Biological information measurement support system and biological information measurement support program

Abstract

A biological information measurement support system according to the present invention performs processing for managing target biological information, and comprises: an input reception unit that receives input of biological information; an analysis unit determination unit that divides the biological information by a preset segment length and determines the divided segments as analysis units; an analyzability determination unit that determines whether analysis is possible for each analysis unit; an effective analysis amount calculation unit that calculates an effective analysis amount on the basis of the segment length and a determination result of analyzability; and a control unit that accumulates the effective analysis amounts of the respective analysis units and executes preset measurement support processing on the basis of the cumulative effective analysis amount resulting from the accumulation.

Description

Biomedical information measurement support system and biomedical information measurement support program

[0001] This invention relates to a series of biological information measurement support systems and biological information measurement support programs that manage measurements based on biological information acquired from a subject.

[0002] The heart repeatedly contracts and expands, acting as a pump to send blood throughout the body. This activity is kept regular by weak electrical impulses in the myocardial cells, but if abnormalities appear in these electrical impulses, abnormalities will occur in the heart's activity. This is called arrhythmia, and there are various types of arrhythmias. Specifically, the importance of arrhythmias differs depending on the type and frequency, with some being highly lethal, causing cardiac arrest, and others potentially leading to serious diseases such as stroke. Therefore, early detection of arrhythmias is extremely important from a healthcare perspective, and techniques using biometric information obtained from patients by biometric information measuring devices are known for diagnosing them (hereinafter also referred to as arrhythmia diagnosis). The most common method involves obtaining electrocardiogram signals as the patient's biometric information and making a determination based on the waveform shape and occurrence interval of the electrocardiogram contained in the electrocardiogram.

[0003] Figures 11A to 11C show examples of electrocardiogram (ECG) signals. The ECG waveform 100 shown in Figure 11A is a normal ECG waveform without arrhythmia. The ECG waveform 110 shown in Figure 11B shows an ECG waveform with premature atrial contraction (PAC). The ECG waveform 120 shown in Figure 11C shows an ECG waveform with premature ventricular contraction (PVC). The ECG waveform may contain waveform components called P wave 101, Q wave 102, R wave 103, S wave 104, and T wave 105 (see Figure 11A). Each of these waveforms has characteristic features in terms of the interval between occurrences and waveform shape, which allows for the diagnosis of arrhythmia.

[0004] In particular, in recent years, measurement support methods and systems have been proposed to enable patients to measure biological information used in arrhythmia diagnosis at home. For example, Patent Document 1 describes a measurement support method and system for enabling patients to measure biological information at home. According to the technology described in Patent Document 1, it is possible to measure biological information over a long period of time continuously while going about daily life, without the need to visit a medical institution, thus enabling arrhythmia diagnosis while reducing the burden on the patient.

[0005] Incidentally, the quality of the biological information is crucial in diagnosing arrhythmias using biological information measured at home. When measuring biological information from a patient using a biological information measuring device, noise can be superimposed due to electrode displacement caused by body movement or other disturbances, making it difficult to clearly read waveform components (for example, P waves, Q waves, R waves, S waves, T waves, etc. in an electrocardiogram waveform). In particular, in home measurements performed by patients, such as in Patent Document 1, the quality of biological information tends to be low because patients themselves are unfamiliar with handling biological information measuring devices.

[0006] Here, the term "effective analysis volume" is sometimes used as an indicator of the quality of biological information. Effective analysis volume refers to the length of a data interval (effective analysis interval) in biological information where there is little noise and the waveform components can be read accurately and clearly. Obtaining a sufficient effective analysis volume is important when performing arrhythmia diagnosis, and if the effective analysis volume is insufficient, it becomes necessary to remeasure, which places a significant burden on both the patient and the doctor. To address this problem, Patent Document 2 describes a technique in which acquired signal values ​​within a predetermined range are treated as normal signal values, and when the total amount of normal signal values ​​(effective analysis volume) reaches a predetermined amount, the measurement is considered complete and an action is taken. According to the technique in Patent Document 2, it is possible to prevent remeasurement due to insufficient effective analysis volume and reduce the burden on the patient.

[0007] Patent No. 7377455 Patent No. 3206461

[0008] However, conventional measurement support methods have a problem in that they cannot determine an effective analysis interval that matches the actual situation of arrhythmia diagnosis. FIG. 12 is a diagram showing an example of determining an effective analysis interval in biological information. In Patent Document 2, the effective analysis interval is determined based on whether the acquired signal value is within a predetermined range. Therefore, for example, in FIG. 12, when the predetermined range is -Th to +Th, the interval T A , T C , T E , T F serve as effective analysis intervals, and the interval T B , T D do not serve as effective analysis intervals.

[0009] In this case, although the acquired signal value of the interval T B is not within the predetermined range due to the influence of baseline fluctuation, the waveform component can be clearly read. Therefore, designating this interval as an effective analysis interval matches the actual situation of arrhythmia diagnosis. On the other hand, although the acquired signal values of the intervals T C , T E are within the predetermined range, the waveform components cannot be clearly read. Therefore, not designating these intervals as effective analysis intervals matches the actual situation of arrhythmia diagnosis. Furthermore, when the waveform occurrence interval is used for arrhythmia diagnosis, in the interval T F , consecutive waveforms do not occur, and the waveform occurrence interval cannot be calculated. Therefore, not designating this interval as an effective analysis interval matches the actual situation of arrhythmia diagnosis. Accordingly, there has been a demand for providing measurement support by determining an effective analysis interval so as to match the actual situation of arrhythmia diagnosis.

[0010] An object of the present invention is to solve the above problems and provide a biological information measurement support system and a biological information measurement support program capable of determining an effective analysis interval that conforms to the actual situation of arrhythmia diagnosis.

[0011] The biological information measurement support system of the present invention that achieves the above objective has the following configuration: (1) A biological information measurement support system that performs processing for managing target biological information, comprising: an input receiving unit that receives input of the biological information; an analysis unit determination unit that divides the biological information into a predetermined segment length and determines the divided segment as an analysis unit; an analysis feasibility determination unit that determines whether or not analysis is possible for the analysis unit; an effective analysis amount calculation unit that calculates an effective analysis amount based on the segment length and the analysis feasibility determination result; and a control unit that accumulates the effective analysis amounts of each analysis unit and executes a predetermined measurement support processing based on the accumulated effective analysis amount.

[0012] (2) The biological information measurement support system according to (1), wherein the segment length is set on a time basis and / or a waveform number basis.

[0013] (3) The biological information measurement support system according to (1) or (2), wherein the effective analysis amount and the cumulative effective analysis amount are set on a time basis and / or waveform number basis.

[0014] (4) The biological information measurement support system according to any one of (1) to (3), wherein the control unit executes the measurement support process based on whether or not the cumulative effective analysis amount exceeds a preset threshold.

[0015] (5) The control unit resets the cumulative effective analysis amount at predetermined intervals, executes a first measurement support process based on whether the cumulative effective analysis amount exceeds a first threshold within the predetermined period, and executes a second measurement support process different from the first measurement support process based on whether the cumulative number of executions obtained by accumulating the number of executions of the first measurement support process exceeds a second threshold, the biological information measurement support system according to any one of (1) to (3).

