Intelligent detection method for excretion of paper diaper and related device

Abstract

The application provides a diaper excretion intelligent detection method and related device, which is applied to a detection host of an intelligent nursing system, the intelligent nursing system further comprises a diaper, a cloud server and a user equipment, the detection host comprises a signal transmission module, a signal processing module and an alarm prompt module, the detection host is in communication connection with the diaper and the cloud server, and the method comprises the following steps: acquiring a first electric signal of the diaper in a preset time period through the signal transmission module; processing the first electric signal through the signal processing module to determine m voltage K lines, determining m excretion attribute information according to the m voltage K lines and determining m abnormal information, executing corresponding early warning prompt operation parameters according to the m abnormal information through the alarm prompt module, and sending the early warning prompt operation parameters to the cloud server and storing the early warning prompt operation parameters, so that the user equipment accesses the early warning prompt operation parameters in the cloud server. In this way, the user experience of the user of the diaper is improved, and the nursing cost of the user is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent nursing equipment, in particular to a urine intelligent detection method for a diaper and a related device. BACKGROUND

[0002] At present, the traditional nursing diaper only has a physical absorption function, which relies on physical absorption materials (such as super absorbent resin, non-woven fabric, etc.) to contain excrement, and has a wide range of uses for users such as infants, the elderly and the disabled, etc. Its core function is passive absorption, and it cannot actively monitor or prompt the existence and type of excrement. However, in clinical practice, users also have other needs when using the nursing diaper, for example, real-time perception of the excretion of urine and stool, and differentiation of the type of excrement (urine or stool). These needs restrict the cost of nursing and the experience of users.

[0003] Therefore, how to improve the user experience of the diaper user and reduce the nursing cost of the user needs to be solved. SUMMARY

[0004] The present application provides a urine intelligent detection method for a diaper and a related device, which improves the user experience of the diaper user and reduces the nursing cost of the user.

[0005] In a first aspect, the present application provides a urine intelligent detection method for a diaper, applied to a detection host of an intelligent nursing system, the intelligent nursing system further comprising a diaper, a cloud server and a user device, the detection host comprising a signal transmission module, a signal processing module and an alarm prompt module, the detection host being in communication connection with the diaper, and the cloud server being in communication connection with the detection host, and the method comprising:

[0006] acquiring a first electrical signal of the diaper in a preset time period through the signal transmission module;

[0007] processing the first electrical signal through the signal processing module to obtain n second electrical signals; n is an integer greater than 1;

[0008] determining m voltage K lines according to the n second electrical signals; m is an integer greater than 1 and less than n;

[0009] determining m excrement attribute information according to the m voltage K lines;

[0010] determining m abnormal information according to the m excrement attribute information;

[0011] executing corresponding early warning prompt operation parameters through the alarm prompt module according to the m abnormal information;

[0012] The pre-warning prompt operation parameter is sent to the cloud server and stored, so that the user equipment accesses the pre-warning prompt operation parameter in the cloud server.

[0013] In a second aspect, the embodiments of the present application provide a smart detection device for excretion of a diaper, which is applied to a detection host of an intelligent nursing system, the intelligent nursing system further comprising a diaper, a cloud server and a user equipment, the detection host comprising a signal transmission module, a signal processing module and an alarm prompt module, the detection host being in communication connection with the diaper, and the cloud server being in communication connection with the detection host, and the device comprising:

[0014] An acquisition unit is configured to acquire a first electrical signal of the diaper in a preset time period through the signal transmission module;

[0015] A control unit is configured to process the first electrical signal through the signal processing module to obtain n second electrical signals; n is an integer greater than 1.

[0016] A determination unit is configured to determine m voltage K lines according to the n second electrical signals; m is an integer greater than 1 and less than n; determine m excretion attribute information according to the m voltage K lines; and determine m abnormal information according to the m excretion attribute information.

[0017] A pre-warning unit is configured to execute corresponding pre-warning prompt operation parameters according to the m abnormal information through the alarm prompt module; and send the pre-warning prompt operation parameter to the cloud server and store it, so that the user equipment accesses the pre-warning prompt operation parameter in the cloud server.

[0018] In a third aspect, the embodiments of the present application provide an electronic device, comprising a processor, a memory, a communication interface and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program comprises instructions for executing steps in any method of the first aspect of the embodiments of the present application.

[0019] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, wherein the computer readable storage medium stores a computer program for electronic data exchange, and the computer program causes a computer to execute part or all steps described in any method of the first aspect of the embodiments of the present application.

[0020] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute part or all of the steps in any method described in the first aspect of the embodiments of the present application. The computer program product can be a software installation package.

[0021] By implementing the embodiments of the present application, the following beneficial effects are achieved:

[0022] The method and related device for excretion intelligent detection of a diaper described in the embodiments of the present application are applied to a detection host of an intelligent nursing system, the intelligent nursing system further includes a diaper, a cloud server and a user device, the detection host includes a signal transmission module, a signal processing module and an alarm prompt module, the detection host is in communication connection with the diaper, the cloud server is in communication connection with the detection host, and the method includes: acquiring a first electric signal of the diaper in a preset time period through the signal transmission module, processing the first electric signal through the signal processing module to obtain n second electric signals, determining m voltage K lines according to the n second electric signals, determining m excretion attribute information according to the m voltage K lines, determining m abnormal information according to the m excretion attribute information, executing corresponding early warning prompt operation parameters according to the m abnormal information through the alarm prompt module, sending the early warning prompt operation parameters to the cloud server and storing the early warning prompt operation parameters, so that the user device accesses the early warning prompt operation parameters in the cloud server. In this way, on the one hand, by actively sensing the excretion of defecation and urination in real time, the nursing staff or the user can be notified to replace the diaper in time, so as to avoid diaper rash, skin inflammation or skin infection caused by long-term contact of excretion with the skin, thereby improving the user experience of the user; on the other hand, by detecting whether the excretion is defecation or urination, whether the defecation and urination are normal is further identified, and the health detection is assisted to give the user a suggestion for diet, thereby reducing the nursing cost of the user. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0024] Figure 1 is an architecture diagram of an excretion intelligent detection system for a diaper provided by the embodiments of the present application;

[0025] Figure 2 is a structural schematic diagram of a diaper provided by the embodiments of the present application;

[0026] Figure 3 is another structural schematic diagram of a paper diaper provided by an embodiment of the present application;

[0027] Figure 4 is a hierarchical schematic diagram of a paper diaper provided by an embodiment of the present application;

[0028] Figure 5 is a structural schematic diagram of an electronic device provided by an embodiment of the present application;

[0029] Figure 6 is a flow schematic diagram of a method for intelligent detection of excrement of a paper diaper provided by an embodiment of the present application;

[0030] Figure 7 is another flow schematic diagram of a method for intelligent detection of excrement of a paper diaper provided by an embodiment of the present application;

[0031] Figure 8 is a working flow schematic diagram of a method for intelligent detection of excrement of a paper diaper provided by an embodiment of the present application;

[0032] Figure 9 is a functional interaction relationship schematic diagram of a method for intelligent detection of excrement of a paper diaper provided by an embodiment of the present application;

[0033] Figure 10 is a functional module composition block diagram of a device for intelligent detection of excrement of a paper diaper provided by an embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor fall within the scope of protection of the present application.

[0035] The terms "first", "second", etc. in the specification and claims of the present application and in the above drawings are used to distinguish different objects, and are not used to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device.

[0036] It should be understood that the term "and / or" in this document merely describes an associated relationship between associated objects, which means that there can be three relationships, for example, A and / or B can represent the following three cases: A exists alone, A and B exist together, and B exists alone. In addition, the character " / " in this document represents an "or" relationship between the front and rear associated objects. "Multiple" in the embodiments of the present application means two or more.

[0037] The "at least one" or similar expressions in the embodiments of the present application refer to any combination of these items, including any combination of single item or multiple items, which means one or more, and multiple means two or more. For example, at least one of a, b or c can represent the following seven cases: a, b, c, a and b, a and c, b and c, a, b and c. Wherein, each of a, b and c can be an element or a set containing one or more elements.

[0038] The "connection" appearing in the embodiments of the present application means direct connection or indirect connection and various connection modes to realize communication between devices, which is not limited in the embodiments of the present application.

[0039] In this document, referring to "embodiments" means that the specific features, structures or characteristics described in conjunction with the embodiments can be included in at least one embodiment of the present application. The phrase appears at various places in the specification does not necessarily mean the same embodiment, nor is it an independent or alternative embodiment to other embodiments. The skilled person explicitly and implicitly understands that the embodiments described herein can be combined with other embodiments.

[0040] The related terms involved in the present application will be explained as follows:

[0041] Excreta: Excreta refers to the waste that cannot be utilized or is redundant after the metabolic process in the body, which is discharged out of the body through a specific organ or system. In humans, excreta mainly includes feces, urine, carbon dioxide and sweat. In the embodiments of the present application, excreta mainly refers to feces (feces) and urine (urine).

[0042] Electrical conductivity: Electrical conductivity, also known as conductivity, is the inverse of resistivity, which represents the ability of a material to conduct current and is an inherent property of the material.

[0043] Currently, the traditional nursing diaper only has a physical absorption function, which relies on physical absorption materials (such as super absorbent resin, non-woven fabric, etc.) to contain excrement, and has a wide range of uses for users such as infants, the elderly and the disabled, and the core function is passive absorption, which cannot actively monitor or prompt the presence and type of excrement. However, in clinical practice, users also have other needs when using nursing diapers, such as real-time sensing of the excretion of urine and stool, and distinguishing the type of excrement (urine or stool). These needs restrict the cost of nursing and the user experience.

[0044] To solve the above problems, the embodiments of the present application provide a kind of excrement intelligent detection method and related device for diaper, applied to the detection host of intelligent nursing system, the intelligent nursing system also includes diaper, cloud server and user equipment, the detection host includes signal transmission module, signal processing module and alarm prompt module, the detection host is connected with diaper, cloud server and detection host are connected by communication, wherein a kind of excrement intelligent detection method for diaper includes: first electrical signal of diaper in preset time period is obtained by signal transmission module, first electrical signal is processed by signal processing module, and n second electrical signal is obtained, m voltage K line is determined according to n second electrical signal, m excrement attribute information is determined according to m voltage K line, m exception information is determined according to m excrement attribute information, and corresponding early warning prompt operation parameter is executed according to m exception information by alarm prompt module, early warning prompt operation parameter is sent to cloud server and is stored, so that user equipment accesses early warning prompt operation parameter in cloud server. In this way, on the one hand, by real-time active sensing of the excretion of urine and stool, nursing staff or users can be notified to replace in time, diaper rash, skin inflammation or skin infection caused by long-term contact of excrement with skin can be avoided, and the user experience of users is improved. On the other hand, by detecting whether excrement is stool or urine, whether urine and stool are normal can be further identified, which can assist health detection to give users dietary suggestions, thereby reducing the nursing cost of users.

[0045] The following will be described in combination with Figure 1 The system architecture of the excrement intelligent detection method for diaper in the embodiments of the present application will be described, Figure 1 It is the architecture diagram of the excrement intelligent detection system for diaper provided by the embodiments of the present application, and the excrement intelligent detection system for diaper 100 includes diaper 110, detection host 120, cloud server 130 and mobile communication device 140.

