Program, information processing method, and information processing apparatus

Abstract

Provided is a program that allows body composition information to be accurately measured while reducing burdens on a subject. In the present invention, a computer acquires a series of bioimpedance data items by bioimpedance measurement and, on the basis of a plot point group plotted on a complex plane with resistance as the horizontal axis and reactance as the vertical axis and a logical formula indicating the relationship between the bioimpedance data and parameters R0 and R∞, identifies a function that represents an optimal Cole–Cole curve of the plot point group. The computer assesses whether or not the bioimpedance data meets compatibility conditions that include a first condition relating to parameters of the identified function, a second condition that relates to the degree of similarity to the optimal Cole–Cole curve of the plot point group, and a third condition that relates to a compatible point group that is a subset of the plot point group and follows the optimal Cole–Cole curve and, if the compatibility conditions are met, stores an estimated value related to body composition that is obtained from the function and generates body composition information on the basis of the estimated value that was stored.

Description

Program, information processing method, and information processing device

[0001] The present invention relates to a program, an information processing method, and an information processing device.

[0002] Body composition analyzers are used that measure the resistance value (bioimpedance) of a subject's body by passing a weak current through the subject's body, and estimate values ​​related to the subject's body composition based on the measured bioimpedance and physical information of the subject, such as age, sex, height, weight, etc. Patent Document 1 discloses a technique for calculating a patient's hydration state and nutritional state using bioimpedance measurements.

[0003] Special table 2014-528295 publication

[0004] A body composition analyzer (bioimpedance sensor) attaches multiple electrodes to measurement sites on a living body and measures the bioimpedance of the living body based on the current flowing through the body. Therefore, appropriate measurement results may not be obtained depending on the posture or condition of the measurement site, and measurements must be taken while maintaining the appropriate posture and condition of the measurement site. For example, a specific posture is required, such as resting in a supine or upright position, touching the electrodes with a hand or foot, or extending the arm when the device is attached to the arm. To accurately measure a subject's condition, it is desirable to increase the number of measurements, but measurements using the above-mentioned body composition analyzer impose a heavy burden on the subject, making frequent measurements difficult. The technology disclosed in Patent Document 1 calculates appropriate bioimpedance measurement data based on first bioimpedance measurement data obtained by a first type of measurement and second bioimpedance measurement data obtained by a second type of measurement, but does not consider a configuration that reduces the burden on the subject.

[0005] In one aspect, an object of the present invention is to provide a program or the like that can reduce the burden on a subject and accurately measure the body composition information of the subject.

[0006] (1) The present disclosure provides a program that causes a computer to execute a process of acquiring a series of bioimpedance data obtained by bioimpedance measurement, identifying a function that indicates an optimal Cole-Cole curve that is most suitable for the series of plot points based on the acquired series of bioimpedance data and a series of plot points plotted on a complex plane with resistance on the horizontal axis and reactance on the vertical axis, and based on a logical formula that shows the relationship between the bioimpedance data and parameters R0 and R∞, determining whether or not the series of bioimpedance data satisfies compatibility conditions that include at least a predetermined first condition on at least one parameter in the identified function, a predetermined second condition on the similarity of the series of plot points to the optimal Cole-Cole curve, and a predetermined third condition on a compatibility point group of the series of plot points that is aligned with the optimal Cole-Cole curve, and if it is determined that the series of bioimpedance data satisfies the compatibility conditions, storing an estimated value of body composition obtained from the function in a storage unit and generating body composition information based on the stored estimated value.

[0007] (2) It is preferable that the program of (1) above further causes the computer to execute a process of identifying a representative value of the estimated values ​​for a specified period based on the estimated values ​​for the body composition for the specified period stored in the memory unit, and generating body composition information based on the identified representative value.

[0008] (3) In the program of (1) or (2) above, the logical formula preferably includes parameters R0, R∞, and Td (time delay correction term), and the first condition preferably includes at least the following two conditions: 1. The parameters R0 and R∞ are positive; and 2. The parameter Td is equal to or greater than a predetermined threshold value.

[0009] (4) In the program according to any one of (1) to (3) above, the second condition preferably includes at least the following two conditions: 1. The proportion of the relevant points in the series of plot points is equal to or greater than a predetermined threshold; 2. The sum of the distances of the relevant points from the optimal Cole-Cole curve is equal to or less than a predetermined threshold.

[0010] (5) In the program according to any one of (1) to (4) above, it is preferable that the third condition includes at least the following two conditions: 1. A trajectory formed by the matching point group straddles a peak of the optimal Cole-Cole curve; and 2. A coverage rate of the trajectory with respect to the optimal Cole-Cole curve is equal to or greater than a predetermined threshold.

[0011] (6) It is preferable that the program described in any of (1) to (5) above further causes the computer to execute a process of discarding the series of bioimpedance data if it is determined that the series of bioimpedance data does not satisfy the compatibility conditions.

[0012] (7) In the program described in any one of (1) to (6) above, the logical formula includes a parameter Td, the first condition includes a first sub-condition that at least the parameter Td is equal to or greater than a predetermined threshold value, the third condition includes a second sub-condition that a trajectory formed by the matching point group crosses a peak of the optimal Cole-Cole curve, and the matching condition has a fitting condition including the first sub-condition and the second sub-condition, and it is preferable that the program further causes the computer to execute a process of determining whether the series of bioimpedance data satisfies the fitting condition, and if it is determined that the fitting condition is not satisfied, determining that the matching condition is not satisfied without determining any other conditions among the matching conditions other than the fitting condition.

[0013] (8) It is preferable that the program described in any of (1) to (7) above further causes the computer to execute a process of determining whether the series of bioimpedance data satisfies the compatibility condition based on a plurality of logical formulas prepared in advance as the logical formula, and if it is determined that the series of bioimpedance data satisfies the compatibility condition, storing the estimated value of body composition obtained from the function identified based on the logical formula among the plurality of logical formulas used when it was determined that the series of bioimpedance data satisfied the compatibility condition.

[0014] (9) It is preferable that the program of (8) above further causes the computer to execute a process of discarding the series of bioimpedance data when it is determined that the series of bioimpedance data does not satisfy the compatibility condition in any of the multiple logical formulas.

[0015] (10) It is preferable that the program of (8) or (9) above further causes the computer to execute a process of identifying one logical formula among the plurality of logical formulas that satisfies the compatibility conditions and has the best judgment result for the compatibility conditions, and storing the estimated value of body composition obtained from the function identified based on the identified one logical formula.

[0016] (11) In the program described in any one of (8) to (10) above, each of the plurality of logical expressions includes a parameter Td, the first condition includes a first sub-condition that at least the parameter Td is equal to or greater than a predetermined threshold value, the third condition includes a second sub-condition that a trajectory formed by the matching point group straddles a peak of the optimal Cole-Cole curve, and the matching condition includes a fitting condition including the first sub-condition and the second sub-condition. Preferably, the program further causes the computer to execute the following steps: determine whether the series of bioimpedance data satisfies the fitting condition based on the plurality of logical expressions; if it is determined that the series of bioimpedance data satisfies the fitting condition, determine whether the series of bioimpedance data satisfies the fitting condition based on the logical expression of the plurality of logical expressions used when it was determined that the series of bioimpedance data satisfied the fitting condition; and, if it is determined that the series of bioimpedance data satisfies the fitting condition, store the estimated value of body composition obtained from the function identified based on the logical expression of the plurality of logical expressions used when it was determined that the series of bioimpedance data satisfied the fitting condition.

[0017] (12) The present disclosure provides an information processing method in which a computer acquires a series of bioimpedance data obtained by bioimpedance measurement, identifies a function that indicates an optimal Cole-Cole curve that is most suitable for the series of plot points based on the acquired series of bioimpedance data and a series of plot points plotted on a complex plane with resistance on the horizontal axis and reactance on the vertical axis, and based on a logical formula showing the relationship between the bioimpedance data and parameters R0 and R∞, determines whether the series of bioimpedance data satisfies compatibility conditions that include at least a predetermined first condition on at least one parameter in the identified function, a predetermined second condition on the similarity of the series of plot points to the optimal Cole-Cole curve, and a predetermined third condition on a compatibility point group of the series of plot points that is aligned with the optimal Cole-Cole curve, and if it is determined that the series of bioimpedance data satisfies the compatibility conditions, stores an estimated value of body composition obtained from the function in a storage unit, and generates body composition information based on the stored estimated value.

[0018] (13) The present disclosure relates to an information processing device having a control unit, wherein the control unit acquires a series of bioimpedance data obtained by bioimpedance measurement, and, based on the acquired series of bioimpedance data, identifies a function that indicates an optimal Cole-Cole curve that is most suitable for the series of plot points based on a series of plot points plotted on a complex plane with resistance on the horizontal axis and reactance on the vertical axis, and a logical formula showing the relationship between the bioimpedance data and parameters R0 and R∞, and determines whether or not the series of bioimpedance data satisfies compatibility conditions that include at least a predetermined first condition on at least one parameter in the identified function, a predetermined second condition on the similarity of the series of plot points to the optimal Cole-Cole curve, and a predetermined third condition on a compatibility point group of the series of plot points that is aligned with the optimal Cole-Cole curve, and if it is determined that the series of bioimpedance data satisfies the compatibility conditions, stores an estimated value of body composition obtained from the function in a storage unit, and generates body composition information based on the stored estimated value.

[0019] (14) It is preferable that the programs of (1) to (11) above further cause the computer to execute the following processes: generate body composition information in predetermined minute increments based on the series of bioimpedance data measured in predetermined minute increments; store the generated body composition information in the memory unit in association with the measurement date and time of the series of bioimpedance data used to generate the body composition information; calculate a representative value of the body composition information at a predetermined time selected from units of several hours to several days from the multiple body composition information stored in the memory unit; and display a time series graph showing the time change of the body composition information on the display unit based on the calculated representative value of the body composition information.

