Health status assessment device

Abstract

To evaluate the health state of a target site more accurately.SOLUTION: A health state evaluation device 10 includes: a video data acquisition unit 11 for acquiring plural pieces of video data about different actions related to a target site of a subject whose health state is to be evaluated; a state score calculation unit 13 for calculating at least one state score showing the state of the action from each video data; and a site-specific score calculation unit 14 for calculating a site-specific score related to the health state of the target site on the basis of the state score.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a health status assessment device. [Background technology]

[0002] With the increasing number of elderly people, various methods for supporting the improvement of physical functions have been studied. For example, Patent Document 1 describes a technology that acquires image data related to a predetermined function of a target user using a camera, extracts feature amounts related to the predetermined function from the image data, and determines an exercise program based on the feature amounts. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-26650 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the method described in Patent Document 1 evaluates a predetermined function of a target area, but does not consider evaluating the health condition of the target area from a broader perspective.

[0005] The present disclosure aims to provide a technology that enables more accurate evaluation of the health state of a target area. [Means for solving the problem]

[0006] A health status evaluation device according to one embodiment of the present disclosure includes a video data acquisition unit that acquires multiple video data images of different movements related to a target body part of a subject whose health status is to be evaluated, a status score calculation unit that calculates one or more status scores indicating the status of the movements from each of the multiple video data images, and a body part score calculation unit that calculates a body part score related to the health status of the target body part based on the status scores.

[0007] According to the above-described health condition evaluation device, one or more condition scores indicating the state of each movement are calculated from each of a plurality of video data capturing different movements, and a body part score relating to the health condition of the target body part is calculated based on these condition scores. In this way, body part scores indicating the health condition of each body part are calculated from a plurality of video data capturing different movements, so the health condition of the target body part can be evaluated more multifacetedly and accurately than when focusing on a specific movement of the body part. [Effects of the Invention]

[0008] According to the present invention, a technique is provided that enables more accurate evaluation of the health condition of a target area. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of a schematic configuration of a health state evaluation system including a health state evaluation device. [Figure 2] FIG. 2 is a diagram showing an example of a correspondence relationship between a movement performed by a subject and a state detected by a state detection unit. [Figure 3] 3(a) and 3(b) are diagrams illustrating an example of a method for calculating a condition score. [Figure 4] FIG. 4 is a diagram illustrating an example of a method for calculating the site-specific score. [Figure 5] FIG. 5 is a diagram illustrating an example of a hardware configuration of a health state evaluation device. [Figure 6] FIG. 6 is a flowchart showing an example of a health condition evaluation method. [Figure 7] FIG. 7 is a diagram showing an example of the configuration of a health condition evaluation program. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same elements are designated by the same reference numerals, and duplicated explanations will be omitted.

[0011] [Health status evaluation system and health status evaluation device] FIG. 1 is a schematic diagram of a health condition evaluation system 1 including a health condition evaluation device 10 according to one embodiment. The health condition evaluation system 1 is a system that captures moving images of the movements of a subject X and evaluates the health condition of target parts of the subject X based on this moving image data. In this embodiment, a case will be described in which the health condition of the "stomatognathic system" is evaluated as the target part of the subject X. The stomatognathic system includes four target parts: the tongue, lips, chin, and cheeks. The health condition evaluation system 1 calculates a site-specific score D as a score indicating the health condition for each of the four sites, and also calculates a score indicating the health condition of all sites, i.e., the stomatognathic system.

[0012] The health state evaluation system 1 includes a health state evaluation device 10 and an imaging device 20. The imaging device 20 has a function of capturing moving images relating to the movement of a target part of the subject X. The imaging device 20 is not limited to any device that has a function of capturing moving images, and devices such as a camera, a tablet terminal, or a smartphone can be used.

[0013] The health state evaluation device 10 includes a video data acquisition unit 11, a state detection unit 12, a state score calculation unit 13, a body part score calculation unit 14, a result output unit 15, and a related information storage unit 16.

[0014] The video data acquiring unit 11 has a function of acquiring multiple types of video data capturing the movements of the subject X from the imaging device 20. The video data of the subject X is data capturing images of the subject X performing movements that are previously specified for calculating the score of the target body part. For example, movements used in evaluating the health state of the stomatognathic system include, for example, pronunciation movements in which a single sound is repeatedly pronounced for a predetermined period of time, facial movements in which several specified facial expressions are imitated, and tongue movement movements in which the tongue is pointed in a specified direction. The subject X is made to perform these movements, and the video images are acquired by the imaging device 20. At this time, video data including audio data is acquired by the imaging device 20, and this data is transmitted to the health state evaluation device 10. The video data acquired by the video data acquiring unit 11 from the imaging device 20 is used for subsequent analysis.

