JP2018183509A - Body condition analysis apparatus and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a body condition analysis apparatus and a body condition analysis method capable of more appropriately analyzing body condition.SOLUTION: A body condition analysis apparatus D according to the present invention includes a mirror 1, generates an analysis object image by capturing an image of the front of the mirror 1 by an imaging unit 3, determines whether or not the user is a user identified by user identification information stored in an identification information storage 61, when it is determined as a result of the determination that the user is a user identified by the user identification information stored in the identification information storage 61, analyzes the body condition based on a determination reference feature amount in the determined user and on an analyzed-time feature amount obtained based on the analysis object image, and outputs the analysis result from a display unit 4, or from a communication IF unit 7 if necessary, to the outside.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a body state analysis device and a body state analysis method for analyzing a body state.

  People want to be healthy every day, but for physical condition management, they often need to be measured by a dedicated measuring device, such as a sphygmomanometer that measures blood pressure as one index. For this reason, a person dislikes a trouble and does not measure or forgets. Therefore, Patent Document 1 proposes a health management system.

  The health management system disclosed in Patent Document 1 includes a mirror unit provided in a dressing table or a washstand, a face image information acquisition unit that acquires face image information of a user who uses the mirror unit, and an acquired face An analysis unit that analyzes the skin condition of the user's face from the image information, and an analysis result notification unit that notifies the analysis result by the analysis unit. According to this, the mirror provided on the dressing table or the washstand that is looked into when preparing for going out in the morning, etc., is used as a mirror part for acquiring the face image information by the face image information acquisition means. In particular, regular health checks can be conducted to improve health (for example, paragraph [0005]). The health management system disclosed in Patent Document 1 includes an acquisition information storage unit that stores face image information acquired by the face image information acquisition unit, and a face image that displays face image information stored in the acquisition information storage unit. A display unit, and a control unit that displays the face image information stored in the acquired information storage unit when the determination result is high when the determination result by the determination unit is low, on the face image display unit Prepare. According to this, when the judgment result notifying by the judgment unit is notified to the user by the judgment result notifying means and the user is depressed, the control unit obtains information when the judgment result is high evaluation. By displaying the face image information stored in the storage unit on the face image display means, the user can be encouraged and health can be promoted (for example, paragraph [0008]).

JP 2009-153609 A

  By the way, since the user who looks into a mirror part is not necessarily one person if there is a living person, for example, in the health management system indicated by the above-mentioned patent documents 1, there is a possibility that data of a plurality of persons may be mixed. . If the data of multiple people are mixed, the physical condition of each person cannot be analyzed properly.

  The present invention has been made in view of the above-described circumstances, and an object thereof is to provide a body state analysis apparatus and a body state analysis method that can analyze a body state more appropriately.

  As a result of various studies, the present inventor has found that the above object is achieved by the present invention described below. That is, the body condition analysis apparatus according to one aspect of the present invention includes a mirror, an imaging unit that images the front of the mirror and generates an image as an analysis target image, and a user identification for identifying and identifying a user An identification information storage unit that stores information; a user determination unit that determines whether or not the user identification information stored in the identification information storage unit is a user based on an analysis target image captured by the imaging unit; A reference feature quantity storage unit that stores the feature quantity that is a predetermined feature quantity used for pathological diagnosis in the user and that serves as a judgment reference when analyzing a physical state, and an image that is captured by the imaging unit A feature amount processing unit that obtains the feature amount from the analysis target image as an analysis feature amount, and the user determination unit that is determined to be a user of the user identification information stored in the identification information storage unit And said Based on the determination reference feature amount stored in the reference feature amount storage unit and the analysis feature amount obtained by the feature amount processing unit for the user of the user identification information determined by the user determination unit. And an analysis unit for analyzing the physical condition and an output unit for outputting the analysis result of the physical condition analyzed by the analysis unit to the outside. Preferably, in the above-described body condition analysis apparatus, the reference feature amount storage unit stores one or more determination criterion feature amounts in association with one or more user identification information. Preferably, in the above-described body condition analysis device, the identification information storage unit stores one or more user identification information in association with one or more users, and the reference feature quantity storage unit is 1 Alternatively, a plurality of determination criterion feature quantities are stored in association with one or more users. Preferably, in the above-described body condition analysis apparatus, a plurality of feature amounts are obtained from a plurality of analysis target images captured by the imaging unit, and an average value of the obtained plurality of feature amounts is obtained as the determination reference feature amount. The determination reference feature quantity generation unit for storing the obtained determination reference feature quantity in the reference feature quantity storage unit. Preferably, in the above-described body condition analysis apparatus, the feature amount includes a first feature amount and a second feature amount that is a component of the first feature amount. Preferably, in the above-described body condition analysis apparatus, the first feature amount is a color of a white eye part (a white part or a conjunctival part in an eyeball). Preferably, since the possibility of jaundice can be analyzed suitably, in the above-described body condition analysis device, the second feature amount is a blue component (blue component of hue) in the color of the white eye portion. Preferably, since the possibility of conjunctivitis can be analyzed favorably, in the above-described body condition analyzer, the second feature amount is a red component (red component of hue) in the color of the white eye portion. Preferably, the possibility of at least one of cataract and pterygium and at least one of the possibility of retinal hemorrhage, retinitis pigmentosa, retinal choroidal atrophy, retinal choroiditis, optic atrophy and optic neuritis Since the analysis can be suitably performed, in the above-described body state analysis device, the second feature amount is lightness in the color of the black eye part (the iris and pupil part in the eyeball). Preferably, in the above-described body condition analysis apparatus, the second feature amount is a color of the cheek portion. Preferably, since the possibility of jaundice can be analyzed suitably, in the above-described body condition analysis apparatus, the second feature amount is a blue component (blue component of hue) in the color of the cheek portion. Preferably, since the possibility of kidney disease can be analyzed suitably, in the above-described body condition analysis apparatus, the second feature amount is lightness in the color of the cheek portion. Preferably, since the possibility of osteoporosis can be suitably analyzed, in the above-described body condition analysis apparatus, the feature amount is the eye height position. Preferably, in the above-described body condition analysis device, the apparatus further includes a reference color storage unit that stores a reference color serving as a reference, and the feature amount processing unit obtains the feature amount from the analysis target image captured by the imaging unit, A corrected feature value obtained by correcting the obtained feature value based on the reference color stored in the reference color storage unit is obtained as the analysis feature value.

  Such a body condition analysis apparatus includes a mirror, generates an analysis target image by imaging the front of the mirror, and uses the user identification information stored in the identification information storage unit based on the analysis target image. If it is determined that the user is a user of the user identification information stored in the identification information storage unit as a result of this determination, in the user of the determined user identification information, Based on the determination reference feature amount and the analysis feature amount obtained based on the analysis target image, the body state is analyzed, and the analysis result is output to the outside. Therefore, the body condition analysis apparatus includes a mirror and generates an analysis target image by imaging the front of the mirror. For example, face washing, tooth brushing, makeup, hair set, contact lens attachment, removal thereof, etc. You can analyze the physical state without being conscious of the natural movement when you look at the mirror in the behavior in daily life, and by referring to the output of the analysis result, you can see the daily physical condition in the natural movement Can be checked. The physical condition analyzer determines whether or not the user identification information stored in the identification information storage unit is a user when analyzing the physical condition, and uses the determined user identification information. The physical condition is analyzed on the basis of the determination criterion feature quantity and the analysis feature quantity in the user, so even if the physical condition analyzer is used by a plurality of users, the determination criterion feature quantity of the user is used. Since the physical condition is analyzed, the physical condition can be analyzed more appropriately.

  In another aspect, in the above-described body condition analysis apparatus, the user identification information is a face image in which the user's face is captured, and the user determination unit is configured to capture the image by the face authentication technique. It is determined whether or not the user is the user of the user identification information stored in the identification information storage unit based on the analysis target image captured in step, and the user identification stored in the identification information storage unit by the user determination unit When it is determined that the user is a user of information, the user identification information stored in the identification information storage unit of the user of the user identification information determined by the user determination unit is captured. And an identification information updating unit that updates based on the analysis target image captured by the unit and stores it in the identification information storage unit.

  Such a physical condition analyzer updates the user identification information stored in the identification information storage unit based on the analysis target image captured by the imaging unit and stores the updated information in the identification information storage unit. Even if the appearance changes, the user can be determined more appropriately. Therefore, since the physical condition is analyzed based on the determination criterion feature quantity of the user, the physical condition analysis apparatus can analyze the physical condition more appropriately.

  In another aspect, the above-described physical condition analysis apparatus further includes a threshold storage unit that stores a determination threshold used by the user for analyzing the physical condition, and the analysis unit is included in the reference feature amount storage unit. The difference between the stored determination criterion feature quantity and the analysis-time feature quantity obtained by the feature quantity processing unit is obtained, and the obtained difference and the user of the user identification information judged by the user judgment unit are obtained. The physical condition is analyzed by comparing the determination threshold value stored in the threshold value storage unit.

  Such a physical condition analyzer stores a determination threshold value used for analyzing the physical condition of the user, and analyzes the physical condition using the determination threshold value of the user. Therefore, the body condition analyzer can customize the determination threshold according to each individual user, and can analyze the body condition more appropriately.

  In another aspect, in the above-described body condition analysis devices, the analysis unit determines whether or not the analysis-time feature amount obtained by the feature amount processing unit is within a predetermined normal range. It is determined whether or not the physical condition is normal, and at least one of electronic medical chart information representing the contents of a medical chart in the user and health check result information representing a result of a health check in the user Past physical state information stored in the past physical state information storage unit in the past physical state information storage unit and the user identification information determined by the user determination unit in the past physical state information storage unit And a normal range adjusting unit for adjusting the normal range.

  Such a physical condition analyzer adjusts the normal range based on past physical condition information on the user of the user identification information determined by the user determination unit. Therefore, the body condition analyzer can determine whether or not the user is within the normal range more appropriately by considering the past body condition information of the individual user.

