Biometric information management system

Abstract

By statistically processing vital sign data up to now in accordance with the characteristics of the individual subject, it is possible to determine daily values ​​taking into account differences and trends in data due to individual characteristics (weight, sex, medical history, etc.). [Solution] The system includes a BS step in which vital sign data of the target organism is continuously or intermittently acquired using a sensor attached directly to the target organism and / or a fixedly installed sensor, and stored in a server; an ND step in which a processing device extracts resting state data that satisfies predetermined set conditions from the stored vital sign data, and statistically processes a group of data for the target organism's resting state over a predetermined period as daily value data; and a PN step in which current or most recent vital sign data for each target organism is displayed in real time, and daily value data for a period of at least a predetermined period is displayed in parallel or superimposed fashion.

Description

[Technical field]

[0001] This invention relates to a biological information management method and a biological information management system for displaying and managing the vital signs (e.g., pulse rate, respiratory rate, and body temperature) of the current life activities of individual living organisms, including animals and humans, as biological information. In particular, this invention includes domesticated mammalian animals, such as pet dogs and cats, and humans as individual living organisms. [Background technology]

[0002] In health checkups for healthy people, the patient's measured values ​​obtained in the test results are compared with standard values. Standard values ​​are values ​​set uniformly throughout the country based on statistics on the health data of the entire population. In health checkups, these standard values ​​are generally considered to be normal values, and normality or abnormality is judged. Previously disclosed sensors for monitoring the health or wellness of animals include a wearable device (and associated base station(s), if present) and a DMS (Patent Document 1). This can form part of a health monitoring system used to collect data on and / or monitor certain health attributes of one or more animals. The health monitoring system can receive data from, for example, non-invasive home telematics solutions. The system can receive data from smart mats, smart movement / IF detectors, and other devices prevalent in the market. Indoor pets and animals can trigger these devices to record sensor artifacts such as presence, weight, physiological signs, and vital signs.

[0003] Another conventionally disclosed information processing device includes a prediction unit that predicts the future state of the care recipient based on the condition information of the care recipient (see Patent Document 2). For example, the prediction unit is said to be able to compare previously acquired condition information with currently acquired condition information and predict the future state of the care recipient based on the comparison result. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Special Publication 2016-514961 [Patent Document 2] Patent Publication No. 2015-062118 DISCLOSURE OF THEINVENTION [Problem to be solved by the invention]

[0005] However, standard values ​​should differ depending on individual characteristics (weight, sex, medical history, etc.), and should be compared with standard values ​​for a group that matches one's characteristics, or with everyday values ​​that take into account the characteristics of a specific individual. This is because the range of values ​​that should be considered normal differs depending on attributes and individual characteristics. In other words, standard values ​​should be adjusted based on individual characteristics, species, and other classifications.

[0006] In particular, it is thought that it is insufficient to simply compare the measured values ​​during a health check with the general standard values. In other words, by comparing with everyday values ​​that take into account the everyday characteristics of the individual, rather than simply comparing with the general standard values, it is possible to more accurately determine whether the current vital signs (biological information) values ​​for that individual are normal or abnormal compared to the everyday values ​​of that individual in a healthy state.

[0007] Even if we consider an example other than health checkups, when a doctor encounters a patient with a chronic illness, they will estimate the condition of the patient by comparing the test results of the patient with the standard values ​​of healthy people. However, in reality, they should be comparing the standard values ​​of a group of patients with the same chronic illness with the patient's everyday values. Using only the standard values ​​of generally healthy people as a reference, it is not possible to accurately estimate the patient's current condition.

[0008] The reason why normality or abnormality cannot be judged based on standard values ​​or daily values ​​that take into account the current condition of each individual is that multiple time series of biological information and test results from the same individual are required to do so. It is difficult to judge daily values ​​by simply recording measurements taken at the time of a visit to the hospital, and daily values ​​can only be understood by recording the results of daily measurements taken by the patient, including at home.

[0009] In order to take into account the characteristics and attributes of individual organisms and statistically process measurement values ​​under the same conditions, a large amount of measurement data from patients under the same conditions would be required, making it difficult to set up unless the measurement data measured at each hospital and at home are managed in a centralized manner.

[0010] Therefore, the objective of the present invention is to provide a biological information management system that can determine daily values ​​taking into account differences and trends in data due to individual characteristics (weight, sex, medical history, etc.) by measuring the vital sign data of a target individual organism and performing statistical processing of previous vital sign data suited to the characteristics of the target individual organism. [Means for solving the problem]

[0011] The following measures have been taken to solve the above problems.

[0012] [1] (Comparison with daily data) The present invention is a system that displays the vital signs (e.g., pulse rate, respiratory rate, and body temperature) of the current life activity of each individual living organism, including animals and humans, in real time as biological information, and is characterized in that the display is made comparable to "daily value data," which is a statistically processed value of the data of the target individual living organism in its daily resting state. That is, the biological information management system of the present invention relates to a system that acquires and manages vital sign data, including at least one of pulse rate, respiratory rate, and body temperature, of a target individual living organism, including humans, as information on the life activity of the target individual living organism, The system comprises a vital sign sensor and a transceiver attached to a target biological individual, a server for storing transmitted and received data, a processing device for processing data from the server, and an output device for outputting the processing contents, A BS step of continuously or intermittently acquiring vital sign data of the target organism by a sensor directly attached to the organism and / or a fixedly installed sensor, and storing the data in a server; an ND step of extracting resting state data that satisfies a predetermined set condition from the stored vital sign data by the processing device, and statistically processing a group of resting state data of the target organism over a predetermined period as daily value data; Regarding the target organism, and a PN step of displaying in parallel or superimposed fashion the current or most recent vital sign data for each target individual organism and the daily value data for a predetermined period or longer. The device is characterized by displaying a comparison result showing how much the vital signs of the target organism at the current time or the most recent time or the calculated values ​​based on them deviate from the cumulative value data of the target organism. In the above and hereinafter, vital sign data refers to detection data of the vital activity of a target individual organism (including, for example, pulse rate, respiratory rate, and body temperature), and processed values ​​calculated or extracted from this vital sign data by statistical processing, arithmetic, or discrimination processing of the target individual organism or its attribute group are referred to as daily value data of vital information. The management system of the present invention is a system that displays or manages daily value data of vital information obtained by extracting daily value data, calculating upper and lower limits, and average values, etc.

[0013] [2] (Calculation of upper limit, lower limit and average value by statistical processing) The present invention is characterized in that the daily value data is calculated by statistical processing of the upper limit, lower limit, and average value. That is, the biological information management system is as follows: A BS step (data acquisition step) of constantly acquiring vital sign data of the target organism by the sensor directly attached to the organism and / or the sensor fixedly installed, and storing updated data at regular time intervals; An ND step (statistical processing step) of extracting resting state data from the vital sign data of the subject organism, statistically processing only the resting state data over a predetermined period by means of histogramming (for example, normal distribution approximation by Fourier transform), etc., and creating and storing data on the upper limit, lower limit and / or average value on the histogram data (normal distribution approximation data) in the resting state over the predetermined period up to the most recent time; a PD step (accumulation processing step) for creating and storing the central value, upper limit value, lower limit value, and standard deviation of the histogram data as accumulated data; A CD step (comparison processing step) of performing a numerical comparison between real-time vital sign data at the current time or the most recent time by the ND step and each data of any of the steps, and displaying and storing the comparison result; A PN step (output processing step) is performed in which real-time display of vital sign data for the current or most recent time for each target individual organism and a comparative display of daily values ​​over a predetermined period of time are superimposed on a gauge displayed in the form of a straight bar. A biological information management system characterized by displaying in real time a comparison result of how much each value of the vital signs of the target biological individual at the current time or the most recent time, or a calculated value based thereon, currently deviates from the cumulative value data of the target biological individual (average cumulative value at rest).

[0015] [4] (Comparison display with attribute value data) The present invention is characterized in that, in addition to the "daily value data", attribute value data of attribute groups are displayed in a comparable manner. This biological information management system includes a step (F31) of setting a predetermined attribute group (large / small / male / female) to which the target biological individual belongs in any of the above systems; A step (F1) of storing the vital sign data of the predetermined attribute group in a server; A step (F32) of extracting daily value data of the predetermined attribute group from the server by the processing device and statistically processing group attribute value data of the predetermined attribute group under specific conditions; and (F4) displaying in parallel or in superimposition a real-time display of current or recent vital sign data for each target individual organism and group attribute value data of a predetermined condition of a predetermined attribute group including the target individual organism over a predetermined period of time or more. The present invention is characterized in that it outputs a comparison result between each value of the current vital sign data of the target individual organism and statistically processed attribute value data in a resting state of an attribute group including the target individual organism.

[0016] Here, attribute value data refers to data obtained by accumulating and statistically processing resting state data or daily value data obtained for each of multiple biological individuals that meet a specified attribute standard. Attribute value data for a specific target biological individual is data obtained by statistically processing or calculating using as original data the resting state data or daily value data of multiple biological individuals included in a specified attribute value group to which the target biological individual falls. The original data also includes the resting state data or daily value data of the symmetrical grain individual itself.

[0017] For example, the results of a numerical comparison between daily values ​​and accumulated attribute value data for a specific attribute group can be displayed simultaneously with the current vital sign data. "Simultaneous display" refers to either superimposed display, side-by-side display, or switching display. By displaying statistically processed values ​​of accumulated information for either daily value data or attribute value data in a comparable manner, it is possible to compare the characteristics of an attribute group to which a specific individual belongs with the average value within the same attribute group, thereby making it possible to more accurately evaluate the current vital sign data.

[0018] [Definition of "attribute value"] Here, the term "attribute value" and "attribute value data" in the present invention refers to a value or data after statistical processing calculated based on the accumulation of daily value data of the individual organisms to which the individual organism belongs when the attribute of the individual organism is compound-classified by a plurality of attribute parameters. For example, the value corresponds to the average value of the daily values ​​of the individual organisms compound-classified into the attribute by day, time period, or time.

[0019] (Definition of "daily value") In addition, the term "daily value" and "daily value data" in the present invention refers to vital sign data of a subject individual organism at rest, excluding active states and states receiving non-daily stimulation, and refers to daily values ​​or data for each day, time period, or time. For example, the daily value or range is the value or range for each time period obtained by statistically processing (e.g., averaging) data on resting states on multiple measurement days for each time period or time, or the value or range obtained by statistically processing (e.g., averaging) all measurement information for all measurement times.

[0020] If the value changes depending on the time of day or time period, the average value for each day divided into each time period corresponds to the daily value for that time period. In addition, statistical processing is used to calculate each value such as the most frequent daily value, the upper limit of the daily value, and the lower limit of the daily value.

[0021] The attribute value is a value displayed as a guideline for whether the attribute of the individual is normal or abnormal, compared to the daily value of the attribute of the individual. In other words, the attribute value data is the daily value data of other animals in the same attribute group, and does not represent a comparison result of normality or abnormality. Whether the current condition of the animal is normal or abnormal is judged by a veterinarian.

[0022] [5] (Comparison of daily value data and excluded attribute value data) A step of statistically processing excluded attribute value data, which is a daily value data group of a plurality of organisms in an attribute group to which a target organism belongs, excluding the daily value data of the target organism; The daily value data of the target individual organism is compared with excluded attribute value data of the attribute group of the individual organism excluding the daily value data of the individual organism, and the comparison result is output.

[0023] To supplement the predictions of recovery before and after surgery for healthy individuals, The area below the 5% significance level of the standard normal distribution plot of vital sign data obtained before surgery is compared with the area below the 5% significance level of the standard normal distribution plot of vital sign data obtained after surgery, and the agreement rate is calculated. Veterinarians use the agreement rate to judge the postoperative recovery status.

[0024] [6] (Hospitalization and visit information) The method further includes a step of setting hospitalization information or hospital or facility visit information for a predetermined symptom of the target biological individual, The data on the resting state is output separately for data at the time of admission or visit to the hospital and data when at home, and as an alert step, a numerical comparison with values ​​from other attribute groups is made to determine whether the difference in value exceeds a threshold, and if it is detected that the threshold has been exceeded, that information is notified.

[0025] (Data recorded before and after symptoms) The system may further include a step of recording data before and after the symptom, i.e., a step of recording data of the resting state of the target organism during a pre-operative or post-operative period as recorded data before and after a specific symptom, and the pre-operative and post-operative data may be recorded as group information including a progress history, and the pre-operative and post-operative data may be compared with a health state to predict and output a comparison result.