[0016] (6) A battery monitoring unit that acquires the remaining battery level of a biological information measuring instrument that measures the biological information, wherein the control unit executes a first measurement support process based on whether the cumulative effective analysis amount exceeds a first threshold, and executes a second measurement support process different from the first measurement support process based on whether the cumulative effective analysis amount exceeds a second threshold smaller than the first threshold, and whether the remaining battery level exceeds a third threshold, the biological information measurement support system according to any one of (1) to (3).

[0017] (7) A memory monitoring unit that acquires the remaining memory amount of a biological information measuring instrument that measures the biological information, wherein the control unit executes a first measurement support process based on whether the cumulative effective analysis amount exceeds a first threshold, and executes a second measurement support process different from the first measurement support process based on whether the cumulative effective analysis amount exceeds a second threshold smaller than the first threshold, and whether the remaining memory amount exceeds a third threshold, the biological information measurement support system according to any one of (1) to (3).

[0018] (8) The biological information measurement support system according to (1), further comprising an analysis unit for analyzing the biological information, and updating each parameter and / or method related to the measurement support processing based on the results of the analysis.

[0019] (9) The biological information measurement support system according to any one of (1) to (8), wherein the control unit performs notification processing to the wearer and / or administrator of the biological information measuring device that measures the biological information, as the measurement support processing.

[0020] (10) The biological information measurement support system according to any one of (1) to (8), wherein the control unit performs a notification process to prompt the distribution of a biological information measuring instrument and its associated components for measuring the biological information, as the measurement support process.

[0021] (11) A biological information measurement support system described in any one of (1) to (10), which is built into a biological information measuring instrument that measures the biological information.

[0022] (12) A biological information measurement support system according to any one of (1) to (10), which is built into a server that is communicably connected to a biological information measuring instrument that measures the biological information.

[0023] (13) A biological information measurement support program that performs processing for managing the biological information of a target, the program which causes a computer to perform a series of processes, including: receiving input of the biological information; dividing the biological information into segments of a predetermined segment length; determining the divided segments as analysis units; determining whether the analysis units can be performed; calculating an effective analysis quantity based on the segment length and the result of the analysis feasibility determination; accumulating the effective analysis quantities of each analysis unit; and executing a predetermined measurement support process based on the accumulated effective analysis quantity.

[0024] According to the present invention, it is possible to determine the effective analysis interval in accordance with the actual conditions of arrhythmia diagnosis, and as a result, it is possible to prevent remeasurement due to insufficient effective analysis volume. Specifically, by determining whether analysis is possible for each segment of the biological information acquired from the subject and performing a predetermined measurement support action based on the stored cumulative effective analysis volume, it is possible to prevent remeasurement due to insufficient effective analysis time in home medical care / long-term electrocardiogram analysis, etc.

[0025] Figure 1 is a diagram showing an example configuration of a biological information management system according to Embodiment 1. Figure 2 is a flowchart showing the flow of measurement support processing according to Embodiment 1. Figure 3 is a flowchart showing the flow of analysis feasibility determination processing by the analysis feasibility determination unit according to Embodiment 1. Figure 4 is a flowchart showing the flow of measurement support processing according to Modification 1 of Embodiment 1. Figure 5 is a flowchart showing the flow of measurement support processing according to Modification 2 of Embodiment 1. Figure 6 is a diagram showing an example configuration of a biological information management system according to Embodiment 2. Figure 7 is a flowchart showing the flow of measurement support processing according to Embodiment 2. Figure 8 is a diagram showing an example configuration of a biological information management system according to Embodiment 3. Figure 9 is a flowchart showing the flow of measurement support processing according to Embodiment 3. Figure 10 is a flowchart showing the flow of measurement support processing according to Embodiment 4. Figure 11A is a diagram showing an example of an electrocardiogram signal (part 1). Figure 11B is a diagram showing an example of an electrocardiogram signal (part 2). Figure 11C is a diagram showing an example of an electrocardiogram signal (part 3). Figure 12 is a diagram showing an example of determination of an effective analysis interval in biological information.

[0026] Embodiments of the biological information management system according to the present invention will be described in detail below with reference to the drawings. However, the present invention is not limited by these embodiments. Furthermore, the individual embodiments of the present invention are not independent but can be combined and implemented as appropriate.

[0027] (Embodiment 1) Figure 1 is a diagram showing an example of the configuration of a biological information management system according to Embodiment 1 of the present invention. The biological information management system comprises an electrocardiogram signal measuring device 2, which is a biological information measuring device, a measurement support system 3, a receiving terminal 4, and a learning device 5. In this Embodiment 1, an example will be described in which the measurement support system 3 is built into a server connected to the electrocardiogram signal measuring device 2, which is a biological information measuring device, by a predetermined communication means.

[0028] The biological information measuring device is freely determined and not limited to the biological information to be acquired. Furthermore, it is assumed that the biological information measuring device includes a connector for electrical connection with the measurement support system 3, a communication device equipped with means for communication with the biological information management system, or a biological information output mechanism such as an input port for a medium on which the acquired biological information is written. In this embodiment 1, the biological information is an electrocardiogram signal 10, the biological information measuring device is an electrocardiogram signal measuring device 2, the electrocardiogram signal measuring device 2 is equipped with an input port for a medium on which the acquired biological information, the electrocardiogram signal 10, is written, and the subject 1 is a person as an example. Note that the biological information is not particularly limited to the electrocardiogram signal 10, as long as it can estimate the heart rate cycle, and may also be a pulse wave signal, heart sounds, etc.

[0029] The electrocardiogram signal 10 to be analyzed is acquired from the subject 1 via the electrocardiogram signal measuring device 2. The subject 1 is not particularly limited to a person or an animal. The receiving terminal 4 is, for example, a smartphone held by the subject 1 or a caregiver (for example, a surgeon such as a doctor, a factory hygiene manager, or a nearby worker).

[0030] An example of an electrocardiogram signal measuring device 2 is a wearable electrocardiograph. Specifically, the electrocardiogram signal measuring device 2 comprises a garment body worn on a subject 1, multiple electrodes, and an electrocardiograph 100 that is electrically connected to each electrode. The electrocardiograph 100 and the like are fixed to the garment body using a band or the like.

[0031] The electrocardiograph 100 is an example of a measuring device that acquires electrocardiogram signals 10. The electrocardiograph 100 has the function of continuously acquiring the electrocardiogram signals 10 of a subject 1, the function of storing the acquired electrocardiogram signals 10, and the function of transferring data to the measurement support system 3 by communication. Alternatively, the electrocardiograph 100 may transfer data including the electrocardiogram signals 10 to a server device, and the server device may transfer the electrocardiogram signals 10 to the measurement support system 3. Hereinafter, subject 1 will be described as a person wearing the electrocardiogram signal measuring device 2.

[0032] In this embodiment 1, the electrocardiogram signal 10 acquired from the subject 1 includes information about the subject 1, information about the electrocardiogram measuring instrument (sampling period, etc.), acquisition date and time, location, and acquisition result. The acquisition result is waveform data 11 obtained by plotting time on the horizontal axis and voltage on the vertical axis (see Figure 1). The waveform data 11 may include waveform components called P waves, Q waves, R waves, S waves, and T waves, and their shapes are used as criteria for determining arrhythmias, etc. For example, the waveform data 11 is made up of repeating patterns of these waveform components. Note that the shape of the waveform data 11 of the electrocardiogram signal 10 may change depending on the subject and the method of attaching the electrocardiograph 100.