  In another aspect, in the above-described body condition analysis apparatus, the feature amount includes a first feature amount and a second feature amount that is a component of the first feature amount, and the feature amount processing unit includes the feature amount processing unit. First and second feature values are obtained as first and second analysis feature values, respectively, and the analysis unit has the first analysis feature value obtained by the feature processing unit within a predetermined normal range. It is determined whether or not the physical condition is normal by determining whether or not the analysis unit is stored in the reference feature amount storage unit when it is determined that it is not within the normal range The difference between the determination reference feature value and the second analysis feature value obtained by the feature value processing unit is obtained, and the obtained difference and the user identification information determined by the user determination unit are determined by the user. And comparing the determination threshold value stored in the threshold value storage unit. , To analyze the physical condition.

  Such a physical condition analyzer analyzes whether or not the user is within the normal range, and then analyzes the physical condition when the user is not within the normal range. Therefore, when the body condition analyzing apparatus is within the normal range, the process of analyzing the body condition can be skipped. On the other hand, since the analysis is performed in two stages, the body condition can be analyzed more appropriately.

  According to another aspect of the present invention, there is provided a body condition analysis method in which an imaging unit provided in a mirror captures an image of the front of the mirror and generates an image as an analysis target image. A user determination step for determining whether the user is the user of the user identification information stored in the identification information storage unit that stores the user identification information for identifying and identifying the user based on the analysis target image; , A feature amount processing step for obtaining a predetermined feature amount used for pathological diagnosis as an analysis feature amount from the analysis target image captured in the imaging step, and a user stored in the identification information storage unit in the user determination step When it is determined that the user is the user of the identification information, the feature amount serving as a determination criterion when analyzing the body condition in the user of the user identification information determined in the user determination step is determined as a determination criterion feature. An analysis step for analyzing a physical state based on the determination reference feature amount stored in the reference feature amount storage unit and the feature amount at the time of analysis obtained in the feature amount processing step; and And an output step of outputting the analysis result of the analyzed physical condition to the outside.

  In such a body condition analysis method, an image to be analyzed is generated by imaging the front of the mirror with an imaging unit provided in the mirror, and stored in the identification information storage unit based on the image to be analyzed It is determined whether or not the user is the user of the user identification information. As a result of the determination, when it is determined that the user is the user of the user identification information stored in the identification information storage unit, the determined user identification Based on the determination criterion feature amount and the analysis time feature amount obtained based on the analysis target image in the information user, the body state is analyzed, and the analysis result is output to the outside. Therefore, the body condition analysis method generates an analysis target image by imaging the front of the mirror with an imaging unit provided on the mirror, so that the natural action of looking at the mirror in the behavior in daily life The body condition can be analyzed without being conscious of the situation, and the daily body condition can be checked during the natural movement by referring to the output of the analysis result. The physical condition analysis method determines whether or not the user identification information stored in the identification information storage unit is a user when analyzing the physical condition, and uses the determined user identification information. Therefore, even when the mirror is used by a plurality of users, the physical condition is determined by the user's determination reference feature amount. Because it analyzes, it can analyze the physical condition more appropriately.

  The body state analysis device and the body state analysis method according to the present invention can analyze the body state more appropriately.

It is a block diagram which shows the structure of the body condition analyzer in embodiment. It is a figure which shows the external appearance structure of the said physical condition analyzer. It is a figure which shows the structure of the base information table memorize | stored in the said physical condition analyzer. It is a figure which shows the structure of the physical condition analysis system provided with the said physical condition analyzer. It is a flowchart which shows operation | movement of the said physical condition analyzer. It is a flowchart which shows each process in the identification process of the user in the flowchart shown in FIG. It is a flowchart which shows each process in the various processes of the user's past physical condition information in the flowchart shown in FIG. It is a flowchart which shows each process in the extraction process of the feature-value in the flowchart shown in FIG. FIG. 6 is a flowchart showing each process of an analysis process based on a black eye part in the analysis process of the flowchart shown in FIG. 5. FIG. 6 is a flowchart showing each process of an analysis process based on a white-eye portion in the analysis process of the flowchart shown in FIG. 5. FIG. 6 is a flowchart showing each process of the analysis process based on the cheek portion in the analysis process of the flowchart shown in FIG. 5. It is a flowchart which shows each process in the process of the analysis result in the flowchart shown in FIG.

  Hereinafter, an embodiment according to the present invention will be described with reference to the drawings. In addition, the structure which attached | subjected the same code | symbol in each figure shows that it is the same structure, The description is abbreviate | omitted suitably. In this specification, when referring generically, it shows with the reference symbol which abbreviate | omitted the suffix, and when referring to an individual structure, it shows with the reference symbol which attached the suffix.

  FIG. 1 is a block diagram illustrating a configuration of a body condition analysis apparatus according to an embodiment. FIG. 2 is a diagram showing an external configuration of the body condition analyzer. FIG. 3 is a diagram showing a configuration of a base information table stored in the physical condition analyzer. FIG. 4 is a diagram illustrating a configuration of a body condition analysis system including the body condition analysis apparatus.

  The body state analysis device in the embodiment is a device that analyzes a user's body state. For example, as illustrated in FIGS. 1 and 2, a mirror 1 and illumination units 2 (2-1, 2-2) The imaging unit 3, the display unit 4, the control processing unit 5, the storage unit 6, the communication interface unit (communication IF unit) 7, and the housing FR are provided.

  The casing FR is a member that houses the mirror 1, the imaging unit 3, the display unit 4, the control processing unit 5, the storage unit 6, and the communication IF unit 7 so that the mirror 1 faces the outside. It is a box. The illumination part 2 is arrange | positioned on the outer surface of the housing | casing FR so that it may mention later. The casing FR may be a single unit that constitutes a hand mirror, a viewing mirror, or the like, or may be a part of a dressing table or a washstand, for example.

  The mirror (mirror) 1 is a member that captures the appearance of an object. In the present embodiment, in order for the imaging unit 3 to image the front of the mirror 1 via the mirror 1 and to allow the display content displayed on the display unit 4 via the mirror 1 to be referred to from the outside, the mirror 1 is It is composed of a half mirror. The ratio between the transmittance and the reflectance of the mirror 1 may be 1: 1, but it is not necessarily 1: 1 and is arbitrary.

  The illumination unit 2 is a light source device that is connected to the control processing unit 5 and emits illumination light that illuminates the front of the mirror 1 according to the control of the control processing unit 5. Although the number of the illuminating units 2 may be one, in the present embodiment, a person who uses the mirror 1 (the body condition analyzing apparatus) on an image (analysis target image) generated by imaging the front of the mirror 1 with the imaging unit 3 In order to suppress the formation of shadows in the person's image when a user registered in D and an unregistered user are captured), there are at least two illumination units 2 The first and second illumination units 2-1 and 2-2 are configured so that the first and second illumination units 2-1 and 2-2 are spaced apart from each other by a predetermined distance. The mirror 1 is disposed on the housing surface at both upper ends. The first and second illumination units 2-1 and 2-2 are, for example, a light bulb, a fluorescent lamp, and a white LED (white light emitting diode).

  The imaging unit 3 is an apparatus that is connected to the control processing unit 5 and generates an image (image data) as an analysis target image (analysis target image data) by imaging the front of the mirror 1 according to the control of the control processing unit 5. . In the imaging unit 3, the image may be a still image or a moving image. For example, in this embodiment, the imaging unit 3 is an imaging optical system that forms an optical image on a predetermined imaging surface, and a light receiving surface that is aligned with the imaging surface. An area image sensor that converts the signal into a simple signal, and a digital camera that includes an image processing circuit that generates image data that represents data by performing image processing on the output of the area image sensor. In this embodiment, the imaging unit 3 is disposed on the back surface of the mirror 1 and images the front of the mirror 1 via the mirror 1. For example, the imaging unit 3 is disposed and fixed so that the objective side of the imaging optical system is in contact with the back surface of the mirror 1 in order to prevent intrusion of dust or the like.

  The display unit 4 is a device that is connected to the control processing unit 5 and displays predetermined information such as the analysis result of the body state analyzed by the body state analysis device D according to the control of the control processing unit 5. The display unit 4 is, for example, an LCD (Liquid Crystal Display) and an organic EL (ElectroLuminescence, OLED (Organic Light Emitting Diode)) display from the viewpoint that the physical condition analyzer D can be suitably thinned. In the present embodiment, the display unit 4 faces the display surface toward the mirror 1 and makes the display surface contact the back surface of the mirror 1 so that the display surface can be referred to from the outside via the mirror 1. It is arranged. The size of the display surface of the display unit 4 may be approximately the same as the size of the mirror 1 or may be smaller than the size of the mirror 1.

  The communication IF unit 7 is a communication circuit that is connected to the control processing unit 5 and performs communication with an external device under the control of the control processing unit 5. The communication IF unit 7 generates a communication signal containing data to be transferred input from the control processing unit 5 in accordance with a communication protocol used in the network NW described later shown in FIG. 4, and generates the generated communication signal in the network NW. To an external device (for example, a personal computer PC or a server device SV described later shown in FIG. 4). The communication IF unit 7 receives a communication signal from the external device via the network NW, extracts data from the received communication signal, and converts the extracted data into data that can be processed by the control processing unit 5 And output to the control processing unit 5. The communication IF unit 7 is, for example, a communication card that performs wired or wireless communication via a communication network such as a mobile communication network or a data communication network, and a communication interface circuit that complies with the IEEE 802 series standard. Note that the communication IF unit 7 further uses, for example, standards such as Bluetooth (registered trademark) standard, IrDA (Infrared Data Association) standard, USB (Universal Serial Bus) standard, etc. An interface circuit may be provided.