[0015] The state detection unit 12 detects the state of the subject X using the video data acquired by the video data acquisition unit 11. FIG. 2 is a diagram illustrating an example of the relationship between actions and states. The "state" to be detected is an index indicating the degree to which a specified action is performed. One or more "states" are set for each action, and each is quantified. For example, for pronunciation actions, the number of pronunciations and clarity of pronunciation can be used as indices by analyzing audio data. Various methods can be used to analyze audio data, and one example is an analysis method using machine learning. For example, a spectrogram can be created by spectrally analyzing the audio data, and feature values ​​can be extracted from the spectrogram using a convolutional neural network (CNN). Furthermore, by using a model such as a long short-term memory (LSTM) or a recurrent neural network (RNN) to calculate the occurrence probability of each state, information related to the sound produced, the number of pronunciations, clarity of pronunciation, etc. can be obtained. These techniques are used in speech recognition methods, and by applying them, it is possible to obtain pronunciation information from speech data.

[0016] On the other hand, by performing image analysis on video data of pronunciation movements, the magnitude of jaw movement can be quantified and used as a numerical value indicating the "state." One example of such analysis is the application of a state detection model using image data. For example, a judgment system model for judging jaw movement, constructed in advance by learning data with known states using a Residual Neural Network (Residual Neural Network), and a measurement system model for measuring the degree of mouth opening and tilt, are prepared, and jaw movement can be quantified by applying image data to these models. Note that the method for creating the judgment system model and the measurement model is not limited to the above-mentioned Residual Neural Network, and known machine learning methods can also be used.

[0017] Similarly, for facial movements, for example, the amount of movement when a facial expression is specified and the duration of the expression can be used as numerical values ​​indicating the state by performing image analysis. Also, for tongue movements, for example, the amount of movement, the duration of time the tongue is stuck out in a specified direction, the degree of mouth opening when stationary, etc. can be used as numerical values ​​indicating the state of the movement.

[0018] As described above, the state detection unit 12 uses various information contained in the video data relating to each action to quantify each indicator indicating the state of the action. Note that the type of state to be quantified may be determined in advance, and this information may be stored in the related information storage unit 16.

[0019] The state score calculation unit 13 has a function of calculating a score from the numerical value of the index detected by the state detection unit 12. Fig. 3 shows an example of the correspondence between the numerical value of the index and the score. Fig. 3(a) shows an example of calculating the state score according to the number of times a predetermined sound is pronounced in a pronunciation operation, where, for example, if the number of pronunciations is 1 to 10, the score is 1 point, if the number of pronunciations is 11 to 30, the score is 5 points, and if the number of pronunciations is 31 or more, the score is 10 points. In this way, the state score calculation unit 13 converts the numerical value of each index into a score.

[0020] FIG. 3(b) shows an example of dynamically changing the relationship between an index (here, the number of pronunciations) and a score, where the score assignment is changed according to the numerical distribution of the index. In this example, a standard is set according to the distribution of the index of the subjects, such that subjects in the top predetermined percentage (e.g., 25%) are given a score of 10 points, subjects in the bottom predetermined percentage (e.g., 25%) are given a score of 1 point, and subjects in between are given a score of 5 points. The relationship between the numerical value of the number of pronunciations and the score is adjusted so that scores are assigned according to this ratio. As a result, in the example shown in FIG. 3(b), if the number of pronunciations is 1 to 7, the score is 1 point, if the number of pronunciations is 8 to 15, the score is 5 points, and if the number of pronunciations is 16 or more, the score is 10 points. In this way, when the condition score calculation unit 13 calculates the score, the relationship between the numerical value of the index and the score may be adjusted so that the relative numerical difference with others is more easily reflected in the score. Note that the score adjustment method may also be an adjustment that takes into account the variation in numerical values ​​related to the condition of a large number of subjects, as described above.

