Vital data evaluation method, vital data evaluation device, vital data evaluation system and program

Abstract

To provide a vital data evaluation method for facilitating determination close to those of skilled medical professionals regarding patients' conditions.SOLUTION: A vital data evaluation method includes: acquiring a first vital data set corresponding to a patient's first vital data of a first type; acquiring a second vital data set corresponding to the patient's second vital data of a second type different from the first type; generating first vital data function information on the basis of the first vital data set; generating second vital data function information on the basis of the second vital data set; and generating patient condition information for estimating a condition of the patient on the basis of a relation between the first vital data function information and the second vital data function information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a vital data evaluation method, a vital data evaluation device, a vital data evaluation system, and a program. [Background technology]

[0002] Vital sign data, which is the digitalized version of "vital signs" that indicate a person is alive, is widely used in medical settings and daily health management. For example, in medical settings, vital data such as pulse rate, blood pressure, body temperature, and respiratory rate are recorded.

[0003] Furthermore, Patent Document 1 discloses an example in which electrocardiogram data and pulse wave data are acquired and processed to calculate the heart rate. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-220175 Summary of the Invention [Problem to be solved by the invention]

[0005] In medical settings, vital signs are often measured over time. In these cases, medical professionals understand the patient's condition based on the transitions and trends of multiple vital signs and provide medical care. However, it is difficult for medical professionals to constantly monitor the same patient and keep track of the patient's condition.

[0006] One of the objects of the present invention is to easily make judgments about the condition of a patient that are similar to those of an experienced medical professional. [Means for solving the problem]

[0007] According to one embodiment of the present invention, there is provided a vital data evaluation method including: acquiring a first vital data set corresponding to a first type of first vital data of a patient; acquiring a second vital data set corresponding to a second type of second vital data of the patient that is different from the first type; generating first vital data function information based on the first vital data set; generating second vital data function information based on the second vital data set; and generating patient condition information for estimating the condition of the patient based on a relationship between the first vital data function information and the second vital data function information.

[0008] In the above vital data evaluation method, first vital data derivative information may be generated based on the first vital data function information, second vital data derivative information may be generated based on the second vital data function information, and the patient condition information may be generated based on the first vital data derivative information, the second vital data derivative information, and a patient condition data set corresponding to a relationship between the first vital data derivative information and the second vital data derivative information.

[0009] In the above vital data evaluation method, the first vital data derivative information and the second vital data derivative information may be generated when at least one of the first vital data function information and the second vital data function information satisfies a predetermined condition.

[0010] In the vital data evaluation method, care information regarding care to the patient may be generated based on a care information dataset associated with the patient condition information.

[0011] In the above vital data evaluation method, severity information may be generated based on at least one of the first vital data function information and the second vital data function information, and the correspondence information may be generated based on the severity information and the patient condition information.

[0012] In the vital data evaluation method, warning information may be generated when at least one of the first vital data function information and the second vital data function information satisfies a predetermined condition.

[0013] In the vital data evaluation method, first identification information associated with the first vital data derivative information and second identification information associated with the second vital data derivative information may be output.

[0014] In the vital data evaluation method, the first identification information may be information that allows visual recognition of a transition in the first vital data, and the second identification information may be information that allows visual recognition of a transition in the second vital data.

[0015] In the above vital data evaluation method, when generating at least one of the first vital data function information and the second vital data function information, a basis function to be applied may be selected from a plurality of basis functions based on at least one of information about the patient and external information associated with the patient.

[0016] In the above vital data evaluation method, the patient condition information may be generated by applying the first vital data function information and the second vital data function information to a machine learning model generated in advance.

[0017] In the vital data evaluation method, the machine learning model may correspond to a shape pattern of first vital data function information and second vital data function information.

[0018] According to one embodiment of the present invention, there is provided a program for causing a computer to execute the vital data evaluation method.

[0019] According to one embodiment of the present invention, there is provided a vital data evaluation device including a control unit that acquires a first vital data set corresponding to a first type of vital data of a patient, acquires a second vital data set corresponding to a second type of vital data different from the first type of vital data of the patient, generates first vital data function information based on the first vital data set, generates second vital data function information based on the second vital data set, and generates patient condition information that estimates the condition of the patient based on a relationship between the first vital data function information and the second vital data function information.

[0020] In the above vital data evaluation device, the control unit may generate first vital data derivative information based on the first vital data function information, generate second vital data derivative information based on the second vital data function information, and generate the patient condition information based on the first vital data derivative information, the second vital data derivative information, and a patient condition data set corresponding to a relationship between the first vital data derivative information and the second vital data derivative information.

[0021] In the above vital data evaluation device, the control unit may generate the first vital data derivative information and the second vital data derivative information when at least one of the first vital data function information and the second vital data function information satisfies a predetermined condition.

[0022] In the vital data evaluation device, the control unit may generate treatment information regarding treatment for the patient based on a treatment information dataset associated with the patient condition information.

[0023] In the above vital data evaluation device, the control unit may generate severity information based on at least one of the first vital data function information and the second vital data function information, and may generate the correspondence information based on the severity information and the patient condition information.

[0024] In the vital data evaluation device, the control unit may generate warning information when at least one of the first vital data function information and the second vital data function information satisfies a predetermined condition.

[0025] In the vital data evaluation device, the control unit may output first identification information associated with the first vital data derivative information and second identification information associated with the second vital data derivative information.

[0026] In the vital data evaluation device, the first identification information may be information that allows visual recognition of a transition of the first vital data, and the second identification information may be information that allows visual recognition of a transition of the second vital data.

[0027] In the above vital data evaluation device, when generating at least one of the first vital data function information and the second vital data function information, the control unit may select an applicable basis function from a plurality of basis functions based on at least one of information about the patient and external information associated with the patient.

[0028] In the above vital data evaluation device, the control unit may generate the patient condition information by applying the first vital data function information and the second vital data function information to a machine learning model generated in advance.

[0029] In the vital data evaluation device, the machine learning model may correspond to a shape pattern of first vital data function information and second vital data function information.

