temperature and humidity parameters detected by the second sensor unit, and the biochemical parameter electrical signals are acquired. Compensation processing is performed based on the temperature parameters detected by the second sensor unit. The implementation of the third sensor unit activation mechanism can significantly reduce system energy consumption and effectively ensure contact between the detection electrodes and the liquid and body surface, thereby reducing signal noise. Combined with the temperature compensation mechanism, accurate detection of urine biochemical indicators is achieved. Furthermore, when used for incontinence risk assessment in sick infants, disabled individuals, and those experiencing dehydration or infection, the method can effectively improve the reliability of risk assessment.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology in medical and nursing care, and in particular to a control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion, and also to a control system for implementing the method. Background Technology

[0002] With the continuous development of medical and nursing technologies, specialized intelligent detection and analysis equipment has been developed and put into practical applications. Examples include diapers and incontinence pads equipped with sensors. These sensors are generally designed for alarm and parameter detection. Sensors designed for alarms can generate a "wet alarm" function after receiving a detection signal, allowing caregivers to promptly obtain information about the user's urination and change the nursing supplies accordingly, thereby improving user comfort and the quality of care. Sensors designed for parameter detection connect to intelligent detection devices, which process and analyze the detection signals to obtain biochemical parameters such as uric acid and electrolytes. These sensor-equipped nursing products are often used for sick infants, bedridden individuals unable to care for themselves, or the elderly. To improve the quality of treatment and care, the obtained biochemical parameters can be used for incontinence risk assessment. However, research has found that existing wearable sensors are prone to electrode interface displacement when the user turns over or moves their limbs, introducing severe motion artifact noise. Furthermore, the high power consumption of continuous sampling by multi-dimensional sensors makes it difficult to meet the long-lasting battery life requirements of button batteries. Specifically, the aforementioned facilities equipped with sensors currently in use mainly face the following technical problems: 1. The sensors used for detection have extremely high requirements for the stability of the electrode interface. When a user turns over or vibrates, the contact surface between the electrode and the skin or liquid will be displaced. Even if the displacement is very small, such as a micrometer-level displacement, the noise of the detected signal will be at least 10 times greater than the effective signal, which will reduce the accuracy of signal detection, increase the difficulty of subsequent processing, and reduce the reliability of the analysis results.

[0003] 2. Analyzing the sensor's detection signals requires the use of an electrochemical analog front-end chip connected to it. However, both consume a lot of power during signal transmission, and current detection signal transmission methods are either continuous or intermittent with fixed intervals. Furthermore, to ensure the comfort of using care products, button batteries are generally chosen as the power source. Button batteries have limited energy storage capacity, and the aforementioned frequent signal transmission means that button batteries can only guarantee continuous operation of various components for a few hours. Therefore, batteries need to be checked and replaced frequently, making it cumbersome and unreliable. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion that can control the transmission of detection signals in a timely manner, provide accurate detection data, have strong continuous working capability, and help improve the assessment results.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is: a control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion, comprising the following steps: SP1: Set the baseline value for determining the user's current motion status; Set the threshold for the rate of change of the user's microenvironment parameters; SP2: Continuously collect the user's motion data using the first sensing unit, and obtain the motion intensity index based on the motion data; The motion intensity index is compared with the state judgment benchmark value, and the user is currently in a state of deep stillness, micro-motion, or significant motion based on the comparison result. Proceed to the next step only if the user is determined to be in a state of deep stillness; SP3: Obtain the user's actual microenvironment parameters through the second sensing unit, and obtain the actual value of the microenvironment parameter change rate based on the actual microenvironment parameters; Compare the actual value of the microenvironment parameter change rate with the microenvironment parameter change rate threshold; Proceed to the next step only when the actual value of the microenvironment parameter change rate exceeds the microenvironment parameter change rate threshold; SP4 wakes up the third sensing unit to detect signals and obtain biochemical parameter electrical signals; SP5. The biochemical parameter electrical signals are compensated and calibrated, and the compensated and calibrated biochemical parameter electrical signals are used for incontinence risk assessment.