[0021] The body part score calculation unit 14 has a function of calculating a condition score for each target body part from the condition scores obtained for each of the above movements. The calculated scores are scores for specific indicators for each movement, and each indicator may be related to at least one of the tongue, lips, jaw, and cheeks. For example, the number of pronunciations in a pronunciation movement can be estimated to be related to the health of the tongue, lips, and jaw. The clarity of pronunciation in a pronunciation movement can be estimated to be related to the health of the tongue and lips. Furthermore, the amount of movement in a facial expression movement can be estimated to be related to the health of the lips, jaw, and cheeks. In this way, the score for the target body part is calculated by combining the condition scores calculated from each of the above movements that are related to the target body part.

[0022] Figure 4 shows an example of how scores are calculated for each body part. Here, the score is set to be calculated on a scale of 100 points. For example, condition scores related to the tongue include the number of pronunciations, clarity of pronunciation, tongue movement amount, and tongue movement maintenance time. These condition scores for the subject are added together, and the score obtained when all condition scores are full marks is set to 100 points. The score is calculated using the following formula (1). (Total condition score / (Number of condition scores x 10)) x 100...(1) Here, each condition score is set to a maximum of 10 points, and the condition for a perfect condition score is the number of condition scores (type of condition score) × 10. However, when calculating the condition score for each body part, a predetermined condition score may be set to a maximum of 20 points by, for example, weighting. In this case, the part (number of condition scores × 10) in the above formula (1) is changed as appropriate.

[0023] The condition score for the lips shown in Figure 4 is calculated in the same way as for the tongue. For the lips, different scores are set for the number of pronunciations and clarity of pronunciation among the condition scores related to pronunciation movements, depending on the type of sound pronounced. In this way, the condition scores may be set by further dividing the movements.

[0024] Furthermore, in Figure 4, a total score is also calculated. Here, the average value of the scores for each part of the tongue, lips, chin, and cheeks is calculated as the condition score for all parts (stomatognathic system). Using the average value is just one example, and different weightings may be applied to each part.

[0025] In this way, the body part score calculation unit 14 calculates a body part score for each target body part by combining the condition scores obtained from the test movements. Note that which condition score for which movement is to be used when calculating the body part score is determined in advance. This information may also be stored in the related information storage unit 16.

[0026] The result output unit 15 has a function of outputting the site-specific scores calculated by the site-specific score calculation unit 14. The output destination and output method are not particularly limited, but for example, the results may be output as data to an external device or may be displayed on a monitor or the like.

[0027] The related information storage unit 16 has a function of storing various information used in calculating the above-mentioned body part scores. Examples of information stored in the related information storage unit 16 include a method for calculating the numerical value related to the above-mentioned condition (e.g., a method for analyzing an image), information related to the correspondence between the numerical value related to the condition and the score, a method for calculating the body part score, etc. In addition to these, information used in each process in the health condition evaluation device 10 may also be stored.

[0028] [Hardware configuration] For example, the above-described health state evaluation device 10 may function as a computer. Fig. 5 is a diagram showing an example of the hardware configuration of the health state evaluation device 10 according to this embodiment. Physically, the health state evaluation device 10 may be configured as a computer device including a processor C1, a memory C2, a storage C3, a communication device C4, an input device C5, an output device C6, a bus C7, etc.

[0029] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the health state evaluation apparatus 10 may be configured to include one or more of the devices shown in FIG. 5. Alternatively, it may be configured without including some of the devices.

[0030] Each function of the health status evaluation device 10 is realized by loading specific software onto hardware such as the processor C1 and memory C2, causing the processor C1 to perform calculations and control communication via the communication device C4, and reading and / or writing of data in the memory C2 and storage C3.

[0031] The processor C1, for example, runs an operating system to control the entire computer. The processor C1 may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc. The processor C1 may also be configured to include a graphics processing unit (GPU). For example, each functional unit of the health state evaluation device 10 may be realized by the processor C1.

[0032] The processor C1 also reads programs (program codes), software modules, and data from the storage C3 and / or the communication device C4 into the memory C2 and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. For example, each functional unit of the health state evaluation device 10 may be implemented by a control program stored in the memory C2 and executed by the processor C1. While the above-described various processes have been described as being executed by one processor C1, they may also be executed simultaneously or sequentially by two or more processors C1. The processor C1 may be implemented on one or more chips. The programs may also be transmitted from a network via a telecommunications line.

