Patent Application
20250152087
The present invention relates to an evaluation method, an evaluation apparatus, and a program.
Conventionally, methods for identifying the state of a blood vessel are known. For example, methods such as OCTA (Optical Coherence Tomography Angiography), a blood flowmeter, Photoacoustic Imaging, and FMD (Flow Mediated Dilatation) are known.
Conventionally, however, there has been no method for obtaining information on the state of blood vessels deep in the face in a non-invasive manner.
Accordingly, it is an object of an embodiment of the present invention to easily identify the state of blood vessels deep in the face.
An evaluation method according to an embodiment of the present invention includes acquiring information relating to an evaluation target person, the information including an actual age of the evaluation target person and an answer to a questionnaire about skin of a face of the evaluation target person; and predicting a state of a blood vessel in a deep part of the face of the evaluation target person from the information relating to the evaluation target person.
According to an embodiment of the present invention, the state of blood vessels deep in the face can be easily identified.
Hereinafter, an embodiment of the present invention will be described by referring to the drawings.
In the present specification, a “blood vessel in the deep part of the face” is an artery in the face (specifically, the buccal artery).
An evaluation apparatus 10 evaluates the state of blood vessels deep in the face of an evaluation target person 30. More specifically, the evaluation apparatus 10 predicts the state of blood vessels deep in the face of the evaluation target person 30 from information relating to the evaluation target person 30 (for example, “actual age and facial skin questionnaire answers” or “facial skin measurement value”). The evaluation apparatus 10 includes one or more computers. In a later stage, the evaluation apparatus 10 will be described in detail by referring to
A skin measuring apparatus 20 measures the skin of the face of the evaluation target person 30. For example, the measurement value of the skin of the face is the amount of sagging around the eyes.
The acquiring unit 101 acquires information relating to the evaluation target person 30.
Information relating to the evaluation target person 30 will now be described. Hereinafter, two examples of information relating to the evaluation target person 30 will be described.
For example, the information relating to the evaluation target person 30 includes the actual age of the evaluation target person 30 and the response to the facial skin questionnaire of the evaluation target person 30. For example, the questionnaire is a questionnaire about sagging around the eyes.
For example, the questionnaire includes at least one of the following questions:
For example, information relating to the evaluation target person 30 includes a measurement value of the facial skin. For example, the measurement value of the skin of the face is a measurement value of sagging around the eyes. Specifically, the measurement value of the skin of the face is the amount of sagging around the eyes.
The “amount of sagging around the eyes” is the volume (cc) of a portion (around the eyes) that is more depressed when the evaluation target person 30 is in the vertical position than when the evaluation target person is in the horizontal position. “Around the eyes” refers to a region of the face defined by the upper limit being the lower eyelid and the lower limit being the cheekbone, sandwiched laterally between the nose and sideburns or ears, and one of the two regions exist on each of the sides of the nose. The “horizontal position” refers to a state in which the midline of the face is stationary at a right angle to the direction of gravity. The “vertical position” refers to a state in which the midline of the face is stationary and parallel to the direction of gravity.
The blood vessel state predicting unit 102 predicts a state of blood vessels deep in the face of the evaluation target person 30 from information relating to the evaluation target person 30 acquired by the acquiring unit 101. Specifically, the blood vessel state predicting unit 102 predicts a state of blood vessels deep in the face of the evaluation target person 30 by referring to a predetermined correspondence relationship between “information relating to the evaluation target person 30” and “a state of blood vessels deep in the face” (described later in detail).
For example, the state of the blood vessel in the deep part of the face is the state of the blood vessel calculated from the blood flow velocity in the blood vessel. For example, the state of the blood vessel in the deep part of the face is the state of the blood vessel calculated from the blood flow rate and the radius of the blood vessel.
The skin state predicting unit 103 predicts a measurement value (for example, the amount of sagging around the eyes) of the skin of the face of the evaluation target person 30 from the state of the blood vessel in the deep part of the face of the evaluation target person 30 predicted by the blood vessel state predicting unit 102. Specifically, the skin state predicting unit 103 predicts a measurement value (for example, the amount of sagging around the eyes) of the skin of the face of the evaluation target person 30 by referring to a predetermined correspondence relationship between the “state of the blood vessel in the deep part of the face” and “facial skin measurement value (for example, the amount of sagging around the eyes)”.
The presentation unit 104 presents beauty information corresponding to the state of the blood vessel in the deep part of the face of the evaluation target person 30. Specifically, the presentation unit 104 extracts and presents beauty information corresponding to the state of the blood vessel in the deep part of the face of the evaluation target person 30 by referring to a predetermined correspondence relationship between the “state of the blood vessel in the deep part of the face” and “beauty information suitable for the state of the blood vessel”. The presentation unit 104 may present beauty information corresponding to the measurement value (for example, the amount of sagging around the eyes) of the skin of the face predicted by the skin state predicting unit 103.
Here, beauty information will be described. The beauty information is information relating to products and services related to beauty (for example, product name, service name, price, etc.). For example, the beauty information includes information relating to cosmetics for skin care and makeup, information relating to foods and drinks such as supplements, information relating to cosmetic equipment, information relating to beauty gear, information relating to esthetics, and a beauty method to be performed by the evaluation target person 30.
Two examples of evaluation processing will be described below.
In step 101 (S101), the acquiring unit 101 acquires information relating to the evaluation target person 30 including the actual age of the evaluation target person 30 and the answer to the questionnaire on the facial skin of the evaluation target person 30.