[0006] As a preferred technical solution, the state judgment benchmark value includes a lower limit benchmark value and an upper limit benchmark value. When the motion intensity index is less than the lower limit benchmark value for state judgment, it is determined that the user is currently in a state of deep stillness. When the lower limit benchmark value for state judgment is less than the exercise intensity index and the upper limit benchmark value for state judgment, it is determined that the user is currently in a micro-movement state. When the exercise intensity index is greater than or equal to the upper limit benchmark value for state judgment, the user is determined to be in a state of significant exercise.

[0007] As a preferred technical solution, when it is determined that the user is currently in a state of micro-movement or significant motion, or when the actual value of the change rate of the micro-environment parameter does not exceed the threshold of the change rate of the micro-environment parameter, a delayed retry strategy or a low confidence marking strategy is executed.

[0008] As a preferred technical solution, the first sensing unit includes an inertial measurement unit, and the motion data includes triaxial acceleration data obtained using the inertial measurement unit; The second sensing unit includes a temperature and humidity sensor, which is used to obtain the actual microenvironment temperature parameters and actual microenvironment humidity parameters of the user's body microenvironment. The third sensing unit includes a flexible electrochemical sensor array, which is used to detect and obtain biochemical parameter electrical signals by contacting the user's urine.

[0009] As a preferred technical solution, in step SP2, the formula for obtaining the exercise intensity index using the exercise data is: In the formula, I motion As an indicator of exercise intensity; 𝑊 is the set sliding time window length; 𝑎 𝑥 (𝑡), 𝑎 𝑦 (𝑡), 𝑎 𝑧 (x) represents the triaxial acceleration value at time x, in g. 𝑎̄ 𝑥 、𝑎̄ 𝑦 、𝑎̄ 𝑧 This represents the average triaxial acceleration within the sliding time window, expressed in g.

[0010] As a preferred technical solution, in step SP3, the actual microenvironment parameters include actual microenvironment temperature parameters and actual microenvironment humidity parameters; The threshold for the rate of change of microenvironment parameters is the threshold for the rate of change of microenvironment humidity parameters, and the actual value of the rate of change of microenvironment parameters is the actual value of the rate of change of microenvironment humidity parameters calculated based on the actual microenvironment humidity parameters.

[0011] As a preferred technical solution, in step SP4, the biochemical parameter electrical signal is denoised using a wavelet transform algorithm, and baseline drift caused by minute vibrations is eliminated using wavelet decomposition.

[0012] As an improvement to the above technical solution, in step SP5, the biochemical parameter electrical signal is calibrated with temperature compensation. The formula for the compensation calibration is as follows: In the formula, 𝐼 𝑐𝑎l𝑖𝑏𝑟𝑎𝑡𝑒d The calibrated current value; L 𝑚𝑒𝑎𝑠𝑢𝑟𝑒d The measured current value of the third sensing unit; 𝐸 𝑎 The activation energy of the biological enzymes used to detect the user's urine; R is the gas constant; 𝑇 𝑏𝑜d𝑦 The user's body surface temperature (Kelvin) is measured using the second sensor. 𝑇 𝑟𝑒𝑓 Standard calibration temperature (Kelvin).

[0013] The present invention also relates to a control system for implementing the above-described method for a non-invasive incontinence risk assessment based on multi-dimensional sensor fusion, comprising a main control chip, a power module connected to the main control chip, the signal output terminals of the first sensing unit and the second sensing unit respectively connected to the main control chip, the control terminal of the main control chip connected to a low-dropout linear regulator, the low-dropout linear regulator connected to an electrochemical simulation front-end chip, and the electrochemical simulation front-end chip further connected to the third sensing unit and the main control chip.