  The storage unit 6 is a circuit that is connected to the control processing unit 5 and stores various predetermined programs and various predetermined data under the control of the control processing unit 5. Examples of the various predetermined programs include control processing programs such as a control program, a user determination program, a feature amount processing program, an analysis program, an identification information update program, and a normal range adjustment program. The said control program is a program which controls each part 2-4, 6, 7 of the said physical condition analyzer D according to the function of the said each part. The user determination program is a program for determining whether or not the user is the user of the user identification information stored in the identification information storage unit 61 described later based on the analysis target image captured by the imaging unit 3. The feature amount processing program is a program for obtaining a predetermined feature amount used for pathological diagnosis from the analysis target image captured by the imaging unit 3 as an analysis feature amount. The analysis program determines the user identification information determined by the user determination program when the user determination program determines that the user is the user of the user identification information stored in the identification information storage unit 61. This is a program for analyzing a physical state based on a determination reference feature value stored in a reference feature value storage unit 62 (to be described later) and a feature value at the time of analysis obtained by the feature value processing program. The identification information update program is determined by the user determination program when the user determination program determines that the user is the user of the user identification information stored in the identification information storage unit 61. This is a program for updating the user identification information stored in the identification information storage unit 61 for the user of the identification information based on the analysis target image captured by the imaging unit 3 and storing it in the identification information storage unit 61. The normal range adjustment program is a program for adjusting a normal range described later. The various kinds of predetermined data include data necessary for analyzing the body condition, such as user identification information, determination reference feature quantity, past physical condition information, determination threshold value, and reference color. The storage unit 6 includes, for example, a ROM (Read Only Memory) that is a nonvolatile storage element, an EEPROM (Electrically Erasable Programmable Read Only Memory) that is a rewritable nonvolatile storage element, and the like. The storage unit 6 includes a RAM (Random Access Memory) that serves as a working memory of the control processing unit 5 that stores data generated during execution of the predetermined program. The storage unit 6 stores the identification information storage unit 61, the reference feature amount storage unit 62, the past body, in order to store the above-described user identification information, determination reference feature amount, past body state information, determination threshold value and reference color A status information storage unit 63, a threshold storage unit 64, a normal range storage unit 65, and a reference color storage unit 66 are functionally provided.

  The identification information storage unit 61 stores the user identification information. The user identification information is information (data) for identifying and identifying the user in order to authenticate the user of the physical condition analyzer D. The user identification information may be, for example, a user name (user name) or an identifier (ID) assigned to the user, but the user identification information is a user name, ID, or the like. In some cases, an input unit that accepts the input is required. From the viewpoint of making the input unit unnecessary, in the present embodiment, the user identification information specifies the user from the image captured by the imaging unit 3. It is an image (face image, face image data) that captures the user's face so that it can be identified.

  The reference feature amount storage unit 62 stores the determination reference feature amount (determination reference feature amount data) for the user of the user identification information stored in the identification information storage unit 61. The determination criterion feature amount is a predetermined feature amount used for pathological diagnosis, and is the feature amount serving as a determination criterion when analyzing a physical state. The predetermined feature amount is a color (hue, saturation, brightness), shape, contrast, or the like in an image area (user image area) in which a user is captured, which is obtained from an image captured by the imaging unit 3. More specifically, in the present embodiment, the feature amount includes a first feature amount and a second feature amount that is a component of the first feature amount. The first feature amount is, for example, the color of a white eye part (a white part in the eyeball, a conjunctival part). In the first feature amount, the second feature amount can be analyzed suitably for the possibility of jaundice, so it is a blue component (blue component of hue) in the color of the white eye portion, and the possibility of conjunctivitis can be analyzed suitably. Therefore, the red component (the red component of the hue) in the color of the white eye portion. Further, for example, the first feature amount is a color of a black eye portion (an iris and a pupil portion in an eyeball), and in the first feature amount, the second feature amount is at least one of a cataract and a pterygium. And the possibility of retinal hemorrhage, retinitis pigmentosa, retinal choroidal atrophy, retinal choroiditis, optic nerve atrophy and optic neuritis can be suitably analyzed. is there. In addition, for example, the first feature amount is a color of the cheek portion, and in the first feature amount, the second feature amount can appropriately analyze the possibility of kidney disease. is there.

  The past physical state information storage unit 63 stores the past physical state information for the user of the user identification information stored in the identification information storage unit 61. The past physical condition information is information (data) of at least one of electronic medical chart information representing the contents of a medical chart and health check result information representing a result of a health check for the user. More specifically, the past physical condition information includes, for example, vital measurement results, blood test results, hospital histories and past histories, chronic diseases, and the like. In the present embodiment, the past physical state information includes an analysis result analyzed by the analysis unit 54 as described later.

  The threshold storage unit 64 stores the determination threshold (determination threshold data) for the user of the user identification information stored in the identification information storage unit 61. The determination threshold value is a threshold value used for analysis of a physical condition. In the present embodiment, the first and second feature quantities, particularly the second feature quantity, may cause jaundice, conjunctivitis, cataract and / or pterygium, retinal hemorrhage, retinal pigment degeneration , Retinal choroid atrophy, retinal choroiditis, optic nerve atrophy and optic neuritis are analyzed, and the possibility of kidney disease is analyzed. Includes a threshold. The first determination threshold value is a threshold value used for determining whether or not there is a possibility of jaundice based on a blue component in the color of the white eye part. When the first subtraction result obtained by subtracting the determination reference feature value from the analysis feature value is a negative value that is equal to or greater than a predetermined first determination threshold value for the blue component in the white-eye color, it is determined that there is a possibility of jaundice. The The second determination threshold is a threshold used for determining whether or not there is a possibility of conjunctivitis based on the red component in the color of the white eye portion. In the red component in the white eye color, it is determined that there is a possibility of conjunctivitis when the second subtraction result obtained by subtracting the determination reference feature amount from the analysis feature amount is a positive value equal to or greater than a predetermined second determination threshold value. The The third determination threshold value is a threshold value used for determining whether or not there is a possibility of at least one of a cataract and a pterygium based on the lightness in the color of the black eye part. When the third subtraction result obtained by subtracting the determination reference feature amount from the analysis feature amount is a positive value equal to or greater than a predetermined third determination threshold value in lightness in the color of the black eye part, at least one of cataract and pterygium It is determined that there is a possibility. Whether the fourth determination threshold value may be at least one of retinal hemorrhage, retinitis pigmentosa, retinal choroiditis, retinal choroiditis, optic atrophy and optic neuritis based on the brightness of the color of the black eye part This is a threshold value used to determine whether or not. When the fourth subtraction result obtained by subtracting the determination reference feature amount from the analysis feature amount is a negative value that is equal to or greater than a predetermined fourth determination threshold value in lightness in the color of the black eye part, retinal bleeding, retinitis pigmentosa, retinal choroid It is determined that there is a possibility of at least one of atrophy, retinal choroiditis, optic atrophy and optic neuritis. The fifth determination threshold value is a threshold value used for determining whether or not there is a possibility of kidney disease based on the lightness in the color of the cheek portion. It is determined that there is a possibility of kidney disease when the fifth subtraction result obtained by subtracting the determination reference feature value from the analysis feature value is a negative value equal to or greater than a predetermined fifth determination threshold value in lightness in the cheek color. The The first to fourth determination threshold values include a plurality of setting values corresponding to differences in color tone of the eyeball color, such as when the eyeball color is relatively light, when the eyeball color is relatively dark, and when the eyeball color is different. Each of these samples is appropriately set. That is, for example, the first determination threshold is the 1a determination threshold when the eyeball color is relatively light, the 1b determination threshold when the eyeball color is relatively dark, and the 1c determination threshold when the eyeball color is brown , And a plurality of threshold values such as a 1d determination threshold value when the eyeball color is blue. In addition, as the fifth determination threshold, a plurality of setting values corresponding to differences in skin color (difference in race) or the like are appropriately set from a plurality of samples. That is, for example, the fifth determination threshold value includes a plurality of threshold values such as a 5a determination threshold value for white race, a 5b determination threshold value for yellow race, and a 5c determination threshold value for black race.

  Preferably, the identification information storage unit 61 stores one or a plurality of user identification information, and the reference feature amount storage unit 62 corresponds one or a plurality of determination reference feature amounts to the one or a plurality of user identification information. The past physical state information storage unit 63 stores one or more past physical state information in association with the one or more user identification information, and the threshold storage unit 64 stores one or more determinations. A threshold value (one or a plurality of first to fifth determination threshold values in the present embodiment) may be stored in association with the one or more user identification information. Preferably, the identification information storage unit 61 stores one or a plurality of user identification information in association with one or a plurality of users (for example, user names and IDs), and the reference feature quantity storage unit 62 One or more determination criterion feature quantities are stored in association with the one or more users, and the past physical state information storage unit 63 associates the one or more past physical state information with the one or more users. The threshold value storage unit 64 may store one or more determination threshold values (in this embodiment, one or more first to fifth determination threshold values) in association with the one or more users. .

  In the present embodiment, the user identification information, the determination reference feature amount, the past physical condition information, and the determination threshold value (one or a plurality of first to fifth determination threshold values in the present embodiment) are collectively stored in one table. The identification information storage unit 61, the reference feature amount storage unit 62, the past physical condition information storage unit 63, and the threshold value storage unit 64 are also used as one another. The base information table TB for registering the user identification information, the determination reference feature amount, the past physical condition information, and the determination threshold value (one or a plurality of first to fifth determination threshold values in this embodiment) is, for example, shown in FIG. As described above, a user identification information field 621 for registering user identification information, a criterion characteristic amount field 622 for registering a criterion characteristic amount for the user of the user identification information registered in the user identification information field 621, and The past physical state information field 623 for registering the past physical state information of the user of the user identification information registered in the user identification information field 621 and the use of the user identification information registered in the user identification information field 621 And a determination threshold field 624 for registering a determination threshold for the user, and a record for each user identification information.In this embodiment, as shown in FIG. 3, the base information table TB includes the user identification information registered in the user identification information field 621 in the user name (user name, ID) and basic attribute information. A user name field 611 and a basic attribute information field 612 for registering each are further provided.

