Stool gas time curve analysis method for bristol type classification

Abstract

The present invention relates to a stool gas analysis method for bristol type classification and, more specifically, to a stool gas time curve analysis method capable of classifying stool into bristol types according to a reduction rate of a gas concentration for each stool. When using a stool gas time curve analysis method for bristol type classification according to one embodiment of the present application, not only can stool be classified into the bristol types regardless of gender, age, diet, and stool weight, but also eating habits of an individual can be identified, and thus the analysis method can be applied to personal health monitoring by means of the bristol type classification of stool.

Description

Fecal gas time curve analysis for Bristol type classification

[0001] The present invention relates to a method for analyzing fecal gas for Bristol type classification and body condition analysis, and more specifically, to a fecal gas time curve analysis method that can classify the Bristol type of feces and analyze the body condition based on the rate of decrease in gas concentration over time for each feces.

[0002] This application claims priority to Korean Patent Application No. 10-2023-0073106, filed June 7, 2023, the entire disclosure of which is incorporated herein by reference.

[0003] Due to changing eating habits and the various stresses of modern people, digestive disorders are on the rise. To determine the progression and causes of these digestive disorders, it's important to monitor the condition of your daily bowel movements, the result of the digestion of the food you consume.

[0004] It would be nice if individuals could check the condition of their stool directly after defecation, but some people are reluctant to do so, and it is difficult for individuals to consistently collect information such as the time, number of times, and type of odor of defecation.

[0005] Another way to assess stool quality is to use fecal gas. This method uses one or more gas sensors to measure the absolute value of gas concentration directly from the stool, allowing for a more accurate assessment of stool quality. However, the absolute value of gas concentration varies depending on various measurement conditions and circumstances, leading to a limitation in accuracy.

[0006] Examples of technologies developed for analyzing fecal gas include an analysis system, a fecal odor gas analysis system, and an exhaled gas analysis system (Japanese Patent Publication No. 2020-187074). However, in-depth development and extensive research into more accurate and effective analysis methods for fecal gas analysis are still needed.

[0007] Accordingly, the inventors of the present invention have made great efforts to develop a fecal gas analysis method for Bristol type classification, and as a result, have developed a fecal gas time curve analysis method capable of classifying the Bristol type of feces based on the rate of decrease in gas concentration over time for each feces, thereby completing the present invention.

[0008] The present invention relates to a method for analyzing fecal gas for Bristol type classification and body condition analysis, and more specifically, to provide a fecal gas time curve analysis method that can classify the Bristol type of feces and analyze the body condition based on the rate of decrease in gas concentration over time for each feces.

[0009] However, the problems that the present invention seeks to solve are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below.

[0010] The first aspect of the present invention provides the same type of fecal gas time curve analysis method for Bristol type classification and body condition analysis.

[0011] The second aspect of this paper provides a fecal gas time curve analysis method for Bristol type classification and body condition analysis.

[0012] The third aspect of the present invention provides a method for outputting a stool gas time curve for Bristol type classification and body condition analysis.

[0013] By using the fecal gas time curve analysis method for Bristol type classification and body condition analysis according to one embodiment of the present invention, it is possible to classify the Bristol type of feces regardless of gender, age, diet, and fecal weight, and also to identify an individual's eating habits. Therefore, the above analysis method can be applied to personal health monitoring through Bristol type classification of feces, etc.

[0014] Figure 1 is a diagram showing the Bristol stool scale.

[0015] Figures 2a to 2c are diagrams showing a gas concentration graph output from seven sensors when measuring gas from one stool and a total gas concentration measurement graph (Figure 2c graph) that adds the measurement values ​​of the seven sensors in real time.

[0016] Figure 3 is a diagram showing a gas concentration measurement graph or a total gas concentration measurement graph of each of the seven sensors.

[0017] Figures 4a to 4e are diagrams showing the process of converting the total gas concentration measurement graphs of five actually measured 4Type stools into time curves, arranging them in consideration of the measurement time points after stool collection [Table 1], and then checking whether they overlap into one 4Type stool time curve.

