Biological information management system

Abstract

To perform statistical processing on vital sign data up to now suitable for the characteristics of a target biological individual, to thereby allowing determination of a daily value considering the difference and tendency of data due to the characteristics (body weight, sexuality, past illness and the like) of the individual.SOLUTION: A biological information management system performs: a BS step of continuously or intermittently acquiring vital sign data of a target biological individual by using a sensor directly attached to the biological individual or / and a fixedly installed sensor, and storing the data in a server; an ND step of, by using a processor, extracting data in a resting state satisfying a predetermined setting condition from the stored vital sign data, and performing statistical processing on a data group of the target biological individual in the resting state over a predetermined period as daily value data; and a PN step of displaying real-time display of the current or latest vital sign data for every target biological individual, and the daily value data over the predetermined period or longer, in parallel or in a superimposed state.SELECTED DRAWING: Figure 18

Description

Technical Field

[0001] The present invention relates to a biological information management method for displaying and managing vital signs (for example, including pulse rate, respiratory rate, body temperature, etc.) of current life activities for each biological individual including animals and humans as biological information, and a biological information management system for performing the same. In particular, it includes breeding animals of mammals such as pet dogs and cats, and biological individuals including humans as targets.

Background Art

[0002] In a medical check-up performed by a healthy person, the measured value of the patient obtained from the test result is compared with a reference value. The reference value is a value set uniformly across the country based on the statistics of the health data of the entire population. Also, in a medical check-up, this reference value is generally regarded as a normal value, and normal or abnormal is determined. As a plurality of sensors for monitoring the health or wellness of animals disclosed in the prior art, there are those equipped with a wearable device (and, if present, a related base station (one or more)) and a DMS (Patent Document 1). This can form part of a health monitoring system used for collecting data regarding specific health attributes of one or more animals and / or monitoring thereof. Also, this health monitoring system can receive data from, for example, a non-invasive home telematics solution. The system can receive data from smart mats, smart movement / IF detectors, and other devices popular in the market. Indoor pets and animals can trigger these devices and record sensor artifacts such as presence, weight, physiological signs, and vital signs.

[0003] As another information processing device disclosed in the prior art, there is one equipped with a prediction unit for predicting the future state of a care recipient based on the state information of the care recipient (see Patent Document 2). For example, the prediction unit can compare the previously acquired state information with the currently acquired state information and predict the future state of the care recipient based on the comparison result.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Disclosure of the Invention

Problems to be Solved by the Invention

[0005] However, originally, there should be differences in the reference values due to individual characteristics (weight, gender, medical history, etc.). For example, it should be compared with the reference value of a group that suits one's own characteristics, or a daily value that takes into account the characteristics of a specific individual. This is because the range of values that should be judged as normal varies depending on differences in attributes and individual characteristics. That is, originally, it is necessary to adjust the reference value according to classifications such as individual characteristics and types.

[0006] In particular, regarding the measured value, it is considered insufficient to simply compare the measured value obtained during a health check with a general reference value. That is, instead of a simple comparison with a general reference value, by comparing with a daily value that takes into account the daily characteristics of the individual, it is possible to more accurately determine whether the value of the current vital sign (biological information) of the individual is normal or abnormal compared to the daily life of the individual's healthy state.

[0007] Even considering an example other than a health check, when a doctor estimates the medical condition of a patient with a pre - existing disease by comparing the reference value of a healthy person with the measured value of the patient's examination, originally, it should be compared with the reference value of a group of patients with the same pre - existing disease and the patient's daily value. If only the reference value of a general healthy person is referred to, the current medical condition of the patient cannot be accurately estimated.

[0008] The reason why the norm or daily value considering the current situation of each individual is not used to determine whether it is normal or abnormal is that in order to do so, biometric information and test results in a plurality of time series of the same individual are required. Just recording the measured values when coming to the hospital makes it difficult to determine the daily value. Only by recording the results of daily measurements including when the patient is at home can the daily value be grasped for the first time.

[0009] If we consider the characteristics and attributes of a biological individual and statistically process the measured values under the same conditions, a large amount of measured value data of patients under the same conditions is required. Therefore, it becomes difficult to set that the measured value data measured at each hospital and the measured value data measured at home are not collectively managed.

[0010] Therefore, in the present invention, it is an object to provide a biometric information management system capable of determining a daily value considering differences and trends in data due to individual characteristics (weight, gender, medical history, etc.) by measuring vital sign data of a target biological individual and performing statistical processing of the previous vital sign data that matches the characteristics of the target biological individual.

Means for Solving the Problems

[0011] In order to solve the above problems, the following means are taken.

[0012] [1] (Comparison with Daily Value Data) The present invention is a system that displays in real time vital signs (including, for example, pulse rate, respiratory rate, body temperature) of the current life activities of each biological individual including animals and humans as biometric information, and is characterized in that it is displayed in a comparable manner with "daily value data" which is a statistical processing value of data in the daily resting state of the target biological individual. That is, the biometric information management system of the present invention relates to a system that acquires and manages data of vital signs including at least one or more of pulse rate, respiratory rate, and body temperature of a target biological individual including humans as information on the life activities of the target biological individual. A vital sign sensor and a transceiver attached to a target biological individual, a server for storing transmission / reception data, a processing device for processing the data of the server, and an output device for outputting the processing content, are provided. A BS step of continuously or intermittently acquiring vital sign data of the biological individual by a sensor directly attached to the target biological individual or / and a fixedly installed sensor and storing the data in a server. An ND step of extracting data in a resting state that satisfies a predetermined set condition from the stored vital sign data by the processing device and statistically processing a data group of the resting state of the target biological individual over a predetermined period as daily value data. For the target biological individual A PN step of performing parallel or superimposed display of real-time display of current to most recent vital sign data for each target biological individual and daily value data over a period of a predetermined time or more. By doing so, It is characterized in that a comparison result between each value of the current vital sign data of the target biological individual and the statistically processed daily value data of the resting state is output. In the present invention above and below, the vital sign data refers to detection data of the life activities of the target biological individual (for example, including the pulse rate, respiration rate, body temperature), and among this vital sign data, a processed value calculated or extracted by statistical processing, arithmetic or discrimination processing in a symmetric particle individual or its belonging attribute group is referred to as daily value data of biological information. The management system of the present invention is a system that displays or manages daily value data of biological information obtained by extraction of daily value data, calculation of upper and lower limit values and average values, etc.

[0013] [2](Calculation of upper and lower limit values and average values by statistical processing) The present invention is characterized in that calculation of upper and lower limit values and average values by statistical processing is performed as the daily value data. That is, the biological information management system A BS step (data acquisition step) of constantly acquiring vital sign data of the biological individual and storing updated data at regular time intervals by the sensor directly attached to or / and fixedly installed on the biological individual of interest; An ND step (statistical processing step) of extracting data in a resting state from the vital sign data of the biological individual of interest, statistically processing only the data in the resting state over a predetermined period by means such as normalization (for example, normal distribution approximation by Fourier transform), and creating and storing data of the upper limit value, lower limit value, or / and average value on the normal distribution approximation data in the resting state over a predetermined period up to the most recent time; A PD step (cumulative processing step) of creating and storing each data of the central value, upper limit value, lower limit value, and standard deviation of the normal distribution data as cumulative data; A CD step (comparison processing step) of performing a numerical comparison between the current vital sign data obtained in the ND step and each data of the step, and displaying and storing the comparison result; A PN step (output processing step) of performing in order parallel or superimposed display of real-time display of the current vital sign data for each biological individual of interest and comparison display of daily values over a predetermined period or more; A biological information management system characterized by displaying a comparison result of how much each value of the current vital sign of the biological individual of interest deviates from the average cumulative value in the resting state.

[0014] [3](Utilization of body temperature change amount or change rate) The present invention is characterized by utilizing the body temperature change amount or change rate of a biological individual of interest obtained by a vital sign sensor as a method for detecting a resting state for acquiring data in the resting state. That is, any of the above biological information management systems In extracting data on the resting state of the ND step, based on the amount of change per unit time (slope) of the body temperature (body surface temperature, rectal temperature or estimated rectal temperature) of the target biological individual obtained by the vital sign sensor, whether the amount of change in the slope is below or above a threshold value, or whether there is an inflection point, determine the transition from the active state to the resting state and the transition from the resting state to the active state, and detect that it is in the resting state based on these transition determination times (and whether the skin temperature exceeds the threshold value). Thereby, it is possible to determine the time period in the resting state. For example, as shown in FIG. 24, values are detected at regular intervals, and by performing first and second order differentiations with respect to time, the first and second inflection points are identified, and also the amount of displacement and the magnitude of the slope per unit time are identified. Assuming that the time point of this inflection point is the intersection of the skin temperature and the rectal temperature, and / or by determining whether each value of the first order differentiation of time, i.e., the amount of displacement per unit time, and the second order differentiation of time, i.e., the amount of displacement of the slope, is within a difference range below a predetermined threshold value, it is possible to detect whether it is data in the resting state (data in the resting state).

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

[0016] Here, the attribute value data refers to data obtained by accumulating and statistically processing resting state data or daily value data of a plurality of biological individuals corresponding to a predetermined attribute criterion. The attribute value data of a specific target biological individual is data statistically processed, calculated, or computed using the resting state data or daily value data of a plurality of biological individuals included in a predetermined attribute value group to which the target biological individual belongs as original data. The original data also includes the resting state data or daily value data of the target biological individual itself.

[0017] For example, the numerical comparison results between the accumulated data of the daily value and the attribute value in a predetermined attribute group can be displayed simultaneously with the current vital sign data. Simultaneous display means any one of superimposed display, side-by-side display, or switching display. By comparably displaying the statistical processing values of the cumulative information regarding either the daily value data or the attribute value data, it is possible to perform a comparison of what characteristics a specific individual has compared to the average value within the same attribute group as the attribute group to which the individual belongs, and thus more accurately evaluate the current vital sign data.

[0018] 〔Definition of "Attribute Value"〕 Here, in the present invention, the "attribute value" and "attribute value data" refer to a value or data after statistical processing calculated based on the accumulation of the daily value data of the biological individuals to which the target biological individual belongs when the attributes of the target biological individual are complexly classified by a plurality of attribute parameters. For example, the value obtained by averaging the daily values of the biological individuals complexly classified into the attribute on a daily basis, or for each time zone or time.

[0019] ("Definition of 'Daily Value'") In addition, the "daily value" and "daily value data" in the present invention refer to vital sign data of the target biological individual at rest, excluding the activity state and the state of receiving non-daily stimuli, and mean daily values or their data for each day, or for each time zone or time. For example, values for each time zone or their ranges obtained by statistically processing (e.g., averaging) the data of the rest state on multiple measurement days for each time zone or time, or values and their ranges obtained by statistically processing (e.g., averaging) all measurement information with all the number of measurements are regarded as the values and their ranges of the daily values.

[0020] When the value changes according to the time or time zone, the average value for each day separated by time zone corresponds to the daily value of that time zone. Also, various numerical values such as the mode value of the daily value, the upper limit value of the daily value, and the lower limit value of the daily value are calculated by statistical processing.

[0021] The attribute value is a value displayed as a criterion for normal or abnormal compared with the daily value of the attribute of the individual. That is, the attribute value data is the data of the daily values of other animals in the same attribute group, and does not represent the comparison result of normal or abnormal. Whether the current state of the animal is normal or abnormal is judged by a veterinarian.