[0033] The measurement support system 3 comprises a communication unit 311, an analysis unit determination unit 312, an analysis feasibility determination unit 313, an effective analysis quantity calculation unit 314, an input / output unit 315, a control unit 316, and a storage unit 317.

[0034] The communication unit 311 can communicate with the electrocardiogram signal measuring device 2 and the receiving terminal 4 via a communication network. The communication network referred to here is configured using, for example, an existing public telephone network, LAN (Local Area Network), WAN (Wide Area Network), etc., and can be wired or wireless. The communication unit 311 is composed of, for example, a connector that electrically connects to the communication target, a communication device equipped with means for communicating with the electrocardiogram signal measuring device 2, or an input port for a media on which data is stored. The communication unit 311 functions as an input receiving unit that accepts input of biological information.

[0035] In this embodiment 1, the electrocardiogram signal measuring device 2, which is a biological information measuring device, is equipped with an input port for a medium on which the acquired biological information, the electrocardiogram signal, is written, and incorporates a measurement support system 3. It is assumed that the electrocardiogram signal measuring device 2 is input to the measurement support system 3 via the medium, but it is not limited to this, and for example, it is also assumed that the electrocardiogram signal measuring device 2, which is a biological information measuring device, and a server incorporating the measurement support system 3 are connected by a predetermined communication means.

[0036] The analysis unit determination unit 312 divides the input biological information into predetermined segment lengths and determines each segment as an analysis unit. The predetermined segment length can be based on time, the number of waveforms, etc., but is not limited to these and can be selected according to operational requirements. For example, if the predetermined segment length is 10 seconds based on time, the analysis unit determination unit 312 divides the biological information into 10-second intervals and uses them as analysis units. In this case, for example, if the predetermined segment length is 10 waveforms based on the number of waveforms, the analysis unit determination unit 312 detects waveforms in the biological information, divides it into 10 waveform intervals and uses them as analysis units.

[0037] Here, if the predetermined segment length is too short, feature extraction may not be successful, which could affect the accuracy of the analysis feasibility determination unit 313, described later. On the other hand, if the predetermined segment length is too long, the real-time capability of the biological information measurement support may be lost. For these reasons, it is desirable to set the predetermined segment length between 1 and 60 seconds based on time, and between 1 and 100 waveforms based on the number of waveforms, however, the optimal segment length varies depending on the final use of the biological information, so it is not limited to this. In this embodiment 1, an example will be described in which the predetermined segment length is 10 seconds based on time, and the biological information is divided into 10-second intervals to be used as the analysis unit.

[0038] The analysis feasibility determination unit 313 determines whether analysis is possible for the determined analysis unit and outputs the result as the analysis feasibility determination result. The determination of whether analysis is possible by the analysis feasibility determination unit 313 can be made based on, but is not limited to, the absence of superimposed noise, the ability to clearly read waveform components, the availability of a sufficient amount of waveform data, and the availability of a sufficient amount of waveform generation intervals. In this embodiment 1, the analysis feasibility determination unit 313 will be described as determining whether arrhythmia diagnosis is possible for the determined analysis unit using a trained model (for example, a CNN (Convolutional Neural Network) model), but is not limited to this.

[0039] The effective analysis amount calculation unit 314 calculates an effective analysis amount for each analysis unit. It is assumed that the effective analysis amount may be based on time, the number of waveforms, or the like, but is not limited thereto. In addition, the effective analysis amount calculated by the effective analysis amount calculation unit 314 does not need to have its reference (unit) matched with the analysis unit determined by the analysis unit determination unit 312. For example, even if a predetermined segment length in the analysis unit determination unit 312 uses the number of waveforms as the analysis unit, the effective analysis amount calculation unit 314 may calculate the effective analysis amount based on time.

[0040] For example, when the result of the analysis availability determination for the target analysis unit is "analysis is impossible", the effective analysis amount calculation unit 314 sets the effective analysis amount to zero. For example, when the result of the analysis availability determination for the target analysis unit is "analysis is possible" and the effective analysis amount is based on time, the effective analysis amount is the time length of the target analysis unit. Further, for example, when the result of the analysis availability determination for the target analysis unit is "analysis is possible" and the effective analysis amount is based on the number of waveforms, the effective analysis amount is the number of waveforms detected from the target analysis unit. In the first embodiment, description is given by taking an example where the effective analysis amount is based on time, but the present invention is not limited thereto.

[0041] The input / output unit 315 is configured by a device having an input function and an output function, and outputs various types of information under the control of the control unit 316. The input / output unit 315 includes a user interface such as a keyboard, a mouse, and a microphone, and has an input function that receives input of an electrocardiographic signal 10 output from the electrocardiographic signal measuring device 2. Furthermore, the input / output unit 315 has an output function such as a display formed of, for example, liquid crystal, organic EL (Electro Luminescence), or the like, and a speaker that outputs sound.

[0042] Furthermore, as the input function of the input / output unit 315, it is assumed that the input / output unit 315 is provided with a biological information input mechanism represented by an input port for a medium in which biological information is written. When the input function of the input / output unit 315 overlaps with the function of the communication unit 311, any one of them only needs to have that function.

[0043] Furthermore, regarding the biological information input to the measurement support system 3, the input method can be selected according to operational requirements. In addition to using electrocardiographic signals 10 acquired in the past, acquisition of the electrocardiographic signal 10 by the electrocardiograph 2 and input to the measurement support system 3 may be performed in parallel. In this case, it is assumed that the electrocardiograph 2 may constantly transmit values acquired by a continuous method, or collectively transmit values acquired by a batch method at regular intervals, and there is no particular limitation thereto.

[0044] A control unit 316 generally controls the operation of the measurement support system 3. The control unit 316 also transmits measurement support information, together with wearer information, to the receiving terminal 4 via the communication unit 311. The wearer information is information for identifying the subject 1, including personal information such as the name and gender of the subject 1, and the management number of the wearable device or peripheral device worn by the subject 1. Furthermore, the control unit 316 may output the measurement support information using the output function of the input / output unit 315.

[0045] A storage unit 317 stores various programs for operating the measurement support system 3 and various types of data including data generated by each unit (for example, segment lengths). The various programs also include programs such as waveform classification processing executed using a trained model. The storage unit 317 also accumulates the effective analysis amount calculated for each analysis unit, and stores the accumulated amount as a cumulative effective analysis amount. Furthermore, various types of data (including setting values) stored in the storage unit 317 can be dynamically reconfigured by the control unit 316. The storage unit 317 is configured using a ROM (Read Only Memory) pre-installed with various programs and the like, a RAM (Random Access Memory) that stores calculation parameters and data for each process, an HDD (Hard Disk Drive), an SSD (Solid State Drive), and the like.

[0046] Various programs can be recorded on computer-readable recording media such as HDDs, flash memory, CD-ROMs, DVD-ROMs, and Blu-ray® and widely distributed; the method is not limited. Furthermore, the communication unit 311 can acquire various programs via a communication network.