[0026] For example, by combining and comparing data from the attribute groups "medical history," "surgical history," "before and after surgery," and "before and after contraception," it is possible to output a predicted result of the postoperative progress compared to the state at rest before surgery based on the recovery curve, in other words, to predict when the patient will be able to move and when the restraints will be removed, and output the predicted timing.

[0027] (Anesthesia decision based on preoperative examination information) The postoperative follow-up observation system may also be a system including anesthesia judgment based on preoperative examination information and intraoperative information. That is, the system may further include a step of recording vital sign data from a preoperative examination and / or vital sign data during surgery, and a step of recording vital sign data in postoperative follow-up observation, and may compare progress information of vital sign data at each step for each anesthesia information, and output as an alert when a predetermined condition is satisfied. In the alert, for example, it is determined whether or not the transmission data exceeds a preset upper limit, lower limit, or average value, and an alert is output when it is detected that the predetermined threshold value has been exceeded. The time period comparison value, the active comparison value, and the rest comparison value may be output together.

[0028] This system links and records preoperative examination information, vital sign data from surgical information, and data on after-effects from postoperative follow-up observation, and can accumulate and statistically process the data as information on the effects of individual biological anesthesia on multiple subjects.

[0029] [7] (Comparison with healthy daily value data) The biological information management system according to claim 1, further comprising a step of recording as recorded data healthy daily value data that satisfies predetermined healthy discrimination conditions, among the daily value data of the target biological individual in a resting state, excluding data on the occurrence time of specific symptoms including the pre-operative or post-operative period, and outputting a comparison result between the most recent vital sign data of the target biological individual and the healthy daily value data in a healthy state.

[0030] [8]((Alert output) The upper limit, lower limit, and average values ​​set in advance in the transmitted data may be, for example, attribute values ​​that are statistical values ​​of a biological population of the same attribute group, and / or values ​​of the health state of the target biological individual at rest. For example, a real-time measurement value is compared with the average attribute value / and the average daily value to determine whether it exceeds a predetermined numerical difference set in advance, and if it exceeds the difference from either comparison, an alert is outputted in a manner that distinguishes whether the difference from the attribute value comparison or the daily value comparison has been exceeded.

[0031] [9] (Wearable transmitter) The sensor for acquiring vital data of the target organism may be a wearable transmitter that is in close contact with the target organism, as shown in FIG. 24 or FIG. 41, in which a periodic transmission sensor is attached to a jacket or harness band that is in close contact with the torso (including the chest, ventral and dorsal) of the target organism (or around the body surface excluding the limbs and neck).

[0032] By using a close-fitting wearable transmitter as the vital sign sensor, vital sign data can be reliably acquired at regular intervals by constantly wearing the vital sign sensor around the chest, ventral back, or body surface of the target organism excluding the limbs and neck. This makes it possible to constantly acquire vital sign data of the target organism, grasp its tendency, and display a highly accurate comparison value. In particular, in FIG. 41, the vital sensor is a jacket-type or harness-band equipped with a curved wire-type sensor 22WS.

[0033] (Used in conjunction with an intestinal insertion testing device (pulse oximeter)) In addition to the above-mentioned close-fitting wearable transmitter, an intestinal insertion testing device (pulse oximeter) is also used as a vital sign sensor. At least the pulse rate and rectal temperature may be measured using an intraenteral insertion examination device (pulse oximeter) and used to calculate the estimated rectal temperature or to check an error in the pulse rate.

[0034]

[10] The sensor for acquiring vital data of a target organism may be a biometric information management system consisting of a wearable transmitter having a curved wire-type sensor attached along the jacket surface of a jacket garment or along the band surface of a harness band.

[0035]

[11] The resting data is stored as daily value data along with time information. The biological information management system may display a frequency distribution or relative frequency distribution of the cumulative data values ​​of daily value data accumulated and stored as time information for a specified time period as a linear gradation bar in which class values ​​are represented in the direction of the length of the bar as sections of a certain length, and display the frequency of each class value that divides the gradation bar by a change in color or a change in the shading pattern.

[0036] For example, as shown in Figures 25 and 26, the biometric information management system may display the frequency (number of data acquisitions) / relative frequency (number of acquisitions per section / total number of acquisitions) as a linear gradation bar (or a color bar if colored) with frequency divisions along the length of the bar.

[0037]

[12] Daily value data for each time period of a group of organisms in the same attribute group, which has the same attributes as the target organism, is accumulated and stored together with time information as accumulated attribute value data (attribute value data obtained by accumulating daily value data of the same attribute). The biometric information management system may display the cumulative data value of the accumulated and stored attribute value data as a gradient bar that divides the frequency (number of data acquisitions) / relative frequency (number of acquisitions of a category / total number of acquisitions) into bar-shaped sections using a gradation-like color change or a change in shading pattern.

[0038]

[13] The biometric information management system may display multiple gradation bars based on accumulated daily data, divided into measurement time periods (e.g., every hour) with the date and time axis as the horizontal or vertical axis, in parallel for each measurement time period.

[0039]

[14] The biometric information management system may display a gradation bar based on accumulated data divided by the number of times daily data is acquired (eg, N number: 50 times), with the date and time axis as the horizontal or vertical axis.

[0040]

[15] The biometric information management system may determine whether the frequency of each class in the relative frequency distribution in the cumulative data displaying the gradation bar exceeds a preset upper limit (lowest range division), lower limit (highest range division), or upper or lower limit value, and whether the value falls within a preset upper or lower critical range, and outputs an alert if it detects that the value has been exceeded.

[0041]

[16] The biometric information management system may determine whether the difference between the average value and the median, or the maximum difference between the upper and lower limit classes, exceeds a preset upper or lower limit in the frequency distribution of the cumulative data displaying the gradation bar, and output an alert if it detects that the difference is exceeded.

[0042]

[17] The bioinformation management system can target multiple biological individuals, each equipped with a microchip, identify each individual using the microchip number, and authenticate whether the individual identification information using the microchip number matches a previously set biological individual number, and display an alert if the numbers differ.

[0043]

[18] Alternatively, a biological information management system can be provided in which photographs or videos of each individual living organism before admission are prepared, and at the time of admission, the system automatically recognizes similarities between the photographs or videos of the pre-registered animal and the current photographs or videos of the animal at the time of admission to detect the identity of the patient animal, and if there is a lack of identity, displays an alert to confirm that the ID number has been swapped. Effect of the Invention

[0044] By using the above-mentioned means, the vital sign data of the target individual organism is measured, and by performing statistical processing of the previous vital sign data suited to the characteristics of the target individual organism, it is possible to provide a vital information management system that can determine daily values ​​taking into account differences and trends in data due to the individual organism's characteristics (weight, sex, medical history, etc.). [Brief description of the drawings]

[0045] [Figure 1] System configuration of the vital sign management system of the first embodiment [Diagram 2] System configuration of vital sign management system of embodiment 2 [Diagram 3] Installation Concept Diagram [Figure 4] Example of a screen for setting a search range for multiple installed targets in the first embodiment [Diagram 5] Example of a screen for setting multiple installed search ranges in Example 2 [Figure 6] Example of the management screen for target organism individual information (basic information setting) [Figure 7] Example 1 of a list of vital data and selected screen [Figure 8] Example 2 of display screen with selected vital data [Figure 9] Example 2 of the management screen for individual organism information (schedule setting) [Figure 10] Example of data structure for vital data [Figure 11] Example of an attribute group classification information input screen [Figure 12] (a) deployed state and (b) worn state of the wearable sensor [Figure 13] A top view (a) and a bottom view (b) of an example of a pulse oximeter [Figure 14] Schematic diagram of pulse oximeter measurement methods: (a) transmissive type (b) reflective type [Figure 15] Data processing flow of the present invention [Figure 16] Standard deviation graph of normal distribution in statistical processing [Figure 17]Image of histogram limits and density function [Figure 18] An example of a display of a measured pulse rate, (a) a comparison diagram with the daily value of a target individual organism, and (b) a comparison diagram with attribute values ​​of the same attribute group. [Figure 19] Normal distribution histogram and display image [Figure 20] Non-normal distribution histogram and display image [Figure 21] Trend graph display screen example [Figure 22] Example of a comparison chart of pulse rate and respiratory rate data sets [Figure 23] Example of a graph showing body surface temperature and rectal temperature [Figure 24] Example of determining resting state by differentiation of body surface temperature [Diagram 25] Display of distribution frequency using a gradient bar (including upper and lower alert range settings) (Daily value bar and attribute value bar can be displayed together or switched) [Figure 26] Display of cumulative distribution frequency by vertical gradation bar for each time period (distribution bar divided into 1 hour intervals, current value also displayed on the right) [Figure 27] Displays cumulative distribution frequency using a vertical color bar (the distribution bar is divided into sections based on the amount of cumulative data, and the current value is displayed on the right) *As data is not acquired during body movement, the thickness of the bar (time axis) varies due to the difference in acquisition time between when the body is stationary and when it is moving. [Figure 28] Monitoring status management screen 1 (Among the list displays of gauges 1 to 4, gauge 1 is entering admission, and gauge 4 is temporarily suspended) [Figure 29] Management screen 2 in monitoring state with details being confirmed (the lower half displays details of the admission registration for the selected gauge 1 (the upper half displays a compressed view of vital sign information for gauges 1 to 4. Gauge 4 is temporarily suspended (not being monitored, undergoing treatment, eating, etc.))) *If the patient is clearly moving, the display is temporarily suspended. [Diagram 30]Management screen 3 in monitoring status and details being checked (the bottom half displays a trend graph of the vital signs of the selected gauge 2) (enlarged display screen of trend progress information for gauge 2) *Graph enlargement adjustment and printing operations are possible [Diagram 31] Management screen 4 in monitoring status and during detailed confirmation (the lower half displays the selected gauge 2's alert output (in this example, [Alarm history]) in table format) (enlarged display screen of gauge 2's alarm message history information) *Printing is possible [Diagram 32] Management screen 5 for monitoring status and detailed confirmation (the lower half of the screen shows the video image of the target organism in Cage 2 in the center with a time axis bar indicating the time when the image was taken, and small previous photos are displayed on the right with the date and time of the image taken). Fast forwarding of the video and printing are possible. [Diagram 33] Management screen 6 in monitoring status and during detailed confirmation (screen showing the daily value gradation bar of gauge 2 and the attribute value gradation bar displayed vertically) can be printed using the print button. *It is also possible to switch to displaying the cumulative distribution frequency using a vertical color bar. [Diagram 34] Management screen 7 during monitoring and operation (night mode setting screen) [Diagram 35] Management screen 8 (operation menu list) of the operation menu in monitoring state and before operation [Diagram 36] Operation menu screen 1 during monitoring and operation (Gauge 2 alarm upper and lower limit setting operation) [Figure 37] Operation menu screen 1 during monitoring and operation (Gauge 2 data acquisition time: data update time interval setting operation) [Figure 38] List monitoring screen for two animals [Figure 39] Operation menu screen 1 during monitoring and operation (entry operation for cage 2, display of the match rate of animals by comparing past and current images captured using the examination card. Prevention of mix-up of animals, simple confirmation for relocation within the cage. Can also be done with nose prints and fingerprints) [Diagram 40]Operation menu screen 1 in monitoring state and during operation (Admission input operation of gauge 2: Input of character information: Identify attribute value information based on input.) [Diagram 41] Appearance of the wearable data acquisition device and transmitter (a) and an example of how it is worn (b) DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0046] (System Configuration) The present invention relates to a system for acquiring and managing vital sign data, including at least one of pulse rate, respiratory rate, and body temperature, of a target individual organism, including a human, as information on the vital activities of the target individual organism, The system comprises a wearable transmitter equipped with a vital sign sensor attached to the target organism, a server that stores the transmitted and received data, a processing device that processes the server data, and an output device that outputs the processed contents.

[0047] <System Overview> (The date of a specific treatment for the target organism is the start date of follow-up observation. Preoperative data, standard deviation data, and lower and upper limit data for time period attributes classified as active data are constantly observed at specified intervals in comparison with current vital data to check whether they are within the attribute value range and to output an alert if the attribute value range is exceeded.

[0048] In addition, stress-related information for a given symptom of the target organism is stored, Based on changes in body temperature and sweating rate, It is preferable to include a step of determining whether a change in the daily vital data value has occurred (whether this change is due to stress).

[0049] (Record of communication between owner and doctor after alert) The alert is output to the owner's terminal, the attending physician, or the hospital terminal, and a text information chat or telephone communication line is secured, a line availability indication is displayed, and communications after the line is used are recorded.

[0050] (Basic contents of the system of the present invention) This invention is a system that sets and displays biological classifications, attributes, and attribute value ranges for each individual, and compares them with the standard deviation of the attribute group and with the daily comparison average value for each individual.