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

[0023] To supplement the prediction of the recovery state before and after surgery of a healthy body, The area under the standard normal distribution diagram of the vital sign data obtained before surgery at a significance level of 5% is compared with the area under the standard normal distribution diagram of the vital sign data obtained after surgery at a significance level of 5%, and the coincidence rate is calculated. With reference to the coincidence rate, a veterinarian judges the postoperative recovery situation.

[0024] [6](Admission, Hospital Visit Information) further comprising the step of setting admission information or hospital visit information to a hospital or facility for a predetermined symptom of the target biological individual, distinguishing and outputting the data in the resting state into data at the time of admission or hospital visit and data when at home, and as an alert step, determining whether the difference in values exceeds a threshold by numerical comparison with values of other attribute groups, and if it is detected that the threshold has been exceeded, notifying that information.

[0025] (Record Data Before and After Symptoms) Further, the system may further comprise the step of recording record data before and after symptoms. That is, it further comprises the step of recording data in the resting state during the preoperative or postoperative period of the target biological individual as record data before and after a specific symptom, recording the preoperative and postoperative data as group information including the progress history, and predicting and outputting a comparison result by comparing with the health state.

[0026] For example, by combining and comparing the data of each of the attribute groups "medical history", "surgical history", "before and after surgery", and "before and after contraception", outputting a state prediction result of the postoperative progress compared with the preoperative resting state based on the regression curve, that is, predicting and determining the time when the patient can move and the time to remove the restraint device and outputting the predicted time.

[0027] (Anesthesia Judgment Based on Preoperative Examination Information) In addition, the postoperative follow-up observation system may be a system that includes anesthesia judgment based on preoperative examination information and intraoperative information. That is, it further includes a step of recording vital sign data from preoperative examinations and / or intraoperative vital sign data, and a step of recording vital sign data in postoperative follow-up observations, comparing the progress information of the vital sign data for each step for each anesthesia information, and outputting an alert notification when predetermined conditions are met. In the alert notification, for example, it is determined whether the transmitted data exceeds a preset upper limit value, lower limit value, and average value, and an alert output is performed when it is detected that a predetermined threshold value has been exceeded. A time zone comparison value, an active time comparison value, and a resting time comparison value may be output together.

[0028] In this system, the vital sign data of preoperative examination information and surgical information can be linked and recorded with the data of postoperative sequelae obtained through postoperative follow-up observations, and data can be accumulated and statistically processed as the influence information of anesthesia for a plurality of target biological individuals.

[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, excluding data of a specific symptom occurrence period including the preoperative or postoperative follow-up period, from the daily value data of the resting state of the target biological individual, and outputting a comparison result between the most recent vital sign data of the target biological individual and the healthy daily value data of the healthy state.

[0030] [8]((Alert output) For the transmitted data, for example, as each value of a preset upper limit value, lower limit value, and average value, each value of an attribute value that is a value of a group of biological individuals of the same attribute by statistics, or / and each value at rest of the health state of the target biological individual can be used. For example, it is determined whether a real-time measurement value exceeds a preset predetermined numerical difference when compared with the average value of the attribute value and / or the average value of the daily value. When the difference in either comparison exceeds the limit, an alert is output in a distinguishable manner indicating which difference in the attribute value comparison or daily value comparison has been exceeded.

[0031] [9](Wearable transmitter) Before acquiring the vital data of the target biological individual, the sensor may use a close-fitting wearable transmitter attached to the target biological individual, which has a periodically transmitting sensor attached to a jacket-type clothing or a harness band that is closely attached around the torso (including the chest and the front and back of the abdomen) or around the body surface (excluding the limbs and the neck) of the target biological individual, such as those shown in FIGS. 24 and 41.

[0032] By using a close-fitting wearable transmitter as the vital sign sensor, it is possible to constantly wear it around the chest, the front and back of the abdomen, or around the body surface (excluding the limbs and the neck) of the target biological individual and reliably acquire vital sign data at regular time intervals. As a result, it is possible to constantly acquire the vital sign data of the target biological individual, grasp its trend, and display a highly accurate comparison value. In particular, in FIG. 41, the vital sensor includes a curved wire-type sensor 22WS in a jacket type or a harness band.

[0033] (Combined use of an intestinal insertion inspection device (pulse oximeter)) As the vital sign sensor, in addition to the above-mentioned close-fitting wearable transmitter, an intestinal insertion inspection device (pulse oximeter) is used in combination. The intestinal insertion inspection device (pulse oximeter) may be used to measure at least the pulse rate and the rectal temperature, and to calculate the estimated rectal temperature or confirm the error of the pulse rate.

[0034]

[10] The sensor for acquiring vital data of a target biological individual may be a wearable transmitter in which a curved wire-type sensor is attached along the jacket surface of a jacket-type clothing or the band surface of a harness band, as a biological information management system.

[0035]

[11] Quiet-time data is cumulatively stored together with time information as cumulative data of daily value data, The frequency distribution or relative frequency distribution of the cumulative data values of the daily value data cumulatively stored as time information for a predetermined time period is displayed as a linear bar-shaped gradation bar in which the class values are represented in the bar length direction with a section 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 shading pattern, as a biological information management system.

[0036] For example, as shown in FIGS. 25 and 26, the frequency (number of data acquisitions) / relative frequency (number of acquisitions in a category / total number of acquisitions) is displayed as a linear bar-shaped gradation bar (a color bar in the case of color) in which the frequency is sectioned in the bar length direction, as a biological information management system.

[0037]

[12] The daily value data for each time period of a group of biological individuals in the same attribute group having the same attributes as the target biological individual is cumulatively stored together with time information as cumulative data of attribute value data (attribute value data obtained by cumulating daily value data of the same attribute), The cumulative data values of the cumulatively stored attribute value data are displayed as a gradation bar in which the frequency (number of data acquisitions) / relative frequency (number of acquisitions in a category / total number of acquisitions) is bar-sectioned by a gradation-like color change or a change in shading pattern, as a biological information management system.

[0038]

[13] With the date and time axis as the horizontal axis or the vertical axis, a plurality of the gradation bars based on the cumulative data of the daily time data, divided for each measurement time period (for example, every hour), are displayed in parallel for each division of the measurement time period, as a biological information management system.

[0039]

[14] It may also be a biological information management system that displays a gradation bar based on cumulative data divided by the number of acquisitions of daily data (for example, N number: counted 50 times) with the date and time axis as the horizontal or vertical axis.

[0040]

[15] In the relative frequency of the frequency distribution in the cumulative data for displaying the gradation bar, it is determined whether the frequency of each class exceeds any of the preset upper limit value (the lowest class), lower limit value (the highest class), and upper and lower limit values, and whether a value appears within the preset upper and lower critical classes. If it is detected that it has exceeded, it may also be a biological information management system that outputs an alert.

[0041]

[16] In the frequency distribution in the cumulative data for displaying the gradation bar, it is determined whether either the difference between the average value and the median, or the maximum difference between the upper and lower limit classes, exceeds a preset lower limit value. If it is detected that it has exceeded, it may also be a biological information management system that outputs an alert.

[0042]

[17] It may also be a biological information management system that targets a plurality of biological individuals equipped with microchips for each individual, performs individual identification using the microchip number, authenticates whether the individual identification information using the microchip number matches a preset number of the biological individual, and displays an alert if the numbers are different.

[0043]

[18] Alternatively, for each individual, prepare a captured photo or video of the biological individual before admission. At the time of admission, automatically recognize the commonality between the pre-registered captured photo or video of the animal and the captured photo or video of the current animal at the time of admission, detect the identity of the diseased animal, and if the identity is lacking, display a confirmation alert for ID number misplacement. It may also be a biological information management system.

Effect of the Invention

[0044] By the above means, while measuring the vital sign data of a target biological individual and performing statistical processing of the previous vital sign data according to the characteristics of the target biological individual, a biological information management system capable of judging daily values considering data differences and trends due to individual characteristics (weight, gender, medical history, etc.) is provided.

Brief Description of Drawings

[0045]

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Mode for Carrying Out the Invention

[0046] (System configuration) The present invention relates to a system for acquiring and managing data of vital signs including at least one or more of the pulse rate, respiratory rate, and body temperature of a biological individual of a target including a human as information on the life activities of the target biological individual, A system comprising a wearable transmitter provided with a vital sign sensor attached to the target biological individual, a server for storing transmission and reception data, a processing device for processing the data of the server, and an output device for outputting the processing content.

[0047] <Overview of the system> (Taking the specific treatment date of the target biological individual as the start date of follow-up observation, Pre-operative data, standard deviation data, lower limit value and upper limit value data in time zone attributes, which are classified as activity data, are constantly observed every predetermined period by comparing them with the current vital data, and it is checked whether they are within the range of the attribute value, and an alert output is performed when the range of the attribute value is exceeded.

[0048] In addition, stress-related information regarding a predetermined symptom of the target biological individual is stored, Based on changes in body temperature and sweating amount, It is preferable to include a step of determining whether a change in the value of daily vital data (is due to stress).

[0049] (Communication line record between pet owner and attending physician after alert) The alert output is performed to the pet owner terminal, the attending physician or the hospital terminal, a character information chat or a call communication line is secured to display that the line is available, and a communication record after using the line is made.

[0050] (Basic content of the system of the present invention) The present invention is a system that sets and displays biological classification, attributes, and attribute value ranges for each individual, and performs and displays comparisons with the standard deviation of the attribute group and with the daily comparison average value for each individual.

[0051] One or more living animals are used as the target biological individuals. This includes pets such as dogs and cats, breeding animals, birds, reptiles, insects, and also humans. When inputting the biological individual, attribute data such as race category, large / small / male / female, birth region, age, etc. are registered as attribute information for distinguishing the target biological individual for each attribute group.

[0052] (Features of the present invention) The present invention is characterized in that it performs a comparison display of the current vital sign data, which is biological information such as the pulse, heart rate, body temperature, and presence or absence of body movement of the target biological individual, with the daily value data of the statistical processed target biological individual. In the embodiment, four types, namely pulse, heart rate, body temperature, and presence or absence of body movement, are used as vital signs. However, at least one or more of pulse, heart rate, and body temperature may be acquired as vital signs.

[0053] That is, it is equipped with a vital sign sensor and transceiver attached to the target biological individual (including humans), a server for storing the transmitted and received data, a processing device for processing the data of the server, and an output device for outputting the processing content. By going through at least the following steps, the current vital sign data of the target biological individual is displayed in real time, and it is displayed where in the range of the corresponding daily value data this vital sign data is located.

[0054] As steps of the processing performed by the biological information processing system, · An ND step of creating (as an attribute value) the standard deviation data of a predetermined attribute group by item classification of the attribute group and data accumulation in the server, A BS step of constantly acquiring (and temporarily saving) the vital signs of the target biological individual by means of a sensor directly attached to the target biological individual and a sensor installed at a distance from it; A step of differentiating between data in a resting state and data in an active state from the saved vital sign data, and creating daily average value data and upper and lower limit data of daily values in the resting state; Based on the standard deviation data of the ND step and the created data of the step, a PN step of calculating and displaying the numerical comparison result of the vital sign data by the current step BS is performed.