[0030] According to one embodiment of the present invention, there is provided a vital data evaluation system including a control unit that acquires a first vital data set corresponding to a first type of vital data of a patient, acquires a second vital data set corresponding to a second type of vital data different from the first type of vital data of the patient, generates first vital data function information based on the first vital data set, generates second vital data function information based on the second vital data set, and generates patient condition information that estimates the condition of the patient based on a relationship between the first vital data function information and the second vital data function information. [Effects of the Invention]

[0031] According to the present invention, judgments on the condition of a patient can be easily made that are close to those of an experienced medical professional. [Brief explanation of the drawings]

[0032] [Figure 1] 1 is a diagram illustrating a vital data evaluation system according to an embodiment of the present invention. [Figure 2] FIG. 1 is a diagram illustrating the hardware configuration of each device constituting a vital data evaluation system according to an embodiment of the present invention. [Figure 3] FIG. 2 is a diagram illustrating the software configuration of a control unit of a vital data evaluation server in one embodiment of the present invention. [Figure 4] FIG. 2 is a diagram showing a basis function data table in one embodiment of the present invention. [Figure 5] FIG. 10 is a diagram showing a vital sign-basis function data table in one embodiment of the present invention. [Figure 6] FIG. 10 is a diagram showing a patient condition information data table in one embodiment of the present invention. [Figure 7] FIG. 10 is a diagram showing a correspondence information data table according to an embodiment of the present invention. [Figure 8] FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 9]FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 10] FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 11] FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 12] FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 13] 4 is an example of first vital data acquired in one embodiment of the present invention. [Figure 14] 10 is an example illustrating a conformance state of a function model in one embodiment of the present invention. [Figure 15] 1 is an example of a GCV graph according to an embodiment of the present invention. [Figure 16] 10 is an example of vital data function information and vital data derivative information. [Figure 17] FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 18] FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 19] FIG. 10 is a diagram showing a correspondence information data table according to an embodiment of the present invention. [Figure 20] FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 21] 10 is a transition marker table of vital data function information in one embodiment of the present invention. [Figure 22] FIG. 2 is a flowchart showing a vital evaluation process of the vital data evaluation system according to one embodiment of the present invention. [Figure 23] FIG. 1 is a flow diagram illustrating a method for generating a machine learning model in one embodiment of the present invention. [Figure 24]1 is an example of a function shape pattern according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0033] The following embodiments are merely examples of the present invention, and the present invention is not limited to these embodiments. In the drawings referred to in this embodiment, the same or similar reference numerals are used to designate the same parts or parts having similar functions, and repeated explanations thereof may be omitted.

[0034] First Embodiment The vital data evaluation system according to this embodiment will be described in detail with reference to the drawings.

[0035] (1-1. Overall configuration of vital data evaluation system) FIG. 1 is a diagram illustrating a vital data evaluation system 1 according to this embodiment. The vital data evaluation system 1 includes a vital data evaluation device 10, a first vital data measurement device 20-1, a second vital data measurement device 20-2, and a terminal device (external device) 40. When it is not necessary to distinguish between the first vital data measurement device 20-1 and the second vital data measurement device 20-2, they will be described as a vital data measurement device 20. In this example, one each of the first vital data measurement device 20-1 and the second vital data measurement device 20-2 is provided, but the present invention is not limited to this. As will be described later, multiple vital data measurement devices may be used when measuring one type of vital data.

[0036] A database 50 is connected to the vital data evaluation device 10. In Fig. 1, the vital data evaluation device 10, the first vital data measurement device 20-1, the second vital data measurement device 20-2, and the terminal device 40 are connected to a network NW. The network NW is a communication network such as the Internet or an intranet, and an appropriate network is used depending on the communication environment.

[0037] According to the vital data evaluation system 1, two types of vital data are measured using two types of vital data measurement devices 20, and a function (vital data function information) of each vital data over a certain period of time can be generated. In this embodiment, the two types of vital data used are systolic blood pressure data and heart rate data measured during surgery under general anesthesia. Furthermore, the vital data evaluation device 10 generates patient condition information that estimates the patient's condition based on the relationship between the two types of vital data function information, and also generates correspondence information for treating the patient. The generated function information, patient condition information, and correspondence information are displayed on the vital data evaluation device 10 (or terminal device 40). The configuration of the vital data evaluation system 1 for realizing such processing will be described below.

[0038] (1-2. Hardware configuration) FIG. 2 is a diagram illustrating the hardware configuration of each device that constitutes the vital data evaluation system 1.

[0039] (1-2-1. Vital Data Evaluation Device 10) The vital data evaluation device 10 includes a control unit 11, a storage unit 12, a communication unit 13, a display unit 14, and an operation unit 15. The vital data evaluation device 10 may be an on-premise server, a cloud server, or other processing device. The control unit 11 is an example of a computer including an arithmetic processing circuit such as a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array). The control unit 11 executes programs stored in the storage unit 12 to realize various functions in the vital data evaluation device 10. This allows the vital data evaluation device 10 to perform processing (vital data evaluation processing) in the vital data evaluation system 1.

[0040] The storage unit 12 includes a storage device and stores a control program. The storage unit 12 also stores various data used when the control program is executed. The program may be provided in a state recorded on a computer-readable recording medium such as a magnetic recording medium, an optical recording medium, a magneto-optical recording medium, or a semiconductor memory. In this case, the vital data evaluation device 10 only needs to include an interface for connecting the recording medium. Here, the storage medium may be defined as a medium separate from the storage unit 12 included in the vital data evaluation device 10, or may be a medium used for the storage unit 12.

[0041] The communication unit 13 includes a communication module, and connects to the network NW under the control of the control unit 11 to transmit and receive information to and from other devices connected to the network NW. In this example, the communication unit 13 also connects to a database 50 to transmit and receive information. The information registered in the database 50 will be described later. The communication unit 13 may be connected to the database 50 via the network NW. The information registered in the database 50 may also be stored in the storage unit 12. In this case, the database 50 may not exist.

[0042] The display unit 14 includes a display device whose display content is controlled by the control unit 11. The operation unit 15 may include a keyboard, switches, a handle, etc., and outputs information corresponding to operations to the control unit 21.

[0043] In addition to the above configuration, the vital data evaluation device 10 may have other components such as an audio output unit and a light emitting unit.

[0044] (1-2-2. Vital Data Measuring Device 20) Vital data measurement device 20 includes control unit 21, storage unit 22, communication unit 23, display unit 24, operation unit 25, and measurement unit 26. Control unit 21 has a configuration basically similar to that of control unit 11 described above, and realizes various functions in vital data measurement device 20. This allows processing in vital data measurement device 20 in vital data evaluation system 1 to be executed. The measured vital data may be stored in storage unit 22 via control unit 21.

[0045] The storage unit 22 has a configuration basically similar to that of the storage unit 12, with the only difference being the contents of the program instructions stored therein, and therefore a description thereof will be omitted. The communication unit 23 has a configuration basically similar to that of the communication unit 13, with the only difference being the connectable networks, and therefore a description thereof will be omitted.