[0014] As an improvement to the above technical solution, the main control chip is pre-set with a state judgment benchmark value for determining the user's current motion state and a threshold value for the change rate of the user's micro-environment parameters.

[0015] Due to the adoption of the above technical solution, the present invention has the following beneficial effects: The user's deep stillness state is used as the activation signal for controlling the acquisition of biochemical parameter electrical signals for incontinence risk assessment. That is, when it is determined that the user has entered a deep stillness state, the third sensing unit is activated by combining the temperature and humidity parameters detected by the second sensing unit. The biochemical parameter electrical signals are acquired through the third sensing unit and compensated by combining the temperature parameters detected by the second sensing unit. The implementation of the third sensing unit activation mechanism can significantly reduce the system's energy consumption and effectively ensure the contact between the detection electrode and the liquid and body surface, thereby reducing signal noise. Combined with the temperature compensation mechanism, accurate detection of urine biochemical indicators can be achieved. Furthermore, when used for incontinence risk assessment in sick infants, disabled individuals, and those experiencing dehydration or infection, the reliability of the risk assessment can be effectively improved. Attached Figure Description

[0016] The accompanying drawings are intended only to illustrate and explain the present invention and do not limit the scope of the invention.

[0017] Figure 1 This is a structural block diagram of the control system according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the third sensing unit in an embodiment of the present invention; Figure 3 This is a timing diagram of the processing of acceleration, humidity signals, etc. in the control method of this embodiment of the invention; In the figure: 1-hydrophilic permeable layer; 2-microfluidic guiding layer; 3-flexible substrate layer; 4-electrochemical electrode; 5-liquid-absorbing and water-locking layer. Detailed Implementation

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the following detailed description, only certain exemplary embodiments of the invention are described by way of illustration. Undoubtedly, those skilled in the art will recognize that various modifications can be made to the described embodiments without departing from the spirit and scope of the invention. Therefore, the drawings and description are illustrative in nature and not intended to limit the scope of the claims.

[0019] like Figure 1 As shown, a non-invasive incontinence risk assessment control method based on multi-dimensional sensor fusion is used to timely activate and acquire biochemical parameters and electrical signals of urine, thereby reducing the energy consumption of related components and stabilizing effective contact between components and liquid / body surface during detection, thus reducing signal noise. Then, combined with a compensation mechanism, accurate detection of urine biochemical indicators is achieved. Finally, the detection data is used for incontinence risk assessment in sick infants and disabled individuals due to dehydration, infection, etc., effectively improving the reliability of risk assessment. The specific structure of the control system implementing the above control method includes a main control chip, which is the core processing unit of the system. It uses a low-power chip with wireless communication capabilities, such as a Cortex-M4 core series chip supporting Bluetooth 5.0, enabling external communication to transmit detection data and connect with external smart devices for display, alarm, and other functional expansion.

[0020] A power module, a first sensing unit, and a second sensing unit are connected to the main control chip. The main control chip receives and processes the detection signals from the first and second sensing units. A low-dropout linear regulator is connected to the control terminal of the main control chip. The low-dropout linear regulator is connected to an electrochemical simulation front-end chip, which is also connected to the third sensing unit and the main control chip. The power module can be a coin cell battery to provide power to the entire control system. The main control chip is used to wake up the third sensing unit in a timely manner based on the detection signals from the first and second sensing units.