[0018] Figure 5 is a diagram showing the complete time curves unique to Type 4 stools expected when the stool gas immediately after collecting stool in a toilet is set to 100%.

[0019] Figures 6a and 6b show individual gas concentration measurement graphs output from the VOCs sensor and the ETO sensor among the seven sensors of Figures 2a to 2c when measuring five 4Type stools, and Figure 6c is a drawing that is output by overlapping one time curve of each 4Type sensor through the same process as Figures 4a to 4e.

[0020] Figures 7a and 7b show time curves of five measured 4Type stools, and Figure 7c is a drawing output through the process of Figures 4a to 4e to check whether they overlap into one time curve.

[0021] Fig. 8 is a drawing output through the process of Figs. 4a to 4e to check whether the three time curves of the measured 2Type stool overlap into one time curve.

[0022] Figures 9a and 9b show time curves of five measured 6Type stools, and Figure 9c is a drawing output through the process of Figures 4a to 4e to check whether they overlap into one time curve.

[0023] Figure 10 is a drawing output through the process of Figures 4a to 4e to check whether the three time curves of 6Type stools in the case of not consuming spicy food overlap into one time curve.

[0024] Figure 11 is a drawing output through the process of Figures 4a to 4e to check whether the two time curves of 6Type stools when spicy food is consumed overlap into one time curve.

[0025] Figure 12 is a drawing showing curve fitting to obtain a graph formula by overlapping and outputting five time curves of the 4Type representations of Figures 7a and 7b.

[0026] Figures 13a to 13g are drawings showing the process of deriving a complete time curve unique to the 4Type of Figure 5 through the process of Figure 12.

[0027] Figure 14 is a diagram showing complete time curves unique to each stool type: Type 2, Type 4, Type 6 when spicy food was not consumed, and Type 6 when spicy food was consumed.

[0028] Below, with reference to the attached drawings, embodiments of the present invention are described in detail to facilitate easy implementation by those skilled in the art. However, the present invention can be implemented in various different forms and is not limited to the embodiments described herein. In the drawings, irrelevant parts have been omitted for clarity, and similar reference numerals have been used throughout the specification to indicate similar elements.

[0029] Throughout this specification, when it is said that an element is "on" another element, this includes not only cases where the element is in contact with the other element, but also cases where another element exists between the two elements.

[0030] Throughout this specification, when a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise specifically stated. The terms "about," "substantially," and the like, as used throughout this specification, are used to mean at or near the numerical values ​​indicated when manufacturing and material tolerances inherent to the meanings referred to, and are used to prevent unscrupulous infringers from unfairly exploiting disclosures that contain precise or absolute values ​​to aid understanding of this specification. The terms "step of doing" or "step of" as used throughout this specification do not mean "step for."

[0031] Throughout this specification, the term "combination(s) thereof" included in the expressions in the Makushi format means one or more mixtures or combinations selected from the group consisting of the components described in the expressions in the Makushi format, and means including one or more selected from the group consisting of said components.

[0032] Throughout this specification, references to “A and / or B” mean “A or B, or A and B.”

[0033] Hereinafter, implementation examples and embodiments of the present invention will be described in detail with reference to the attached drawings. However, the present invention may not be limited to these implementation examples and embodiments and drawings.

[0034] The first aspect of the present invention provides the same type of fecal gas time curve analysis method for Bristol type classification and body condition analysis.

[0035] According to one embodiment of the present invention, the present invention provides a stool gas time curve analysis method of the same type for Bristol type classification and body condition analysis, comprising the steps of: (a) measuring the concentration values ​​(ppm) of gases emitted from each stool using a gas sensor; (b) adding the concentration values ​​of the gases measured above in real time to derive a graph of the total gas concentration of each stool; (c) deriving a time curve of each stool by setting the point at which the gas begins to decrease in the derived gas concentration total measurement graph as 100%; (d) arranging the time curves of each stool derived above in the order of measurement time points after stool collection; (e) overlapping the time curves of the remaining stools based on the time curve of the stool measured first after stool collection and outputting them as a single time curve; and (f) confirming that data of stools of the same type overlap into a single time curve.