[0020] (15) It is preferable that the program of (14) above further causes the computer to execute a process in which the representative value of the body composition information includes a first representative value of the body composition information for a first period selected from units of several hours to several days, and a second representative value of the body composition information for a second period selected from units of several hours to several days and shorter than the first period, and receives an instruction to switch between a first time series graph on which the first representative value of the body composition information is plotted and a second time series graph on which the second representative value of the body composition information is plotted, and switches the time series graph displayed on the display unit to the first time series graph or the second time series graph in accordance with the received switching instruction.

[0021] In one aspect, the burden on the subject can be reduced and the body composition information of the subject can be measured with high accuracy.

[0022] 1 is a block diagram showing an example of the configuration of a body composition meter. FIG. 1 is an explanatory diagram of a measurement process of bioimpedance by a measurement unit. FIG. 1 is an explanatory diagram showing an example of a record layout of a patient DB. FIG. 2 is a flowchart showing an example of a measurement process procedure of bioimpedance. FIG. 2 is an explanatory diagram of a measurement process. FIG. 3 is an explanatory diagram of a measurement process. FIG. 4 is an explanatory diagram of a measurement process. FIG. 5 is an explanatory diagram of a measurement process. FIG. 6 is a flowchart of a measurement process procedure of embodiment 2. FIG. 7 is a flowchart of an example of a measurement process procedure of embodiment 3. FIG. 8 is a flowchart of an example of a measurement process procedure of embodiment 4. FIG. 9 is an explanatory diagram showing an example of the configuration of an information processing system of embodiment 5. FIG. 10 is a block diagram showing examples of the configuration of an information processing device and a terminal device. FIG. 11 is an explanatory diagram showing an example of a record layout of a patient DB stored in an information processing device. FIG. 12 is a flowchart of an example of a measurement result registration process. FIG. 13 is a flowchart of an example of a measurement process procedure of bioimpedance of embodiment 6. FIG. 14 is a flowchart of an example of a presentation process procedure of a time series graph of body composition information. FIG. 15 is an explanatory diagram showing an example of a screen. FIG. 16 is an explanatory diagram showing an example of a screen. FIG. 17 is a flowchart of another example of a presentation process procedure of a time series graph of body composition information. FIG. 18 is an explanatory diagram showing an example of a screen.

[0023] Hereinafter, the program, information processing method, and information processing device of the present disclosure will be described in detail with reference to the drawings showing an embodiment in which the program, information processing method, and information processing device are applied to a body composition monitor.

[0024] (Embodiment 1) In this embodiment, a body composition meter (information processing device) will be described that measures bioimpedance, which is the resistance value of a subject's living body, according to bioelectrical impedance analysis (Bioimpedance Analysis), and measures (estimates) the body composition of the living body based on the measured bioimpedance. The body composition meter of this embodiment is a wearable device, such as a wristwatch or wristband, that is worn on the subject's arm, leg, or the like.

[0025] FIG. 1 is a block diagram showing an example of the configuration of a body composition monitor. Body composition monitor 10 of this embodiment includes a control unit 11, a storage unit 12, a communication unit 13, an input unit 14, a display unit 15, a measurement unit 16, and other components, all of which are interconnected via a bus. Control unit 11 has one or more processors, such as a CPU (Central Processing Unit), an MPU (Micro-Processing Unit), or a GPU (Graphics Processing Unit). Control unit 11 performs processing to be performed by body composition monitor 10 by appropriately executing a program P stored in storage unit 12. If control unit 11 has multiple processors, each process may be performed by a different processor. Control unit 11 may also include a clock that outputs date and time information.

[0026] The storage unit 12 includes RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EEPROM (Electrically Erasable and Programmable Read Only Memory), etc. The storage unit 12 pre-stores a program P (program product, computer program) executed by the control unit 11 and various data necessary for executing the program P. The storage unit 12 also temporarily stores data generated when the control unit 11 executes the program P. The storage unit 12 also stores a patient DB 12a. A portion of the storage unit 12 may be a storage medium detachable from the body composition monitor 10, and the patient DB 12a may be stored in a storage medium attached to the body composition monitor 10. The program P and various data stored in the storage unit 12 may be written to the storage unit 12 during the manufacturing process of the body composition monitor 10, or may be downloaded by the control unit 11 from another device via the communication unit 13 and stored in the storage unit 12. The control unit 11 may be a computing device (computer) having a processor, ROM, and RAM. In this case, the ROM stores a program P to be executed by the processor, and the processor reads the program P into the RAM and executes it, thereby performing the processing that the body composition monitor 10 should perform.

[0027] The communication unit 13 includes, for example, a communication module for wired communication via a USB (Universal Serial Bus) cable, or a communication module for short-range wireless communication such as Bluetooth (registered trademark) or a wireless LAN (Local Area Network), and transmits and receives information to and from other devices via wired or wireless communication. The communication unit 13 may also include a communication module for connecting to a network via wired or wireless communication, in which case, transmits and receives information to and from other devices via the network. The network may be, for example, the Internet or a public communication line, or a LAN (Local Area Network) established within a facility such as a medical institution where the body composition monitor 10 is used.

[0028] The input unit 14 accepts operation inputs from a user (e.g., a medical professional) and sends a control signal corresponding to the operation content to the control unit 11. The display unit 15 is a liquid crystal display or the like, and displays various information according to instructions from the control unit 11. The input unit 14 and the display unit 15 may be integrated into a touch panel. Note that the input unit 14 and the display unit 15 are not essential, and the body composition monitor 10 may be configured to accept operations via another device connected by communication and output the information to be displayed to the other display device for display.

[0029] The measurement unit 16 includes an electrode unit 16a, a current supply unit 16b, and a voltage measurement unit 16c. The electrode unit 16a has, for example, two electrodes, and with each electrode attached to the subject's living body (in contact with the living body), the current supply unit 16b applies a current to the living body via one of the electrodes. The voltage measurement unit 16c measures the voltage value between the two electrodes at this time, and measures the bioimpedance of the living body of the subject based on the applied current value and the measured voltage value. Note that the electrode unit 16a may also have four electrodes.

[0030] FIG. 2 is an explanatory diagram of the bioimpedance measurement process performed by the measurement unit 16. The measurement unit 16 of this embodiment uses a multi-frequency BIA, which measures bioimpedance while switching the frequency of the applied current. In measurements using the multi-frequency BIA, bioimpedance data is acquired when a current of each frequency is applied, which is sequentially switched, to acquire bioimpedance data (a series of bioimpedance data) corresponding to each frequency in a single measurement process. Hereinafter, the series of bioimpedance data will be referred to as measurement data. It is known that when measurement data obtained by the multi-frequency BIA is plotted on a complex plane (complex number plane) with resistance on the horizontal axis and reactance on the vertical axis, a Cole-Cole curve (also called the Cole-Cole model) such as that shown in FIG. 2 is drawn. The real part of the bioimpedance (complex impedance) represents the resistance component, and the imaginary part represents the reactance component. There are several types of logical formulas known to represent the Cole-Cole curve, and body composition monitor 10 performs a fitting process on the measurement data for each of the logical formulas prepared in advance, and identifies the logical formula and parameter values ​​within the logical formula that fit the measurement data to a high degree.

[0031] In the fitting process of this embodiment, logical formulas defined using parameters R0, R∞, Td, τm, α, and β, such as the following logical formulas A and B, are used to identify optimal values ​​for each parameter in logical formulas A and B. Note that ω indicates the frequency of the applied current, and j indicates the imaginary unit. Parameter R0 indicates the impedance (i.e., resistance) at a frequency of 0 kHz, and parameter R∞ indicates the impedance (i.e., resistance) at an infinite frequency. Parameter Td is a parameter (time delay correction term) for correcting the phase difference between current and voltage, i.e., the time delay when current flows through a living body. In the fitting process, the parameters of the logical formula are changed, and a function representing the measurement data is identified by identifying the logical formula and the values ​​of each parameter that best fit the measurement data. The logical formulas used in the fitting process are not limited to logical formulas A and B, but may include a logical formula that uses parameters R0 and R∞ to show the relationship between a series of bioimpedance data and parameters R0 and R∞, a logical formula that uses parameters R0, R∞, and Td, and a logical formula that does not include parameter Td in logical formulas A and B. In this embodiment, a logical formula in which parameters are not defined is referred to as a "logical formula," and a logical formula in which parameters are defined is referred to as a "function" to distinguish them.

[0032]

[0033] In the body composition monitor 10 configured as described above, the measurement unit 16 acquires measurement data (bioimpedance data for each frequency), and the control unit 11 performs a fitting process based on the measurement data to identify a function that represents the measurement data. The control unit 11 acquires values ​​of parameters R0, R∞, etc. (estimated values ​​related to body composition) as measurement results from the function obtained by the fitting process. The parameter R0 indicates the extracellular fluid resistance of the living body and is therefore used to calculate (estimate) the extracellular fluid volume, while the parameter R∞ indicates the sum of the biological resistances and is therefore used to calculate (estimate) the body water volume.

[0034] The body composition monitor 10 of this embodiment is used by being worn by, for example, a subject (hereinafter referred to as a patient) hospitalized at a medical institution. When the body composition monitor 10 is first used, a medical professional enters the patient's information via the input unit 14 and registers it in the patient DB 12a as an initial setting. The registered information includes, for example, identification information such as a patient ID or the patient's name, and physical information such as the patient's age, gender, height, and weight. After the initial setting is complete, the body composition monitor 10 is worn by the patient. Thereafter, the body composition monitor 10 periodically performs a bioimpedance measurement process, and the measurement results (e.g., the values ​​of parameters R0 and R∞) are associated with the measurement date and time and sequentially stored in the patient DB 12a. When the body composition monitor 10 acquires bioimpedance measurement results, it may calculate the patient's body composition information based on the measurement results and the physical information. In this case, the calculated body composition information is also stored in the patient DB 12a in association with the measurement date and time. Body composition monitor 10 not only displays the measurement results on display unit 15, but can also transmit the results to other devices such as an electronic medical record server via communication unit 13.