[0021] The first sensing unit includes an inertial measurement unit, such as a miniature accelerometer or acceleration sensor; the second sensing unit includes a temperature and humidity sensor; and the third sensing unit includes a flexible electrochemical sensor array. Figure 2As shown, the flexible electrochemical sensor array is configured with several electrochemical electrodes 4 printed on a flexible substrate 3, and the flexible substrate 3 is provided with circuits that cooperate with the electrochemical electrodes 4. Depending on the different urine detection tasks, the electrochemical electrodes 4 are grouped and use different biological enzymes. During detection, the urine comes into contact with the flexible electrochemical sensor array and reacts with the biological enzymes on the electrochemical electrodes 4, ultimately obtaining the corresponding biochemical parameter electrical signals. The flexible substrate 3 with the electrochemical electrodes 4 is sandwiched within layers of different fabrics, such as... Figure 2 The fabric layers shown, from top to bottom, are a hydrophilic and liquid-permeable layer 1, a microfluidic guiding layer 2, a flexible base layer 3, and an absorbent and water-locking layer 5. These layers form an integrated fixed structure that can be made into diapers, incontinence pads, and other nursing products for use by people with disabilities.

[0022] In this embodiment, the main control chip communicates with the high-precision electrochemical simulation front-end chip (AFE) via a high-speed digital communication interface such as SPI or I2C bus. The interrupt pin of the electrochemical simulation front-end chip is connected to the external wake-up pin of the main control chip through the low-dropout linear regulator. Under this design, the control system enables the third sensing unit to operate in a hierarchical manner, with sleep and active modes. The power supply to the third sensing unit is no longer directly provided by the power module, but rather through a combination of the low-dropout linear regulator controlled by the main control chip and the electrochemical simulation front-end chip.

[0023] Specifically, in sleep mode, the main control chip controls the low-dropout linear regulator to shut down, and the current in the connection circuit between the third sensing unit and the electrochemical simulation front-end chip approaches 0 nA, causing the third sensing unit to enter a non-operating sleep state. When the main control chip determines that the third sensing unit needs to be activated based on the detection signals from the first and second sensing units, it raises the enable pin of the low-dropout linear regulator to power on and reset the electrochemical simulation front-end chip, applying a bias voltage to the detection electrode of the third sensing unit to wake it up and put it into operation. The weak signal collected by the third sensing unit in contact with urine is first sent to the electrochemical simulation front-end chip for amplification, filtering, and conditioning, and then converted from analog to digital before being sent to the main control chip for processing and analysis. The specific structures and interconnections of the main control chip, the low-dropout linear regulator, and the electrochemical simulation front-end chip, as well as the connection between the electrochemical simulation front-end chip and the third sensing unit, are beyond the scope of those skilled in the art and will not be described in detail here.

[0024] The specific process of the control method in this embodiment is as follows: SP1. Set the state judgment benchmark value for determining the user's current motion state; set the threshold value for the change rate of the user's micro-environment parameters. Both of these values ​​are set in the main control chip. The motion state mentioned in this embodiment is actually the user's activity state.

[0025] SP2. The system continuously collects the user's motion data using a first sensing unit and obtains a motion intensity index based on the motion data. The first sensing unit includes an inertial measurement unit, and the motion data includes triaxial acceleration data obtained using the inertial measurement unit, which is used to calculate the motion intensity index.

[0026] The calculated motion intensity index is compared with the state judgment benchmark value, and the user is determined to be in a state of deep stillness, slight movement, or significant movement based on the comparison result. Specifically, the state judgment benchmark value includes a lower limit benchmark value and an upper limit benchmark value. When the motion intensity index is less than the lower limit benchmark value, the user is determined to be in a state of deep stillness; when the lower limit benchmark value is less than or equal to the upper limit benchmark value, the user is determined to be in a state of slight movement; when the motion intensity index is greater than or equal to the upper limit benchmark value, the user is determined to be in a state of significant movement.

[0027] In this step, the lower limit benchmark value for state judgment is set to 0.05g, and the upper limit benchmark value for state judgment is set to 0.2g. To accurately quantify the user's motion state, this embodiment does not directly use the original acceleration value, but instead calculates the magnitude of the signal amplitude vector, or performs variance calculation. The formula for obtaining the motion intensity index using the motion data is as follows: In the formula, I motion As an indicator of exercise intensity; 𝑊 is the set sliding time window length; 𝑎 𝑥 (𝑡), 𝑎 𝑦 (𝑡), 𝑎 𝑧 (x) represents the triaxial acceleration value at time x, in g. 𝑎̄ 𝑥 、𝑎̄ 𝑦 、𝑎̄ 𝑧 This represents the average triaxial acceleration within the sliding time window, expressed in g.

