Intelligent excrement analysis system and method for intelligent closestool

Abstract

The invention relates to the technical field of data processing, in particular to an intelligent excrement analysis system and method for an intelligent closestool, and the system comprises an acquisition module, a first judgment module, a second judgment module, an abnormality determination module, a risk determination module, an adjustment module and an output module. Key data are acquired in real time, a temporary event is judged according to the gas concentration change rate, then an abnormal event is judged by combining the color spot area and the foam concentration ratio, then the abnormal type is determined according to the gas concentration and the foam concentration ratio, and high-risk abnormity is determined by combining the frequency, the oil film area and the color spot area. Furthermore, the preset threshold value is dynamically adjusted based on the high-risk abnormality, and the analysis report of the re-determined high-risk event is output after the adjustment is completed, so that the excrement change in the use process of the intelligent closestool can be comprehensively and accurately analyzed, and the problem of low analysis accuracy caused by excessive dependence on single data is effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an intelligent excrement analysis system and method for an intelligent toilet. Background Art

[0002] In daily life, people are paying more and more attention to their intestinal health. However, traditional methods of monitoring intestinal health often have problems such as lag or lack of comprehensiveness. For example, some people may only seek medical attention after occasional physical examinations or after experiencing obvious discomfort symptoms, which can easily miss some early intestinal health issues. The bathroom is an important scene in people's daily lives. When people use the toilet, the various characteristics of excrement may contain potential information about intestinal health, but traditional monitoring methods cannot fully utilize this information for timely and comprehensive health monitoring.

[0003] Patent document with publication number CN117147544A discloses a urine detection and analysis system for a smart toilet, including: a real-time multi-index analysis module that uses miniaturized biosensors to quantify multiple biomarkers in urine in real time, and is combined with adaptive sampling technology, which can automatically adjust the urine sampling frequency according to the user's physiological state and behavior; the system further integrates a contactless detection module, uses optical or electromagnetic fields to collect urine samples in a contactless manner, and integrates a microfluidic chip to perform micro-processing and detection of samples; the system also includes an AI diagnostic engine, which uses machine learning algorithms to perform real-time diagnosis and prediction of urine analysis data, and can generate personalized health reports.

[0004] It can be seen that the urine detection and analysis system of the smart toilet has the following problems: miniaturized biosensors are prone to decreased sensitivity or cross-reaction in long-term high-humidity and high-salt environments, resulting in deviations in real-time quantitative results; the sampling frequency will be over-adjusted, causing data redundancy or omission of key windows; data collection is easily affected by fluctuations in urine flow patterns, and trace samples cannot reflect the overall component distribution; the lack of diversity in training data leads to misjudgment or missed diagnosis of special pathological conditions. Summary of the Invention

[0005] To this end, the present invention provides an intelligent analysis system and method for excrement of a smart toilet, which is used to overcome the problem of low analysis accuracy in the prior art due to over-reliance on single data through multi-dimensional data analysis and dynamic adjustment mechanism.

[0006] To achieve the above objectives, the present invention provides, on the one hand, an intelligent excrement analysis system for an intelligent toilet, comprising:

[0007] The acquisition module is used to collect real-time data on the gas concentration in the toilet space, the area of ​​spots on the surface of solid excrement, the concentration of foam, and the area of ​​oil film remaining on the toilet wall after flushing when the target uses the smart toilet;

[0008] a first determination module, connected to the acquisition module, for determining the occurrence of a temporary event based on the gas concentration and a preset change rate threshold, and obtaining a temporary determination result;

[0009] a second determination module, connected to the acquisition module and the first determination module respectively, for determining the occurrence of an abnormal event based on the temporary determination result, the color spot area, the foam concentration, and a preset synchronization threshold, and obtaining an abnormality determination result;

[0010] an abnormality determination module, connected to the acquisition module and the second determination module respectively, for determining the type of the abnormal event as abnormal inflammatory activity based on the abnormality determination result, the gas concentration, and the foam concentration, and obtaining an abnormality determination result;

[0011] a risk determination module, connected to the acquisition module and the abnormality determination module, respectively, for determining that the abnormal event is a high-risk abnormality based on the timestamp of the abnormality determination result within a preset risk period, the oil film area, and the color spot area, and obtaining a risk determination result;

[0012] an adjustment module, connected to the acquisition module and the risk determination module, respectively, and configured to adjust the preset change rate threshold according to the risk determination result and the gas concentration to obtain an adjusted change rate threshold, and to adjust the preset synchronization threshold according to the risk determination result obtained based on the adjusted change rate threshold and the color spot area to obtain an adjusted synchronization threshold;

[0013] An output module is connected to the risk determination module and is used to output an excrement change analysis report according to the risk determination result re-determined based on the adjusted synchronization threshold.

[0014] Furthermore, the first determination module includes:

[0015] a concentration rate calculation unit, configured to calculate a concentration change rate according to all gas concentrations within a preset determination time period based on a comparison result between the gas concentration and a preset concentration threshold;

[0016] The temporary determination unit is connected to the concentration rate calculation unit and is used to determine the occurrence of a temporary event based on a comparison result between the concentration change rate and the preset change rate threshold, and obtain a temporary determination result.

[0017] Furthermore, the second determination module includes:

[0018] an abnormal fluctuation calculation unit, configured to calculate a plurality of color spot fluctuation values ​​according to the color spot area within the preset determination time, and to calculate a plurality of concentration fluctuation values ​​according to the foam concentration within the preset determination time;

[0019] The second determination unit is connected to the abnormal fluctuation calculation unit and is used to determine the abnormality determination result according to all the color spot fluctuation values ​​and all the concentration fluctuation values.

[0020] Furthermore, the second determining unit includes:

[0021] a synchronization degree calculation subunit, configured to calculate a change synchronization degree based on all the color spot fluctuation values ​​and all the concentration fluctuation values;

[0022] The second determination subunit is connected to the synchronization degree calculation subunit and is used to determine the occurrence of an abnormal event based on a comparison result between the change synchronization degree and the preset synchronization degree threshold, and obtain the abnormality determination result.

[0023] Furthermore, the abnormality determination module includes:

[0024] an abnormal change calculation unit, configured to calculate a plurality of rate change values ​​based on all of the gas concentrations within a predetermined time period, and to calculate a plurality of concentration change values ​​based on all of the foam concentrations within a predetermined time period;

[0025] An abnormality determination unit is connected to the abnormal change calculation unit and is used to determine the abnormality determination result according to all the concentration change values ​​and all the concentration change values.