[0035] FIG. 3 is an explanatory diagram showing an example of the record layout of the patient DB 12a. The patient DB 12a is a database that stores data on patients who wear and use the body composition analyzer 10. The patient DB 12a shown in FIG. 3 includes a patient ID column, a physical information column, a measurement information column, etc., and stores information on the patient in association with the patient ID. The patient ID column stores identification information for identifying each patient (e.g., patient ID, patient name, etc.). The patient ID may be, for example, the patient card number of a patient card issued by a medical institution. The physical information column stores physical information including the patient's age, gender, height, and weight input via the input unit 14. The measurement information column stores measurement information of the patient measured by the body composition analyzer 10 in association with the measurement date and time. The measurement information includes measurement results (specifically, the values ​​of parameters R0 and R∞, etc.) and body composition information calculated from the measurement results. The body composition information includes, for example, total body water (TBW), extracellular water (ECW), intracellular water (ICW), hydration rate, and extracellular water ratio (edema index). In addition to the above, the body composition information may also include fat-free mass (FFM), fat mass, body fat percentage, FFMI (Fat Free Mass Index), phase angle, muscle mass, internal / external fluid ratio, internal / external fluid ratio, skeletal muscle mass, SMI (Skeletal Muscle Index), bone mineral content (estimated bone mass), protein content, and basal metabolic rate. The patient DB 12a is not limited to the configuration shown in FIG. 3 , and may store measurement data (a series of bioimpedance data) obtained by bioimpedance measurement.

[0036] The following describes the bioimpedance measurement process performed by the body composition monitor 10. Fig. 4 is a flowchart showing an example of the bioimpedance measurement process procedure, and Figs. 5A to 7 are explanatory diagrams of the measurement process.

[0037] In this embodiment, body composition monitor 10 starts a bioimpedance measurement process when the patient's information (identification information and physical information) is registered in patient DB 12a, the monitor is attached to the patient's body, and an instruction to start operation is given. Body composition monitor 10 periodically performs the bioimpedance measurement process at predetermined intervals, such as every few minutes to every 10 minutes, every 30 minutes, or every hour. Therefore, control unit 11 performs the following process each time the timing for performing the bioimpedance measurement process arrives. Note that the measurement process execution interval may be configured to be changeable via input unit 14, and in this case, it can be changed as appropriate depending on the patient's medical condition and physical state, etc.

[0038] When the measurement timing arrives, the control unit 11 acquires measurement data using the measurement unit 16 (S11). Specifically, the control unit 11 passes a current through the patient's living body by sequentially switching the frequency of the current supplied by the current supply unit 16b between approximately 100 different frequencies, for example, in a range of 2.5 kHz to 350 kHz, and acquires bioimpedance data when a current of each frequency is passed. Thus, the control unit 11 acquires a series of bioimpedance data corresponding to each frequency in a single measurement process.

[0039] Next, the control unit 11 performs a fitting process on the acquired measurement data using the above-described logical formula A (S12). The fitting process can be a known fitting process such as a fitting process using the least squares method. For example, the control unit 11 varies the value of each parameter in the logical formula A and identifies the parameter values ​​(parameter set) that minimize the difference between the value calculated by the logical formula A using the varied parameter values ​​and the values ​​obtained after correcting the measurement data using the logical formula A. That is, the control unit 11 identifies the parameter values ​​that result in an optimal Cole-Cole curve that is most suitable for the series of plot points plotted on a complex plane based on the measurement data and the logical formula A, and obtains a function using the identified parameter values.

[0040] The control unit 11 determines whether the fitting process was successful (S13). FIG. 5A shows an example of the results of the fitting process using Logical Formula A. The small dots in FIG. 5A represent plots of measurement data, and the dashed curve represents the impedance values ​​calculated based on Logical Formula A when each parameter in Logical Formula A is a predetermined parameter set. Specifically, the theoretical impedance values ​​calculated by introducing each frequency into a logical formula obtained by removing the time delay correction term from Logical Formula A are shown. The large dots and cross marks in FIG. 5A represent a group of points (hereinafter referred to as a group of plotted points) on which impedance values ​​after correcting measurement data based on Logical Formula A are plotted. Specifically, among the impedance values ​​after correcting measurement data using the time delay correction term included in Logical Formula A at each frequency, those whose difference from the theoretical value (the distance indicating the difference) is less than a predetermined threshold (fitted) are shown with large dots, and those whose difference from the theoretical value is greater than or equal to a predetermined threshold (uncovered) are shown with cross marks. Whether or not the fitting of each impedance value was successful is determined by whether or not the difference (distance indicating the difference) between the theoretical impedance value calculated by the logical formula A and the impedance value after the measurement data has been corrected using the logical formula A is less than a predetermined threshold. Whether or not the fitting process for the measurement data was successful is determined according to a determination criterion based on the degree of fitting, such as whether or not the number (or percentage) of impedance values ​​for which fitting failed is less than a predetermined number, or whether or not the total difference (distance indicating the difference) between the theoretical impedance value calculated by the logical formula A and the impedance value after the measurement data has been corrected using the logical formula A is calculated for each frequency and whether or not the total difference is less than a predetermined value.

[0041] If it is determined that the fitting process using logical formula A has failed (S13: NO), the control unit 11 performs a fitting process using the above-mentioned logical formula B on the measurement data (S14) and determines whether the fitting process was successful (S15). Steps S14 to S15 are the same as steps S12 to S13, except for the logical formula used in the fitting. FIG. 5B shows an example of the results of the fitting process using logical formula B. In FIG. 5B, the small dots, dashed curves, large dots, and crosses represent the same elements as in FIG. 5A. If it is determined that the fitting process using logical formula B has failed (S15: NO), the control unit 11 discards the measurement data as data for which measurement has failed (S16). In the process shown in FIG. 4, if a measurement fails in one measurement process, the process ends, but the process may return to step S11 and the measurement may be performed again.

[0042] If it is determined that the fitting process using Logical Formula A has been successful (YES in S13), or if it is determined that the fitting process using Logical Formula B has been successful (YES in S15), the control unit 11 performs a process of determining whether the shape of the Cole-Cole curve indicated by the function obtained by the successful fitting process (hereinafter referred to as the optimal Cole-Cole curve) satisfies predetermined compatibility conditions (S17). The compatibility conditions include at least a first condition related to at least one parameter in the obtained function, a second condition related to the similarity between a series of plot points obtained by plotting the measurement data on a complex plane and the optimal Cole-Cole curve, and a third condition related to a compatibility point group (a plot point group of impedance values ​​for which the fitting was successful) along the optimal Cole-Cole curve among the series of plot points.

[0043] The first condition includes, for example, the following two conditions: (1) The values ​​of the parameters R0 and R∞ in the logical formula are positive numbers; and (2) The value of the parameter Td is equal to or greater than a predetermined threshold value (for example, a value between 0 and −5).

[0044] The second condition includes, for example, the following two conditions: (1) The proportion of the plot points (suitable points) of impedance values ​​that have been successfully fitted in the measurement data (a series of plot points) is equal to or greater than a predetermined threshold; and (2) The sum of the distances of the plot points that make up the suitable points from the optimal Cole-Cole curve is equal to or less than a predetermined threshold.

[0045] The third condition includes, for example, the following two conditions: (1) the trajectory formed by the matching point group crosses the peak of the optimal Cole-Cole curve, and (2) the coverage rate of the trajectory with respect to the optimal Cole-Cole curve is equal to or greater than a predetermined threshold.

[0046] For example, the control unit 11 determines whether a first condition is satisfied: that the values ​​of parameters R0 and R∞ of the function (logical formula A or B) obtained by a successful fitting process are both positive numbers, and that the value of parameter Td is equal to or greater than a predetermined threshold. The control unit 11 also determines whether a second condition is satisfied: that the proportion of the relevant point group in the measurement data is equal to or greater than a predetermined threshold, and that the sum of the distances of each plot point constituting the relevant point group from the optimal Cole-Cole curve is equal to or less than a predetermined threshold. The control unit 11 also determines whether a third condition is satisfied: that the trajectory of the relevant point group crosses the peak of the optimal Cole-Cole curve, and that the coverage rate of the trajectory of the optimal Cole-Cole curve is equal to or greater than a predetermined threshold. If the control unit 11 determines that all of the first to third conditions are satisfied, it determines that the shape of the optimal Cole-Cole curve indicated by the function obtained by a successful fitting process satisfies the fitting conditions. On the other hand, if the control unit 11 determines that any one of the first to third conditions is not satisfied, it determines that the shape of the optimal Cole-Cole curve does not satisfy the compatibility condition.

[0047] As a second condition regarding the similarity between the plot points plotted on a complex plane and the optimal Cole-Cole curve, the control unit 11 may estimate the similarity between the plot points and the optimal Cole-Cole curve using a learning model trained by machine learning to estimate the similarity between the plot points and the optimal Cole-Cole curve from an image of a complex plane including the plot points and the optimal Cole-Cole curve, as shown in Figures 5A to 6C. Regarding the third condition regarding the matched points along the optimal Cole-Cole curve, the control unit 11 may determine whether each condition is satisfied using a learning model trained by machine learning to estimate the positional relationship between the plot points and the optimal Cole-Cole curve from an image of a complex plane including the plot points and the optimal Cole-Cole curve.

