Liquid inlet amount control instrument for uremia hemodialysis

Abstract

The invention provides a liquid input control instrument for uremia hemodialysis. The liquid inflow control instrument for uremia hemodialysis comprises a pulse wave monitoring module used for monitoring the arterial pressure waveform of a patient and obtaining pulse wave data, a data input module used for inputting and storing individualized parameters of the patient, including the age, the gender, the height, the weight, the urine volume, the basic blood pressure and whether diabetes is combined or not, and a data processing unit used for processing the individualized parameters. And the processor is connected with the pulse wave monitoring module and the data input module. According to the liquid input control instrument for uremia hemodialysis, the liquid management capacity of a patient is remarkably improved, the pulse wave monitoring module and the data processing unit are integrated, the instrument can monitor the arterial pressure waveform of the patient in real time, hemodynamic parameters are accurately extracted, and then the stroke volume and cardiac output are evaluated.

Description

Technical Field

[0001] The invention relates to the technical field of uremic hemodialysis, in particular to a liquid input control instrument for uremic hemodialysis. Background Art

[0002] The fluid intake control instrument for uremia hemodialysis mainly consists of three parts: a fluid monitoring module, a data processing unit, and a warning system. The fluid monitoring module monitors the amount of fluid in the patient's body in real time through sensors, usually using bioimpedance or ultrasound technology. The data processing unit receives the monitoring data and analyzes and classifies the patient's fluid status according to the preset fluid volume classification standards (red card, yellow card, green card). The warning system uses color labels (red, yellow, green) to remind medical staff and patients based on the classification results to help control the patient's fluid intake.

[0003] Although the system aims to control the patient's fluid intake by grading the amount of fluid into red, yellow, and green cards, it still has some defects. Some uremia hemodialysis patients lack self-control ability, and repeated education has not been effective. Simply relying on the instrument's graded reminders may not be enough to change their behavior of excessive fluid intake. The hemodialysis room and the ward doctors are two sets of personnel, which may lead to unequal information on the patient's condition between different departments. Such information asymmetry will affect the overall management of the patient's fluid intake by medical staff and reduce the effectiveness of the system. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a fluid intake control instrument for uremia hemodialysis, which solves the problem that patients lack self-control ability and relying solely on the instrument's graded reminders may not be enough to change their excessive fluid intake behavior; the information asymmetry between the hemodialysis room and the ward doctors will affect the medical staff's overall management of the patient's fluid intake and reduce the effectiveness of the system.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a liquid intake control instrument for uremia hemodialysis, comprising:

[0006] A pulse wave monitoring module is used to monitor the patient's arterial pressure waveform and obtain pulse wave data;

[0007] The data input module is used to input and store the patient's individual parameters, including age, gender, height, weight, urine volume, basal blood pressure, and whether or not the patient has diabetes;

[0008] A data processing unit is connected to the pulse wave monitoring module and the data input module, and the data processing unit is configured as follows:

[0009] Analyzing the pulse wave data to extract arterial pressure waveform features;

[0010] Based on the characteristics of the arterial pressure waveform, the stroke volume (SV) and cardiac output (CO) were estimated using the following hemodynamic model:

[0011] Stroke volume (SV) formula:

[0012]

[0013] Where K is the proportionality coefficient, is the maximum rising rate of the pressure waveform, and Z is the characteristic impedance.

[0014] Cardiac output (CO) formula:

[0015] CO=SV×HR

[0016] Among them, HR is heart rate.

[0017] Characteristic impedance (Z) formula:

[0018]

[0019] Where ρ is the blood density, L is the arterial length, A is the arterial cross-sectional area, and the arterial cross-sectional area formula is:

[0020] A=π×r 2

[0021] Where r is the arterial radius, which is estimated based on the patient's blood pressure and individualized parameters, and the estimated stroke volume and cardiac output are compared with the patient's individualized reference range to monitor fluid loading;

[0022] The patient's body fluid status is divided into three levels: normal, warning and dangerous, and green, yellow and red labels are generated accordingly;

[0023] an alarm system connected to the data processing unit, and used to alert the patient and medical staff by visual and auditory means according to the liquid status indicator, so as to control the patient's liquid intake;

[0024] The communication module is used to transmit the patient's fluid status data and alarm information to the medical staff in the hemodialysis room and ward in real time to achieve information sharing;

[0025] A user interface module for patients and medical staff to interact, input data and view fluid status information;

[0026] The wearable housing integrates the above modules into a bracelet or other portable form, making it convenient for patients to carry and continuously monitor.

[0027] Preferably, the pulse wave monitoring module includes a photoplethysmographic pulse wave sensor and a pressure sensor for simultaneously acquiring volume changes and pressure waveforms. The data processing unit uses a pulse wave conduction velocity model, combined with the patient's blood pressure and degree of arteriosclerosis, to optimize the estimation of stroke volume and cardiac output. The PWV calculation formula is:

[0028]

[0029] Where D is the distance between the two measurement points, and Δt is the time difference between the pulse wave reaching the two points.