[0026] Furthermore, the abnormality determination unit includes:

[0027] a correlation calculation subunit, configured to calculate a change correlation based on all of the concentration change values ​​and all of the concentration change values;

[0028] The abnormality determination subunit is connected to the correlation calculation subunit and is used to determine the type of the abnormal event as the abnormal inflammatory activity based on the comparison result of the change correlation and the preset correlation threshold, and obtain the abnormality determination result.

[0029] Furthermore, the risk determination module includes:

[0030] a risk parameter calculation unit, configured to calculate an abnormality frequency based on all the time stamps, calculate an oil film fluctuation value based on all the oil film areas, and calculate a color spot change value based on all the color spot areas;

[0031] a risk index calculation unit connected to the risk parameter calculation unit, for calculating a risk index based on the abnormal frequency, the oil film fluctuation value, and the color spot change value;

[0032] A risk determination unit is connected to the risk index calculation unit and is used to determine that the abnormal event is a high-risk abnormality based on a comparison result between the risk index and a preset index threshold, thereby obtaining a risk determination result.

[0033] Furthermore, the adjustment module includes:

[0034] a change rate average calculation unit, configured to calculate a concentration change rate average according to all gas concentrations within a preset adjustment period based on the risk determination result;

[0035] a fluctuation threshold value adjustment unit connected to the change rate mean value calculation unit, configured to adjust the preset change rate threshold value according to a comparison result of the concentration change rate mean value and the preset change rate threshold value to obtain the adjusted change rate threshold value;

[0036] The synchronization adjustment unit is connected to the fluctuation threshold adjustment unit and is used to adjust the preset synchronization threshold according to the risk determination result obtained based on the adjusted change rate threshold and the color spot area to obtain the adjusted synchronization threshold.

[0037] Furthermore, the synchronization adjustment unit includes:

[0038] a color spot area change calculation subunit, configured to calculate a color spot area change value based on all the color spot areas within a preset adjustment period;

[0039] a deviation calculation subunit, connected to the color spot area change calculation subunit, for calculating an area deviation based on a comparison result of the color spot area change value and a preset area threshold;

[0040] The synchronization adjustment subunit is connected to the deviation calculation subunit and is used to adjust the preset synchronization threshold based on the comparison result between the area deviation and the preset deviation threshold to obtain the adjusted synchronization threshold.

[0041] On the other hand, the present invention also provides an intelligent analysis method for excrement of an intelligent toilet, comprising:

[0042] Real-time data collection: gas concentration in the toilet space, color spot area on the surface of solid excrement, foam concentration, and oil film area remaining on the toilet wall after flushing.

[0043] Determining the occurrence of a temporary event based on the gas concentration and a preset change rate threshold, and obtaining a temporary determination result;

[0044] Determining that an abnormal event occurs according to the temporary determination result, the color spot area, the foam concentration, and a preset synchronization threshold, and obtaining an abnormality determination result;

[0045] determining, based on the abnormality determination result, the gas concentration, and the foam concentration, that the type of the abnormal event is abnormal inflammatory activity, and obtaining an abnormality determination result;

[0046] Determine the abnormal event as a high-risk abnormality based on the timestamp of the abnormality determination result within a preset risk period, the oil film area, and the color spot area, and obtain a risk determination result;

[0047] adjusting the preset change rate threshold according to the risk determination result and the gas concentration to obtain an adjusted change rate threshold, and adjusting the preset synchronization threshold according to the risk determination result obtained again based on the adjusted change rate threshold and the color spot area to obtain an adjusted synchronization threshold;

[0048] An excrement change analysis report is outputted according to the risk determination result re-determined based on the adjusted synchronization threshold.

[0049] Compared with the existing technology, the beneficial effect of the present invention lies in that, by acquiring data such as gas concentration, color spot area, foam concentration and oil film area in real time, temporary events are determined according to the rate of change of gas concentration, and then abnormal events are determined in combination with color spot area and foam concentration. Subsequently, the abnormality type is determined according to the gas concentration and foam concentration. Next, high-risk abnormalities are determined by combining the frequency, oil film area and color spot area of ​​the abnormal type. The preset threshold is further dynamically adjusted based on the high-risk abnormality. After the adjustment is completed, an analysis report of the re-determined high-risk abnormality is output, which can comprehensively and accurately analyze the changes in excrement during the use of the smart toilet, provide the target with a scientific and reliable health monitoring report, and effectively solve the problem of low analysis accuracy due to over-reliance on single data.

[0050] Furthermore, by calculating the concentration change rate when the gas concentration exceeds the preset concentration threshold, it means that the gas concentration detected at the current time point has exceeded the normal physiological range. This may be due to an abnormal increase in metabolites (such as 6-methylheptanone, etc.) caused by abnormal intestinal activity. At this time, the concentration change rate is calculated to further analyze the dynamic change trend of the gas concentration. When the concentration change rate is greater than the preset change rate threshold, it indicates that the gas concentration has not only exceeded the normal range, but is also rising rapidly. This may be due to a rapid increase in metabolites caused by intensified abnormal intestinal activity. Only when the gas concentration not only exceeds the threshold but also rises rapidly is it determined to be a temporary event, thereby avoiding misjudgment and capturing potential abnormal changes in a timely manner.

[0051] Furthermore, by calculating the standard deviation of the spot area and foam concentration, and judging abnormal events based on these fluctuation values, the spot area and foam concentration are important indicators reflecting intestinal inflammatory activity. The increase in spot area may be related to tiny ruptures of the intestinal mucosa, while the change in foam concentration may be related to abnormal intestinal flora metabolism. If the standard deviation is large, it means that these indicators fluctuate violently within the time period, which is more likely to be a manifestation of pathological signals rather than accidental fluctuations. Data relying solely on the spot area or foam concentration at a single time point may be interfered with by accidental factors. By calculating the standard deviation, the dynamic changes within the entire time period can be comprehensively considered, thereby improving the accuracy and reliability of monitoring.

[0052] Furthermore, the color spot fluctuation value and concentration fluctuation value are processed by maximum-minimum normalization to eliminate the dimension and magnitude differences, and then the Pearson correlation coefficient of the two is calculated to obtain the synchronization of changes. When the synchronization of changes exceeds the preset threshold, it means that the fluctuations of the color spot area and foam concentration have a significant correlation in the time series. When the intestinal inflammatory activity intensifies, the infiltration of inflammatory cells and the release of inflammatory mediators will cause damage and bleeding to the intestinal mucosa. At the same time, the inflammatory environment will change the pH value and the distribution of nutrients in the intestine, thereby affecting the metabolic activity of the intestinal flora and producing more gas and foam, so it indicates that intestinal inflammatory activity has occurred. At this time, it is determined that an abnormal event has occurred, and abnormal intestinal inflammatory activity can be detected in time.