  In the determination criterion feature value field 622, in the present embodiment, the first determination criterion feature value for jaundice, which is used when determining the possibility of jaundice based on the blue component in the color of the white eye portion, the color of the white eye portion. The second criterion feature value for conjunctivitis used when determining the possibility of conjunctivitis based on the red component in the eye, the possibility of at least one of cataract and pterygium based on the brightness in the color of the black eye part Retinal hemorrhage, retinitis pigmentosa, retinal choroiditis, retinal choroiditis, optic nerve atrophy, and optic nerve Based on the fourth criterion feature value for retinal hemorrhage and the like used in determining the possibility of at least one of the flames and the lightness in the color of the cheek portion Used in determining the likelihood of, the fifth criterion characteristic quantity for kidney disease is registered. In the determination threshold field 624, in the present embodiment, first to fifth determination thresholds are registered. In the basic attribute information field 612, the user's sex, date of birth (age), eye color tone, skin color, and the like are registered as the basic attribute information.

  These user name, basic attribute information, and past physical condition information are, for example, as shown in FIG. 4, a terminal device as a user interface (for example, a personal computer or a smart phone) connected to the physical condition analysis device D so as to be communicable. Etc.) A new record is generated from the PC at an appropriate timing such as when the user Ob starts using the physical condition analyzer D, and a user name field 611 in the newly generated record is generated. The basic attribute information field 612 and the past physical condition information field 623 are registered. At this timing, for example, the terminal device PC prompts the user Ob to be in front of the mirror 1, and the imaging unit 3 generates an image of the user Ob. A person area is extracted from the generated image of the user Ob by the background subtraction method. From this person region, for example, by circular or elliptical Hough transform, by pattern matching using a head model (template) prepared in advance, for example, by a neural network learned for head detection, etc. An image of the head region of Ob is extracted as a face image. This extracted face image is used as user identification information, and this user identification information (face image) is registered in the user identification information field 621 in the newly generated record. Then, first to fourth determination thresholds corresponding to the color tone of the eyeball color in the input and registered basic attribute information are registered in the newly generated determination threshold field 624, and the input and registered basic attribute information The fifth determination threshold value corresponding to the skin color is registered in the newly generated determination threshold value field 624. For example, as shown in FIG. 4, the past physical condition information is obtained from a server apparatus SV that manages an electronic medical record, for example, disposed in a hospital HS or the like, which is connected to the physical condition analysis apparatus D. The user name may be searched for using a search key, downloaded, and registered in the past physical condition information field 623. After each information is registered in this way, for example, when the user is in front of the mirror 1 during a predetermined preparation period such as one week, two weeks, or one month, the control processing unit 5 Thus, an image is generated by the imaging unit 3, the predetermined feature amount is obtained based on the generated image, and stored in the storage unit 6 in association with the user identification information or the user name. When obtaining the predetermined feature amount, the color misregistration is corrected in the same manner as the color misalignment correction performed when obtaining the analysis feature amount, which will be described later. When the predetermined preparation period elapses, an average value of the determined plurality of the predetermined feature amounts is obtained as a determination reference feature amount, and the record for registering the user identification information in the user identification information field 621, or The user name is registered in the determination criterion feature field 622 in the record in which the user name field 611 is registered. In one example, each piece of information (data) is registered in each field 611, 612, 621 to 624 of the base information table TB in this way.

  Returning to FIG. 1, the normal range storage unit 65 stores a normal range (normal range data). The normal range is used to determine whether or not the physical condition is normal, and is a range in which the physical condition is normal. In the present embodiment, the determination as to whether or not the physical condition is normal is performed based on the first feature amount of the analysis feature amount. For this reason, the normal range includes a first normal range representing a range in which the color of the white eye portion is normal, a second normal range representing a range in which the color of the black eye portion is normal, and a range in which the color of the cheek portion is normal. It consists of the 3rd normal range which represents. Each of the first to third normal ranges is appropriately set using a plurality of samples, and is stored as a default value in the normal range storage unit 65. As will be described later, each of the first to third normal ranges is adjusted based on the past physical condition information by the normal range adjustment unit 56 based on the default value.

  The reference color storage unit 66 stores the reference color (reference color data). The reference color is a color that serves as a reference when correcting the color misalignment that is performed when obtaining the analysis feature amount. For example, the reference value for red that corrects the red component, the green component The reference value for green to be corrected and the reference value for blue to correct the blue component are provided. For example, at the time of initial setting of the body condition analyzer D, the control processing unit 5 turns on the illumination unit 2 (2-1, 2-2) and performs color correction in the analysis target image obtained by the imaging unit 3. The color of the area is obtained as the reference color and stored in the reference color storage unit 66. The color correction region is a region of an image in which a background portion in which a person in the analysis target image is not reflected is captured, and is usually located at the upper right end in the analysis target image, which is considered not to include a person, for example. These are a predetermined small area, a predetermined small area located at the upper center of the predetermined small area, a predetermined small area located at the upper left end thereof, and the like.

  The control processing unit 5 is a circuit for controlling the units 2 to 4, 6, and 7 of the body condition analyzer D according to the function of each unit and analyzing the body state. The control processing unit 5 includes, for example, a CPU (Central Processing Unit) and its peripheral circuits. The control processing unit 5 functions as a control unit 51, a user determination unit 52, a feature amount processing unit 53, an analysis unit 54, an identification information update unit 55, and a normal range adjustment unit 56 by executing a control processing program. Configured.

  The control unit 51 controls each part 2 to 4, 6, and 7 of the body condition analyzer D according to the function of each part, and governs overall control of the body condition analyzer D.

  The user determination unit 52 determines whether or not the user is the user of the user identification information stored in the identification information storage unit 61 based on the analysis target image captured by the imaging unit 3. In the present embodiment, as described above, the user identification information is a face image (face image data), and the user determination unit 52 analyzes the image to be analyzed by the imaging unit 3 using a known face authentication technique. It is determined whether or not the user is the user of the user identification information stored in the identification information storage unit 61 based on the image. Face authentication technology is disclosed in, for example, Hitoshi Imaoka, et al., “Face Authentication Technology and its Applications”, NEC Technique, Vol 63 No. 3, 2010 (searched on March 29, 2017, Internet, <URL: http://jpn.nec.com/techrep/journal/g10/n03/pdf/100306.pdf>). The face authentication technique extracts a face area image (face image) from an image, detects face feature points such as eyes, nose, and mouth edge from the extracted face image to obtain a face feature point position. After generating a collation image by normalizing the position and size of the face image using the detection process and the feature point position of the face obtained in this detection process, the collation image and a registered image (this In the embodiment, it is provided with a collation process for obtaining and collating the degree of similarity with the user identification information.

  The feature amount processing unit 53 obtains the predetermined feature amount used for pathological diagnosis from the analysis target image captured by the image capturing unit 3 as an analysis feature amount. In this embodiment, when obtaining the analysis feature quantity, the feature quantity processing unit 53 obtains the feature quantity from the analysis target image imaged by the imaging unit 3, and uses the obtained feature quantity as a reference color storage unit. A corrected feature amount corrected based on the reference color stored in 66 is obtained as the analysis feature amount.

  The analysis unit 54 determines the user identification information determined by the user determination unit 52 when the user determination unit 52 determines that the user is the user of the user identification information stored in the identification information storage unit 61. Based on the determination criterion feature quantity stored in the reference feature quantity storage unit 62 and the analysis feature quantity obtained by the feature quantity processing unit 53 of the user, the body state is analyzed. More specifically, the analysis unit 54 obtains a difference between the determination reference feature quantity stored in the reference feature quantity storage unit 62 and the analysis feature quantity obtained by the feature quantity processing unit 53, and the obtained difference The body condition is analyzed by comparing the determination threshold value stored in the threshold value storage unit 64 for the user of the user identification information determined by the user determination unit 52. Further, the analysis unit 54 determines whether or not the physical condition is normal by determining whether or not the analysis-time feature value obtained by the feature value processing unit 53 is within a predetermined normal range. More specifically, in the present embodiment, the analysis unit 54 determines whether or not the first analysis feature amount (the first feature amount analysis feature amount) obtained by the feature amount processing unit 53 is within a predetermined normal range. By determining whether or not the physical condition is normal, and the analysis unit 54 determines that the physical condition is not within the normal range, the determination reference feature amount stored in the reference feature amount storage unit 62 And the second analysis feature amount obtained by the feature amount processing unit 53 (analysis feature amount of the second feature amount), and the obtained difference and the user determined by the user determination unit 52 The physical condition is analyzed by comparing the determination threshold stored in the threshold storage unit 64 with the user of the identification information.

  The identification information update unit 55 determines the user identification determined by the user determination unit 52 when the user determination unit 52 determines that the user is the user of the user identification information stored in the identification information storage unit 61. The user identification information stored in the identification information storage unit 61 for the information user is updated based on the analysis target image captured by the imaging unit 3 and stored in the identification information storage unit 61.

  The normal range adjustment unit 56 stores in the normal range storage unit based on the past physical state information stored in the past physical state information storage unit 63 for the user of the user identification information determined by the user determination unit 52. The normal range is adjusted.

  Next, the operation of this embodiment will be described. FIG. 5 is a flowchart showing the operation of the physical condition analyzer. FIG. 6 is a flowchart showing each process in the user identification process in the flowchart shown in FIG. FIG. 7 is a flowchart showing each process in the various processes of the user's past physical condition information in the flowchart shown in FIG. FIG. 8 is a flowchart showing each process in the feature amount extraction process in the flowchart shown in FIG. FIG. 9 is a flowchart showing each process of the analysis process based on the black eye part in the analysis process of the flowchart shown in FIG. FIG. 10 is a flowchart showing each process of the analysis process based on the white-eye portion in the analysis process of the flowchart shown in FIG. FIG. 11 is a flowchart showing each process of the analysis process based on the cheek portion in the analysis process of the flowchart shown in FIG. FIG. 12 is a flowchart showing each process in the analysis result process in the flowchart shown in FIG.