[0046] The paper diaper 110 is used as a front-end sensing unit for intelligent detection of excretion, and is used for detecting excretion and transmitting a physical basis of an electrical signal. The paper diaper 110 is embedded with an electrode structure (a transmitting electrode and a receiving electrode). When there is excretion, the excretion fills the space between the electrodes, and the electrodes are turned on, thereby providing conditions for generation and detection of a subsequent electrical signal. The paper diaper 110 ensures that the possible excretion distribution area can be effectively covered, and in addition, the normal use performance (such as comfort and air permeability) of the paper diaper is avoided from being excessively affected.

[0047] For ease of understanding, please refer to Figure 2 , Figure 2 is a structural diagram of a paper diaper provided by the application. As can be seen, the electrode structure of the paper diaper mainly includes a connector, a transmitting electrode and a receiving electrode. The connector is a bridge for signal interaction between the entire electrode structure and a detection host, and is mainly used for input and output functions of an electrical signal. It can stably connect the signal transmission line of the detection host through a specific interface design (which can be a Type-C interface or a Micro-USB interface, and is not limited herein), and ensure efficient and error-free transmission of the electrical signal between the paper diaper electrode and the detection host. The transmitting electrode and the receiving electrode are arranged in parallel in the absorption area of the paper diaper, forming an electrical signal detection path. The transmitting electrode is responsible for transmitting a preset electrical signal (such as a low-frequency excitation signal) to the absorption area of the paper diaper. The amplitude, frequency and other parameters of the signal need to be set according to the excretion detection requirements. When excretion (feces or urine) occurs, the excretion will change the electrical properties such as electrical conductivity and dielectric constant between the electrodes, thereby affecting the transmission of the electrical signal, so that the electrical signal received by the receiving electrode changes accordingly. The receiving electrode is mainly used for collecting the electrical signal after the absorption area of the paper diaper. The receiving electrode has the characteristics of high sensitivity and low noise, and can accurately capture the subtle changes of the electrical signal, thereby providing reliable original signals for the subsequent detection host to distinguish the excretion type and judge the excretion state by analyzing the voltage K line and other characteristic parameters (such as peak time and decay amplitude).

[0048] For ease of understanding, please refer to Figure 3 , Figure 3is another structure schematic diagram of a paper diaper provided by the embodiment of the application, and it can be seen that the paper diaper mainly comprises a skin-friendly surface layer nonwoven fabric, a permeation notch, a surface layer nonwoven fabric, an ultrasonic bonding point and a conductive fiber line, and each part cooperates to guarantee the functions of excretion detection and comfortable wearing. The skin-friendly surface layer nonwoven fabric is the outermost structure in contact with the human body, and is prepared from a material that is soft, breathable and has good skin-friendliness. The function of the skin-friendly surface layer nonwoven fabric is mainly to provide a comfortable contact experience for the user, reduce skin friction and discomfort, and at the same time, the layer of nonwoven fabric needs to have a certain liquid permeation guiding ability, so that when excretion occurs, the liquid can be quickly permeated to the lower layer, avoiding the skin problems caused by the long-term residence of excretion on the surface layer, thereby avoiding causing skin inflammation and other diseases of the user. The permeation notch is regularly distributed between the skin-friendly surface layer nonwoven fabric and the surface layer nonwoven fabric, and its function is to further accelerate the permeation and diffusion of excretion. By setting the notch structure in the nonwoven fabric layer, the flow path of the liquid in the paper diaper can be changed, the contact area of the liquid and the lower layer of the absorption structure is increased, and the absorption efficiency and speed are improved. In addition, the permeation notch enables the excretion to act more uniformly and quickly on the conductive fiber line below, reduces the detection delay or error caused by uneven distribution of the liquid, and guarantees the timeliness and accuracy of the electrical signal detection. The surface layer nonwoven fabric serves as a support and auxiliary permeation layer. On the one hand, the surface layer nonwoven fabric is combined with the skin-friendly surface layer nonwoven fabric to form the surface layer structure of the paper diaper, and jointly undertakes the functions of liquid guiding and skin contact. On the other hand, the surface layer nonwoven fabric provides a carrier for the arrangement of the conductive fiber line. The ultrasonic bonding point is used to realize the connection and fixation of the multi-layer structure of the skin-friendly surface layer nonwoven fabric, the surface layer nonwoven fabric and the like. Compared with the traditional gluing or sewing method, the ultrasonic bonding has the advantages of no chemical pollution, high connection strength, good sealing performance and the like. In the paper diaper structure, the ultrasonic bonding point can ensure that the layers of nonwoven fabric are tightly combined to prevent displacement between the layers, and at the same time, avoid the irritation of chemicals such as glue to the skin. The conductive fiber line is the core component for realizing the electrical detection of excretion, and is distributed in the paper diaper structure in a double-layer surface. The function of the conductive fiber line is to build an electrical signal transmission path. When excretion permeates to this layer, the electrical characteristics (such as electrical conductivity) of the excretion will change the electrical signal transmission parameters (such as voltage attenuation) between the conductive fiber lines. The detection host can distinguish the type of excretion (feces or urine) and judge the state of the excretion (such as the consistency and concentration) by collecting the changes of the electrical signals on the conductive fiber line (such as analyzing the peak time and attenuation amplitude through the voltage K line).

[0049] For ease of understanding, please refer to Figure 4 , Figure 4A schematic diagram of a paper diaper provided by an embodiment of the present application can be seen, which presents a multi-layer coordinated design in structure to realize the function integration of excrement absorption, electrical detection and wearing comfort, mainly including a skin-friendly surface layer, a conductive fiber line, a non-woven fabric, a water-locking layer, a high-molecular water-absorption layer, a leakage-proof layer and the like, which are orderly arranged and functionally complementary. The skin-friendly surface layer as the outermost layer directly contacting the human body is designed in a double-layer surface, is made of soft, breathable and skin-friendly materials, mainly provides a comfortable contact experience for the wearer, reduces skin friction and irritation, and has a preliminary guiding effect of excrement penetration. When excrement (such as urine) is generated, the skin-friendly surface layer can quickly guide the liquid downward, avoiding the excrement staying on the surface for a long time to cause skin discomfort; the conductive fiber line is clamped between the double skin-friendly surface layers, which senses the electrical characteristic change caused by excrement, when excrement penetrates to the area, changes the electrical conductivity, dielectric constant and other parameters between the conductive fiber lines, and then makes the transmitted electrical signal fluctuate in a specific rule. The detection host can distinguish the excrement type and judge the excrement state by collecting the electrical signal change of the conductive fiber line; the conductive fiber line has good electrical conductivity and chemical stability to maintain stable electrical performance and ensure the reliability of the detection result; the non-woven fabric layer plays multiple roles in the paper diaper structure, on the one hand, as an intermediate transition layer, connects the skin-friendly surface layer, the water-locking layer, the high-molecular water-absorption layer and the like, assists liquid penetration and diffusion through its own fiber structure to improve absorption efficiency; on the other hand, provides physical support for the conductive fiber line, the water-locking layer and the like to ensure the stability of the structure of each layer and prevent displacement and deformation. The water-locking layer and the high-molecular water-absorption layer are the key to realize high-efficiency absorption of the paper diaper, the water-locking layer can quickly capture the penetrated liquid to prevent back seepage and keep the surface dry; the high-molecular water-absorption layer uses the high water absorption and water retention of the high-molecular material to fully absorb and fix the liquid, greatly improving the absorption capacity and water-locking capacity of the paper diaper; the leakage-proof layer is located at the bottom of the paper diaper structure and is made of waterproof and breathable materials, which mainly prevents excrement from leaking to protect external clothes or beds.

[0050] The detection host 120 is the core processing unit of the excretion intelligent detection system 100 for the diaper, which is used for key functions such as electric signal processing, analysis and operation, and instruction interaction. The electric signal receiving and rectifying module is used to receive the original electric signal from the electrode of the diaper 110. Since the electric signal transmitted by the diaper electrode often has problems such as unstable amplitude and noise interference, the module first performs voltage doubling processing on the signal, and then performs rectification processing to convert the alternating current signal into a direct current signal. At the same time, through the filter circuit, high-frequency noise and low-frequency drift components are removed. For example, a bridge rectifier circuit is used to realize full-wave rectification of the signal, and an RC filter circuit or an active filter circuit is used to filter the rectified signal, so that the electric signal input to the subsequent module has good stability and signal-to-noise ratio; the multi-channel signal sending module is mainly used for signal interaction between the diaper 110 electrode. According to the preset time sequence and frequency, the excitation signal is sent to different electrode channels, and the feedback signal is received at the same time. It uses multiplexing technology to detect multiple electrode channels in the same time period, greatly improving the efficiency and comprehensiveness of the detection. For example, through time division multiplexing, different electrode channels are allocated specific time slices in turn, low-frequency excitation signals are sent, and feedback voltage attenuation signals are collected synchronously, realizing rapid scanning detection of different areas of the diaper. The ADC (analog-to-digital conversion module) is used to convert the analog electric signal after rectification and filtering into a digital signal. It can select high-resolution (such as 12 bits and above) and high-speed ADC chips to ensure that the subtle changes of the electric signal can be accurately captured. The converted digital signal is transmitted to the single-chip microcomputer module. Based on the received digital signal, the single-chip microcomputer module performs a series of analysis and operation operations. On the one hand, it analyzes the time sequence of the signal and draws a curve of voltage change over time (i.e. voltage K line). By identifying the peak time, decay amplitude, decay rate and other characteristic parameters of the curve, the type of excretion (feces or urine) is distinguished, and the state of the excretion (such as the transparency of urine and the consistency of feces) is judged. The PWM module is mainly used to output controllable pulse signals, and cooperates with other modules to realize multiple functions. For example, in the electric signal excitation link, PWM technology can be used to generate low-frequency excitation signals with specific duty cycle and frequency, which are sent to the electrodes of the diaper 110 to meet the needs of signals in different detection scenarios. At the same time, the output intensity of the alarm prompt module can also be controlled. The PWM module can adjust the pulse width to accurately control the volume of the buzzer and the brightness of the LED lamp; the alarm and indication module is the direct medium for information interaction between the detection host 120 and the outside world (such as caregivers and wearers), which is used to issue intuitive alarm and indication signals when detecting abnormal excretion or specific state. The module integrates a buzzer, an LED indicator and other peripherals. When the single-chip microcomputer module determines that there is an excretion abnormality (such as abnormal transparency of urine and abnormal consistency of feces), the corresponding alarm action will be triggered.

[0051] In one possible embodiment, when the electrical signal transmitted by the diaper 110 is detected, the electrical signal receiving and rectifying module will preliminarily screen the signal according to the preset threshold range. If the signal amplitude exceeds the fluctuation range of the electrical signal that may be generated by normal physiological excretion, it is determined to be an interference signal, which is directly filtered to avoid invalid signals entering the subsequent processing flow, thereby improving the anti-interference ability and detection efficiency of the system. The multi-channel signal sending module dynamically adjusts the sending strategy of the multi-channel signal according to the size and electrode layout of the diaper 110. For baby diapers, considering that the amount of excretion is relatively small and the distribution range is limited, the scanning frequency of the multi-channel can be reduced to reduce system power consumption. For adult diapers, since the excretion situation in the use scenario is more complex, the scanning frequency and signal acquisition points can be increased to improve the detection accuracy. The specific scanning frequency is not limited here. When the single-chip microcomputer detects that the voltage K line reaches the peak at about 2.5 seconds and the decay amplitude is in the interval of 25% to 35% within 2 minutes, it is determined to be urine. If the peak time is about 8 seconds and the decay amplitude is less than or equal to 8%, it is determined to be stool. In addition, the single-chip microcomputer internally stores an excretion electrical signal characteristic database of different age groups and different health status populations. After receiving the current detected digital signal, it will automatically compare and match the data in the database to achieve more accurate attribute judgment and health status auxiliary analysis of excretion. For example, for baby diaper detection, if the matched electrical signal mode matches the diarrhea characteristics, it will be marked as abnormal in time and the alarm will be triggered preferentially. The PWM module cooperates with the single-chip microcomputer module to dynamically adjust the PWM signal parameters according to the abnormal level obtained by the single-chip microcomputer analysis. For example, the abnormal level is divided into mild, moderate, and severe, corresponding to different PWM duty cycle and frequency combinations to achieve differentiated and intelligent control of alarm prompts.