[0053] Furthermore, by calculating the rate of change and standard deviation of gas concentration and foam concentration within a preset time period, the dynamic change characteristics of these two key indicators were quantified. The rate of change of gas concentration reflects the dynamic changes of intestinal metabolic products, while the standard deviation of foam concentration reflects the fluctuation of intestinal flora metabolism. By comprehensively analyzing the change characteristics of these two indicators, abnormal changes in the intestine can be captured more comprehensively, which not only improves the sensitivity and specificity of monitoring, but also can timely detect potential abnormal changes and avoid misjudgment due to accidental fluctuations of a single indicator.

[0054] Furthermore, the concentration change values ​​and concentration change values ​​are processed by maximum-minimum normalization to eliminate the dimension and magnitude differences, and then the Pearson correlation coefficient of the two is calculated to obtain the change correlation. When the change correlation is greater than the preset correlation threshold, it means that the gas concentration change and the foam concentration change have a significant correlation in the time series, indicating that it is caused by abnormal intestinal inflammatory activity, reflecting the dual effects of inflammatory activity on intestinal mucosa and intestinal flora metabolism, and is an important sign of abnormal intestinal health. At this time, the type of abnormal event is determined to be abnormal inflammatory activity, which can timely detect inflammatory activity and provide a basis for intervention.

[0055] Furthermore, by calculating the abnormal frequency, we can reflect the frequency of abnormal events, which is an important parameter for assessing the activity of the disease. A higher abnormal frequency may mean frequent inflammatory activity and unstable intestinal health. By calculating the oil film fluctuation value, we can reflect the inflammatory activity of the intestinal mucosa. A larger oil film fluctuation value may indicate an abnormal increase in intestinal secretions, which is related to the aggravation of inflammatory activity. By calculating the color spot change value, we can reflect the changes in the intestinal mucosa, which is a direct manifestation of mucosal damage caused by inflammatory activity. A larger color spot change value may mean more severe mucosal damage. The abnormal frequency, oil film fluctuation value and color spot change value are normalized respectively and then multiplied by the preset weights for weighted summation to obtain a risk index, which can more accurately reflect the overall risk level. When the preset index threshold is exceeded, the abnormal event is judged to be a high-risk abnormality, ensuring that normal fluctuations and high-risk abnormal states can be effectively distinguished.

[0056] Furthermore, by calculating the mean of the gas concentration change rate during high-risk anomalies, and dynamically adjusting the change rate threshold according to the relative deviation between the mean and the preset change rate threshold, when the mean concentration change rate is greater than the preset change rate threshold, it means that the currently monitored gas concentration change rate has exceeded the normal range set by the system as a whole. This may mean that intestinal inflammatory activity is more frequent or severe, resulting in more drastic dynamic changes in gas concentration. At this time, if the original preset change rate threshold is continued to be used, the system may not be sensitive enough to subsequent signals and miss some important change information. At the same time, re-evaluating high-risk anomalies based on the adjusted threshold and adjusting the synchronization threshold can optimize the sensitivity and specificity of the monitoring system in real time according to the actual monitoring data. By dynamically adjusting the threshold, the system can better adapt to the individual differences and health changes of different users, capture potential abnormal health signals in a timely manner, and reduce misjudgments.

[0057] Furthermore, by calculating the standard deviation of the spot area change value, the system can quantify the dynamic change characteristics of the spot area. When the spot area change value exceeds the preset area threshold, it means that the current spot area fluctuation has exceeded the normal range, and there may be abnormal changes in intestinal health. At this time, the significance of this change is further evaluated by calculating the relative deviation between the spot area change value and the preset area threshold. If the area deviation exceeds the preset deviation threshold, it means that the change is significant, and the synchronization threshold needs to be adjusted to improve the sensitivity of monitoring. By reducing the preset synchronization threshold, the system can more sensitively capture changes in the correlation between the spot area and other indicators (such as changes in gas concentration), thereby identifying potential high-risk events more promptly.

[0058] Furthermore, through multi-dimensional, real-time monitoring and dynamic adjustment of thresholds, accurate monitoring of users' intestinal health is achieved. Starting from four key indicators: gas concentration, spot area, foam concentration and oil film area, these indicators will change significantly when intestinal inflammation is active, and there is a close logical correlation between them. For example, rapid changes in gas concentration usually indicate abnormal intestinal flora metabolism, while changes in spot area and foam concentration reflect the degree of inflammation of the intestinal mucosa and the physical state of the excrement. By setting preset change rate thresholds and synchronization thresholds, the system can screen out abnormal events in a hierarchical and gradually refined manner, and ultimately determine whether they are high-risk abnormalities. This not only improves the accuracy of monitoring, but also reduces the false alarm rate. In addition, by dynamically adjusting the thresholds, the monitoring parameters can be automatically optimized according to individual differences of users and intestinal health status, further improving the adaptability and reliability of the system. Finally, the excrement change analysis report output by the system provides users with real-time, personalized health monitoring, helping users to conduct daily intestinal health monitoring and management in a timely manner, thereby achieving early intervention and improving treatment effects and quality of life. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 Schematic diagram of the intelligent excrement analysis system of the smart toilet in this embodiment;

[0060] Figure 2 This is a determination logic diagram for the first determination module of this embodiment to determine the occurrence of a temporary event;

[0061] Figure 3 This is a determination logic diagram for the second determination unit of this embodiment to determine the occurrence of an abnormal event;

[0062] Figure 4 This is a flow chart of the intelligent analysis method for excrement of the smart toilet in this embodiment. DETAILED DESCRIPTION

[0063] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0064] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0065] See also Figure 1 As shown in FIG, which is a schematic diagram of the intelligent excrement analysis system of the smart toilet of this embodiment, on the one hand, this embodiment provides an intelligent excrement analysis system of the smart toilet, including:

[0066] The acquisition module is used to collect real-time data on the gas concentration in the toilet space, the area of ​​spots on the surface of solid excrement, the concentration of foam, and the area of ​​oil film remaining on the toilet wall after flushing when the target uses the smart toilet;

[0067] a first determination module, connected to the acquisition module, for determining the occurrence of a temporary event based on the gas concentration and a preset change rate threshold, and obtaining a temporary determination result;

[0068] a second determination module, connected to the acquisition module and the first determination module respectively, for determining the occurrence of an abnormal event based on the temporary determination result, the color spot area, the foam concentration, and a preset synchronization threshold, and obtaining an abnormality determination result;