[0036] The term "time curve" as used throughout this specification means a graph of the rate of reduction (%) of gas over time.

[0037] As used throughout this specification, the term “post-stool collection time” refers to the time elapsed between the stool collection in the toilet and the start of the measurement in the laboratory.

[0038] The term "Time Shifting" as used throughout this specification refers to arranging the time curves to be analyzed in the order of measurement time points after stool collection.

[0039] According to one embodiment of the present invention, the step (a) comprises: a step of passing a prepared sample;

[0040] The method may include, but is not limited to, a step of turning on the switch of the gas sensor to start receiving data, turning on the fan within 2 minutes to circulate air within the gas sensor; a step of placing prepared feces on a feces collection paper within 2 minutes, closing the toilet cover to seal it as much as possible from the outside, and then attaching a connecting tube to connect the gas sensor and the toilet; a step of measuring feces gas for 20 to 40 minutes and then disconnecting the tube; and a step of turning off the switch of the gas sensor within 2 minutes to stop transmitting data.

[0041] When measuring fecal gas at our hospital, the gas does not decrease for the first 5 to 10 minutes and a constant signal is output, so in order to collect sufficient data, the fecal gas was measured for more than 20 minutes to measure the Time Curve. In addition, when the fecal gas was measured for more than 40 minutes, the decrease rate over time was too low, making it difficult to analyze the Time Curve (decrease rate over time). In addition, the longer the measurement time, the higher the probability of being affected by the surrounding environment, so the fecal data was measured for less than 40 minutes.

[0042] The second aspect of this document provides a fecal gas time curve analysis method for Bristol type classification and body condition analysis. Any content that overlaps with the first aspect of this document also applies to the second aspect.

[0043] According to one embodiment of the present invention, in a stool gas time curve analysis method for Bristol type classification and body condition analysis, the present invention comprises the steps of: (a) measuring the concentration values ​​(ppm) of gases coming from each stool using a gas sensor; (b) adding the concentration values ​​of the gases measured above in real time to derive a graph of the total gas concentration of each stool; (c) deriving a time curve of each stool by setting the point at which the gas begins to decrease in the derived gas concentration total measurement graph as 100%; (d) arranging the time curves of each stool derived above in the order of measurement time points after stool collection; (e) overlapping the time curves of the remaining stools based on the time curve of the stool measured first after stool collection and outputting them as a single time curve; (f) confirming that data of stools of the same type overlap into a single time curve; (g) A step of deriving a time curve equation by superimposing the time curves of the same type of stools confirmed above and performing curve fitting on the time curve; (h) A method for analyzing a stool gas time curve for Bristol type classification and body condition analysis is provided, comprising the steps of: (i) deriving a type of time curve based on 100% of the amount of gas immediately after stool collection through calculation; and (ii) comparing the result with other types of stool time curves.

[0044] In the above step (h), the “amount of gas (%) at 0 minute of the time curve equation” means the y-intercept of the time curve equation derived in the above step (g).

[0045] The third aspect of this application provides a method for outputting a stool gas time curve for Bristol type classification and body condition analysis. Any content overlapping with the first and second aspects of this application also applies to the third aspect.

[0046] According to one embodiment of the present invention, the present invention provides a method for outputting a stool gas time curve for Bristol type classification and body condition analysis, comprising the steps of: (a) measuring the concentration value (ppm) of each gas coming from one stool using a gas sensor; (b) deriving a time curve for each gas by taking the point at which the concentration value of each gas measured above begins to decrease as 100%; and (c) arranging the time curves of each gas derived above in the order of measurement time points after stool collection.

[0047] Hereinafter, the present invention will be described in more detail through examples of the present invention. However, the following examples are provided only to help understanding of the present invention, and the contents of the present invention are not limited to the following examples.