[0052] The cloud server 130 is configured to receive various data uploaded from the detection host 120, including raw electrical signal data, excretion attribute information after analysis and processing, abnormal information, and pre-warning prompt operation parameters, and store them in a long-term and safe manner according to a standardized data format and storage strategy. The cloud server 130 can adopt a distributed storage architecture and can store data according to types, generation time, and associated devices, and has a data backup and disaster recovery mechanism to ensure data integrity and reliability. In addition, the cloud server 130 has data processing and analysis capabilities and can use big data analysis and machine learning techniques to deeply mine massive excretion detection data. On the one hand, by analyzing historical data of the same device or the same user group, the change trend of excretion attributes can be mined to assist in judging the health status change of the wearer. On the other hand, the cloud server 130 can analyze user data of different regions, different age groups, and different health statuses to construct an excretion characteristic model and a health assessment system, thereby providing data reference for medical care, product research and development, and other fields.

[0053] The mobile communication device 140 is the main carrier for the nursing staff and the user to obtain the excretion detection information and perform interactive operation, and realizes visual presentation and remote control of the detection data. A special application program is installed on the mobile communication device 140, which serves as an interface for the user to interact with the system and has rich functional modules. It can include a data display module for receiving and displaying the excretion detection data from the cloud server 130 in real time, including excretion type, attribute parameters (such as urine transparency, stool consistency, density, etc.), detection time, etc., and presenting in the form of intuitive charts, text lists, etc., to facilitate the user to quickly understand the use state of the diaper and the excretion situation. The application program also includes individualized setting of the alarm reminding mode, and the user can select to turn on or turn off a certain reminding mode according to the own needs, and adjust the volume, vibration intensity and other parameters of the reminder. In addition, the APP of the mobile communication device 140 also supports remote management and control of the system. The user can access the cloud server 130 through the APP to set and adjust the working parameters of the detection host 120, such as modifying the frequency of the electric signal detection, adjusting the threshold of the abnormality judgment, configuring the rules of the alarm prompt, etc. The APP can also realize the query, export and analysis functions of the historical detection data, and the user can filter the data according to the time range, device number, etc., generate a data analysis report, and assist in health management and nursing decision-making.

[0054] In a possible embodiment, when the diaper 110 absorbs excretion (feces or urine), the internal electrode is conducted to generate an electric signal. After the electric signal is processed by the electric signal receiving and rectifying module of the detection host 120, the signal acquisition, conversion and analysis are performed by the multi-channel signal sending module in cooperation with the ADC and single-chip module. The single-chip module identifies the voltage K line and other characteristics to determine the type and attribute of the excretion, and determine whether there is an abnormality. If there is an abnormality, corresponding early warning prompt operation parameters are generated, local prompt is performed through the alarm and indication module, and the parameters are uploaded to the cloud server 130 for storage. The mobile communication device 140 accesses the cloud server 130 through the APP to obtain the detection data and early warning information, and realizes remote monitoring and management.

[0055] It can be seen that the excretion intelligent detection system 100 for the diaper cooperates with the diaper 110, the detection host 120, the cloud server 130 and the mobile communication device 140 to realize the precision, intelligence and convenience of excretion detection, and provides an innovative technical solution and application mode for the field of intelligent nursing, which is expected to play an important role in medical care and scene.

[0056] The following will be described in combination with Figure 5 The electronic device in the embodiment of the present application is described, Figure 5is a structural diagram of an electronic device provided in an embodiment of the present application, such as Figure 5 As shown, the electronic device 500 includes one or more processors 510, a memory 520, a communication interface 530 and one or more programs 521. The processor 510 is communicatively connected to the memory 520 and the communication interface 530 via an internal communication bus.

[0057] The processor 510 may be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, units, and circuits described in conjunction with the disclosure of this application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and so on. The communication unit may be a communication interface, a transceiver, a transceiver circuit, etc., and the storage unit may be a memory.

[0058] The memory 520 can be a volatile memory or a nonvolatile memory, or can include both volatile and nonvolatile memory. The nonvolatile memory can be a read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically EPROM (EEPROM), or flash memory, for example. The volatile memory can be a random access memory (RAM), which is used as the external cache. By way of example, and not limitation, a number of forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM). The RAM can also include a non-volatile memory, such as flash memory. The RAM allows for the fastest maximum access time to read or write data in the memory circuits. The memory circuits store application data that is processed by the application circuits 512. In addition, the application circuits 512 can further include a non-volatile memory, such as a ROM, EPROM, and EEPROM, for example. The non-volatile memory can also include a memory, such as a flash memory.

[0059] The one or more programs 521 stored in the memory 520 and configured to be executed by the processor 510 include instructions for performing any of the steps of one of the embodiments of the method for intelligent detection of excretion of a diaper.

[0060] It can be understood that the electronic device 500 can include more or fewer structural elements than those shown in the above structural block diagram, for example, a power module, a physical key, a Wi-Fi module, a speaker, a Bluetooth module, a sensor, a display module, and the like, which are not limited herein. It can be understood that the electronic device can be equipped with an architecture of the system for intelligent detection of excretion of a diaper as described above. Figure 1 The architecture of the system for intelligent detection of excretion of a diaper.

[0061] After understanding the software and hardware architecture of the present application, the following will be combined with the description of the method for intelligent detection of excretion of a diaper. Figure 6 The method for intelligent detection of excretion of a diaper is described below. Figure 6Fig. 1 is a flowchart of a urine intelligent detection method for a diaper provided by an embodiment of the present application. The method is applied to a detection host of an intelligent nursing system, the intelligent nursing system further comprising a diaper, a cloud server and a user device. The detection host comprises a signal transmission module, a signal processing module and an alarm prompt module. The detection host is in communication connection with the diaper, and the cloud server is in communication connection with the detection host. The method comprises the following steps:

[0062] In step S610, the first electrical signal of the diaper in a preset time period is acquired by the signal transmission module.

[0063] The first electrical signal refers to the electrical signal formed between the sending electrode and the receiving electrode in the diaper due to contact with the excrement. The signal is actively emitted by the frequency conversion electrical signal sending module in the signal transmission module and is conducted to the receiving electrode through the conductive fiber cotton thread in the diaper, and is the original data carrier for subsequent signal processing and excrement attribute identification. Since the composition and form of the excrement (urine, feces) are different, the conduction characteristics (attenuation amplitude, propagation speed) of different frequency bands of electrical signals are different, so the first electrical signal can objectively reflect the type and state characteristics of the excrement.

[0064] The preset time period is usually 1-2 minutes, which needs to be combined with the penetration and diffusion law of the excrement. On the one hand, the complete process of urine in the diaper from the contact surface layer to the water absorption layer is about 2 minutes, and the penetration and signal stabilization process of feces due to high viscosity are also within this time range, which can ensure that the complete time sequence characteristics of the signal from initial contact to stable attenuation are captured. On the other hand, if the time period is too short, the attenuation stage after the signal peak value may be missed, resulting in the inability to accurately extract the attenuation amplitude parameter; if the time period is too long, the signal tends to be stable after the water absorption layer is completely locked, which may cause data redundancy and increase the system processing load.

[0065] Specifically, the signal transmission module is composed of a variable frequency electric signal sending module and a signal receiving unit. The first electric signal is obtained by the variable frequency electric signal sending module transmitting the detection signal in the mode of "low frequency-high frequency alternation", that is, a group of low frequency signals (frequency range 1KHz~1MHz) are first transmitted, and a group of high frequency signals (frequency range 1.1MHz~12MHz) are transmitted after the signal is zeroed, and the cycle is repeated until the preset time period ends. Alternatively, the variable frequency electric signal sending module can transmit low frequency or high frequency signals alone or alternately and irregularly transmit low frequency and high frequency electric signals for single or multiple times, which is not limited herein. Among them, the low frequency signal is used to reflect the overall penetration speed of the excretion (because the low frequency signal has a large penetration depth, and the attenuation is mainly determined by the conductivity), and the high frequency signal is used to reflect the surface component characteristics of the excretion (because the high frequency signal has a small penetration depth, and the attenuation is more significantly affected by dielectric loss and particle scattering). The receiving electrode transmits the conducted electric signal to the receiving unit of the signal transmission module. The unit preliminarily amplifies and filters the signal to remove environmental electromagnetic interference (such as static signals generated by clothing friction), finally forms the first electric signal containing low frequency and high frequency components, and temporarily stores in the cache unit of the signal transmission module, waiting for subsequent processing.

[0066] It should be noted that in the process of obtaining the first electric signal, the following special cases and processing methods may exist: if the paper diaper does not contact the excretion, there is no conductive path between the sending electrode and the receiving electrode, at this time the first electric signal is a zero value or a noise signal close to zero, the signal transmission module will record this state and continuously monitor until a non-zero signal is detected to start timing; if the excretion only partially contacts the electrode (such as a small amount of urine not completely covering the conductive fiber cotton thread), it may cause the first electric signal to fluctuate, at this time the signal transmission module will reduce the influence of signal fluctuation on subsequent processing by emitting signals of the same frequency band multiple times and taking the average value; the contact state of the conductive fiber cotton thread (such as electrode displacement caused by paper diaper deformation) may affect the signal conduction efficiency, therefore the signal transmission module will monitor the initial impedance between the electrodes (impedance greater than 10MΩ in dry state) in real time, if the impedance is abnormal (such as less than 5MΩ), the signal is marked as "suspicious data", and is verified in combination with historical data in subsequent processing to ensure the reliability of the first electric signal.

[0067] Step S620, processing the first electric signal through the signal processing module to obtain n second electric signals; n is an integer greater than 1.

[0068] The second electric signal is a standardized electric signal obtained by processing the first electric signal and can be used for subsequent voltage K-line analysis. Since the first electric signal contains multiple frequency band components such as low frequency (1KHz-1MHz or 0.1KHz) and high frequency (1.1MHz or 12MHz), and the original signal is weak and susceptible to interference, it needs to be processed by the signal processing module to separate the effective signals of different frequency bands and eliminate noise. The value of n is related to the number of signal frequency bands and the sampling accuracy. For example, at least two second electric signals can be obtained after processing the low frequency and high frequency signals respectively, to ensure that the subsequent excrement properties can be analyzed based on different frequency band characteristics.

[0069] The signal processing target is to convert the original electric signal into a stable and quantifiable direct current voltage signal. The first electric signal is an alternating current signal, which needs to be converted into a direct current voltage by a voltage doubling rectifier module (composed of capacitors, resistors, diodes, etc.). At the same time, environmental electromagnetic interference and noise in the signal transmission process are removed through filtering processing, so that the characteristics of electric signals of different frequency bands are clearer.