[0033] The memory C2 is a computer-readable recording medium and may be composed of at least one of, for example, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), and a random access memory (RAM). The memory C2 may also be called a register, a cache, a main memory (primary storage device), or the like. The memory C2 can store executable programs (program codes), software modules, and the like for implementing a health condition evaluation method according to one embodiment of the present invention.

[0034] Storage C3 is a computer-readable recording medium, and may be composed of at least one of an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray disc), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy disk, a magnetic strip, etc. Storage C3 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including memory C2 and / or storage C3.

[0035] The communication device C4 is hardware (transmission / reception device) for performing communication between computers via a wired and / or wireless network, and is also called, for example, a network device, a network controller, a network card, or a communication module.

[0036] The input device C5 is an input device (for example, a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device C6 is an output device (for example, a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device C5 and the output device C6 may be integrated into one device (for example, a touch panel).

[0037] Furthermore, each device such as the processor C1 and memory C2 is connected by a bus C7 for communicating information. The bus C7 may be configured as a single bus, or may be configured as different buses between the devices.

[0038] [Health status assessment method] A health state evaluation method using the health state evaluation device 10 will be described with reference to FIG.

[0039] First, the health state evaluation device 10 executes step S01. In step S01, the moving image data acquisition unit 11 acquires moving image data from the imaging device 20.

[0040] Next, health state evaluation device 10 executes step S02. In step S02, state detection unit 12 detects a preset state from the video data. As a result, a numerical value that serves as an index of a specific state is obtained. As described above, one or more states are detected from one piece of video data. Furthermore, if there are multiple pieces of video data, the same process is performed for each piece of video data.

[0041] Next, health state evaluation device 10 executes step S03. In step S03, condition score calculation unit 13 converts the numerical value related to the condition detected by condition detection unit 12 into a condition score. This process is performed for each numerical value obtained for each condition.

[0042] Note that step S02 (detecting the state) and step S03 (calculating the state score) may be performed in parallel. For example, after detecting the state of one video data, the state may be converted into a state score (S03), while detecting the state of other video data (S02) in parallel.

[0043] Next, health state evaluation device 10 executes step S04. In step S04, region-specific score calculation unit 14 calculates region-specific scores by combining and aggregating the condition scores calculated by condition score calculation unit 13. This results in region-specific scores D indicating the health state of each region. Note that at this stage, a condition score for all of the multiple types of target regions (the entire stomatognathic system in the above embodiment) may also be calculated.

[0044] Finally, health state evaluation device 10 executes step S05. In step S05, result output unit 15 outputs the body part score D calculated by body part score calculation unit 14. This allows the operator of health state evaluation device 10, subject X, and the like to confirm the results.

[0045] [Health Status Assessment Program] 7, health state evaluation program P1 is composed of a main module m10 that controls the overall processing related to score calculation in health state evaluation device 10, a moving image data acquisition module m11, a condition detection module m12, a condition score calculation module m13, a body part score calculation module m14, and a result output module m15. The modules m11 to m15 realize the functions of moving image data acquisition unit 11, condition detection unit 12, condition score calculation unit 13, body part score calculation unit 14, and result output unit 15.

[0046] The health state evaluation program P1 may be transmitted via a transmission medium such as a communication line, or may be stored in a recording medium M1 as shown in FIG.

[0047] [Effect] The above-described health state evaluation device 10 calculates one or more condition scores indicating the state of each movement from each of a plurality of video data capturing different movements, and calculates a body part score related to the health state of the target body part based on these condition scores. In this way, health state evaluation device 10 calculates body part scores indicating the health state of each body part from a plurality of video data capturing different movements, allowing for a more multifaceted evaluation of the health state of the target body part compared to when focusing on a specific movement of that body part.

[0048] Conventionally, a method for evaluating health status has been to evaluate whether a specific movement is performed. It has also been considered to perform the evaluation based on video data of the movement. However, it may be difficult to accurately grasp the health status of a target part of subject X simply by performing a specific movement. In contrast, the health status evaluation device 10 calculates status scores from movement data relating to multiple movements and combines these to calculate a body part score, thereby enabling a more accurate evaluation of the status of the target part.

[0049] The condition score calculation unit 13 of the health condition evaluation device 10 may calculate multiple types of condition scores from each of the multiple video data. Furthermore, the body part score calculation unit 14 may calculate the body part score based on the multiple types of condition scores obtained from each of the multiple video data. With this configuration, multiple condition scores can be obtained from video data capturing a single movement, so that a single movement can be evaluated using more condition scores. Therefore, the health condition of the target body part can be evaluated more accurately.