[0028] Therefore, when I motion When the concentration is <0.05g, the user is considered to be in a state of deep stillness; when 0.05g ≤ I motionWhen the amount is <0.2g, the user is determined to be in a micro-motion state; when I motion When the amount is ≥0.2g, the user is considered to be in a state of significant motion.

[0029] Proceed to the next step only if the user is determined to be in a state of deep stillness. That is, when... I motion This method can only proceed when the concentration is <0.05g, because in this state, the electrochemical electrode 4 maintains stable contact with the skin and liquid, avoiding noise caused by electrode friction and displacement at the source of signal formation. This helps ensure the accuracy of signal detection and improves the reliability of the incontinence risk assessment results obtained using the detection signal. Therefore, this step essentially constitutes the first requirement for allowing the electrochemical simulation front-end chip to activate and scan the third sensing unit.

[0030] When it is determined that the user is currently in a state of slight movement or significant motion, a delayed retry strategy or a low-confidence marking strategy is executed. The delayed retry strategy involves controlling the first sensing unit to detect user activity signals and determine the status again after a certain interval (which can be set or adjusted by the main control chip). This helps reduce power consumption and extend the replacement interval of the power module. The low-confidence marking strategy aids in the training and learning of status judgment, improving the accuracy of subsequent status judgments. The specific implementation process of these two strategies is for those skilled in the art and will not be described in detail here.

[0031] SP3 acquires the user's actual micro-environment parameters through the second sensing unit, and obtains the actual value of the micro-environment parameter change rate based on the actual micro-environment parameters. Specifically, it is obtained by the main control chip through calculation and processing based on the detected actual micro-environment parameters and the commonly used change rate calculation formula.

[0032] The actual value of the microenvironment parameter change rate is compared with the microenvironment parameter change rate threshold. Only when the actual value exceeds the threshold does the process proceed to the next step. Therefore, this step essentially constitutes the second requirement allowing the electrochemical simulation front-end chip to activate and scan the third sensing unit. When the actual value does not exceed the threshold, a delayed retry strategy or a low-confidence marking strategy is executed. The purpose of strategy selection is consistent with the aforementioned purpose and will not be repeated here. Thus, the cooperation between the first and second sensing units effectively creates a "gated monitoring mode" in this embodiment.

[0033] The second sensing unit includes a temperature and humidity sensor, which is used to obtain the actual microenvironmental temperature and humidity parameters of the user's body microenvironment. In this step, the actual microenvironmental parameters include the actual microenvironmental temperature and humidity parameters. The threshold for the rate of change of the microenvironmental parameters is the threshold for the rate of change of the microenvironmental humidity parameters, and the actual value of the rate of change of the microenvironmental parameters is calculated based on the actual microenvironmental humidity parameters. When the actual value of the rate of change of the microenvironmental humidity parameters exceeds the threshold for the rate of change of the microenvironmental humidity parameters, it indicates that the second sensing unit has detected a rapid increase in ambient humidity, and the main control chip can then determine that the user is urinating and can activate the third sensing unit.

[0034] SP4 wakes up the third sensing unit to detect signals and obtain biochemical parameter electrical signals. The coordination relationship of each sensing unit is as follows: Figure 3 As shown, the third sensing unit only enters the working state when the signal of the first sensing unit is stable (i.e., the user is in a state of deep stillness) and the second sensing unit detects urination. The third sensing unit includes a flexible electrochemical sensor array, which detects and obtains the biochemical parameter electrical signals by contacting the user's urine. These signals are then transmitted by the electrochemical simulation front-end chip to the main control chip for processing and analysis.