[0070] Consistent with the above Figure 6 The embodiment one is shown in Figure 7 , Figure 7 is another flowchart of the excrement intelligent detection method for paper diapers provided by the embodiment of the present application. The signal processing module processes the first electric signal to obtain n second electric signals, which specifically includes the following steps:

[0071] S710, obtaining a reference electric signal of the paper diaper; the reference electric signal is an electric signal of the paper diaper detected by the detection host in a dry environment;

[0072] S720, performing difference operation according to the reference electric signal and the first electric signal to obtain a first difference electric signal;

[0073] S730, performing voltage doubling rectification processing on the first difference electric signal to obtain a first rectification electric signal;

[0074] S740, processing the first rectification electric signal according to a preset filtering method to obtain a first rectification filtering signal;

[0075] S750, sampling the first rectification filtering signal according to a preset sampling rate to obtain the n second electric signals.

[0076] The processing process of the signal processing module on the first electric signal aims to eliminate environmental noise, separate multi-band effective signals, and complete the conversion of analog signals to digital signals, providing standardized data for the subsequent extraction of voltage K lines. The first electric signal, as the original detection signal, contains low-frequency (1 KHz~1 MHz) and high-frequency (1.1 MHz~12 MHz) components, and is affected by factors such as diaper material and environmental electromagnetic interference, resulting in baseline drift and uneven signal attenuation. Through differential operation, rectification, filtering, and sampling, etc. processing, the invalid noise can be stripped, and the unique electric signal characteristics of the excrement (such as the low-frequency permeation speed characteristic and the high-frequency particle interface characteristic) can be retained, making the second electric signal quantifiable and comparable. The value of n is related to the number of frequency bands, sampling accuracy, and processing dimension of the first electric signal. Since the first electric signal contains two types of core frequency band signals, low-frequency and high-frequency, and each type of frequency band needs to be processed independently to retain its unique characteristics (such as low-frequency signals reflecting permeation speed and high-frequency signals reflecting particle size), therefore n is at least 2 (corresponding to low-frequency processed signal and high-frequency processed signal respectively).

[0077] Specifically, the acquisition of the reference electrical signal needs to be completed in the dry state when the diaper is not in contact with the excretion. Usually, the host automatically triggers the calibration process in the initial start-up stage, the transmitting electrode transmits a detection signal of a preset frequency band, the receiving electrode collects the signal strength when there is no excretion (at this time the signal should tend to be zero or be stable at a very low noise level, such as less than 0.01V), and the signal is stored as a reference value. The differential operation is realized by the hardware circuit or algorithm of the signal processing module, and the calculation formula is "first differential electrical signal = first electrical signal - reference electrical signal". Through the differential operation, the background noise (such as the inherent resistance noise of conductive fibers and environmental electromagnetic interference) can be effectively stripped, and only the electrical signal change caused by the contact of excretion is retained, so as to highlight the dynamic characteristics of the effective signal (such as the sudden rise of the signal when urine penetrates and the slow change of the signal caused by the difference in feces viscosity).

[0078] In step S630, m voltage K lines are determined according to the n second electrical signals; m is an integer greater than 1 and less than n.

[0079] Among them, the voltage K line refers to the voltage change curve formed by the second electrical signal in the time dimension, to reflect the characteristics of the excretion. Its essence is to quantize the voltage value in different time periods, present the dynamic change of the electrical signal in the form of a curve, and contain key parameters such as peak time, decay amplitude and stable value. These parameters are directly related to the type (urine or feces) and state (normal or abnormal) of the excretion. For example, the voltage K line corresponding to urine usually reaches the peak value at about 2.5 seconds, while the voltage K line corresponding to feces reaches the peak value at about 8 seconds, and the decay amplitudes of the two are significantly different (25-35% for urine and less than or equal to 6% or 8% for feces).

[0080] Wherein, the value of m is obtained according to the frequency band characteristics of the second electric signal and analysis, since the second electric signal contains two types of core signals of low frequency (1KHz~1MHz) and high frequency (1.1MHz~12MHz), and the low frequency signal mainly reflects the penetration speed of excrement (used to distinguish between types of stool), and the high frequency signal mainly reflects the surface composition and particle characteristics of excrement (used to identify the transparency of urine and the consistency of stool), therefore m is at least 2 (corresponding to low frequency voltage K line and high frequency voltage K line respectively).

[0081] In one possible embodiment, the determining of the m voltage K lines according to the n second electric signals specifically comprises the following steps:

[0082] 631, segmenting the target second electric signal according to a preset time interval to obtain p target signal sequences; the target second electric signal is any one of the n second electric signals; p is a positive integer greater than 1;

[0083] 632, extracting the average voltage of each target signal sequence in the p target signal sequences to obtain p average voltages;

[0084] 633, performing curve fitting operation on the p average voltages and the p target signal sequences with voltage as the vertical axis and time as the horizontal axis to obtain a first voltage K line;

[0085] 634, determining the slope corresponding to each signal sequence in the p target signal sequences to obtain p target voltage slopes;

[0086] 635, calculating each signal sequence in the p target signal sequences by Fourier transform to obtain p amplitude spectra corresponding to the p target signal sequences;

[0087] 636, performing time-frequency feature fusion on the p amplitude spectra and the p target voltage slopes according to a preset first formula to obtain p first fusion parameters;

[0088] 637, determining the voltage K line of the target second electric signal according to the p first fusion parameters and the first voltage K line.

[0089] The conversion of the second electrical signal into a voltage K-line is designed to preserve the temporal characteristics (e.g., peak onset time, decay rate) and frequency-band specificity (e.g., penetration dynamics in the low-frequency band, particle interface characteristics in the high-frequency band) of the fecal electrical signal. The voltage K-line is essentially a quantized curve of voltage per unit time. Its key parameters (e.g., peak time and decay amplitude) are essential for distinguishing fecal and urination types and abnormal states. First, segmented processing discretizes the continuous signal into analyzable time windows, capturing the dynamic changes during the initial contact phase (signal surge), mid-penetration phase (signal peak), and stable phase (signal decay). Next, average voltage calculation and curve fitting eliminate signal fluctuation noise, generating a smooth voltage curve. Furthermore, by extracting the slope and amplitude spectrum (the energy distribution of different frequency components obtained through Fourier transform corresponds to the particle scattering characteristics of high-frequency signals), and preserving multi-dimensional features through time-frequency fusion, the voltage K-line ensures that it reflects both the decay patterns in the temporal dimension and the component differences in the frequency band dimension.

[0090] Specifically, the preset first formula realizes the weighted fusion of the target voltage slope and the amplitude spectrum through the weight coefficients (α and β). For the second electrical signal in the low-frequency band (reflecting the penetration rate), the target voltage slope (such as the rising rate of the signal from the initial value to the peak value) is used to distinguish between urine and feces (the slope of urine is large and the slope of feces is small); for the second electrical signal in the high-frequency band (reflecting the interface characteristics of the particles), the amplitude spectrum (especially the energy attenuation of the high-frequency component) can better reflect the size of the feces particles (the larger the particles, the faster the high-frequency attenuation) or the transparency of urine (the lower the transparency, the stronger the high-frequency scattering and the lower the amplitude spectrum energy). By dynamically adjusting the weights, the first fusion parameter can retain the core features of signals in different frequency bands in a targeted manner, so that the final voltage K-line not only contains the temporal variation rules (such as peaking at 8 seconds and attenuation amplitude at 2 minutes), but also integrates frequency band-specific information. Among them, the preset first formula can be in the form of:

[0091]

[0092] in, For the The first fusion parameter, is the first weight coefficient, is the second weight coefficient, and , For the A target voltage slope, For the Amplitude spectrum, Indicates the characteristic frequencies, is the number of amplitude spectra.

[0093] Finally, the voltage value of each segment is calculated using the first formula and the K-line is reconstructed for subsequent abnormality detection.

[0094] In step S640, m pieces of excrement attribute information are determined according to the m pieces of voltage K lines.

[0095] The excrement attribute information is obtained by voltage K line feature analysis, and mainly includes excrement type (urine or stool), excrement state characteristics (for example, urine transparency, presence or absence of sediment, stool consistency), and the like. The time sequence characteristics (for example, peak time, decay amplitude) and frequency band characteristics (permeability speed reflected by low-frequency signals, particle interface characteristics reflected by high-frequency signals) in the voltage K line are key bases for determining these attributes. For example, if the voltage K line corresponding to the low-frequency signal has a feature of "peaking at about 2.5 seconds and decaying by 25-35% within 2 minutes", it can be determined as urine; if the voltage K line corresponding to the low-frequency signal has a feature of "peaking at about 8 seconds and decaying by less than or equal to 8% within 2 minutes", it can be determined as stool; and the voltage K line corresponding to the high-frequency signal can further identify urine transparency (the slower the decay rate, the higher the transparency) or stool consistency (the faster the decay rate, the larger the particle, and the thicker the stool) through the decay rate.

[0096] In one possible embodiment, the determining of the m pieces of excrement attribute information according to the m pieces of voltage K lines specifically includes the following steps.

[0097] 641. Determining m voltage decay parameters according to the m pieces of voltage K lines.

[0098] 642. Determining m excrement densities according to the m voltage decay parameters.

[0099] 643. Performing feature extraction on the m pieces of voltage K lines based on a preset feature extraction rule to obtain m feature vectors.

[0100] 644. Inputting the m feature vectors into a preset excrement attribute recognition model to obtain m first excrement attribute information.

[0101] 645. Determining the m pieces of excrement attribute information according to the m first excrement attribute information and the m excrement densities.

[0102] Among them, the precise identification of excrement attributes is realized by the multi-dimensional fusion of voltage attenuation characteristics and feature vectors. The voltage attenuation parameter is an index reflecting the conductivity characteristics and penetration law of excrement, which is directly related to the type and state of excrement. The density of excrement is positively correlated with the concentration (density) of solid particles in excrement according to the conductivity (such as the conductivity of feces is lower than that of urine, and the attenuation is slower), so the density can be inversely mapped by the attenuation parameter to distinguish excrement with similar characteristics (such as loose stool and a large amount of urine). The feature vector integrates the time sequence characteristics (peak time, attenuation rate) and frequency band characteristics (low frequency penetration speed, high frequency particle scattering characteristics) of the voltage K line, providing comprehensive input for the identification model. The preset model is trained based on a large amount of labeled data (such as voltage curves of different types and states of excrement), realizing the automatic mapping from features to attributes.

[0103] Among them, the dimension of the feature vector needs to include the "peak time difference" of the low frequency band (2.5s for urine and 8s for feces) and the amplitude spectrum attenuation rate of the high frequency band (such as the high frequency 12MHz signal attenuates faster when the feces particles are larger); the training data of the excrement attribute recognition model needs to cover excrement samples of different age groups (infants / elderly) and different health states (normal / abnormal) to improve the generalization ability of the model.