[0050] Furthermore, as described in the above embodiment, the video data may be data capturing images of movements related to multiple target parts. Furthermore, the part-specific score calculation unit 14 may calculate the part-specific score for each target part based on a portion of the condition scores related to that target part among the condition scores. With the above configuration, part-specific scores can be calculated for multiple target parts of the subject. Furthermore, since these target parts are related to the same movements and are therefore closely related to each other, it is possible to obtain a more bird's-eye view of the condition around the multiple target parts of the subject, and also to perform a more detailed evaluation by taking into account differences in the part-specific scores between the target parts.

[0051] The body part score calculation unit 14 may calculate an overall score from the body part scores for multiple target body parts. With this configuration, it is possible to obtain information that provides a more bird's-eye view of the health condition of the body parts that include multiple target body parts of the subject, and to grasp the health condition trend that is not limited to a specific body part.

[0052] Furthermore, like the data capturing the pronunciation movement in the above embodiment, the video data may include video data capturing the vocalization movement. In this case, the condition score calculation unit 13 may calculate a first condition score (in the above embodiment, the number of pronunciations, clarity of pronunciation, etc.) obtained from the audio information included in the video data, and a second condition score (in the above embodiment, jaw movement, etc.) obtained from the image information. With this configuration, two condition scores can be obtained from the video data using audio information and image information, and more detailed information about the video data based on the vocalization movement can be obtained. Note that, as described in the above embodiment, a configuration may be adopted in which three or more condition scores are obtained. Furthermore, it is not necessary for all of the multiple video data to include audio data. If at least one video data includes audio data, the condition score is calculated based on information other than image analysis, and the site-specific scores are calculated based on this. This allows for more detailed evaluation of the target site, as described above.

[0053] Although the above embodiment describes a case where health status is evaluated assuming the stomatognathic system, the health status evaluation device 10 using video data can be applied to areas other than the stomatognathic system. For example, body tissues related to vocalization, similar to the stomatognathic system, can be cited as examples of areas related to vocalization. For example, the cricothyroid muscle controls the vocal cords, so a status score can be calculated based on the quality and pitch of the vocalized voice. Furthermore, the diaphragm controls breathing, which occurs simultaneously with vocalization, so a status score can be calculated based on the number of vocalizations and the rise and fall of the area around the diaphragm and shoulders. Furthermore, because abdominal muscles and back muscles also contribute to vocalization, a status score can be calculated based on the clarity and pitch of pronunciation and the movement of the abdomen and back. When evaluating areas related to vocalization other than the stomatognathic system, site-specific scores can be calculated based on multiple video data, as with the above-described health status evaluation device 10. In this case, the imaging range of the video data is not limited to the area around the mouth, but can be, for example, the upper body. In this way, the imaging range can be appropriately changed depending on the target area.

[0054] [others] The block diagrams used to explain the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of hardware and / or software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are connected directly or indirectly (e.g., via wire, wirelessly, etc.) and these multiple devices. A functional block may be realized by combining software with the single device or multiple devices. Furthermore, the term "device" used in the present embodiments may be replaced with "circuit," "device," "unit," etc.

[0055] Functions include, but are not limited to, judgment, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, election, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocation, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0056] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0057] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0058] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0059] Each aspect / embodiment described in this disclosure may be used alone, in combination, or switched depending on the implementation. Furthermore, notification of predetermined information (e.g., notification that "X is true") is not limited to being done explicitly, but may be done implicitly (e.g., by not notifying the predetermined information).

[0060] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0061] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0062] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0063] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0064] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0065] The terms "connected," "coupled," or any variation thereof, refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access." As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using one or more wires, cables, and / or printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and optical (both visible and invisible) range, as some non-limiting and non-exhaustive examples.

[0066] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0067] When used in this disclosure, the terms "include," "including," and variations thereof are intended to be inclusive, similar to the term "comprising." Furthermore, when used in this disclosure, the term "or" is not intended to be an exclusive or.

[0068] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0069] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different."

[0070] [Note] A health status evaluation device according to one embodiment includes a video data acquisition unit that acquires multiple video data images of different movements related to a target body part of a subject whose health status is to be evaluated, a status score calculation unit that calculates one or more status scores indicating the status of the movements from each of the multiple video data images, and a body part score calculation unit that calculates body part scores related to the health status of the target body part based on the status scores.

