Recovery assistance device, recovery assistance system, and storage medium

Abstract

The present invention relates to a recovery assistance device, a recovery assistance system, and a storage medium. This recovery assistance device (22) comprises at least: an information acquisition unit (50) that acquires biological information relating to the physical function of a subject and treatment information including a plurality of treatment method candidates; a curve generation unit (52) that uses the acquired biological information and treatment information to generate, for each treatment method candidate, a prognosis prediction curve (94) indicating the prediction result of the degree of recovery of the physical function relative to elapsed time from a reference time point; and a display instruction unit 62 that instructs a display means (26) to compare and display the prognosis prediction curve (94) for each of the generated treatment method candidates.

Description

Recovery support device, recovery support system, and storage medium

[0001] The present invention relates to a recovery support device, a recovery support system, and a storage medium.

[0002] Conventionally, in various fields including medicine, health, nursing care, and sports, there are known techniques for detecting the movements of a subject using various sensors and using the obtained detection data to assist the subject in recovering their physical functions.

[0003] JP 2013-515995 A discloses a system that devise an exercise training plan for a patient and automatically updates the exercise training plan if physiological data measured during monitoring is outside a control range.

[0004] Japanese Patent Application Laid-Open No. 2021-022401 discloses a system that proposes rehabilitation goal examples and rehabilitation programs according to their respective priorities.

[0005] JP 2013-515995 A JP 2021-022401 A

[0006] However, when multiple treatment options are available for a patient, it can be difficult for medical professionals to grasp the differences in outcomes (i.e., clinical results) between the treatment options.

[0007] The present invention has been made in consideration of these problems, and its purpose is to provide a recovery support device, recovery support system, and storage medium that allow medical professionals to relatively easily understand the differences in outcomes between treatment methods.

[0008] A recovery support device in a first aspect of the present invention includes at least an information acquisition unit that acquires biometric information regarding the subject's physical function and treatment information including a plurality of candidate treatment methods, a curve generation unit that uses the biometric information and treatment information acquired by the information acquisition unit to generate, for each candidate treatment method, a prognosis prediction curve that indicates the predicted result of the degree of recovery of the physical function versus the elapsed time from a reference point in time, and a display instruction unit that instructs a display means to comparatively display the prognosis prediction curve for each candidate treatment method generated by the curve generation unit.

[0009] A recovery support system in a second aspect of the present invention comprises a terminal device having a display means and a recovery support device configured to be able to communicate with the terminal device, wherein the recovery support device comprises at least an information acquisition unit that acquires biometric information regarding the subject's physical functions and treatment information including a plurality of candidate treatment methods, a curve generation unit that uses the biometric information and the treatment information acquired by the information acquisition unit to generate, for each of the candidate treatment methods, a prognosis prediction curve that indicates the predicted result of the degree of recovery of the physical functions versus the elapsed time from a reference point in time, and a display instruction unit that instructs the display means to comparatively display the prognosis prediction curves for each of the candidate treatment methods generated by the curve generation unit.

[0010] The storage medium in the third aspect of the present invention stores a program for causing one or more computers to execute at least the following steps: an acquisition step of acquiring biometric information regarding the subject's physical functions and treatment information including a plurality of candidate treatment methods; a generation step of using the acquired biometric information and treatment information to generate, for each of the candidate treatment methods, a prognosis prediction curve indicating the predicted results of the degree of recovery of the physical functions versus the elapsed time from a reference point; and an instruction step of instructing a display means to comparatively display the generated prognosis prediction curves for each of the candidate treatment methods.

[0011] The recovery assistance program in a fourth aspect of the present invention causes one or more computers to execute at least the following steps: an acquisition step of acquiring biometric information regarding the subject's physical functions and treatment information including a plurality of candidate treatment methods; a generation step of using the acquired biometric information and treatment information to generate, for each of the candidate treatment methods, a prognosis prediction curve indicating the predicted results of the degree of recovery of the physical functions versus the elapsed time from a reference point in time; and an instruction step of instructing a display means to comparatively display the generated prognosis prediction curves for each of the candidate treatment methods.

[0012] According to the present invention, medical personnel can relatively easily grasp the differences in outcomes between treatment methods.

[0013] 1 is a diagram illustrating an overall configuration of a recovery support system in one embodiment of the present invention. FIG. 2 is a block diagram illustrating an example of the configuration of the recovery support device in FIG. 1. FIG. 3 is a functional block diagram of a curve generation unit shown in FIG. 2. FIG. 4 is a diagram illustrating an example of a method for classifying state groups. FIG. 5 is a diagram illustrating an example of a method for calculating a degree of recovery. FIG. 6 is a diagram illustrating an example of a generation result of a prognosis prediction curve. FIG. 7 is a flowchart regarding a first support operation by the recovery support device. FIG. 8 is a diagram illustrating an example of an input screen displayed on a display device of a terminal device. FIG. 9 is a diagram illustrating an example of a proposal screen displayed on a display device of a terminal device. FIG. 10 is a flowchart regarding a second support operation by the recovery support device. FIG. 11 is a diagram illustrating a first example of a progress confirmation screen displayed on a display device of a terminal device. FIG. 12 is a functional block diagram of a problem extraction unit shown in FIG. 2. FIG. 13 is a flowchart regarding a third support operation by the recovery support device. FIG. 14 is a diagram schematically illustrating the concept of a double loop realized by the recovery support system of FIG. 1.

[0014] Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings. To facilitate understanding of the description, the same components and steps in each drawing will be denoted by the same reference numerals as much as possible, and duplicate explanations will be omitted. Furthermore, the term "means" may be replaced with other terms such as "part," "unit," or "element."