[0104] Specifically, the calculation method of the voltage decay parameter is: (peak voltage-steady voltage) / peak voltage x 100%. Wherein, the peak voltage is the maximum value in the voltage K line (such as 2.5V at 2.5s for urine, 1.66V at 8s for stool), and the steady voltage is the voltage at the end of the preset time period (such as the value after 2 minutes). Wherein, the decay parameter of low-frequency K line focuses on reflecting the difference of penetration speed (urine decays fast, parameter is large; stool decays slowly, parameter is small), and the decay parameter of high-frequency K line reflects the intensity of particle scattering (such as the larger the stool particles, the more obvious the high-frequency signal decay, the larger the parameter). The determination of the density of excrement is based on the preset "voltage decay parameter-conductivity-density" mapping table. First, the corresponding conductivity is queried through the decay parameter (such as low-frequency decay 25% corresponding to urine conductivity 10~20mS / cm, decay 5% corresponding to stool conductivity 2~5mS / cm), and then the density value is calculated according to the linear relationship between conductivity and density. The mapping table can be obtained through a large number of experiments, or can be obtained by machine learning method based on historical experimental data, or can be a statistical model based on a large number of samples, wherein the machine learning method can be a model based on convolutional neural network, or a model based on recurrent neural network, or a model based on long short-term memory neural network, which is not limited here. The feature extraction rule needs to include 3 types of features, including time sequence features (peak time, 2-minute decay amplitude, rising slope), frequency band features (low-frequency 1KHz signal duration, high-frequency 12MHz amplitude spectrum main peak frequency), and stability features (voltage fluctuation standard deviation, such as stool signal fluctuation less than or equal to 0.05V, urine signal fluctuation less than or equal to 0.1V). After normalization, the three types of features are combined to form a feature vector, which is then input into the excretion property recognition model. The excretion property recognition model adopts a machine learning model based on support vector machine, random forest, or a neural network-based model (such as a convolutional neural network model, an LSTM model, etc.). Wherein, the training data includes a large number of samples (including normal / abnormal excretions of infants / elderly people), and the labels include "urine / stool", "normal / abnormal". The model input is the feature vector, and the output is the first excretion property information. If the first property is urine and the density is greater than 1.025g / cm 3 , it is corrected as high-concentration urine; if the first property is stool and the density is less than 1.015g / cm 3 , it is corrected as thin stool (abnormal). The final output of the excretion property information includes type, state, key parameters (such as decay amplitude 28%, density 1.02g / cm 3 ), which provides a basis for subsequent abnormal judgment.

[0105] In one possible embodiment, the m voltage decay parameters are determined according to the m voltage K lines, specifically including the following steps:

[0106] 6411、extracting a target feature voltage parameter from a target voltage K-line; the target feature voltage parameter comprises: a target peak voltage, a target steady-state voltage; the target voltage K-line is any one of the m voltage K-lines;

[0107] 6412、obtaining a reference voltage parameter of a reference voltage K-line;

[0108] 6413、determining a reference steady-state voltage in the reference voltage parameter;

[0109] 6414、determining a voltage difference between the target steady-state voltage and the reference steady-state voltage;

[0110] 6415、determining a first voltage weight corresponding to the voltage difference based on a preset mapping relationship between voltage difference and steady-state voltage weight;

[0111] 6416、determining a second steady-state voltage according to the first voltage weight and the target steady-state voltage;

[0112] 3417、determining a first time length from the target peak voltage to the target steady-state voltage according to the target voltage K-line;

[0113] 6418、if the first time length is less than or equal to a preset first time threshold, determining a voltage decay parameter of the target voltage K-line according to the target peak voltage, the second steady-state voltage and the first time length;

[0114] 6419、if the first time length is greater than the first time threshold, taking a preset first parameter as the voltage decay parameter of the target voltage K-line.

[0115] The target peak voltage corresponds to the maximum signal value when the excrement first contacts the electrode, and its occurrence time (e.g. 2.5 seconds for urine and 8 seconds for feces) is a marker for distinguishing types. The target steady-state voltage is a stable value after a preset time period, reflecting the signal state after the excrement is absorbed or stably attached to the diaper, and the difference between the two is the basis for calculating the decay amplitude. Due to individual specificity, the reference voltage K-line is introduced to eliminate individual differences (e.g. conductivity differences between infant excrement and elderly excrement) and environmental interference (e.g. the influence of temperature on the signal of conductive fibers), and the calibration of the steady-state voltage improves the calculation accuracy. The mapping relationship between voltage difference and weight is used to correct the steady-state voltage deviation caused by diaper batch differences (e.g. resistance fluctuations of conductive fibers).

[0116] The first time threshold is set to a signal stabilization period of 1-2 minutes: when the first time length (peak to steady state) is ≤2 minutes, it indicates that the signal has completed a complete penetration-decay process, and the decay parameter calculated at this time can effectively distinguish the types of excreta; if the time length exceeds 2 minutes, the signal has tended to be stable (with a very small decay amplitude, such as ≤1%), and it is not meaningful to continue to calculate, so a preset first parameter is used to simplify the processing. In addition, the purpose of introducing the weight is to correct the steady-state voltage, because the high-frequency low-voltage signal has high attenuation, so the steady-state voltage is adjusted by the operation of the steady-state voltage and the weight to improve the measurement accuracy. The mapping relationship between the voltage difference and the steady-state voltage weight can be obtained through a large number of experiments, and is not limited here. For example, according to multiple measurements, it is found that the highest voltage value of feces is reached at about 8 seconds, and the voltage decay amplitude is within 8% within 2 minutes, wherein the original data of the feces detection is shown in Table 1:

[0117] Table 1 Original data of feces sample detection

[0118]

[0119] For example, according to multiple measurements, it is found that the highest value of urine is reached at 2.5 seconds, and the voltage decreases by 25-30% within 2 minutes, and the voltage value reaches the highest value at 2.5 seconds after the urine is saturated, and the voltage value decreases by 10-15% within 2 minutes, wherein the original data of the urine detection is shown in Table 2:

[0120] Table 2 Original data of urine sample detection

[0121]

[0122] Specifically, the extraction of the target characteristic voltage parameter is realized by detecting the ADC module of the host computer. The digital sampling data (sampling rate ≥ 24 MHz, meeting the high-frequency signal requirement) of the target voltage K line is traversed, and the maximum value is determined as the target peak voltage (accurate to 0.001 V), such as 2.5 V at 2.5 seconds in the urine K line. The voltage value at the end of the preset time period is taken as the target steady-state voltage, such as 1.55 V at 60 seconds in the urine. The reference voltage K line is derived from the standard sample library pre-stored in the detection host computer. The sample library contains average voltage curves of different types of excreta (normal urine, normal stool, abnormal urine, and abnormal stool), and the reference steady-state voltage is the voltage average of the standard sample at 2 minutes. The preset mapping relationship is a piecewise function. When the voltage difference is ≤0.03 V, the first voltage weight is equal to 0.1; when 0.03 V < difference ≤0.07 V, the weight is equal to 0.3; when the difference is >0.07 V, the weight is equal to 0.5. The second steady-state voltage = target steady-state voltage × (1-first voltage weight) + reference steady-state voltage × first voltage weight, for example, the second steady-state voltage corresponding to the difference of 0.05 V = 1.55 × 0.7 + 1.5 × 0.3 = 1.535 V, which is closer to the true steady-state value after correction. In order to make it clearer, an example is given below to illustrate: when the time length is ≤2 minutes, the decay parameter is (target peak voltage-second steady-state voltage) / target peak voltage × 100%, the decay parameter of urine is (2.5-1.535) / 2.5 × 100% ≈ 38.6%; the peak value of stool is 1.66 V, the second steady-state is 1.62 V, and the time length is 8 seconds (≤120 seconds), the decay parameter is (1.66-1.62) / 1.66 × 100% ≈ 2.4%. If the time length is >120 seconds, the preset first parameter (0.01%) is taken as the decay parameter, which corresponds to the state where the signal has stabilized.

[0123] In one possible embodiment, the determining of the m excrement densities according to the m voltage decay parameters specifically includes the following steps:

[0124] 6421、based on the mapping relationship between the preset voltage decay parameter and the excrement conductivity, determining the conductivity of the excrement corresponding to each of the m voltage decay parameters, to obtain m first excrement conductivities;

[0125] 6422、obtaining a historical excrement conductivity;

[0126] 6423、determining an error correction parameter of the excrement conductivity according to the historical excrement conductivity;

[0127] 6424、determining m second excrement conductivities according to the error correction parameter and the m first excrement conductivities;

[0128] 6425、determine the excrement density corresponding to each of the m second excrement conductivities based on a preset mapping relationship between excrement conductivity and excrement density, to obtain the m excrement densities.

[0129] wherein the voltage attenuation parameter is negatively correlated with the conductivity, and the conductivity is positively correlated with the excrement density, the attenuation parameter can be converted into the conductivity through the preset mapping relationship, and then the error caused by individual differences (such as the baseline difference of excrement conductivity of infants and the elderly) is corrected in combination with historical data, and finally the density value is obtained through the fixed correlation between the conductivity and the density. The mapping relationship between the voltage attenuation parameter and the conductivity is established based on a large number of sample experiments. The historical excrement conductivity should be derived from the historical data of the same user (such as the same old person or infant) stored in the cloud server, so as to eliminate the influence of individual metabolic differences (such as the change of urine concentration caused by diet) on the current measurement. The error correction parameter reflects the fluctuation range (such as the standard deviation or average deviation) of the historical data, ensures that the corrected conductivity is closer to the true value, and improves the detection accuracy.

[0130] Specifically, the preset voltage attenuation parameter and excrement conductivity mapping relationship is derived from the synchronous measurement of different types of excrement. For urine (normal / abnormal), feces (thin / normal / thick) samples, under the control of temperature (25℃±1℃) environment, synchronous record its voltage attenuation parameter (decay amplitude within 1~2 minutes) and conductivity (measured by portable conductivity meter, accuracy 0.1mS / cm), statistical analysis to establish the corresponding relationship. For example, the attenuation of urine is 28% corresponding to the conductivity of 15mS / cm, the attenuation of feces is 4% corresponding to the conductivity of 3mS / cm, stored in the local database of the detection host. When the input voltage attenuation parameter is input, the first excrement conductivity is obtained by looking up the table or interpolation calculation. The historical excrement conductivity is derived from the historical data of the same user stored in the cloud server, if it is a new user, the average conductivity data of the same group (such as the same age baby, the same health status of the elderly) is called. The data time span is 30 days, which ensures the coverage of different metabolic states, for example, the historical data of a certain old man, the normal urine conductivity is concentrated in 12-18mS / cm, and the normal feces is concentrated in 2-4mS / cm. The calculation of error correction parameter is based on the statistical characteristics of historical conductivity, if the standard deviation of historical data is σ (such as urine σ=2mS / cm), the error correction parameter k=σ / mean (such as the mean of 15mS / cm corresponds to k=0.13), which reflects the fluctuation degree of historical data. The greater the fluctuation, the stronger the correction, which is used to reduce the influence of accidental factors (such as the conductivity mutation caused by single diet anomaly) on the current measurement. The second conductivity=first conductivity×(1-k)+history mean×k. For example, the first conductivity is 18mS / cm (higher than the historical mean of 15mS / cm), k=0.13, then the second conductivity=18×0.87+15×0.13=17.46mS / cm, which not only retains the characteristics of the current measurement value, but also calibrates to the historical baseline to improve stability. The mapping relationship between excrement conductivity and density is based on the linear model established by experiment, density=0.005×conductivity+1.000 (unit: g / cm 3 ), which is fitted by measuring the density of samples with different conductivity. For example, the second conductivity 15mS / cm corresponds to density=0.005×15+1.000=1.075g / cm 3 (urine), 3mS / cm corresponds to density=0.005×3+1.000=1.015g / cm 3 (feces).