[0047] The measurement support system 3 having the above functional configuration is a computer composed of one or more hardware components such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), ASIC (Application Specific Integrated Circuit), and FPGA (Field Programmable Gate Array). The measurement support system 3 may be configured separately from the electrocardiogram signal measuring device 2, or it may be configured integrally with the electrocardiogram signal measuring device 2.

[0048] The receiving terminal 4 comprises a communication unit 41, an output unit 42, and a control unit 43.

[0049] The communication unit 41 receives information output from the measurement support system 3 via the communication network. For example, the communication unit 41 receives processing results and wearer information from the measurement support system 3.

[0050] The output unit 42 is composed of output devices such as display devices and printing devices, and outputs various types of information under the control of the control unit 43. The output unit 42 has output functions such as a display made of liquid crystal or organic EL, or a speaker.

[0051] The control unit 43 comprehensively controls the operation of the receiving terminal 4. The control unit 43 also outputs the processing results using the output function of the output unit 42.

[0052] The receiving terminal 4 having the above functional configuration is a computer composed of one or more hardware components such as a CPU, GPU, ASIC, FPGA, etc. The receiving terminal 4 may also have a user interface.

[0053] The learning device 5 creates training data and generates a trained model using the created training data. In this embodiment 1, the learning performed by the learning device 5 can employ known machine learning methods such as Bayesian optimization, genetic algorithms, linear regression, nonlinear regression, logistic regression, k-nearest neighbors, support vector machines, decision trees, random forests, gradient boosting trees, k-means algorithms, principal component analysis, and deep learning. The trained model is, for example, a neural network consisting of an input layer, hidden layers, and output layers, with each layer having one or more nodes. Information such as network parameters in the trained model is stored in memory. Network parameters include information about the weights and biases between layers of the neural network. The learning device 5 generates a trained model. The learning device 5 is a computer composed of one or more hardware components such as a CPU, GPU, ASIC, FPGA, and memory.

[0054] Next, we will explain the sequence of steps for assisting in the measurement of biological information by the measurement support system 3. Figure 2 is a flowchart showing the flow of the measurement support process according to Embodiment 1. In the classification process, first, the measurement support system 3 receives input of the electrocardiogram signal 10 obtained from the subject 1 (step S101). In this Embodiment 1, the input / output unit 315 is provided with an input port for a medium on which the electrocardiogram signal 10 is written, and after the acquisition of the electrocardiogram signal 10 is complete, the electrocardiogram signal 10 stored on the medium is read as an example, but the communication unit 311 may also receive input of the electrocardiogram signal 10. The control unit 316 processes the waveform data 11 of the acquired electrocardiogram signal 10 as needed to generate processing data.

[0055] After acquiring the electrocardiogram signal 10, the analysis unit determination unit 312 divides the input electrocardiogram signal into 10-second intervals based on time, and determines the divided signals as analysis units (step S102).

[0056] After determining the analysis unit, the analysis feasibility determination unit 313 determines whether analysis is possible for the determined analysis unit (step S103). In this embodiment 1, the determination of whether arrhythmia diagnosis is possible for the determined analysis unit using a trained CNN model will be explained as an example.

[0057] Figure 3 is a flowchart showing the flow of the analysis feasibility determination process by the analysis feasibility determination unit according to Embodiment 1. First, the analysis feasibility determination unit 313 acquires a CNN model that has been learned in two classes, "1: arrhythmia diagnosis is possible" and "0: arrhythmia diagnosis is not possible" for multiple analysis units determined from an arbitrary electrocardiogram signal (step S201). This CNN model is generated by, for example, the learning device 5 and acquired by outputting it from the learning device 5, or if it is stored in the storage unit 317 beforehand, it is acquired by referring to the storage unit 317.

[0058] Here, the arbitrary electrocardiogram signals are not limited to those obtained from the subject 1 themselves, those quoted from publicly available datasets, or those artificially generated; a combination of these is also envisioned.

[0059] After acquiring the CNN model, the analysis feasibility determination unit 313 inputs the target analysis unit into the acquired CNN model (step S202). In this embodiment 1, the CNN model determines whether the input analysis unit corresponds to "1: arrhythmia diagnosis is possible" or "0: arrhythmia diagnosis is not possible" based on the features extracted by the convolutional layer, and outputs the result.

[0060] The analysis feasibility determination unit 313 then obtains the output of the CNN model as the determination result (step S203). In this embodiment 1, the determination result is either "1: arrhythmia diagnosis is possible" or "0: arrhythmia diagnosis is not possible". If the determination result is "1: arrhythmia diagnosis is possible", the target analysis unit is determined to be "analysis possible", and if it is "0: arrhythmia diagnosis is not possible", the target analysis unit is determined to be "analysis impossible".

[0061] Returning to Figure 2, the effective analysis amount calculation unit 314 calculates the effective analysis amount for each analysis unit (step S104). In this embodiment 1, the segment length of the analysis unit is 10 seconds on a time basis, and it is assumed that the effective analysis amount is based on time. Therefore, if the determination result for the target analysis unit is "analysis possible", the effective analysis amount for the target analysis unit will be 10 seconds. Also, if the determination result for the target analysis unit is "analysis impossible", the effective analysis amount for the target analysis unit will be 0 seconds, but this is not limited to this.

[0062] After calculating the effective analysis amount, the control unit 316 accumulates the effective analysis amounts calculated for each analysis unit and stores them in the storage unit 317 as the cumulative effective analysis amount (step S105). In addition to the cumulative effective analysis amount obtained by accumulating the effective analysis amounts, the total measurement period length, including analysis units where the effective analysis amount is 0 seconds and therefore "analysis is impossible," may also be stored, but is not limited to this.

[0063] The control unit 316 then reads the cumulative effective analysis amount from the storage unit 317 and determines whether the cumulative effective analysis amount is equal to or greater than a predetermined threshold (step S106). The predetermined threshold is a value used to determine whether or not to execute a predetermined measurement support action, and is set based on the cumulative effective analysis amount. For example, the threshold is set to 432,000 seconds. If the control unit 316 determines that the cumulative effective analysis amount is less than the threshold (step S106: No), it returns to step S102 and repeats the determination for the next analysis unit. On the other hand, if the control unit 316 determines that the cumulative effective analysis amount is equal to or greater than the threshold (step S106: Yes), it proceeds to step S107.

[0064] In step S107, the control unit 316 performs a predetermined measurement support action. In this embodiment 1, since the amount of analysis has become a quantity that can diagnose arrhythmia as a cumulative effective analysis amount, the control unit 316 is expected to perform a predetermined measurement support action, such as notifying the subject 1 that the measurement is complete, transferring the measured electrocardiogram signal 10, or turning off the switch of the electrocardiogram signal measuring device 2. For example, the notification process is expected to be carried out by using the notification function of the electrocardiogram signal measuring device 2, which is a biological information measuring device, or via a terminal equipped with a notification function, but is not limited to these. The notification function is expected to be a speaker (sound), lamp (light), vibration, etc., but is not limited to these.

[0065] In this embodiment 1 described above, it is determined whether arrhythmia diagnosis is possible for each determined analysis unit, the effective analysis volume is calculated using the analysis units for which arrhythmia diagnosis is possible, and notification that the measurement is complete is given based on the cumulative effective analysis volume obtained by accumulating these effective analysis volumes. According to this embodiment 1, the determination of the effective analysis interval and the management of the effective analysis volume can be performed in a manner that suits the actual situation of each analysis, including arrhythmia diagnosis, so that measurement support in home medical care / long-term electrocardiogram analysis etc. can be provided, and it is possible to prevent remeasurement due to insufficient effective analysis time.