[0030] Preferably, the proportionality coefficient K is adjusted according to the following formula:

[0031] K=K0×(1+α×BMI+β×Age+γ×Diabetes)

[0032] Wherein, K0 is the initial coefficient, α, β, γ are weight coefficients, BMI is body mass index, Age is age, Diabetes is a binary variable (0 or 1) of combined diabetes, and the arterial length L and radius r are estimated according to the following formula:

[0033] Artery length formula:

[0034] L = k1 × height + k2

[0035] Among them, k1 and k2 are empirical coefficients.

[0036] Arterial radius (r) formula:

[0037]

[0038] Among them, k3 is the proportional coefficient, and the systolic and diastolic blood pressures come from the patient's basic blood pressure data.

[0039] Preferably, the data processing unit dynamically adjusts the individualized reference range R of the fluid load according to the patient's urine volume U and basal blood pressure:

[0040]

[0041] Among them, R0 is the standard reference range, δ is the adjustment coefficient, U norm Normal urine volume.

[0042] Preferably, the alarm system comprises:

[0043] Visual prompting devices, such as LED displays or indicator lights, used to display green, yellow, and red signs;

[0044] An auditory prompt device, such as a buzzer or voice prompt, is used to sound an alarm when the liquid state is abnormal. The communication module supports wireless communication protocols, including Bluetooth, Wi-Fi or cellular networks, to achieve remote transmission of data.

[0045] Preferably, the data processing unit has a historical data storage and analysis function for tracking the patient's fluid load change trend and using the following trend analysis formula:

[0046]

[0047] Where T(t) is the trend value of the average stroke volume at time t, SV i is the stroke volume measured for the i-th time, and N is the number of measurements.

[0048] Preferably, the historical data analysis results can generate a report for medical staff to refer to in order to adjust the treatment plan, and the user interface module allows medical staff to remotely set alarm thresholds and individualized reference ranges.

[0049] Preferably, the instrument includes a patient education module to provide personalized advice and educational content on fluid management to improve the patient's self-control ability, and the data processing unit uses a machine learning algorithm to continuously optimize the estimation model of stroke volume and cardiac output based on the patient's historical data and feedback, wherein the loss function is defined as:

[0050]

[0051] Among them, SV pred,i is the predicted stroke volume for the i-th time, SV true,i is the true value, n is the number of samples, λ is the regularization parameter, θ is the model parameter, and the machine learning algorithm uses the gradient descent method to minimize the loss function to update the model parameters:

[0052]

[0053] Wherein, η is the learning rate. The instrument is integrated with a mobile application software, and patients and medical staff can access fluid status data, receive alarms and communicate through mobile devices.

[0054] The present invention provides a liquid intake control instrument for uremia hemodialysis. It has the following beneficial effects:

[0055] The liquid intake control instrument for uremic hemodialysis of the present invention significantly improves the patient's liquid management ability. By integrating the pulse wave monitoring module and the data processing unit, the instrument can monitor the patient's arterial pressure waveform in real time, accurately extract hemodynamic parameters, and then evaluate the stroke volume and cardiac output. This precise monitoring method can timely identify the patient's liquid status and adjust the liquid intake reference range according to individualized parameters, ensuring that the patient will not take in excessive liquid due to insufficient self-control during the dialysis process, thereby reducing the risk of related complications.

[0056] The instrument also enables information sharing between medical staff and patients. Through the communication module, the patient's fluid status data is transmitted in real time to medical staff in the hemodialysis room and ward, ensuring that medical staff can grasp the patient's condition in a timely manner and make effective interventions. The alarm system ensures that both patients and medical staff can respond quickly through visual and auditory prompts, enhancing the effectiveness of the overall fluid management system. This information-based and intelligent fluid management solution not only improves the quality of medical services, but also provides a scientific basis for patients' health management, helping them to better participate in self-care. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a schematic diagram of the structure of the present invention;

[0058] Figure 2 It is a schematic diagram of the structure of the wearable shell of the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] like Figure 1-2 As shown, an embodiment of the present invention provides a liquid intake control instrument for uremia hemodialysis, including a pulse wave monitoring module for monitoring the patient's arterial pressure waveform and obtaining pulse wave data. The pulse wave monitoring module includes a photoelectric volumetric pulse wave sensor and a pressure sensor for simultaneously obtaining volume changes and pressure waveforms.