[0015] [Configuration of Recovery Support System 10] <Overall Configuration> Figure 1 is a diagram showing the overall configuration of a recovery support system 10 according to one embodiment of the present invention. This recovery support system 10 is configured to be able to provide a "recovery support service" that supports the recovery of a subject's physical and mental functions through medical rehabilitation. Here, "medical rehabilitation" refers to training activities aimed at recovering, maintaining, or strengthening physical and mental functions. This recovery support system 10 can be applied in a variety of fields, including medicine, health, nursing care, and sports.

[0016] "Subjects" of rehabilitation include patients with paralysis of motor function of body parts, patients with reduced motor function of body parts, etc. Body parts are body parts (especially limbs or trunk) that are moved during extension / flexion movements, and specific examples include hands, feet, fingers, knees, elbows, hips, shoulders, neck, and waist.

[0017] Specifically, this recovery support system 10 includes one or more terminal devices 12, a data collection device group 14, rehabilitation devices 16, an in-hospital server 18, a relay device 20, and a recovery support device 22. The terminal devices 12, the data collection device group 14, the rehabilitation devices 16, the in-hospital server 18, and the relay device 20 are each installed on the premises of a medical institution such as a hospital or a clinic, and are configured to be able to communicate with each other via an in-hospital network NT1. The recovery support device 22 is configured to be able to communicate with at least the terminal devices 12 and the in-hospital server 18 via an external network NT2 and the relay device 20.

[0018] The terminal device 12 is a computer owned or managed by a medical professional belonging to a medical institution. Medical professionals include, for example, doctors, nurses, therapists, or caregivers. Specifically, the terminal device 12 is a stationary or portable computer, including a personal computer, laptop, smartphone, tablet, or wearable device. The terminal device 12 may include, for example, an input device 24, a display device 26 (corresponding to "display means"), a processor, memory, a speaker, a communication module, and a camera unit. The terminal device 12 creates a graphical user interface (GUI) by combining the input function of the input device 24 and the display function of the display device 26.

[0019] The data collection device group 14 is a collection of devices capable of acquiring various data related to the subject's physical functions. In the example of Fig. 1, the data collection device group 14 includes a wearable terminal 30, a camera 32, and a biometric device 34. The biometric device 34 can measure various biometric signals, including, for example, myoelectric potential signals, muscle sound signals, electroencephalogram signals, blood oxygen dynamics measured by muscle infrared spectroscopy, and muscle contraction videos measured by ultrasound echograms.

[0020] The rehabilitation equipment 16 is a device capable of acquiring various data related to the physical functions of the subject during rehabilitation. Examples of the rehabilitation equipment 16 include a fitness bike, a treadmill, a pneumatic strength training machine, a self-motion induction illusion system, and a brain-machine interface.

[0021] The hospital server 18 is a server device that manages various medical information in a medical institution. For example, an electronic medical record system, an ordering system, or a medical receipt system is built around the hospital server 18.

[0022] The recovery support device 22 is a computer that controls various aspects of support operations for recovering physical functions. In the example of Fig. 1, the recovery support device 22 is shown as a single computer, but instead, the recovery support device 22 may be a group of computers that form a distributed system. Furthermore, the recovery support device 22 may be a cloud-based server or an on-premise server.

[0023] <Configuration of Recovery Support Device 22> Fig. 2 is a block diagram showing an example of the configuration of the recovery support device 22 in Fig. 1. The recovery support device 22 includes a server-side communication unit 40, a server-side control unit 42, and a server-side storage unit 44.

[0024] The server-side communication unit 40 is an interface that transmits and receives electrical signals to and from external devices, thereby enabling the recovery support device 22 to exchange various data with the terminal device 12 or the hospital server 18.

[0025] The server-side control unit 42 is configured with a processor including a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The server-side control unit 42 reads and executes the recovery support program and necessary data stored in the server-side storage unit 44, thereby functioning as an information acquisition unit 50, a curve generation unit 52, a plan creation unit 54, a data processing unit 56, a problem extraction unit 58, a screen generation unit 60, a display instruction unit 62, and a notification instruction unit 64.

[0026] The information acquisition unit 50 acquires information necessary for the assist operation from an external device or the server-side storage unit 44. For example, the information acquisition unit 50 acquires patient information transmitted from the terminal device 12, and also reads and acquires various pieces of information corresponding to the patient information (for example, the biological information 80, the treatment information 82, or the related information 88 in FIG. 3 ) from the server-side storage unit 44.

[0027] The curve generator 52 uses the biological information 80 and treatment information 82 acquired by the information acquirer 50 to generate, for each candidate treatment method, a characteristic curve (hereinafter referred to as a "prognosis prediction curve") that indicates the predicted result of the degree of recovery of physical function versus the elapsed time from a reference time point. The "reference time point" may be any time point at which rehabilitation becomes necessary, such as the date of surgery for the subject. The specific operation of the curve generator 52 will be described later with reference to FIG. 3.

[0028] The plan creation unit 54 creates a treatment plan for the subject based on a treatment method selected from multiple candidate treatment methods. Examples of treatment methods include the type of exercise therapy, the type of physical therapy, the content of instruction, the magnitude of load, or a combination thereof. The treatment method may be [1] automatically selected based on the evaluation value (or outcome) for the prognosis prediction curve 94 ( FIG. 6 ), or [2] manually selected via the terminal device 12. In the case of manual selection, for example, a user control (e.g., a radio button, a text box, etc.) is used to select a treatment method from multiple candidate treatment methods.

[0029] The above-mentioned candidate treatment methods may be selected according to the attributes of the subject. For example, the plan creation unit 54 may extract relevant past cases based on the patient attributes of the subject, and select a treatment method that was actually adopted in the case as one candidate. Alternatively, the plan creation unit 54 may extract relevant past cases based on the patient attributes of the subject, and select a treatment method with a higher therapeutic effect as one candidate as a result of categorizing the case.