[0066] In this embodiment 1, arbitrary data processing may be performed on the input electrocardiogram signal. Examples of data processing include, but are not limited to, applying filtering or normalization. Such processing allows for the capture of more important features from the electrocardiogram signal and the determination of the effective analysis interval with high accuracy. Furthermore, the above-described data processing may be performed on the electrocardiogram signal by the input / output unit 315, or on the analysis units by the analysis unit determination unit 312 or the analysis feasibility determination unit 313; these methods are not limited to these methods.

[0067] Furthermore, in this embodiment 1, the analysis feasibility determination unit 313 was described using two classes as an example, "1: Arrhythmia diagnosis is possible" and "0: Arrhythmia diagnosis is not possible," to indicate whether or not arrhythmia diagnosis is possible as an analysis feasibility determination result. However, it may also have three or more classes, and is not limited to this embodiment.

[0068] Furthermore, in this embodiment 1, the parameters and methods related to the measurement support processing, including the predetermined segment length in the analysis unit determination unit 312, the method for determining whether analysis is possible (threshold) in the analysis feasibility determination unit 313, the method for calculating the effective analysis amount in the effective analysis amount calculation unit 314, the conditions for executing the measurement support action in the control unit 316 (determination threshold), and the content of the measurement support action in the control unit 316, may be configured to allow for changes during the process. For example, it is conceivable, but not limited, that the system may include an analysis unit that analyzes biological information and outputs analysis results, and that these results may be changed according to the analysis results or according to external commands. The analysis unit may be performed by the control unit 316, or it may be configured separately from the components of the measurement support system 3 shown in Figure 1.

[0069] One example of analysis performed by the analysis unit is model updating. In this embodiment 1, the analysis unit is connected to the learning device 5 by a predetermined communication means, and determines whether or not to update the model based on the cumulative effective analysis amount. If the analysis unit determines that a model update is necessary, it creates training data from the biological information obtained from the subject 1, generates a new trained model by performing training or additional training on the learning device 5, and updates the storage unit 317 as necessary. As a result, the new trained model reflects the characteristics of the biological information obtained from the subject 1, and by using the new trained model to determine whether or not to perform analysis, the analysis feasibility determination process can be performed with higher accuracy.

[0070] Another example of analysis performed by the analysis unit is the adjustment of waveform detection parameters. In an embodiment different from that of this embodiment 1, assuming that a predetermined segment length is based on the number of waveforms, the analysis unit determines whether or not adjustment of the waveform detection parameters is necessary based on the amplitude of the detected waveform, in parallel with the waveform detection in the analysis unit determination unit 312. If the analysis unit determines that adjustment of the waveform detection parameters is necessary, the analysis unit creates new waveform detection parameters and updates the storage unit 317. As a result, the new waveform detection parameters reflect the characteristics of the biological information obtained from the subject 1, and by performing waveform detection using the new waveform detection parameters, the analysis unit determination process can be performed with higher accuracy.

[0071] Furthermore, in this embodiment 1, the control unit 316 sets the threshold to 432,000 seconds and, as a predetermined measurement support action, notifies the subject 1 wearing the biological information measuring device that the measurement is complete. However, multiple conditions may be set or multiple measurement support actions may be executed.

[0072] One example of combining conditions with measurement support actions is notification of measurement progress. This could involve, for example, providing notification of the total measurement period length, cumulative effective analytes, and the percentage of the cumulative effective analytes over the total measurement period (effectiveness rate) after a certain period of time has elapsed. Possible means of notification include displaying text or numbers on a screen or visualizing the effectiveness rate with a level meter. This would allow subjects 1 and administrators at medical institutions to check the measurement progress of subject 1 at each stage.

[0073] Another example of a combination of conditions and measurement support actions is notification of the attachment status. This is based on the condition that the cumulative effective analysis amount over a predetermined period (for example, every 24 hours) is below a threshold, and the system determines that the attachment status of the biometric information measuring device on subject 1 is poor and issues a notification. Possible means of notification include emitting a sound from the speaker provided by the input / output unit 315, displaying text on the display, or notifying via the receiving terminal 4. The content of the notification is expected to include not only a statement that the attachment status is poor, but also specific instructions on how to attach the biometric information measuring device, such as tightening the strap. This makes it possible to maintain a good attachment status of the biometric information measuring device on subject 1.

[0074] (Modification 1 of Embodiment 1) Next, Modification 1 of Embodiment 1 of the present invention will be described. In this Modification 1, the notification method is switched on the condition that a predetermined activity time has passed. The biological information management system in this Modification 1 is the same as the biological information management system in Embodiment 1, so its description will be omitted. The same reference numerals are used for the same components as described above. The following describes a process that differs from Embodiment 1 with reference to Figure 4.

[0075] Figure 4 is a flowchart showing the flow of the measurement support process according to Modification 1 of Embodiment 1. In the measurement support process according to this Modification 1, it is determined whether or not arrhythmia diagnosis is possible for each analysis unit, in the same manner as steps S101 to S106 of Embodiment 1 described above (see Figure 2), and a determination process is executed based on the accumulated effective analysis volume (steps S301 to S306).

[0076] Then, if the control unit 316 determines that the cumulative effective analysis amount is above a threshold (step S306: Yes), it determines whether the current time is within a predetermined activity time (step S307). If the control unit 316 determines that the current time is within the predetermined activity time (step S307: Yes), it proceeds to step S308. On the other hand, if the control unit 316 determines that the current time is outside the predetermined activity time (step S307: No), it proceeds to step S309. The predetermined activity time is set to, for example, 9:00 to 21:00.

[0077] In steps S308 and S309, the control unit 316 executes two different measurement support actions (a first measurement support action and a second measurement support action). In step S308, the control unit 316 performs a vibration notification to the subject 1 as the first measurement support action. In step S309, since it is highly likely that the subject 1 is asleep, a notification process different from the first measurement support action is executed. For example, in step S309, the control unit 316 performs a lamp (light) notification to the subject 1 as a predetermined measurement support action, instead of sound or vibration. Other possibilities include scheduling a notification and performing a sound or vibration notification when a predetermined activity time is reached, but these are not limited to these options.

[0078] According to the modified example 1 described above, similar to Embodiment 1, the system notifies that the measurement is complete based on the cumulative effective analysis amount, which is the sum of the effective analysis amounts of analysis units capable of diagnosing arrhythmias. This enables measurement support in home medical care / long-term electrocardiogram analysis, etc., and prevents re-measurement due to insufficient effective analysis time.

[0079] Furthermore, according to this modified example 1, the notification method is switched based on whether a predetermined activity period has occurred, making it possible to provide measurement support without interfering with the subject's daily life (sleep, etc.).

[0080] (Modification 2 of Embodiment 1) Next, Modification 2 of Embodiment 1 of the present invention will be described. In this Modification 2, in addition to the measurement support processing in Embodiment 1, measurement support processing is performed based on the determination of whether the biological information measuring device has been forgotten to be attached. The biological information management system in this Modification 2 is the same as the biological information management system in Embodiment 1, so its description will be omitted. The same reference numerals are used for the same components as described above. The following describes the processing that differs from Embodiment 1 with reference to Figure 5.