  In the body condition analysis apparatus D having the above-described configuration, when power is turned on by turning on a power switch (not shown), necessary parts are initialized and started to operate. By executing the control processing program, the control processing unit 5 is functionally configured with a control unit 51, a user determination unit 52, a feature amount processing unit 53, an analysis unit 54, and an identification information update unit 55. In the initial setting, the control processing unit 5 turns on the illumination unit 2 (2-1, 2-2), generates a background image by the imaging unit 3, and sets the color from the color correction area of the background image as a reference color. And the obtained reference color is stored in the reference color storage unit 66 of the storage unit 6.

  In one example, as described above, the user Ob connects the terminal device PC to the physical condition analyzer D so as to be communicable with the physical condition analyzer D. From the terminal device D, the user name and basic attribute information are connected. When the user is input in the past physical condition information and is prompted by a message displayed on the terminal device PC and stands in front of the mirror 1, an image of the user Ob is generated by the imaging unit 3, and the face of the user Ob is generated from the image of the user Ob. An image is extracted as user identification information. Then, first to fourth determination threshold values are set according to the color tone of the eyeball color in the input basic attribute information, and a fifth determination threshold value is set according to the skin color. These user identification information, past physical condition information, and determination threshold value are stored in the identification information storage unit 61, the past physical condition information storage unit 63, and the threshold storage unit 64 in the storage unit 6, respectively. In the present embodiment, the user name, basic attribute information, user identification information, past physical condition information, and determination threshold value are the fields 611, 612, 621, and 623 of the newly generated record in the base information table TB. , 624 and stored in the storage unit 6. If necessary, the past physical state information may be downloaded from the server device SV that manages the electronic medical record using the user name as a search key, downloaded, and stored in the storage unit 6. Then, a determination reference feature value is obtained from the plurality of predetermined feature values obtained during the preparation period, and the obtained determination reference feature value is stored in the reference feature value storage unit 62, in this embodiment, the base information table TB. Are registered in the determination criterion feature quantity field 622 and stored in the storage unit 6.

  When each piece of information customized for the user Ob is stored in the storage unit 6, an analysis of the physical state is started, and the physical state of the user Ob is changed to the natural state of the daily mirror 1 by the following operation. This is automatically done when using it. It is assumed that the body condition analysis device D can communicate with the above-described server device SV that manages the electronic medical record.

  When the user Ob goes in front of the mirror 1, for example, when the user Ob is detected by an unillustrated human sensor such as a pyroelectric type, the body state analyzer D in FIG. 51, the 1st and 2nd illumination parts 2-1 and 2-2 are lighted (S1).

  Next, the body condition analyzer D performs an analysis target image acquisition process by the control unit 51 of the control processing unit 5 (S3). More specifically, the control unit 51 captures an image with the imaging unit 3 and generates an image as an analysis target image. As a result, an analysis target image is acquired. Since the first and second illumination units 2-1 and 2-2 illuminate the user Ob from both upper ends of the mirror 1, the image of the user Ob reflected in the analysis target image captured by the imaging unit 3 The image to be analyzed can be generated in a stable shooting environment with the same lighting environment that is difficult to shadow. In the present embodiment, since the possibility of illness is determined (pathological diagnosis) based on the color change, such a stable imaging environment is preferable.

  Next, the body condition analysis apparatus D performs a user authentication process by the user determination unit 52 of the control processing unit 5.

  More specifically, in FIG. 6, the user determination unit 52 executes face authentication processing (S501) using a known face authentication technique based on the analysis target image captured and acquired by the imaging unit 3 in step S3. Then, it is determined whether or not the user Ob of the analysis target image is a user of the user identification information stored in the identification information storage unit 61 (S502). More specifically, the user determination unit 52 first extracts a face area image (face image) from the analysis target image captured and acquired by the imaging unit 3 in step S3. Next, the user determination unit 52 obtains the feature point positions of, for example, eyes, nose, and both mouth ends from the extracted face image. Next, the user determining unit 52 normalizes the position and size of the face image using the obtained feature point positions of the face, and generates a collation image. Then, the user determination unit 52 compares the collation image with the user identification information (registered image) registered in the user identification information field 621 in the base information table TB, and matches (matches) the collation image. It is determined whether or not user identification information (registered image) to be present exists. As a result of this determination, when there is no user identification information (registered image) that matches the matching image (No), the body condition analyzer D then performs a process S503 by the control processing unit 5. Execute. On the other hand, if there is user identification information (registered image) that matches the collation image as a result of the determination (Yes), the body condition analyzer D next performs the process S504 by the control processing unit 5. Run.

  In this process S503, the physical condition analyzer D reads out and acquires the first to fifth determination threshold values for general use from the storage unit 6 as values used by the analysis unit 54 in the later-described process S7 by the control processing unit 5. Then, step S6 is executed. The first to fifth determination threshold values for general use are appropriately set and prepared in advance based on a plurality of samples, and are stored in the storage unit 6 in advance as one of the various predetermined data.

  In the process S504, the physical condition analyzer D is registered in the user identification information field 621 of the base information table TB determined by the identification information update unit 55 of the control processing unit 5 to match the collation image in the process S502. The user identification information (registered image) that has been updated is updated based on the analysis target image captured and acquired by the imaging unit 3 in the process S3. Next, after the process S505 is performed, the process S6 is performed.

  In this process S505, the physical condition analyzer D performs various processes of the user's past physical condition information by the control processing unit 5, and then executes a process S6.

  More specifically, various processes shown in FIG. 7 are performed as various processes S505 of the user's past physical condition information in the present embodiment, for example.

  In FIG. 7, next, the physical condition analyzer D uses the user identification information (registered image) determined by the control processing unit 5 to match the collation image in step S502 as the user identification information in the base information table TB. Stores the user name, past physical condition information, and first to fifth determination threshold values registered in the user name field 611, the past physical condition information field 623, and the determination threshold value field 624, respectively, in the record registered in the field 621. The data is read from the unit 6 and acquired (S551).

  Next, the physical condition analysis device D searches the user name acquired in the process S551 from the server device SV that manages the electronic medical record using the search key by the control processing unit 5, and downloads the user's electronic medical record, Obtain (S552).

  Next, the body condition analyzer D determines whether or not the electronic medical record has been updated by the control processing unit 5 (S553). More specifically, the control processing unit 5 determines whether or not the electronic medical record has been updated by comparing the past physical condition information acquired in step S551 with the electronic medical record acquired in step S552. If the result of this determination is that there is no difference between them, the control processing unit 5 determines that the electronic medical record has not been updated (No), and then executes step S557. On the other hand, as a result of the determination, if there is a difference between the two, the control processing unit 5 determines that the electronic medical record has been updated (Yes), and the content of the electronic medical record acquired in the processing S552 is the processing S502. The past physical state information registered in the past physical state information field 623 in the record for registering the user identification information (registered image) determined to match the collation image in the user identification information field 621 of the base information table TB. Update and register, and then execute step S554.

  In this process S554, the body condition analyzer D determines what the disease under treatment is by the control processing unit 5. If there is no disease under treatment as a result of this determination (No), the control processing unit 5 next executes step S555. On the other hand, as a result of the determination, there is a disease under treatment (Yes). Then, the control processing unit 5 next executes a process S556.

  In this process S555, since there is no disease under treatment, the control processing unit 5 reads the normal range stored in the normal range storage unit 65 of the storage unit 6, sets the normal range with this default value, and then Then, process S6 is executed.

  In this process S556, the control processing unit 5 reads the normal range stored in the normal range storage unit 65 of the storage unit 6 by the normal range adjustment unit 56, and adjusts this default value according to the disease being treated. Then, a new normal range is set with the adjusted value, and then step S6 is executed. More specifically, the normal range adjustment unit 565 merges the disease under treatment with the disease that is the subject of analysis in the later-described processing S7 or the disease that is the subject of analysis in the later-described processing S7. If the disease develops, the normal range of the disease is narrowed by a predetermined ratio, and the narrowed range is set as a new normal range. For example, when the disease under treatment is jaundice, in the present embodiment, the possibility of jaundice is analyzed by the color of the white eye portion, so the first normal range of the default value is a predetermined ratio (for example, 5% or 10%). %) And the narrowly adjusted range is set as a new first normal range. Also, for example, when the disease being treated is hypertension, the third normal range of kidney disease that may develop as a complication of this disease is narrowed by a predetermined percentage and set to a new third normal range. The

  On the other hand, in process S557, the body condition analyzer D determines whether or not the treatment has been completed by the control processing unit 5. For example, in the case where the electronic medical record includes a treatment completion flag indicating the presence or absence of treatment completion, the treatment completion flag of the electronic medical record acquired in step S552 is referred to, and the treatment completion flag is present (or treatment completion flag). Is “1” indicating the completion of treatment), it is determined that the treatment is complete, and when there is no treatment completion flag (or when the treatment completion flag is “0” indicating that the treatment is not complete). Determine that treatment is not complete. Also, for example, this determination refers to the prescription issuance status. If issuance of prescriptions that have been issued regularly has been stopped, it is determined that treatment has been completed, and prescription issuance continues. It is determined that the treatment is not completed. As a result of this determination, if the treatment is complete (Yes), the control processing unit 5 next executes the process S6. On the other hand, if the determination is that the treatment is complete (No) Next, the control processing unit 5 executes a process S558.

  In this process S558, the physical condition analyzer D determines whether or not a regular checkup is possible by the control processing unit 5. More specifically, for example, the control processing unit 5 obtains the average visit interval days from the treatment date (the medical record description date, the visit date) in the electronic medical record acquired in the process S552, and determines the predetermined average visit interval days. Is multiplied by a constant (for example, 1.3 or 1.5), and this multiplication result is added to the final treatment date, and it is determined whether or not today's date exceeds the date of the addition result. As a result of this determination, if today's date exceeds the date of the addition result, the control processing unit 5 determines that regular checkup has not been made (No), and then executes step S559. On the other hand, as a result of the determination, if today's date does not exceed the date of the addition result, the control processing unit 5 determines that a regular checkup has been made (Yes), and then executes step S6.