[0071] According to the above-described health condition evaluation device, one or more condition scores indicating the state of the movement are calculated from each of a plurality of video data capturing different movements, and a body part score relating to the health condition of the target body part is calculated based on these condition scores. In this way, body part scores indicating the health condition of each body part are calculated from a plurality of video data capturing different movements, so the health condition of the target body part can be evaluated from more multiple perspectives than when focusing on a specific movement of the body part.

[0072] The condition score calculation unit may calculate multiple types of condition scores from each of the multiple video data, and the body part score calculation unit may calculate the body part score based on the multiple types of condition scores obtained from each of the multiple video data.

[0073] With the above configuration, multiple condition scores can be obtained from video data capturing a single movement, allowing for evaluation using multiple condition scores for a single movement, thereby enabling a more accurate evaluation of the health condition of the target area.

[0074] The video data may be data capturing images of movements related to multiple target parts, and the part-specific score calculation unit may calculate the part-specific score for each target part based on a portion of the condition scores related to the target part.

[0075] The above configuration allows for calculation of site scores for multiple target sites of a subject. Furthermore, since these target sites are related to the same movement and therefore have a strong correlation with each other, it is possible to grasp the condition of the area around the multiple target sites of the subject from a more bird's-eye view, and also to perform a more detailed evaluation by taking into account the differences in site scores between target sites, etc.

[0076] The site-specific score calculation unit may be configured to calculate an overall score from the site-specific scores for the plurality of target sites.

[0077] With the above configuration, it is possible to obtain information that provides a more bird's-eye view of the health condition of the subject's body parts that include multiple target parts, and to grasp trends in the health condition that are not limited to specific parts.

[0078] The video data may include video data capturing vocalization actions, and the condition score calculation unit may calculate a first condition score obtained from audio information included in the video data and a second condition score obtained from image information.

[0079] With the above configuration, two state scores can be obtained from the video data using the audio information and the image information, and more detailed information about the video data based on vocalization actions can be obtained. [Explanation of symbols]

[0080] 1...health condition evaluation system, 10...health condition evaluation device, 11...video data acquisition unit, 12...condition detection unit, 13...condition score calculation unit, 14...body part score calculation unit, 15...result output unit, 16...related information storage unit.

Claims

1. a video data acquisition unit that acquires a plurality of video data capturing different movements of a target body part of a subject whose health condition is to be evaluated; a state detection unit that detects a state of the subject as a detection target state using the video data; a condition score calculation unit that calculates a first condition score and a second condition score based on the detection target condition; a site score calculation unit that calculates a site score related to the health state of the target site based on the first state score and the second state score; and the moving image data includes moving image data and audio data relating to vocalization movements of parts related to vocalization; The state detection unit analyzes the audio data and detects, corresponding to one movement, the sound emitted, the number of times the sound is pronounced, and the clarity of the pronunciation as the state to be detected, and performs image analysis of the video data and detects jaw movement as the state to be detected, The health condition evaluation device, wherein the condition score calculation unit calculates the first condition score from the sound produced, the number of times it is produced, and the clarity of the pronunciation, and calculates the second condition score from the jaw movement.

2. The video data is data obtained by capturing images of movements of a plurality of target parts, The health state evaluation device according to claim 1 , wherein the body part score calculation unit calculates the body part score for each of the target body parts based on a condition score associated with the target body part.

3. The health state evaluation device according to claim 2 , wherein the site score calculation unit calculates an overall score from the site scores related to the plurality of target sites.

4. The state detection unit performs image analysis on the video data, detects facial expression movements as the detection target state, the condition score calculation unit calculates a third condition score from an amount of exercise for the facial expression and a duration for which the facial expression is maintained; The site-specific score calculation unit further calculates the site-specific score using the third condition score. The health condition evaluation device according to any one of claims 1 to 3.

5. The state detection unit performs image analysis on the video data, detects tongue movement as the detection target state, the condition score calculation unit calculates a fourth condition score from the amount of tongue movement, the time the tongue is held out in the specified direction, and the degree of opening of the mouth when stationary; The site-specific score calculation unit further calculates the site-specific score using the fourth condition score. The health condition evaluation device according to any one of claims 1 to 3.

Images