[0069] an abnormality determination module, connected to the acquisition module and the second determination module respectively, for determining the type of the abnormal event as abnormal inflammatory activity based on the abnormality determination result, the gas concentration, and the foam concentration, and obtaining an abnormality determination result;

[0070] a risk determination module, connected to the acquisition module and the abnormality determination module, respectively, for determining that the abnormal event is a high-risk abnormality based on the timestamp of the abnormality determination result within a preset risk period, the oil film area, and the color spot area, and obtaining a risk determination result;

[0071] an adjustment module, connected to the acquisition module and the risk determination module, respectively, and configured to adjust the preset change rate threshold according to the risk determination result and the gas concentration to obtain an adjusted change rate threshold, and to adjust the preset synchronization threshold according to the risk determination result obtained based on the adjusted change rate threshold and the color spot area to obtain an adjusted synchronization threshold;

[0072] An output module is connected to the risk determination module and is used to output an excrement change analysis report according to the risk determination result re-determined based on the adjusted synchronization threshold.

[0073] The target refers to users who use smart toilets to pay attention to their daily intestinal health status; gas concentration refers to the presence of certain gases in the toilet space when the user uses the smart toilet. These gases may be derived from intestinal metabolites (including but not limited to 6-methylheptanone). Changes in the concentration of these gases can reflect the dynamic changes in intestinal inflammatory activity and are collected by gas sensors. The color spot area refers to the area of ​​the color spots that appear on the surface of solid excrement. These color spots may be formed on the surface of excrement by food residues, blood, bile and other components. The appearance and area of ​​the color spots can provide important information about the health of the digestive system. For example, red or black color spots may indicate gastrointestinal bleeding. By equipping with a high-resolution camera, it is possible to capture images of solid excrement in real time, and automatically identify and calculate the area of ​​the color spots through image recognition technology. Foam concentration refers to the presence of foam in solid excrement during defecation. The formation of these foams is related to the metabolic activity of the intestinal flora, especially in an inflammatory environment. The metabolism of the flora will produce more gas, forming foam. The excrement is captured by a high-resolution camera, and all foam areas are extracted from the image and divided into several squares of equal size. The distance between each square and the center point of the square is calculated, and the inverse of the standard deviation of all distances is calculated to obtain the foam concentration. The oil film area refers to the layer of oil film that may remain on the toilet wall after flushing. The formation of this oil film is related to abnormal intestinal secretions. Especially in an inflammatory environment, the composition and amount of intestinal secretions may change, leading to the formation of an oil film. The oil film components will fluoresce under 365nm ultraviolet light. The fluorescence coverage area is detected by a fluorescence sensor to obtain the oil film area.

[0074] The output module is responsible for generating a detailed fecal change analysis report based on the analysis of risk determination results obtained from high-risk anomalies. The report details fecal changes during the monitoring period and analyzes and warns of potential metabolic anomalies, including basic information, changes in monitoring data, and risk assessment results. This helps patients better understand their health status and promptly identify potential intestinal health anomalies. At the same time, the report provides detailed abnormal monitoring data, which can provide strong support for users' daily intestinal health monitoring and management, improving the efficiency and accuracy of early diagnosis and intervention.

[0075] By acquiring data such as gas concentration, color spot area, foam concentration and oil film area in real time, temporary events are determined based on the rate of change of gas concentration, and then abnormal events are determined based on the color spot area and foam concentration. Subsequently, the type of abnormality is determined based on the gas concentration and foam concentration. Next, high-risk abnormalities are determined based on the frequency, oil film area and color spot area of ​​the abnormality type. The preset threshold is further dynamically adjusted based on the high-risk abnormality. After the adjustment is completed, an analysis report of the re-determined high-risk abnormality is output. This can comprehensively and accurately analyze the changes in excrement during the use of smart toilets, provide the target with scientific and reliable health monitoring reports, and effectively solve the problem of low analysis accuracy due to over-reliance on single data.

[0076] See also Figure 2 As shown, it is a determination logic diagram of the first determination module of this embodiment for determining the occurrence of a temporary event. In this embodiment, the first determination module includes:

[0077] a concentration rate calculation unit, configured to calculate the rate of change of all the gas concentrations within a preset determination time period when the gas concentration is greater than a preset concentration threshold, to obtain a concentration change rate;

[0078] A temporary determination unit is connected to the concentration rate calculation unit and is used to determine that a temporary event occurs when the concentration change rate is greater than the preset change rate threshold, and obtain the temporary determination result.

[0079] The preset concentration threshold is a baseline value used to determine whether gas concentrations have reached a level of concern. It depends on the nature of the target gas and the target's intestinal health and is typically set between 10 ppm and 100 ppm. In this example, it is set to 50 ppm to ensure that further analysis is initiated only when gas concentrations reach a certain level, improving the system's sensitivity and accuracy.

[0080] The preset determination time is the length of time used to calculate the gas concentration change rate. It depends on the dynamic characteristics of gas concentration changes, the real-time requirements of the usage scenario, and the frequency of data collection, and is typically set between 10 seconds and 2 minutes. In this embodiment, it is set to 1 minute to capture rapid changes in gas concentration while ensuring data stability, preventing accidental fluctuations caused by an overly short time window from affecting the determination results.

[0081] The preset rate of change threshold is a baseline value used to determine whether the rate of change in gas concentration is abnormal. It depends on the normal fluctuation range of gas concentration changes and the target's intestinal health status and is typically set between 0.1ppm / s and 1.0ppm / s. In this embodiment, it is set to 0.5ppm / s to effectively distinguish normal gas concentration fluctuations from abnormal changes, ensuring that the system promptly triggers a temporary event detection when gas concentration rises rapidly.

[0082] By calculating the concentration change rate when the gas concentration exceeds the preset concentration threshold, it means that the gas concentration detected at the current time point has exceeded the normal physiological range. This may be due to an abnormal increase in metabolites (such as 6-methylheptanone) caused by abnormal intestinal activity. At this time, the concentration change rate is calculated to further analyze the dynamic change trend of the gas concentration. When the concentration change rate is greater than the preset change rate threshold, it indicates that the gas concentration has not only exceeded the normal range but is also rising rapidly. This may be due to a rapid increase in metabolites caused by increased abnormal intestinal activity. Only when the gas concentration not only exceeds the threshold but also rises rapidly is it determined to be a temporary event, thereby avoiding misjudgment and capturing potential abnormal changes in a timely manner.