[0051] The target individual organism is one or more living animals. This includes pets such as dogs and cats, domestic animals, birds, reptiles, insects, and humans. When inputting an individual organism, attribute data such as species, subject, large / small / male / female, place of birth, and age are registered as attribute information for distinguishing the target individual organism by attribute group.

[0052] (Features of the present invention) The present invention is characterized in that vital sign data, which is current biological information of a target individual organism, such as pulse, heart rate, body temperature, and the presence or absence of body movement, is compared and displayed with daily value data of the individual organism that has been statistically processed. Note that in the embodiment, four types of vital signs, namely pulse, heart rate, body temperature, and the presence or absence of body movement, are used, but at least one of pulse, heart rate, and body temperature may be acquired as the vital sign.

[0053] In other words, it comprises a vital sign sensor and a transceiver attached to the target biological individual (including humans), a server that stores the transmitted and received data, a processing device that processes the server data, and an output device that outputs the processed contents, and by going through at least each of the following steps, it displays the current vital sign data of the target biological individual in real time, and also displays where this vital sign data is within the range of the corresponding daily value data.

[0054] The steps of the process performed by the biometric information processing system are as follows: An ND step that creates standard deviation data (as attribute values) for a given attribute group by classifying attribute groups and storing the data on a server; A BS step of constantly acquiring and (temporarily) storing vital signs of the target individual organism by a sensor directly attached to the individual organism and a sensor installed remotely; a step of distinguishing between resting state data and active state data from the stored vital sign data and generating daily average data and upper and lower limit data of daily values ​​in the resting state; A PN step is performed in which a numerical comparison result of the vital sign data in the current step BS is calculated and displayed based on the standard deviation data in the ND step and the data created in the previous step.

[0055] The steps performed in sequence in this method are described below. First, the BS step is performed, in which vital sign data of the target individual organism is continuously or intermittently acquired by a sensor directly attached to the individual organism and / or a fixedly installed sensor, and the data is stored in a server. Here, vital sign data of an individual organism refers to measurement information that indicates the physical and mental state of the individual organism in its living state, such as heart rate, respiratory rate, body temperature, body movement, and SOPOO2 (blood oxygen concentration). In this embodiment, at least two of the heart rate, respiratory rate, body temperature, body movement, and SOPOO2 are referred to, and information that can be obtained by various sensors such as a temperature sensor, an optical sensor, an ultrasonic sensor, a pressure sensor, and a gyro sensor is referred to as vital sign data or vital data. In the BS step, a pulse oximeter 61S (FIG. 13) that is attached to or inserted into the target individual organism may be used in combination with a sensor (23) that detects by remote observation. Continuous acquisition may be performed by repeatedly acquiring data at set intervals ranging from 5 to 60 seconds, or at set intervals ranging from 1 to 10 minutes. The acquired data is displayed in real time as the current individual organism's vital sign data, and is used to determine whether the data is from a resting state by calculating the amount of change in the value and the rate of change in the amount of change as continuous data.

[0056] The ND step is a step in which the processing device extracts resting state data that meets predetermined set conditions from the stored vital sign data, and statistically processes the data group of the resting state of the target organism over a predetermined period as daily value data. It is premised on the storage of accumulated data of the target organism or alternative data in place of it. This is a second step in which resting state data is extracted from the vital sign data of the target organism, only the resting state data over a predetermined period is normalized (normal distribution approximation by Fourier transform), and data of upper limit, lower limit and / or average value (on the normal distribution approximation data) in the resting state over a predetermined period up to the most recent time is created and stored. The PD step is a third step of creating and storing at least one data item selected from the upper limit and lower limit, the average or median value, and the standard deviation of the normal distribution data. Next, the CD step is performed. The CD step is a fourth step in which a numerical comparison is made between the current vital sign data from the ND step and each data from the PD step, and the comparison result is displayed and stored.

[0057] Next, the PN step is performed. The PN step is a step of displaying the current or most recent vital sign data of each target individual organism in real time and daily value data over a predetermined period of time in parallel or superimposed fashion. This step outputs the comparison results between each value of the current vital sign data of the target individual organism and the statistically processed daily value data at rest (FIG. 18(a), FIG. 21).

[0058] (Upper and lower limits are displayed together) In the PN step, the current vital sign values ​​are superimposed on the display to show the comparison results of how much they currently differ from the resting state values, i.e., the resting state data. By displaying in parallel or on top of each other a real-time display of the current vital sign data for each target organism and a comparative display of daily values ​​over a specified period of time or longer, the comparison result is displayed showing how much each of the current vital sign values ​​of the target organism currently deviates from the daily values ​​in a resting state.

[0059] Here, the daily value at rest to be compared may be a value after statistical processing based on cumulative data at rest of the specific target biological individual, or a value after statistical processing based on cumulative data at rest of biological individuals of the same attribute group to which the specific target biological individual belongs (excluding the specific target biological individual). In the present invention, the former is referred to as daily value or daily value data, and the latter is referred to as attribute value or attribute value data.

[0060] Fig. 18(a) shows an example of a display in which each current vital sign value is superimposed on a box plot of the upper limit, lower limit, and average value of the daily value data, while Fig. 18(b) shows an example of a display in which each current vital sign value is superimposed on a box plot of the upper limit, lower limit, and average value of the attribute value data.

[0061] Figure 8 shows an example in which (a) a boxplot comparison with daily value data, which is data on the resting state of a symmetrical grain individual, and (b) a boxplot comparison with attribute value data are displayed side by side. In addition, it is possible to switch between Figure 18(a) and Figure 18(b) and display them interchangeably. For example, it is possible to display all the values ​​of the current vital sign data collectively in a so-called daily value comparison display, which displays the data in comparison with a boxplot of the daily value of the target biological individual. It is also possible to switch from this state to display all the values ​​of the current vital sign data collectively in a so-called attribute value comparison display, which displays the data in comparison with the daily value of the attribute group to which the target biological individual belongs.

[0062] Another example of the superimposed display is shown in Fig. 21, where the current vital sign value is superimposed on a line graph of daily value data and an average curve of attribute value data. In Fig. 21, each current vital sign value is represented by a thick broken line and is displayed in a graph progression over time.

[0063] In Fig. 21, the vital signs are displayed in line graph form, and the average value, upper value, and lower limit value of the data of the target organism at rest for the same time period are displayed as daily average value, daily upper value, and daily lower limit values ​​in line graph form as dashed lines or dashed two dotted lines. Furthermore, in Fig. 21, the vital signs are displayed in bold line graph form, and the daily value data is displayed in dashed lines or dashed two dotted lines as line graph form, and the average upper value and average lower limit value of the attribute value data to which the target organism belongs for the same time period are displayed as dashed curves and dotted ranges above and below the curves.

[0064] Note that the × (cross) marks superimposed on the vital signs line graph in Figure 21 indicate the inflection points where the sign of the slope changes. Additionally, the arrows touching the line graph indicate the points at which an alert was issued based on each comparison value. Additionally, the vertical lines crossing the line graph indicate the points at which each comparison value intersects with the value. These vertical lines indicate the points at which the average of the daily value upper and lower limits or attribute value upper and lower limits up to that point was exceeded, and the start and end times are estimated based on the slope of the graph and the values ​​on the graph. The estimated start and end times are displayed in the alert dialog (Figure 21).

[0065] In Fig. 21, the daily value data and attribute value data are simultaneously superimposed on the vital signs graph, but it is also possible to switch to superimposing only one of the daily value data and attribute value data and display them as a comparison graph (not shown). Also, the display on the line graph can be switched to a single-axis display as in Fig. 18.

[0066] (Detection at rest) This system is A step of creating standard deviation data (attribute values) for a given attribute group by classifying the attribute group items and storing the data in a server; A step of constantly acquiring and (temporarily) storing vital signs of the target organism using a sensor directly attached to the organism and a sensor installed remotely; The ND step is to distinguish between resting state data and active state data from the stored vital sign data and to create daily average value data in the resting state and upper and lower limit data of the daily values. In this ND step, the following resting state detection methods can be used to extract resting state data.

[0067] (Extraction of resting state data) That is, in the extraction of data on the resting state in the ND step, the transition from the active state to the resting state and the transition from the resting state to the active state are determined based on the unit time change (slope) of the temperature change, whether the change in the slope is below or above a threshold, or whether there is an inflection point. The resting state is detected based on the time of these transitions (and whether the skin temperature exceeds the threshold).

[0068] (Alert detection by numeric comparison with values ​​of other attribute groups) The method further includes a step of setting a predetermined attribute group to which the target organism belongs; A comparison is made to see what characteristics a specific individual has compared to the average values ​​within the same attribute group, and the results of a numerical comparison between the daily values ​​and the accumulated attribute value data for a specific attribute group are output separately for daily value comparison data during stress (when hospitalized) and daily value comparison data during non-stress (when at home).

[0069] By comparing the characteristics of a specific individual with the average value within the same attribute group, it is possible to understand the individual characteristics and make judgments by comparing with other individuals in the same attribute group. Detailed alerts can be issued by combining daily value alerts with accumulated attribute value data. It is possible to distinguish between daily values ​​during stress (when hospitalized) and daily values ​​during non-stress (at home).

[0070] The specific steps for comparing with the attribute group standard values ​​are as follows: A step of setting a predetermined attribute group (such as large / small / male / female / temperament, or in the case of humans, weight / height / sex) to which the target biological individual belongs (attribute setting step); storing the vital sign data of the predetermined attribute group in a server; A step of extracting daily value data of the predetermined attribute group from the server by a processing device and statistically processing accumulated attribute value data of the predetermined attribute group under specific conditions (attribute value statistical step); and a step of displaying in parallel or in superimposition (parallel display step) real-time display of current or recent vital sign data for each target biological individual and attribute value data after statistical processing of an attribute group under predetermined conditions including the target biological individual over a predetermined period or more. As a result of the above, a comparison result between each value of the current vital sign data of the target biological individual and the statistically processed attribute value data of a resting state of the attribute group including the target biological individual is output.

[0071] (Compared with excluded attribute value data) A step of statistically processing excluded attribute value data, which is a daily value data group of a plurality of organisms in an attribute group to which a specific target organism belongs, excluding the daily value data of the target organism; The biological information management system according to claim 3KL, characterized in that it compares the daily value data of the target biological individual with excluded attribute value data of the attribute group of the biological individual excluding the daily value data of the biological individual, and outputs the comparison result.

[0072] (Compared to daily data of healthy subjects) The method further includes a step of recording as recorded data healthy daily value data that satisfies predetermined healthy discrimination conditions, from the daily value data of the target biological individual in a resting state, excluding data for the time period during which specific symptoms occurred including the pre-operative or post-operative period, and outputting a comparison result between the most recent vital sign data of the target biological individual and the healthy daily value data in a healthy state.

[0073] (Alert sounds when comparing daily data with upper and lower limits) Regarding the output compared to the upper and lower limits of the daily value data above, At a significance level of 5%, which is twice the standard deviation, If there is no significant difference, no alert will be issued. If there is a significant difference, an alert will be issued. This is the basic output process. The position of the significance level can be preset by a veterinarian as the boundary position of an alert, for example, by a percentage, pulse rate, respiratory rate, or the like.

[0074] Daily value data at rest, that is, data at rest, is extracted, statistically processed, and output, for example, by the following process. As an active period exclusion process, data for time periods that satisfy the discrimination conditions for the amount of activity in the exclusion process are excluded as active period data. As a statistical treatment, the mode or second most frequent value, or the extreme 2-5% range of the standard deviation data (this varies greatly depending on the amount of activity) is calculated. -To display the fluctuation range comparison, the extreme value fluctuation guideline (outlier guideline) whether it is within the fluctuation range due to the daily time period is displayed with classification symbols such as ABC or comments.

[0075] "The cumulative values ​​of the average value, comparison with the upper and lower limits, and standard deviation (variation) are stored together with the data within each group, including the period group, the time period group, and the rest / active ratio data.

[0076] (Data update) The data created for the daily values ​​is updated as needed by the accumulation of vital sign data. At this time, accumulated data obtained by accumulating detection values ​​using an acceleration sensor for each unit time is used as a criterion for distinguishing or extracting whether the state is at rest or active. In determining whether the state is at rest, for example, the accumulated data obtained by accumulating detection values ​​for each unit time is used to calculate the maximum upper and lower values ​​in a specified time period, or the degree of change over time (the inclination on the time axis or the amount of displacement of the inclination), and is compared with a threshold value previously set for each individual organism or for each attribute group, to extract only data that is determined to be data in the resting state. At this time, it is preferable to accumulate and store only data in the resting state together with time information by attaching time (time period) data. By accumulating and storing data in the resting state together with time information for a specified period for one individual organism, comparison based on time period and prediction of fluctuation over time can be performed. Using this comparison or prediction, it is possible to determine, for example, whether a current fluctuation in vital sign data is simply a temporary fluctuation in value or a fluctuation in value due to an emergency. For example, it is possible to determine a symptom that is low in urgency and gradually worsening, and to detect it early by data prediction. With pet livestock in particular, it is important to be able to judge and predict abnormal symptoms.