[0048] 6A to 6C show examples where the compatibility condition is not met. In FIG. 6A, the value of the parameter Td is negative due to the positional relationship between the measurement data on the complex plane and the measurement data corrected by the function (logical expression). In this case, the first condition that the value of the parameter Td is equal to or greater than a predetermined threshold (e.g., 0) is not met, and therefore the compatibility condition is determined to be not met. In FIG. 6B, the measurement data on the low frequency side and the measurement data on the high frequency side fit the optimal Cole-Cole curve, but the measurement data at medium frequencies do not fit the optimal Cole-Cole curve, resulting in a low proportion of the compatible points. In this case, the second condition that the proportion of the compatible points is equal to or greater than a predetermined threshold is not met, and therefore the compatibility condition is determined to be not met. Note that in the example of FIG. 6B, it can also be determined that the condition that the sum of the distances of each plot point of the compatible points from the optimal Cole-Cole curve is equal to or less than a predetermined threshold is not met. In FIG. 6C, the trajectory of the compatible points does not cross the peak of the optimal Cole-Cole curve. In this case, the third condition, that the trajectory formed by the group of relevant points crosses the vertex of the optimal Cole-Cole curve, is not satisfied, and therefore it is determined that the relevant condition is not satisfied. In the example of FIG. 6C , the coverage rate of the optimal Cole-Cole curve of the trajectory is low, so it can also be determined that the condition that the coverage rate of the optimal Cole-Cole curve of the trajectory is equal to or greater than a predetermined threshold is not satisfied. The coverage rate of the optimal Cole-Cole curve of the trajectory may be expressed as the angle (indicated by the arrows in FIG. 6C ) formed by the line segments connecting each end of the group of relevant points to the center 0 after normalizing the optimal Cole-Cole curve to a semicircle with a radius of 1 and its central axis at 0, as shown in FIG. 6C . In this case, the third condition may be that the calculated angle is equal to or greater than a predetermined threshold.

[0049] The above-described matching conditions are not limited to the configuration used in the determination process of step S17. For example, among the matching conditions, the first condition (2) that the value of the parameter Td is equal to or greater than a predetermined threshold (first sub-condition) and the third condition (1) that the trajectory formed by the matching point group crosses the peak of the optimal Cole-Cole curve (second sub-condition) may be used as fitting conditions (applying conditions) to determine whether the fitting process of steps S13 and S15 was successful. In this case, in step S17, the control unit 11 determines whether the first condition (1), the second condition, and the third condition (2) of the matching conditions are satisfied. In this configuration, if it is determined that the fitting process has failed based on the fitting conditions, it can determine that the matching conditions are not satisfied and terminate the process without determining conditions other than the fitting conditions, thereby improving processing efficiency.

[0050] Based on the result of the judgment process in step S17, the control unit 11 determines whether the shape of the optimal Cole-Cole curve obtained by the fitting process satisfies the compatibility conditions (S18). If it determines that the shape does not satisfy the compatibility conditions (S18: NO), the control unit 11 proceeds to step S16. That is, if the optimal Cole-Cole curve does not satisfy the compatibility conditions, the control unit 11 discards the measurement data. If it determines that the compatibility conditions are satisfied (S18: YES), the control unit 11 acquires the measurement results (S19). For example, the control unit 11 acquires the values ​​of the parameters R0, R∞, and Td in the obtained function as the measurement results. The control unit 11 then reads the measurement results from the nth measurement to the most recent measurement results stored in the patient DB 12a and calculates a representative value of each parameter based on the read measurement results and the measurement results acquired in step S19 (S20). The representative value can be, for example, the median, mean, mode, etc. The number of measurement results (n) used to calculate the representative value may be set based on a predetermined number of measurements or a predetermined period. In this case, all the measurement results measured during a predetermined period are read out, and a representative value is calculated based on the measurement results acquired in step S19.

[0051] The control unit 11 sets the date and time when the measurement data was acquired in step S11 as the measurement date and time, and stores the calculated representative value in the patient DB 12a as the measurement result, corresponding to the measurement date and time (S21). The control unit 11 may store only the measurement results in the patient DB 12a when the bioimpedance measurement results are acquired, or may calculate (generate) body composition information for the patient using the measurement results and the patient's physical information, and store the body composition information in the patient DB 12a as well. Note that when only the measurement results are stored in the patient DB 12a, the body composition monitor 10 may send the bioimpedance measurement results stored in the patient DB 12a to another device, such as an electronic medical record server, and the other device may calculate the patient's body composition information.

[0052] When bioimpedance measurement is performed using the above-described process, a fitting process using multiple logical expressions identifies a function that indicates an optimal Cole-Cole curve that best fits a series of plot points obtained by plotting measurement data on a complex plane. Therefore, it is possible to identify the logical expression with the highest degree of fit among the multiple logical expressions, and by using such a logical expression to obtain bioimpedance measurement results, highly accurate measurement results can be obtained. Furthermore, when identifying the function that indicates the optimal Cole-Cole curve, it is determined whether the optimal Cole-Cole curve satisfies compatibility conditions, including a first condition related to the parameters of the identified function, a second condition related to the similarity between the series of plot points and the optimal Cole-Cole curve, and a third condition related to the compatibility points along the optimal Cole-Cole curve. If it is determined that the compatibility conditions are not satisfied, the measurement data is discarded as noise data. Therefore, measurement data that fails to be measured due to factors such as the posture or state of the body composition monitor 10 being worn is discarded, thereby avoiding the acquisition of inappropriate bioimpedance measurement results.

[0053] Furthermore, after obtaining a function representing the optimal Cole-Cole curve, the system determines whether the geometric shape of the optimal Cole-Cole curve satisfies predetermined fitting conditions. If it does not, the measurement data is discarded as noise data. Therefore, even if the fitting process is successful, which would normally be considered a failure, the measurement data is discarded if the shape of the optimal Cole-Cole curve does not satisfy the predetermined fitting conditions, thereby avoiding the acquisition of erroneous bioimpedance measurement results. Cases in which the shape of the optimal Cole-Cole curve does not satisfy the fitting conditions may occur, for example, when the measurement data can be fitted to multiple Cole-Cole curves. By excluding such measurement data from the processing target, measurement accuracy is improved. Furthermore, because the measurement result is a representative value calculated from measurement results obtained a predetermined number of times or over a predetermined period, variation in measurement results due to the patient's condition at the time of measurement is reduced, resulting in more accurate measurement results (bioimpedance and body composition information).

[0054] The body composition monitor 10 of this embodiment is a wearable device that simply needs to be worn by the patient. The patient does not need to be aware of the bioimpedance measurement process, reducing the burden and allowing for increased measurement frequency. Increasing the number of measurements allows for more accurate measurement results (bioimpedance and body composition information) of the patient's biological condition. FIG. 7 illustrates the effects of measurement results obtained using the body composition monitor 10 of this embodiment. The graph in FIG. 7 shows time on the horizontal axis and the R∞ (Rinf) value from the measurement results on the vertical axis, illustrating the change in R∞ over time. The thick solid line in FIG. 7 illustrates the measurement results using the body composition monitor 10 of this embodiment, demonstrating that a stable value was measured for R∞, which indicates the total bioresistance. The thin solid line in FIG. 7 illustrates the measurement results based on a function representing a Cole-Cole curve obtained by fitting the bioimpedance data measured by the measurement unit 16 without performing the processing performed by the body composition monitor 10 of this embodiment. It can be seen that an unstable value containing noise was measured for R∞. In the measurement results shown by the thin solid line, there is a large variation in the measurement results depending on the timing of the measurement, making it difficult to obtain measurement results that accurately measure the patient's condition. In contrast, the body composition monitor 10 of this embodiment can obtain measurement results that accurately measure the patient's condition.

[0055] In the body composition monitor 10 of this embodiment, bioimpedance measurement processing is performed, for example, every few minutes to 10 minutes, and as described above, measurement data that is inappropriate is discarded. Therefore, measurement data that failed to be measured is automatically identified and excluded from processing, thereby obtaining measurement data with reduced variation due to noise, etc. Furthermore, because measurement data that failed to be measured is discarded, restrictions such as the patient's posture during measurement are unnecessary. Therefore, the body composition monitor 10 can perform measurements at any timing, and by increasing the number of measurements and discarding inappropriate measurement data, the accuracy of the measurement data can be improved. It is believed that each patient has a time period during the day when they are in an appropriate posture and state for measuring bioimpedance. Therefore, by discarding measurement data in an inappropriate state and using measurement data in an appropriate state, highly accurate measurement results can be obtained using measurement data with reduced noise.

[0056] In this embodiment, in the process of determining whether the optimal Cole-Cole curve indicated by the function obtained by the fitting process satisfies the compatibility conditions, the order of execution of the determination process for each condition included in the compatibility conditions can be changed as appropriate. For example, it is determined whether condition (2) of the first condition (the condition that the value of the parameter Td is equal to or greater than a predetermined threshold) is satisfied, and if satisfied, it is determined whether condition (2) of the second condition (the condition that the sum of the distances of each plot point of the compatibility point group from the optimal Cole-Cole curve is equal to or less than a predetermined threshold) is satisfied, and if satisfied, it is determined whether condition (1) of the third condition (the condition that the trajectory of the compatibility point group straddles the peak of the optimal Cole-Cole curve) is satisfied, and if satisfied, it is determined whether condition (2) of the third condition (the condition that the trajectory of the compatibility point group straddles the peak of the optimal Cole-Cole curve) is satisfied, and if satisfied, it is determined whether condition (1 .... It is also possible to determine whether condition (1) in the first condition (the condition that the proportion of the relevant point group is equal to or greater than a predetermined threshold) is satisfied, and if so, determine whether condition (2) in the third condition (the condition that the coverage rate of the optimal Cole-Cole curve of the trajectory of the relevant point group is equal to or greater than a predetermined threshold) is satisfied, and if so, determine whether condition (1) in the first condition (the condition that the values ​​of parameters R0 and R∞ are positive numbers) is satisfied, and if so, determine that the optimal Cole-Cole curve satisfies the relevant conditions. Note that if it is determined that any of the conditions is not satisfied, it can be determined that the optimal Cole-Cole curve does not satisfy the relevant conditions, and the process of determining the relevant conditions can be terminated at that point.

[0057] Furthermore, the judgment process for each condition included in the compatibility conditions may be performed in parallel. By first performing the judgment process for condition (2) in the first condition and condition (2) in the third condition as fitting conditions (applied conditions), judgment results can be obtained early for measurement data that clearly does not satisfy the compatibility conditions, thereby efficiently reducing the overall calculation volume. In particular, when performing fitting processes using multiple logical formulas, the judgment process for the fitting conditions can be used to confirm whether each logical formula can be used, thereby enabling efficient judgment processes. Furthermore, when performing fitting processes using multiple logical formulas, the judgment process for each logical formula to determine whether the compatibility conditions are satisfied can be performed in parallel, making it possible to adopt logical formulas that perform well in the judgment process.