[0083] Specifically, the second determination module includes:

[0084] an abnormal fluctuation calculation unit, configured to calculate a standard deviation of all the color spot areas from the initial moment to each moment within the preset determination time period to obtain a plurality of color spot fluctuation values, and to calculate a standard deviation of all the foam concentrations from the initial moment to each moment within the preset determination time period to obtain a plurality of concentration fluctuation values;

[0085] The second determination unit is connected to the abnormal fluctuation calculation unit and is used to determine the occurrence of an abnormal event according to all the color spot fluctuation values ​​and all the concentration fluctuation values ​​to obtain the abnormality determination result.

[0086] By calculating the standard deviation of the spot area and foam concentration, and judging abnormal events based on these fluctuation values, the spot area and foam concentration are important indicators reflecting intestinal inflammatory activity. The increase in spot area may be related to tiny ruptures of the intestinal mucosa, while the change in foam concentration may be related to abnormal intestinal flora metabolism. If the standard deviation is large, it means that these indicators fluctuate violently during the time period, which is more likely to be a manifestation of pathological signals rather than accidental fluctuations. Data on spot area or foam concentration that only rely on a single time point may be interfered with by accidental factors. By calculating the standard deviation, the dynamic changes during the entire time period can be comprehensively considered, thereby improving the accuracy and reliability of monitoring.

[0087] See also Figure 3 As shown in FIG. 1 , it is a determination logic diagram of the second determination unit in this embodiment for determining the occurrence of an abnormal event. In this embodiment, the second determination unit includes:

[0088] a synchronization calculation subunit, configured to perform maximum-minimum normalization processing on all the color spot fluctuation values ​​to obtain a plurality of color spot normalized values, and to perform maximum-minimum normalization processing on all the concentration fluctuation values ​​to obtain a plurality of concentration normalized values, and to calculate the Pearson correlation coefficient of all the color spot normalized values ​​and all the concentration normalized values ​​to obtain the change synchronization;

[0089] The second determination subunit is connected to the synchronization degree calculation subunit and is used to determine that an abnormal event occurs when the change synchronization degree is greater than the preset synchronization degree threshold, and obtain the abnormality determination result.

[0090] The preset synchronization threshold is a benchmark value used to determine the strength of the correlation between spot area fluctuations and foam concentration fluctuations. It is determined by statistical analysis of intestinal health characteristics and clinical data and is typically set between 0.5 and 0.8. In this example, it is set to 0.6, which effectively reduces false positives while maintaining high sensitivity.

[0091] The color spot fluctuation value and concentration fluctuation value are processed by maximum-minimum normalization to eliminate the dimension and magnitude differences, and then the Pearson correlation coefficient between the two is calculated to obtain the synchronization of changes. When the synchronization of changes exceeds the preset threshold, it means that the fluctuations of the color spot area and foam concentration have a significant correlation in the time series. When the intestinal inflammatory activity intensifies, the infiltration of inflammatory cells and the release of inflammatory mediators will cause damage and bleeding to the intestinal mucosa. At the same time, the inflammatory environment will change the pH value and the distribution of nutrients in the intestine, thereby affecting the metabolic activity of the intestinal flora and producing more gas and foam, so it indicates that intestinal inflammatory activity has occurred. At this time, it is determined that an abnormal event has occurred, and abnormal intestinal inflammatory activity can be detected in time.

[0092] Specifically, the anomaly determination module includes:

[0093] an abnormal change calculation unit, configured to calculate a rate of change of all of the gas concentrations from an initial moment to each moment within a predetermined time period to obtain a plurality of concentration change rates, calculate a standard deviation of all of the concentration change rates from the initial moment to each moment within the predetermined time period to obtain a plurality of concentration change values, and calculate a standard deviation of all of the foam concentrations from the initial moment to each moment within the predetermined time period to obtain a plurality of concentration change values;

[0094] An abnormality determination unit is connected to the abnormal change calculation unit and is used to determine the type of the abnormal event as the abnormal inflammatory activity based on all the concentration change values ​​and all the concentration change values, and obtain the abnormality determination result.

[0095] The preset duration refers to the length of the time window used to calculate the characteristics of gas concentration and foam concentration changes. It depends on the real-time requirements of the monitoring system, the frequency of data collection, and the dynamic characteristics of intestinal health changes, and is typically set between 1 and 10 minutes. In this embodiment, it is set to 5 minutes, which ensures real-time data collection while providing a sufficient time window to capture dynamic changes in gas concentration and foam concentration.

[0096] By calculating the rate of change and standard deviation of gas concentration and foam concentration within a preset time period, the dynamic change characteristics of these two key indicators are quantified. The rate of change of gas concentration reflects the dynamic changes of intestinal metabolic products, while the standard deviation of foam concentration reflects the fluctuation of intestinal flora metabolism. By comprehensively analyzing the change characteristics of these two indicators, abnormal changes in the intestine can be captured more comprehensively, which not only improves the sensitivity and specificity of monitoring, but also can timely detect potential abnormalities and avoid misjudgment due to accidental fluctuations of a single indicator.

[0097] Specifically, the abnormality determination unit includes:

[0098] a correlation calculation subunit, configured to perform maximum-minimum normalization processing on all the concentration change values ​​to obtain a plurality of concentration standard values, and to perform maximum-minimum normalization processing on all the concentration change values ​​to obtain a plurality of concentration standard values, and to calculate the Pearson correlation coefficient of all the concentration standard values ​​and all the concentration standard values ​​to obtain the change correlation;

[0099] The abnormality determination subunit is connected to the correlation calculation subunit and is used to determine that the abnormal type of the abnormal event is abnormal inflammatory activity when the change correlation is greater than a preset correlation threshold, and obtain the abnormality determination result.

[0100] The preset correlation threshold is a benchmark value used to determine the strength of the correlation between changes in gas concentration and foam concentration. It is determined by statistical analysis of intestinal health characteristics and clinical data, and is typically set between 0.5 and 0.8. In this example, it is set to 0.65, which effectively reduces false positives while maintaining high sensitivity and allowing for the timely detection of potential abnormal events.

[0101] The concentration change values ​​and concentration change values ​​are processed by maximum-minimum normalization to eliminate dimension and magnitude differences, and then the Pearson correlation coefficient of the two is calculated to obtain the change correlation. When the change correlation is greater than the preset correlation threshold, it means that the gas concentration change and the foam concentration change have a significant correlation in the time series, indicating that it is caused by abnormal intestinal inflammatory activity, reflecting the dual effects of inflammatory activity on intestinal mucosa and intestinal flora metabolism, and is an important sign of abnormal intestinal health. At this time, the type of abnormal event is determined to be abnormal inflammatory activity, which can timely detect inflammatory activity and provide a basis for intervention.