[0081] Figure 5 is a flowchart showing the flow of the measurement support process according to Modification 2 of Embodiment 1. In the measurement support process according to this Modification 2, it is determined whether arrhythmia diagnosis is possible for each analysis unit, in the same manner as steps S101 to S105 of Embodiment 1 described above (see Figure 2), and the accumulated effective analysis volume is stored (steps S401 to S405).

[0082] Then, the control unit 316 determines whether the cumulative effective analysis amount is equal to or greater than a first threshold (step S406). In this embodiment 2, the control unit 316 reads the cumulative effective analysis amount from the storage unit 317, and if it determines that the cumulative effective analysis amount is less than the first threshold (step S406: No), it proceeds to step S408. On the other hand, if the control unit 316 determines that the cumulative effective analysis amount is equal to or greater than the first threshold (step S406: Yes), it proceeds to step S407.

[0083] In step S407, the control unit 316 performs the first measurement support action in the same manner as in step S107 (see Figure 2) described above.

[0084] Furthermore, in step S408, the control unit 316 determines whether the cumulative effective analysis amount for a predetermined period is less than a second threshold. In this modified example 2, the predetermined period is assumed to be set to 7:00 to 10:00 each day, but is not limited to this.

[0085] If the control unit 316 determines that the cumulative effective analysis amount over a predetermined period is not less than the second threshold (step S408: No), it returns to step S402 and repeats the determination for the next analysis unit. On the other hand, if the control unit 316 determines that the cumulative effective analysis amount over a predetermined period is less than the second threshold (step S408: Yes), it proceeds to step S409.

[0086] In step S409, the control unit 316 performs a predetermined measurement support action as a second measurement support action. In this modified example 2, the control unit 316 determines that the subject 1 has forgotten to wear the biometric information measuring device because the cumulative effective analysis amount over a predetermined period is small, and as a second measurement support action, it notifies the subject 1, for example, to prompt them to wear the biometric information measuring device. Possible means of notification include making a sound through the speaker, which is a notification function of the electrocardiogram signal measuring device 2, or notifying via the receiving terminal 4.

[0087] According to the modified example 2 described above, similar to embodiment 1, the system notifies that the measurement is complete based on the cumulative effective analysis amount, which is the sum of the effective analysis amounts of analysis units capable of diagnosing arrhythmias. This enables measurement support in home medical care / long-term electrocardiogram analysis, etc., and prevents re-measurement due to insufficient effective analysis time.

[0088] Furthermore, according to this modified example 2, if the subject 1 forgets to attach the biometric information measuring device, a notification is issued prompting the subject to attach the biometric information measuring device, thereby enabling optimal measurement support in home measurements by patients, etc. In addition, in this modified example 2, in addition to the measurement support processing in Embodiment 1, measurement support processing for forgetting to attach the biometric information measuring device is performed, but the system is not limited to this configuration, and may also be configured to perform the measurement support processing for forgetting to attach the biometric information measuring device independently.

[0089] (Embodiment 2) Next, Embodiment 2 of the present invention will be described. The biological information management system according to Embodiment 2 includes a measurement support system 3A in place of the measurement support system 3 according to Embodiment 1. The same reference numerals are used for the same components as described above.

[0090] Figure 6 shows an example of the configuration of a biometric information management system according to this second embodiment. The biometric information management system according to this second embodiment comprises an electrocardiogram signal measuring device 2, a measurement support system 3A, a receiving terminal 4, and a learning device 5.

[0091] The measurement support system 3A includes a communication unit 311, an analysis unit determination unit 312, an analysis feasibility determination unit 313, an effective analysis quantity calculation unit 314, a battery monitoring unit 318, an input / output unit 315, a control unit 316, and a storage unit 317.

[0092] The battery monitoring unit 318 monitors the battery of the biological information measuring device and stores the remaining battery level in the storage unit 317. Here, the unit of the remaining battery level is not limited to, but may be discharge capacity [mAh], estimated operating time [seconds], or percentage.

[0093] In this embodiment 2, the control unit 316, on the condition that the cumulative effective analysis amount reaches a first threshold, performs a predetermined measurement support action by notifying the subject 1 wearing the biological information measuring device that the measurement is complete. Furthermore, on the condition that the cumulative effective analysis amount has not reached a second threshold and the battery level of the biological information measuring device falls below a third threshold, it performs a predetermined measurement support action by notifying the administrator of a medical institution or the like that the battery level is low. The first threshold is set to 432,000 seconds, for example, to determine the cumulative effective analysis amount, as in embodiment 1. In this embodiment 3, the second threshold is set to be shorter than the first threshold, for example, 345,600 seconds. In addition, the third threshold in this embodiment 3 is set to 5% of the battery level.

[0094] Next, the measurement support process according to this second embodiment will be described. Figure 7 is a flowchart showing the flow of the measurement support process according to this second embodiment. In the measurement support process according to this second embodiment, in the same manner as steps S101 to S105 of the first embodiment described above (see Figure 2), it is determined whether or not arrhythmia diagnosis is possible for each analysis unit, and the accumulated cumulative effective analysis volume is stored (steps S501 to S505).

[0095] The control unit 316 determines whether the cumulative effective analysis amount is equal to or greater than a first threshold (step S506). In this embodiment 2, if the control unit 316 determines that the cumulative effective analysis amount is less than the first threshold (step S506: No), it proceeds to step S508. Conversely, if the control unit 316 determines that the cumulative effective analysis amount is equal to or greater than the first threshold (step S506: Yes), it proceeds to step S507.

[0096] In step S507, the control unit 316 executes a predetermined measurement support action as the first measurement support action, in the same manner as in step S107 (see Figure 2) described above.

[0097] Furthermore, in step S508, the battery monitoring unit 318 obtains the remaining battery level from the electrocardiogram signal measuring device 2, which is a biological information measuring device, and stores the remaining battery level in the storage unit 317.

[0098] After storing the battery level, the control unit 316 reads the cumulative effective analysis amount and the battery level from the storage unit 317 and determines whether the cumulative effective analysis amount is less than or equal to the second threshold and the battery level of the biological information measuring device is less than or equal to the third threshold (step S509). If the control unit 316 determines that the cumulative effective analysis amount is greater than the second threshold or the battery level of the biological information measuring device is greater than the third threshold (step S509: No), it proceeds to step S502 and repeats the determination process for the next analysis unit. On the other hand, if the control unit 316 determines that the cumulative effective analysis amount is less than or equal to the second threshold and the battery level of the biological information measuring device is less than or equal to the third threshold (step S509: Yes), it proceeds to step S510.

[0099] In step S510, the control unit 316 performs a notification process to the administrator of a medical institution or other facility that the battery level is low, as a second measurement support action. After the notification process, the control unit 316 proceeds to step S502 and repeats the determination process for the next analysis unit.

[0100] According to Embodiment 2 described above, similar to Embodiment 1, the system notifies that the measurement is complete based on the cumulative effective analysis amount, which is the sum of the effective analysis amounts of analysis units capable of diagnosing arrhythmias. This enables measurement support in home medical care / long-term electrocardiogram analysis, etc., and prevents re-measurement due to insufficient effective analysis time.