[0131] Step S650, determine m abnormal information according to the m excrement attribute information.

[0132] The excrement attribute information includes type, state parameters (such as urine transparency, stool consistency, density, etc.), and the abnormal information is a specific representation of the parameters exceeding the normal threshold. The type information (urine / stool) determined by the low-frequency signal provides the applicable normal range (such as the normal transparency of urine and the normal consistency standard of stool), and the surface characteristics (such as high-frequency attenuation anomaly caused by urine sediment and too large / too small stool particles) analyzed by the high-frequency signal provide specific abnormal judgment basis, and the combination of the two realizes accurate positioning of the abnormal information. The threshold of the normal range is set based on a large number of sample experiments, for example, "the voltage attenuation parameter of the high-frequency signal corresponding to the normal urine transparency is 10-15%, and the voltage attenuation parameter of the high-frequency signal >20% when abnormal", "the high-frequency signal attenuation rate corresponding to the normal stool consistency is 5-8% / min, and >10% / min when too thin", in addition, the abnormal information includes specific parameter values (such as "stool consistency deviates from the reference value by 30%"), which provides a quantitative basis for subsequent alarm prompts, and ensures that the protection personnel can quickly locate the problem.

[0133] In a possible embodiment, the determining m abnormal information according to the m excrement attribute information specifically includes the following steps:

[0134] 651、determining a target excrement type identifier in target excrement attribute information; the target excrement type identifier includes stool or urine; the target excrement attribute information is any one of the m excrement attribute information; the target excrement attribute information includes target transparency, target concentration and target consistency;

[0135] 652、determining target abnormal information according to the target excrement type identifier;

[0136] 653、wherein the determining target abnormal information according to the target excrement type identifier includes:

[0137] 654、if the target excrement type identifier is the urine, then obtaining the reference transparency and the reference concentration of the normal urine; when the target transparency is greater than the reference transparency and the target concentration is less than the reference concentration, generating the target abnormal information for representing the abnormality of the urine;

[0138] 655、if the target excrement type identifier is the stool, then obtaining the reference consistency of the normal stool; when the target consistency is less than or equal to the reference consistency, generating the target abnormal information for representing the abnormality of the stool.

[0139] The determination of the target excrement type identification (feces / urine) relies on the timing characteristics of the low-frequency signal analysis, and the type division is used for the relationship of subsequent abnormality judgment (abnormality of urine is related to transparency and concentration; abnormality of feces is related to dilution). The setting of normal reference value (reference transparency, concentration, and dilution) is based on experimental data and high-frequency signal characteristics. The reference transparency corresponds to the voltage attenuation parameter (normal urine transparency is high, high-frequency attenuation is slow, and the voltage attenuation parameter is 10-15%) of the high-frequency signal (such as 12 MHz). When the transparency is low, the voltage attenuation parameter is >20%. The reference concentration is related to the conductivity of the low-frequency signal (the normal urine concentration corresponds to the conductivity of 10-20 mS / cm, and when it is abnormal, it is <8 mS / cm or >25 mS / cm). The reference dilution corresponds to the particle scattering intensity of the high-frequency signal (the normal feces particles are uniform, the high-frequency attenuation rate is 5-8% / min, and when it is too dilute, the particle is small, and the attenuation rate is >10% / min).

[0140] Specifically, if the voltage K line reaches the peak at about 2.5 seconds and decays by 25-35% within 2 minutes, it is determined to be "urine"; if it reaches the peak at about 8 seconds and decays by ≤8%, it is determined to be "feces". When the type identification is "urine", the reference transparency and the reference concentration are called from the pre-stored standard library (the standard library is established based on the high-frequency signal characteristics of the urine of healthy people, such as the voltage attenuation parameter of 12 MHz signal in normal urine is 12%, and the concentration corresponds to the conductivity average of 15 mS / cm). The target transparency is calculated by the attenuation amplitude of the high-frequency signal (the smaller the attenuation, the higher the transparency), and the target concentration is converted by the conductivity of the low-frequency signal (the higher the conductivity, the greater the concentration). If the voltage attenuation parameter corresponding to the target transparency is >20% (i.e. the transparency is lower than the reference value), and the conductivity corresponding to the target concentration is <8 mS / cm (i.e. the concentration is lower than the reference value), the target abnormal information of "urine abnormality (suspected to contain precipitate, low concentration)" is generated. When the type identification is "feces", the reference dilution is determined based on the high-frequency signal attenuation rate (5-8% / min) of normal feces, and the target dilution is obtained by the particle scattering analysis of the high-frequency signal (the faster the attenuation, the smaller the particle, and the more dilute the feces). If the attenuation rate corresponding to the target dilution is >10% / min (i.e. the dilution is ≤ the reference dilution), the target abnormal information of "feces abnormality (suspected to be dilute)" is generated. The generation of abnormal information needs to include specific parameter values, and is synchronously associated with the characteristic segment of the voltage K line (such as the voltage fluctuation curve of the abnormal period), to provide traceable judgment basis for the subsequent alarm prompt module.

[0141] In step S660, the alarm prompt module executes corresponding pre-warning prompt operation parameters according to the m abnormal information.

[0142] The early warning prompt operation parameter needs to match the type and severity of the abnormal information, for example, the prompt mode and intensity corresponding to the abnormality of urine (such as reduced transparency) and the abnormality of stool (such as excessive thinness) are different, so as to ensure that the nursing personnel can quickly judge the emergency degree. The generation of the parameter needs to be combined with the hardware capabilities (such as a buzzer and an LED lamp) and communication functions (such as pushing a message to a mobile device) of the detection host, so as to meet the local real-time prompt and realize remote notification through a cloud server. The early warning prompt operation parameter can be a local sound and light alarm, or a remote message push (such as an APP notification and a short message), or a combination of the two, which is not limited herein. The prompt intensity is positively correlated with the severity of the abnormality; the prompt content needs to include key information (such as “abnormality of urine: low transparency” and “abnormality of stool: thin stool”), so as to facilitate quick understanding.

[0143] In step S670, the early warning prompt operation parameter is sent to the cloud server and stored, so that the user device accesses the early warning prompt operation parameter in the cloud server.

[0144] The early warning prompt operation parameter (such as an alarm type, a time, and an abnormality degree) is a key basis for nursing decision, and storage to the cloud server can realize long-term retention and multi-end access of data, solving the problems of limited local storage capacity and easy data loss. At the same time, as a data hub, the cloud server can integrate historical abnormal data (such as daily abnormal times and type changes) of the same wearer, providing a basis for health trend analysis.

[0145] It can be seen that, by means of the above-mentioned intelligent detection method for excretion of a diaper, applied to a detection host of an intelligent nursing system, the intelligent nursing system further comprises a diaper, a cloud server and a user device, the detection host comprises a signal transmission module, a signal processing module and an alarm prompt module, the detection host is in communication connection with the diaper and the cloud server, and the method comprises: acquiring, by means of the signal transmission module, a first electric signal of the diaper in a preset time period; processing, by means of the signal processing module, the first electric signal to determine m voltage K lines, determining m excretion attribute information according to the m voltage K lines and determining m abnormal information; executing, by means of the alarm prompt module, corresponding early warning prompt operation parameters according to the m abnormal information, and sending the early warning prompt operation parameters to the cloud server and storing, so that the user device accesses the early warning prompt operation parameters in the cloud server. In this way, the user experience of a user of the diaper can be improved and the nursing cost of the user can be reduced.

[0146] For ease of understanding, please refer to Figure 8 , Figure 8is a working flow diagram of a urine intelligent detection method for a diaper provided by the present application. It can be seen that the urine intelligent detection method for a diaper is based on a finite state machine architecture, from state transition, signal feature analysis, event type determination and human-computer interaction architecture, and realizes automatic detection and intelligent response of diaper urine signals through modular design. The method can realize low power consumption management, in addition, it can accurately distinguish the type and state of the excretion. Specifically, the initial state of the method includes two modes of sleep and start, and the state switching is realized by key operation. The key on can make it enter the start state from the sleep state, and the key off can make it return to the sleep state from the start state. In this way, the energy consumption can be reduced during the non-working period, and the device endurance can be prolonged. When the intelligent detection starts, it first enters the idle state, which is a ready state waiting for the appearance of the signal. Until the user starts the detection process through the key, the signal acquisition mechanism is triggered. The signal detection stage follows the timing logic of "rise-peak-fall" (i.e. voltage K line). The target signal voltage is collected in a timely manner. When the signal rises to the threshold value, it enters the step of waiting for the signal peak, and continues to detect for 6 seconds, and then determines that the signal appears and enters the "peak detected and stable" stage. During the continuous sampling process, if the current voltage value continuously exceeds the historical peak value and the difference is stable within a small threshold range (such as 50mV), it is determined that the peak value appears and is stable, and then enters the "fall time to signal fall" detection stage. In the signal feature analysis link, the falling percentage of the peak value and the current voltage is taken as the discrimination index, and the signal falling degree is divided into three intervals: when "fall" < 3% (proportion), it is determined as event A (such as defecation), and the voice prompt is triggered immediately, and after completion, it enters a 30-second waiting period; when "fall" > 70% (proportion), it is determined as event B (such as urination), and also waits for 30 seconds; when "fall" is 3% < fall < 70% (proportion), it is selected to continue to observe and keep a 30-second waiting state. Regardless of whether it is determined as event A, determined as event B or continues to observe, after the 30-second waiting period is over, the subsequent operation will be decided according to the current state. If the voice playback is completed and there is no new signal trigger, its state returns to the idle state waiting for the next detection request, or automatically enters the sleep state when there is no operation for a long time.

[0147] In addition, the method combines user interaction, signal acquisition and processing, intelligent discrimination, voice interaction and low-power management functions: key input (on / off key) processes on / off and detects start instructions, signal acquisition (achieved by detecting the host's electrical signal receiving rectifier module) is responsible for regularly sampling voltage and recording key time points, intelligent discrimination (achieved by a single-chip microcomputer module) classifies events by calculating the percentage of decline, voice interaction (achieved by an alarm and indication module) plays corresponding prompts according to the discrimination results, and the low-power management module optimizes energy consumption through sleep / wake control. The modules work together to ensure that in the portable health monitoring scenario, the properties of excreta can be accurately detected, and the user experience can be improved through intelligent interaction. On the one hand, the user experience of the user can be improved; on the other hand, through low-power control, the user's nursing cost is reduced.