[0102] Specifically, the risk determination module includes:

[0103] a risk parameter calculation unit, configured to calculate a ratio of all the timestamps to the total number of toilet uses within the preset risk period to obtain an abnormality frequency, calculate a standard deviation of all the oil film areas to obtain an oil film fluctuation value, and calculate a standard deviation of all the color spot areas to obtain a color spot change value;

[0104] a risk normalization processing unit connected to the risk parameter calculation unit, configured to perform maximum-minimum normalization processing on the abnormal frequency to obtain a standard abnormal frequency, perform maximum-minimum normalization processing on the oil film fluctuation value to obtain a standard oil film fluctuation value, and perform maximum-minimum normalization processing on the color spot change value to obtain a standard color spot change value;

[0105] a risk index calculation unit connected to the risk normalization processing unit, configured to perform a weighted summation on the abnormal frequency, the oil film fluctuation value, the color spot change value, a preset frequency weight, a preset oil film weight, and a preset color spot weight to obtain a risk index;

[0106] A risk determination unit is connected to the risk index calculation unit and is used to determine that the abnormal event is a high-risk abnormality when the risk index is greater than a preset index threshold, and obtain a risk determination result.

[0107] The preset frequency weight is a coefficient used to measure the contribution of abnormal frequency to the overall risk in the risk index calculation. It depends on the importance of the abnormal frequency in the overall risk assessment and its relative relationship to the oil film fluctuation value and the color change value. It is typically set between 0.2 and 0.5. In this embodiment, it is set to 0.4, which reasonably reflects the importance of abnormal frequency in the risk assessment while balancing the impact of the oil film fluctuation value and the color change value, ensuring a more comprehensive and scientific risk index calculation.

[0108] The preset oil film weight is used to measure the contribution of oil film fluctuation to the overall risk in the risk index calculation. It is determined by the importance of oil film fluctuation in the overall risk assessment and its relative relationship to anomaly frequency and color change. It is typically set between 0.2 and 0.4. In this example, it is set to 0.3, which reasonably reflects the importance of oil film fluctuation in risk assessment while preventing it from overly influencing the risk index, ensuring a balanced and accurate risk assessment.

[0109] The preset color spot weight is used to measure the contribution of color spot variation to the overall risk in the risk index calculation. This weighting is determined by the importance of the color spot variation in the overall risk assessment, as well as its relative relationship to the anomaly frequency and oil film fluctuation. It is typically set between 0.2 and 0.4. In this embodiment, it is set to 0.3, which reasonably reflects the importance of color spot variation in the risk assessment while preventing it from overly influencing the risk index, ensuring a balanced and accurate risk assessment.

[0110] The preset index threshold is a benchmark used to determine whether the risk index has reached a high-risk level. It depends on the risk assessment objectives, the security requirements of the application scenario, and the specific needs of the user, and is typically set between 1.0 and 3.0. In this embodiment, it is set to 2.0, which effectively distinguishes between normal and high-risk levels, ensuring that high-risk events are triggered promptly when the risk index reaches a high level, while avoiding frequent misjudgments caused by excessively low thresholds.

[0111] Calculating the abnormal frequency reflects the frequency of abnormal events, which is an important parameter for assessing the activity of the disease. A higher abnormal frequency may mean frequent inflammatory activity and unstable intestinal health. Calculating the oil film fluctuation value reflects the inflammatory activity of the intestinal mucosa. A larger oil film fluctuation value may indicate an abnormal increase in intestinal secretions, which is related to the aggravation of inflammatory activity. Calculating the color spot change value reflects the changes in the intestinal mucosa, which is a direct manifestation of mucosal damage caused by inflammatory activity. A larger color spot change value may mean more severe mucosal damage. The abnormal frequency, oil film fluctuation value and color spot change value are normalized respectively and then multiplied by the preset weights for weighted summation to obtain a risk index, which can more accurately reflect the overall risk level. When the preset index threshold is exceeded, the abnormal event is judged to be a high-risk abnormality, ensuring that normal fluctuations and high-risk abnormal states can be effectively distinguished.

[0112] Specifically, the adjustment module includes:

[0113] a change rate average calculation unit, configured to calculate, based on the risk determination result, a change rate of the gas concentration of each of the high-risk events within the preset adjustment period to obtain a plurality of overall concentration change rates, and to calculate an average of all the overall concentration change rates to obtain a concentration change rate average;

[0114] a fluctuation threshold adjustment unit connected to the change rate mean calculation unit, for reducing the preset change rate threshold according to the relative deviation between the concentration change rate mean and the preset change rate threshold and a preset rate adjustment coefficient to obtain the adjusted change rate threshold when the concentration change rate mean is greater than the preset change rate threshold, wherein R'=R×(1-a×(S-S0) / S0), R' is the adjusted change rate threshold, R is the preset change rate threshold, a is the preset rate adjustment coefficient, S is the concentration change rate mean, and S0 is the preset change rate threshold;

[0115] The synchronization adjustment unit is connected to the fluctuation threshold adjustment unit and is used to adjust the preset synchronization threshold according to the risk determination result obtained based on the adjusted change rate threshold and the color spot area to obtain the adjusted synchronization threshold.

[0116] The preset adjustment period is the time interval used to calculate and adjust the gas concentration rate of change threshold. The setting depends on the dynamic nature of intestinal health changes and the real-time requirements of the monitoring system, and is typically set between 1 and 7 days. In this embodiment, it is set to 3 days to ensure timely dynamic adjustments to the system while avoiding instability caused by overly frequent adjustments.

[0117] The preset rate adjustment factor is a parameter used to determine the magnitude of threshold adjustment. It is determined by balancing sensitivity to gas concentration change rate with system stability and is typically set between 0.1 and 0.3. In this embodiment, it is set to 0.2, which ensures the system's sensitivity to gas concentration changes while avoiding misjudgments caused by over-adjustment.

[0118] By calculating the mean of the gas concentration change rate during high-risk anomalies, and dynamically adjusting the change rate threshold based on the relative deviation between the mean and the preset change rate threshold, when the mean concentration change rate is greater than the preset change rate threshold, it means that the currently monitored gas concentration change rate has exceeded the normal range set by the system as a whole. This may mean that intestinal inflammatory activity is more frequent or severe, resulting in more drastic dynamic changes in gas concentration. At this time, if the original preset change rate threshold continues to be used, the system may not be sensitive enough to subsequent signals and miss some important change information. At the same time, re-evaluating high-risk anomalies based on the adjusted threshold and adjusting the synchronization threshold can optimize the sensitivity and specificity of the monitoring system in real time according to actual monitoring data. By dynamically adjusting the threshold, the system can better adapt to the individual differences and health changes of different users, capture potential abnormal health signals in a timely manner, and reduce misjudgments.