[0030] The data processing unit 56 performs various statistical processes on the population data to be analyzed. The data content includes, for example, the start date and number of days for each treatment method. The population attributes include, for example, [1] personal attributes including age, sex, height, and weight, [2] disease information including the name of the main disease and whether or not there are complications, and [3] scale attributes including nationwide, prefecture, region, and medical institution. The statistical processes may be [1] relatively simple arithmetic processes including the mean, mode, median, maximum, and minimum values, or [2] relatively complex arithmetic processes including principal component analysis, regression analysis, and clustering.

[0031] The problem extraction unit 58 extracts current problems related to the treatment plan using treatment plan information 77 indicating the treatment plan and treatment result information 78 indicating the treatment result. The specific operation of the problem extraction unit 58 will be described later with reference to FIG. 13.

[0032] The screen generator 60 generates display data indicating a screen to be displayed on a display means of an external device (for example, the display device 26 of the terminal device 12). Examples of the screen include: [1] an input screen 100 (FIG. 8) for inputting patient information; [2] a proposal screen 130 (FIG. 9) for proposing a treatment plan; [3] a progress confirmation screen 150 (FIG. 11) for checking the progress of the treatment plan; or [4] an analysis result screen 170 (FIG. 12) for presenting analysis results regarding the treatment plan or treatment results.

[0033] The display instruction unit 62 instructs the display means of the external device to display the screen generated by the screen generation unit 60. Specifically, the display instruction unit 62 transmits display data indicating the screen to be displayed to the external device (e.g., the terminal device 12). When displaying the proposal screen 130, the display instruction unit 62 instructs the display means to further display a user control for selecting a treatment method from among the multiple treatment method candidates, in addition to the comparative display of the prognosis prediction curves 94 for each treatment method candidate generated by the curve generation unit 52.

[0034] The notification instruction unit 64 instructs the notification means of the external device to issue a notification regarding the treatment plan created by the plan creation unit 54. The timing of the notification may be, for example, immediately before the start of an action or when a problem with the treatment plan is extracted. The notification may be in the form of an alert display, a message, a buzzer, audio guidance, or the illumination of a lamp.

[0035] The server-side storage unit 44 stores programs and data necessary for the server-side control unit 42 to control each component. The server-side storage unit 44 is configured from a non-transitory, computer-readable recording medium. Here, the computer-readable storage medium is a portable medium such as a magneto-optical disk, a read-only memory (ROM), a compact disc (CD)-ROM, or a flash memory, or a storage device built into a computer system such as a hard disk drive (HDD) or a solid-state drive (SSD).

[0036] In the example of Figure 2, the server-side memory unit 44 has constructed therein a database related to hospital information (hereinafter referred to as hospital information DB70), a database related to patient information (hereinafter referred to as patient information DB71), a database related to treatment content (hereinafter referred to as treatment content DB72), a database related to outcomes (hereinafter referred to as outcome DB73), and a database related to evidence (hereinafter referred to as evidence DB74).

[0037] The hospital information includes, for example, [1] organizational information such as the name of the medical institution and medical department, [2] personal information such as the names and affiliations of medical personnel, or [3] equipment information such as the rehabilitation equipment 16. The patient information includes, for example, [1] personal information such as the name, age, sex, height, and weight, or [2] morbidity information such as the diagnosis, current history, past medical history, and the presence or absence of other diseases.

[0038] The treatment details include, for example, [1] treatment plan information 77 including a treatment plan, [2] treatment result information 78 including treatment results, or [3] rehabilitation information related to rehabilitation. Examples of rehabilitation information include preset information (protocols established within the hospital), test results, treatment progress, and standard data. Standard data is data that indicates representative or typical values ​​in a population, and includes national average values, in-hospital average values, theoretical values, and literature values.

[0039] Outcomes include, for example, the target and actual values ​​of a treatment plan. Evidence includes the application conditions, contraindications, and effect size of each treatment method. Examples of outcome indicators include: [1] the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, the Japanese Knee Osteoarthritis Measure (JKOM) score, [2] the 10-meter walking test, the range of motion (ROM) measurement value, and [3] the degree of recovery on the prognosis prediction curve 94 (Figure 6).

[0040] The server-side storage unit 44 also stores prognosis prediction information 76, treatment plan information 77, treatment performance information 78, and analysis result information 79.

[0041] The prognosis prediction information 76 includes various information for identifying the functional shape of the prognosis prediction curve 94, specifically, a lookup table (LUT), the type and coefficients of the function, or the coordinate values ​​of two or more points passing through the prognosis prediction curve 94.

[0042] The treatment plan information 77 includes, for example, evaluation items, treatment methods, milestones, and risks. The evaluation items and treatment methods have been described above, so a repeated explanation will be omitted. Milestones include target values ​​for a given exercise, the necessity and type of equipment to be used (e.g., a walker, crutches, T-shaped cane, etc.). Risks include falls, deep vein thrombosis, and embryonic embolism. The treatment plan information 77 may also include information regarding daily routines within the treatment plan (hereinafter also referred to as "daily routine information").

[0043] The treatment result information 78 may include, for example, a result value (quantitative value or qualitative value) for a given exercise, whether or not a treatment method has been changed and the details of the change, or comments from medical professionals. The treatment result information 78 may also include information regarding the performance of daily routines in the treatment plan (hereinafter also referred to as "performance information").

[0044] The analysis result information 79 includes, for example, [1] the processing results by the data processing unit 56 (such as statistical values ​​of the start time and number of days for each treatment method) or [2] the extraction results by the problem extraction unit 58 (such as the first problem and second problem described below).