[0055] The content of each step sequentially performed by this method will be described below. First, the BS step is performed. The BS step is a step of continuously or intermittently acquiring vital sign data of the target biological individual by means of a sensor directly attached to the target biological individual or / and a fixedly installed sensor, and saving it on a server. Here, the vital sign data of the biological individual means measurement information indicating the physical and mental state in the living state of the biological individual, such as heart rate, respiratory rate, body temperature, body movement, and SPOO2 (blood oxygen concentration). In this embodiment, it means at least two or more of heart rate, respiratory rate, body temperature, body movement, and SOPOO2, and the information that can be acquired by various sensors such as a temperature sensor, a light sensor, an ultrasonic sensor, a pressure sensor, and a gyro sensor is regarded as vital sign data or vital data. In the BS step, a pulse oximeter 61S (Fig. 13) that is in close contact with or inserted into the target biological individual and a sensor (23) detected by remote observation may be used in combination. As a method of constantly acquiring, it is repeatedly acquired at set times in the range of 5 to 60 seconds or at set times between 1 minute and 10 minutes. The acquired data is displayed in real time as the current vital sign data of the biological individual, and is used to determine whether it is data in a resting state by calculating the amount of change and the change rate of the amount of change of the value as continuous data.

[0056] The ND step is a step in which a processing device extracts data in a resting state that satisfies predetermined setting conditions from the stored vital sign data, and statistically processes a data group of the resting state of the target biological individual over a predetermined period as daily value data. This is premised on the storage of accumulated data of the target biological individual or alternative data in place of it. From the vital sign data of the target biological individual, data in the resting state is extracted, and only the data in the resting state over a predetermined period is normalized (approximated to a normal distribution by Fourier transform), and data on the upper limit value, lower limit value, or / and average value (on the normal distribution approximation data) in the resting state over a predetermined period up to the most recent is created and stored as a second step. Also, the PD step is performed. The PD step is a third step of creating and storing at least one or more data selected from any of the upper limit value, lower limit value, average value or median value, and standard deviation of the normal distribution data. Next, the CD step is performed. The CD step is a fourth step of numerically comparing the current vital sign data obtained by the ND step with each data of the PD step, and displaying and storing the comparison result.

[0057] Then, the PN step is performed. The PN step is a step of displaying in parallel or superimposing the real-time display of the current or most recent vital sign data for each target biological individual and the daily value data over a predetermined period or more for the target biological individual. By this step, the comparison result between each value of the current vital sign data of the target biological individual and the statistically processed daily value data in the resting state is output (FIG. 18(a), FIG. 21).

[0058] (Superimposed display of upper and lower limit values) In the PN step, the comparison result of how much each value of the current vital sign deviates from the value in the resting state, that is, the data in the resting state, is superimposed and displayed. By performing parallel or overlapping display of real-time display of current vital sign data for each target biological individual and comparison display of daily values over a predetermined period or longer, a comparison result indicating how much each value of the current vital signs of the target biological individual deviates from the daily value in the resting state is displayed.

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

[0060] An example of a display in which each value of the current vital signs is superimposed on a box plot of the upper limit value, lower limit value, and average value of the daily value data is shown in FIG. 18(a). On the other hand, an example of a display in which each value of the current vital signs is superimposed on a box plot of the upper limit value, lower limit value, and average value of the attribute value data is shown in FIG. 18(b).

[0061] FIG. 18 shows an example in which a box plot comparison (a) with daily value data, which is data of the resting state of a symmetric particle individual, and a box plot comparison (b) with attribute value data are arranged vertically side by side. In addition, FIGS. 18(a) and 18(b) can be switched and displayed with each other. For example, in a so-called daily value comparison display in which it is desired to display a comparison with the box plot of the daily value of the target biological individual, each value of the current vital sign data can be collectively displayed. Further, by switching from this state, each value of the current vital sign data can be collectively displayed in a so-called attribute value comparison display in which it is desired to compare with the daily value of the attribute group to which the target biological individual belongs.

[0062] As another example of superimposed display, FIG. 21 shows an example in which the values of the current vital signs are simultaneously superimposed on a line graph of the daily value data and an average curve of the attribute value data. In FIG. 21, each value of the current vital signs, represented by a thick line, is displayed in a graph progression state over time.

[0063] In FIG. 21, together with the line graph display of the vital signs, the average value, upper limit value, and lower limit value of the data of the target biological individual in the resting state in the same time zone are superimposed and displayed in a line graph using a single-dashed line or double-dashed line as the daily value average, daily value upper limit, and daily value lower limit. Further, in FIG. 21, together with the bold line graph display of the vital signs and the line graph display of the daily value data with a single-dashed line or double-dashed line, the average upper limit value and average lower limit value of the attribute value data of the target biological individual in the same time zone are superimposed and displayed by a broken-line curve and dot filling in the upper and lower ranges of the curve.

[0064] Note that the × (cross) marks overlapping the line graph of the vital signs in FIG. 21 indicate inflection points where the sign of the slope changes. Also, the display of the arrow touching the line graph indicates the time point when an alert is notified based on each comparison value. Further, the vertical line intersecting the line graph indicates the time point when the value intersects with each comparison value. This vertical line display indicates the time point exceeding the average of the daily value upper and lower limits and attribute value upper and lower limits up to now, and also estimates the start time and end time based on the slope of the graph and the value on the graph. The estimated start time and end time are displayed in the alert dialog (FIG. 21).

[0065] In FIG. 21, two types of data, namely daily value data and attribute value data, are simultaneously superimposed and displayed on the graph of the vital signs. However, it is also possible to switch to the superimposed display of any one type of daily value data or attribute value data and display them as respective comparison graphs (not shown). Also, the display on the line graph can be switched to the one-axis display as shown in FIG. 18.

[0066] (Detection at rest) This system creates standard deviation data (attribute values) of a predetermined attribute group by item classification of the attribute group and data accumulation to the server, constantly acquires (and temporarily stores) the vital signs of the biological individual by means of a sensor directly attached to the target biological individual and a sensor installed at a distance, Distinguish between resting state data and active state data from the saved vital sign data, and perform an ND step of creating daily average value data and upper and lower limit value data of daily values in the resting state. In this ND step, the following resting state detection methods can be mentioned as methods for extracting resting state data.

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

[0068] (Alert detection by numerical comparison with values of other attribute groups) Further include a step of setting a predetermined attribute group to which the target biological individual belongs, Compare how a specific solid behaves compared to the average value within the same attribute group, and output the numerical comparison results between the daily value and the accumulated data of the attribute value in the predetermined attribute group separately as daily value comparison data during stress (at the time of hospitalization) and daily value comparison data during non-stress (at home).

[0069] By comparing how a specific solid behaves compared to the average value within the same attribute group, the individual characteristics can be grasped and a judgment can be made compared to other same attribute groups. A detailed alert can be issued by combining the daily value alert and the accumulated data of the attribute value. It is possible to distinguish the daily value during stress (at the time of hospitalization) and the daily value during non-stress (at home).

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

[0071] (Comparison with excluded attribute value data) A step of statistically processing the excluded attribute value data, which is a group of daily value data of a plurality of biological individuals in the attribute group to which a specific target biological individual belongs, excluding the daily value data of the target biological individual, The biological information management system according to claim 3KL, characterized in that the daily value data of the target biological individual is compared with the excluded attribute value data of the attribute group of the biological individual excluding the daily value data of the biological individual, and the comparison result is output.

[0072] (Comparison with healthy daily value data) The method further includes a step of recording, as record data, the healthy daily value data that satisfies a predetermined healthy determination condition, excluding the data of the occurrence time of a specific symptom including the preoperative or postoperative elapsed period, among the daily value data of the target biological individual in the resting state, and outputting the comparison result between the most recent vital sign data of the target biological individual and the healthy daily value data in the healthy state.

[0073] (Alert sounding by comparing the upper and lower limit values of daily value data) Regarding the output compared with the upper and lower limit values of the above daily value data, at a significance level of 5% with a value twice the standard deviation, if there is no significant difference, no alert is sounded. If there is a significant difference, an alert is sounded. This output process is the basis. The position of the significance level can be preset by a veterinarian as the boundary position of the alert. For example, it is set by %, pulse rate, respiratory rate, etc.

[0074] The daily value data at rest, that is, the data in the resting state, is extracted, statistically processed, and output by the following processes, for example. · As an activity exclusion process, the data in the time period that satisfies the discrimination condition regarding the exclusion processing activity amount is excluded as activity zone data. · As a statistical process, the mode value, the second value, or the extreme 2.5% region of the standard deviation data (which varies greatly depending on the activity amount) is calculated. · As a variation range comparison display, the boundary values of the variation range by daily time period (abnormal value criteria), whether it is within the variation range or not, are displayed with classification symbols such as ABC or comments.

[0075] "Save the average value, the comparison with the upper and lower limit values, and each cumulative value of the standard deviation (variation) together with the data within each group of the period group, time zone group, and rest / activity ratio data.

[0076] (Data update) The data for creating daily values is updated as needed by accumulating vital sign data. At this time, the accumulated data obtained by accumulating the detection values using an acceleration sensor for each unit of time is used as a criterion for distinguishing or extracting whether it is a resting state or an active state. In determining whether it is a resting state, for example, using the accumulated data obtained by accumulating the detection values for each unit of time, the maximum upper and lower values in a predetermined time period or the value of the degree of change over time (the slope or the displacement amount of the slope on the time axis) is calculated, and compared with a threshold value set in advance for each biological individual or its attribute group, and only the data determined to be in the resting state is extracted. At this time, by attaching time (time period) data, it is preferable to accumulate and store only the data in the resting state together with time information. By accumulating and storing the data in the resting state together with time information over a predetermined period for a single target biological individual, comparison based on the time period criterion and prediction of changes over time can be performed. Using this comparison and prediction, for example, it is possible to determine whether the current fluctuation of the vital sign data is just a temporary value fluctuation or a value fluctuation due to an emergency. For example, symptoms that are of low urgency and gradually deteriorate can be judged, and early detection can be achieved through data prediction. In particular for pet livestock, the judgment and prediction of symptoms are important.

[0077] Specifically, it includes the PD step 3-3 of setting and displaying the biological classification / attributes and the attribute value range for each individual, comparing with the standard deviation of the attribute group, and displaying the fluctuations in time series together with the time data, It includes the GD step of creating reference data for a predetermined attribute group, such as standard deviation data, by classifying the items of the attribute group and accumulating data in the server.

[0078] (Admission / hospital visit information) It further includes a step of setting the admission information or the hospital visit information to a hospital or facility for a predetermined symptom of the target biological individual, It can be a biological information management system that outputs separately the data at the time of admission or hospital visit and the data at home.

[0079] (Group record of pre-operative and post-operative data) It further comprises the step of storing the treatment information for a predetermined symptom of the target biological individual, and grouping and recording the data of the resting state during the preoperative or postoperative elapsed period of the target biological individual as the 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", the postoperative progress can be judged.

[0080] (Alert output) Determine whether the transmitted data exceeds the preset upper limit value, lower limit value, and average value. If it is detected that the value has exceeded, an alert output is performed.

[0081] For example, in a morphological example of an alert output system for postoperative progress observation, Taking the specific surgery date of the target biological individual as the start date of follow-up observation, the preoperative data, standard deviation data, lower limit value, and upper limit value data classified in the activity data are constantly observed at each predetermined elapsed period in comparison with the current vital data, checking whether it is within the range of the attribute value, and performing an alert output when the range of the attribute value is exceeded.

[0082] In addition, it is also possible to make a judgment based on the preoperative examination information and during anesthesia. For example, a judgment system for preoperative examination and anesthesia that displays whether it is within the range of the attribute value and the presence or absence of fluctuations can be considered. Also, in the judgment during anesthesia, ···· becomes the judgment item.

[0083] As another morphological example different from the above, there is an alert system for inpatient management and during operation. This morphological example targets a plurality of biological individuals equipped with microchips for each individual, performs individual identification using the microchip number, and collectively displays the current vital sign information and the presence or absence of alerts of all biological individuals corresponding to the attribute group, classified by the number of the positive particle individuals.