[0061] The data input module is used to input and store the patient's individual parameters, including age, gender, height, weight, urine volume, basal blood pressure, and whether or not the patient has diabetes. The data processing unit uses the pulse wave velocity model, combined with the patient's blood pressure and degree of arteriosclerosis, to optimize the estimation of stroke volume and cardiac output. The PWV calculation formula is:

[0062]

[0063] Where D is the distance between the two measurement points, and Δt is the time difference between the pulse wave reaching the two points.

[0064] The data processing unit is connected to the pulse wave monitoring module and the data input module, and the data processing unit is configured as follows:

[0065] Analyze the pulse wave data, extract the characteristics of the arterial pressure waveform, and the data processing unit dynamically adjusts the individualized reference range R of the fluid load according to the patient's urine volume U and basal blood pressure:

[0066]

[0067] Among them, R0 is the standard reference range, δ is the adjustment coefficient, U norm For normal urine volume, the data processing unit has historical data storage and analysis functions to track the patient's fluid load change trend and use the following trend analysis formula:

[0068]

[0069] Where T(t) is the trend value of the average stroke volume at time t, SV i is the stroke volume measured for the i-th time, and N is the number of measurements.

[0070] Based on the characteristics of the arterial pressure waveform, the stroke volume (SV) and cardiac output (CO) were estimated using the following hemodynamic model:

[0071] Stroke volume (SV) formula:

[0072]

[0073] Where K is the proportionality coefficient, is the maximum rising rate of the pressure waveform, and Z is the characteristic impedance.

[0074] Cardiac output (CO) formula:

[0075] CO=SV×HR

[0076] Where HR is the heart rate and the proportionality factor K is adjusted according to the following formula:

[0077] K=K0×(1+α×BMI+β×Age+γ×Diabetes)

[0078] Among them, K0 is the initial coefficient, α, β, γ are weight coefficients, BMI is body mass index, Age is age, Diabetes is a binary variable (0 or 1) with diabetes, and arterial length L and radius r are estimated according to the following formula:

[0079] Artery length formula:

[0080] L = k1 × height + k2

[0081] Among them, k1 and k2 are empirical coefficients.

[0082] Arterial radius (r) formula:

[0083]

[0084] Among them, k3 is the proportional coefficient, and the systolic and diastolic blood pressures come from the patient's basic blood pressure data.

[0085] Characteristic impedance (Z) formula:

[0086]

[0087] Where ρ is the blood density, L is the arterial length, A is the arterial cross-sectional area, and the arterial cross-sectional area formula is:

[0088] A=π×r 2

[0089] Where r is the arterial radius, which is estimated based on the patient's blood pressure and individualized parameters, and the estimated stroke volume and cardiac output are compared with the patient's individualized reference range to monitor fluid loading.

[0090] The patient's body fluid status is divided into three levels: normal, warning and dangerous, and corresponding green, yellow and red labels are generated.

[0091] The alarm system is connected to the data processing unit and is used to visually and audibly remind the patient and medical staff according to the fluid status mark to control the patient's fluid intake. The alarm system includes:

[0092] Visual prompting devices, such as LED displays or indicator lights, are used to display green, yellow, and red signs.

[0093] An auditory prompt device, such as a buzzer or voice prompt, is used to sound an alarm when the liquid state is abnormal, and the communication module supports wireless communication protocols, including Bluetooth, Wi-Fi or cellular networks, to achieve remote transmission of data.

[0094] The communication module is used to transmit the patient's fluid status data and alarm information to the medical staff in the hemodialysis room and ward in real time to achieve information sharing.

[0095] User interface module for patients and healthcare professionals to interact, input data and view fluid status information.

[0096] The wearable shell integrates the above modules into a bracelet or other portable form, which is convenient for patients to carry and continuously monitor. The historical data analysis results can generate reports for medical staff to refer to and adjust the treatment plan. The user interface module allows medical staff to remotely set alarm thresholds and individualized reference ranges. The instrument includes a patient education module to provide personalized advice and educational content on fluid management to improve the patient's self-control ability. The data processing unit uses a machine learning algorithm to continuously optimize the estimation model of stroke volume and cardiac output based on the patient's historical data and feedback, where the loss function is defined as:

[0097]

[0098] Among them, SV pred,i is the predicted stroke volume for the i-th time, SV true,i is the true value, n is the number of samples, λ is the regularization parameter, θ is the model parameter, and the machine learning algorithm uses the gradient descent method to minimize the loss function to update the model parameters:

[0099]

[0100] Where η is the learning rate. The instrument is integrated with mobile application software, and patients and medical staff can access fluid status data, receive alarms and communicate through mobile devices.