[0048] [Example]

[0049] Example 1. Gas sensor and sample placement

[0050] (1) Preparation of gas sensor

[0051] After connecting the power and stabilizing the gas sensor, the gas sensor array was made to measure a person's exhaled breath to confirm whether the gas sensor was connected and functioning normally.

[0052] (2) Sample preparation and storage

[0053] After installing the stool sample in the toilet, the switch was turned on to begin receiving data from the gas sensor. After 2 minutes, the fan was turned on to allow outside air to be sucked and circulated through the gas sensor array. After 2 minutes, the prepared stool was placed on the stool sample and the toilet lid was closed to create a sealed environment. A tube was attached to the toilet lid to connect the toilet and the gas sensor array so that the stool gas in the toilet could be sucked into the sensor array. After measuring the stool gas for approximately 30 minutes, the tube was disconnected. After 2 minutes, the gas sensor switch was turned off to stop data transmission.

[0054] Example 2. Measurement of fecal gas and output of time curve

[0055] (1) Gas measurement and time curve output for each stool

[0056] Fecal gas was measured using 13 stool samples, varying in Bristol type (see Figure 1), diet, subject, age, gender, and stool weight. The collected stool samples were not measured immediately after collection from the toilet, and the fecal gas measurement experiment proceeded as follows:

[0057] Step 1. Defecate in the toilet and collect stool in a stool container.

[0058] Step 2. Take the stool to the lab.

[0059] Step 3. Attach a stool collection strip to the toilet installed in the laboratory, and place the collected stool on the strip.

[0060] Step 4. Measure stool data for 30 minutes.

[0061] Considering that the location of the toilet where the subject collected stool (distance from the laboratory) and the time required to set up the experimental equipment varied for each experiment, the 'time from stool collection in the toilet to the start of measurement in the laboratory' for the 13 collected stools were all different. For example, the stool sample collected on the first day was measured on the laboratory toilet 9 minutes after collecting stool in the toilet, and the stool sample collected on the second day was measured on the laboratory toilet 30 minutes after collecting stool in the toilet, and data were collected for 30 minutes. The time from stool collection in the toilet to the start of measurement in the laboratory (time point after stool collection) for the 13 stools is as shown in [Table 1] below.

[0062] [Table 1]

[0063]

[0064] Person A: Woman, Person B: Woman, Person C: Man, Person E: Man

[0065] For stool data measurement, stool was first placed on a stool collection paper installed in the toilet, the toilet lid was closed, and a tube was connected to measure the stool gas for about 30 minutes. SO2, H2S, NH3, ETO, VOCs, CH2O, and C2H4 sensors were selected as the targets of time curve analysis. In addition to the time curve for each sensor, the time curve for each stool type was analyzed through a graph of the total gas concentration obtained by adding the values ​​measured from the seven sensors in real time (i.e., both the gases measured from each of the seven gas sensors and the sum of these gases were used). The point at which the gas began to decrease in the gas concentration measurement graph or the total gas concentration measurement graph output from each gas sensor was set to 100%, and a time curve was output for each stool (see Fig. 3).

[0066] Hereinafter, the time curve refers to a graph of the gas reduction rate over time.

[0067] (2) One type of time curve output using the gas total measurement graph of 7 sensors: Analysis of one gas total measurement graph per stool

[0068] Seven sensors, including SO2, VOCs, CH2O, ETO, C2H4, H2S, and NH3, were selected for time curve analysis. For the time curve analysis by stool type, both individual gas concentration measurement graphs from each sensor and a summation graph of gas concentration measurements from all seven sensors were used. In this analysis, the summation graph of gas concentration measurements from all seven sensors in real time was used for time curve analysis.

[0069] A time curve is a graph of gas reduction rate [%] over time. Furthermore, stool gas is highly time-sensitive, making time a crucial factor in analysis. Therefore, for all analyses, the time curves for each stool type were arranged (time-shifted) based on the "measurement time point after stool collection" and then the graphs were superimposed.