[0148] For ease of understanding, please refer to Figure 9 , Figure 9is a functional interaction relationship diagram of a urine intelligent detection method for a diaper provided by the embodiment of the present application. It can be seen that the urine intelligent detection method for the diaper includes user interaction function, low-power management function, signal acquisition and processing function, intelligent discrimination function, and voice interaction function. The five functions realize complete functions from user instruction input to detection result output and interactive feedback through ordered operation calling and data flow, and build an intelligent urine detection method suitable for portable health monitoring needs. First, the user interaction function. User interaction serves as an interactive entrance with the user and is used for instruction input function, including two operations of "key KEY2 power on / off (provided on the diaper)" and "key KEY1 detection start (provided on the detection host)". Among them, "key KEY2 power on / off" provides basic power management instructions. The user can realize the switching from the sleep state to the start state or from the running to the sleep state through the key, which is the basic interaction point of controlling the energy consumption and working state of the device. "Key KEY1 detection start" triggers the entry into the urine detection process. When the user needs to monitor the state of the diaper, the key is pressed, and the subsequent signal acquisition and analysis tasks are started. Second, the low-power management function. When the user turns off the device through the key KEY2 or the system is not operated for a long time, the module responds to the instruction or automatically triggers to enter the sleep state, reduce the power consumption of the device during the non-working period, and prolong the endurance. When the key KEY2 is turned on or there is a detection demand trigger, the device can be awakened from the sleep state and return to the normal working mode. Through the precise sleep and wake-up control of the module, the system performance and energy consumption are balanced, and the device can have continuous working ability and effectively save energy in the portable use scenario. Third, the signal acquisition and processing function is mainly used for the detection host to receive the electric signal sent by the diaper. The single-chip module of the detection host collects and preliminarily processes the electric signal, including the operations of timing signal voltage acquisition, signal rising / peak / falling detection, and key time point and voltage recording in sequence. Among them, "timing signal voltage acquisition" samples the voltage signal of the corresponding detection part of the diaper according to the preset time interval, provides the original data source for subsequent analysis, and ensures that the dynamic changes of the signal during the generation of the urine can be captured. "Signal rising / peak / falling detection" identifies the characteristics of the collected voltage signal, judges whether the signal appears rising trend, reaches the peak value, and enters the falling stage, and mines the feature information related to the urine event by tracking these key change nodes of the signal. "Key time point and voltage recording" stores the important moments (such as the signal rising start time, peak value appearance time, and falling start time) and the corresponding voltage value in the signal change process, and provides the data basis containing time sequence and voltage characteristics for the intelligent discrimination module. Fourth, the intelligent discrimination function. Based on the data provided by the signal acquisition and processing, the event discrimination is performed, mainly including the operations of calculating the falling percentage and discriminating the event type.The "calculate the percentage of drop" is obtained by calculating the percentage of drop of the voltage according to the signal peak value and the current voltage value. The percentage of drop is a key indicator for distinguishing different excretion events (such as defecation, urination, etc.). According to the design of the peak value and the percentage of drop as the core judgment basis for signal feature analysis, the percentage of drop is accurately calculated to provide a quantitative reference for event type distinction. The "distinguish event type" classifies and identifies the excretion event occurring in the diaper according to the calculated percentage of drop, in combination with the preset threshold (such as the percentage of drop less than 3% being determined as a defecation event, more than 70% being determined as a urination event, etc.), and determines whether it is urination, defecation or other state, so as to realize the conversion from signal data to event type and provide the judgment result for the subsequent voice interaction module. The fifth is the voice interaction function, which is realized through the alarm and indication module. It is mainly used for detection result feedback function, including playing corresponding voice prompt and controlling the operation of playing interval and times. Among them, "playing corresponding voice prompt" calls the corresponding voice content (such as playing the urination prompt voice when detecting urination, playing the defecation prompt voice when detecting defecation) according to the event type output by the intelligent judgment module, feeds back the current state of the diaper to the user, realizes intelligent interaction, and improves the user experience. "Control the playing interval and times" manages the frequency and duration of voice playing, avoids excessive voice interference to the user due to frequent detection of the same event or misjudgment, and through reasonable control of the playing interval and times, ensures the effective transmission of information while taking into account the user experience, so that in the health monitoring scene, the detection result can be accurately fed back, and the user can be interacted in a friendly way.

[0149] The above mainly introduces the scheme of the embodiments of the present application from the perspective of the execution process of the method. It can be understood that the electronic device contains the hardware structure and / or software module corresponding to the execution of each function in order to realize the above functions. Those skilled in the art should easily realize that the units and algorithm steps of each example described in combination with the embodiments provided in the present text can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in hardware or computer software driven hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0150] The embodiments of the present application can divide the functional units of the electronic device according to the above method examples. For example, each functional unit can be divided according to each function, or two or more functions can be integrated in one processing unit. The integrated unit can be realized in the form of hardware or software functional unit. It should be noted that the division of the units in the embodiments of the present application is illustrative, and is only a logical function division. In actual implementation, there can be another division manner.

[0151] In the case of dividing each functional module according to each function, Figure 10 is a functional module composition block diagram of a urine intelligent detection device for a diaper provided by an embodiment of the present application. The urine intelligent detection device for the diaper is applied to a detection host of an intelligent nursing system. The intelligent nursing system further includes a diaper, a cloud server and a user device. The detection host includes a signal transmission module, a signal processing module and an alarm prompt module. The detection host is in communication connection with the diaper. The cloud server is in communication connection with the detection host. The urine intelligent detection device 1000 includes:

[0152] An acquisition unit 1010 is configured to acquire a first electrical signal of the diaper in a preset time period through the signal transmission module.

[0153] A control unit 1020 is configured to process the first electrical signal through the signal processing module to obtain n second electrical signals. n is an integer greater than 1.

[0154] A determination unit 1030 is configured to determine m voltage K lines according to the n second electrical signals. m is an integer greater than 1 and less than n. m pieces of excretion attribute information are determined according to the m voltage K lines. m pieces of abnormal information are determined according to the m pieces of excretion attribute information.

[0155] A warning unit 1040 is configured to perform a corresponding warning prompt operation parameter according to the m pieces of abnormal information through the alarm prompt module. The warning prompt operation parameter is sent to the cloud server and stored, so that the user device accesses the warning prompt operation parameter in the cloud server.

[0156] In a possible embodiment, the control unit, in the aspect of processing the first electrical signal through the signal processing module to obtain n second electrical signals, is specifically configured to:

[0157] Acquire a reference electrical signal of the diaper. The reference electrical signal is an electrical signal of the diaper detected by the detection host in a dry environment.

[0158] determine a first differential electrical signal by performing a differential operation on the reference electrical signal and the first electrical signal;

[0159] perform a voltage doubling rectification operation on the first differential electrical signal to obtain a first rectified electrical signal;

[0160] perform a filtering operation on the first rectified electrical signal according to a preset filtering method to obtain a first rectified and filtered signal;

[0161] sample the first rectified and filtered signal according to a preset sampling rate to obtain the n second electrical signals.

[0162] In a possible implementation, the determining unit 1030, in the determination of the m voltage K-lines according to the n second electrical signals, is specifically configured to:

[0163] segment the target second electrical signal according to a preset time interval to obtain p target signal sequences; the target second electrical signal is any one of the n second electrical signals; p is a positive integer greater than 1;

[0164] extract an average voltage of each of the p target signal sequences to obtain p average voltages;

[0165] perform a curve fitting operation on the p average voltages and the p target signal sequences with voltage as the vertical axis and time as the horizontal axis to obtain a first voltage K-line;

[0166] determine a slope corresponding to each of the p target signal sequences to obtain p target voltage slopes;

[0167] perform a Fourier transform on each of the p target signal sequences to obtain p amplitude spectrums corresponding to the p target signal sequences;

[0168] perform time-frequency feature fusion on the p amplitude spectrums and the p target voltage slopes according to a preset first formula to obtain p first fusion parameters;

[0169] determine a voltage K-line of the target second electrical signal according to the p first fusion parameters and the first voltage K-line.

[0170] In a possible implementation, the determining unit 1030, in the determination of the m excrement attribute information according to the m voltage K-lines, is specifically configured to:

[0171] determine m voltage decay parameters according to the m voltage K-lines;

[0172] determine m excrement densities according to the m voltage decay parameters; the greater the voltage decay parameter, the greater the excrement density.

[0173] perform feature extraction on the m voltage K-lines based on a preset feature extraction rule to obtain m feature vectors;

[0174] input the m feature vectors into a preset excrement attribute recognition model to obtain m first excrement attribute information;

[0175] determine the m excrement attribute information according to the m first excrement attribute information and the m excrement density.

[0176] In a possible implementation, the determination unit 1030, in the determination of the m voltage decay parameters according to the m voltage K-lines, is specifically configured to:

[0177] extract a target feature voltage parameter from a target voltage K-line; the target feature voltage parameter includes a target peak voltage and a target steady voltage; the target voltage K-line is any one of the m voltage K-lines;

[0178] obtain a reference voltage parameter of a reference voltage K-line;

[0179] determine a reference steady voltage in the reference voltage parameter;

[0180] determine a voltage difference between the target steady voltage and the reference steady voltage;

[0181] determine a first voltage weight corresponding to the voltage difference based on a preset mapping relationship between the voltage difference and a steady voltage weight;

[0182] determine a second steady voltage according to the first voltage weight and the target steady voltage;

[0183] determine a first time length from the target peak voltage to the target steady voltage according to the target voltage K-line;

[0184] if the first time length is less than or equal to a preset first time threshold, determine a voltage decay parameter of the target voltage K-line according to the target peak voltage, the second steady voltage, and the first time length;

[0185] if the first time length is greater than the first time threshold, determine a preset first parameter as the voltage decay parameter of the target voltage K-line.

[0186] In a possible implementation, the determination unit 1030, in the determination of the m excrement density according to the m voltage decay parameters, is specifically configured to:

[0187] determine, based on a preset mapping relationship between the voltage attenuation parameters and the conductivities of the excrements, the conductivity of the excrement corresponding to each of the m voltage attenuation parameters, to obtain m first excrement conductivities;

[0188] obtain a historical excrement conductivity;

[0189] determine an error correction parameter of the excrement conductivity according to the historical excrement conductivity;

[0190] determine m second excrement conductivities according to the error correction parameter and the m first excrement conductivities;

[0191] determine, based on a preset mapping relationship between the excrement conductivities and excrement densities, the excrement density corresponding to each of the m second excrement conductivities, to obtain m excrement densities.

[0192] In a possible embodiment, the determining unit 1030, in the aspect of determining m abnormal information according to the m excrement attribute information, is specifically configured to:

[0193] determine a target excrement type identifier in target excrement attribute information; the target excrement type identifier includes a stool or a urine; the target excrement attribute information is any one of the m excrement attribute information; the target excrement attribute information includes a target transparency, a target concentration and a target consistency;

[0194] determine target abnormal information according to the target excrement type identifier;

[0195] The determining target abnormal information according to the target excrement type identifier includes:

[0196] if the target excrement type identifier is the urine, obtain a reference transparency and a reference concentration of a normal urine; when the target transparency is greater than the reference transparency and the target concentration is less than the reference concentration, generate the target abnormal information for representing an abnormality of the urine;

[0197] if the target excrement type identifier is the stool, obtain a reference consistency of a normal stool; when the target consistency is less than or equal to the reference consistency, generate the target abnormal information for representing an abnormality of the stool.

[0198] It should be noted that the specific function implementation of the excrement intelligent detection device 1000 for the paper diaper is described above Figure 6The description of the urine intelligent detection method for the diaper shown, for example, the acquisition unit 1010 is used to realize the related content of executing S610, and the early warning unit 1040 is used to realize the related content of executing S660 and S670, and details are not repeated. Each unit or module in the urine intelligent detection device 1000 for the diaper can be combined into one or several other units or modules, or some of the units or modules can be further split into a plurality of units or modules with smaller functions to constitute, which can realize the same operation without affecting the implementation of the technical effects of the embodiments of the application. The above-mentioned units or modules are divided based on logical functions. In actual application, the function of one unit (or module) is realized by a plurality of units (or modules), or the functions of a plurality of units (or modules) are realized by one unit (or module).