[0058] In the first embodiment described above, body composition monitor 10 attached to a patient identifies an optimal Cole-Cole curve function based on a series of periodically measured bioimpedance data, obtains estimated values ​​related to body composition (parameters R0, R∞, etc.) based on the identified function, and generates body composition information using the obtained estimated values. Alternatively, body composition monitor 10 may be configured to only periodically measure a series of bioimpedance data. In this case, body composition monitor 10 may transmit the measured series of bioimpedance data to another information processing device, and the other information processing device (computer) may identify an optimal Cole-Cole curve function, obtain estimated values ​​related to body composition (parameters R0, R∞, etc.) based on the identified function, and generate body composition information using the obtained estimated values. Even in this case, the same processing as in the present embodiment is possible, and the same effects can be obtained.

[0059] Second Embodiment A modified example of the bioimpedance measurement process will be described. The body composition monitor 10 of this embodiment has the same configuration as the body composition monitor 10 of the first embodiment shown in FIG. 1, and therefore a description of the configuration of the body composition monitor 10 will be omitted.

[0060] 8 is a flowchart showing an example of a measurement process procedure according to the second embodiment. When the measurement timing arrives, the control unit 11 of this embodiment acquires measurement data using the measurement unit 16 (S31). Here, too, the control unit 11 acquires a series of bioimpedance data corresponding to each frequency in one measurement process.

[0061] Next, the control unit 11 performs a fitting process using logical formula A on the acquired measurement data and a determination process to determine whether the shape of the optimal Kohl-Cole curve indicated by the function obtained by the fitting process satisfies the matching conditions (S32). The control unit 11 then determines whether the fitting process is successful and whether the shape of the optimal Kohl-Cole curve indicated by the function obtained by the successful fitting process satisfies the matching conditions (S33). Steps S32 and S33 include the processes of steps S12 to S13 and S17 to S18 in FIG. 4. Specifically, the control unit 11 searches for a function that provides an optimal Kohl-Cole curve that is most suitable for a series of plot points obtained by plotting the measurement data on a complex plane while changing each parameter of logical formula A through the fitting process, and determines whether the shape of the found optimal Kohl-Cole curve satisfies the matching conditions. Here, too, the control unit 11 determines whether the matching conditions, including the first to third conditions described in the first embodiment, are satisfied. The control unit 11 then acquires an optimal Kohl-Cole curve that satisfies the matching conditions.

[0062] If the fitting process fails, or if it is determined that the shape of the optimal Cole-Cole curve obtained by a successful fitting process does not satisfy the matching conditions (S33: NO), the control unit 11 performs a fitting process using logical formula B on the acquired measurement data and a determination process of whether or not the shape of the optimal Cole-Cole curve indicated by the function obtained by the fitting process satisfies the matching conditions (S37), and then determines whether or not the fitting process is successful and the shape of the optimal Cole-Cole curve indicated by the function obtained by the successful fitting process satisfies the matching conditions (S38). Steps S37 and S38 are the same processes as steps S32 to S33, except for the logical formula used for fitting.

[0063] If the controller 11 determines that the fitting process using logical formula A is successful and that the shape of the optimal Cole-Cole curve represented by the obtained function satisfies the compatibility condition (S33: YES), or if the controller 11 determines that the fitting process using logical formula B is successful and that the shape of the optimal Cole-Cole curve represented by the obtained function satisfies the compatibility condition (S38: YES), the controller 11 executes the same processes as steps S19 to S21 in Fig. 4 (S34 to S36). As a result, the controller 11 acquires the values ​​of the parameters R0, R∞, and Td in the obtained function as measurement results (S34), calculates a representative value of each parameter based on the measurement results from the nth measurement back to the most recent measurement stored in the patient DB 12a and the measurement result acquired in step S34 (S35), and stores the calculated representative value as the measurement result in the patient DB 12a in association with the measurement date and time of the measurement data (S36).

[0064] If the fitting process using logical formula B fails, or if it is determined that the shape of the optimal Cole-Cole curve obtained by the successful fitting process does not satisfy the compatibility conditions (S38: NO), the control unit 11 discards the measurement data (S39). Note that if the measurement fails in one measurement process, the control unit 11 may return to step S31 and perform the measurement again.

[0065] The above-described processing allows the present embodiment to achieve the same effects as those of the first embodiment. Also, in the present embodiment, in the process of determining whether the optimal Cole-Cole curve obtained by the fitting process satisfies the compatibility conditions, the order in which the determination processes for each condition included in the compatibility conditions are executed can be changed as appropriate. Therefore, by performing the determination processes for each condition in an appropriate order, the determination process can be terminated when it is determined that any of the conditions is not satisfied, thereby efficiently reducing the overall calculation volume. Furthermore, each determination process may be executed in parallel. Note that the modified examples described in the first embodiment can also be applied to this embodiment.

[0066] Third Embodiment A modified example of the bioimpedance measurement process will be described. The body composition monitor 10 of this embodiment has the same configuration as the body composition monitor 10 of the first embodiment shown in FIG. 1, and therefore a description of the configuration of the body composition monitor 10 will be omitted.

[0067] 9 is a flowchart showing an example of a measurement processing procedure according to the third embodiment. After the control unit 11 acquires measurement data using the measurement unit 16 (S41), the control unit 11 performs a fitting process using logical formula A on the acquired measurement data and a determination process of whether the shape of the optimal Kohl-Cole curve indicated by the function obtained by the fitting process satisfies the compatibility condition (S42), and then performs a fitting process using logical formula B and a determination process of whether the shape of the optimal Kohl-Cole curve indicated by the function obtained by the fitting process satisfies the compatibility condition (S43). Steps S42 and S43 are the same as steps S32 and S37 in FIG. 8. Steps S42 and S43 may be performed in parallel, or their order may be reversed.

[0068] The control unit 11 determines whether the fitting process is successful for logical formula A and logical formula B and whether the shape of the optimal Cole-Cole curve indicated by the function obtained by the successful fitting process satisfies the compatibility condition (S44). If the fitting process fails for at least one of logical formula A and logical formula B, or if it is determined that the shape of the optimal Cole-Cole curve obtained by the successful fitting process does not satisfy the compatibility condition (S44: NO), the control unit 11 discards the measurement data (S45). In this case, the control unit 11 may also return to step S41 and perform measurement again without terminating the process.

[0069] If the control unit 11 determines that the fitting process is successful for both Logical Formula A and Logical Formula B and that the shape of the optimal Cole-Cole curve indicated by the function obtained by the successful fitting process satisfies the matching condition (S44: YES), it selects the Logical Formula A or B that fits the measurement data obtained by the fitting process to a higher degree, i.e., the more suitable Logical Formula (S46). A logical formula with a higher degree of fitting may be, for example, a logical formula in which the matching point group accounts for a higher proportion of the matching points in the second condition (1) of the matching conditions described above, a logical formula in which the sum of the distances of each plot point of the matching point group from the optimal Cole-Cole curve is smaller in the second condition (2), or a logical formula in which the trajectory of the matching point group covers the optimal Cole-Cole curve to a higher degree in the third condition (2). The control unit 11 then executes the same processes as steps S19 to S21 in FIG. 4 (S47 to S49). As a result, the control unit 11 stores the representative values ​​of the parameters R0, R∞, and Td as measurement results in the patient DB 12a in association with the measurement date and time of the measurement data. Note that in step S47, the control unit 11 acquires the values ​​of the parameters R0, R∞, and Td in the function specified based on the logical expression selected in step S46 as measurement results.

[0070] The above-described processing allows the present embodiment to achieve the same effects as those of the first embodiment. Also, in the present embodiment, in the process of determining whether the optimal Cole-Cole curve obtained by the fitting process satisfies the compatibility conditions, the order in which the determination processes for each condition included in the compatibility conditions are executed can be changed as appropriate. Therefore, by performing the determination processes for each condition in an appropriate order, the determination process can be terminated when it is determined that any of the conditions is not satisfied, thereby efficiently reducing the overall calculation volume. Furthermore, each determination process may be executed in parallel. Note that the modified examples described in the first and second embodiments can also be applied to this embodiment.

[0071] (Embodiment 4) A modified example of the bioimpedance measurement process will be described. The body composition monitor 10 of this embodiment has the same configuration as the body composition monitor 10 of embodiment 1 shown in Fig. 1, so a description of the configuration of the body composition monitor 10 will be omitted. In this embodiment, a fitting process is performed using one logical formula.

[0072] 10 is a flowchart showing an example of a measurement processing procedure according to the fourth embodiment. After acquiring measurement data using the measurement unit 16 (S51), the control unit 11 of this embodiment performs a fitting process using one logical formula on the acquired measurement data, and a determination process to determine whether the shape of the optimal Kohl-Cole curve indicated by the function obtained by the fitting process satisfies the compatibility condition (S52). Here, either logical formula A or logical formula B used in the first to third embodiments is used. Note that other logical formulas may also be used.

[0073] The control unit 11 determines whether the fitting process is successful and whether the shape of the optimal Cole-Cole curve indicated by the function obtained by the successful fitting process satisfies the compatibility condition (S53). If the fitting process fails or if it is determined that the shape of the optimal Cole-Cole curve obtained by the successful fitting process does not satisfy the compatibility condition (S53: NO), the control unit 11 discards the measurement data (S57). In this case, the control unit 11 may also return to step S51 and perform measurement again without terminating the process.

[0074] If the controller 11 determines that the fitting process is successful and that the shape of the optimal Cole-Cole curve indicated by the function obtained by the successful fitting process satisfies the compatibility condition (S53: YES), it executes the same processes as steps S19 to S21 in Fig. 4 (S54 to S56). As a result, the controller 11 stores the representative values ​​of the parameters R0, R∞, and Td as measurement results in the patient DB 12a, in association with the measurement date and time of the measurement data.