[0077] Specifically, the PD step 3-3 sets and displays the biological classification and attributes, the attribute value range for each individual, compares it with the standard deviation of the attribute group, and displays the fluctuations over time along with the time data. The system includes a GD step for creating standard data for a given attribute group, such as standard deviation data, by classifying the attribute groups and storing the data in a server.

[0078] (Hospitalization and Visit Information) The method further includes a step of setting hospitalization information or hospital or facility visit information for a predetermined symptom of the target biological individual, The biological information management system can output data separately for when the patient is admitted or visits the hospital and when the patient is at home.

[0079] (Group recording of pre- and post-operative data) The method further comprises a step of storing treatment information for a predetermined symptom of the target organism, and group-recording data on the resting state of the target organism during a pre-operative or post-operative period as attribute data of the symptom. For example, by combining the attribute groups "medical history," "surgical history," "before and after surgery," and "before and after contraception," it is possible to determine the status of postoperative progression.

[0080] (Alert output) It determines whether the transmitted data exceeds preset upper, lower, and average values, and if it detects that the values ​​have been exceeded, it outputs an alert.

[0081] For example, in the case of an alert output system for postoperative follow-up observation, The date of a specific treatment for the target organism is set as the start date of follow-up observation, and pre-operative data, standard deviation data, lower limit data, and upper limit data classified as active data are compared with the current vital data for constant observation at specified intervals to check whether they are within the attribute value range, and an alert is output if the attribute value range is exceeded.

[0082] It is also possible to make judgments based on preoperative examination information and during anesthesia. For example, a preoperative examination and anesthesia judgment system can be considered that displays whether the attribute value is within the range and whether there is any variation. In addition, when making judgments during anesthesia, ... is a judgment item.

[0083] Another example of the system is a hospitalization management system and an alert system during operation. This system targets multiple individual organisms, each equipped with a microchip, and identifies the individual organisms using the microchip number. The current vital sign information and the presence or absence of alerts for all the individual organisms that fall into an attribute group are displayed together, classified by the number of the healthy individual organism.

[0084] In this system, when multiple animals are identified using installed and wearable transmitters, in addition to identification by ROI, individual identification is performed using microchip numbers.

[0085] (Record of communication between owner and doctor after alert) When an abnormal value is detected, an alert is output to the owner's terminal, the attending physician, or the hospital terminal, and the system can secure a text chat or telephone communication line, display an indication that the line is available, and record communications after the line is used.

[0086] (Health information diagnostic system (system for use in health checkups) A system that adds measurement data of individual organisms during health checkups and records it as time-series data.

[0087] (Wearable transmitter) The sensor for acquiring vital data of the target organism is composed of a wearable transmitter with a sensor attached to a jacket or harness band that is always worn in close contact around the torso (including the chest, ventral and dorsal areas) of the target organism (or around the body surface excluding the limbs and neck) (FIG. 12).

[0088] (13) Estimation of rectal temperature: Use an intrarectal insertion testing device (pulse oximeter) in conjunction. A system including an intestinal insertion test device (pulse oximeter 6) that is temporarily inserted into the intestine of the individual organism, in addition to the wearable transmitter that is always worn, At least the pulse rate and rectal temperature are measured by the enteral insertion examination device (pulse oximeter 6), and an error in the calculation process of the estimated rectal temperature or the pulse rate can be displayed. For example, the rectal temperature is estimated on the assumption that the maximum and minimum rectal temperature times coincide with the maximum and minimum epidermal temperature times.

[0089] (Steps in the first biological information management method) The first biological information management method of the present invention comprises a vital sign sensor and a transceiver attached to a target biological individual including a human, a server that stores the transmitted and received data, a processing device that processes the server data, and an output device that outputs the processed contents, and is executed including at least the following steps.

[0090] The steps are: A data acquisition step of continuously or intermittently acquiring vital sign data of the target organism using a sensor directly attached to the organism and / or a fixedly installed sensor, and storing the data in a server; a statistical processing step of extracting resting state data, which is determined to be a resting state by satisfying a predetermined set condition, from the stored vital sign data by the processing device, and statistically processing a group of resting state data of the target organism over a predetermined period as daily value data; Regarding the target organism, The method includes an output processing step of displaying vital sign data for the current or most recent time for each target individual organism while updating it as needed, and displaying the daily value data for a predetermined period of time or duration in parallel or superimposed thereon.

[0091] The output step The comparison results between each value of the current vital sign data of the target organism and the statistically processed daily value data in a resting state are output.

[0092] (Steps in the second biological information management method) The second biological information management method of the present invention is executed by at least the following steps, which are more specifically specified than the first biological information management method. a data acquisition step of acquiring vital sign data of the target organism at regular time intervals using the sensor directly attached to the target organism and / or the sensor fixedly installed, and storing the data together with the time of acquisition and information about the organism; a statistical processing step of extracting resting state data from vital sign data of the target organism, subjecting the resting state data over a predetermined period to normal distribution processing, and creating and storing normal distribution data in the resting state over a predetermined period up to a most recent time; an accumulation processing step of creating at least one data selected from upper and lower limit values, average or median value, and standard deviation from the normal distribution data at each time point acquired, and storing the data as accumulated value data; a comparison processing step of comparing the vital sign data at the current time or the immediately preceding time with the data in any one of the steps and displaying and storing the comparison result; and an output processing step of displaying in parallel or superimposed fashion a real-time display of the current vital sign data for each target individual organism and a comparative display of daily value data over a predetermined period or more. The device is characterized by outputting a comparison result showing how much the vital signs of the target biological individual at the current time or the most recent time or the calculated values ​​based on them deviate from the cumulative value data of the target biological individual.

[0093] [Explanation of each step] (Creating specific attribute group data) In the accumulation processing step, examples of classification items for attribute groups and data accumulation on the server, that is, data accumulation storage processing is performed. In this step, biological classifications and attributes, and attribute value ranges for each individual are set, and multiple selections are made possible using option tags. Accumulated data corresponding to all options is extracted, and standard deviation data for the attribute groups to be compared (for example, the average, upper limit, and lower limit of attribute values) is created.

[0094] The standard deviation data consist of nocturnal respiratory rate, nocturnal pulse rate, blood pressure, SPO2 (blood oxygen concentration), daytime body surface temperature at rest, predicted body temperature based on daytime body surface temperature, and instantaneous acceleration of the torso when the body is at rest with reduced body movement.

[0095] For comparing vital sign data, it is preferable to categorize the target biological individual (target animal) by a plurality of corresponding attribute parameters and specify an attribute group by a combination of each attribute parameter. In specifying the attribute group, for example, the attribute group of the attribute parameter is specified in multiple stages according to the input contents. For example, as shown in FIG. 11, by grouping by combining three types (large / medium / small), two types (gender), three types (young, middle-aged, adult), two types (temperament), and three types (weight) in the BCS 5-stage evaluation, it is possible to specify which attribute group the target biological individual (target animal) belongs to out of a maximum of 216 types of attribute groups. The specified attribute group can be displayed on the management screen of the target biological individual (target animal) with an identification symbol 221DG (FIG. 8).

[0096] In the case of humans, groups are created by combining, for example, sex (male and female), age (approximately 5 groups), and BMI based on weight and height (3 groups).

[0097] (Example of attribute parameters for animal species: "dog / cat") The display software displays a screen for basic information on the target individual living organism (animal) in a selection or fill-in format, and prompts the user to enter information. <In the case of animals> ·Animal species (dog / cat) Breed (3 groups per species) Gender (male / female) Age (3 groups) Temperament (2 groups) Enter weight (BCS "Body Condition Score" 5-point scale, divided into 3 groups) Maximum 216 groups <In humans> Gender (male / female) Age (about 5 groups) Enter weight and height (BMI "Body Condition Score" 5-point scale, divided into 3 groups) Maximum 30 groups

[0098] (Accelerometer and transmitter) In the data acquisition step, measurements are taken at regular intervals using a three-axis acceleration sensor, and the data is collected and transmitted at intervals of several minutes.

[0099] (Data acquisition step) Data acquisition is performed, for example, every second to every few seconds, and data transmission is performed, for example, at intervals of 5 to 10 minutes. These time intervals can be set. The data acquisition step specifically includes the following steps F11 to F13. F11: Data extraction step for resting state: Exclude data that meets activity conditions (server), accumulate and store vital data at rest (server) F12: Extract only resting state data DR, excluding activity condition data DA, from vital sign data D of the target organism measured per unit time, and collect, accumulate, and overwrite in memory M. F13: Overwrite the oldest time data (sent at a specific time or by the amount of data accumulated, and saved on the server)

[0100] In the F12: resting state data extraction step, <detection of resting and active states> is performed based on the contents of the ND step: resting state data extraction. Here, data is acquired at intervals of one to several minutes, and data is periodically output at intervals of once every several minutes to several hours.

[0101] (Statistical processing step) Accumulation of daily value data for a specific individual: The lower limit, upper limit, and average daily value at rest are measured continuously and accumulated along with each attribute data value. The accumulated data is saved as "attribute values" in an overwritable manner (Figure 13).

[0102] When the statistical processing information is updated by the accumulation processing step, the upper and lower limits are automatically adjusted based on the accumulated data value. The automatically adjusted upper and lower limits are used as thresholds to issue an alert against the attribute value.

[0103] In the comparison processing step and the output processing step, the average value comparison with the attribute value, the upper limit comparison, and the lower limit comparison are output as comparisons with other individuals.

[0104] <How to issue an alert against attribute values> Six types of alerts can be issued based on respiratory rate, pulse rate, and body temperature. A combination of alert types can produce potential cases. However, the upper and lower limits vary depending on the time period. The specific statistical processing procedure is as follows, for example:

[0105] Step 1: Create a frequency distribution table, record pulse rate and respiration rate data, determine the bins for the pulse rate and respiration rate data, determine the bin value (median) for each bin, find the number of data in each bin (frequency), find what percentage of the number of data in each bin accounts for compared to the whole (relative frequency), and finally find the sum of the relative frequencies below a certain bin (cumulative relative frequency).

[0106] Step 2. Calculate the mean, variance, and standard deviation.

[0107] Step 3. Create a histogram based on the frequency distribution table. Normalize the histogram so that its total area is 1.

[0108] Step 4. Step to connect the histograms with a smooth curve.

[0109] When a large amount of data is collected and accumulated, the graph connecting the top ends of the histograms gradually becomes smoother. This curve is called the probability density function or density function of the variable. The area can be found by integrating this probability density function f(x) in definite form, and this area is the probability. The sum of the areas of the probability density function is 1.

[0110] Step 1 of 4: A step of calculating the area (probability) of the histogram or the area (probability) obtained by definite integration of the probability density function f(x), and calculating the percentage of overlapping areas (matching rate) between two data sets with the same parameter set, or between the areas obtained by definite integration of the probability density function f(x).

[0111] Step 5: Determine whether the distribution of the data is normal.

[0112] In this step, visual confirmation is performed using a frequency distribution diagram (histogram) or a normal probability graph. For example, if a graph (QQ plot) with the expected value according to the normal distribution on the vertical axis and the numerical value of the data itself on the horizontal axis forms a straight line, it is judged that the data is normally distributed. Alternatively, a statistical method described separately can be used to determine whether the data is normally distributed.

[0113] <Regarding normal distribution processing> The left panel of Figure 16 shows a graph of a normal distribution, as well as the standard deviation and its range of two and three times the standard deviation. Regardless of the values ​​of the mean, variance, and standard deviation, all graphs of normal distributions exhibit the following properties: Approximately 68 percent of the total are within the range of plus or minus 1 of the average Approximately 95 percent of the total falls within the range of the mean plus or minus 2 (in some cases, a value of 1.96σ is used). Approximately 99.7 percent of the total are within the range of plus or minus 3 of the average

[0114] The following null hypothesis can be used as the test statistic: Null hypothesis: The hypothesis to be tested to see if it can be rejected. This is the hypothesis that there is no difference. If the null hypothesis is not rejected, there is no significant difference. When the null hypothesis is rejected, it is assumed that there is no difference, i.e., there is a significant difference.