[0070] Below, the analysis of the 4Type stool time curve is described, and the same analysis was performed for Type 2 and Type 6.

[0071] Type 4 contains five stool samples, or five time curves. All five stool samples were collected on different days, and the diets, gender, and age of the individuals were all different. The information for the five Type 4 stool samples collected is shown in [Table 2] below.

[0072] [Table 2]

[0073]

[0074] The following is the step of analyzing the time curves of the 4Type 5 stools (data analysis step in Figures 4a to 4e).

[0075] Step 1. Create a graph measuring the total gas concentration of each stool.

[0076] When measuring a single stool sample, gas concentration measurement graphs from each of the seven gas sensors were output individually, and these were converted into a total gas concentration measurement graph by adding them all up in real time. In other words, a single total graph was analyzed when analyzing a single stool sample (Fig. 2c graph).

[0077] Step 2. Deriving a time curve from the graph of the total gas concentration of each of the five stools, with the starting point of gas reduction as 100%: The graphs of the total gas concentrations from the five stools were converted into five time curves.

[0078] Step 3. Arrange the time curves of the five stools by the measurement time after stool collection (0 minutes), not by the measurement date (Time Shifting).

[0079] The time curves of the five stools derived above are time shifted in the order of measurement time after each stool collection (see Table 2).

[0080] Step 4. Adjust the ratio of the time curves of the other four stools based on the time curve of the first stool measured after collection.

[0081] [Table 2] and [Figures 4a to 4e] show that the first stool measured in the laboratory after defecation, i.e., stool collected in the toilet, is the 4Type 20.67g stool data (purple graph) of Person A collected on the fourth day (Day 4). Based on the time curve of the corresponding stool, the ratios of the remaining four stool time curves were adjusted to check whether the time curves of the five 4Type stools were output as a single time curve.

[0082] The method for adjusting the ratio of the remaining four curves based on the first measured stool curve after stool collection is as follows.

[0083] For example, on the second day (Day2), the 27.4g stool of Person A of Type 4 was measured in the laboratory 24 minutes after the stool was collected. Therefore, 24 minutes after the stool collection in the toilet, the gas reduction rate of Person A's 27.4g stool of Type 4 (red graph) is 100%, and the gas reduction rate of the 20.67g stool of Type 4 (purple graph) of Person A, which is the reference, is 45%. At this time, since the time curve of the 20.67g stool of Type 4 of Person A (purple graph), which was measured first after the stool collection, should be the standard for the ratio adjustment, the time curve of the 27.4g stool of Type 4 of Person A (red graph) was multiplied by 45 / 100 to check whether the curves of the two stools overlapped into a single time curve. Through this process, the remaining stool data were output as time curves based on the reference stool data (purple graph) (see Figures 4a to 4e).

[0084] Step 5. Check if a single curve appears.

[0085] When the ratio of each side curve was adjusted as above, it was confirmed that the time curves of the five 4Type sides were overlapped and output as a single time curve (Figs. 7a to 7c).

[0086] In addition to the 4 types analyzed above, the time curves of 2 types (Fig. 8) and 6 types of stool (Figs. 9a to 9c) were also analyzed, and the analysis results confirmed the existence of a unique time curve for each type. On the other hand, it was confirmed that the time curve of 6 types of stool could be classified according to whether spicy food was consumed.

[0087] This confirms that when the time curves are superimposed and output based on the first measured stool after each stool type is collected, all of the superimposed output stools are of the same type if they are drawn as a single graph.

[0088] (3) Output of one type of time curve using each of the seven sensors: Analysis of the gas measurement graph of each of the seven sensors per stool

[0089] This analysis analyzes the time curves through the individual gas concentration measurement graphs of the sensors. When the gas of one stool is measured, the seven gas concentration measurement graphs output from each of the seven sensors are each output as a time curve. In other words, each sensor outputs a stool time curve, and similar to the experiment above, the time curves of stools of the same type are time-shifted by considering the measurement time after each stool collection, and then the time curve graphs of other stools are superimposed on the time curve of the stool measured first after stool collection, and output and analyzed.