[0199] It can be seen that the urine intelligent detection device for the diaper described in the embodiments of the present application is applied to a detection host of an intelligent nursing system, and the intelligent nursing system further includes a diaper, a cloud server and a user equipment. The detection host includes a signal transmission module, a signal processing module and an alarm prompt module. The detection host is in communication connection with the diaper, and the cloud server is in communication connection with the detection host. The device acquires a first electric signal of the diaper in a preset time period through the signal transmission module in the acquisition unit. The first electric signal is processed through the signal processing module in the control unit to obtain n second electric signals. N is an integer greater than 1. M voltage K lines are determined according to the n second electric signals through the determination unit. M is an integer greater than 1 and less than n. M pieces of excretion attribute information are determined according to the m voltage K lines. M pieces of abnormal information are determined according to the m pieces of excretion attribute information. The alarm prompt module in the early warning unit performs corresponding early warning prompt operation parameters according to the m pieces of abnormal information, and sends the early warning prompt operation parameters to the cloud server and stores them, so that the user equipment accesses the early warning prompt operation parameters in the cloud server, and the effect of improving the user experience of the user of the diaper and reducing the nursing cost of the user is realized.

[0200] The embodiments of the present application further provide a computer readable storage medium, wherein the computer readable storage medium stores a computer program for electronic data exchange, and the computer program causes a computer to execute part or all of the steps of any method described in the above method embodiments. The above computer includes an electronic device.

[0201] The embodiments of the present application further provide a computer program product, and the computer program product includes a non-transitory computer readable storage medium storing a computer program. The computer program is operable to cause a computer to execute part or all of the steps of any method described in the above method embodiments. The computer program product can be a software installation package, and the computer includes an electronic device.

[0202] It should be noted that, for the above-mentioned various embodiments, for the sake of simple description, they are all expressed as a series of action combinations. Those skilled in the art should know that the present application is not limited by the order of the described actions, because some steps in the embodiments of the present application can be performed in other orders or simultaneously. In addition, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions, steps, modules or units involved are not necessarily required in the embodiments of the present application.

[0203] In the above embodiments, the description of each embodiment of the embodiments of the present application has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0204] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by a computer program instructing relevant hardware to complete, and the program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. The storage medium mentioned above includes: ROM, random access memory (RAM), magnetic disk or optical disk and various storage medium that can store program codes.

[0205] The steps of the method or algorithm described in the embodiments of the present application can be implemented in the form of hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in RAM, flash memory, ROM, EPROM, electrically EPROM (EEPROM), register, hard disk, mobile hard disk, read-only optical disk (CD-ROM) or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor, so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a terminal device or a management device. Of course, the processor and the storage medium can also exist as discrete components in the terminal device or the management device.

[0206] Those skilled in the art should be aware that, in one or more examples described above, the functions described in the embodiments of the present application can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, the computer program instructions generate, in whole or in part, the processes or functions described in the embodiments of the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center through a wired (for example, coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (for example, infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a digital video disc (DVD)), or a semiconductor medium (for example, a solid state disk (SSD)), etc.

[0207] The various modules / units included in the various devices and products described in the above embodiments can be software modules / units or hardware modules / units, or partially software modules / units and partially hardware modules / units. For example, for the various devices and products applied to or integrated in a chip, the various modules / units included therein can all be implemented in the form of hardware such as circuitry, or at least some of the modules / units can be implemented in the form of software running on a processor integrated in the chip, and the remaining (if any) modules / units can be implemented in the form of hardware; for the various devices and products applied to or integrated in a chip module, the various modules / units included therein can all be implemented in the form of hardware such as circuitry, and different modules / units can be located in the same component (e.g., a chip, a circuit module, etc.) or different components of the chip module, or at least some of the modules / units can be implemented in the form of software running on a processor integrated in the chip module, and the remaining (if any) modules / units can be implemented in the form of hardware; for the various devices and products applied to or integrated in a terminal device, the various modules / units included therein can all be implemented in the form of hardware such as circuitry, and different modules / units can be located in the same component (e.g., a chip, a circuit module, etc.) or different components of the terminal device, or at least some of the modules / units can be implemented in the form of software running on a processor integrated in the terminal device, and the remaining (if any) modules / units can be implemented in the form of hardware.

[0208] The above detailed description of the specific embodiments of the present application has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the application to the precise form described, and many modifications, equivalents and alternatives shown thereby will be apparent to those skilled in the art.

Claims

1. A method for detecting excretion of a diaper, characterized by, The application is applied to the detection host of the intelligent nursing system, the intelligent nursing system further includes a paper diaper, a cloud server and a user equipment, the detection host includes a signal transmission module, a signal processing module and an alarm prompt module, the detection host is communicated with the paper diaper, the cloud server is communicated with the detection host, and the method includes: Through the signal transmission module, the first electric signal of the paper diaper in a preset time period is acquired; Through the signal processing module, the first electric signal is processed to obtain n second electric signals; n is an integer greater than 1; According to the n second electric signals, m voltage K lines are determined; m is an integer greater than 1 and less than n; According to the m voltage K lines, m excrement attribute information is determined; According to the m excrement attribute information, m abnormal information is determined; Through the alarm prompt module, corresponding early warning prompt operation parameters are executed according to the m abnormal information; The early warning prompt operation parameters are sent to the cloud server and stored, so that the user equipment accesses the early warning prompt operation parameters in the cloud server; Wherein, the m excrement attribute information is determined according to the m voltage K lines, including: According to the m voltage K lines, m voltage attenuation parameters are determined; According to the m voltage attenuation parameters, m excrement densities are determined; According to the m voltage K lines, m feature vectors are obtained based on the preset feature extraction rule; The m feature vectors are input into the preset excrement attribute identification model to obtain m first excrement attribute information; According to the m first excrement attribute information and the m excrement densities, the m excrement attribute information is determined.

2. The method of claim 1, wherein, Through the signal processing module, the first electric signal is processed to obtain n second electric signals, including: The reference electric signal of the paper diaper is acquired; the reference electric signal is the electric signal of the paper diaper detected by the detection host in a dry environment; According to the reference electric signal and the first electric signal, a first differential electric signal is obtained by difference operation; The first differential electric signal is subjected to voltage doubling and rectification processing to obtain a first rectified electric signal; The first rectified electric signal is processed according to the preset filtering method to obtain a first rectified filtered signal; The first rectified filtered signal is sampled at a preset sampling rate to obtain the n second electric signals.

3. The method of claim 1, wherein, According to the n second electric signals, m voltage K lines are determined, including: The target second electric signal is segmented according to the preset time interval to obtain p target signal sequences; the target second electric signal is any one of the n second electric signals; p is a positive integer greater than 1; The average voltage of each target signal sequence in the p target signal sequences is extracted to obtain p average voltages; The p average voltages and the p target signal sequences are subjected to curve fitting operation with voltage as the vertical axis and time as the horizontal axis to obtain a first voltage K line; The slope corresponding to each signal sequence in the p target signal sequences is determined to obtain p target voltage slopes; perform Fourier transform on each of the p target signal sequences to obtain p amplitude spectrums corresponding to the p target signal sequences; perform time-frequency feature fusion on the p amplitude spectrums and the p target voltage slopes according to a preset first formula to obtain p first fusion parameters; determine the voltage K line of the target second electric signal according to the p first fusion parameters and the first voltage K line.

4. The method of claim 1, wherein, The determining of the m voltage decay parameters according to the m voltage K lines comprises: extract a target feature voltage parameter from a target voltage K line; the target feature voltage parameter comprises a target peak voltage and a target steady-state voltage; the target voltage K line is any one of the m voltage K lines; obtain a reference voltage parameter of a reference voltage K line; determine a reference steady-state voltage in the reference voltage parameter; determine a voltage difference between the target steady-state voltage and the reference steady-state voltage; determine a first voltage weight corresponding to the voltage difference based on a preset mapping relationship between the voltage difference and the steady-state voltage weight; determine a second steady-state voltage according to the first voltage weight and the target steady-state voltage; determine a first time length from the target peak voltage to the target steady-state voltage according to the target voltage K line; if the first time length is less than or equal to a preset first time threshold, determine a voltage decay parameter of the target voltage K line according to the target peak voltage, the second steady-state voltage and the first time length; if the first time length is greater than the first time threshold, set a preset first parameter as the voltage decay parameter of the target voltage K line.

5. The method of claim 1, wherein, The determining of the m excrement densities according to the m voltage decay parameters comprises: determine the conductivity of the excrement corresponding to each voltage decay parameter in the m voltage decay parameters based on a preset mapping relationship between the voltage decay parameter and the conductivity of the excrement to obtain m first excrement conductivities; obtain a historical excrement conductivity; determine an error correction parameter of the excrement conductivity according to the historical excrement conductivity; determine m second excrement conductivities according to the error correction parameter and the m first excrement conductivities; determine the excrement density corresponding to each excrement conductivity in the m second excrement conductivities based on a preset mapping relationship between the excrement conductivity and the excrement density to obtain the m excrement densities.

6. The method according to any one of claims 1 to 3, wherein The determining of the m abnormal information according to the m excrement attribute information comprises: determine a target excrement type identifier in target excrement attribute information; the target excrement type identifier comprises stool or urine; the target excrement attribute information is any one of the m excrement attribute information; the target excrement attribute information comprises target transparency, target concentration and target consistency; determine target abnormal information according to the target excrement type identifier; The determining of the target abnormal information according to the target excrement type identifier comprises: If the target excrement type is identified as the urine, a reference transparency and a reference concentration of normal urine are obtained; when the target transparency is greater than the reference transparency and the target concentration is less than the reference concentration, the target abnormal information for representing the abnormality of the urine is generated; If the target excrement type is identified as the stool, a reference consistency of normal stool is obtained; when the target consistency is less than or equal to the reference consistency, the target abnormal information for representing the abnormality of the stool is generated.

7. A leakage intelligent detection device for a diaper, characterized by, The detection host applied to the intelligent nursing system further includes a paper diaper, a cloud server and a user equipment, and the detection host includes a signal transmission module, a signal processing module and an alarm prompt module, the detection host is in communication connection with the paper diaper, the cloud server is in communication connection with the detection host, and the device includes: An acquisition unit is configured to acquire a first electric signal of the paper diaper in a preset time period through the signal transmission module; A control unit is configured to process the first electric signal through the signal processing module to obtain n second electric signals; n is an integer greater than 1; A determination unit is configured to determine m voltage K lines according to the n second electric signals; m is an integer greater than 1 and less than n; determine m excrement attribute information according to the m voltage K lines; and determine m abnormal information according to the m excrement attribute information; wherein the determination of the m excrement attribute information according to the m voltage K lines includes: determining m voltage attenuation parameters according to the m voltage K lines; determining m excrement densities according to the m voltage attenuation parameters; performing feature extraction on the m voltage K lines based on a preset feature extraction rule to obtain m feature vectors; inputting the m feature vectors into a preset excrement attribute recognition model to obtain m first excrement attribute information; and determining the m excrement attribute information according to the m first excrement attribute information and the m excrement densities; An early warning unit is configured to perform corresponding early warning prompt operation parameters according to the m abnormal information through the alarm prompt module; and send the early warning prompt operation parameters to the cloud server and store the early warning prompt operation parameters, so that the user equipment accesses the early warning prompt operation parameters in the cloud server.

8. An electronic device, comprising: including: a processor, a memory, a communication interface, and one or more programs; the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing steps in the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program includes program instructions, which, when executed by a processor, cause the processor to execute the method of any one of claims 1-6.

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