[0075] The above-described process achieves the same effects as in the first embodiment. While the present embodiment is configured to perform fitting using a single logical formula, the measurement data is determined to be noise data based on whether the fitting process is successful and whether the optimal Cole-Cole curve satisfies the matching conditions. If the measurement data is determined to be noise data, it is discarded. This allows only properly measured measurement data to be processed. This enables highly accurate bioimpedance measurement. Also in this embodiment, the order of execution of the determination process for each condition included in the matching conditions in the process of determining whether the optimal Cole-Cole curve obtained by the fitting process satisfies the matching conditions can be appropriately changed. Therefore, by performing the determination process for each condition in an appropriate order, the determination process can be terminated when it is determined that any of the conditions is not satisfied, thereby efficiently reducing the overall calculation volume. Furthermore, each determination process may be executed in parallel. The modifications described in the first to third embodiments can also be applied to this embodiment.

[0076] (Embodiment 5) In the above-described embodiments 1 to 4, body composition monitor 10 periodically performs a measurement process for bioimpedance data, identifies an optimal Cole-Cole curve function based on the measurement results, obtains an estimated value related to body composition based on the identified function, and performs a process for generating body composition information using the obtained estimated value. This embodiment describes an information processing system in which body composition monitor 10 only performs a measurement process and transmits the measurement results together with the measurement date and time to an information processing device, and the information processing device identifies the optimal Cole-Cole curve function, obtains an estimated value related to body composition based on the identified function, and generates body composition information using the obtained estimated value.

[0077] FIG. 11 is an explanatory diagram showing an example of the configuration of an information processing system according to a fifth embodiment. The information processing system according to this embodiment includes a body composition monitor 10 worn on the arm or the like of a subject P1, an information processing device 20, and a terminal device 30, and these devices are communicatively connected via a network N. The network N may be the Internet, a public telephone network, a dedicated line, or a local area network (LAN) established within a facility where the information processing system is installed. The body composition monitor 10 according to this embodiment has the same configuration as the body composition monitor 10 according to the first embodiment shown in FIG. 1 , but may not include the input unit 14 and the display unit 15, and the patient DB 12a may not be stored in the memory unit 12. The information processing device 20 is a computer capable of various information processing and information transmission / reception, such as a server computer or a personal computer. The information processing device 20 receives measurement data measured by the body composition monitor 10, identifies an optimal Cole-Cole curve function based on the received measurement data, obtains an estimated value for body composition based on the identified function, and generates body composition information using the obtained estimated value. The terminal device 30 is a terminal used by a medical professional P2 such as a doctor. The terminal device 30 is a computer capable of various information processing and information transmission and reception, such as a personal computer, tablet terminal, or smartphone. The information processing device 20 transmits the generated body composition information to the terminal device 30, and the terminal device 30 displays the received body composition information to present the results of measurement using the body composition analyzer 10 to the medical professional P2. A plurality of body composition analyzers 10 and / or terminal devices 30 may be provided.

[0078] FIG. 12 is a block diagram showing an example configuration of the information processing device 20 and the terminal device 30. The information processing device 20 includes a control unit 21, a memory 22 that stores temporary data generated during calculations, a storage unit 23, a reading unit 24, and a communication unit 25. The control unit 21 has one or more processors such as a CPU, an MPU, a GPU, or a multi-core CPU. The control unit 21 may be configured using a quantum computer. When the control unit 21 has multiple processors, each process may be executed by a different processor. The memory 22 is, for example, a RAM. The storage unit 23 is nonvolatile, for example, a hard disk or a nonvolatile semiconductor memory. The reading unit 24 reads information from a recording medium 20a such as an optical disk or a portable memory. The communication unit 25 communicates with the outside of the information processing device 20. Specifically, the communication unit 25 communicates with the body composition monitor 10 and the terminal device 30 via a network N.

[0079] The control unit 21 causes the reading unit 24 to read a program (program product, computer program) 23P recorded on the recording medium 20a and stores the read program 23P in the memory unit 23. The control unit 21 executes processing to realize the functions of the information processing device 20 in accordance with the program 23P. The program 23P may be stored in the memory unit 23 in advance or downloaded from outside the information processing device 20. In this case, the information processing device 20 does not need to include the reading unit 24. The memory unit 23 stores a patient DB 23a. The memory unit 23 may be composed of multiple storage devices, and some of the storage devices may be other storage devices connected to the information processing device 20 or other storage devices with which the information processing device 20 can communicate. The information processing device 20 may be configured to include an input unit that accepts operational inputs from a user (e.g., a medical professional) and a display unit such as a liquid crystal display.

[0080] In this embodiment, the information processing device 20 is not limited to a single computer, but may be a multi-computer consisting of multiple computers, or may be a virtual machine virtually constructed by software within a single device. The information processing device 20 may also be a local server installed in a facility where an information processing system is installed, or a cloud server connected to the information processing system via a network N. The program 23P may be deployed and executed on a single computer or at one site, or may be distributed across multiple sites and deployed to be executed on multiple computers interconnected via the network N.

[0081] The terminal device 30 includes a control unit 31, a memory 32, a reading unit 33, a storage unit 34, an input unit 35, a display unit 36, and a communication unit 37. The control unit 31, the memory 32, the reading unit 33, the storage unit 34, and the communication unit 37 are similar in configuration to the control unit 21, the memory 22, the reading unit 24, the storage unit 23, and the communication unit 25 of the information processing device 20, and therefore detailed description thereof will be omitted. The input unit 35 accepts operation inputs from a user (e.g., medical professional P2) and sends control signals corresponding to the operation content to the control unit 31. The display unit 36 ​​is a liquid crystal display, an electroluminescent display (EL display), or the like, and displays various information in accordance with instructions from the control unit 31. The input unit 35 and the display unit 36 ​​may be integrated into a touch panel. Note that the input unit 35 and the display unit 36 ​​are not required, and the terminal device 30 may be configured to accept operations via another device connected for communication and output the information to be displayed to another display device for display.

[0082] 13 is an explanatory diagram showing an example of the record layout of the patient DB 23a stored in the information processing device 20. The patient DB 23a has a configuration similar to that of the patient DB 12a shown in FIG. 3, and further includes measurement data (a series of bioimpedance data) obtained by bioimpedance measurement using the body composition monitor 10 in the measurement information stored in the measurement information sequence.

[0083] In this embodiment, body composition monitor 10 periodically performs a bioimpedance measurement process and registers the measurement results in information processing device 20. Fig. 14 is a flowchart showing an example of the measurement result registration process procedure. In Fig. 14, the left side shows the process performed by control unit 11 of body composition monitor 10, and the right side shows the process performed by control unit 21 of information processing device 20. Body composition monitor 10 of this embodiment stores identification information (patient ID) of the patient to whom body composition monitor 10 is attached in memory unit 12.

[0084] When the body composition monitor 10 of this embodiment is attached to a patient's body and an instruction to start operation is given, the body composition monitor 10 starts a bioimpedance measurement process. The control unit 11 of the body composition monitor 10 executes the bioimpedance measurement process at predetermined intervals, such as every five minutes, and acquires measurement data (bioimpedance data) using the measurement unit 16 (S61). After acquiring the measurement data, the control unit 11 transmits the patient ID, the measurement date and time (measurement date and time), and the measurement data to the information processing device 20 (S62). The control unit 21 of the information processing device 20 receives the patient ID, measurement date and time, and measurement data transmitted from the body composition monitor 10 (S63) and stores the measurement date and time and measurement data in the patient DB 23a in association with the patient ID (S64). The body composition monitor 10 transmits the acquired measurement data to the information processing device 20 each time it acquires measurement data, and the information processing device 20 stores the received measurement data in the patient DB 23a each time it receives measurement data from the body composition monitor 10. As a result, measurement data periodically measured by the body composition monitor 10 is accumulated in the information processing device 20 .

[0085] The control unit 21 of the information processing device 20 of this embodiment can execute processing similar to that shown in FIG. 4 . In step S11 of FIG. 4 , the control unit 21 acquires measurement data measured by the body composition monitor 10 from the measurement data of each patient stored in the patient DB 23a. The other steps are similar to those of the first embodiment. Therefore, the information processing device 20 of this embodiment can calculate representative values ​​of the measurement results (parameters R0, R∞, and Td) based on the measurement data acquired from the patient DB 23a in step S11 and store the representative values ​​in the patient DB 23a. Therefore, in this embodiment as well, the information processing device 20 can present a graph showing the time change in the measurement results (parameter Rinf in FIG. 7 ) as shown in FIG. 7 , based on the measurement results stored in the patient DB 23a.

[0086] Although the information processing system of this embodiment has been described as a modification of embodiment 1, the configuration of this embodiment can also be applied to embodiments 2 to 4, and similar effects can be obtained when applied to embodiments 2 to 4. When applied to embodiment 2, the control unit 21 of the information processing device 20 simply acquires the measurement data measured by the body composition monitor 10 from the measurement data of each patient stored in the patient DB 23a in step S31 of FIG. 8. When applied to embodiment 3, the control unit 21 of the information processing device 20 simply acquires the measurement data measured by the body composition monitor 10 from the measurement data of each patient stored in the patient DB 23a in step S41 of FIG. 9. When applied to embodiment 4, the control unit 21 of the information processing device 20 simply acquires the measurement data measured by the body composition monitor 10 from the measurement data of each patient stored in the patient DB 23a in step S51 of FIG. 10. The modifications described as appropriate in embodiments 1 to 4 can also be applied to this embodiment.

[0087] (Embodiment 6) In the above-described embodiments 1 to 5, a configuration has been described as an example in which a graph showing the time variation of the parameter Rinf, as shown in FIG. 7, is presented as a measurement result by the body composition monitor 10. This embodiment describes an information processing system that calculates body composition information of a patient from parameters of the measurement result and presents the body composition information. While this embodiment will be described as a modification of embodiment 5, the configuration of this embodiment is of course also applicable to embodiments 1 to 4. The information processing system of this embodiment can be realized using devices similar to those of the information processing system of embodiment 5 shown in FIGS. 11 and 12, and therefore a description of each device will be omitted.