  In this process S559, the physical condition analyzer D displays a notification of a recommended regular check-up such as “please go to the hospital” on the display unit 4 for a predetermined time by the control processing unit 5, and performs the process S6. Run.

  Returning to FIG. 5, in this process S <b> 6, the body condition analysis apparatus D obtains a feature value at the time of analysis by the feature value processing unit 53 of the control processing unit 5. More specifically, the feature amount processing unit 53 obtains the predetermined feature amount as the analysis feature amount from the analysis target image captured by the imaging unit 3 in the process S2. More specifically, the feature amount processing unit 53 obtains the predetermined feature amount from the analysis target image captured by the imaging unit 3 in step S3, and the obtained feature amount is a reference stored in the reference color storage unit 66. A corrected feature amount corrected based on the color is obtained as the analysis feature amount.

  In this embodiment, since the possibility of a predetermined disease is analyzed based on the color of the white eye part, the color of the black eye part, or the color of the cheek part, in one example, in FIG. In S3, a person region is extracted from the analysis target image captured by the imaging unit 3 by the background subtraction method (S601). Next, the feature amount processing unit 53 extracts a face region from the extracted person region by, for example, elliptical Hough transform or pattern matching using a head model (template) (S602). Next, in order to extract the eye area and the cheek area, the feature amount processing unit 53 extracts an edge from the extracted face area image by an edge filter to generate an edge image, and the generated edge image is Divided into four parts vertically and horizontally, or a pair of left and right ellipses that are horizontally long and located slightly above the center position, for example, by the Hough transform of the ellipse, or the eye model ( A pair of left and right eye regions are extracted by pattern matching using a template, and a lower fixed region is extracted as a cheek region with respect to the extracted eye regions (S603). The extracted cheek region image is the cheek portion in the analysis target image. Next, the feature amount processing unit 53 separates at least one of the extracted left and right pair of eye regions into a white eye region and a black eye region based on the pixel value, and the white eye region image (white eye image, white eye region) in the analysis target image. Part) and the image of the black eye region (black eye image, black eye part) in the analysis target image are extracted (S604). Next, the feature amount processing unit 53 obtains each analysis feature amount from the white eye portion, the black eye portion, and the cheek portion (S605). More specifically, the feature amount processing unit 53 obtains the red component in the extracted white eye portion by, for example, averaging each red component of each pixel in the white eye portion, and determines the blue component in the extracted white eye portion as, for example, the white eye The blue component of each pixel in the portion is obtained by averaging, and the green component in the extracted white-eye portion is obtained by, for example, averaging each green component of each pixel in the white-eye portion. As a result, the color of the white eye portion (red component, blue component, green component) is obtained as the first feature amount relating to the white eye portion, and the red component and the blue component of the white eye portion are obtained as the second feature amount relating to the white eye portion. Similarly, the feature amount processing unit 53 obtains the red component in the extracted black eye portion by, for example, averaging each red component of each pixel in the black eye portion, and calculates the blue component in the extracted black eye portion, for example, the black eye portion. The green component in the extracted black eye part is obtained by averaging the green component of each pixel in the black eye part, for example, and the lightness in the black eye part is calculated based on these. Ask. As a result, the color of the black eye part (red component, blue component, green component) is obtained as the first feature quantity relating to the black eye part, and the brightness of the black eye part is obtained as the second feature quantity relating to the black eye part. Similarly, the feature amount processing unit 53 obtains the red component in the extracted cheek portion by, for example, averaging each red component of each pixel in the cheek portion, and calculates the blue component in the extracted cheek portion, for example, the cheek portion. The green component in the extracted cheek part is obtained by averaging the green component of each pixel in the cheek part, for example, and the lightness in the cheek part is calculated based on these. Ask. Accordingly, the color of the cheek portion (red component, blue component, green component) is obtained as the first feature amount relating to the cheek portion, and the brightness of the cheek portion is obtained as the second feature amount relating to the cheek portion. If both the left and right eye regions are used, the red component, the blue component, the green component, and the lightness are obtained for each of the left and right eye regions. The average is calculated | required by each of a component and lightness, and each average value should just be made into each value of final red component, blue component, green component, and lightness. Next, in order to correct the color misregistration in the red component, blue component, green component, and brightness, the feature amount processing unit 53 changes the color of the color correction region of the analysis target image captured by the imaging unit 3 in step S3. The correction value of each component is obtained based on the obtained color of the color correction area and the reference color stored in the reference color storage unit 66. Then, the feature amount processing unit 53 determines the red component, the blue component, and the green component in the obtained white eye portion, the red component, the blue component, the green component, and the brightness in the obtained black eye portion, and the obtained cheek eye portion. Red component, blue component, green component, and brightness are corrected with each correction value, and the corrected white-eye color, red component and green component, black-eye color and brightness, and cheek Find the color and brightness of the part. Thereby, for example, the color of the white eye part, the red component and the green component, the color and brightness of the black eye part, as the characteristic amount at the time of analysis, which corrects the color shift caused by the change of the illumination light in the illumination unit 2 due to deterioration over time, In addition, the color and brightness of the cheek portion are required. In the above description, the brightness itself is corrected. However, the brightness after the color shift correction may be obtained by using the red component, the blue component, and the green component after the color shift correction.

  Returning to FIG. 5, after such processing S <b> 6 is performed, the body condition analyzer D uses the user identification information determined by the user determination unit 52 in the processing S <b> 5 by the analysis unit 54 of the control processing unit 5. Based on the determination criterion feature quantity stored in the reference feature quantity storage unit 62 and the analysis-time feature quantity obtained by the feature quantity processing unit 53 in step S6, an analysis process for analyzing the physical state is executed (step S6). S7).

  In this embodiment, since the possibility of a predetermined disease is analyzed based on the color of the white eye part, the color of the black eye part, and the color of the cheek part, in one example, the color of the black eye part is analyzed in FIG. First, the color (red component, blue component, green component) of the black eye as the first analysis feature amount (first feature analysis feature amount) obtained in step S605 is within the second normal range. It is determined whether or not there is (S710). As a result of this determination, when the color of the black eye portion is within the second normal range (Yes), the analysis unit 54 determines that there is no abnormality (S713), and the body condition analyzer D is controlled by the control processing unit 5. Next, the process S8 is executed. On the other hand, if the result of the determination is that the color of the black eye portion is not within the second normal range (No), the analysis unit 54 next executes step S711.

  In this process S711, the analysis unit 54 determines whether or not the lightness of the color in the black eye portion is high as the second analysis feature quantity (the second feature quantity analysis feature quantity) obtained in the process S605. . More specifically, the determination criterion feature field in the record for registering the user identification information (registered image) determined to match the collation image in the processing S502 in the user identification information field 621 of the base information table TB. Based on the lightness in the color of the black eye portion as the second analysis time feature amount obtained by reading out and obtaining from the storage unit 6 the determination reference feature amount for cataract and pterygium registered in 622. Then, it is determined whether or not the acquired third subtraction result obtained by subtracting the acquired determination reference feature amount for cataract and pterygium is a positive value that is equal to or greater than the third determination threshold acquired in step S505. As a result of this determination, when the brightness is not high, that is, when the third subtraction result is not a positive value equal to or greater than the third determination threshold value (No), the analysis unit 54 is at least one of cataract and pterygium. In view of this possibility, it is determined that there is no abnormality, and then processing S712 is executed. On the other hand, when the lightness is high as a result of the determination, that is, when the third subtraction result is a positive value equal to or higher than the third determination threshold (Yes), there is a possibility of at least one of cataract and pterygium. (S715), the body condition analyzer D next executes the process S8 by the control processing unit 5.

  In this process S712, the analysis unit 54 determines whether or not the lightness of the color in the black eye portion is low as the second analysis feature quantity (the second feature quantity analysis feature quantity) obtained in the process S605. . More specifically, the determination criterion feature field in the record for registering the user identification information (registered image) determined to match the collation image in the processing S502 in the user identification information field 621 of the base information table TB. From the lightness in the color of the black eye portion as the second analysis time feature amount obtained by reading out and obtaining the determination reference feature amount for retinal hemorrhage registered in 622 from the storage unit 6 and in the process S605, It is determined whether or not the fourth subtraction result obtained by subtracting the acquired determination criterion feature value for retinal hemorrhage is a negative value that is equal to or greater than the fourth determination threshold acquired in step S505. As a result of this determination, if the brightness is not low, that is, if the fourth subtraction result is not a negative value equal to or greater than the fourth determination threshold value (No), the analysis unit 54 performs retinal bleeding, retinitis pigmentosa, retina It is determined that there is no abnormality in at least one of the possibilities of choroidal atrophy, retinal choroiditis, optic atrophy and optic neuritis (S713), and the body condition analyzer D is then controlled by the control processing unit 5. Process S8 is executed. On the other hand, when the lightness is low as a result of the determination, that is, when the fourth subtraction result is a negative value that is equal to or greater than the fourth determination threshold (Yes), the analysis unit 54 performs retinal bleeding, retinitis pigmentosa, It is determined that there is a possibility of at least one of retinal choroidal atrophy, retinal choroiditis, optic nerve atrophy, and optic neuritis (S714), and the body condition analyzer D then performs process S8 by the control processing unit 5. Run.

  In one example, with respect to the color of the white eye portion, in FIG. 10, the analysis unit 54 firstly uses the white eye portion as the first analysis feature amount (the first feature amount analysis feature amount) obtained in step S605. It is determined whether the colors (red component, blue component, green component) are within the first normal range (S720). If the result of this determination is that the color of the white-eye portion is within the first normal range (Yes), the analysis unit 54 determines that there is no abnormality (S723), and the body condition analyzer D is controlled by the control processing unit 5. Next, the process S8 is executed. On the other hand, if the result of the determination is that the color of the white eye portion is not within the first normal range (No), the analysis unit 54 next executes step S721.