[0045] <Functional Blocks of Curve Generator 52> Figure 3 is a functional block diagram of the curve generator 52 shown in Figure 2. This curve generator 52 includes a group classification unit 52a, a recovery degree conversion unit 52b, and a curve shape determination unit 52c. After receiving the biological information 80, the treatment information 82, the classification information 84, the conversion information 86, and the related information 88, the curve generator 52 outputs the prognosis prediction information 76 already described in Figure 2.

[0046] The biological information 80 includes various biological data related to the subject's physical functions. In the case where the subject is a hemiplegic patient, examples of the biological data include muscle strength on the affected side, muscle strength on the healthy side, abductor muscle strength, lower limb muscle strength, and maximum walking speed.

[0047] The treatment information 82 includes multiple treatment methods that can be adopted for the subject. Here, if at least one of the types of exercise therapy, physical therapy, instruction content, and load magnitude differs, they are treated as different treatment methods.

[0048] Classification information 84 is provided for each treatment method included in the treatment information 82. Each classification information 84 includes partition information for partitioning multiple subregions in a multidimensional feature space 90 ( FIG. 4 ) with body feature values ​​as each axis. The subregions are divided through hierarchical clustering of population data of body feature values. The population data includes body feature values ​​of other people with which at least one type of personal attribute matches or is similar to the subject's, among multiple types of personal attributes assigned to the subject.

[0049] The conversion information 86 includes various information for describing conversion rules for converting the classified status groups into physical function recovery levels. The conversion information 86 includes, for example, [1] first information for converting the status groups into hierarchical categories, and [2] second information for converting the hierarchical categories into recovery levels.

[0050] The related information 88 includes various information correlated with the degree of recovery of physical functions, for example, patient information read from the patient information DB 71 or rehabilitation information read from the treatment content DB 72. For example, the younger the subject, the greater the rise in recovery tends to be, whereas the older the subject, the smaller the rise in recovery tends to be.

[0051] The group classification unit 52a classifies the biometric information 80 into groups related to the state of bodily functions (hereinafter also referred to as "condition groups") using classification information 84 that describes classification rules. For example, the group classification unit 52a calculates multiple types of body feature amounts based on the biometric information 80 at a reference time point or an elapsed time point, and identifies a condition group at the reference time point or an elapsed time point depending on whether the sub-regions in a multidimensional feature amount space 90, each axis of which is the body feature amount, belong to one of multiple sub-regions. The "elapsed time point" refers to a time point at which an elapsed time has elapsed since the reference time point. Note that prior to the classification, a "principal component analysis process" may be performed to reduce N types of body feature amounts to n (2≦n<N) types of body feature amounts.

[0052] FIG. 4 is a diagram showing an example of a method for classifying state groups. For convenience of illustration, a feature space 90 formed by multidimensional body feature values ​​is represented by a plane coordinate system with the first and second components of the body feature set as two axes. In the example of FIG. 4, multiple sub-regions in the feature space 90 are defined according to the description of the classification information 84 (FIG. 3). In this way, the state groups G1, G2, G5, and G7 are classified based on whether the sub-regions belong to a specific group and the subordinate relationships between the sub-regions.

[0053] 3 uses conversion information 86 describing a conversion rule to convert the status groups classified by the group classification unit 52a into physical function recovery levels. This conversion rule may be determined by a lookup table (LUT) or a function that uses the status groups as arguments. The index indicating the recovery level may be an index separate from the physical feature amount, or may be the physical feature amount itself.

[0054] FIG. 5 is a diagram showing an example of a method for calculating recovery levels. The example in FIG. 5 shows a tree structure 92 relating to condition groups G1 to G7. The hierarchical categories for each condition group G1 to G7 and the corresponding recovery levels are determined through the description of the conversion information 86 (FIG. 3). In this way, the recovery level of physical function can be quantitatively determined from the correspondence between the condition group and the hierarchical category.

[0055] The curve shape determination unit 52c in Fig. 3 determines the curve shape of the prognosis prediction curve 94 using the subject's related information 88. This curve shape simulates the tendency for the gradient of the recovery degree to be greatest immediately after the start of rehabilitation (near the reference time point) and for the gradient to gradually decrease over time. Examples of curve shapes include nonlinear functions such as polynomials, exponential functions, hyperbolic functions, logarithmic functions, and sigmoid functions. Parameters for determining the curve shape include, for example, the gradient at the reference time point or a saturation value (upper limit).

[0056] 6 is a diagram showing an example of the results of generating a prognosis prediction curve 94. The horizontal axis of the graph indicates elapsed time (unit: days), and the vertical axis of the graph indicates the degree of recovery (unit: dimensionless). The degree of recovery is defined as a continuous value in the range of [0, 100], for example, where the degree of recovery of physical function decreases as the value approaches 0 and increases as the value approaches 100. CX, CY, and CZ represent prognosis prediction curves 94 for treatment methods X, Y, and Z, respectively. As can be seen from the graph, the degree of recovery differs depending on the treatment method.

[0057] [Operation of Recovery Support System 10] The recovery support system 10 in this embodiment is configured as described above. Next, the support operation by the recovery support device 22 will be described with reference to FIGS.

[0058] <Explanation of First Assisting Action> The first assisting action by the recovery assist device 22 will be described with reference to the flowchart of Fig. 7. This first assisting action is performed to assist medical personnel in creating a treatment plan.

[0059] 7, the information acquisition unit 50 acquires the patient information of the subject. Prior to the acquisition, the terminal device 12 receives an instruction from the display instruction unit 62 and displays the input screen 100 (FIG. 8) on the display device 26.

[0060] 8 is a diagram showing an example of an input screen 100 displayed on the display device 26 of the terminal device 12. On the input screen 100, three types of input sections 102, 104, and 106 and four buttons 108, 110, 112, and 114 are provided.