[0088] Fig. 15 is a flowchart showing an example of a bioimpedance measurement process procedure according to embodiment 6. The process shown in Fig. 15 is the process shown in Fig. 4 with steps S71 and S72 added instead of steps S20 and S21. Explanation of the same steps as in Fig. 4 will be omitted.

[0089] After processing step S19, the control unit 21 of the information processing device 20 of this embodiment acquires body composition information of the patient based on the measurement results (values ​​of parameters R0, R∞, etc.) acquired in step S19 and the patient's physical information stored in the patient DB 23a (S71). The body composition information may be, for example, extracellular water volume (extracellular fluid volume), intracellular water volume (intracellular fluid volume), total body water volume, hydration rate, extracellular water ratio, etc., but is not limited to these. Calculation formulas for calculating each value of the body composition information from the measurement results and physical information are pre-set and stored in the memory unit 23. The control unit 21 retrieves the calculation formula for the body composition information to be calculated from the memory unit 23 and acquires each value of the body composition information by substituting the measurement results and physical information into the calculation formula.

[0090] The control unit 21 stores the measurement results acquired in step S19 and the body composition information acquired in step S71 in the patient DB 23a in association with the patient ID of the patient and the measurement date and time of the measurement data acquired in step S11 (S72). As a result, the measurement results identified from the measurement data of each patient and the body composition information identified from the measurement results are stored in the patient DB 23a as shown in FIG.

[0091] The following describes the process by which the information processing device 20 presents a time-series graph showing the time change of body composition information stored in the patient DB 23a to a medical professional. Fig. 16 is a flowchart showing an example of the process procedure for presenting a time-series graph of body composition information, and Figs. 17A and 17B are explanatory diagrams showing example screens. In Fig. 16, the left side shows the process performed by the control unit 31 of the terminal device 30, and the right side shows the process performed by the control unit 21 of the information processing device 20. The information processing device 20 performs the process of Fig. 15 at appropriate times, thereby storing body composition information of each patient in the patient DB 23a in association with the measurement date and time.

[0092] When a medical professional wishes to check the body composition status of a patient, the medical professional selects the patient to be diagnosed and the body composition information (e.g., extracellular water) to be checked via the input unit 35 of the terminal device 30. The control unit 31 of the terminal device 30 accepts the selection of the patient and the body composition information via the input unit 35 (S81). The control unit 31 transmits the patient ID of the selected patient and the type of body composition information (e.g., name) to the information processing device 20 (S82), and requests the body composition information of the patient.

[0093] The control unit 21 of the information processing device 20 acquires the patient ID and the type of body composition information from the terminal device 30, and acquires each value of the acquired body composition information along with the measurement date and time from the body composition information stored in the patient DB 23a in association with the acquired patient ID (S83). For example, the control unit 21 acquires each value of the body composition information measured over a predetermined period (e.g., two weeks) from this point in time. The control unit 21 calculates a representative value of the body composition information for each day based on each value of the acquired body composition information (S84). For example, the control unit 21 defines 0:00 to 24:00 as one day and calculates a representative value of the body composition information for each measurement day. The representative value may be a median, average, mode, or the like. The control unit 21 associates each measurement day with the representative value of the body composition information for that measurement day and stores them in the memory 22 or the storage unit 23 (S85).

[0094] The control unit 21 generates a time-series graph of body composition information, such as that shown in FIG. 17A , based on the stored representative values ​​of the body composition information for each measurement date (S86). The graph in FIG. 17A shows the change in extracellular water content over time, with the horizontal axis representing the date (measurement date) and the vertical axis representing the extracellular water content value of the body composition information. While the example in FIG. 17A shows the change in extracellular water content over time for a two-week period, the period plotted on the graph is not limited to two weeks and may be changed as desired. The control unit 21 then transmits the generated time-series graph of body composition information to the terminal device 30 (S87). The control unit 31 of the terminal device 30 then receives the time-series graph of body composition information from the information processing device 20 and displays it on the display unit 36 ​​(S88). This displays a screen such as that shown in FIG. 17A on the terminal device 30, allowing medical professionals to check the daily changes in the patient's body composition information (e.g., extracellular water content).

[0095] The time series graph of body composition information can be configured so that when a cursor is placed over a plot point or date on the graph, a pop-up display of the body composition information value for that date is displayed, as shown in FIG. 17A . Furthermore, the time series graph of body composition information can be configured so that when a selection operation is performed on a plot point or date on the graph, a detailed time series graph for the selected date and a predetermined number of days before and after the selected date is displayed. For example, if 2022 / 11 / 20 is selected on the graph of FIG. 17A , a detailed time series graph for 2022 / 11 / 20 and the three days before and after (2022 / 11 / 19 to 2022 / 11 / 21) is generated and displayed, as shown in FIG. 17B . In the example of FIG. 17B , the plotting interval of the plot points on the graph has been changed from one day to six hours. The displayed period and plotting interval of the detailed time series graph may be configured to be configurable as desired.

[0096] Below, we will explain modified examples of the screen when the information processing device 20 presents a time-series graph of a patient's body composition information to a medical professional. Fig. 18 is a flowchart showing another example of the processing procedure for presenting a time-series graph of body composition information, and Figs. 19A and 19B are explanatory diagrams showing example screens. In Fig. 18, the left side shows the processing performed by the control unit 31 of the terminal device 30, and the right side shows the processing performed by the control unit 21 of the information processing device 20.

[0097] The control unit 31 of the terminal device 30 and the control unit 21 of the information processing device 20 execute the same processes as steps S81 to S85 in FIG. 16 (S91 to S95). The control unit 21 then generates a time-series graph of body composition information for two weeks, as shown in FIG. 19A, based on the stored representative values ​​of the body composition information for each measurement date (S96). The graph in FIG. 19A is the same as the graph in FIG. 17A and shows the change in extracellular water over time for two weeks, but the plotted period is not limited to two weeks. The control unit 21 then transmits the generated time-series graph of body composition information for two weeks to the terminal device 30 (S97). The control unit 31 of the terminal device 30 then receives the time-series graph of body composition information for two weeks from the information processing device 20 and displays it on the display unit 36 ​​(S98). This displays a screen like that shown in FIG. 19A on the terminal device 30, allowing medical professionals to check the daily changes in the patient's two-week body composition information (e.g., extracellular water).

[0098] 19A has a 3-day tab, a 2-week tab, and a 4-week tab, and is configured so that by switching the tab selection, a time series graph of body composition information for 3 days, a time series graph of body composition information for 2 weeks, or a time series graph of body composition information for 4 weeks (first time series graph, second time series graph) is switched and displayed depending on the selected tab. Note that the periods that can be switched by selecting a tab are not limited to these and may be changeable as desired.

[0099] The control unit 31 of the terminal device 30 determines whether the selection of any of the tabs has been accepted (S99). If it is determined that the selection has been accepted (S99: YES), the control unit 31 transmits tab information indicating the selected tab to the information processing device 20 (S100). The control unit 31 transmits tab information indicating the 3-day tab, the 2-week tab, or the 4-week tab. When the control unit 21 of the information processing device 20 receives tab information from the terminal device 30, the control unit 21 acquires, from the patient DB 23a, each value of the body composition information selected via the terminal device 30 from the body composition information measured during the period corresponding to the received tab information, together with the measurement date and time (S101). Here, the control unit 21 acquires the body composition information values ​​for the 3-day period corresponding to the 3-day tab, the 2-week period corresponding to the 2-week tab, and the 4-week period corresponding to the 4-week tab.

[0100] Based on each value of the acquired body composition information, the control unit 21 calculates a representative value of the body composition information for each predetermined time period corresponding to the tab information (S102). For example, the control unit 21 calculates a representative value (first representative value, second representative value) of the body composition information for each six-hour period corresponding to the three-day tab, and for each day corresponding to the two-week and four-week tabs. The time span (first period, second period) for calculating the representative value is not limited to six hours or one day, but may be any time period selected from a few hours to several days, and may be arbitrarily changeable. The control unit 21 stores the calculated representative value of the body composition information for each predetermined time period in the memory 22 or the storage unit 23 in association with the measurement date and time (S103). The measurement date and time may be the first date and time, the middle date and time, or the last date and time of measurement of each value used to calculate the representative value.

[0101] The control unit 21 generates a time series graph of body composition information for the period corresponding to the tab information based on the representative values ​​of body composition information for each measurement date and time stored in step S103 (S104) and transmits the generated time series graph of body composition information to the terminal device 30 (S105). The control unit 31 of the terminal device 30 receives the time series graph of body composition information for the period corresponding to the tab information from the information processing device 20 and displays it on the display unit 36 ​​(S106). As a result, a screen such as that shown in FIG. 19B is displayed on the terminal device 30. FIG. 19B shows an example of a screen when the 3-day tab is selected. In the example of FIG. 19B, the change in extracellular water volume over three days is displayed every 6 hours. In this way, by switching tabs, medical professionals can change the period over which each value of body composition information is plotted, allowing them to check long-term and short-term changes. Furthermore, switching tabs changes the plotting period, which in turn changes the time span over which the representative value is calculated. Therefore, when presenting long-term and short-term changes over time, the plot width of each graph can be changed, making it possible to provide graphs that make it easier to grasp trends in the patient's body composition information. Similarly to the graphs in Figures 17A and 17B, the graphs in Figures 19A and 19B may be configured so that, when the cursor is placed over a plot point or date on the graph, a pop-up display of the body composition information values ​​for the selected date is displayed. Furthermore, when a selection operation is performed on a plot point or date on the graph, a detailed time series graph for a predetermined number of days before and after the selected date may be displayed.