[0090] For example, after time-shifting the five time curves of the VOCs sensor that measured five 4-type feces by considering the measurement time after each feces collection, the time curves of other feces were proportionally adjusted to match the time curve of the feces measured first after the feces collection. In Figures 6a to 6c, it was confirmed that the five time curves of the VOCs sensor for the 4-type feces were all overlapped and output as a single curve.

[0091] As a result of the analysis, it was confirmed that each of the seven sensors outputs one time curve for one stool type (see Figures 6a to 6c).

[0092] (4) Output and comparison of various types of time curves

[0093] In order to confirm the existence of a unique time curve for each stool type, the start point of decrease of the stool measured first after stool collection was set to 100% for each stool type and the time curve was output. However, since the actual stool gas amount is the largest immediately after stool collection in the toilet, the expected time curve was output when immediately after stool collection was set as 100% and the gas reduction rate graph for each type was compared (see Fig. 5). At this time, the total gas concentration measurement graph obtained by adding up the seven sensors in real time, rather than the individual sensor measurement graph, was used for the analysis. Fig. 5 shows the time curve of one of the five measured stools of the four types, considering the measurement time point after stool collection.

[0094] However, the above-mentioned fecal gas measurement method is to move the feces collected in the restroom to the laboratory for measurement, and since it is difficult to measure immediately after collecting the feces in the restroom, the collected feces data does not have 'data from immediately after collecting the feces to before measurement in the laboratory (feces movement time)'. Therefore, in order to estimate the data that does not exist, the equations of the time curves for each type (Figs. 7a, 7b, 7c, 8, 10, and 11) that were actually measured and overlaid above were derived by curve fitting (Fig. 12).

[0095] The time curves (Figs. 7a, 7b, 7c, 8, 10, and 11) are curve-fitted to derive a time curve equation for each stool type, with the starting point of the decrease in the first measured stool after stool collection set to 100%. In the derived time curve equation, the time curve equation is adjusted as follows to set the gas reduction rate immediately after stool collection (0 minutes) to 100%, thereby deriving a complete time curve unique to each stool type. The corresponding analysis process is illustrated in Figs. 13a to 13g.

[0096]

[0097] A gas reduction rate graph was derived by following this process for each type (see Figure 10). The analysis results revealed a unique, complete time curve for each stool type, confirming the gas reduction rate and trend over time for each stool type (Figure 14).

[0098] The analysis results showed that there was a unique gas reduction rate graph (time curve) depending on the stool type, and the gas reduction rate and trend over time for each stool type could be confirmed.

[0099] The above description of the present invention is for illustrative purposes only, and those skilled in the art will readily appreciate that the present invention can be readily modified into other specific forms without altering the technical spirit or essential characteristics of the present invention. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. For example, each component described as a single entity may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined manner.

[0100] The scope of the present invention is indicated by the claims described below rather than the detailed description above, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention.

Claims

1. In the same type of fecal gas time curve analysis method for Bristol type classification and body condition analysis, (a) A step of measuring the concentration value (ppm) of gases coming from each stool using a gas sensor; (b) a step of adding the concentration values ​​of the gases measured above in real time to derive a graph measuring the total gas concentration of each stool; (c) A step of deriving a time curve for each side by setting the point where the gas starts to decrease as 100% in the gas concentration total measurement graph derived above; (d) a step of arranging the time curves of each stool derived above in the order of measurement time points after each stool collection; (e) a step of overlapping the time curves of the remaining feces based on the time curve of the first measured feces after collection and outputting it as a single time curve; and (f) A method for analyzing the same type of stool gas time curve for Bristol type classification and body condition analysis, including a step of confirming that data of the same type of stool overlaps into one time curve.