[0035] In this step, the main control chip can use wavelet transform algorithm to denoise the biochemical parameter electrical signal and use wavelet decomposition to remove baseline drift caused by minute vibrations, thereby improving the accuracy of the detection signal.

[0036] SP5. The biochemical parameter electrical signals are compensated and calibrated. The compensated and calibrated biochemical parameter electrical signals are then used for incontinence risk assessment. This primarily involves temperature compensation calibration of the biochemical parameter electrical signals. The compensation calibration formula is as follows: In the formula, 𝐼 𝑐𝑎l𝑖𝑏𝑟𝑎𝑡𝑒d The calibrated current value; L 𝑚𝑒𝑎𝑠𝑢𝑟𝑒d The measured current value of the third sensing unit; 𝐸 𝑎 The activation energy of the biological enzymes used to detect the user's urine; R is the gas constant; 𝑇 𝑏𝑜d𝑦 The user's body surface temperature (Kelvin) is measured using the second sensor. 𝑇 𝑟𝑒𝑓 The standard calibration temperature (Kelvin) is typically 310.15 K, or 37 °C.

[0037] The reason for implementing the above-mentioned temperature compensation calibration for the biochemical parameter electrical signals is that the activity of biological enzymes such as uricase and glucose oxidase is greatly affected by temperature; typically, for every 1°C decrease, the current response decreases by 4–6%. 𝑎 The specific data needs to be set according to the specific biological enzyme. For example, when it is uricase, it is about 30-50 kJ / mol. This system can be preset to 42 kJ / mol (note that 𝐸 should be noted during calculation). 𝑎 (Matching with the unit energy level of 𝑅). Through the above temperature compensation algorithm, even if the user's body surface and surrounding temperature drop after urinating in winter, the detected biochemical indicators can be restored to the biochemical parameters under standard body temperature, avoiding misjudgment when applying them to incontinence risk assessment, thereby improving the accuracy of the assessment.

[0038] To verify the effectiveness of this embodiment, a test comparison was set up that included "continuous monitoring mode (existing technology)" and "gated monitoring mode (this embodiment)," as shown in Table 1.

[0039] Table 1 It is evident that this embodiment demonstrates outstanding performance in terms of energy consumption and false alarm rate.

[0040] This invention forms a multi-dimensional sensor through the first, second, and third sensing units. By fusing the signals and cooperating with other structures in the system, a "multimodal confidence gating" mechanism is effectively formed. Based on the signals from the first and second sensing units, dynamic and adaptive strategy selection is performed, which can effectively eliminate motion noise and significantly reduce the power consumption of the system. Combined with a temperature compensation algorithm, it achieves clinical-grade accurate detection of biochemical indicators such as uric acid and electrolytes, providing a reliable early warning of dehydration and infection risks for disabled individuals.

[0041] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion, characterized in that: Includes the following steps, SP1: Set the baseline value for determining the user's current motion status; Set the threshold for the rate of change of the user's microenvironment parameters; SP2: Continuously collect the user's motion data using the first sensing unit, and obtain the motion intensity index based on the motion data; The motion intensity index is compared with the state judgment benchmark value, and the user is currently in a state of deep stillness, micro-motion, or significant motion based on the comparison result. Proceed to the next step only if the user is determined to be in a state of deep stillness; SP3: Obtain the user's actual microenvironment parameters through the second sensing unit, and obtain the actual value of the microenvironment parameter change rate based on the actual microenvironment parameters; Compare the actual value of the microenvironment parameter change rate with the microenvironment parameter change rate threshold; Proceed to the next step only when the actual value of the microenvironment parameter change rate exceeds the microenvironment parameter change rate threshold; SP4 wakes up the third sensing unit to detect signals and obtain biochemical parameter electrical signals; SP5. The biochemical parameter electrical signals are compensated and calibrated, and the compensated and calibrated biochemical parameter electrical signals are used for incontinence risk assessment.