[0101] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A liquid intake control instrument for uremic hemodialysis, characterized in that: include: A pulse wave monitoring module is used to monitor the patient's arterial pressure waveform and obtain pulse wave data; The data input module is used to input and store the patient's individual parameters, including age, gender, height, weight, urine volume, basal blood pressure, and whether or not the patient has diabetes; A data processing unit is connected to the pulse wave monitoring module and the data input module, and the data processing unit is configured as follows: Analyzing the pulse wave data to extract arterial pressure waveform features; Based on the characteristics of the arterial pressure waveform, the stroke volume and cardiac output (CO) were estimated using the following hemodynamic model: Stroke volume formula: Where K is the proportionality coefficient, is the maximum rising rate of the pressure waveform, and Z is the characteristic impedance; Cardiac output (CO) formula: CO=SV×HR Among them, HR is heart rate; Characteristic impedance formula: Where ρ is the blood density, L is the arterial length, A is the arterial cross-sectional area, and the arterial cross-sectional area formula is: A＝π×r 2 Where r is the arterial radius, which is estimated based on the patient's blood pressure and individualized parameters, and the estimated stroke volume and cardiac output are compared with the patient's individualized reference range to monitor fluid loading; The patient's body fluid status is divided into three levels: normal, warning and dangerous, and green, yellow and red labels are generated accordingly; an alarm system, connected to the data processing unit, for visually and audibly reminding the patient and medical staff according to the liquid status indicator, so as to control the patient's liquid intake; The communication module is used to transmit the patient's fluid status data and alarm information to the medical staff in the hemodialysis room and ward in real time to achieve information sharing; A user interface module for patients and medical staff to interact, input data and view fluid status information; The wearable housing integrates the above modules into a bracelet or other portable form, making it convenient for patients to carry and continuously monitor.

2. The liquid intake control instrument for uremic hemodialysis according to claim 1, characterized in that: The pulse wave monitoring module includes a photoelectric volumetric pulse wave sensor and a pressure sensor, which are used to simultaneously obtain volume changes and pressure waveforms. The data processing unit uses a pulse wave conduction velocity model, combined with the patient's blood pressure and arteriosclerosis, to optimize the estimation of stroke volume and cardiac output. The PWV calculation formula is: Where D is the distance between the two measurement points, and Δt is the time difference between the pulse wave reaching the two points.

3. The liquid intake control instrument for uremic hemodialysis according to claim 1, characterized in that: The proportionality coefficient K is adjusted according to the following formula: K=K0×(1+α×BMI+β×Age+γ×Diabetes) Wherein, K0 is the initial coefficient, α, β, γ are weight coefficients, BMI is body mass index, Age is age, Diabetes is a binary variable of 0 or 1 for combined diabetes, and the arterial length L and radius r are estimated according to the following formula: Artery length formula: L = k1 × height + k Among them, k1, k2 are empirical coefficients; Arterial radius (r) formula: Among them, k3 is the proportional coefficient, and the systolic and diastolic blood pressures come from the patient's basic blood pressure data.

4. The liquid intake control instrument for uremic hemodialysis according to claim 1, characterized in that: The data processing unit dynamically adjusts the individualized reference range R of fluid load according to the patient's urine volume U and basal blood pressure: Among them, R0 is the standard reference range, δ is the adjustment coefficient, U norm Normal urine volume.

5. The liquid intake control instrument for uremic hemodialysis according to claim 1, characterized in that: The alarm system comprises: Visual prompting devices, such as LED displays or indicator lights, used to display green, yellow, and red signs; An auditory prompt device, such as a buzzer or voice prompt, is used to sound an alarm when the liquid state is abnormal. The communication module supports wireless communication protocols, including Bluetooth, Wi-Fi or cellular networks, to achieve remote transmission of data.

6. The liquid intake control instrument for uremic hemodialysis according to claim 1, characterized in that: The data processing unit has a historical data storage and analysis function for tracking the patient's fluid load change trend and using the following trend analysis formula: Where T(t) is the trend value of the average stroke volume at time t, SV i is the stroke volume measured for the i-th time, and N is the number of measurements.

7. The liquid intake control instrument for uremic hemodialysis according to claim 1, characterized in that: The historical data analysis results can generate a report for medical staff to refer to in order to adjust the treatment plan. The user interface module allows medical staff to remotely set alarm thresholds and individualized reference ranges.

8. The liquid intake control instrument for uremic hemodialysis according to claim 1, characterized in that: The instrument includes a patient education module that provides personalized recommendations and educational content on fluid management to improve the patient's self-control ability. The data processing unit uses a machine learning algorithm to continuously optimize the estimation model of stroke volume and cardiac output based on the patient's historical data and feedback, where the loss function is defined as: Among them, SV pred,i is the stroke volume predicted for the i-th time, SV true,i is the true value, n is the number of samples, λ is the regularization parameter, θ is the model parameter, and the machine learning algorithm uses the gradient descent method to minimize the loss function to update the model parameters: Wherein, η is the learning rate. The instrument is integrated with a mobile application software, and patients and medical staff can access fluid status data, receive alarms and communicate through mobile devices.

Images