[0046] Display unit 24 has a configuration basically similar to that of display unit 14, and can display acquired vital data. Operation unit 25 has a configuration similar to that of operation unit 15, and the only difference is the content of the operations, so a description thereof will be omitted.

[0047] The measurement unit 26 is used to measure vital data of a patient. The measurement unit 26 may measure the vital data invasively or non-invasively.

[0048] (1-2-4. Terminal device 40) The terminal device 40 is configured as at least one of a desktop PC (personal computer), a notebook PC, a mobile phone, a smartphone, a tablet terminal, and other electronic application devices. The terminal device 40 can function as a client. The terminal device includes a control unit 41, a storage unit 42, a communication unit 43, a display unit 44, and an operation unit 45. The control unit 41 has a configuration basically similar to the above-mentioned control unit 11, and realizes various functions in the terminal device 40. The control unit 41 executes processing in the terminal device 40 in the vital data evaluation system 1.

[0049] The storage unit 42 has a configuration basically similar to that of the storage unit 12, with the only difference being the contents of the program instructions stored therein, and therefore a description thereof will be omitted. The communication unit 43 has a configuration basically similar to that of the communication unit 13, with the only difference being the connectable networks, and therefore a description thereof will be omitted.

[0050] The display unit 44 includes a display device whose display content is controlled by the control unit 41. The operation unit 45 includes a touch sensor in this example, and outputs information corresponding to the position operated by a user (e.g., a medical professional) to the control unit 41. This touch sensor is provided on the display area of ​​the display unit 44. That is, the display unit 44 and the operation unit 45 form a touch panel. Note that the touch panel may also be used in the vital data evaluation device 10 and the vital data measurement device 20.

[0051] (1-3. Software configuration of the vital data evaluation device) 3 is a diagram showing the software configuration of the control unit 11 of the vital data evaluation device 10. The control unit 11 includes an acquisition unit 11a, a data preprocessing unit 11b, a generation unit 11c, an analysis unit 11d, and an output instruction unit 11e.

[0052] The acquisition unit 11a has a function of acquiring various information from each device. In this example, vital data is stored in a vital database (DB) 50a of the database 50. Function information is stored in a function information database (DB) 50b. Patient condition information is stored in a patient condition information database (DB) 50c. Correspondence information is stored in a correspondence information database (DB) 50d.

[0053] The data preprocessing unit 11b has a function of excluding (preprocessing, cleaning) data that meets predetermined conditions from the acquired log data. In this example, the data preprocessing unit 11b excludes data that exceeds a preset range.

[0054] The analysis unit 11d has a function of analyzing the condition of the patient using the generated vital data function information.

[0055] The generator 11c has a function of generating various types of information. In this embodiment, function information is generated using the acquired vital data. In this example, a fitting curve is generated using a function model that best fits a vital data set in which vital data for a certain period are arranged in chronological order. The generator 11c also generates patient condition information based on the relationship between two types of vital data function information, based on the analysis results. Furthermore, the generator 11c generates response information for proposing a response method based on the patient condition information.

[0056] The output instruction unit 11e has a function of instructing the output of the patient condition information and the corresponding information. In this example, the output instruction unit instructs the display unit 14 to display the patient condition information and the corresponding information, or instructs the terminal device 40 to output the patient condition information and the corresponding information.

[0057] (1-4. Various tables) Next, various data tables used in the vital data evaluation system 1 will be described.

[0058] (1-4-1. Basis function data table) FIG. 4 shows a basis function data table 100. The basis function data table 100 and the vital sign-basis function data table 110 are stored in a function information database (DB) 50b. The basis function data table 100 includes basis function (type name) information 101 and feature information 103. The basis function data table 100 includes basis functions that have been prepared in advance. In the basis function data table 100, basis functions can be added or modified as appropriate.

[0059] (1-4-2. Vital Signs - Basis Function Data Table) FIG. 5 shows a vital sign-basis function data table 110. The vital sign-basis function data table 110 is stored in a function information database (DB) 50b. The vital sign-basis function data table 110 includes vital sign (type name) information 111 and basis function (type name) information 113. In this embodiment, a basis function to be used may be associated with each vital sign. In this example, when the vital sign is "systolic blood pressure," a B-spline is associated as the basis function (model) for generating function information. The vital sign-basis function data table 110 can be updated as appropriate. In the case of a function model that does not require a basis function, there is no need to select a basis function.

[0060] (1-4-3. Patient condition data table) 6 shows a patient condition data table 200. The patient condition data table 200 includes first vital data derivative information (f1') 201, first identification information 201m, second vital data derivative information (f2') 203, second identification information 203m, and patient condition information 205. The patient condition data table 200 shows patient condition information based on the relationship between first vital data derivative information f1' generated from the first vital data function information and second vital data derivative information f2' generated from the second vital data function information. For example, when the first vital data function information f1' is negative (-) (decreased systolic blood pressure) and the second vital data function information f2' is positive (+) (increased heart rate), the patient condition information "circulating plasma volume deficiency" is associated.

[0061] (1-4-4. Correspondence information data table) 7 shows a corresponding information data table 300. The corresponding information data table 300 includes patient condition information 301 and corresponding information 303. The corresponding information data table 300 shows corresponding information associated with patient condition information. In this example, the corresponding information "infusion or blood transfusion" is associated with the patient condition information "circulating plasma volume insufficiency."

[0062] (1-5. Vital Data Evaluation Processing) Next, a description will be given of the vital data evaluation process implemented in the vital data evaluation system of this embodiment. Figures 8 to 12 are flow charts showing the vital data evaluation process of the vital data evaluation system 1 of this embodiment.

[0063] (1-5-1. Acquisition of first vital data and second vital data) 8, the vital data evaluation device 10 generates vital data measurement instruction information (step S101). For example, the vital data evaluation device 10 may generate the vital data measurement instruction information when it receives a vital data measurement request from the terminal device 40 or another vital data measurement request. The vital data evaluation device 10 transmits the vital data measurement instruction information to the first vital data measurement device 20-1 and the second vital data measurement device 20-2 (steps S103, S105).

[0064] Based on the vital data measurement instruction information, the first vital data measurement device 20-1 measures one type of first vital data. In this example, the first vital data measurement device measures systolic blood pressure (mmHg) (step S107). At this time, the first vital data measurement device may measure for a predetermined period of time, or may continuously acquire data until an instruction to end measurement is received. Alternatively, the first vital data measurement device may measure data based on instructions (information) directly input to an individual vital data measurement device, rather than based on vital data measurement instruction information. The measured first vital data is transmitted to the vital data evaluation device 10 as a data set arranged in chronological order (step S109), and the vital data evaluation device 10 acquires the first vital data (step S111). The acquired first vital data (data set) is stored in the vital DB 50a. FIG. 13 shows an example of the acquired first vital data set. 13, the acquired first vital data (data set) may be a discrete data set (scatter plot) with time (minutes) on the horizontal axis and systolic blood pressure on the vertical axis. In this example, the vital data is data acquired every minute.