[0084] In this system, when performing multi-head individual identification using an installed type total transmitter and a wearable transmitter, in addition to identification by ROI, individual identification using the microchip number is performed.

[0085] (Communication line record between pet owner and attending physician after alert) When an abnormal value is detected, an alert output is sent to the pet owner terminal, the attending physician, or the hospital terminal, and a character information chat or a call communication line is secured to display that the line is available, and a communication record after line use can be made into a system.

[0086] (Diagnosis system for health information (system for utilization in health check) A system that adds measurement data of a biological individual in a health check and records it as time-series data.

[0087] (Wearable transmitter) The sensor that acquires vital data of the target biological individual is a wearable transmitter in which the sensor is attached to a jacket clothing or a harness band that is always worn by being closely attached around the torso (including the chest and the back and abdomen) of the target biological individual (or around the body surface excluding the limbs and the neck) (Figure 12).

[0088] (13) Estimation of rectal temperature: Use an intestinal insertion inspection device (pulse oximeter) in combination. Separate from the wearable transmitter that is always worn, it is a system equipped with an intestinal insertion inspection device (pulse oximeter 6) that is temporarily inserted into the intestine of the biological individual, The intestinal insertion inspection device (pulse oximeter 6) measures at least the pulse rate and the rectal temperature, and can calculate the estimated rectal temperature or display the error of the pulse rate. For example, assuming that the time corresponding to the highest temperature and the time corresponding to the lowest temperature of the rectal temperature coincide with the time corresponding to the highest temperature and the time corresponding to the lowest temperature of the epidermal temperature, the rectal temperature is estimated.

[0089] (Each step in the first biological information management method) The first biological information management method of the present invention includes a vital sign sensor and a transceiver attached to a target biological individual including a human, a server that stores transmission and reception data, a processing device that processes the data of the server, and an output device that outputs the processing content, and is executed including at least the following steps.

[0090] Each of the above steps refers to A data acquisition step of continuously or intermittently acquiring vital sign data of the biological individual by a sensor directly attached to or / and a fixedly installed sensor of the target biological individual and storing it in a server; A statistical processing step of extracting data in a resting state determined to be in a resting state by satisfying a predetermined setting condition from the stored vital sign data by the processing device, and statistically processing a data group in the resting state of the target biological individual over a predetermined period as daily value data; For the target biological individual An output processing step of displaying while updating in real time the vital sign data of the current time to the most recent time for each of the target biological individuals, and displaying in parallel or superimposed with the daily value data over a predetermined time or period.

[0091] By the above output step The comparison result between each value of the current vital sign data of the target biological individual and the statistically processed daily value data in the resting state is output.

[0092] (Steps in the second biological information management method) The second biological information management method of the present invention includes at least the following steps, which specifically specify the first biological information management method more specifically. That is, The data acquisition step of acquiring the vital sign data of the biological individual at regular time intervals by the sensor directly attached to or / and the fixedly installed sensor of the target biological individual and storing it together with the acquired time and information of the biological individual; The statistical processing step of extracting data in a resting state from the vital sign data of the target biological individual, performing normal distribution processing on the data in the resting state over a predetermined period, and creating and storing normal distribution data in the resting state over a predetermined period up to the most recent time; In the normal distribution data at each obtained time, at least one or more data selected from the upper limit value, lower limit value, average value or median value, and standard deviation are created and saved as cumulative value data in a cumulative processing step; A comparison processing step of performing a numerical comparison between the vital sign data at the current time or the most recent time and the data of any of the above steps, and displaying and saving the comparison result; The output processing step of performing parallel or superimposed display of the real-time display of the current vital sign data for each biological individual of the target and the comparison display of the daily value data over a period of a predetermined length or more. By performing these steps in order, It is characterized by outputting a comparison result of how much the vital sign at the current time or the most recent time of the biological individual of the target or the calculated value based on the same deviates from the cumulative value data of the biological individual of the target.

[0093] [Explanation of each step] (Creation of specific attribute group data) In the cumulative processing step, classification item examples of the attribute group and data accumulation to the server, that is, data cumulative storage processing are performed. In this step, biological classification / attributes and the attribute value range for each individual are set to be selectable in multiple ways with option tags. All accumulated data corresponding to all options are extracted to create standard deviation data (for example, average value, upper limit value, lower limit value of the attribute value) of the attribute group to be compared.

[0094] The standard deviation data consists of data on the number of breaths at night, pulse rate at night, blood pressure, SPO2 (blood oxygen concentration), body surface temperature at rest during the day, predicted body temperature based on the body surface temperature during the day, and instantaneous acceleration of the torso in a quiet state with suppressed body movement.

[0095] For the comparison of vital sign data, it is preferable to categorize the target biological individual (target animal) with a plurality of attribute parameters and identify the attribute group according to the combination of each attribute parameter. In the identification of the attribute group, for example, according to the above input content, which attribute group of which attribute parameter is to be identified in multiple steps. For example, as shown in FIG. 11, by performing grouping by combining three types of large / medium / small, two genders, three types of age: young, middle-aged, and prime, two types of temperament, and three types in the BCS "Body Condition Score" 5-stage evaluation of weight, it is possible to identify which attribute group the target biological individual (target animal) belongs to among a maximum of 216 attribute groups. The identified attribute group can be displayed on the management screen of the target biological individual (target animal) with the identification symbol 221DG attached (FIG. 8).

[0096] In the case of humans, for example, grouping is performed by combining gender (male and female), age (about 5 groups), and BMI (3 groups) based on weight and height.

[0097] (Examples of attribute parameters in the case of animal species: "dog / cat") The display software presents the display screen of the basic information of the living body (animal) of the target biological individual in a selection or entry form to prompt the user for input. <In the case of animals> · Animal species (dog / cat) · Breed (3 groups for one animal species) · Gender (male / female) · Age (3 groups) · Temperament (2 groups) · Enter weight (grouped into 3 groups with the BCS "Body Condition Score" 5-stage evaluation) Maximum 216 groups <In the case of humans> · Gender (male and female) · Age (about 5 groups) · Enter weight and height (grouped into 3 groups with the BMI "Body Condition Score" 5-stage evaluation) Maximum 30 groups

[0098] (Acceleration sensor and transmission) In the data acquisition step, measurements are taken at regular time intervals using a three-axis acceleration sensor. The data is transmitted in batches at several-minute intervals.

[0099] (Data acquisition step) Data acquisition is performed, for example, every second to several seconds, and data transmission is performed, for example, at 5- to 10-minute intervals. These time intervals are configurable. The data acquisition step specifically includes the following steps F11 to F13. F11: Data extraction step for resting state: Exclude data that meets the activity conditions (server), and accumulate and store the resting vital data (server). F12: Extract only the data DR in the resting state obtained by excluding the activity condition data DA from the vital sign data D of the target biological individual measured every unit time, and collect, accumulate, and overwrite and store it in the memory M. F13: Overwrite and store on the oldest time data, transmit at specific times or per data accumulation amount, and store at the server

[0100] In the F12: Data extraction step for the resting state, <detection of resting and active states> is performed based on the content of the ND step: extraction of data in the resting state. Here, data is acquired at intervals of 1 minute to several minutes, and regular data output is performed at intervals of several minutes to several hours.

[0101] (Statistical processing step) Accumulate data of daily values for a specific individual: Continuously measure and accumulate the lower limit value, upper limit value, and average value of the resting daily value together with each value of the attribute data. The accumulated data is stored in an overwritable manner as an "attribute value" (Figure 13).

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

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

[0104] <How to issue counter-attribute value alerts> Six types of alerts can be issued based on the respiratory rate, pulse rate, and body temperature. Hypothetical cases can be presented based on combinations of alert types. However, the upper and lower limits vary depending on the time zone classification. The specific procedures for statistical processing are as follows, for example.

[0105] Step 1. Create a frequency distribution table, record the data of the pulse rate and respiratory rate, determine the classes of the pulse rate and respiratory rate data, determine the class values (median) of each class, find the number of data (frequency) in each class, find the proportion (relative frequency) that each number of data in each class occupies with respect to the whole, and then find the cumulative relative frequency, which is the sum of the relative frequencies up to a certain class.

[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 the total area is 1.

[0108] Step 4. Connect the histogram with a smooth curve.

[0109] When a large number of data are collected and accumulated, the graph connecting the upper ends of the histogram gradually becomes smoother. This curve is called the probability density function or density function of the variable. By performing a definite integral on this probability density function f(x), the area can be obtained, and this area becomes the probability. The sum of the areas of the probability density function is 1.

[0110] Step 4-1: Calculate the area (probability) of the histogram or the area (probability) obtained by performing a definite integral on the probability density function f(x), and calculate the ratio (coincidence rate) of the overlapping area of two data sets of histograms with the same parameters or areas obtained by performing a definite integral on the probability density function f(x).

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

[0112] In this step, visual confirmation is performed using a frequency distribution diagram (histogram) or a normal probability graph. For example, if a graph (Q-Q plot) with the expected value of the data following a normal distribution on the vertical axis and the numerical value of the data itself on the horizontal axis forms a straight line, it is determined that the data is normally distributed. The normality is also judged using statistical methods described separately.

[0113] <Regarding Normal Distribution Processing> The left figure in Fig. 16 shows a graph of a normal distribution and the ranges of the standard deviation and its 2-fold and 3-fold values. 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 whole is within the range of plus or minus 1 of the mean value · Approximately 95 percent of the whole is within the range of plus or minus 2 of the mean value (in some cases, the value of 1.96σ may also be used). · Approximately 99.7 percent of the whole is within the range of plus or minus 3 of the mean value

[0114] As the test statistic, the following null hypothesis can be used. · Null hypothesis: The hypothesis to be tested for rejection. It is the hypothesis of "no difference". · When the null hypothesis is not rejected, it is considered that there is no significant difference. · When the null hypothesis is rejected, it is considered that there is a difference, that is, there is a significant difference.

[0115] Here, the significance level (risk rate) is explained. The criterion for judging "whether to be rejected" uses the probability of the null hypothesis being established as an index, and this probability is called the significance level (or risk rate). There is no clear criterion for setting the significance level, but 5% (0.05) is adopted in the medical field. For example, "significance level 5%" means that "the probability of the null hypothesis being established is 5%". If the probability of the calculated value of the test statistic appearing is lower than the significance level, it means that "something that rarely happens has happened", and the null hypothesis is rejected.

[0116] The right figure of Fig. 16 shows an example in which, assuming a normal distribution through data correction, the range of the test statistic, that is, the boundaries of the P-value, are displayed as UDmin (minimum value) and UDmax (maximum value) for each number of trials in the statistical processing step. In this figure, the significance level is set at 5%, that is, the area of the test statistic where the null hypothesis is not rejected is 95%, and it is assumed that there is no significant difference within this area range. On the other hand, the 2.5% area regions at both the left and right ends of this figure are the regions where the null hypothesis is rejected and are excluded from the range of the test statistic.

[0117] Note that without performing the standard normal distribution process, the four values of the median, mean, upper limit value, and lower limit value may be displayed side by side as reference values. 5.0% on the left and right, that is, 2.5% on each side. The upper figure of Fig. 18 shows a comparative display of the biological substances of the target biological individual, and the lower figure of Fig. 18 shows a comparative display of the biological substances of target G.

[0118] When it is determined that the data follows a normal distribution after the statistical method judgment, the following subsequent Step 5-1 can be mentioned. <Step 5-1. When it is normally distributed> First, from the value of 100P% obtained by converting the probability P to %, the pulse rate or respiratory rate is calculated at both the 10% points (5% points on one side), or both the 5% points (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 % point set by veterinary medical personnel, on both sides of the normal distribution curve of the pulse rate or respiratory rate.