2. In paragraph 1, Step (a) above, Step of placing the prepared sample; Step of turning on the switch of the gas sensor to start receiving data, and turning on the fan within 2 minutes to circulate air inside the gas sensor; The step of placing the prepared feces on the toilet bowl within 2 minutes, closing the toilet lid to seal it as much as possible from the outside, and then installing a connecting pipe to connect the gas sensor and the toilet; Step of disconnecting the tube after measuring the stool gas for 20 to 40 minutes; and Including a step of stopping data transmission by turning off the switch of the gas sensor within 2 minutes, Same type of fecal gas time curve analysis method for Bristol type classification and body condition analysis.

3. In paragraph 1, The gas sensor of the above step (a) is at least one selected from the group consisting of SO2, VOCs, CH2O, ETO, C2H4, H2S and NH3. Same type of fecal gas time curve analysis method for Bristol type classification and body condition analysis.

4. In the fecal gas time curve analysis method for Bristol type classification and body condition analysis, (a) A step of measuring the concentration value (ppm) of gases coming from each stool using a gas sensor; (b) a step of adding the concentration values ​​of the gases measured above in real time to derive a graph measuring the total gas concentration of each stool; (c) A step of deriving a time curve for each side by setting the point where the gas starts to decrease as 100% in the gas concentration total measurement graph derived above; (d) a step of arranging the time curves of each stool derived above in the order of measurement time points after each stool collection; (e) A step of overlapping the time curves of the remaining feces based on the time curve of the first feces measured after collection and outputting it as a single time curve; (f) a step of confirming that data of the same type of stool overlaps into one time curve; (g) A step of deriving a time curve equation by performing curve fitting on the time curve derived by overlapping the time curves of the same type of stools confirmed above; (h) A step of deriving one type of time curve based on the amount of gas immediately after stool collection by calculation; and (i) A method of stool gas time curve analysis for Bristol type classification and body condition analysis, including a step of comparing with other types of stool time curves.

5. In paragraph 4, Step (a) above, Step of placing the prepared sample; Step 1: Turn on the switch of the gas sensor to start receiving data, and connect the fan within 2 minutes to circulate air inside the gas sensor; Step 2: Place the prepared feces on the toilet paper tray within 2 minutes, close the toilet lid to seal it as much as possible from the outside, and then attach a connecting pipe to connect the gas sensor and the toilet; Step of disconnecting the tube after measuring the stool gas for 20 to 40 minutes; and Including a step of stopping data transmission by turning off the switch of the gas sensor within 2 minutes, Fecal gas time curve analysis method for Bristol type classification and body condition analysis.

6. In paragraph 4, The gas sensor of the above step (a) is at least one selected from the group consisting of SO2, VOCs, CH2O, ETO, C2H4, H2S and NH3. Fecal gas time curve analysis method for Bristol type classification and body condition analysis.

7. In the method of outputting the stool gas time curve for Bristol type classification and body condition analysis, (a) A step of measuring the concentration value (ppm) of each gas coming from a single stool using a gas sensor; (b) a step of deriving a time curve for each gas by taking the point at which the concentration value of each gas measured above begins to decrease as 100%; and (c) A method for outputting a stool gas time curve for Bristol type classification and body condition analysis, including a step of arranging the time curves of each gas derived above in the order of measurement time after stool collection.

8. In paragraph 7, Step (a) above, Step of placing the prepared sample; Step 1: Turn on the switch of the gas sensor to start receiving data, and connect the fan within 2 minutes to circulate air inside the gas sensor; Step 2: Place the prepared feces on the toilet paper tray within 2 minutes, close the toilet lid to seal it as much as possible from the outside, and then attach a connecting pipe to connect the gas sensor and the toilet; Step of disconnecting the tube after measuring the stool gas for 20 to 40 minutes; and Including a step of stopping data transmission by turning off the switch of the gas sensor within 2 minutes, A method for outputting stool gas time curves for Bristol type classification and body condition analysis.

9. In paragraph 7, The gas sensor of the above step (a) is at least one selected from the group consisting of SO2, VOCs, CH2O, ETO, C2H4, H2S and NH3. A method for outputting stool gas time curves for Bristol type classification and body condition analysis.

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