[0061] The input section 102 is composed of a user control (e.g., a pair of radio buttons) for selecting whether or not to include patient information. The input section 104 is composed of a user control (e.g., a text box) for entering the patient's name. The input section 106 is composed of a user control (e.g., a text box) for entering the patient ID.

[0062] The "Details" button 108 is a user control for opening a window displaying detailed patient information. The "Enter" button 110 is a user control for opening a window for manually entering detailed patient information. The "Propose" button 112 is a user control for requesting a treatment plan proposal. The "Cancel" button 114 is a user control for canceling the display of the input screen 100.

[0063] After inputting the patient information through the input units 102, 104, and 106, the medical professional clicks or taps the [Proposal] button 112. In response, the information acquisition unit 50 receives a proposal request signal including the patient information from the terminal device 12, thereby acquiring the desired patient information.

[0064] In step SP12 of FIG. 7, the information acquisition unit 50 reads and acquires various information corresponding to the patient information acquired in step SP10, such as the biological information 80 and treatment information 82, from the corresponding database.

[0065] In step SP14, the curve generator 52 selects one candidate treatment method that has not yet been selected from among a plurality of candidate treatment methods that can be adopted in the treatment plan.

[0066] In step SP16, the curve generator 52 generates a prognosis prediction curve 94 in the case where the candidate treatment method selected in step SP14 is adopted.

[0067] In step SP18, the curve generator 52 checks whether all of the multiple candidate treatment methods have been selected in step SP14. If all of the candidate treatment methods have not been selected (step SP18: NO), the curve generator 52 returns to step SP14 and sequentially repeats steps SP14 to SP18 until all of the candidate treatment methods have been selected. On the other hand, if all of the candidate treatment methods have been selected (step SP18: YES), the curve generator 52 proceeds to the next step SP20.

[0068] In step SP20, the screen generator 60 generates display data showing the proposal screen 130 (FIG. 9) for comparatively displaying the multiple prognosis prediction curves 94 generated in step SP16.

[0069] In step SP22, the display instruction unit 62 instructs the terminal device 12 that transmitted the proposal request signal to display the proposal screen 130 generated in step SP20.

[0070] 9 is a diagram showing an example of a proposal screen 130 displayed on the display device 26 of the terminal device 12. The proposal screen 130 is provided with a patient information field 132, a candidate proposal field 134, a candidate selection section 136, a graph 138, a Gantt chart 140, and three buttons 142, 144, and 146.

[0071] The patient information field 132 shows the patient's name, age, sex, height, weight, primary illness, and whether or not they are experiencing pain. The candidate suggestion field 134 shows a first candidate treatment method (here, treatment method X) and a second candidate treatment method (here, treatment method Y). The candidate selection unit 136 is composed of a user control (e.g., a radio button) for selecting one treatment method. In the example of FIG. 9, the first candidate treatment method X is selected.

[0072] Graph 138 shows an overlay of a prognosis prediction curve for treatment method X (shown by a solid line) and a prognosis prediction curve for treatment method Y (shown by a dashed line). Gantt chart 140 shows the recommended timing for performing the four steps that make up treatment method X by the positions and lengths of the bars.

[0073] The "Evidence" button 142 is a user control for opening a window displaying evidence for potential treatments. The "OK" button 144 is a user control for opening a window for manually entering detailed patient information. The "Cancel" button 146 is a user control for canceling the display of the proposal screen 130.

[0074] Through the comparative display using the graph 138, the medical professional can see at a glance that treatment method X may have a higher outcome than treatment method Y. For example, the medical professional performs an operation to select treatment method X using the candidate selection unit 136, and then clicks or taps the [OK] button 144. Then, the information acquisition unit 50 receives a creation request signal including the selection result from the terminal device 12, thereby acquiring the desired selection result.

[0075] 7, the server-side control unit 42 checks whether or not the above-mentioned selection operation has been accepted via the terminal device 12. If the selection operation has not yet been accepted (step SP24: NO), the server-side control unit 42 remains in step SP24 until the selection operation is accepted. On the other hand, if the selection operation has been accepted (step SP24: NO), the server-side control unit 42 proceeds to the next step SP26.

[0076] In step SP26, the plan creation unit 54 creates a treatment plan for the subject based on the treatment method selected in step SP24. The created treatment plan is stored in the server-side storage unit 44 as treatment plan information 77.

[0077] In this way, the first assist operation by the recovery assist device 22 is completed. [1] Proposal of candidate treatment methods suitable for the subject and [2] Automatic creation of a treatment plan reduces the workload of medical personnel.

[0078] <Explanation of Second Assisting Operation> Next, the second assisting operation by the recovery assist device 22 will be described with reference to Figures 10 to 12. This second assisting operation is performed to assist medical personnel in managing the progress of the treatment plan.

[0079] In step SP30 of FIG. 10, the server-side control unit 42 accepts a progress confirmation request from the terminal device 12 by receiving a confirmation request signal including patient information.

[0080] In step SP32, the information acquisition unit 50 acquires the patient information included in the progress confirmation request received in step SP30.

[0081] In step SP34, the information acquisition unit 50 identifies the subject from the patient information acquired in step SP32, and acquires the treatment plan information 77 for the corresponding subject.

[0082] In step SP36, the data processing unit 56 uses the patient information acquired in step SP32 to determine population data consisting of a population of other individuals whose personal attributes match or are similar to those of the subject.

[0083] In step SP38, the data processing unit 56 performs statistical processing on the population data determined in step SP36.

[0084] In step SP40, the screen generator 60 generates display data for showing a progress confirmation screen 150 (FIG. 11) including the treatment plan information 77 acquired in step SP34 and the statistical processing result information obtained in step SP38.

[0085] In step SP42, the display instruction unit 62 instructs the terminal device 12 that sent the confirmation request signal to display the progress confirmation screen 150 generated in step SP40.