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

[0120] <How to issue alerts for daily values> Six types of alerts can be issued by the server based on the respiratory rate, pulse rate, and body temperature. Hypothetical cases can be presented according to the combination of alert types.

[0121] And when, at each % point, the currently measured pulse rate and respiratory rate are lower than the pulse rate and respiratory rate at the lower % point, a lower limit alert is generated. The pulse rate and respiratory rate at each % point are updated each time data collected every few minutes is statistically processed. The alert setting range and the upper and lower limit values of the alert are also automatically changed.

[0122] When creating the standard deviation and calculating the upper and lower limit values of the daily values, the parameter: measurement time zone (early morning, morning, noon, evening, night, late at night) may be used. When adding comparison items in creating the daily average value data in the resting state, the daily average value data in the resting state is transmitted every hour.

[0123] [Processing in the operation of this system] This system constructs the following mechanism. (1) By continuously recording the measured values of vital signs, whether in the hospital or at home, the daily values of the patient or the target biological individual are calculated and recorded. (2) From the collected data, the attribute values of a group that matches the characteristics of the target biological individual (including other individuals) (characteristics combined with attribute parameters such as male / female / age / dog breed / origin, / blood type, etc.) are statistically calculated, and at the same time, the normal range for the patient or the target biological individual is calculated using the standard deviation from the collected data. (3) Compare the daily values and attribute values of the patient or the target biological individual, and based on the normal range, assist in determining whether the daily values and measured values are normal or abnormal.

[0124] Specifically, the following three numerical comparisons are made. · Compare the attribute values of a group of biological individuals with the same underlying disease with the daily values. · Compare the attribute values of healthy biological individuals in an attribute group with the same age and race category within a group of biological individuals with the same underlying disease with the daily values of the biological individual. · At the same time, estimate the severity of the current situation by comparing the daily values of this biological individual with each other.

[0125] [Explanation of Terms] The daily value information refers to the daily values based on biological and living information. For example, there is the quantification of information such as the amount, frequency, and color of excrement.

[0126] The following ABCD are listed as application examples of this system.

[0127] Application Example A: A pre - anesthesia evaluation (referring to objective vital signs in addition to the interview) system. It is used during anesthesia treatment, postoperative progress observation, or postoperative treatment and daily recovery judgment.

[0128] Application Example B: An intraoperative management system: A system that refers to daily attribute values to set the stage of the variation range according to the individual, and details the alert content during risk judgment. Since the alert risk information (time margin until death) varies for each animal species attribute, improving alert accuracy is important in veterinary treatment. For example, anesthetic depth and arousal level are mentioned.

[0129] Application Example C (Health information diagnosis system (system for utilization in health check - ups)) A system that adds the measurement data of biological individuals in a health check - up, records and displays it as data by measurement year.

[0130] Application Example D (Alert system during hospitalization management) A system that targets a plurality of biological individuals equipped with microchips for each target biological individual, performs individual identification using the microchip number, and collectively displays the current vital sign information and the presence or absence of alerts for all biological individuals belonging to the attribute group, classified by the number of the biological individual.

[0131] [Specific examples of procedures in surgery] Data to be used: Set the daily value of the individual from the numerical values of the vital signs when the target biological individual is relaxed and sleeping at night at home. Obtain the numerical values of the vital signs and the data of the upper and lower fluctuation ranges (resting values) when the target biological individual is sleeping after surgery in an animal hospital.

[0132] The timing of obtaining daily value data is ideally when the patient is at home before surgery or before hospitalization. However, if there is already data obtained at home, the data at that time should be used. The attribute values are statistically calculated from the data of various individuals collected nationwide under the same conditions (such as the same disease name, the same animal, the same age, the same gender, etc.). When the data is insufficient, substitute the numerical values of the general vital signs of animals described in papers or the like.

[0133] Before surgery (judge whether the off - hospital vital data is a stable value as "pre - operative examination information") Compare the daily value and the attribute value (in the case of having a chronic disease, the pre - operative attribute value of the same disease state and the same disease group, and the attribute value of a healthy person if healthy) from the accumulated data. Compare the individual daily value obtained before surgery or before hospitalization with the attribute value. When there is no particular problem with the individual, the daily value and the attribute value should be in the same range of values. However, if there is an error of a certain numerical value or more between the daily value and the attribute value, the system automatically judges the possibility that something abnormal has occurred in the individual or the possibility that the chronic disease has deteriorated (such as congenital anomalies), and the system assists in judging the implementation of other examinations, the postponement or cancellation of surgery (the safety of surgery execution).

[0134] The wearable sensor measures the body surface temperature, and it may also be used to estimate and calculate the rectal temperature from this body surface temperature. <Estimation and calculation of estimated rectal temperature> The calculation of the estimated rectal temperature is performed, for example, by the following four steps. Step 1. Four times a day, at the time of getting up, before lunch, before dinner, and before going to bed, spot - measure the rectal temperature of the animal using the wearable transmitter or the installed - type transmitter with a rectal - insertion - type pulse oximeter (such as the reference numeral 6 in FIG. 13). 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 skin temperature and the outside air temperature, and the difference between the average rectal temperature of the four measured values and the skin temperature, and calculate the estimated rectal temperature. Step 4. Each time the rectal temperature is spot-measured, the estimated rectal temperature is updated by calculating and recalculating the average value by adding the rectal temperature at that time and the epidermal temperature at the same time.

[0135] Refer to the outside air temperature and the attribute group value. In the embodiment, the wearable transmitter suppresses the influence of the outside air temperature by a jacket-type clothing with high adhesiveness. Alternatively, a harness type or a harness structure with high adhesiveness may be used in combination. As the wearable transmitter, it also has the effect of preventing hair loss and stress reduction due to friction. By measuring the abdominal temperature and the heartbeat (pulsation) with a jacket-type sensor, highly accurate measurement can be performed at all times. The respiratory rate is measured using an acceleration sensor and a tension sensor.

[0136] Similar to the body temperature measurement, if the oxygen saturation can be measured rectally, it is possible to reduce the labor and achieve both the stability and reproducibility of the measured values. For example, by using a pulse oximeter 6 inserted into the rectum and incorporating a transparent resin part 610 with a built-in pulse oxygen sensor 51S (Fig. 13), a measurement method including the step of measuring the oxygen saturation rectally can be obtained. The thermometer-type pulse oximeter 6 as shown in Fig. 13 has the function of a pulse oximeter added to the thermometer incorporation part of a flexible shaft for rectal measurement. For example, as shown in Fig. 13, this pulse oximeter has a form in which a flexible shaft 61 that can be elastically bent and deformed is connected to the side part of each plate-shaped control box 62 via a conical elastic connection part 61T. The control box 62 has a power supply, 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, a long hemispherical part with a tip that tapers toward the front side, a cylindrical transparent resin part 610 incorporated near the tip, and a sensor 61S incorporated in the transparent resin part 610. The sensor 61S has a temperature sensor and a reflective SPO2 sensor incorporated with a circumferential separation.

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

[0138] (Use of attribute values in preoperative examinations) In the preoperative assessment (preoperative examination), normal values and attribute values can also be used. (Regarding preoperative assessment) The veterinarian performs a preoperative assessment immediately before anesthesia on the day of surgery. The purpose of the preoperative assessment is to grasp the general condition of the animal and evaluate the severity, predict intraoperative and postoperative complications, and formulate perinatal management measures. This system is a system that particularly assists in the preoperative assessment among preoperative examinations. In the preoperative assessment, the veterinarian makes an evaluation with reference to the evaluation items described below.

[0139] (Evaluation items) · Heart rate · Respiratory rate · Presence or absence of heart murmur · Presence or absence of abnormal breath sounds: · Oral medications · X-ray examination: · Ultrasonic examination: · Blood test (WBC, PCV, PLT, ALB, GLU, ALT, ALP, BUN, CRE, Na, K, Cl, CRP / SAA) · Presence or absence of epilepsy, allergy · Presence or absence of dyspnea, cyanosis, mucosal pallor, abdominal distension · Consciousness level: Any of normal · drowsy · confused · comatose · ASA-PS, BCS, degree of expected pain: Mild · Moderate · Severe

[0140] The inquiry information provided by veterinarians to pet owners is inaccurate because it pertains not to the owners themselves but to animals that cannot communicate. Additionally, due to the lack of past records, there may be misunderstandings, lapses in memory, or forgetfulness on the part of the owners. Therefore, a device is used to continuously obtain objective vital sign information for pre-anesthetic evaluation.

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

[0142] Furthermore, an anesthesia record format is used to record anesthesia information and biometric information during surgery, but it is time-consuming to fill out during the operation. Additionally, there are facilities that do not have anesthesia records themselves. Therefore, after unifying the format in this system, records are made, and all veterinarians using this system can view the anesthesia records and their prognosis records from other hospitals to search for the types of anesthetics, the amounts of anesthetics, and their prognosis used in past cases of pets with similar individual information. Also, the daily values and attribute values of vital signs are reflected in the anesthesia records.

[0143] The recorded information during anesthesia includes, for example, the following administration information. For example, information such as oxygen, air, infusion therapy (physiological saline, Ringer's solution, colloidal solution), inotropic agents (dobutamine, dopamine, ephedrine), analgesics, and other atropine.

[0144] Automatically set upper and lower limit alarms for the attribute values such as pulse rate, respiratory rate, and body temperature of pets with the same individual information on the biometric information monitor used during surgery, and alert the surgeon. Additionally, by automatically reflecting the following information in the anesthesia record, the workload of veterinarians and pet owners is reduced, and pre-anesthetic evaluation is performed with accurate information. ·Biological information of the pet collected by a home device when the pet is at home before surgery (vital information during home standby, urine volume, feces volume, and toilet visit frequency information, beverage and food intake information, weight information) ·Biological information of the pet collected by a hospital device when the pet is at the animal hospital before and during surgery (vital information during hospitalization, biological information monitor, drug information during surgery, blood loss information, etc.) ·Information in the (electronic) medical record of the animal hospital (past anesthesia experience, medical history, etc.) ·Individual information registered by the owner in the home display software

[0145] This system can be applied as a system that particularly assists in the pre-anesthetic evaluation during the preoperative examination. <Pre-anesthetic Evaluation System> The purpose of the pre-anesthetic evaluation system of the present invention is to grasp the overall condition and severity of the animal using vital sign data immediately before anesthesia on the day of surgery, predict complications during and after surgery, and formulate perinatal management measures. In the pre-anesthetic evaluation, the veterinarian conducts an evaluation with reference to the following items. (1) Reduction of the burden of preoperative examination The interview is conducted by the veterinarian to the owner. Since these information are not about the owner's own body and the animal cannot talk, there may be inaccurate information. Also, due to the lack of past records, there may be misunderstandings, misrecollections, or forgetfulness on the part of the owner. Therefore, by using a device to collect data, the pre-anesthetic evaluation is performed based on accurate (objective) information. (2) Pre-recording of anesthesia records, recording during surgical treatment, data accumulation In addition, a format of anesthesia record such as an attached file is used for recording anesthesia information and biological information during surgery, but it is time-consuming to fill in during surgery. Also, there are facilities that do not have anesthesia records themselves. Therefore, after unifying the format in this system, records are made, and all veterinarians using this system can view the anesthesia records and their prognosis records of other hospitals, so as to search for the types of anesthetics, the amounts of anesthetics, and their prognosis used in past cases of pets with the same individual information. In addition, the daily values and attribute values of vital signs are also reflected in the anesthesia record.