[0119] Specifically, the synchronization adjustment unit includes:

[0120] a color spot area change calculation subunit, configured to calculate the standard deviation of all the color spot areas of the high-risk events within a preset adjustment period to obtain a color spot area change value;

[0121] a deviation calculation subunit, connected to the color spot area change calculation subunit, for calculating the relative deviation between the color spot area change value and the preset area threshold value when the color spot area change value is greater than the preset area threshold value, to obtain an area deviation;

[0122] A synchronization adjustment subunit is connected to the deviation calculation subunit and is used to reduce the preset synchronization threshold according to the relative deviation between the area deviation and the preset deviation threshold and the preset synchronization adjustment coefficient when the area deviation is greater than the preset deviation threshold, so as to obtain the adjusted synchronization threshold, wherein L'=L×(1-b×(M-M0) / M0), L' is the adjusted synchronization threshold, L is the preset synchronization threshold, b is the preset synchronization adjustment coefficient, M is the area deviation, and M0 is the preset deviation threshold.

[0123] The preset area threshold is a benchmark used to determine whether a change in the spot area is abnormal. Its setting depends on the statistical distribution of spot areas under normal physiological conditions and the range of spot area changes under abnormal intestinal health conditions. It is typically set between 0.1 and 0.3. In this embodiment, it is set to 0.2, which ensures the system's sensitivity to spot area changes while avoiding misjudgments due to normal physiological fluctuations.

[0124] The preset deviation threshold is a benchmark used to determine whether the relative deviation between the spot area change value and the preset area threshold is abnormal. It depends on the distribution of the spot area change values ​​and the actual deviation range under abnormal conditions, and is typically set between 0.2 and 0.5. In this embodiment, it is set to 0.3, which ensures the system's sensitivity to spot area changes while avoiding misjudgments due to normal physiological fluctuations.

[0125] The preset synchronization adjustment coefficient is a parameter that determines the amplitude of the synchronization threshold adjustment. It is determined by balancing the sensitivity to synchronization changes and system stability, and is usually set between 0.1 and 0.3. In this embodiment, it is set to 0.2 to avoid misjudgment caused by excessive adjustment and ensure system stability and accuracy.

[0126] By calculating the standard deviation of the spot area change value, the system can quantify the dynamic change characteristics of the spot area. When the spot area change value exceeds the preset area threshold, it means that the current spot area fluctuation has exceeded the normal range, and there may be abnormal changes in intestinal health. At this time, the significance of this change is further evaluated by calculating the relative deviation between the spot area change value and the preset area threshold. If the area deviation exceeds the preset deviation threshold, it means that the change is significant, and the synchronization threshold needs to be adjusted to increase the sensitivity of monitoring. By reducing the preset synchronization threshold, the system can more sensitively capture changes in the correlation between the spot area and other indicators (such as changes in gas concentration), thereby identifying potential high-risk events more promptly.

[0127] See also Figure 4 As shown, it is a flow chart of the method for intelligent analysis of excrement of the smart toilet of this embodiment. On the other hand, this embodiment also provides a method for intelligent analysis of excrement of the smart toilet, including:

[0128] Real-time data collection: gas concentration in the toilet space, color spot area on the surface of solid excrement, foam concentration, and oil film area remaining on the toilet wall after flushing.

[0129] Determining the occurrence of a temporary event based on the gas concentration and a preset change rate threshold, and obtaining a temporary determination result;

[0130] Determining that an abnormal event occurs according to the temporary determination result, the color spot area, the foam concentration, and a preset synchronization threshold, and obtaining an abnormality determination result;

[0131] determining, based on the abnormality determination result, the gas concentration, and the foam concentration, that the type of the abnormal event is abnormal inflammatory activity, and obtaining an abnormality determination result;

[0132] Determine the abnormal event as a high-risk abnormality based on the timestamp of the abnormality determination result within a preset risk period, the oil film area, and the color spot area, and obtain a risk determination result;

[0133] adjusting the preset change rate threshold according to the risk determination result and the gas concentration to obtain an adjusted change rate threshold, and adjusting the preset synchronization threshold according to the risk determination result obtained again based on the adjusted change rate threshold and the color spot area to obtain an adjusted synchronization threshold;

[0134] An excrement change analysis report is outputted according to the risk determination result re-determined based on the adjusted synchronization threshold.

[0135] Through multi-dimensional, real-time monitoring and dynamic adjustment of thresholds, accurate monitoring of users' intestinal health is achieved. Starting from four key indicators: gas concentration, spot area, foam concentration and oil film area, these indicators will change significantly when intestinal inflammation is active, and there is a close logical correlation between them. For example, rapid changes in gas concentration usually indicate abnormal intestinal flora metabolism, while changes in spot area and foam concentration reflect the degree of inflammation of the intestinal mucosa and the physical state of the feces. By setting preset change rate thresholds and synchronization thresholds, the system can screen out abnormal events in a hierarchical and gradually refined manner, and ultimately determine whether they are high-risk abnormalities. This not only improves the accuracy of monitoring but also reduces the false alarm rate. In addition, by dynamically adjusting the thresholds, the monitoring parameters can be automatically optimized according to individual differences of users and intestinal health status, further improving the adaptability and reliability of the system. Finally, the fecal change analysis report output by the system provides users with real-time, personalized health monitoring, helping users to conduct daily intestinal health monitoring and management in a timely manner, thereby achieving early intervention and improving treatment effects and quality of life.