[0086] 11 is a diagram showing a first example of a progress check screen 150 displayed on the display device 26 of the terminal device 12. The progress check screen 150 is provided with a patient information field 152, a Gantt chart 154, and two buttons 156 and 158.

[0087] The patient information field 152 shows the patient's name, age, sex, height, weight, main illness, and whether or not they are experiencing pain. The Gantt chart 154 shows the in-hospital average, national average, in-hospital protocol, and planned performance for each process by the position and length of a bar. The [Analysis] button 156 is a user control for opening a window containing a separate analysis results screen 170. The [Cancel] button 158 is a user control for canceling the display of the progress confirmation screen 150. The cursor 160 indicates the current (today's) position on the time axis of the Gantt chart 154.

[0088] The medical personnel can grasp at a glance the progress of the current treatment plan through the comparative display of the Gantt chart 154. For example, the medical personnel clicks or taps the [Analysis] button 156. In response, the display instruction unit 62 instructs the terminal device 12 that sent the analysis request signal to display the analysis result screen 170 ( FIG. 12 ) further generated by the screen generation unit 60.

[0089] 12 is a diagram showing a second example of an analysis result screen 170 displayed on the display device 26 of the terminal device 12. The analysis result screen 170 is provided with a patient information field 172, a graph 174, two problem description fields 176 and 178, and a button 180 labeled "Back."

[0090] The patient information field 172 displays the patient's name, age, sex, height, weight, primary illness, and whether or not they are experiencing pain. The graph 174 displays a graph 182 (shown by a solid line) indicating the treatment plan and a plurality of points 184 indicating treatment results, superimposed on each other. The problem description field 176 displays problems related to the implementation of the treatment plan (hereinafter also referred to as "first problems"). The problem description field 178 displays problems related to the implementation of daily routines within the treatment plan (hereinafter also referred to as "second problems"). The "Back" button 180 is a user control for canceling the display of the analysis result screen 170 and returning to the progress confirmation screen.

[0091] Medical personnel can see at a glance that progress on the current treatment plan is beginning to slow down through the comparative display of graph 174. Medical personnel can also see at a glance any problems with the treatment plan or daily routine through the contents displayed in problem description fields 176 and 178.

[0092] In this way, the second support operation by the recovery support device 22 is completed. By displaying the progress check results of the treatment plan, it is possible to compare the treatment plan with the treatment results and feed back any discrepancies between them. For example, if a delay occurs in the treatment plan, it is possible to prompt medical personnel to review the treatment plan.

[0093] <Explanation of Third Assisting Operation> Next, the third assisting operation by the recovery assist device 22 will be described with reference to Figures 13 to 15. This third assisting operation is performed to assist medical personnel in managing the progress of the treatment plan.

[0094] Fig. 13 is a functional block diagram of the problem extraction unit 58 shown in Fig. 2. This problem extraction unit 58 includes an information selection unit 58a, a first analysis unit 58b, and a second analysis unit 58c. After the treatment plan information 77 and the treatment result information 78 are input, the problem extraction unit 58 outputs the analysis result information 79 already explained in Fig. 2.

[0095] The information selection unit 58a selects and outputs information according to the type of analysis processing from the treatment plan information 77 and the treatment result information 78. When the selection flag has a value indicating "main loop," the information selection unit 58a selects information related to the execution of the treatment plan (hereinafter also referred to as "first analysis information") and supplies the first analysis information to the first analysis unit 58b. When the selection flag has a value indicating "daily loop," the information selection unit 58a selects information related to the daily routine of the treatment plan (hereinafter also referred to as "second analysis information") and supplies the second analysis information to the second analysis unit 58c.

[0096] The first analysis unit 58b performs an analysis process on the first analysis information from the information selection unit 58a to analyze the presence and type of a problem (i.e., a first problem) related to the execution of the overall plan (i.e., the main loop). The analysis result is output as one form of analysis result information 79. For example, the first analysis unit 58b determines that there is no first problem when the difference between an index in the treatment results (hereinafter, the actual value) and an index in the treatment plan (hereinafter, the target value) is below a threshold, and determines that there is a first problem when the difference between the actual value and the target value is above the threshold. The first analysis unit 58b may also perform a search process to search past case data to identify the presence or type of the first problem.

[0097] The second analysis unit 58c performs an analysis process on the second analysis information from the information selection unit 58a to analyze the presence and type of a problem (i.e., a second problem) related to the performance of the daily routine (i.e., the daily loop). The analysis result is output as one form of analysis result information 79. For example, the second analysis unit 58c may perform a search process to search past case data to identify the presence or type of the second problem.

[0098] Next, the second assisting operation by the recovery assisting device 22 will be described with reference to the flowchart of FIG.

[0099] 14, the server-side control unit 42 checks, through receipt of an extraction request signal including patient information, whether or not it has accepted an extraction request from the terminal device 12. If an extraction request has not yet been accepted (step SP50: NO), the server-side control unit 42 remains in step SP50 until it accepts the extraction request.

[0100] On the other hand, if an extraction request has been received from the terminal device 12 (step SP50: YES), the server-side control unit 42 proceeds to the next step SP52. In the example of Fig. 11, the extraction request is made when the [Analysis] button 158 on the progress confirmation screen 150 is clicked or tapped.

[0101] In step SP52, the problem extractor 58 checks the type of treatment loop by referring to the value of the selection flag. If the main loop is selected (step SP52: main loop), the problem extractor 58 proceeds to step SP54.

[0102] In step SP54, the problem extraction section 58 (more specifically, the information selection section 58a) selects and outputs the first analysis information from the treatment plan information 77 and the treatment result information 78 related to the patient.