[0065] Similarly, based on the vital data measurement instruction information, the second vital data measurement device 20-2 measures second vital data (a second type) that is different in type from the first vital data. In this example, the second vital data measurement device 20-2 measures the heart rate (bpm) (step S113). At this time, the second vital data measurement device 20-2 may measure for a predetermined period or may continuously acquire data until an instruction to end measurement is received. Alternatively, the second vital data measurement device 20-2 may measure based on instructions (information) directly input to an individual vital data measurement device, rather than based on the vital data measurement instruction information. The measured second vital data is transmitted to the vital data evaluation device 10 as a data set arranged in chronological order (step S115), and the vital data evaluation device 10 acquires the second vital data (data set) (step S117). The acquired first vital data set and the acquired second vital data set correspond in time period. Specifically, this means that there are a first vital data set and a second vital data set in a specific period such as from 10:00 to 11:00.

[0066] (1-5-2. Preprocessing of vital data) Next, as shown in FIG. 9, the vital data evaluation device 10 preprocesses the vital data. First, the vital data evaluation device 10 preprocesses the acquired first vital data. In this example, data outside a preset numerical range is removed (cleaned) from the first vital data set (step S201). Because the first vital data may be measured at predetermined time intervals, the first vital data set is discrete time-series data. When generating function information, if the acquired first vital data set is directly applied to a function model, it will be strongly influenced by outliers. However, in this embodiment, by performing the above-described preprocessing, the first vital data function information can be generated accurately or easily (or quickly). The preprocessed first vital data set may be stored in the vital DB 50a. At this time, the first vital data set before preprocessing may be deleted from the vital DB 50a.

[0067] Next, the vital data evaluation device 10 preprocesses the acquired second vital data. In this embodiment, similar to the first vital data, second vital data that exceeds a preset range is excluded (cleaned) from the acquired second vital data set (step S203). The preprocessed second vital data set may be stored in the vital DB 50a. At this time, the preprocessed second vital data set may be deleted from the vital DB 50a.

[0068] (1-5-3. Generating function information) Next, as shown in Fig. 10, the vital data evaluation device 10 generates vital data function information using the vital data set. First, the vital data evaluation device 10 generates first vital data function information (step S301). Fig. 11 is a flowchart for generating the first vital data function information.

[0069] In FIG. 11 , first, the vital data evaluation device 10 generates a function model for the first vital data set (step S3011). When generating the function model, a basis function to be used is selected from a plurality of basis functions prepared in advance, as shown in the data table of FIG. 4 . In this example, the B-spline, Fourier, polygonal basis, polynomial basis, and constant basis are used as the basis functions. The B-spline is characterized by its ease of use. The Fourier function is composed of sine and cosine functions and is characterized by its ease of use when there is periodicity, such as diurnal variation. The polygonal basis is recommended when the purpose is function regression. The polynomial basis is characterized by its ability to fit well to the center of the data but not to fit well to the tails. The constant basis is characterized by its ability to fit well to data that does not change over time. Note that other basis functions may also be used as the basis function. Alternatively, an autoregressive function or a moving average function that does not use a basis function may be used. The basis function or function model may be selected based on information about the target vital data, patient information, or external information associated with the patient (e.g., environmental information). In this embodiment, the basis function to be used may be set in advance depending on the type of vital sign. For example, in this embodiment, as shown in FIG. 5, a B-spline is selected as the basis function for the vital data of systolic blood pressure.

[0070] Next, the vital data evaluation device 10 analyzes and evaluates the fitness of the generated function model by model validation (step S3013). In this example, when a function model is generated by selecting B-spline as a basis function, the Generalized Validation may be performed using Cross Validation (GCV). The formula used for GCV (Formula 1) is shown below. In GCV evaluation, a function model is input into Formula 1. At this time, the smaller the GCV value, the higher the fitness of the function model.

number

[0071] Figure 14 shows an example of a generated function model. In Figure 14, the upper left shows the function model when log(λ) = -1, the upper right shows log(λ) = 0, the lower left shows log(λ) = 3, and the lower right shows log(λ) = 5.

[0072] Fig. 15 is a graph for evaluating a function model, with the horizontal axis representing log(λ) and the vertical axis representing the GCV value. From Fig. 15, it can be seen that the GCV takes the minimum value when log(λ) = 3. As a result, the function model with log(λ) = 3 using B-splines as basis functions is selected as the optimal function model (step S3015).

[0073] Finally, the vital data evaluation device 10 generates first vital data function information by fitting the first vital data set using the above-mentioned optimal function model (in this example, log(λ) = 3 is set using B-spline as the basis function) (step S3017) (see the left diagram in Figure 16: circles are the first vital data set, solid lines are the first vital data function information, triangles are the second vital data set, and dashed lines are the second vital data function information).

[0074] Next, the vital data evaluation device 10 generates second vital data function information for the second vital data set (step S303). The method for generating the second vital data function information is generally similar to that for the first vital data function information, and therefore, description thereof will be omitted.

[0075] In one embodiment of the present invention, the vital data evaluation device 10 may adjust a penalty term when evaluating a function model. The penalty term represents a constraint on the parameters of the function model and improves the generalization performance of the function model. Examples of the penalty term include L1 regularization (Lasso regularization), L2 regularization (Ridge regularization), and Elastic Net regularization. For example, in the case of vital data of a vital sign that is prone to fluctuation (e.g., heart rate), the penalty term may be set to be weaker. Furthermore, in situations where vital signs fluctuate significantly (such as in an operating room), the penalty term may be set to be weaker. Furthermore, when long-term trends are desired, the penalty term may be set to be stronger.

[0076] (1-5-4. Analysis of vital data function information, generation of patient condition information and response information) 12, the vital data evaluation device 10 analyzes the generated first vital data function information and second vital data function information (step S401). At this time, the vital data evaluation device 10 generates first vital data derivative information based on the first vital data function information (step S403). In this example, the first vital data derivative information is generated by performing a first-order differential calculation process on the first vital data function information (see the center diagram in FIG. 16: the solid line is the first vital data derivative information).

[0077] Similarly, the vital data evaluation device 10 generates second vital data derivative information based on the second vital data function information (step S405). In this example, the second vital data derivative information is generated by performing a first-order differential calculation process on the second vital data function information (see the center diagram in FIG. 16: the dashed line is the second vital data derivative information).