[0115] Here, we will explain the significance level (risk rate). The standard for determining whether or not a hypothesis is rejected is the probability that the null hypothesis is established, and this probability is called the significance level (or risk rate). There are no clear standards for setting the significance level, but in the medical field, 5% (0.05) is used. For example, a "significance level of 5%" means that "there is a 5% chance that the null hypothesis is established." If the probability that the value of the calculated test statistic appears is lower than the significance level, it means that "something that rarely occurs has occurred," and the null hypothesis is rejected.

[0116] The right diagram in Figure 16 is an example in which the range of the test statistic, i.e., the boundaries of the P value, are displayed for each number of trials of the statistical processing step, assuming a normal distribution through data correction. In this diagram, the significance level is 5%, i.e., the area of ​​the test statistic where the null hypothesis is not rejected is 95%, and within this area there is no significant difference. On the other hand, the 2.5% area areas on both the left and right ends of the diagram are areas where the null hypothesis is rejected, and are excluded from the range of the test statistic.

[0117] In addition, the four values ​​of the median, mean, upper limit, and lower limit may be displayed side by side as reference values ​​without performing the standard normal distribution process. 5.0% on the left and right, that is, 2.5% on the right and left. The upper diagram of Figure 18 is a comparative display of the target organisms, and the lower diagram of Figure 18 is a comparative display of the target organisms G.

[0118] If the statistical method determines that the data is normally distributed, the following step 5-1 is carried out. <Step 5-1. If the distribution is normal> First, from the 100P% point obtained by converting probability P into a percentage, the pulse rate and respiratory rate are calculated at 10% points on both sides (5% point on one side), or 5% points on both sides (2.5% on one side), or the upper 5% point, or the upper 2.5% point, the lower 5% point, or the lower 2.5% point, or any percentage point set by veterinary personnel, of the normal distribution curve of the pulse rate or respiratory rate.

[0119] Next, at each percentage point, if the currently measured pulse rate or respiration rate becomes greater than the pulse rate or respiration rate at the upper percentage point, an upper limit alert is generated.

[0120] <How to issue alerts against daily values> The server can issue six types of alerts based on respiratory rate, pulse rate, and body temperature. Potential cases can be generated by combining the types of alerts.

[0121] If the currently measured pulse rate or respiration rate at each percentage point becomes lower than the pulse rate or respiration rate at the lower percentage point, a lower limit alert will be triggered. The pulse rate and respiration rate at each percentage point are updated every few minutes when the collected data is statistically processed. The alert setting range and upper and lower limit values ​​of the alert are also automatically changed.

[0122] When creating standard deviation and calculating upper and lower limits of daily values, the parameter: measurement time period (early morning, morning, daytime, evening, night, late night) may be used. When adding a comparison item to create daily average data in a resting state, the daily average data in a resting state is transmitted every hour.

[0123] [Operational processing of this system] This system will be structured as follows: (1) By continuously recording the vital sign measurements, whether in the hospital or at home, the daily values ​​of the patient or individual subject are calculated and recorded. (2) From the collected data, statistically calculate the attribute values ​​of a group (characteristics combining attribute parameters such as male / female, age, breed, place of origin, and blood type) that match the characteristics of the target individual organism (person), including other individuals, and at the same time, use the standard deviation from the collected data to calculate the normal range for the patient or target individual organism. (3) Assist in comparing the daily values ​​and attribute values ​​of the patient or target organism and determining whether the daily values ​​and measured values ​​are normal or abnormal based on the normal range.

[0124] Specifically, the following three numerical comparisons are made: -Compare the attribute values ​​of a group of organisms with the same chronic condition with their everyday values. Compare the attribute values ​​of healthy organisms in the same attribute group of age and species category among the organisms with the same chronic disease with the daily values ​​of the organism. At the same time, the severity of the current situation is estimated by comparing the daily values ​​of this individual organism.

[0125] [Terminology explanation] Daily value information refers to daily value information based on biological and lifestyle information, such as the amount, frequency, and color of excrement, converted into numerical values.

[0126] The following are examples of applications of this system:

[0127] Application example A: Pre-anesthesia evaluation system (referring to objective vital signs in addition to a medical interview). Used during anesthesia treatment, post-operative observation, post-operative treatment, and to determine return to daily life.

[0128] Application example B: Management system during operation: A system that references daily attribute values, sets the stage of the fluctuation range according to each individual, and issues detailed alerts when danger is judged. Since the alert danger information (time until death) varies depending on the attributes of each animal species, it is important in veterinary treatment to be able to increase the accuracy of alerts. For example, anesthesia depth and degree of awakening can be mentioned.

[0129] Application example C (Health information diagnostic system (system for use in health checkups) A system that adds measurement data of individual organisms during health checkups, records and displays the data by year of measurement.

[0130] Application example D (alert system during hospitalization management) The system targets multiple individual organisms, each equipped with a microchip, identifies each organism using its microchip number, and displays the current vital sign information and the presence or absence of alerts for all organisms that fit into an attribute group, categorized by organism number.

[0131] <Examples of surgical procedures> Data used: Daily values ​​for the subject individual are set based on the vital sign values ​​when the subject individual is relaxed and asleep at home at night. Data on the vital signs of the subject individual animal while it is sleeping after surgery at the veterinary hospital and the range of fluctuation (resting values) are obtained.

[0132] The ideal timing for obtaining daily value data is when the patient is at home before surgery or hospitalization, but if data obtained at home is already available, this data should be used. Attribute values ​​are calculated statistically from data on various individuals collected nationwide under the same conditions (same disease name, same animal, same age, same sex, etc.) When data is insufficient, general vital sign values ​​for animals listed in papers, etc. are used instead.

[0133] Pre-surgery (judging whether the vital signs outside the hospital are stable as "pre-surgery test information") Compare the daily values ​​and attribute values ​​from the accumulated data (attribute values ​​before surgery for the same condition or disease group if there is a chronic illness, or attribute values ​​of healthy individuals if healthy). Individual daily values ​​obtained before surgery or hospitalization are compared with the attribute values. If there are no particular problems with an individual, the daily value and attribute value should be in roughly the same range, but if there is a difference between the daily value and the attribute value of a certain amount or more, the system will automatically determine the possibility that some abnormality has already occurred in the individual or that a chronic illness may be worsening (congenital abnormality, etc.), and will assist in the decision to conduct other tests or postpone or cancel surgery (safety of surgery).

[0134] The wearable sensor measures body surface temperature, and may also be used to estimate and calculate an estimated rectal temperature from this body surface temperature. <Estimated rectal temperature calculation> The estimated rectal temperature is calculated, for example, by the following four steps. Step 1. The rectal temperature of an animal using a wearable or installed transmitter is spot measured using a rectally inserted pulse oximeter (e.g., symbol 6 in Figure 13) four times a day: upon waking, before lunch, before dinner, and before going to bed. Step 2. Record the spot measured rectal temperature, the skin temperature at the same time, and the outside air temperature at that time. Step 3. Calculate the difference between the surface skin temperature and the outside air temperature, and the difference between the average rectal temperature of the four measurements and the surface skin temperature to calculate the estimated rectal temperature. Step 4. Each time a spot measurement of rectal temperature is taken, the estimated rectal temperature is updated by adding the rectal temperature at that time and the surface skin temperature at the same time and recalculating the average value.

[0135] This is done with reference to the outside temperature and attribute group values. In this embodiment, the wearable transmitter is fitted with a tight-fitting jacket to reduce the influence of the outside temperature. Alternatively, a tight-fitting harness type or harness structure may be used in combination. As a wearable transmitter, it also has the effect of preventing hair loss due to friction and reducing stress. By measuring abdominal temperature and heart rate (pulse) using a jacket-type sensor, high-precision measurements can be made at all times. The respiration rate is measured using an acceleration sensor and a tension sensor.

[0136] If oxygen saturation could be measured rectally in the same way as body temperature measurement, it would be possible to reduce the labor and improve the stability and reproducibility of the measured value. For example, by using a pulse oximeter 6 that is inserted into the rectum and has a transparent resin part 610 incorporating a pulse oxisensor 51S (FIG. 13), a measurement method including a step of measuring oxygen saturation in the rectum can be achieved. The thermometer-type pulse oximeter 6 shown in FIG. 13 is a thermometer-type flexible shaft for rectal measurement with a function of a pulse oximeter added to the thermometer-integrated part of the flexible shaft for rectal measurement. For example, as shown in FIG. 13, this pulse oximeter has a flexible shaft 61 that can be elastically bent and deformed, which is connected to the side of each plate-shaped control box 62 via a cone-shaped elastic connecting part 61T. The control box 62 has a power source, a circuit, and a display part, and a display part 6D and a switch button 63 are provided on the surface. The flexible shaft 621 is composed of a cylindrical part with a diameter that can be inserted into the rectum, an elongated hemispherical part whose tip part is tapered toward the tip side, a cylindrical transparent resin part 610 incorporated near the tip part, and a sensor 61S incorporated in the transparent resin part 610. The sensor 61S is incorporated with a temperature sensor and a reflective SPO2 sensor spaced apart in the circumferential direction.

[0137] (Measurement principle) There are two types of pulse oximeters: a transmission type (left in Fig. 14) that measures oxygen saturation by sandwiching the target blood vessel between a light emitting sensor and a receiving sensor, and a reflection type (right in Fig. 14) that does not sandwich the target blood vessel. The form shown in Fig. 13 incorporates a reflection type pulse oximeter 61S (Fig. 13(a)). Data on the "amount of change in SPO2" is accumulated. A pressure sensor is provided in the shaft. In addition to this form, the shaft shape can also be changed to a thicker tip type.

[0138] (Use of attribute values ​​in preoperative testing) Daily values ​​and attribute values ​​can also be used in pre-anesthesia evaluation (pre-operative examination). <Preanesthesia evaluation> Veterinarians perform preanesthetic evaluation just before administering anesthesia on the day of surgery. The purpose of preanesthetic evaluation is to grasp the animal's overall condition and evaluate the severity of the condition, predict complications during and after surgery, and plan perinatal management measures. This system is a system that assists in preanesthetic evaluation, among other preoperative tests. During the pre-anesthetic evaluation, the veterinarian will conduct an evaluation using the evaluation items listed below as a reference.

[0139] (Evaluation items) Heart rate, Respiratory rate, Presence or absence of heart murmurs, Presence or absence of abnormal breath sounds: ·Medications ·X-ray: ·Ultrasound: Blood test (WBC, PCV, PLT, ALB, GLU, ALT, ALP, BUN, CRE, Na, K, Cl, CRP / SAA) -Whether you have epilepsy or allergies -Presence or absence of labored breathing, cyanosis, pale mucous membranes, and abdominal distension Level of consciousness: normal, drowsy, confused, or comatose ASA-PS, BCS, expected pain level: Mild / Moderate / Severe

[0140] The interview information given by veterinarians to pet owners is inaccurate because it is not about the owner's own body, and animals cannot speak. Also, since there are no past records, owners may make mistakes, forget, or misremember. Therefore, a device is used to continuously obtain objective vital sign information to perform a preanesthetic evaluation.

[0141] The vital sign information used includes heart rate, pulse rate, systolic blood pressure, mean blood pressure (non-invasive), mean blood pressure (invasive), diastolic blood pressure, spontaneous respiration, and artificial respiration. Other information such as body temperature, exhaled anesthetic concentration, end-tidal carbon dioxide partial pressure, inhaled oxygen concentration, percutaneous arterial oxygen saturation, airway pressure, tidal volume, eye position, eyelid reflex, and jaw tension can also be used.

[0142] In addition, anesthesia record formats are used to record anesthesia information and vital information during surgery, but filling them out during surgery is time-consuming. Also, since some facilities do not have anesthesia records, this system will standardize the format and record them, and all veterinarians using this system will be able to view anesthesia records and prognosis records from other hospitals, and search for the type of anesthetic used, amount of anesthetic, and prognosis in past cases of pets with similar individual information. Daily values ​​and attribute values ​​of vital signs will also be reflected in the anesthesia record.

[0143] Recorded information during anesthesia includes, for example, administration information for the following: oxygen, air, fluid therapy (saline, Ringer's, colloidal fluid), inotropes (dobutamine, dopamine, ephedrine, analgesics, and other information such as atropine.