[0103] In step SP56, the problem extraction unit 58 (more specifically, the first analysis unit 58b) performs an analysis process on the first analysis information selected in step SP54 to extract a first problem in the main loop (i.e., the overall plan). Thereafter, the problem extraction unit 58 proceeds to step SP62, which will be described later.

[0104] Returning to step SP52, if the daily loop is selected (step SP52: daily loop), the problem extracting section 58 proceeds to step SP58.

[0105] In step SP58, the problem extraction section 58 (more specifically, the information selection section 58a) selects and outputs second analysis information from the treatment plan information 77 and treatment result information 78 related to the patient.

[0106] In step SP60, the problem extraction unit 58 (more specifically, the second analysis unit 58c) performs an analysis process on the second analysis information selected in step SP58 to extract a second problem in the daily loop (i.e., daily routine). Thereafter, the problem extraction unit 58 proceeds to the next step SP62.

[0107] In step SP62, the problem extraction unit 58 checks whether or not a first problem has been extracted in step SP56 (or whether or not a second problem has been extracted in step SP60). If no problem has been extracted (step SP62: NO), the server-side control unit 42 returns to step SP50 and sequentially repeats steps SP50 to SP62. On the other hand, if a problem has been extracted (step SP62: YES), the process proceeds to the next step, SP64.

[0108] In step SP64, the display instruction unit 62 instructs the terminal device 12 that sent the extraction request signal to display the problems extracted by the problem extraction unit 58. As a result, the analysis result screen 170 (FIG. 12) including problem description fields 176 and 178 is displayed.

[0109] This is how the third assisting operation by the recovery assisting device 22 ends. By displaying the problems with the treatment plan, it is possible to encourage, for example, medical personnel to review the overall plan or daily routine.

[0110] Figure 15 is a diagram that schematically illustrates the concept of a double loop realized by the recovery support system 10 of Figure 1. This diagram shows the physical therapy treatment process in parallel on two time scales. This double loop is composed of [1] a "main loop" that is developed from a medium- to long-term perspective, and [2] a "daily loop" that is developed from a short-term perspective. Both the main loop and the daily loop show the framework of the "OODA cycle."

[0111] The OODA cycle consists of four phases: [1] Observe, [2] Orient, [3] Decide, and [4] Act. Daily diagnosis is performed as the "A" (Act) of the main loop. During daily diagnosis, the "O" (Observe), "O" (Understand), "D" (Decide), and "A" (Act) loops are constantly running, with information constantly being updated and reflected in the execution of treatment. The information obtained in each daily loop is stored in the main loop database and is used when updating the main loop.

[0112] For example, in pre-clinical training, students can learn about the framework of clinical practice through double-loop simulation. Furthermore, in clinical practice, physical therapists and occupational therapists can visually grasp the type of treatment they are performing, including the timeline. This allows medical professionals to virtually experience a real-life treatment.

[0113] 15 has been described using an example of a recovery support service with a double loop, the framework is not limited to this configuration. For example, a recovery support service that implements only a main loop may be provided, or a recovery support service that implements only a daily loop may be provided.

[0114] [Summary of the embodiment] As described above, the recovery support system 10 in this embodiment includes a terminal device 12 having a display means (here, the display device 26), and a recovery support device 22 configured to be able to communicate with the terminal device 12. The recovery support device 22 includes at least an information acquisition unit 50 that acquires biological information 80 related to the subject's physical functions and treatment information 82 including a plurality of candidate treatment methods, a curve generation unit 52 that uses the acquired biological information 80 and treatment information 82 to generate, for each candidate treatment method, a prognosis prediction curve 94 that indicates a prediction result of the degree of recovery of the physical function with respect to the elapsed time from a reference time point, and a display instruction unit 62 that instructs the display device 26 (or the terminal device 12) to comparatively display the generated prognosis prediction curve 94 for each candidate treatment method.

[0115] According to the recovery support program and recovery support method of this embodiment, one or more computers (or one or more processors) execute at least an acquisition step (SP12) of acquiring biometric information 80 regarding the subject's physical function and treatment information 82 including multiple candidate treatment methods, a generation step (SP16) of using the acquired biometric information 80 and treatment information 82 to generate, for each candidate treatment method, a prognosis prediction curve 94 showing the predicted results of the degree of recovery of physical function over time since a reference point, and an instruction step (SP20) of instructing the display device 26 (or terminal device 12) to comparatively display the generated prognosis prediction curves 94 for each candidate treatment method.

[0116] In this way, by instructing the display device 26 to display a comparative display of the prognosis prediction curves 94 for each candidate treatment method, medical personnel can relatively easily grasp the differences in outcomes for each treatment method through this comparative display.

[0117] Furthermore, the curve generating unit 52 may obtain multiple types of physical feature amounts based on the biometric information 80 at the reference time point or the elapsed time point, and calculate the degree of recovery at the reference time point or the elapsed time point depending on whether the subregions belong to multiple subregions partitioned in a multidimensional feature space 90 with the physical feature amounts as each axis.

[0118] The subregions may be divided by hierarchical clustering of population data of physical features. The population data may include physical features of other people with which at least one of the multiple types of personal attributes assigned to the subject matches or is similar.

[0119] In addition, the display instruction unit 62 may instruct the display device 26 of the terminal device 12 to further display a user control (here, the candidate selection unit 136) for selecting a treatment method from among multiple candidate treatment methods, along with the comparative display of the prognosis prediction curve 94.

[0120] In addition, the recovery support device 22 may further include a plan creation unit 54 that, when receiving a selection operation by a medical professional via the candidate selection unit 136, creates a treatment plan for the subject based on the selected treatment method, and a notification instruction unit 64 that instructs an external device to issue a notification regarding the execution of the treatment plan created by the plan creation unit 54.