[0078] In this embodiment, the vital data evaluation device 10 generates first identification information associated with the first vital data derivative information. Similarly, the vital data evaluation device generates second identification information associated with the second vital data derivative information. The first identification information is information that allows the transition of the first vital data to be visually recognized. Specifically, as shown in FIG. 6, when the first vital data (in this example, systolic blood pressure) is on an upward trend, the first identification information 201m is an arrow pointing upward to the right. When the first vital data (systolic blood pressure) is on a downward trend, the first identification information 201m is an arrow pointing downward to the right. The second identification information is information that allows the transition of the second vital data to be visually recognized, and has an arrow shape similar to the first identification information. Note that the shape of the arrow (size, thickness, color, etc.) may be changed depending on whether the derivative is positive or negative and the magnitude of the value, and the shape need not be an arrow as long as the direction can be identified. The first identification information and the second identification information may be displayed (output) on the display unit 14. This allows medical personnel to easily understand trends in vital data.

[0079] Next, the vital data evaluation device 10 generates patient condition information based on the relationship between the first vital data derivative information and the second vital data derivative information (step S407). The patient condition information is information for estimating the patient's condition. In this example, the patient condition information is selected from a patient condition data table 200 (also referred to as a "patient condition data set") shown in FIG. 6. Specifically, when the first vital data function information f1' is negative (-) (decreased systolic blood pressure) and the second vital data function information f2' is positive (+) (increased heart rate), the vital data evaluation device 10 generates patient condition information "circulating plasma volume deficiency." The vital data evaluation device 10 displays the generated patient condition information on the display unit 14. This allows medical personnel to understand the patient's condition.

[0080] Next, the vital data evaluation device 10 generates corresponding information based on the patient condition information (step S409). In this example, the corresponding information is selected from the corresponding information data table 300 (also referred to as the "corresponding information data set") shown in FIG. 7. The corresponding information is associated with the patient condition information. In this example, the corresponding information "infusion or blood transfusion" is generated, which is associated with the patient condition information "circulating plasma volume insufficiency." The vital data evaluation device 10 displays the generated corresponding information on the display unit 14 (step S411). This allows the medical staff to understand how to respond to the patient. This completes the vital data evaluation method in this embodiment.

[0081] According to this embodiment, by generating a function (vital data function information) from two types of vital data measured over a predetermined period, it is possible to accurately grasp the fluctuation trends of vital data. Furthermore, patient condition information and even correspondence information can be easily generated based on the relationship between the function information of the two types of vital data. In other words, by using this embodiment, it is possible to easily make judgments about the patient's condition that are similar to those of an experienced medical professional.

[0082] An example of an actual medical procedure based on the correspondence information obtained by this embodiment will now be described. After initiating a transfusion or blood transfusion procedure based on the correspondence information "infusion or blood transfusion," first vital data and second vital data may be acquired. Next, the vital data evaluation device 10 generates first vital data function information and second vital data function information based on the acquired first vital data and second vital data. Furthermore, the vital data evaluation device 10 generates first vital data derivative information and second vital data derivative information based on the first vital data function information and the second vital data function information. In this case, if the first vital data derivative information indicates "an increasing trend in systolic blood pressure" and the second vital data derivative information indicates "a decreasing trend in heart rate," the vital data evaluation device can analyze and determine that the patient's condition is stabilizing, even if the vital data or vital data function information is within an abnormal value range. When the actual systolic blood pressure and heart rate fall within the normal range, the vital data evaluation device can analyze and evaluate that the patient's condition has stabilized.

[0083] In one embodiment of the present invention, for simplicity, only positive and negative information of first-order derivative information is used as the first vital data derivative information and the second vital data derivative information, but numerical information may also be used. Also, while only first-order derivative information is used, second-order derivative information may also be used in addition to this. This makes it possible to evaluate the degree of change in more detail.

[0084] In addition, in one embodiment of the present invention, an example has been shown in which the vital data evaluation device 10 displays the generated patient condition information and response information on the display unit 14, but the present invention is not limited to this. For example, the vital data evaluation device 10 may output the patient condition information and / or response information as voice, or may output it to an external device (terminal device 40).

[0085] Although an example of generating patient condition information based on first vital data derivative information and second vital data derivative information has been described in one embodiment of the present invention, the present invention is not limited thereto. For example, in addition to the first vital data derivative information and the second vital data derivative information, patient condition information may be generated using first vital data, first vital data function information, second vital data, second vital function information, patient information, or environmental information. Patient information includes at least one piece of information such as the patient's gender, age, occupation, and test results. Environmental information includes patient-related information such as time information, spatial information such as an operating room or hospital room, and information regarding medication administration. This patient information and environmental information may be information that changes over time. For information that changes over time, a function model may be generated, similar to the vital data, to generate function information or derivative information. This allows for more accurate patient condition information to be generated. The above-described information may also be used when generating correspondence information.

[0086] Second Embodiment In this embodiment, a patient condition information method different from that in the first embodiment will be described. Specifically, an example will be described in which first vital data derivative information and second vital data derivative information are generated when first vital data function information exceeds (or falls below) a threshold.

[0087] FIG. 17 is a flow diagram of a vital data evaluation method. As shown in FIG. 17, when analyzing the relationship between the first vital data function information and the second vital data function information, it may be determined whether the first vital data function information satisfies a predetermined condition (step S4021). In this example, the vital data evaluation device 10 determines whether the latest value (or current value) of the function information of "systolic blood pressure" is less than 100. If the latest value of the function information of "systolic blood pressure" is 100 or more (step S4021; No), the first vital data evaluation device updates the first vital data function information and the second vital data function information (step S4022) and returns to step S401. If the latest value of the function information of "systolic blood pressure" is less than 100 (step S4021; Yes), it may generate first vital data derivative information and second vital data derivative information. The subsequent processing is the same as in the first embodiment. Note that vital data may be used in the determination of S4021. In this embodiment, the calculation process for generating vital data derivative information is triggered by a change in the patient's symptoms, so that judgments on the patient's condition can be easily made in a manner similar to that of an experienced medical professional while reducing the calculation load. Note that if there is room in the calculation function, the vital data derivative information may be calculated at any time.

[0088] In this embodiment, the above processing may be executed when the first vital data or the first vital data function information f1 falls below the cutoff value (or when the second vital data or the vital data function information f2 exceeds the cutoff value).

[0089] <Third embodiment> In this embodiment, an example will be described in which severity is included when generating patient condition information.