[0144] The system automatically sets upper and lower limit alarms for the range of attribute values ​​such as pulse rate, respiratory rate, and body temperature of the same individual pet on the vital signs monitor used during surgery, and alerts the surgeon. In addition, the following information is automatically reflected in the anesthesia record, reducing the workload of veterinarians and owners and enabling pre-anesthesia evaluation with accurate information. - Biological information of your pet collected by a home device while your pet is at home prior to surgery (vital information while waiting at home, urine and feces volume and number of times your pet goes to the toilet, information on the amount of food and drink consumed, and weight information) - Biological information of pets collected by hospital devices while the pet is at the veterinary hospital before and during surgery (vital information during hospitalization, biological information monitor, medication information during surgery, bleeding amount information, etc.) · Information on the veterinary clinic's (electronic) medical records (past anesthesia experience, medical history, etc.) -Individual information registered by the owner in the home display software

[0145] This system can be used to assist in pre-anesthesia evaluation, among other pre-operative examinations. <Preanesthesia evaluation system> The purpose of the preanesthetic evaluation system of the present invention is to predict complications during and after surgery and to plan perinatal management measures by grasping the animal's overall condition and evaluating the severity using vital sign data immediately before anesthesia on the day of surgery. In the preanesthetic evaluation, a veterinarian will make an evaluation with reference to the following items. (1) Reducing the burden of preoperative testing The interview is conducted by the veterinarian to the owner. This information may be inaccurate, since it is not about the owner's own body, and animals cannot speak. Also, since there are no past records, the owner may misunderstand, misremember, or forget. Therefore, by using a device to collect data, pre-anesthesia evaluation can be performed based on accurate (objective) information. (2) Pre-recording of anesthesia records, records during surgical treatment, and data accumulation In addition, anesthesia record formats such as the attached file are used to record anesthesia information and vital information during surgery, but it is time-consuming to fill them out during surgery. Also, since some facilities do not have anesthesia records, this system will unify the format and record them, and all veterinarians using this system will be able to view anesthesia records and prognosis records from other hospitals, and search for the type of anesthetic used, amount of anesthetic, and prognosis in past cases of pets with similar individual information. Daily values ​​and attribute values ​​of vital signs will also be reflected in the anesthesia record.

[0146] Specifically, upper and lower limit alarms are automatically set on the vital sign monitor used during surgery within the range of attribute values ​​such as the pulse rate, respiratory rate, and body temperature of the same individual pet, and the surgeon is alerted. The following information is automatically reflected as anesthesia records, reducing the workload of veterinarians and owners and providing accurate information for pre-anesthesia evaluation. For example, pet vital sign information collected with a home device when the pet is at home before surgery (vital sign information while waiting at home, urine and stool volume and number of times the pet has gone to the toilet, amount of food and drink, and weight information), pet vital sign information collected with a hospital device when the pet is at the veterinary clinic before and during surgery (vital sign information during hospitalization, vital sign monitor, medication information during surgery, amount of bleeding, etc.), information from the veterinary clinic's (electronic) medical record (past anesthesia experience "anesthesia record", medical history, etc.), and individual information registered by the owner in the home display software.

[0147] Additionally, information obtained through interviews may be added to the display items of the system, such as medical history, anesthesia experience (lifestyle information), whether the patient is taking any medication, how much, for how long, whether the patient has had diarrhea or vomiting, etc.

[0148] In addition to the above, information from a measurement device for urine volume and feces volume may be used, such as appetite, amount of water consumed, amount and frequency of urination and defecation, whether there is coughing, or irregular heartbeat.

[0149] In addition to the above, the individual information may be information about the pet's individual registered in the owner's home software. For example, information on the animal species, breed, sex, age, temperament, anesthesia history, and weight. These have different anatomical or pharmacological reaction characteristics, and may affect the anesthetic drug or anesthesia method used. This information can be used to classify the attribute values ​​(normal range), a specific method for classifying "adjusted attribute values," and a comparative evaluation of the attribute values ​​and measured values ​​at the time of comparison. For example, an evaluation can be made that this individual is within the normal range, so that it is operable or has an anesthesia resistance level.

[0150] In addition to the above, this system may further include a rectally inserted reflection type pulse oximeter as an examination device. This pulse oximeter is used during examinations. Animal examinations are temporarily performed on the tongue, lips, and ears (areas without hair, no pigmentation, and areas with little body movement). Three items, rectal temperature, oxygen saturation, and pulse rate, can be simultaneously examined and measured from the rectum. Conventionally, a rectal thermometer was used, and oxygen saturation and pulse rate were not measured simultaneously. In contrast, this system is equipped with a pulse oximeter as a separate device from the wearable transmitter (which constantly measures on the tongue during anesthesia) as a monitoring device.

[0151] (Wearable Sensors) As another type of wearable sensor described above, the present system may use a wearable transmitter that is in close contact with the target organism, in which a periodic transmission sensor is attached to a jacket or harness band that is in close contact with the torso (including the chest, ventral and back) of the target organism (or around the body surface excluding the limbs and neck). Also, A vest / harness (shoulder belt) with an estimation meter for rectal temperature based on the change in epidermal temperature per unit time (first derivative dt) or the change in the change per unit time (second derivative dtdt) may be provided. Sensing using elastic fibers may be used as the epidermal temperature detection sensor. For example, the body surface temperature near the femoral artery of the target organism is measured, and the estimated rectal temperature is calculated based on the difference between the epidermal temperature and the outside air temperature.

[0152] In the previous gradation bar, the frequency of each class is displayed by the shade of the paint in the class bar, making it possible to display the most frequent (high frequency) class in high density and the relatively low frequency (low frequency) class in relatively light density, thereby enabling a gradation distribution in a compact bar-shaped bar. It is also possible to display the daily value bar and the attribute value bar together as shown in the lower half of Figure 33, or to switch between them.

[0153] In addition, Figure 25 shows the daily value data of the target organism in gradation. If information on an animal group with the same attribute as the target organism is accumulated, the daily value data for each time period of the same attribute group is accumulated and stored together with time information as attribute value data (attribute value data that accumulates the daily value data of the same attribute), The accumulated data value of the attribute value data can be displayed as a color bar that divides the frequency (number of data acquisitions) / relative frequency (number of acquisitions of a category / total number of acquisitions) into bars using gradation-like color changes or changes in shading. The highest frequency and upper and lower limits of the same attribute group can be intuitively grasped by the shading.

[0154] The current measurement value may be displayed overlapped with a color bar for the same measurement time zone or measurement date range as the current measurement value.

[0155] Figure 26 shows the cumulative distribution frequency displayed by vertical gradation bar for each time period. This screen shows the distribution bar divided into 1-hour segments, and the current value is also displayed on the right.

[0156] Fig. 27 shows the cumulative distribution frequency by displaying the number of acquisitions side by side using a vertical gradation bar. In other words, it displays a gradation bar based on the cumulative data of daily data divided by the number of measurements (for example, every 50 times) with the date and time axis as the horizontal or vertical axis. On this screen, the distribution bar is divided into sections based on the cumulative data volume, and the current value is displayed to the right. Because no data is acquired during bodily movement, which is not included in resting data, the thickness of the bar (time axis) varies due to the difference in acquisition time between when still and when moving. Note that the gradation shade display in the figure is omitted, but in reality it is color-coded according to the vertical class divisions, and is color-coded according to the gradation density or color. In addition to the display using the gradation bar as in Figure 27, it is also possible to switch to a variable graph based on cumulative data divided by the number of times daily data is acquired (e.g. N number: 50 counts).

[0157] 28 is a monitoring status management screen 1. In this screen, among the list display of gauges 1 to 4, gauge 1 indicates that admission input is in progress and gauge 4 is temporarily suspended.

[0158] FIG. 29 shows the management screen 2 in the monitoring state while details are being confirmed. In this screen, the details of the admission registration of the selected gauge 1 are displayed in the lower half of the screen. This lower half display shows the results of the advance interview and advance questions conducted at the time of system registration, i.e., admission to the living object management location. These items are used to determine the population of attribute values. In addition to these items, at the time of admission, information such as medical history and characteristics previously obtained in the nursing information at the time of admission, as well as individual information such as allergies and personality, may also be entered and displayed.

[0159] In addition, the upper half of the screen in Figure 29 shows a compressed display of vital sign information for gauges 1 to 4. Gauge 4 is temporarily suspended (when not being monitored, such as during treatment or eating). For example, it is temporarily suspended when the patient is clearly in a state of physical activity, such as taking a walk or a bath.

[0160] Figure 30 shows the management screen 3 in the monitoring state with details being confirmed. In this screen, a trend graph of the vital signs of the selected gauge 2 is displayed in the lower half. The most recent fluctuations in the vital signs of the gauge 2 can be confirmed using a time-based variable graph. In addition to adjusting the enlargement of the progress graph, it is possible to switch between vital sign types such as skin temperature, pulse rate, respiratory rate, and body movement using the switch buttons, and to print the data.

[0161] Fig. 31 shows the management screen 4 in the monitoring state and during detailed confirmation. In this screen, the lower half displays the alert output of the selected gauge 2 ([Alarm History] in this embodiment) in a table format. This is an enlarged display screen of the history information of the alarm message of the gauge 2, and it is possible to confirm what abnormal condition was detected in the past, when, and when it was released. It is possible to switch between types of vital signs such as skin temperature, pulse rate, respiratory rate, and body movement using the switch button, and to perform printing operations. By setting alerts and listing variations in data, you can spot signs of abnormalities. A gradation bar or color bar based on the cumulative data can be displayed along the time axis for each past measurement period, with the alert setting category highlighted. For example, by looking at the changes in the amount of variance and bias in the cumulative data, it is possible to infer abnormalities in animals or sensors due to changes in the variance in the data.

[0162]

[0163]

[0164]

[0165]

[0166] Figure 36 shows the operation menu screen 1 during monitoring and operation. On this screen, it is also possible to set the upper and lower limits of the alarm for the gauge 2. It judges whether the relative frequency value of the frequency distribution in the accumulated data that displays the gradation bar as in Figures 25, 26, and 33 exceeds the upper limit value (lowest range division), lower limit value (highest range division), or upper and lower limit values ​​of a preset division, or whether the value is within the upper or lower critical division that has been preset, and outputs an alert if it detects that it has exceeded the limit. In addition to the above, it is also possible to determine whether the difference between the average value and the median value, and the difference between the upper and lower limits of the cumulative value categories are above a certain level, and to output an alert if it is detected that they are exceeded.

[0167] FIG. 37 shows the operation menu screen 1 during monitoring and operation. On this screen, it is also possible to set the data acquisition time for the gauge 2: the data update time interval. By setting the interval for acquiring daily data, the number of times data is acquired per hour, for example, is determined. Note that since differences in the acquisition of acquired data and data when an individual organism is moving are not saved and only data at rest is saved, data at the timing of movement will be blank data.

[0168] FIG. 38 shows the overview monitoring screen for two animals.

[0169] Figure 39 shows the operation menu screen 1 during monitoring and operation. This screen shows the admission input operation for the cage 2, and the coincidence rate of the animal based on the comparison of the past captured image and the current captured image from the examination card, as a percentage such as "95%." Simple confirmation to prevent mix-ups and to relocate animals within the cage. It can also be done using nose prints and fingerprints.

[0170] FIG. 39 shows the screen when the identity detection step is performed. This system includes a step of automatically recognizing the commonality between the pre-registered animal photo (registered photo posted at the first visit or in advance: overall image or nose print) and the current animal image at the time of admission (in the case of a microchip-embedded organism, ID information is entered or automatically recognized). By checking the commonality, the identity of the target organism is detected, and if there is a lack of identity, an alert is displayed to confirm the ID number mismatch. Figure 39 shows a screen that compares the current video of the target organism (acquired image for face recognition) with a previously registered photo of the same organism, displays the result of comparing the two images (the figure shows a match rate of 95%), and displays the possibility of a mismatch of the organism. After this, the current video of the organism is registered as a history of the photos taken, and the photo history is added.

[0171] In addition to the above, a system may be adopted in which multiple biological individuals, each equipped with a microchip, are identified using the microchip number, and the individual identification information using the microchip number is authenticated to determine whether it matches a previously set biological individual number, and an alert is displayed if the numbers differ (not shown).

[0172] Alternatively, a photograph of the individual animal before admission may be prepared for each individual, and at the time of admission, the system automatically recognizes similarities between the pre-registered photograph of the animal and the current image of the animal at the time of admission to detect the identity of the patient animal, and if there is a lack of identity, displays an alert to confirm that the ID number has been swapped.

[0173] 40 shows the operation menu screen 1 in the monitoring state and during operation. In this screen, the admission input operation of the gauge 2: input of character information: attribute value information is specified based on the input.