[0121] In addition, the recovery support device 22 may further include a plan creation unit 54 that creates a treatment plan for the subject based on a treatment method selected from a plurality of candidate treatment methods, and a problem extraction unit 58 that extracts a first problem regarding the execution of the treatment plan using treatment plan information 77 that indicates the created treatment plan and treatment result information 78 that indicates the treatment results for the treatment plan.

[0122] In addition, if the treatment plan information 77 includes daily routine information regarding the daily routine of the treatment plan and the treatment result information 78 includes performance information regarding the performance of the daily routine, the problem extraction unit 58 may further extract a second problem regarding the performance of the daily routine using the daily routine information and the performance information.

[0123] The display instruction unit 62 may also instruct the display device 26 (or the terminal device 12) to display at least one of the extracted first problem and second problem.

[0124] [Modifications] The present invention is not limited to the above-described specific examples. In other words, designs that are appropriately modified by a person skilled in the art from the above-described specific examples are also included within the scope of the present invention as long as they include the features of the present invention. Furthermore, the elements of the above-described embodiments can be combined to the extent technically possible, and such combinations are also included within the scope of the present invention as long as they include the features of the present invention.

[0125] 2 and 3 generates the prognosis prediction curve 94 using a statistical method, the curve generation method is not limited to the statistical method. For example, machine learning may be performed on a regressor that receives a set of body feature amounts as input and outputs a time series of recovery levels, and the shape of the prognosis prediction curve may be determined using the trained regressor.

[0126] In the above embodiment, an example is described in which the databases are built inside the recovery support device 22. Alternatively, at least a part of the databases may be built in an external device. In this case, the recovery support device 22 may request the external device to analyze the population data and obtain the necessary analysis results from the external device.

[0127] [Explanation of symbols] 10. Recovery support system, 12. Terminal device, 22. Recovery support device, 50. Information acquisition unit, 52. Curve generation unit, 54. Plan creation unit, 58. Problem extraction unit, 60. Screen generation unit, 62. Display instruction unit, 76. Prognosis prediction information, 77. Treatment plan information, 78. Treatment performance information, 79. Analysis result information, 80. Biological information, 82. Treatment information, 100. Input screen, 130. Proposal screen, 150. Progress confirmation screen, 170. Analysis result screen

Claims

1. A recovery support device comprising: an information acquisition unit that acquires at least bioinformation regarding a subject's physical function and treatment information including a plurality of candidate treatment methods; a curve generation unit that uses the bioinformation and treatment information acquired by the information acquisition unit to generate, for each of the candidate treatment methods, a prognosis prediction curve indicating a prediction result of the degree of recovery of the physical function versus the elapsed time from a reference point in time; and a display instruction unit that instructs a display means to comparatively display the prognosis prediction curves for each of the candidate treatment methods generated by the curve generation unit.

2. The recovery support device of claim 1, wherein the curve generation unit determines multiple types of body features based on the biometric information at the reference time point or the elapsed time point, and calculates the recovery level at the reference time point or the elapsed time point depending on whether the recovery level belongs to multiple sub-areas partitioned in a multi-dimensional feature space with the body features as each axis.

3. The recovery support device according to claim 2, wherein the sub-regions are divided through hierarchical clustering of population data of the physical features.

4. The recovery support device according to claim 3, wherein the population data includes physical features of other people with which at least one of the multiple types of personal attributes assigned to the subject is identical or similar.

5. The recovery support device according to claim 1, wherein the display instruction unit instructs the display means to further display user controls for selecting a treatment method from among the plurality of candidate treatment methods, together with the comparative display of the prognostic prediction curves.

6. The recovery support device as described in claim 5, further comprising: a plan creation unit which, when a selection operation by a medical professional is received via the user control, creates a treatment plan for the subject based on the selected treatment method; and a notification instruction unit which instructs an external device to provide a notification regarding the execution of the treatment plan created by the plan creation unit.

7. The recovery support device of claim 1, further comprising: a plan creation unit that creates a treatment plan for the subject based on the treatment method selected from the plurality of candidate treatment methods; and a problem extraction unit that extracts a first problem regarding the execution of the treatment plan using treatment plan information indicative of the treatment plan created by the plan creation unit and treatment result information indicative of treatment results for the treatment plan.

8. The recovery support device of claim 7, wherein the treatment plan information includes daily routine information regarding the daily routine of the treatment plan, the treatment performance information includes performance information regarding the performance of the daily routine, and the problem extraction unit further extracts a second problem regarding the performance of the daily routine using the daily routine information and the performance information.

9. The recovery support device according to claim 8, wherein said display instruction section instructs said display means to display at least one of said first problem and said second problem extracted by said problem extraction section.

10. A recovery support system comprising: a terminal device having a display means; and a recovery support device configured to be able to communicate with the terminal device, wherein the recovery support device comprises: an information acquisition unit that acquires at least bioinformation regarding a subject's physical function and treatment information including a plurality of candidate treatment methods; a curve generation unit that uses the bioinformation and the treatment information acquired by the information acquisition unit to generate, for each of the candidate treatment methods, a prognosis prediction curve indicating a prediction result of the degree of recovery of the physical function versus the elapsed time from a reference point in time; and a display instruction unit that instructs the display means to comparatively display the prognosis prediction curve for each of the candidate treatment methods generated by the curve generation unit.

11. A storage medium storing a program, the program causing one or more computers to execute at least the following steps: an acquisition step of acquiring bioinformation regarding a subject's physical functions and treatment information including a plurality of candidate treatment methods; a generation step of using the acquired bioinformation and treatment information to generate, for each of the candidate treatment methods, a prognosis prediction curve indicating a prediction result of the degree of recovery of the physical functions versus the elapsed time from a reference point in time; and an instruction step of instructing a display means to comparatively display the generated prognosis prediction curves for each of the candidate treatment methods.

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