[0090] FIG. 18 is a flowchart of generating patient condition information. As shown in FIG. 18, the vital data evaluation device 10 analyzes the first vital data function information (step S401). At this time, the vital data evaluation device 10 calculates the latest value (current value) of the first vital data (step S4023). The vital data evaluation device 10 may generate severity information based on the latest value of the first vital data function information (step S4024). Specifically, the first vital data is determined to be "mild" when the "systolic blood pressure" is less than 100, "severe" when the "systolic blood pressure" is less than 80, and "emergency" when the "systolic blood pressure" is less than 60. In this embodiment, the vital data evaluation device 10 can add severity to the patient condition information generated in the first embodiment (step S407A). The severity refers to the degree of severity or severity of the patient's condition, urgency, etc.

[0091] Furthermore, the vital data evaluation device 10 generates correspondence information based on the severity and the patient condition information (step S409A). FIG. 19 is an example of the correspondence information data table 400 in this embodiment. In this example, similar to the first embodiment, it is assumed that the first vital data function information f1' is negative (-) (decreased systolic blood pressure) and the second vital data function information f2' is positive (+) (increased heart rate). The correspondence information data table 400 includes patient condition information 411 and correspondence information 413. As shown in FIG. 19, the patient condition information 411 includes severity information in addition to the patient condition information. The correspondence information 413 is associated with the patient's condition and severity. Specifically, when the patient condition information is "circulating plasma volume deficiency (systolic blood pressure 100 or less, mild)," the correspondence information is set to "infusion or blood transfusion." When the patient condition information is "circulating plasma volume deficiency (systolic blood pressure 80 or less, severe)," the correspondence information is set to "administration of a vasopressor" in addition to "infusion or blood transfusion." Furthermore, in the case of "circulating plasma volume deficiency (systolic blood pressure 60 or less, emergency)," in addition to the response information "infusion or blood transfusion, administration of vasopressor," an "emergency alert (gather personnel)" is set. Therefore, by using this embodiment, it is possible to classify the patient's condition according to the severity and propose responses, and it is easy to make a judgment on the patient's condition that is closer to that of an experienced medical professional.

[0092] In this embodiment, the vital data evaluation device 10 may generate the severity based on a predetermined condition. For example, as shown in FIG. 20, the vital data evaluation device 10 determines whether the first vital data function information satisfies a predetermined condition (exceeds a threshold) (step S4025). In this example, the vital data evaluation device 10 determines whether the latest value of the function information of "systolic blood pressure" is less than 100. If the latest value of the function information of "systolic blood pressure" is 100 or greater (step S4025; No), the first vital data evaluation device updates the first vital data function information and the second vital data function information (step S4026) and returns to step S401. If the latest value of the function information of "systolic blood pressure" is less than 100 (step S4025; Yes), the vital data evaluation device 10 generates severity information (step S4027). The severity information may be generated based on the latest value of the first vital data function information.

[0093] In addition, in this embodiment, for simplicity, only positive / negative information of the derivative information is used, but numerical information may also be used. Furthermore, while only first-order derivative information is used, second-order derivative information may also be used in addition to this. This enables a detailed severity assessment that reflects the degree of change. Furthermore, as in the first embodiment, severity information may be generated using first vital data, first vital data function information, second vital data, second vital function information, patient information, or environmental information in addition to these pieces of information. In this case, more detailed severity information of the patient's condition may be generated by combining the severity based on the first vital data (first vital data function information, first vital data derivative) with the severity based on the second vital data (second vital data function information, second vital data derivative).

[0094] <Fourth embodiment> In this embodiment, a method for generating vital data derivative information that is different from that in Embodiment 1 will be described. Specifically, an example in which a state transition marker is generated and output as vital data derivative information will be described.

[0095] FIG. 21 shows a state transition marker data table 500. The state transition marker data table 500 includes first-order derivative information 501, second-order derivative information 503, and a transition marker 505. In this embodiment, the vital data evaluation device 10 generates (calculates) a first-order derivative and a second-order derivative from the vital data function information (see the center and right diagrams in FIG. 16). The vital data evaluation device 10 generates a transition display marker as vital data derivative information from a combination of the generated first derivative and second derivative based on the state transition marker data table 500 in FIG. 21.

[0096] Specifically, the shape of the mark is determined using the value of the first derivative f' and the value of the second derivative f". For example, assume that the vital data function information is in the state of Equation 2 at the 100th minute (t = 100). Note that the equations and values ​​here have been simplified for the sake of explanation. f(t) = 2t 2 - 19890 (Formula 2) If we calculate the derivative (1st and 2nd order) from this, we get f'(t) = 4t f''(t) = 4 In this case, f, f', and f'' at time t=100 minutes (current values) will be as follows: f(100) = 2 * 100 2 - 19890 = 110 f'(100) = 4 * 100 = 400 f''(100) = 4 As described above, when the first derivative f' is 400, i.e., "+", and the second derivative f" is 4, i.e., "+", the arrow points to the upper right and is convex downwards, indicating a nonlinear, rapid rise (top left of the transition marker 505 in FIG. 21). As another example, when the first derivative f' is "+" and the second derivative f" is "0", the transition marker is a straight arrow pointing to the upper right (top center of the transition marker 505 in FIG. 21). This arrow indicates that the vital data is steadily rising. As another example, when the first derivative f' is "+" and the second derivative f" is "-", the arrow points to the upper right and is convex upwards, indicating that the rate of rise is gradual (top right of the transition marker 505 in FIG. 21). It is also possible to display the degree of change by reflecting the degree of these "+"s and "-"s in the size and shape of the arrow. Also, the display format does not have to be an arrow as long as the direction is clear. The second derivative may be omitted for the purpose of simplifying the display and calculation processing.

[0097] Furthermore, in this embodiment, the vital data evaluation device 10 can generate patient condition information and even correspondence information based on the relationship between the first vital data trend marker generated based on the first vital data function information and the second vital data trend marker generated based on the second vital data function information.

[0098] By using this embodiment, the transition of vital data can be grasped in more detail. Therefore, patient condition information can be generated more accurately. Furthermore, by displaying the generated transition display marker in this embodiment, the transition of the patient's vital data (the transition of the patient's condition) can be visually recognized quickly and in detail.

[0099] Fifth Embodiment In this embodiment, an example will be described in which patient condition information is generated by machine learning the patterns of first vital data function information and second vital data function information. Note that descriptions of parts that overlap with the first embodiment of the present invention will be omitted as appropriate.