[0174]

[0175] (Animal vital signs management system) The present invention relates to an animal vital sign management system that is also applicable as an animal vital sign confirmation system that confirms or manages the vital signs of animals in a specified location as an animal vital sign management system (FIGS. 1 to 10). For example, the present invention relates to a system in which a veterinarian monitors the vital signs of animals in a veterinary clinic for a long period of time using a host PC or a mobile terminal, or a system in which the veterinarian can view and confirm the vital signs of animals in a veterinary clinic using a mobile terminal. In addition, the present invention relates to a system in which an owner can view and check the vital signs of an animal at home using a mobile terminal, or a system in which a doctor in charge can check the vital signs of a person at home or in a hospital room, or an animal in a storage room or cage room.

[0176] Example 1 The first embodiment is a system for managing the vital signs of a plurality of animals (target animals) in an integrated manner. The first embodiment has the following system configuration (FIGS. 1 to 4). A host PC 1 (a PC for overall management installed at a data overall management location such as a hospital or system administrator) that controls the entire system and manages each vital sign of each target animal, Cloud server 2 (the data server in the figure) stores the data, A comprehensive installation sensor 3 (a ceiling-mounted human presence sensor 21 in Figs. 1 and 3) for acquiring vital signs of a target animal; An individually installed sensor 4 (floor-mounted infrared camera 23 in Figs. 1 and 3) for acquiring vital signs of a target animal; The device comprises a plurality of wearable sensors 22 (attached to a harness or collar 221 in Figs. 1 to 5, or to a vest 221 in Fig. 12) to be attached to the target animal.

[0177] Example 2 The second embodiment is a host PC management system. The second embodiment is composed of the following systems (Figure 2): A host PC that controls the entire system and manages each vital sign of the target animals, Cloud server 2 for storing the data; A comprehensive installation sensor (for the entire room) that acquires the vital signs of the target animal, An individually installed sensor (for the target animal cage) that acquires the vital signs of the target animal; The sensor is constituted by a wearable sensor 22 (attached to a harness or collar 221 in Figs. 1 to 5, or to a vest 221 in Fig. 12) that is attached to a target animal to acquire vital signs.

[0178] The following are examples of animal management systems within the veterinary clinic HS, including this system. (1-1) There is an example of a system configuration in which a veterinarian's host PC 3 can monitor the vital signs of animals in a veterinary clinic for long periods of time. (1-2) There is an example of a system in which a veterinarian can view and check the vital signs of animals in a veterinary clinic using a mobile terminal 5 or the like. Alternatively, there is an example of a system in which an owner can view and check the vital signs of an animal at home using a mobile terminal or the like.

[0179] In addition to the above, there are also examples of equipment rental management and reservation management systems in veterinary clinics that use this system. (3-1) A lending system that allows veterinarians at animal hospitals to lend a vital sign transmitter for use with animals at home, a software for checking the vital signs of animals in remote locations, and a dedicated smartphone to owners, and to check the lending history, etc. (2) A reservation system for veterinarians at animal hospitals to borrow vital sign transmitters for use with animals at home, software for checking vital signs of animals in remote locations, and dedicated smartphones from our company. (3) A system that allows veterinarians at animal hospitals to check the maintenance and repair history of equipment. In other words, a system that can link the medical information of owners and animals registered and edited by veterinarians with the acquired data to analyze, compile statistics, and predict medical conditions and pathological conditions. An example of the procedure for using an animal management system in a veterinary clinic is shown below. (1) Select "Register" from the menu button and register information about the owner and the animal. Beforehand, complete the setting up of the stationary terminal and the installation of the wearable sensor.

[0180] As an example of the device of this invention · Monitoring camera 21 as an integrated installation sensor, ROI monitoring camera 23R Microwave Doppler displacement measuring device 231 (individually installed sensor 23) or wearable sensor 22 IR Camera Temperature Measuring Instrument 232(23) Laser rangefinders 233 (23) (Figure 3).

[0181] The monitoring camera 21, which acts as a comprehensive installation sensor, checks the layout of the entire room (hospital room) and monitors the situation. If the monitoring camera 21 is an ROI monitoring camera 23R equipped with an ROI function, the position of the monitoring target is specified using the ROI function (Figure 4). In this case, the purpose is to exclude information other than the ROI.

[0182] The wearable sensor 22 comprises one or more of a microwave Doppler displacement measuring device, a temperature measuring sensor, an acceleration sensor, and a microphone, and is placed on the subject animal using a harness-type or collar-type attachment 221.

[0183] For example, the attachment 221 can be made of a vest made of elastic fiber, and the wearable sensor 22 can be fixed to the abdomen when the vest is worn. In this way, when the wearable sensor 22 is worn on the target living organism (target animal) in a tightly fitting state, the occurrence of duplicate detection errors (contamination) on the wearable sensor 22 is extremely low.

[0184] On the other hand, the individually installed sensor 23 consists of either a microwave Doppler displacement measuring device 231, an IR camera temperature measuring device 232, a laser rangefinder 233, or a combination of these, and each device is installed individually in the vicinity of each of the target animals P1, P2, P3, etc. to be measured, or is attached and placed inside the cage C of the target animal.

[0185] Of the individually installed sensors 23, the microwave Doppler displacement measuring device 231 detects the pulsation obtained from the entire target animal, and thus eliminates the occurrence of contamination by "selecting the Doppler signal with the maximum intensity."

[0186] When using the microwave Doppler displacement measuring device 231 and the IR camera temperature measuring device 232 among the individually installed sensors 23, it is preferable to use a laser distance meter 232 in addition to these. In the case of contamination in the distance direction, that is, when some obstruction is mixed between the monitored target animals P1, P2, P3, etc. and the detection parts of each sensor, the occurrence of contamination is eliminated by synchronous analysis with abnormality detection by the laser distance meter.

[0187] The occurrence of contamination and the operation of information rejection are described in detail below. (Criteria for determining whether a sensor is contaminated or an animal's pathology) First, the criteria for determining whether a sensor is contaminated or has a pathological condition in an animal will be described.

[0188] The criteria for determining whether the sensor is contaminated or the animal is in a pathological condition are determined based on the location information (data area RA) automatically set in the ROI of the monitoring camera and the distance to the animal measured by the laser rangefinder in the IR camera unit used to measure body temperature in the installed sensor.

[0189] When using a stationary sensor, it is assumed that the animal to be measured is within the cage C, and the distance and range that the animal moves are limited to the size of the cage C. Therefore, the measurement values ​​of the laser distance meter in the stationary sensor do not fluctuate significantly.

[0190] (Determining whether contamination has occurred) Next, how to determine whether contamination has occurred will be explained. If the distance from the stationary sensor to the animal to be measured changes significantly in a short period of time, or if the distance to the animal to be measured changes from short to long, it can be determined that animals or humans other than the target animal are being measured, and it is determined that contamination has occurred.

[0191] In addition to the above, The monitoring screen and the data transfer screen to the viewing terminal 4 of a veterinarian or the like display the data reliability level as determined by AI from 0 to 100%, providing assistance to the veterinarian.

[0192] (Main features) This system has the following features: Feature 1: It is characterized by the combination of a fixed power supply type installed sensor using non-contact microwave Doppler (MWD) and a battery-powered wearable sensor.

[0193] Although stationary sensors are advantageous in terms of data volume, transmission frequency, and multiple animal detection by securing a fixed power supply voltage, they have issues such as being unable to be used at home or outdoors due to limited installation conditions, and having limitations on the detection range and body movement measurement.On the other hand, wearable sensors are advantageous in tracing and recording specific targets and detecting emergencies by detecting proximity when worn, but have the disadvantage that they cannot measure due to intense movement because they are non-contact MWDs.

[0194] In response to this, by using a non-contact microwave Doppler (MWD), which is inexpensive and allows easy data synchronization and simultaneous measurement, it is possible to combine both fixed-type and wearable sensors. In other words, by synchronizing and storing the detection data from a fixed-power-supply type sensor and a battery-powered wearable sensor, it is possible to supplement the data from the wearable sensor with the installation conditions, detection range limitations, and body movement measurement limitations. This also makes it possible to measure many animals for long periods of time at once, and improves emergency detection by reducing the error rate.

[0195] Feature 2: It is a host computer-managed remote data management system that uses sensors to solve the following problems:

[0196] The above-mentioned features make it possible to provide a method for managing a plurality of sensor targets under the control of a host computer, in which the operation of each sensor is centrally controlled by the host computer, rather than each sensor operating independently.

[0197] In addition, the above features make it possible to provide a method for preventing misidentification of a sensor target or misidentification of the sensor target with other target animals (humans), which prevents misrecognition of the sensing target by setting areas of the cage space and estimating individual data.

[0198] A system having the above features 1 or 2 can be used as a management system that automatically transmits data to owners and hospitals by storing and managing data on a cloud server.

[0199] (Sensor type) In the embodiment, a wearable sensor is disclosed as a type of sensor in the above management system. However, only a stationary sensor may be used, or a combination of a stationary sensor and a wearable sensor may be used. In the case of a combination, the above (A) data complementation becomes a supplementary point. The sensor may be used in a hospital or at home.

[0200] (Other embodiment examples) In addition to the above, the following embodiment examples are possible. Third embodiment C: Equipment rental management system and reservation management system in veterinary clinics (1) A lending system that allows veterinarians at animal hospitals to lend a vital sign transmitter for use with animals at home, a software for checking the vital signs of animals in remote locations, and a dedicated smartphone to owners, and to check the lending history, etc. (2) A reservation system for veterinarians at animal hospitals to borrow vital sign transmitters for use with animals at home, software for checking vital signs of animals in remote locations, and dedicated smartphones from our company. (3) A system that allows veterinarians at animal hospitals to check the maintenance and repair history of equipment.

[0201] Fourth embodiment D: A system of (4), (5), and (6) using a home pulse oximeter (body temperature, heart rate, blood flow, SPO2 measuring device).

[0202] (4) System A "Remote medical interview system before medical examination and surgery (before visiting the hospital)". This remote medical interview system, as a "remote medical interview system before medical examination and surgery (before visiting the hospital)", allows the contents of the interview to be input or displayed in interview mode (preoperative medical treatment mode), and outputs an input screen and an interview result list screen to each terminal of the medical staff and the owner of the living organism. It may also be a registration system on an application that can register photos of the living organism (patient). When an abnormal value of the vital signs is detected based on a threshold value of the difference between a preset threshold value and the daily value, the medical interview mode (list of questions, photo taking instructions) automatically selected according to the conditions is automatically started, and the data is displayed so that it can be input on the owner's (owner's) terminal of the living organism, and the interview input results can be sent to the medical institution. When the input results are received at the medical institution's terminal, a notification is given by displaying the screen or flashing, etc. In addition, the risk level may be automatically determined based on the risk level of the biometric information (the magnitude of the difference between the daily value / attribute value), and the content of the preliminary interview may be automatically adjusted in accordance with pre-set conditions based on the determined risk level in the interview mode or emergency mode (the information necessary to estimate the abnormality may be automatically selected by automatically selecting the ABC route of the interview content).

[0203] For example, by using a cumulative data transition graph such as the gradation bar in Figure 25, when the rate of change between past cumulative data and the most recent cumulative value exceeds ○% or ●%, interview modes A and B can be launched, respectively, and displayed on the management terminal and each individual terminal, reflecting the input results. Examples of types of interview patterns include high fluctuation rates of respiratory rate and heart rate → interviews regarding excretory information, high fluctuation rates of body movement → interviews regarding surgical factors, and interviews regarding other medium to large fluctuation rates, appetite, body temperature, and stress factors.

[0204] In this interview mode, the interview results sent from the terminal of the owner of the individual organism are displayed in a scrolling manner in the lower half of the centralized management screen as shown in Figure 31, and the interview results for values ​​with large fluctuations are highlighted and displayed as an assistance display.

[0205] By having owners pre-register medical interview information on their smartphones while waiting at home, veterinarians can be aware of the information in advance. In addition, medical interview information required for pre-anesthesia evaluation can be obtained in advance. This can be achieved by incorporating a vital information reporting + medical interview answering app (5-point evaluation screen).

[0206] (5) System B "Medical appointment system." This remote monitoring service incorporates a daily record mode and an emergency mode, so that when a veterinarian determines that a visit is necessary, the veterinarian will contact the owner, explain the urgency and severity of the pet's condition, and confirm whether the owner is able to visit the hospital.

[0207] As a daily record mode (diary mode / postoperative progress mode), it is possible to incorporate a management screen for biological information before and after injections, such as the photographs taken in Figure 32 and the biological information graph in Figure 33. From the home software, pet owners can check the hours when the hospital is open and make appointments for treatment. From the hospital software, veterinarians can track the GPS signal of the owner's smartphone and check the estimated time of arrival at the hospital, whether the pet is on its way to the hospital, etc.