[0136] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An intelligent excrement analysis system for an intelligent toilet, characterized in that: include: The acquisition module is used to collect real-time data on the gas concentration in the toilet space, the area of ​​spots on the surface of solid excrement, the concentration of foam, and the area of ​​oil film remaining on the toilet wall after flushing when the target uses the smart toilet; a first determination module, connected to the acquisition module, for determining the occurrence of a temporary event based on the gas concentration and a preset change rate threshold, and obtaining a temporary determination result; a second determination module, connected to the acquisition module and the first determination module respectively, for determining the occurrence of an abnormal event based on the temporary determination result, the color spot area, the foam concentration, and a preset synchronization threshold, and obtaining an abnormality determination result; an abnormality determination module, connected to the acquisition module and the second determination module respectively, for determining the type of the abnormal event as abnormal inflammatory activity based on the abnormality determination result, the gas concentration, and the foam concentration, and obtaining an abnormality determination result; a risk determination module, connected to the acquisition module and the abnormality determination module, respectively, for determining that the abnormal event is a high-risk abnormality based on the timestamp of the abnormality determination result within a preset risk period, the oil film area, and the color spot area, and obtaining a risk determination result; an adjustment module, connected to the acquisition module and the risk determination module, respectively, and configured to adjust the preset change rate threshold according to the risk determination result and the gas concentration to obtain an adjusted change rate threshold, and to adjust the preset synchronization threshold according to the risk determination result obtained based on the adjusted change rate threshold and the color spot area to obtain an adjusted synchronization threshold; An output module is connected to the risk determination module and is used to output an excrement change analysis report according to the risk determination result re-determined based on the adjusted synchronization threshold.

2. The intelligent excrement analysis system for an intelligent toilet according to claim 1, characterized in that: The first determination module includes: a concentration rate calculation unit, configured to calculate a concentration change rate according to all gas concentrations within a preset determination time period based on a comparison result between the gas concentration and a preset concentration threshold; The temporary determination unit is connected to the concentration rate calculation unit and is used to determine the occurrence of a temporary event based on a comparison result between the concentration change rate and the preset change rate threshold, and obtain a temporary determination result.

3. The intelligent excrement analysis system for an intelligent toilet according to claim 2, characterized in that: The second determination module includes: an abnormal fluctuation calculation unit, configured to calculate a plurality of color spot fluctuation values ​​according to the color spot area within the preset determination time, and to calculate a plurality of concentration fluctuation values ​​according to the foam concentration within the preset determination time; The second determination unit is connected to the abnormal fluctuation calculation unit and is used to determine the abnormality determination result according to all the color spot fluctuation values ​​and all the concentration fluctuation values.

4. The intelligent excrement analysis system for an intelligent toilet according to claim 3, characterized in that: The second determining unit includes: a synchronization degree calculation subunit, configured to calculate a change synchronization degree based on all the color spot fluctuation values ​​and all the concentration fluctuation values; The second determination subunit is connected to the synchronization degree calculation subunit and is used to determine the occurrence of an abnormal event based on a comparison result between the change synchronization degree and the preset synchronization degree threshold, and obtain the abnormality determination result.

5. The intelligent excrement analysis system for an intelligent toilet according to claim 4, characterized in that: The abnormality determination module includes: an abnormal change calculation unit, configured to calculate a plurality of rate change values ​​based on all of the gas concentrations within a predetermined time period, and to calculate a plurality of concentration change values ​​based on all of the foam concentrations within a predetermined time period; An abnormality determination unit is connected to the abnormal change calculation unit and is used to determine the abnormality determination result according to all the concentration change values ​​and all the concentration change values.

6. The intelligent excrement analysis system for an intelligent toilet according to claim 5, characterized in that: The abnormality determination unit includes: a correlation calculation subunit, configured to calculate a change correlation based on all of the concentration change values ​​and all of the concentration change values; The abnormality determination subunit is connected to the correlation calculation subunit and is used to determine the type of the abnormal event as the abnormal inflammatory activity based on the comparison result of the change correlation and the preset correlation threshold, and obtain the abnormality determination result.

7. The intelligent excrement analysis system for an intelligent toilet according to claim 6, characterized in that: The risk determination module includes: a risk parameter calculation unit, configured to calculate an abnormality frequency based on all the time stamps, calculate an oil film fluctuation value based on all the oil film areas, and calculate a color spot change value based on all the color spot areas; a risk index calculation unit connected to the risk parameter calculation unit, for calculating a risk index based on the abnormal frequency, the oil film fluctuation value, and the color spot change value; A risk determination unit is connected to the risk index calculation unit and is used to determine that the abnormal event is a high-risk abnormality based on a comparison result between the risk index and a preset index threshold, thereby obtaining a risk determination result.

8. The intelligent excrement analysis system for an intelligent toilet according to claim 7, characterized in that: The adjustment module includes: a change rate average calculation unit, configured to calculate a concentration change rate average according to all gas concentrations within a preset adjustment period based on the risk determination result; a fluctuation threshold value adjustment unit connected to the change rate mean value calculation unit, configured to adjust the preset change rate threshold value according to a comparison result of the concentration change rate mean value and the preset change rate threshold value to obtain the adjusted change rate threshold value; The synchronization adjustment unit is connected to the fluctuation threshold adjustment unit and is used to adjust the preset synchronization threshold according to the risk determination result obtained based on the adjusted change rate threshold and the color spot area to obtain the adjusted synchronization threshold.

9. The intelligent excrement analysis system for an intelligent toilet according to claim 8, characterized in that: The synchronization adjustment unit includes: a color spot area change calculation subunit, configured to calculate a color spot area change value based on all the color spot areas within a preset adjustment period; a deviation calculation subunit, connected to the color spot area change calculation subunit, for calculating an area deviation based on a comparison result of the color spot area change value and a preset area threshold; The synchronization adjustment subunit is connected to the deviation calculation subunit and is used to adjust the preset synchronization threshold based on the comparison result between the area deviation and the preset deviation threshold to obtain the adjusted synchronization threshold.

10. A method for intelligent analysis of excrement from a smart toilet, applied to the intelligent analysis system for excrement from any one of claims 1 to 9, characterized in that: include: Real-time data collection: gas concentration in the toilet space, color spot area on the surface of solid excrement, foam concentration, and oil film area remaining on the toilet wall after flushing. Determining the occurrence of a temporary event based on the gas concentration and a preset change rate threshold, and obtaining a temporary determination result; Determining that an abnormal event occurs according to the temporary determination result, the color spot area, the foam concentration, and a preset synchronization threshold, and obtaining an abnormality determination result; determining, based on the abnormality determination result, the gas concentration, and the foam concentration, that the type of the abnormal event is abnormal inflammatory activity, and obtaining an abnormality determination result; Determine the abnormal event as a high-risk abnormality based on the timestamp of the abnormality determination result within a preset risk period, the oil film area, and the color spot area, and obtain a risk determination result; adjusting the preset change rate threshold according to the risk determination result and the gas concentration to obtain an adjusted change rate threshold, and adjusting the preset synchronization threshold according to the risk determination result obtained again based on the adjusted change rate threshold and the color spot area to obtain an adjusted synchronization threshold; An excrement change analysis report is outputted according to the risk determination result re-determined based on the adjusted synchronization threshold.

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