  In this process S721, the analysis unit 54 determines whether or not the blue component in the color of the white eye portion is low as the second analysis feature quantity (the second feature quantity analysis feature quantity) obtained in the process S605. The More specifically, the determination criterion feature field in the record for registering the user identification information (registered image) determined to match the collation image in the processing S502 in the user identification information field 621 of the base information table TB. The determination reference feature value for jaundice registered in 622 is read out from the storage unit 6 and obtained, and the obtained jaundice is obtained from the blue component in the color of the white eye portion as the second analysis time feature value obtained in the processing S605. It is determined whether or not the first subtraction result obtained by subtracting the determination criterion feature value for use is a negative value that is equal to or greater than the first determination threshold acquired in step S505 (S721). As a result of this determination, when the blue component is not low, that is, when the first subtraction result is not a negative value equal to or higher than the first determination threshold value (No), the analysis unit 54 has the possibility of jaundice, It is determined that there is no abnormality, and then processing S722 is executed. On the other hand, if the blue component is low as a result of the determination, that is, if the first subtraction result is a negative value equal to or greater than the first determination threshold (Yes), the analysis unit 54 may have jaundice. Then, the body condition analyzer D performs the process S8 by the control processing unit 5 (S725).

  In the process S722, the analysis unit 54 determines whether or not the red component in the color of the white eye portion is high as the second analysis time feature amount (the second feature amount analysis feature amount) obtained in the process S605. The More specifically, the determination criterion feature field in the record for registering the user identification information (registered image) determined to match the collation image in the processing S502 in the user identification information field 621 of the base information table TB. The determination criteria feature quantity for conjunctivitis registered in 622 is read out and acquired from the storage unit 6, and the acquired conjunctivitis is obtained from the red component in the white eye color as the second analysis feature quantity obtained in the processing S 605. It is determined whether or not the second subtraction result obtained by subtracting the determination criterion feature value for use is a positive value that is equal to or greater than the second determination threshold acquired in step S505. As a result of this determination, if the red component is not high, that is, if the second subtraction result is not a positive value equal to or greater than the second determination threshold (No), the analysis unit 54 is in terms of the possibility of conjunctivitis, It is determined that there is no abnormality (S723), and the body condition analyzer D next executes the process S8 by the control processing unit 5. On the other hand, as a result of the determination, when the red component is high, that is, when the second subtraction result is a positive value equal to or greater than the second determination threshold (Yes), the analysis unit 54 has the possibility of conjunctivitis. Then, the physical condition analyzer D executes the process S8 by the control processing unit 5 (S724).

  Furthermore, in one example, with respect to the color of the cheek portion, in FIG. 11, the analysis unit 54 firstly uses the cheek portion as the first analysis feature quantity (first feature quantity analysis feature quantity) obtained in step S605. It is determined whether the colors (red component, blue component, green component) are within the third normal range (S730). As a result of this determination, when the color of the cheek portion is within the third normal range (Yes), the analysis unit 54 determines that there is no abnormality (S732), and the body condition analyzer D is controlled by the control processing unit 5. Next, step S8 is executed. On the other hand, if the result of the determination is that the color of the cheek portion is not within the third normal range (No), the analysis unit 54 next executes step S731.

  In this process S731, the analysis unit 54 determines whether or not the lightness in the color of the cheek portion as the second analysis feature quantity (the second feature quantity analysis feature quantity) obtained in the process S605 is low. . More specifically, the determination criterion feature field in the record for registering the user identification information (registered image) determined to match the collation image in the processing S502 in the user identification information field 621 of the base information table TB. The determination criterion feature value for kidney disease registered in 622 is read out and acquired from the storage unit 6, and this acquired jaundice is determined from the brightness in the color of the cheek portion as the second analysis time feature value obtained in the processing S 605. It is determined whether or not the fifth subtraction result obtained by subtracting the determination criterion feature value for use is a negative value that is equal to or greater than the fifth determination threshold value acquired in step S505. As a result of this determination, if the lightness is not low, that is, if the fifth subtraction result is not a negative value equal to or higher than the fifth determination threshold (No), the analysis unit 54 is in terms of the possibility of kidney disease, It is determined that there is no abnormality, and then step S732 is executed. On the other hand, if the brightness is low as a result of the determination, that is, if the fifth subtraction result is a negative value that is equal to or greater than the fifth determination threshold (Yes), the analysis unit 54 determines that there is a possibility of kidney disease. Then, the physical condition analyzer D performs the process S8 by the control processing unit 5 next.

  Returning to FIG. 5, in process S <b> 8, the body condition analyzer D determines whether or not the control processing unit 5 determines that there is a possibility of some disease in the process S <b> 7. In the present embodiment, the control processing unit 5 includes at least one of the possibility of cataract and pterygium, retinal hemorrhage, retinitis pigmentosa, retinal choroid atrophy, retinal choroiditis, optic atrophy and optic neuritis. It is determined whether at least one of any of the possibilities, the possibility of jaundice, the possibility of conjunctivitis, and the possibility of kidney disease has been determined to be possible. As a result of this determination, the possibility of at least one of cataract and pterygium, the possibility of at least one of retinal hemorrhage, retinitis pigmentosa, retinal choroid atrophy, retinal choroiditis, optic atrophy and optic neuritis, When it is determined that all of the possibility of jaundice, the possibility of conjunctivitis, and the possibility of kidney disease are determined (No), the body condition analyzer D ends the process, while the determination As a result, the possibility of at least one of cataract and pterygium, possibility of retinal hemorrhage, retinitis pigmentosa, retinal choroidal atrophy, retinal choroiditis, optic atrophy and optic neuritis, jaundice If at least one of the possibility, the possibility of conjunctivitis, and the possibility of kidney disease is determined to be possible (Yes), the body condition analyzer Is the control processing unit 5 executes the processing of the analysis result (S9), the process ends.

  In the analysis result processing S9, the body condition analyzer D stores the analysis result and the like by the control processing unit 5 and displays the analysis result as necessary. More specifically, in FIG. 12, the control processing unit 5 stores the analysis result and the like in the storage unit 6 (S901). More specifically, the control processing unit 5 records past user identification information (registered image) determined to match the collation image in the processing S502 in the user identification information field 621 of the base information table TB. An analysis result is added and registered in the physical condition information field 623. As a result, the current analysis result is stored (recorded) in the storage unit 6.

  Next, based on the determination result of the process S554, the control processing unit 5 determines whether or not all the disease names included in the analysis result in the process S7 are the names of the diseases being treated. If all the disease names are being treated as a result of this determination (Yes), the control processing unit 5 ends the process. On the other hand, when all the disease names are not being treated (No), the control processing unit 5 displays the analysis result on the display unit 4 and ends the processing. Here, the display unit 4 may preferably display the remaining analysis result excluding the name of the disease being treated from the analysis result, but all the analysis result may be displayed on the display unit 4. As described above, the display unit 4 corresponds to an example of an output unit that outputs the analysis result of the physical state analyzed by the analysis unit to the outside. Note that the analysis result of the process S7 may be output from the communication IF unit 7 to an external device as necessary. In this case, the communication IF unit 7 corresponds to another example of an output unit that outputs the analysis result of the body state analyzed by the analysis unit to the outside.

  As described above, the body state analysis device D and the body state measurement method mounted thereon according to the present embodiment are analyzed images by imaging the front of the mirror 1 with the imaging unit 3 provided in the mirror 1. Based on the analysis target image, it is determined whether or not the user Ob of the user identification information stored in the identification information storage unit 61. As a result of this determination, the user identification information is stored in the identification information storage unit 61. When it is determined that the user is the user Ob of the user identification information, the analysis characteristic obtained from the determination reference feature amount and the analysis target image in the user Ob of the determined user identification information Based on the quantity, the body condition is analyzed and the analysis result is output to the outside. Therefore, in the body condition analysis apparatus D and the body condition analysis method, the image to be analyzed is generated by imaging the front of the mirror 1 with the imaging unit 3 provided in the mirror 1, and thus, for example, face washing, tooth brushing, makeup The body condition can be analyzed without being aware of the natural movement of looking at the mirror 1 during daily activities such as up, hair set, contact lens attachment, and removal, and refer to the output of the analysis result. Thus, the daily physical condition can be checked during the natural movement. Then, the body condition analysis apparatus D and the body condition analysis method determine whether or not the user is the user Ob of the user identification information stored in the identification information storage unit 61 when analyzing the body condition. Since the body state is analyzed based on the determination criterion feature amount and the analysis time feature amount in the user Ob of the user identification information that has been obtained, the body state analyzing apparatus D and the body state analyzing method are performed by a plurality of users. Even when it is used, the physical state is analyzed based on the determination criterion feature quantity of the user Ob, so that the physical state can be analyzed more appropriately.

  In the body condition analysis device D and the body condition analysis method, the user identification information stored in the identification information storage unit 61 is updated based on the analysis target image captured by the imaging unit 3 and stored in the identification information storage unit 61. Since it memorize | stores, even if the appearance of user Ob changes, user Ob can be determined more appropriately. Therefore, since the body state is analyzed based on the determination criterion feature amount of the user Ob, the body state analysis apparatus and the body state analysis method can analyze the body state more appropriately.

  The body condition analysis apparatus D and the body condition analysis method store a determination threshold value used for analyzing the body condition of the user, and analyze the body condition using the determination threshold value of the user. Therefore, the body condition analyzer D and the body condition analysis method can customize the determination threshold according to the individual user, and can analyze the body condition more appropriately.

  The body condition analyzer D and the body condition analysis method adjust the normal range based on the past body condition information of the user of the user identification information determined by the user determination unit 52. Therefore, the body condition analysis apparatus D and the body condition analysis method can determine whether or not the user is within the normal range more appropriately by considering the past body condition information of each user.

  The body state analysis device D and the body state analysis method analyze the body state when it is not within the normal range after determining whether or not the user is within the normal range. Therefore, the body state analysis apparatus and the body state analysis method can skip the process of analyzing the body state when it is within the normal range, and can analyze the body state more appropriately because the analysis is performed in two stages.