[0208] When the system detects an alert output, it can also launch an emergency treatment mode in the event of an emergency. In emergency mode, data is shared with night hospitals.

[0209] (6) System C "Remote Examination Service System". Medication schedules are adjusted based on daily vital sign data collected during home life (used as a factor in determining the progression of the disease). In addition, the collected vital information from daily life can be used in the daily record mode (diary mode), with a screen displaying three measurement items in a calendar list, the import of photos of the sick animal or affected area, and linking the diary mode with the vital information. It may also be a system for remote management of vital information by linking the owner's terminal with the medical staff's terminal. This system will issue emergency alerts and open a veterinarian contact line as described above in B.

[0210] In cases where medical treatment is not required, pets need to live with the disease for a long time in their daily lives. In the case of heart or lung diseases, owners need to ensure that the pet takes the medicine, go to the hospital immediately in case of acute exacerbation, and collect information including the pet's condition at home so that veterinarians can adjust the type and amount of medicine while checking the pet's condition. Pet owners are worried about their pet's anesthesia, surgery, and health after discharge from the hospital. Therefore, we developed a system that allows pets undergoing medical treatment to be examined at home during their daily lives.

[0211] As the night mode\remote management mode in FIG. 34, the emergency notification alert of the management terminal is muted at night, and the mode is switched to a remote notification mode in which the viewer is monitored from a pre-registered mobile terminal.

[0212] A fourth embodiment other than those described above: A system that can link the medical information of owners and animals registered and edited by veterinarians with the acquired data to analyze, compile statistics, and predict medical conditions and pathological conditions.

[0213] Fifth embodiment: Animal information application software that receives and displays detection data from a non-contact MWD sensor installed (worn) in a hospital / home, and has the following functions: D1. A function to change the display content depending on the user of the mobile device (doctor, nurse, owner), D2·MWD sensor-based remote medical examination and emergency response assistance function D3: Detection of mass infections in hospitals (group accommodation areas), monitoring alert function for home use, D4 - Notification function that launches communication application software when an alert occurs and automatically connects the line

[0214] Sixth embodiment: A sensor system used for managing local animal information, animal insurance review information, and vaccination management.

[0215] One issue with wearing detection is that, although tongue, puncture, or paw detection is highly accurate, there is a problem that measurement cannot be performed continuously due to measurement errors caused by body hair. On the other hand, since temporary measurement is possible by wetting the body hair with salt water, a harness equipped with a wearable sensor may be equipped with a saline spray function that wets the body hair with salt water.

[0216] (Example of the device of the present invention) An example of an apparatus according to the invention is presented comprising: · Monitoring camera 21 as an integrated installation sensor, ROI monitoring camera 23R Microwave Doppler displacement measuring device 231 (individually installed sensor 23) or wearable sensor 22 IR Camera Temperature Measuring Instrument 232(23) Laser rangefinders 233 (23)

[0217] The monitoring camera 21 as the above-mentioned comprehensive installation sensor checks the layout of the entire room (hospital room) and monitors the situation. If the monitoring camera 21 is an ROI monitoring camera 23R equipped with an ROI function, the position of the monitoring target is specified using the ROI function (Figure 4). In this case, the purpose is to exclude information other than the ROI.

[0218] The wearable sensor 22 comprises one or more of a microwave Doppler displacement measuring device, a temperature measuring sensor, an acceleration sensor, and a microphone, and is placed on the subject animal using a harness-type or collar-type attachment.

[0219] When the wearable sensor 22 is worn on clothing, the occurrence of duplicate detection errors (contamination) on the wearable sensor 22 is extremely low.

[0220] On the other hand, the individually installed sensor 23 consists of either a microwave Doppler displacement measuring device 231, an IR camera temperature measuring device 232, a laser rangefinder 233, or a combination of these, and each device is installed individually in the vicinity of each of the target animals P1, P2, P3, etc. to be measured, or is attached and placed inside the cage C of the target animal. Of the individually installed sensors 23, the microwave Doppler displacement measuring device 231 detects the pulsation obtained from the entire target animal, and thus eliminates the occurrence of contamination by "selecting the Doppler signal with the maximum intensity."

[0221] When using the microwave Doppler displacement measuring device 231 and the IR camera temperature measuring device 232 among the individually installed sensors 23, it is preferable to use a laser distance meter 232 in addition to these. In the case of contamination in the distance direction, that is, when some obstruction is mixed between the monitored target animals P1, P2, P3, etc. and the detection parts of each sensor, the occurrence of contamination is eliminated by synchronous analysis with abnormality detection by the laser distance meter.

[0222] In addition to the above, the rental management screen and home (central) screen will display alerts (rental period alerts,) (management display of the treatment status of sick animals (home waiting, hospitalization, home treatment)), equipment rental status, rental alerts, and reservation information (screen examples will be added). Used for sorting information as one of the attribute data.

[0223] The present invention, including the above-mentioned embodiments, can be modified in various ways without departing from the spirit of the invention. For example, some components can be omitted, extracted, or modularized, or interchangeable components can be combined, or replaced with known components. [Explanation of symbols]

[0224] 1. Integrated installation sensor 21 Surveillance Camera 22 Wearable Sensors 221 Mounting fixture 23 Individually installed sensors 23R ROI monitoring camera 2. Cloud Server 3. Management terminal 3A Data Management Software 4 Viewing device 4A Data Check Software 5. Viewing and management terminal 5A Data Management Software C Cage P1, P2, P3,... Target organisms (target animals) RA, RA11, RA12... Data area

Claims

1. A system for acquiring and managing vital sign data, including at least one of pulse rate, respiratory rate, and body temperature, of a target individual organism, including a human, as information on the vital activities of the target individual organism, The system comprises a sensor directly attached to a target biological individual and / or a vital sign sensor and a transceiver fixedly installed thereon, a server for storing transmitted and received data, a processing device for processing data from the server, and an output device for outputting the processing contents, A step of continuously or intermittently acquiring vital sign data of the target organism by a sensor directly attached to the organism and / or a fixed sensor, and storing the data in a server; extracting resting state data, which is determined to be a resting state by satisfying a predetermined set condition, from the stored vital sign data by the processing device, and statistically processing a group of resting state data of the target organism over a predetermined period as daily value data; Regarding the target organism, and displaying the vital sign data of the target individual organism at the current time or the most recent time while updating it as needed, and superimposing daily value data over a predetermined time or period or longer. and outputting a comparison result between each value of the vital sign data of the target biological individual at the current time or the most recent time and the statistically processed daily value data in a resting state, In the step of superimposing and displaying, A vital sign data management system characterized in that updated values ​​of vital sign data at the current time or the most recent time are superimposed on a box diagram consisting of upper limit values, lower limit values, and average values ​​of daily value data, and on a gauge displayed in the form of a straight bar overlaid on the box diagram, and the position of each on the gauge is displayed.

2. acquiring vital sign data of the target organism at regular time intervals using the sensor directly attached to the organism and / or the fixed sensor, and storing the data together with the time of acquisition and information about the organism; extracting resting state data from the vital sign data of the target organism, subjecting the resting state data over a predetermined period to frequency distribution processing, and creating and storing histogram data in the resting state over a predetermined period up to a most recent time; creating at least one data item selected from the upper limit value, the lower limit value, the average value or the median value, and the standard deviation in the histogram data for each time point obtained, and storing the data as cumulative value data; A step of performing a numerical comparison between real-time vital sign data at a current time or an immediately preceding time and data from any of the steps, and displaying and storing the comparison result; and a step of superimposing a real-time display of the current vital sign data of each target individual organism and a comparative display of daily value data over a predetermined period of time on a gauge displayed in the form of a straight bar. The biological information management system of claim 1, characterized in that it displays in real time a comparison result of how much the vital signs of the target biological individual at the current time or the most recent time or the calculated values ​​based thereon deviate from the cumulative value data of the target biological individual.

3. A step of setting a predetermined attribute group to which a target biological individual belongs; storing the vital sign data of the predetermined attribute group in a server; extracting daily value data of the predetermined attribute group from the server by a processing device, and statistically processing group attribute value data of the predetermined attribute group under specific conditions; and a step of displaying in parallel or in superimposition a real-time display of current or recent vital sign data for each target biological individual and group attribute value data of a predetermined condition of a predetermined attribute group including the target biological individual over a predetermined period of time or more, 2. The biological information management system according to claim 1, characterized in that it outputs a comparison result between each value of the current vital sign data of the target biological individual and statistically processed attribute value data of a resting state of an attribute group including the target biological individual.

4. A step of statistically processing excluded attribute value data, which is a daily value data group of a plurality of organisms in an attribute group to which a target organism belongs, excluding the daily value data of the target organism; 4. The biological information management system according to claim 3, characterized in that it compares the daily value data of the target biological individual with excluded attribute value data of the attribute group of the biological individual excluding the daily value data of the biological individual, and outputs the comparison result.

5. The method further includes a step of setting hospitalization information or hospital or facility visit information for a predetermined symptom of the target biological individual, 2. The biological information management system according to claim 1, wherein data at the time of admission or visit to the hospital and data at home are output separately.

6. The biological information management system according to claim 1, further comprising a step of recording as recorded data daily value data of the target biological individual at rest that satisfies a predetermined healthy discrimination condition, excluding data on the occurrence time of specific symptoms including the pre-operative or post-operative period, and outputting a comparison result between the most recent vital sign data of the target biological individual and the daily value data in a healthy state.

7. The biological information management system according to claim 1, characterized in that it determines whether the transmitted data exceeds a preset upper limit, lower limit, or average value based on the relative frequency, and outputs an alert if it is detected that the values ​​have been exceeded.

8. The biological information management system of claim 1, characterized in that the sensor for acquiring vital data of the target biological individual is a wearable transmitter having a sensor attached to a jacket or harness band that is worn tightly around the waist of the target biological individual at all times.

9. The biological information management system according to claim 8, characterized in that the sensor for acquiring vital data of the target biological individual is a wearable transmitter having a curved wire-type sensor attached along the jacket surface of a jacket wearing garment or the band surface of a harness band.

10. The resting data is stored as daily value data along with time information.

2. The biological information management system according to claim 1, characterized in that a frequency distribution or a relative frequency distribution of the cumulative data values ​​of the daily value data accumulated and stored as time information for a specified time period is displayed as a linear gradation bar in which the class values ​​are represented in the direction of the length of the bar as sections of a certain length, and the frequency of each class value dividing the gradation bar is displayed by a change in color or a change in a shading pattern.

11. Daily value data for each time period of a group of organisms in the same attribute group, which has the same attributes as the target organism, is accumulated as attribute value data, which is accumulated daily value data for the same attributes, together with time information, and stored as attribute value data; 2. The biometric information management system according to claim 1, wherein the accumulated data value of the accumulated and stored attribute value data is displayed as a gradation bar that divides the frequency / relative frequency into bar-shaped sections by gradation-like color changes or changes in shading patterns.

12. The biological information management system according to claim 11, characterized in that the gradation bar based on the cumulative data of daily data, divided into predetermined measurement times or measurement time periods with the date and time axis as the horizontal or vertical axis, is displayed in parallel in multiple lines for each measurement time period.

13. 12. The biological information management system according to claim 11, wherein a gradation bar based on accumulated data divided according to the number of times daily data is acquired is displayed with the date and time axis as the horizontal axis or the vertical axis.

14. 12. The biological information management system according to claim 11, characterized in that in the relative frequency of the frequency distribution in the cumulative data displaying the gradation bar, it is determined whether the frequency of each class exceeds a preset upper limit, lower limit, or upper or lower limit value, and whether the value falls within a preset upper or lower critical division, and an alert is output when it is detected that the value has been exceeded.

15. 12. The biological information management system according to claim 11, characterized in that in a frequency distribution in the cumulative data for which the gradation bar is displayed, it is determined whether or not either a difference between an average value and a median value or a maximum difference between upper and lower limit classes exceeds a preset upper or lower limit value, and an alert is output when it is detected that the difference is exceeded.

16. The biological information management system according to claim 1, characterized in that it targets a plurality of biological individuals, each equipped with a microchip, identifies each individual using the microchip number, authenticates whether the individual identification information using the microchip number matches a previously set biological individual number, and displays an alert if the numbers differ.

17. The biological information management system of claim 1, characterized in that photographs or videos of each individual living organism before admission are prepared, and at the time of admission, the photographs or videos of the pre-registered animal are automatically recognized to have similarities with the photographs or videos of the animal at the time of admission to detect the identity of the patient animal, and if there is a lack of identity, an alert is displayed to confirm that the ID number has been swapped.

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