[0102] After processing step S106, the control unit 31 of the terminal device 30 returns to step S99 and performs the processing from step S100 onward each time it receives the selection of one of the tabs. The information processing device 20 stores each measurement date and time and a representative value of the body composition information at each measurement date and time, in association with each selected tab. Therefore, when the same tab is selected two or more times, the control unit 21 may generate a time series graph using the representative value of the body composition information at each measurement date and time stored in the memory 22 or the storage unit 23. Furthermore, when the latest body composition information is stored in the patient DB 23a, the control unit 21 may generate a time series graph based on the most recent body composition information.

[0103] The embodiments disclosed herein are illustrative in all respects and should not be considered limiting. The scope of the present invention is defined by the claims, not by the meaning described above, and is intended to include all modifications within the meaning and scope of the claims. For example, the control unit 21 of the information processing device 20 may periodically, for example, at a predetermined time each day, calculate a representative value of body composition information for each predetermined time period from the measurement date and time and measurement data stored in the patient DB 23a in association with the patient ID in step S64 of FIG. 14, and store the calculated representative value of body composition information for each predetermined time period in the patient DB 23a in association with the patient ID and the measurement date and time. In this case, the control unit 21 of the information processing device 20 acquires representative values ​​of the requested body composition information together with the measurement date and time from the body composition information stored in the patient DB 23a based on the patient's body composition information requested by the terminal device 30 in step S82 in Fig. 16 or step 92 in Fig. 18, and generates a time series graph of the body composition information as shown in Fig. 17A, 17B, 19A, or 19B based on the acquired representative values ​​of the body composition information and the measurement date and time of each representative value. In this way, by calculating the representative values ​​of the body composition information for each predetermined time period in advance and storing them in the patient DB 23a, it is possible to quickly generate a time series graph of the requested representative values ​​of the body composition information in response to a request from the terminal device 30, and it is possible to shorten the time required to display the time series graph on the display unit 36 ​​of the terminal device 30.

[0104] The features described in each of the above-mentioned embodiments can be combined with each other. Furthermore, the independent claims and dependent claims described in the claims can be combined with each other in any and all combinations, regardless of the reference format. Furthermore, while the claims use a format in which a claim references two or more other claims (multiple claim format), this is not limited to this format. A multiple claim (multi-multi claim) that references at least one other multiple claim may also be used.

[0105] REFERENCE SIGNS LIST 10 Body composition monitor 11 Control unit 12 Storage unit 13 Communication unit 16 Measurement unit 20 Information processing device 21 Control unit 30 Terminal device 31 Control unit 12a Patient DB 16a Electrode unit 16b Current supply unit 16c Voltage measurement unit

Claims

1. A program that causes a computer to execute the following processes: acquire a series of bioimpedance data obtained by bioimpedance measurement; identify a function that indicates an optimal Cole-Cole curve that is most suitable for a series of plot points plotted on a complex plane with resistance on the horizontal axis and reactance on the vertical axis based on the acquired series of bioimpedance data, and based on a logical formula showing the relationship between the bioimpedance data and the parameters R0 and R∞; determine whether the series of bioimpedance data satisfies compatibility conditions that include at least the following: a predetermined first condition related to at least one parameter in the identified function; a predetermined second condition related to the similarity of the series of plot points to the optimal Cole-Cole curve; and a predetermined third condition related to a compatibility point group that follows the optimal Cole-Cole curve among the series of plot points; and if it is determined that the series of bioimpedance data satisfies the compatibility conditions, store an estimated value related to body composition obtained from the function in a memory unit; and generate body composition information based on the stored estimated value.

2. The program according to claim 1, which causes the computer to execute the following process: based on the estimated values ​​of body composition for a predetermined period stored in the memory unit, identify a representative value of the estimated values ​​for the predetermined period; and generate body composition information based on the identified representative value.

3. The program according to claim 1 or 2, wherein the logical formula includes parameters R0, R∞, and Td (a time delay correction term), and the first condition includes at least the following two conditions:

1. The parameters R0 and R∞ are positive; and 2. The parameter Td is equal to or greater than a predetermined threshold value.

4. The program according to claim 1 or 2, wherein the second condition includes at least the following two conditions:

1. The proportion of the group of relevant points in the group of plot points is equal to or greater than a predetermined threshold; and 2. The sum of the distances of each of the group of relevant points from the optimal Cole-Cole curve is equal to or less than a predetermined threshold.

5. The program according to claim 1 or 2, wherein the third condition includes at least the following two conditions:

1. A trajectory formed by the matching point group straddles a peak of the optimal Cole-Cole curve; and 2. A coverage rate of the trajectory with respect to the optimal Cole-Cole curve is equal to or greater than a predetermined threshold.

6. The program according to claim 1 or 2, which causes the computer to execute a process of discarding the series of bioimpedance data when it is determined that the series of bioimpedance data does not satisfy the compatibility condition.

7. The program according to claim 1 or 2, which causes the computer to execute the following process: the logical formula includes a parameter Td; the first condition includes a first sub-condition that at least the parameter Td is equal to or greater than a predetermined threshold value; the third condition includes a second sub-condition that a trajectory formed by the group of matching points straddles a peak of the optimal Cole-Cole curve; the matching conditions have fitting conditions including the first sub-condition and the second sub-condition; and it is determined whether the series of bioimpedance data satisfies the fitting conditions; and if it is determined that the series of bioimpedance data does not satisfy the fitting conditions, it is determined that the matching conditions are not satisfied without determining any other conditions of the matching conditions than the fitting conditions.

8. The program according to claim 1 or 2, which causes the computer to execute the following process: determine whether the series of bioimpedance data satisfies the compatibility condition based on a plurality of logical formulas prepared in advance as the logical formula; and, if it is determined that the series of bioimpedance data satisfies the compatibility condition, store the estimated value of body composition obtained from the function specified based on the logical formula from the plurality of logical formulas used when it was determined that the series of bioimpedance data satisfied the compatibility condition.

9. The program according to claim 8, which causes the computer to execute a process of discarding the series of bioimpedance data when it is determined that the series of bioimpedance data does not satisfy the compatibility condition in any of the plurality of logical expressions.

10. The program according to claim 8, which causes the computer to execute the process of identifying one logical formula from the plurality of logical formulas that satisfies the compatibility conditions and provides the best judgment result for the compatibility conditions, and storing the estimated value of body composition obtained from the function identified based on the identified one logical formula.

11. The program according to claim 8, which causes the computer to execute the following processes: each of the plurality of logical formulas includes a parameter Td; the first condition includes a first sub-condition that at least the parameter Td is equal to or greater than a predetermined threshold value; the third condition includes a second sub-condition that a trajectory formed by the group of matching points straddles a peak of the optimal Cole-Cole curve; the matching condition has a fitting condition including the first sub-condition and the second sub-condition; determining whether the series of bioimpedance data satisfies the fitting condition based on the plurality of logical formulas; if it is determined that the series of bioimpedance data satisfies the fitting condition, determining whether the series of bioimpedance data satisfies the fitting condition based on the logical formula of the plurality of logical formulas used when it was determined that the series of bioimpedance data satisfied the fitting condition; and if it is determined that the series of bioimpedance data satisfies the fitting condition, storing the estimated value of body composition obtained from the function identified based on the logical formula of the plurality of logical formulas used when it was determined that the series of bioimpedance data satisfied the fitting condition.

12. An information processing method in which a computer executes the following processes: acquiring a series of bioimpedance data obtained by bioimpedance measurement; identifying a function that indicates an optimal Cole-Cole curve that is most suitable for a series of plot points plotted on a complex plane with resistance on the horizontal axis and reactance on the vertical axis based on the acquired series of bioimpedance data, and based on a logical formula showing the relationship between the bioimpedance data and the parameters R0 and R∞; determining whether the series of bioimpedance data satisfies compatibility conditions including at least the following: a predetermined first condition related to at least one parameter in the identified function; a predetermined second condition related to the similarity of the series of plot points to the optimal Cole-Cole curve; and a predetermined third condition related to a compatibility point group along the optimal Cole-Cole curve among the series of plot points; and if it is determined that the series of bioimpedance data satisfies the compatibility conditions, storing an estimated value related to body composition obtained from the function in a memory unit; and generating body composition information based on the stored estimated value.

13. An information processing device having a control unit, wherein the control unit: acquires a series of bioimpedance data obtained by bioimpedance measurement; based on the acquired series of bioimpedance data, identifies a function that indicates an optimal Cole-Cole curve that is most suitable for the series of plot points plotted on a complex plane with resistance on the horizontal axis and reactance on the vertical axis, and based on a logical formula showing the relationship between the bioimpedance data and the parameters R0 and R∞; determines whether the series of bioimpedance data satisfies compatibility conditions including at least the following: a predetermined first condition related to at least one parameter in the identified function; a predetermined second condition related to the similarity of the series of plot points to the optimal Cole-Cole curve; and a predetermined third condition related to a compatibility point group along the optimal Cole-Cole curve among the series of plot points; and if it is determined that the series of bioimpedance data satisfies the compatibility conditions, stores an estimated value related to body composition obtained from the function in a memory unit; and generates body composition information based on the stored estimated value.

14. The program according to claim 1 or 2, which causes the computer to execute the following processes: generate body composition information in predetermined minute increments based on the series of bioimpedance data measured in the predetermined minute increments; store the generated body composition information in the memory unit in association with the measurement date and time of the series of bioimpedance data used to generate the body composition information; calculate a representative value of the body composition information at a predetermined time selected from units of several hours to several days from the multiple pieces of body composition information stored in the memory unit; and display a time series graph showing the change in the body composition information over time on a display unit based on the calculated representative value of the body composition information.

15. The program described in claim 14 causes the computer to execute a process in which the representative values ​​of the body composition information include a first representative value of the body composition information for a first period selected from units of several hours to several days, and a second representative value of the body composition information for a second period selected from units of several hours to several days and shorter than the first period, and receives an instruction to switch between a first time series graph on which the first representative values ​​of the body composition information are plotted and a second time series graph on which the second representative values ​​of the body composition information are plotted, and switches the time series graph displayed on the display unit to the first time series graph or the second time series graph in accordance with the received switching instruction.

Images