  In the above-described embodiment, the predetermined feature amount is the color of the white eye portion, the color of the black eye portion, or the color of the cheek portion, but is not limited to this, and is used for other pathological diagnosis. It may be various quantities. For example, instead of the above, or in addition to the above, in the case where the first feature amount is the color of the cheek portion, the second feature amount can suitably analyze the possibility of jaundice. Since it is a blue component (a blue component of hue) and the possibility of cirrhosis can be analyzed suitably, the lightness in the color of the cheek portion may be used. In the blue component in the cheek color, the sixth subtraction result obtained by subtracting the determination reference feature amount from the second analysis feature amount (analysis feature amount of the second feature amount) is a negative value greater than or equal to a predetermined sixth determination threshold value. In some cases, it is determined that there is a possibility of jaundice. It is determined that there is a possibility of cirrhosis when the seventh subtraction result obtained by subtracting the determination reference feature amount from the second analysis feature amount is a negative value that is equal to or greater than a predetermined seventh determination threshold value in lightness in the cheek color. Is done. As for the sixth and seventh determination thresholds, a plurality of setting values corresponding to the difference in skin color are appropriately set from a plurality of samples, similarly to the first to fifth determination thresholds described above. Even when analyzing the possibility of jaundice and the possibility of cirrhosis, a normal range (fourth normal range) similar to the first to third normal ranges may be provided. Further, the fourth normal range is not only based on the past physical condition information, but may be adjusted according to, for example, color black or white. Alternatively, in addition to or in addition to the above, since the possibility of osteoporosis can be analyzed appropriately, the feature amount may be the eye height position. It is determined that there is a possibility of osteoporosis when the eighth subtraction result obtained by subtracting the determination reference feature value from the analysis feature value at the eye height position is a negative value equal to or greater than a predetermined eighth determination threshold value. The setting value of the eighth determination threshold is appropriately set from a plurality of samples, and is set to several centimeters such as 1 cm, 2 cm, and 3 cm, for example.

  Moreover, in the above-mentioned embodiment, as shown with the broken line in FIG. 1, the body condition analyzer D calculates | requires several said feature-value from the some analysis object image imaged by the imaging part 3, and the said some obtained | required these some The control processing unit 5 is further functionally provided with a determination reference feature amount generation unit 57 that obtains an average value of feature amounts as the determination reference feature amount and stores the obtained determination reference feature amount in the reference feature amount storage unit 62. You may prepare. For example, the determination criterion feature value generation unit 57 obtains the feature value from the analysis target image captured by the imaging unit 3 in the process S3 before the process S505 described above or after the process S505 described above. Then, an average value of the obtained feature amount and the determination reference feature amount stored in the reference feature amount storage unit 62 in the user Ob of the user identification information determined by the user determination unit 52 is obtained. The determination reference feature quantity stored in the reference feature quantity storage unit 62 is updated and stored with the obtained average value. According to this, the criterion characteristic amount is finely adjusted according to the daily change of each individual user, and the physical state can be analyzed more appropriately. Further, the determination reference feature quantity generation unit 57 may generate the determination reference feature quantity during the preparation period.

  In the above-described embodiment, the terminal apparatus PC is communicably connected to the body condition analyzer D, and as a result of the determination in step S502, there is no user identification information (registered image) that matches the collation image. In the case (No), the body condition analyzer D may perform a process of newly registering a user before the execution of the process S503. In the process of newly registering a user, first, the body condition analysis apparatus D causes the control processing unit 5 to display a message as to whether or not to newly register on the terminal device PC, and waits for a reply. If the reply of the terminal device PC means that new registration is not performed, the control processing unit 5 next executes step S503. On the other hand, if the reply of the terminal device PC means that new registration is performed, control is performed. The processing unit 5 generates user identification information (collation image) based on the analysis target image captured and acquired by the imaging unit 3 in step S3, and inputs the user name, basic attribute information, and past physical condition information. A prompt message is displayed on the terminal device PC, and a reply is waited for. Upon receiving this reply, the control processing unit 5 generates a new record in the base information table TB, and a user name field 611, basic attribute information field 612, and user identification information field 621 in the newly generated record. The user name, basic attribute information, user identification information (collation image), and past physical condition information are registered in the past physical condition information field 623, respectively. The control processing unit 5 registers the fifth determination threshold corresponding to the basic attribute information in the newly generated determination threshold field 624. The past physical condition information may be retrieved from the server device SV that manages the electronic medical record using the user name as a search key, downloaded, and registered in the past physical condition information field 623, as described above. And the predetermined preparation period which produces | generates a determination reference | standard feature-value is started, and the control process part 5 performs process S503 next. Then, when the predetermined preparation period has elapsed, the control processing unit 5 obtains an average value of the plurality of predetermined feature amounts obtained during the preparation period as a determination reference feature amount, which is determined as the user identification. A record for registering information in the user identification information field 621 or a record for registering the user name in the user name field 611 is registered in the determination criterion feature field 622. In this way, a process for newly registering a user is executed.

  In order to express the present invention, the present invention has been properly and fully described through the embodiments with reference to the drawings. However, those skilled in the art can easily change and / or improve the above-described embodiments. It should be recognized that this is possible. Therefore, unless the modifications or improvements implemented by those skilled in the art are at a level that departs from the scope of the claims recited in the claims, the modifications or improvements are not covered by the claims. To be construed as inclusive.

D Body condition analyzer 1 Mirror 2 (2-1, 2-2) Illuminating unit 3 Imaging unit 4 Display unit 5 Control processing unit 6 Storage unit 7 Communication interface unit (communication IF unit)
51 Control Unit 52 User Determination Unit 53 Feature Amount Processing Unit 54 Analysis Unit 55 Identification Information Update Unit 56 Normal Range Adjustment Unit 57 Determination Criteria Feature Amount Generation Unit 61 Identification Information Storage Unit 62 Reference Feature Amount Storage Unit 63 Past Physical State Information Storage Unit 64 threshold storage unit 65 normal range storage unit 66 reference color storage unit

Claims (6)

Mirror,
An imaging unit that images the front of the mirror and generates an image as an analysis target image;
An identification information storage unit for storing user identification information for identifying and identifying a user;
A user determination unit that determines whether the user is the user of the user identification information stored in the identification information storage unit based on the analysis target image captured by the imaging unit;
A reference feature amount storage unit that stores the feature amount that is a predetermined feature amount used for pathological diagnosis in the user and that serves as a determination reference when analyzing a physical state, as a determination reference feature amount;
A feature amount processing unit for obtaining the feature amount as an analysis-time feature amount from an analysis target image captured by the imaging unit;
When it is determined that the user is a user of the user identification information stored in the identification information storage unit by the user determination unit, in the user of the user identification information determined by the user determination unit, An analysis unit that analyzes a physical state based on the determination criterion feature amount stored in the reference feature amount storage unit and the analysis-time feature amount obtained by the feature amount processing unit;
An output unit for outputting the analysis result of the physical state analyzed by the analysis unit to the outside,
Body condition analyzer. The user identification information is a face image in which the user's face is copied,
The user determination unit determines whether or not the user is a user of the user identification information stored in the identification information storage unit based on an analysis target image captured by the imaging unit by using a face authentication technique.
When it is determined that the user is a user of the user identification information stored in the identification information storage unit by the user determination unit, in the user of the user identification information determined by the user determination unit, An identification information updating unit that updates the user identification information stored in the identification information storage unit based on the analysis target image captured by the imaging unit and stores the updated information in the identification information storage unit;
The body condition analyzer according to claim 1. A threshold storage unit that stores a determination threshold used for analyzing the physical condition of the user is further provided,
The analysis unit obtains a difference between the determination reference feature amount stored in the reference feature amount storage unit and an analysis feature amount obtained by the feature amount processing unit, and the obtained difference and the user determination Analyzing the physical state by comparing the determination threshold stored in the threshold storage unit in the user of the user identification information determined by the unit;
The body condition analysis apparatus according to claim 1 or 2. The analysis unit determines whether the physical condition is normal by determining whether the analysis-time feature value obtained by the feature value processing unit is within a predetermined normal range,
A past physical condition information storage unit that stores at least one of electronic medical record information representing the contents of a medical chart in the user and health check result information representing a result of a health check in the user as past physical condition information When,
A normal range adjustment unit that adjusts the normal range based on past physical state information stored in the past physical state information storage unit for the user of the user identification information determined by the user determination unit; Prepare
The body condition analysis apparatus according to claim 1 or 2. The feature amount includes a first feature amount and a second feature amount that is a component of the first feature amount,
The feature amount processing unit obtains the first and second feature amounts as first and second analysis feature amounts, respectively.
The analysis unit determines whether or not the physical state is normal by determining whether or not the first analysis feature amount obtained by the feature amount processing unit is within a predetermined normal range. ,
When the analysis unit determines that it is not within the normal range, the determination reference feature amount stored in the reference feature amount storage unit and the second analysis feature amount obtained by the feature amount processing unit A physical condition is analyzed by determining a difference and comparing the determined difference with a determination threshold value stored in the threshold value storage unit in the user of the user identification information determined by the user determination unit. To
The body condition analysis apparatus according to claim 4, which refers to claim 3. An imaging step of imaging the front of the mirror and generating an image as an analysis target image by an imaging unit provided in the mirror;
Based on the analysis target image captured in the imaging step, it is determined whether or not the user is the user of the user identification information stored in the identification information storage unit that stores user identification information for identifying and identifying the user. A user determination process to perform,
A feature amount processing step for obtaining a predetermined feature amount used for pathological diagnosis as a feature amount during analysis from the analysis target image captured in the imaging step,
When it is determined that the user is the user of the user identification information stored in the identification information storage unit in the user determination step, the user's body of the user identification information determined in the user determination step The determination reference feature quantity stored in a reference feature quantity storage unit that stores the feature quantity as a determination reference feature quantity when analyzing the state, and the analysis feature quantity obtained in the feature quantity processing step Based on the analysis process of analyzing the physical state,
An output step of outputting the analysis result of the physical condition analyzed in the analysis step to the outside,
Body condition analysis method.