[0146] Specifically, for the biological information monitor used in surgery, upper and lower limit alarms are automatically set within the range of attribute values such as the pulse rate, respiratory rate, and body temperature of the pet with the same individual information, and the surgeon is alerted. By automatically reflecting the following information as anesthetic records, the workload of veterinarians and pet owners is reduced, and pre-anesthetic evaluation based on accurate information is performed. For example, the biological information of the pet collected by a home device when the pet is at home before surgery (vital information during home standby, urine volume, feces volume, and toilet visit frequency information, beverage and food intake information, weight information), the biological information of the pet collected by a hospital device when the pet is at the animal hospital before and during surgery (vital information during hospitalization, biological information monitor, drug information during surgery, blood loss information, etc.), the information in the (electronic) medical record of the animal hospital (past anesthesia experience "anesthesia record", medical history, etc.), and the individual information registered by the pet owner in the home display software.

[0147] In addition, as a display item of the system, the information obtained by interviewing may be added. For example, medical history, anesthesia experience (lifestyle information), whether taking any medications, the amount, and the duration of taking them, whether having diarrhea or vomiting, etc.

[0148] In addition to the above, the information of the measuring device for urine volume and feces volume may be used. For example, how much is the appetite and water intake, how much is the urine and feces volume and frequency, whether coughing or the heartbeat is periodically irregular, etc.

[0149] In addition to the above, as individual information, the individual information of the pet registered in the pet owner's home software may be used. For example, animal species, breed, gender, age, temperament, anesthesia history, weight information. These have different anatomical or pharmacological reaction characteristics and may affect the anesthetic drugs and anesthesia methods used. With these information, the attribute values can be classified (normal range, etc.), the specific method of "adjusted attribute value" classification, and the comparative evaluation between the attribute value and the measured value during comparison can be performed. For example, for this individual, since it is within the normal range, it can be evaluated that it is suitable for surgery or has an anesthesia tolerance level.

[0150] In addition to the above, the system may further include a rectal insertion type reflectance pulse oximeter as an inspection device. This pulse oximeter is used during examination. The examination of animals is temporarily performed on the tongue, lips, and ears (at locations without body hair, pigmentation, and with little body movement). Three items, namely rectal temperature, oxygen saturation, and pulse rate, can be simultaneously examined and measured from the rectum. Conventionally, it was a rectal thermometer and did not simultaneously measure oxygen saturation and pulse rate. In contrast, as a system equipped with a pulse oximeter as a separate device from a wearable transmitter (which constantly measures with the tongue during anesthesia) as a monitoring device.

[0151] (Wearable sensor) In addition to the above, as the wearable sensor of other forms, the sensor for acquiring vital data of the target biological individual may use a close-fitting wearable transmitter for the target biological individual, in which a periodic transmission type sensor is attached to a jacket clothing or a harness band that is closely attached around the torso (including the chest, abdomen, and back) (or around the body surface excluding the limbs and neck) of the target biological individual. Also, It may be provided with a torso clothing / harness (shoulder belt) with a rectal temperature estimator based on the amount of change per unit time (first derivative dt) of the skin temperature or the displacement of the amount of change per unit time (second derivative dtdt). As this skin temperature detection sensor, sensing using stretchable fibers may be performed. For example, the skin temperature near the femoral artery (hemorrhage) of the target biological individual is measured, and the estimated rectal temperature is calculated based on the difference between the skin temperature and the outside air temperature.

[0152] In the previous gradation bar, by displaying the frequency of each class according to the shading within the division of the bar of the class, the class with the highest frequency is filled with a high density, and the class with a relatively low frequency is filled with a relatively light density, enabling a gradation distribution within a compact bar-shaped bar. It is also possible to display the daily value bar and the attribute value bar together or switch the display as shown in the lower half of FIG. 33.

[0153] Note that FIG. 25 shows the daily value data of the target biological individual in a gradation display. However, if information on the animal group of the attribute group that has the same attribute as the target biological individual is accumulated, the daily value data for each time zone of this same attribute group is accumulated and stored together with time information as attribute value data (attribute value data obtained by accumulating the daily value data of the same attribute). It is also possible to display the cumulative data value of the accumulated attribute value data as a color bar that bars the frequency (number of data acquisitions) / relative frequency (number of acquisitions in a category / total number of acquisitions) by a gradation-like color change or a change in shading pattern. The mode, upper and lower limits of the same attribute group can be intuitively grasped by the shading.

[0154] Also, the measured value at the current time may be displayed superimposed on the color bar of the same measurement time zone or measurement date zone as the current time.

[0155] FIG. 26 shows the display of the cumulative distribution frequency by side-by-side display for each time zone division of the vertical gradation bar. In this screen, the division display of the distribution bar at 1-hour intervals is shown, and the current value is also displayed side by side on the right.

[0156] FIG. 27 shows the display of the cumulative distribution frequency by side-by-side display for each number of acquisitions using a vertical gradation bar. That is, with the date and time axis as the horizontal axis or the vertical axis, a gradation bar based on the data accumulation of the daily data divided for each number of measurements (for example, every 50 times) is displayed. In this screen, the division display of the distribution bar is performed at intervals of the cumulative data volume, and the current value is displayed on the right. Since body movement times not included in the resting data are not acquired, a difference in acquisition time occurs between the resting time and the body movement time, so the thickness (time axis) of the bar is variable. Note that the shading display of the gradation in the figure is omitted in the figure, but in reality, it is color-coded for each vertical class division and color-coded by gradation density or color. In addition to the display using a gradation bar as shown in FIG. 27, it is also possible to switch and display a variable graph based on the cumulative data divided for each number of acquisitions of the daily data (for example, N count: every 50 times).

[0157] Figure 28 is the management screen 1 in the monitoring state. On this screen, among the list displays of gauges 1 to 4, gauge 1 indicates that floor entry input is in progress, and gauge 4 indicates that it is in a temporary interruption state.

[0158] Figure 29 is the management screen 2 in the monitoring state and during detailed confirmation. On this screen, in the lower half of the screen, the details of the floor entry registration of the selected gauge 1 are displayed. The display in this lower half shows the results of pre-admission interviews and pre-questions when registering in the system, that is, when entering the living body management location. These items are used for the judgment of the population of attribute values. Note that not limited to these items, at the time of floor entry, information such as medical history and characteristics pre-acquired from the nursing information at the time of admission, and individual information such as allergies and personality may be input and displayed.

[0159] In addition, in the upper half of the screen in Figure 29, the vital sign information of gauges 1 to 4 is compressed and displayed. Gauge 4 is in a temporary interruption (a state outside monitoring such as during treatment or meal time)). For example, in the case of an obvious body movement state such as during a walk or a bath, it is set to temporary interruption.

[0160] Figure 30 is the management screen 3 in the monitoring state and during detailed confirmation. On this screen, in the lower half, a trend graph of the vital signs of the selected gauge 2 is displayed. The recent changes in the vital signs of gauge 2 can be confirmed by a variable graph based on the time axis. In addition to zooming in and adjusting the progress graph, switching operations and printing operations can be performed by switching buttons for vital sign types such as epidermal temperature, pulse rate, respiratory rate, and body movement.

[0161] Figure 31 is the management screen 4 in the monitoring state and during detailed confirmation. On this screen, in the lower half, the alert output ([alarm history] in the embodiment) of the selected gauge 2 is displayed in tabular form. It is an enlarged display screen of the history information of the alarm messages of gauge 2, and it is possible to check what abnormal states were detected at what times in the past and when they were cleared. Switching operations and printing operations can be performed using the switching buttons for vital sign types such as skin temperature, pulse rate, respiratory rate, and body movement. By listing the variations in data together with the alert settings, it is possible to detect signs of abnormalities. Based on the cumulative data, it is possible to display gradation bars or color bars side by side for each past measurement time zone along the time axis and to emphasize the alert setting categories. For example, by observing the changes in the amount of variation and the amount of bias of the cumulative values of the data, it is possible to infer abnormalities in animals or sensors due to changes in the variation of the data.

[0162]

[0163]

[0164]

[0165]

[0166] Figure 36 is the operation menu screen 1 in the monitoring state and during operation. On this screen, it is also possible to perform the upper and lower limit setting operations for the alarm of gauge 2. It is determined whether the relative frequency value of the frequency distribution in the cumulative data that displays gradation bars such as in Figures 25, 26, and 33 exceeds any of the preset upper limit values (the lowest division), lower limit values (the highest division), and upper and lower limit values, or whether a value has emerged within the preset upper and lower critical divisions. If it is detected that it has exceeded, an alert output is to be performed. In addition to the above, it may also be determined whether the difference between the average value and the median value and the difference between the upper and lower limits of the cumulative value division are a certain amount or more, and if it is detected that it has exceeded, an alert output may be performed.

[0167] Figure 37 shows the operation menu screen 1 in the monitoring state and during operation. On this screen, it is also possible to set the data acquisition time: data update time interval of the gauge 2. By setting the feeling of the acquisition time of daily data, for example, the number of data acquisitions per hour is determined. Note that since the differences in the acquired data and the data during body movement when the biological individual is moving are not saved and only the resting data is saved, the data at the timing of body movement becomes blank data.

[0168] Figure 38 is a list monitoring screen for two individuals.

[0169] Figure 39 shows the operation menu screen 1 in the monitoring state and during operation. On this screen, the floor entry input operation of the gauge 2 and the display of the matching rate of animals by comparing the past imported image and the current acquired image with a diagnostic card are shown as a percentage such as "95%". To prevent misidentification and for a simple confirmation for relocation within the gauge. It is also possible with nose prints and fingerprints.

[0170] Figure 39 is, that is, the screen when performing the steps of identity detection. In this system, when registering or admitting a target biological individual, it includes the step of automatically recognizing the commonality of the images between the pre-registered photo of the animal (photo at the first examination or pre-submitted registration photo: full body image or nose print) and the current animal at the time of admission (in the case of a microchip-embedded living body, input or automatically recognize the ID information). By recognizing the commonality, the identity of the target biological individual is detected, and if the identity is lacking, an alert for confirming ID number misplacement is displayed. In Figure 39, the current captured video screen (acquired image for face recognition) of the target biological individual and the registered photo of the same biological individual taken in the past are compared and displayed, and the collation result by comparing the two images is shown (the matching rate is 95% in the figure), which is a screen showing the possibility of misidentification of the biological individual. After this title, the current video of the review movie increase is registered as the history of the captured photos, and the photo history is added.

[0171] In addition, separately from the above, a plurality of biological individuals equipped with microchips for each individual are targeted, individual identification is performed using the microchip number, and it is verified whether the individual identification information using the microchip number matches the number of the biological individual set in advance, and an alert may be displayed if the numbers are different (not shown).

[0172] Alternatively, a photograph of the biological individual before bedding is prepared for each individual, and at the time of bedding, the commonality of the image between the photograph of the animal registered in advance and the current animal at the time of bedding is automatically recognized to detect the identity of the diseased animal, and an alert for confirming ID number misplacement may be displayed if the identity is lacking.

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

[0174]

[0175] (Vital Sign Management System for Animals) The present invention is also applicable as a vital sign confirmation system for animals that confirms or manages the vital signs of animals in a predetermined place as an animal vital sign management system (Figs. 1 to 10). For example, a system in which a veterinarian monitors the vital signs of animals in an animal hospital for a long time using a host PC or a mobile terminal, or a system in which the vital signs of animals in an animal hospital can be viewed and confirmed using a mobile terminal or the like. In addition, for example, a system in which a pet owner can view and confirm the vital signs of their pet at home using a mobile terminal or the like, or, furthermore, for example, a system in which a doctor in charge can confirm the vital signs of a human in their home or in a hospital room, or an animal in a storage room or a cage room.