2. The control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in claim 1, characterized in that: The state judgment benchmark values ​​include a lower limit benchmark value and an upper limit benchmark value for state judgment; When the motion intensity index is less than the lower limit benchmark value for state judgment, it is determined that the user is currently in a state of deep stillness. When the lower limit benchmark value for state judgment is less than the exercise intensity index and the upper limit benchmark value for state judgment, it is determined that the user is currently in a micro-movement state. When the exercise intensity index is greater than or equal to the upper limit benchmark value for state judgment, the user is determined to be in a state of significant exercise.

3. The control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in claim 2, characterized in that: When it is determined that the user is currently in a state of micro-movement or significant motion, or when the actual value of the change rate of the micro-environment parameter does not exceed the threshold of the change rate of the micro-environment parameter, a delayed retry strategy or a low confidence marking strategy is executed.

4. The control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in claim 1, characterized in that: The first sensing unit includes an inertial measurement unit, and the motion data includes triaxial acceleration data obtained using the inertial measurement unit; The second sensing unit includes a temperature and humidity sensor, which is used to obtain the actual microenvironment temperature parameters and actual microenvironment humidity parameters of the user's body microenvironment. The third sensing unit includes a flexible electrochemical sensor array, which is used to detect and obtain biochemical parameter electrical signals by contacting the user's urine.

5. The control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in claim 1, characterized in that: In step SP2, the formula for obtaining the exercise intensity index using the exercise data is as follows: In the formula, I motion As an indicator of exercise intensity; 𝑊 is the set sliding time window length; a 𝑥 (t), a 𝑦 (t), a 𝑧 (t) is the three-axis acceleration value at time t, with units of g; ā 𝑥 ā 𝑦 ā 𝑧 is the mean value of the tri-axial acceleration in the sliding time window length, in g.

6. The control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in claim 1, characterized in that: In step SP3, the actual microenvironment parameters include the actual microenvironment temperature parameters and the actual microenvironment humidity parameters; The threshold for the rate of change of microenvironment parameters is the threshold for the rate of change of microenvironment humidity parameters, and the actual value of the rate of change of microenvironment parameters is the actual value of the rate of change of microenvironment humidity parameters calculated based on the actual microenvironment humidity parameters.

7. The control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in claim 1, characterized in that: In step SP4, the biochemical parameter electrical signal is denoised using a wavelet transform algorithm, and baseline drift caused by minute vibrations is eliminated using wavelet decomposition.

8. The control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in claim 6 or 7, characterized in that: In step SP5, the biochemical parameter electrical signal is calibrated with temperature compensation. The formula for the compensation calibration is as follows: In the formula, 𝐼 𝑐𝑎l𝑖𝑏𝑟𝑎𝑡𝑒d The calibrated current value; L 𝑚𝑒𝑎𝑠𝑢𝑟𝑒d The measured current value of the third sensing unit; 𝐸 𝑎 The activation energy of the biological enzymes used to detect the user's urine; R is the gas constant; 𝑇 𝑏𝑜d𝑦 The user's body surface temperature (Kelvin) is measured using the second sensor. 𝑇 𝑟𝑒𝑓 Standard calibration temperature (Kelvin).

9. A control system for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion, used to implement the control method for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in any one of claims 1 to 8, characterized in that: The device includes a main control chip, a power module connected to the main control chip, signal output terminals of the first sensing unit and the second sensing unit respectively connected to the main control chip, a low dropout linear regulator connected to the control terminal of the main control chip, the low dropout linear regulator connected to an electrochemical simulation front-end chip, and the electrochemical simulation front-end chip also connected to the third sensing unit and the main control chip respectively.

10. The control system for non-invasive incontinence risk assessment based on multi-dimensional sensor fusion as described in claim 9, characterized in that: The main control chip is pre-set with a state judgment benchmark value for determining the user's current motion state and a threshold value for the change rate of the user's micro-environment parameters.

Images