[0100] Fig. 22 is a flow diagram showing the vital data evaluation process in this embodiment. First, the vital data evaluation device 10 generates an image (also referred to as a "function shape pattern") in which the generated first vital data function information and the generated second vital data function information are superimposed (step S501). Fig. 24 is an example of a function shape pattern 600. As shown in Fig. 24, the function shape pattern 600 includes first vital data function information 601 and second vital data function information 603, but may also include first vital data and second vital data.

[0101] Next, machine learning is performed by applying the generated function shape pattern to a machine learning model for generating patient condition information (step S503). The machine learning model for generating patient condition information corresponds to the shape patterns of the first vital data function information and the second vital data function information.

[0102] 23 is a flow diagram of generating a machine learning model for generating patient condition information in this embodiment. As shown in Fig. 23, a function shape pattern for generating a machine learning model for generating patient condition information is acquired in advance (step S5031).

[0103] Next, teacher data is generated based on the previously acquired function shape pattern (step S5033). At this time, teacher data may be generated arbitrarily based on input from the user. Specifically, teacher data may be generated by inputting information corresponding to the actual condition of the patient and the transition of vital data. Furthermore, patient information or environmental information such as that used in the first embodiment may be used as teacher data.

[0104] Next, machine learning is performed using the training data and the previously acquired function shape pattern (step S5035). For the machine learning, known learning methods such as backpropagation and genetic algorithm (GA) may be used. By repeating the machine learning, a machine learning model for generating patient condition information is generated (step S5037).

[0105] Returning to Fig. 22, the explanation will be made. Machine learning is performed by applying the generated function shape pattern to the machine learning model, and as a result, the vital data evaluation device 10 generates (outputs) patient condition information (step S505). Next, the vital data evaluation device 10 generates correspondence information based on the generated patient condition information (step S507). This completes the vital data evaluation method in this embodiment.

[0106] By using this embodiment, the function shape pattern obtained from two vital signs data can be recognized by machine learning, and the patient's condition can be easily understood. In other words, by using this embodiment, it is possible to easily make a judgment on the patient's condition close to that of an experienced medical professional.

[0107] In this embodiment, image information in which the first vital data function information and the second vital data function information are superimposed, or markers indicating changes or states as in the fourth embodiment may be displayed, or may be output to the terminal device 40. This allows the relationship between the first vital data function information and the second vital data function information to be visually recognized.

[0108] In addition, in this embodiment, when performing machine learning, training data may be created by appropriately combining at least one of vital data and derivative information, and machine learning may be performed. In addition, in this embodiment, for ease of explanation, an example is shown in which an image in which two vital data function information are physically superimposed is used, but the present invention is not limited to this. For example, if it is known that the time on the horizontal axis is consistent, individual images may be used for each vital data function information.

[0109] <Modification> The present disclosure is not limited to the above-described embodiments and includes various other modifications. For example, the above-described embodiments have been described in detail to clearly explain the present disclosure, and are not necessarily limited to those including all of the described configurations. Furthermore, part of the configuration of one embodiment may be replaced with the configuration of another embodiment, or the configuration of another embodiment may be added to the configuration of one embodiment. Furthermore, part of the configuration of each embodiment may be added, deleted, or replaced with other configurations. Some modifications will be described below. Note that examples of modifications of each embodiment can also be applied as examples of modifications of other embodiments.

[0110] (1) One embodiment of the present invention can be applied to not only patients but also healthy individuals. It can also be applied to not only humans but also animals. Furthermore, it can provide information on the condition of a subject not only to medical professionals but also to the subject himself or herself and non-medical professionals.

[0111] (2) In the first embodiment of the present invention, an example was shown in which two types of vital data were measured and a patient's condition was estimated from the relationship between the two types of functional information, but the present invention is not limited to this. For example, three or more types of vital data may be measured and a patient's condition may be estimated from the relationship between the three or more types of functional information. Furthermore, similar time-series data that is continuously recorded like vital data may also be treated in the same way as vital data. This makes it possible to grasp the patient's condition more accurately. Furthermore, in situations where there is little need to combine data, a patient's condition may be estimated from the functional information of one type of vital data.

[0112] (3) In one embodiment of the present invention, the value of vital sign function information is used as the cutoff value, but an actually measured value may also be used as the cutoff value. Such function information and an actually measured value may also be used in combination.

[0113] (4) In one embodiment of the present invention, when preprocessing the first vital data, the first vital data may be associated with vital data different from the second vital data. For example, if the third vital data, "pulse pressure value (difference between systolic blood pressure and diastolic blood pressure)," is less than a threshold value for the first vital data, "systolic blood pressure (value)," there is a strong suspicion of a measurement error, and the temporally corresponding systolic blood pressure value may be excluded. This reduces the influence of measurement errors, making the vital data function information more accurate and allowing for a more accurate understanding of the transition of vital data.

[0114] (5) In one embodiment of the present invention, patient condition information and response information are displayed, and it is assumed that medical professionals and others will respond accordingly. However, for events that can be handled without the intervention of medical professionals and others, the system may directly handle them without the intervention of medical professionals and others. In this case, the vital data evaluation system may include medical devices, air conditioning equipment, and other electronic devices. For example, various processes, such as adjusting the dosage of medication by medical devices or adjusting the room temperature by air conditioning equipment, may be performed based on instruction information generated by the control unit of the vital data evaluation device.

[0115] (6) When the same vital data is measured simultaneously using multiple devices, the vital data may be preprocessed to take into account measurement errors specific to the vital data. For example, when measuring the second vital data "heart rate" using two second vital data measurement devices, if the "heart rate" measured by the electrocardiogram is approximately twice the "heart rate" measured by the pulse oximeter, the "heart rate" of the electrocardiogram may be considered double counted and excluded, or may be divided by two. This makes it less susceptible to measurement errors, making it easier to generate vital data function information and enabling more accurate understanding of trends in vital data.

[0116] (7) In one embodiment of the present invention, first vital data may be measured using not only one first vital data measurement device but also multiple first vital data measurement devices. For example, blood pressure measurement using a cuff is non-invasive and can be widely used in everyday settings and hospital settings, but there are limits to shortening the measurement interval. Furthermore, frequent repeated measurements may lead to skin damage at the measurement site. On the other hand, blood pressure measurement using an invasive arterial pressure measuring device, while invasive, allows continuous monitoring of blood pressure and is therefore primarily used when the subject's blood pressure changes significantly. Therefore, the period during which invasive arterial pressure measurement is performed is often short. Furthermore, when blood pressure measurement using an invasive arterial pressure measuring device is being performed, blood pressure measurement using a cuff is often discontinued or performed less frequently. Therefore, using data measured using only one first vital data measurement device may result in missing values ​​for a certain period of time. By combining data measured by multiple first vital data measurement devices, it is possible to supplement the first vital data when the measurements of the first vital data are interrupted (first vital data is missing for a specified period) at one first vital data measurement device, and to generate an uninterrupted (stable) time series data set for the specified period.