[0176] (Example 1) Example 1 is a system for comprehensively managing the vital signs of a plurality of animals (target animals). Example 1 has the following system configuration (Figs. 1 to 4). A host PC1 that oversees the entire system and manages each vital sign for each target animal (a centralized management PC installed at a data centralized management location such as a hospital or system administrator), a cloud server 2 that stores the data (data server in the figure), a comprehensive installation type sensor 3 that acquires the vital signs of the target animal (the human presence sensor 21 with a ceiling in FIGS. 1 and 3), an individual installation type sensor 4 that acquires the vital signs of the target animal (the floor-mounted infrared camera 23 in FIGS. 1 and 3), and a plurality of wearable sensors 22 to be worn on the target animal (attached to the harness or collar 221 in FIGS. 1 to 5, attached to the body suit 221 in FIG. 12).

[0177] (Example 2) Example 2 is a management system of a host PC. Example 2 is composed of the following system (FIG. 2) A host PC that oversees the entire system and manages each vital sign of the target animal for each target animal, a cloud server 2 that stores the data, a comprehensive installation type sensor (for the entire room) that acquires the vital signs of the target animal, an individual installation type sensor (for the target animal gauge) that acquires the vital signs of the target animal, and a wearable sensor 22 worn on the target animal to acquire vital signs (attached to the harness or collar 221 in FIGS. 1 to 5, attached to the body suit 221 in FIG. 12).

[0178] As a management system for animals in the animal hospital HS including this system, there are the following morphological examples. (1-1) There is a morphological example of a system in which a veterinarian's host PC3 can monitor the vital signs of animals in the animal hospital for a long time. (1-2) There is a morphological example of a system in which a veterinarian's mobile terminal 5 or the like can view and confirm the vital signs of animals in the animal hospital. Alternatively, there is a morphological example of a system in which a pet owner can view and confirm the vital signs of their pet at home using a mobile terminal or the like.

[0179] In addition to the above, there is an example of a lending management system and a reservation management system for equipment in an animal hospital using this system. Specifically, the following are listed. (3-1) A lending system that is used when a veterinarian in an animal hospital lends a vital sign transmitter for use in home animals, animal vital sign confirmation software for remote locations, and a dedicated smartphone to the owner, and can check the lending history and the like. (2) A reservation system that is used when a veterinarian in an animal hospital borrows a vital sign transmitter for use in home animals, animal vital sign confirmation software for remote locations, and a dedicated smartphone from our company. (3) A system that allows a veterinarian in an animal hospital to check the maintenance and repair history of equipment. That is, a system that can analyze, statistically process, and predict the disease state and condition by linking the medical information of the owner and animal registered and edited by the veterinarian with the acquired data. An example of the usage procedure of the animal management system in the animal hospital is shown below. (1) Select "Registration" from the menu button and register the information of the owner and the animal. Complete the setting of the pre-installed terminal and the wearing of the wearable sensor in advance.

[0180] As an example of the device of the present invention · Monitoring camera 21 as an integrated installation type sensor, ROI monitoring camera 23R · Microwave Doppler displacement measuring device 231 (individual installation type sensor 23) or wearable type sensor 22 · IR camera temperature measuring device 232(23) · Laser rangefinder 233(23) It has (Fig. 3).

[0181] The monitoring camera 21 as an integrated installation type sensor monitors the arrangement and situation of the entire room (ward). When the monitoring camera 21 is an ROI monitoring camera 23R having an ROI function, the position of the monitoring target is defined using the ROI function (Fig. 4). In this case, the purpose is to exclude information other than the ROI.

[0182] The wearable sensor 22 includes one or more of a microwave Doppler displacement measuring device, a temperature measuring sensor, an acceleration sensor, and a microphone, and is arranged by being worn on the target animal by a harness-type or collar-type fixture 221.

[0183] For example, the fixture 221 can be composed of a stretchable fiber body garment, and the wearable sensor 22 can be fixed at the abdominal position when the body garment is worn. In this way, when the wearable sensor 22 is worn on the target biological individual (target animal) in a close contact state, the occurrence of duplicate detection errors (contamination) on the wearable sensor 22 is extremely small.

[0184] On the other hand, the individually installed sensor 23 is composed of any one of a microwave Doppler displacement measuring device 231, an IR camera temperature measuring device 232, a laser rangefinder 233, or a composite device combining these, and each device is individually installed near each of the target animals P1, P2, P3... to be measured, or installed and arranged in the cage C of the target animal.

[0185] Among the individually installed sensors 23, the microwave Doppler displacement measuring device 231 detects the pulsation obtained from the entire target animal, and rejects 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 the laser rangefinder 232 in combination. When there is contamination in the distance direction, that is, when some obstacles are mixed between the target animals P1, P2, P3... to be monitored and the detection parts of the respective sensors, the occurrence of contamination is rejected by synchronously analyzing the abnormal detection by the laser rangefinder.

[0187] The details of the occurrence of contamination and the operation of information rejection are described below. (Criteria for the sensor to determine whether it is contamination or the pathological condition of the animal) First, the criteria for the sensor to determine whether it is contamination or the animal's pathological condition will be described.

[0188] The criteria for the sensor to determine whether it is contamination or the animal's pathological condition are determined from the position information (data area RA) automatically set in the ROI of the monitoring camera and the distance to the measured animal by the laser rangefinder in the IR camera unit used for body temperature measurement in the installed sensor.

[0189] When using the installed sensor, it is assumed that the measured animal is within gauge C, and the distance and range that the animal moves are limited to the size range of gauge C. Therefore, the measured value of the laser rangefinder in the installed sensor does not vary greatly.

[0190] (Judgment of contamination occurrence) Next, the judgment of contamination occurrence will be described. When the distance from the installed sensor to the measured animal fluctuates greatly in a short time, or when there are changes such as the distance to the measured animal becoming shorter or longer, it can be judged that animals or humans other than the measured target animal are being measured, and it is judged that contamination has occurred.

[0191] In addition to the above, The reliability level of the data is displayed on the monitoring screen and the data transfer screen to the viewing terminal 4 of veterinarians, etc., from 0 to 100% by AI judgment, and it is characterized by assisting veterinarians.

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

[0193] The fixed-type sensor is advantageous in terms of data volume, transmission frequency, and detecting multiple animals by ensuring a fixed power supply voltage. However, due to limited installation conditions, it cannot be used at home or outdoors. Additionally, there are issues such as limited detection range and limitations in body movement measurement. On the other hand, the wearable sensor is advantageous for trace recording of specific targets and emergency detection through proximity detection while wearing. However, due to non-contact MWD, it has the drawback of being unable to measure during intense movement.

[0194] In contrast, by using a non-contact microwave doppler (MWD) that is inexpensive and enables easy data synchronization and simultaneous measurement, both the fixed-installation type and wearable type sensors can be combined. That is, by synchronizing and storing the detection data from each sensor, namely the fixed power supply type fixed-installation sensor and the battery type wearable sensor, it is possible to complement the data with a sensor that can overcome the limitations of installation conditions, detection range, and body movement measurement. Moreover, this enables batch measurement of multiple animals over a long period of time and improvement of emergency detectability by reducing the error occurrence rate.

[0195] Feature 2: It has the feature of a host computer management type remote data management system using a sensor that solves the following problems.

[0196] The above feature is a method for managing multiple sensor targets under host computer control, which enables centralized control of the operation of each sensor by the host computer instead of the independent operation of each sensor.

[0197] Moreover, the above feature is a method for preventing misidentification of sensor targets or misidentification with other target animals (misidentification with humans), which enables prevention of misrecognition of the sensing target through area setting of the cage space and individual data estimation.

[0198] A system equipped with the above Feature 1 or 2 can be utilized as a management system that automatically transmits data to the owner and hospital through data storage and management on a cloud server.

[0199] (Type of sensor) As a type of sensor in the above management system, in the embodiment, one equipped with a wearable sensor is disclosed. However, only an installed sensor may be used, or a combination of an installed sensor and a wearable sensor may be used. In the case of combined use, the above (A) data complementation serves as an auxiliary point. Note that it may be used in a hospital or at home.

[0200] (Other exemplary forms) In addition to the above, the following exemplary embodiments may be mentioned. Third Embodiment C: Lending management system and reservation management system for equipment in an animal hospital (1) A lending system that can be used when a veterinarian in an animal hospital lends a vital sign transmitter for use with animals at home, animal vital sign confirmation software for a remote location, and a dedicated smartphone to the owner, and can check the lending history, etc. (2) A reservation system that can be used when a veterinarian in an animal hospital borrows a vital sign transmitter for use with animals at home, animal vital sign confirmation software for a remote location, and a dedicated smartphone from our company. (3) A system that allows a veterinarian in an animal hospital to check the maintenance and repair history of equipment.

[0201] Fourth Embodiment D: Systems (4), (5), and (6) using a household pulse oximeter (a device for measuring body temperature, heart rate, blood flow, and SPO2).

[0202] (4) System A, "Remote Consultation System Before Diagnosis and Surgery (Before Arrival at the Hospital)". This remote consultation system, as a "remote consultation system before diagnosis and surgery (before arrival at the hospital)", enables the input or display of consultation content in the consultation mode (pre-operative medical treatment mode), and outputs an input screen and a consultation result list screen to each terminal of medical staff and the biological individual owner. It may also be a registration system on an application that can register photos of biological individuals (affected animals). When an abnormal value of biological information is detected based on the difference between a preset threshold value and the daily value, the automatically selected consultation mode (question list, photo shooting instruction) is automatically activated according to the conditions, and is displayed on the terminal of the owner of the living organism so that it can be input, and the consultation input result can be transmitted to the medical institution. When the input result is received at the consultation medical institution terminal, it is notified by screen display or blinking, etc. Also, based on the risk level of biological information (the magnitude of the difference between the daily value / attribute value), the risk level is automatically determined, and as the consultation mode or emergency mode, based on the determined risk level, the content of the pre-consultation is automatically adjusted according to the preset conditions (automatically select the necessary information for estimating abnormal content by automatically selecting the ABC route of the consultation content).

[0203] For example, using a cumulative data shift graph like the gradient bar in Fig. 25, when the change rates ○%, ●% of the past cumulative data and the most recent cumulative value exceed, start consultation modes A and B respectively, display them on the management terminal and each individual terminal, and the input results can be reflected. Examples of the types of consultation patterns include: large change rate of respiratory rate and heart rate → consultation of the excretory information system, large change rate of body movement → consultation of the surgical factor stem, medium to large change rate of others, appetite, consultation of body temperature / stress factors, etc.

[0204] In this consultation mode, the consultation results transmitted from the terminal of the owner of the biological individual are scrolled and displayed in the lower half of the centralized management screen as shown in Fig. 31, or the consultation results for values with large fluctuations are emphasized and assist-displayed.

[0205] By the owner pre-registering consultation information on the smartphone while waiting at home, the veterinarian can grasp the consultation information in advance. Also, the consultation information necessary for pre-anesthetic evaluation can be obtained in advance. This can be achieved by incorporating a biometric information report + consultation answer app (5-step evaluation screen).

[0206] (5) System B "Medical Appointment System". In the remote monitoring service, by incorporating the daily record mode and the emergency mode, when the veterinarian determines that a visit to the hospital is necessary, the veterinarian contacts the owner and explains the urgency and severity regarding the condition of the pet and confirms whether a visit to the hospital is possible.