[0101] Furthermore, according to this second embodiment, since a predetermined measurement support action is performed with the remaining battery level of the biometric information measuring device as one of the conditions, for example, by notifying the user that the battery level is low, it is possible to smoothly arrange (distribute) the biometric information measuring device itself and accessories such as batteries, thereby realizing measurement support in home medical care / long-term electrocardiogram analysis, etc.

[0102] (Embodiment 3) Next, Embodiment 3 of the present invention will be described. The biological information management system according to Embodiment 3 includes a measurement support system 3B instead of the measurement support system 3 according to Embodiment 1. The same reference numerals are used for the same components as described above.

[0103] Figure 8 shows an example of the configuration of a biological information management system according to this third embodiment. The biological information management system according to this third embodiment comprises an electrocardiogram signal measuring device 2, a measurement support system 3B, a receiving terminal 4, and a learning device 5.

[0104] The measurement support system 3B includes a communication unit 311, an analysis unit determination unit 312, an analysis feasibility determination unit 313, an effective analysis quantity calculation unit 314, a memory monitoring unit 319, an input / output unit 315, a control unit 316, and a storage unit 317.

[0105] The memory monitoring unit 319 monitors the memory of the biological information measuring device and stores it as remaining memory. The unit of remaining memory may be memory capacity [B (bytes)] or a percentage, but is not limited to these.

[0106] Next, the measurement support process according to this third embodiment will be described. Figure 9 is a flowchart showing the flow of the measurement support process according to this third embodiment. In the measurement support process according to this second embodiment, in the same manner as steps S101 to S105 of the first embodiment described above (see Figure 2), it is determined whether or not arrhythmia diagnosis is possible for each analysis unit, and the accumulated cumulative effective analysis volume is stored (steps S601 to S605).

[0107] The control unit 316 determines whether the cumulative effective analysis amount is equal to or greater than a first threshold (step S606). If the control unit 316 determines that the cumulative effective analysis amount is less than the first threshold (step S606: No), it proceeds to step S608. On the other hand, if the control unit 316 determines that the cumulative effective analysis amount is equal to or greater than the first threshold (step S606: Yes), it proceeds to step S607. The first threshold in this embodiment 3 is the same as the first threshold in embodiment 2.

[0108] In step S607, the control unit 316 executes a predetermined measurement support action as the first measurement support action, in the same manner as in step S107 (see Figure 2) described above.

[0109] Furthermore, in step S608, the memory monitoring unit 319 obtains the remaining memory amount from the electrocardiogram signal measuring device 2, which is a biological information measuring device, and stores this remaining memory amount in the storage unit 317.

[0110] After storing the remaining memory, the control unit 316 determines whether the cumulative effective analysis amount is less than or equal to the second threshold and the remaining memory of the biological information measuring device is less than or equal to the third threshold (step S609). If the control unit 316 determines that the cumulative effective analysis amount is greater than the second threshold or the remaining memory of the biological information measuring device is greater than the third threshold (step S609: No), it proceeds to step S602 and repeats the determination process for the next analysis unit. On the other hand, if the control unit 316 determines that the cumulative effective analysis amount is less than or equal to the second threshold and the remaining memory of the biological information measuring device is less than or equal to the third threshold (step S609: Yes), it proceeds to step S610. In this case, the third threshold in this embodiment 3 is set as the remaining memory, for example, 5%. The second threshold in this embodiment 3 is the same as the second threshold in this embodiment 2.

[0111] In step S610, the control unit 316 performs a notification process to the administrator of the medical institution or other facility that there is insufficient memory, as a second measurement support action. After the notification process, the control unit 316 proceeds to step S602 and repeats the determination process for the next analysis unit.

[0112] According to Embodiment 3 described above, similar to Embodiment 1, the system notifies that the measurement is complete based on the cumulative effective analysis amount, which is the sum of the effective analysis amounts of analysis units capable of diagnosing arrhythmias. This enables measurement support in home medical care / long-term electrocardiogram analysis, etc., and prevents re-measurement due to insufficient effective analysis time.

[0113] Furthermore, according to this embodiment 3, since a predetermined measurement support action is executed with the remaining memory level of the biological information measuring device as one of the conditions, for example, by notifying the device that the remaining memory level is insufficient, it is possible to realize measurement support in home medical care / long-term electrocardiogram analysis, etc., which allows for the smooth arrangement (distribution) of the biological information measuring device itself and accessories such as memory.

[0114] (Embodiment 4) Next, Embodiment 4 of the present invention will be described. The components of the biological information management system according to Embodiment 2 are the same as the components of the biological information management system according to Embodiment 1, so their description will be omitted. The following describes a process that differs from Embodiment 1 with reference to Figure 10.

[0115] In this fourth embodiment, the storage unit 317, similar to the storage unit 317 in the first embodiment, stores the effective analysis amount calculated for each analysis unit as a cumulative effective analysis amount, and also resets the cumulative effective analysis amount at predetermined intervals. Here, the predetermined period can be set arbitrarily and may be based on predetermined parameters such as elapsed time or the number of analysis units that have been determined, or on an external command, but is not limited to these.

[0116] In this embodiment 4, the control unit 316, similar to the control unit 316 in embodiment 1, executes a predetermined measurement support action (first measurement support action) based on the stored cumulative effective analysis amount, and also executes a third measurement support action based on the number of times a second measurement support action different from the first measurement support action has been executed. Here, the first measurement support action may be in a form that encompasses the second measurement support action and / or the third measurement support action.

[0117] In this fourth embodiment, the cumulative effective analysis amount is reset every time the time reaches 9:00. At the time the cumulative effective analysis amount is reset, if the cumulative effective analysis amount for the day reaches, for example, 21,600 seconds, a first measurement support action is performed to notify subject 1 that the measurement for that day has been completed. If the cumulative effective analysis amount for the day has not reached 21,600 seconds, a second measurement support action is performed to notify subject 1 that the measurement for that day has not been completed. If the number of times the second measurement support action has been performed reaches seven, a third measurement support action is performed to notify subject 1 that all measurements for seven days have been completed.

[0118] Figure 10 is a flowchart showing the flow of the measurement support process according to Embodiment 4. In the measurement support process according to Embodiment 4, in the same manner as steps S101 to S105 of Embodiment 1 described above (see Figure 2), it is determined whether or not arrhythmia diagnosis is possible for each analysis unit, and the accumulated cumulative effective analysis volume is stored (steps S701 to S705).

[0119] The control unit 316 determines whether the time has crossed a predetermined time (step S706). If the control unit 316 determines that the time has crossed a predetermined time (step S706: Yes), it proceeds to step S707. On the other hand, if the control unit 316 determines that the time has not crossed a predetermined time (step S706: No), it proceeds to step S702 and repeats the determination process for the next analysis unit. The predetermined time here is set to, for example, 9:00. This predetermined time is set, for example, based on a predetermined activity time.

[0120] In step S707, the control unit 316 determines whether the cumulative effective analysis amount is equal to or greater than a first threshold. If the control unit 316 determines that the cumulative effective analysis amount is less than the first threshold (step S707: No), it proceeds to step S708. On the other hand, if the control unit 316 determines that the cumulative effective analysis amount is equal to or greater than the first threshold (step S707: Yes), it proceeds to step S712. In this embodiment 4, the first threshold is set, for example, based on the target daily cumulative effective analysis amount, and for example, the above-mentioned 21,600 seconds is set.