[0117] (8) Measuring the first vital data using multiple first vital data measurement devices makes the system more robust against measurement errors. For example, measuring "heart rate" using an electrocardiogram is vulnerable to electrical scalpels, electromyograms, and vibrations. On the other hand, measuring heart rate using a pulse oximeter is vulnerable to blockage of blood flow, obstacles at the measurement site (nail polish, etc.), and limb movement. Even if multiple first vital data measurement devices are used in this way, if measurements taken using any of the first vital data measurement devices can be considered medically nearly identical, generating a first vital data function from both measurements can be expected to make the system more robust against measurement errors.

[0118] (9) In one embodiment of the present invention, the first vital data derivative information and the second vital data derivative information are used to generate patient condition information, correspondence information, and transition markers based on the relationship between the first vital data function information and the second vital data function information. However, the present invention is not limited to this. For example, the patient condition information, correspondence information, and transition markers may be generated based on the relationship between the integral value of the first vital data function information and the integral value of the second vital data function information.

[0119] For example, a transition to (mild) hypotension may be determined based on the time integral of values ​​below a threshold in the first vital data (blood pressure) function, and a transition to (mild) tachycardia may be determined based on the time integral of values ​​above a threshold in the second vital data function information (heart rate). Furthermore, the patient condition information "circulating plasma volume deficiency" and corresponding information "infusion or blood transfusion" may be generated based on the combination of the integral of the first vital data function and the integral of the second vital data function information. Furthermore, transition markers may be generated to indicate that blood pressure is trending low and heart rate is trending high. Furthermore, an abnormality may be analyzed based on the integral of the first vital data function and the integral of the second vital data function information, and severity information may be generated. Furthermore, the cutoff value parameters may be changed based on the integral (e.g., increasing sensitivity to derivative information if abnormal values ​​persist).

[0120] (10) In one embodiment of the present invention, an example has been shown in which vital data derivative information (velocity of vital data function information if it is a first-order derivative, or acceleration of vital data function information if it is a second-order derivative) is evaluated and analyzed from the vital data function, but patient condition information may also be generated from the relationship with the variance value of the vital data function information or vital data derivative information. For example, a large variance value of the velocity can be used to determine that the patient's condition is becoming unstable.

[0121] (11) In one embodiment of the present invention, prediction information regarding changes in the first vital data can be generated by arithmetically processing the first vital data function information. For example, a short-term moving average (short-term line) and a long-term moving average (long-term line) of the first vital data can be prepared, and changes in the first vital data can be predicted from the relationship between the long-term line and the short-term line. More specifically, if the long-term line exceeds the short-term line, the vital data evaluation device 10 may use this as information for generating patient condition information or a transition marker indicating that the first vital data is currently increasing. Alternatively, prediction information indicating that the first vital data will increase in the future may be generated.

[0122] (12) In one embodiment of the present invention, the generated patient condition information and corresponding information may be analyzed based on information input to the terminal device 40. For example, if the patient condition information and corresponding information need to be corrected, the patient condition information DB 50c and the corresponding information DB 50d may be appropriately corrected based on the information input to the terminal device 40.

[0123] (13) In one embodiment of the present invention, the vital data evaluation device 10 may generate warning information when the first vital data function information (or the first vital data derivative information) or the second vital data function information (or the second vital data derivative information) satisfies a predetermined condition. For example, this may be the case when a part (maximum or minimum value) of the first vital data function information exceeds a predetermined numerical range, or when the integral value of the first vital data function information over a certain period of time exceeds a predetermined threshold. Furthermore, if it is difficult to calculate an accurate integral value, an approximation of the integral value may be calculated from the vital data itself using numerical integration, etc. Furthermore, patient condition information may be generated based on the relationship between the integral value of the first vital data function information and the integral value of the second vital data function information.

[0124] (14) In one embodiment of the present invention, the first vital data and the second vital data may be measured using a single measuring device.

[0125] (15) In the third embodiment of the present invention, an example was shown in which the vital data evaluation device 10 determined whether the first vital data function information satisfies a predetermined condition (exceeds a threshold), but the present invention is not limited to this. The vital data evaluation device 10 may determine whether the vital data (current value) satisfies a predetermined condition and then execute the next process. This makes it possible to generate severity information, patient condition information, or response information using data that a medical professional can normally grasp. In other embodiments, vital data evaluation processing may also be performed using appropriate vital data. [Explanation of symbols]

[0126] 1 vital data evaluation system, 10 vital data evaluation device, 11 control unit, 11a acquisition unit, 11b data preprocessing unit, 11c generation unit, 11d analysis unit, 11e output instruction unit, 12 storage unit, 13 communication unit, 14 display unit, 15 operation unit, 20 vital data measurement device, 20-1 first vital data measurement device, 20-2 second vital data measurement device, 21 control Control unit, 22...Memory unit, 23...Communication unit, 24...Display unit, 25...Operation unit, 26...Measuring unit, 40...Terminal device (external device), 41...Control unit, 42...Memory unit, 43...Communication unit, 44...Display unit, 45...Operation unit, 50...Database, 50a...Vital database (DB), 50b...Function information database (DB), 50c...Patient condition information database (DB), 50d...Corresponding information database Database (DB), 100: Basis function data table, 101: Basis function information, 103: Feature information, 110: Vital sign-basis function data table, 111: Vital sign information, 113: Basis function information, 200: Patient condition data table, 201: First vital data derivative information, 201m: First identification information, 203: Second vital data derivative information, 203m: Second identification information, 205: Patient condition Information, 300···Correspondence information data table, 301···Patient condition information, 303···Correspondence information, 400···Correspondence information data table, 411···Patient condition information, 413···Correspondence information, 500···State transition marker data table, 501···First order derivative information, 503···Second order derivative information, 505···Transition marker, 600···Function shape pattern, 601···First vital data function information, 603···Second vital data function information

Claims

[Claim 1] acquiring a first vital data set corresponding to a first type of first vital data for the patient; acquiring a second vital data set corresponding to a second type of second vital data of the patient that is different from the first type; generating first vital data function information based on the first vital data set; generating second vital data function information based on the second vital data set; generating patient condition information for estimating a condition of the patient based on a relationship between the first vital data function information and the second vital data function information; Vital data assessment methods.

Images