[0207] As the daily record mode (diary mode, postoperative progress mode), it is possible to incorporate a management screen for biometric information before and after injection, such as the photographed images in Fig. 32 and the biometric information graph in Fig. 33. The owner can also check the time slots when the hospital can provide medical treatment from the home software and make a medical appointment. The veterinarian can track the GPS signal of the owner's smartphone from the hospital software to confirm the scheduled arrival time at the hospital and whether the owner is on the way to the hospital, etc.

[0208] When alert output information is detected by the system, in the emergency mode, it is also possible to start the emergency medical treatment mode in case of an emergency. In the emergency mode, data linkage with the night hospital is performed.

[0209] (6) System C "Remote Inspection Service System". Adjust the drug administration schedule based on the daily vital sign data obtained during home life. (This is a factor for judging the progress of the disease). Also, as the daily record mode (diary mode) for the obtained biometric information of daily life, a screen that displays three measurement items within the calendar list, captures photos of the affected animal and the affected part, and can link the diary mode with the biometric information. It can also be a system for remotely managing biometric information through the linkage between the owner's terminal and the terminal for medical staff. In this system, an emergency alert is issued as in B above, and a communication line with the veterinarian is opened.

[0210] In the case of cases where medical treatment is carried out without surgery, the owner has to deal with the illness in daily life for a long time. In the case of heart or lung diseases, the owner must ensure that the pet takes the medicine, go to the hospital immediately in case of acute exacerbation, and the veterinarian needs to collect information including the situation at home in order to check the pet's condition and adjust the type and amount of medicine. The owner is worried about the pet's anesthesia, surgery, and physical condition after discharge. Therefore, a system that can perform in-home examinations of pets during their daily life for medical treatment is provided.

[0211] As the night mode / remote management mode in FIG. 34, at night, the emergency notification alert of the management terminal is muted, and it switches to a mode of remotely notifying by monitoring with a viewer from a pre-registered mobile terminal.

[0212] Fourth Embodiment Other than the Above: A system that can analyze, statistically process, and predict the disease state and condition by linking the medical information of the owner and the animal registered and edited by the veterinarian with the acquired data.

[0213] Fifth Embodiment: An 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 vary the display content according to the user of the mobile terminal (doctor, nurse, owner). D2. A function to assist in telemedicine and emergency measures using communication with the MWD sensor. D3. A function to detect group infections in the hospital (collective accommodation area), and a monitoring alert function for home use. D4. A function to start the linkage of communication application software at the time of an alert and notify by automatic line connection.

[0214] Sixth Embodiment: A sensor system that is utilized for regional animal information management, insurance review information for animals, and preventive vaccination management.

[0215] Regarding the problem of wearing detection, tongue, piercing, or papilla detection has high accuracy, but there is a problem that it cannot be measured constantly due to measurement errors caused by body hair. In contrast, since it becomes possible to measure temporarily by wetting the body hair with saline, the harness equipped with the wearable sensor may be equipped with a saline spray function for wetting the body hair with saline in a part thereof.

[0216] (Device example of the present invention) As an example of the device of the present invention, the following is presented. · Monitoring camera 21 as an integrated installation type sensor, ROI monitoring camera 23R · Microwave Doppler displacement measuring device 231 (individual installation type sensor 23) or wearable type sensor 22 · IR camera temperature measuring device 232(23) · Laser rangefinder 233(23)

[0217] The monitoring camera 21 as the integrated installation type sensor described above checks the arrangement of the entire room (hospital room) and monitors the situation. When the monitoring camera 21 is an ROI monitoring camera 23R having an ROI function, the position of the monitoring target is defined using the ROI function (Fig. 4). In this case, the purpose is to exclude information other than the ROI.

[0218] The wearable type sensor 22 includes one or more of a microwave Doppler displacement measuring device, a temperature measuring sensor, an acceleration sensor, and a microphone, and is arranged by dressing the target animal with a harness type or collar type fixture.

[0219] When the wearable type sensor 22 is dressed, the occurrence of duplicate detection errors (contamination) on the wearable type sensor 22 is extremely small.

[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 Terminal 4A Data Confirmation Software 5 Viewing Management Terminal 5A Data Management Software C Cage P1, P2, P3, ··· Target Organisms (Target Animals) RA, RA11, RA12 ··· Data Areas

Claims

1. A system for acquiring and managing data of vital signs including at least one or more of the pulse rate, respiratory rate, and body temperature of a biological individual of a subject including a human as information on the life activities of the subject biological individual, comprising a vital sign sensor and a transceiver attached to the subject biological individual, a server for storing the transmitted and received data, a processing device for processing the data of the server, and an output device for outputting the processing content, the step of continuously or intermittently acquiring vital sign data of the biological individual by a sensor directly attached to or / and a fixedly installed sensor of the subject biological individual and storing it in a server, the step of extracting, by the processing device, data of a resting state determined to be in a resting state by satisfying a predetermined set condition from the stored vital sign data, and statistically processing a data group of the resting state of the subject biological individual over a predetermined period as daily value data, for the subject biological individual, the step of displaying while updating at any time the vital sign data of the current time to the most recent time for each of the subject biological individuals, and displaying in parallel or superimposing with the daily value data over a predetermined time or period, characterized in that a comparison result between each value of the current vital sign data of the subject biological individual and the statistically processed daily value data of the resting state is output, a biological information management system.

2. the step of acquiring vital sign data of the biological individual at regular time intervals by the sensor directly attached to or / and the fixedly installed sensor of the subject biological individual and storing it together with the acquired time and information of the biological individual, the step of extracting data of a resting state from the vital sign data of the subject biological individual, performing normal distribution processing on the data of the resting state over a predetermined period, and creating and storing normal distribution data in the resting state over a predetermined period up to the most recent time, the step of creating at least one or more data selected from the upper limit value, lower limit value, average value or central value, and standard deviation in the normal distribution data of each acquired time, and storing it as cumulative value data, the step of performing a numerical comparison between the vital sign data at the current time to the most recent time and the data of any of the steps, and displaying and storing the comparison result, Performing in sequence the steps of displaying in parallel or in an overlapping manner the real-time display of the current vital sign data for each biological individual of the target and the comparative display of the daily value data over a period of a predetermined length or more. The biological information management system according to claim 1, characterized in that a comparison result is displayed of how much the vital sign or the calculated value based thereon of the biological individual of the target at the current time or the most recent time deviates from the cumulative value data of the biological individual of the target.

3. In the extraction of the data in the resting state, a determination of introduction from the active state to the resting state and a determination of introduction from the resting state to the active state are made based on whether the amount of change per unit time of the temperature change, i.e., the amount of change of the slope, is below or above a threshold value, or whether there is an inflection point, and the resting state is detected based on these introduction determination times and whether the skin temperature exceeds the threshold value. The biological information management system according to claim 1.

4. The step of setting a predetermined attribute group to which the biological individual of the target belongs. The step of storing the vital sign data of the predetermined attribute group in a server. The step of extracting, by a processing device, the daily value data of the predetermined attribute group from the server and statistically processing the group attribute value data of the predetermined attribute group under specific conditions. By performing the steps of displaying in parallel or in an overlapping manner the real-time display of the current to most recent vital sign data for each biological individual of the target and the group attribute value data of a predetermined condition of a predetermined attribute group including the biological individual of the target over a period of a predetermined length or more. The biological information management system according to claim 1, characterized in that a comparison result is output between each value of the current vital sign data of the biological individual of the target and the statistically processed attribute value data of the resting state of the attribute group including the biological individual of the target.

5. The step of statistically processing the excepted attribute value data, which is a group of daily value data of a plurality of biological individuals in the attribute group to which the biological individual of the target belongs and excludes the daily value data of the biological individual of the target. The biological information management system according to claim 3, characterized in that the daily value data of the biological individual of the target is compared with the excepted attribute value data, which is the attribute group of the biological individual and excludes the daily value data of the biological individual, and the comparison result is output.

6. Further comprising a step of setting hospitalization information or visit information to a hospital or facility for a predetermined symptom of a target biological individual, The biological information management system according to claim 1, characterized in that it outputs separately from the data at the time of hospitalization or visit and the data at home.

7. Further comprising a step of recording, as record data, daily value data that satisfies a predetermined healthy determination condition among the daily value data of the target biological individual in a resting state, excluding data on the occurrence time of a specific symptom including the preoperative or postoperative period, and outputting a comparison result between the vital sign data of the target biological individual and the daily value data of the healthy state. The biological information management system according to claim 1.

8. The biological information management system according to claim 1, characterized in that it determines whether the transmission data exceeds a preset upper limit value, lower limit value, and average value, and outputs an alert when it detects that the value has been exceeded.

9. The sensor for acquiring the vital data of the target biological individual is a wearable transmitter in which the sensor is attached to a jacket wearing garment or a harness band that is always worn in close contact with the torso of the target biological individual. The biological information management system according to claim 1.

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

11. Save the data at rest as cumulative data of daily value data together with time information, The frequency distribution or relative frequency distribution of the cumulative data values of the daily value data cumulatively stored as time information for a predetermined time zone is displayed as a linear bar-shaped gradient bar in which the class values are represented in the bar length direction as sections of a certain length, and the frequency of each class value dividing the gradient bar is displayed by a change in color or a change in shading pattern. The biological information management system according to claim 1.

12. Cumulatively save the daily value data for each time zone of a group of biological individuals in the same attribute group as the target biological individual as cumulative data of attribute value data (attribute value data obtained by cumulating the daily value data of the same attribute) together with time information, The biological information management system according to claim 1, characterized in that the cumulative data value of the cumulative attribute value data is displayed as a gradient bar in which the frequency / relative frequency is bar-divided by a gradient-like color change or a change in shading pattern.

13. The biological information management system according to claim 11, characterized in that a plurality of the gradient bars based on the cumulative data of the daily data, divided for each predetermined measurement time or measurement time zone with the date and time axis as the horizontal axis or the vertical axis, are displayed in parallel for each division of the measurement time zone.

14. The biological information management system according to claim 11, characterized in that a gradient bar based on cumulative data divided for each number of acquisitions of daily data with the date and time axis as the horizontal axis or the vertical axis is displayed.

15. In the relative frequency of the frequency distribution in the cumulative data for displaying the gradient bar, it is determined whether the frequency of each class exceeds any of a preset upper limit value, lower limit value, and upper and lower limit values, and whether a value appears within a preset upper and lower critical division, and when it is detected that the limit has been exceeded, an alert output is performed. The biological information management system according to claim 11.

16. In the frequency distribution in the cumulative data for displaying the gradient bar, it is determined whether any of the difference between the average value and the median value, or the maximum difference between the upper and lower limit classes, exceeds a preset lower limit value, and when it is detected that the limit has been exceeded, an alert output is performed. The biological information management system according to claim 11.

17. The biological information management system according to claim 1, characterized in that a plurality of biological individuals equipped with microchips for each individual are targeted, individual identification is performed using the microchip number, and it is verified whether the individual identification information using the microchip number matches a preset number of the biological individual, and when the numbers are different, an alert is displayed.

18. For each individual, an imaging photo or a filmed video of the biological individual before admission is prepared, and at the time of admission, the commonality between the pre-registered imaging photo or filmed video of the animal and the imaging photo or filmed video of the current animal at the time of admission is automatically recognized to detect the identity of the diseased animal, and when the identity is lacking, an ID number misplacement confirmation alert is displayed. The biological information management system according to claim 1.

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