[0121] In step S708, the control unit 316 performs a first measurement support action by notifying the subject 1 that the measurement for that day has been completed. The control unit 316 then increments the number of times the first measurement support action has been performed (step S709).

[0122] After accumulating the number of times the first measurement support action is performed, the control unit 316 determines whether the number of times the first measurement support action is performed has reached a second threshold (step S710). If the control unit 316 determines that the number of times the first measurement support action is performed is less than the second threshold (step S710: No), it proceeds to step S713. On the other hand, if the control unit 316 determines that the number of times the first measurement support action is performed is equal to or greater than the second threshold (step S710: Yes), it proceeds to step S711. In this case, the second threshold is set to, for example, 7 times, which is the number of measurements required to complete all measurements.

[0123] In step S711, the control unit 316 performs a notification process to the subject 1 that all measurements for 7 days have been completed, as a second measurement support action.

[0124] Furthermore, in step S712, the control unit 316 performs a notification process to the subject 1 that the measurement for that day was not completed, as a third measurement support action.

[0125] Then, in step S713, the control unit 316 resets the cumulative effective analysis amount. This makes the cumulative effective analysis amount for the day zero. After resetting the cumulative effective analysis amount, the control unit 316 proceeds to step S602 and repeats the determination process for the next analysis unit.

[0126] According to Embodiment 4 described above, similar to Embodiment 1, the system notifies that the measurement is complete based on the cumulative effective analysis amount, which is the sum of the effective analysis amounts of analysis units capable of diagnosing arrhythmias. This enables measurement support in home medical care / long-term electrocardiogram analysis, etc., and prevents re-measurement due to insufficient effective analysis time.

[0127] Furthermore, according to this embodiment 4, by managing the cumulative effective analysis volume and measurement support actions for each short period, more complex measurement support becomes possible. Specifically, since seven days' worth of biological information that provides sufficient effective analysis time each day can be acquired, optimal measurement support can be achieved in cases where "diagnosis requires at least a certain number of days of effective analysis time," such as in follow-up observation of patients who have undergone treatment for arrhythmias with ablation or medication, or in cases where analysis time is required based on the medical fee system classification.

[0128] (Other Embodiments) While embodiments for carrying out the present invention have been described so far, the present invention is not limited to the embodiments described above. The present invention is not limited to the embodiments described above, and can be implemented in combination with each other. Furthermore, the present invention is not limited to the configurations shown in Embodiments 1 to 4 described above, and can be modified in various ways without departing from the spirit of the invention. For example, although the measurement support system has been described as being provided separately from the biological information measuring instrument, the measurement support system may be built into the biological information measuring instrument and configured integrally with the biological information measuring instrument.

[0129] Furthermore, each process, such as the analysis unit determination process by the analysis unit determination unit 312, the analysis feasibility determination process by the analysis feasibility determination unit 313, the effective analysis amount calculation process by the effective analysis amount calculation unit 314, the battery monitoring process by the battery monitoring unit 318, and the memory monitoring process by the memory monitoring unit 319, is preferably, but not limited to, being performed mechanically based on the instruction sequence of the control unit 316 and the setting values ​​stored in the storage unit 317, thereby eliminating human judgment.

[0130] 1 Subject 2 Electrocardiogram signal measuring device 3, 3A, 3B Measurement support system 4 Receiving terminal 5 Learning device 10 Electrocardiogram signal 11 Waveform data 41, 311 Communication unit 42 Output unit 43, 316 Control unit 100, 110, 120 Electrocardiogram waveform 312 Analysis unit determination unit 313 Analysis feasibility determination unit 314 Effective analysis amount calculation unit 315 Input / output unit 317 Storage unit 318 Battery monitoring unit 319 Memory monitoring unit

Claims

1. A biological information measurement support system that performs processing for managing target biological information, comprising: an input receiving unit that receives input of the biological information; an analysis unit determination unit that divides the biological information into a predetermined segment length and determines the divided segment as an analysis unit; an analysis feasibility determination unit that determines whether or not analysis is possible for the analysis unit; an effective analysis amount calculation unit that calculates an effective analysis amount based on the segment length and the analysis feasibility determination result; and a control unit that accumulates the effective analysis amounts of each analysis unit and executes a predetermined measurement support process based on the accumulated effective analysis amount.

2. The biological information measurement support system according to claim 1, wherein the segment length is set on a time basis and / or a waveform number basis.

3. The biological information measurement support system according to claim 1, wherein the effective analysis quantity and the cumulative effective analysis quantity are set on a time basis and / or a waveform number basis.

4. The biological information measurement support system according to claim 1, wherein the control unit executes the measurement support process based on whether or not the cumulative effective analysis amount exceeds a preset threshold.

5. The biological information measurement support system according to claim 1, wherein the control unit resets the cumulative effective analysis amount at predetermined intervals, executes a first measurement support process based on whether the cumulative effective analysis amount exceeds a first threshold within the predetermined period, and executes a second measurement support process different from the first measurement support process based on whether the cumulative number of executions obtained by accumulating the number of executions of the first measurement support process exceeds a second threshold.

6. A battery monitoring unit that acquires the remaining battery level of a biological information measuring device that measures the biological information, wherein the control unit performs a first measurement support process based on whether the cumulative effective analysis amount exceeds a first threshold, and performs a second measurement support process different from the first measurement support process based on whether the cumulative effective analysis amount exceeds a second threshold smaller than the first threshold, and whether the remaining battery level exceeds a third threshold.

7. A memory monitoring unit that acquires the remaining memory amount of a biological information measuring instrument that measures the biological information, wherein the control unit executes a first measurement support process based on whether the cumulative effective analysis amount exceeds a first threshold, and executes a second measurement support process different from the first measurement support process based on whether the cumulative effective analysis amount exceeds a second threshold smaller than the first threshold, and whether the remaining memory amount exceeds a third threshold.

8. The biological information measurement support system according to claim 1, further comprising an analysis unit for analyzing the biological information, and updating each parameter and / or method related to the measurement support processing based on the results of the analysis.

9. The biological information measurement support system according to claim 1, wherein the control unit performs notification processing to the wearer and / or administrator of the biological information measuring device that measures the biological information, as the measurement support processing.

10. The biological information measurement support system according to claim 1, wherein the control unit performs a notification process to prompt the distribution of a biological information measuring device and its associated components for measuring the biological information, as the measurement support process.

11. A biological information measurement support system according to claim 1, which is incorporated into a biological information measuring instrument that measures the biological information.

12. The biological information measurement support system according to claim 1, which is built into a server that is communicably connected to a biological information measuring device that measures the biological information.

13. A biological information measurement support program that performs processing for managing target biological information, wherein the program receives input of the biological information, divides the biological information into pre-set segment lengths, determines the divided segments as analysis units, determines whether analysis is possible for each analysis unit, calculates an effective analysis quantity based on the segment length and the result of the analysis feasibility determination, accumulates the effective analysis quantities for each analysis unit, and executes a pre-set measurement support process based on the accumulated effective analysis quantity, thereby causing a computer to perform a series of processes.

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