In step 102 (S102), the blood vessel state predicting unit 102 predicts the blood vessel state deep in the face of the evaluation target person 30 from the information relating to the evaluation target person 30 acquired in S101.
In step 103 (S103), the skin state predicting unit 103 predicts a measurement value (for example, the amount of sagging around the eyes) of the facial skin of the evaluation target person 30 from the blood vessel state deep in the face of the evaluation target person 30 predicted in S102.
In step 104 (S104), the presentation unit 104 presents beauty information corresponding to the blood vessel state deep in the face of the evaluation target person 30 predicted in S102. The presentation unit 104 may present beauty information corresponding to the measurement value (for example, the amount of sagging around the eyes) of the facial skin predicted in S103.
In step 201 (S201), the acquiring unit 101 acquires information relating to the evaluation target person 30 including a measurement value (for example, the amount of sagging around the eyes) of the skin of the face of the evaluation target person 30.
In step 202 (S202), the blood vessel state predicting unit 102 predicts the state of blood vessels deep in the face of the evaluation target person 30 from the information relating to the evaluation target person acquired in S201.
In step 203 (S203), the presentation unit 104 presents beauty information according to the state of blood vessels deep in the face of the evaluation target person 30 predicted in S202.
Here, the state of blood vessels (e.g., arteries in the face) in the deep part of the face will be described.
In the present invention, the intensity of MRI (Magnetic Resonance Imaging) is used as an index (health of blood vessels) for quantifying the state of blood vessels in the deep part of the face. Specifically, in all images acquired by MRA-PC (Magnetic Resonance Angiography-Phase Contrast) from a subject, the maximum intensity of brightness is calculated within a range of 10P (pixels)×10P (pixels) of the position of blood vessels, and the average value of all maximum intensities is defined as the intensity of blood vessel brightness in the deep part of the face. The measurement parameter is set so that the intensity of blood vessel brightness in the deep part of the face is proportional to the blood flow velocity, and the concept of quantifying the state of blood vessels in the deep part of the face will be described in detail below.
The following formula is derived from fluid dynamics.
It is known that the radius of a blood vessel (e.g., arteries in the face) in the deep part of the face decreases with aging. From the above formula (1), the blood flow velocity is inversely proportional to the square of the radius of a blood vessel. That is, if the intensity of a blood vessel brightness is used as an index for quantifying the state of a blood vessel in the deep part of the face, the health of a blood vessel can be quantified with high sensitivity. For example, if the blood flow velocity is fast, which can be said to be an unhealthy blood vessel, the blood vessel becomes bright, and if the blood flow velocity is slow, which can be said to be a healthy blood vessel, the blood vessel becomes dark. From these facts, it can be seen that the brighter blood vessel (that is, the square of the radius of the blood vessel is small) is the less healthy blood vessel, and the darker blood vessel (that is, the square of the radius of the blood vessel is greater) is the healthier blood vessel.
The correspondence relationship between “information relating to the evaluation target person 30” and “state of blood vessels in the deep part of the face” will now be described. Descriptions will be made for a case where “information relating to the evaluation target person 30” includes “actual age and facial skin questionnaire answers” and a case where “information relating to the evaluation target person 30” includes “a measurement value of the skin of the face”.
A case where information relating to the evaluation target person 30 includes “actual age and facial skin questionnaire answers” will be described.
When the following questionnaire was implemented for the subjects (46 persons), the answers indicated in
· Feeling [1] or not feeling [0] “dullness”.
“No” in
Thus, it was found that “actual age and facial skin questionnaire answers” and “the state of blood vessels in the deep part of the face” are correlated. Therefore, the blood vessel state predicting unit 102 can predict, as the state of blood vessels in the deep part of the face (health of blood vessels), a value obtained by weighting the answers (that is, 1 or 0) of each question of the questionnaire by the respective coefficients illustrated in
A case will be described in which the information relating to the evaluation target person 30 includes “facial skin measurement value (for example, the amount of sagging around the eyes)”.
Thus, it was found that the “facial skin measurement value (for example, the amount of sagging around the eyes)” and the “state of blood vessels deep in the face” are more correlated than the actual age and the “state of blood vessels deep in the face”. Therefore, the blood vessel state predicting unit 102 can predict the state of blood vessels deep in the face more accurately than using the actual age by using the measurement value (for example, the amount of sagging around the eyes) of the skin of the face.
The skin state predicting unit 103 can predict the measurement value (for example, the amount of sagging around the eyes) of the skin of the face of the evaluation target person 30 from the state of blood vessels deep in the face of the evaluation target person predicted by the blood vessel state predicting unit 102 by using the correlation between the “facial skin measurement value (for example, the amount of sagging around the eyes)” and the “state of blood vessels deep in the face”.
According to the present invention, the state of blood vessels deep in the face can be easily identified. For example, the state of blood vessels deep in the face can be identified simply by acquiring the actual age of the evaluation target person and the answer to the questionnaire on the face skin of the evaluation target person. Moreover, for example, the state of blood vessels deep in the face can be identified more accurately than using the actual age simply by acquiring the measurement value of the face skin of the evaluation target person.
Thus, according to the present invention, the state of blood vessels deep in the face that affect the skin can be identified. The conventional method (specifically, a technique based on the structure of blood vessels) can only identify the capillaries affected by the skin, however, according to the method of the present invention, the blood vessels deep in the face that affect the skin can be identified.
The CPU 1 is an arithmetic device that executes various programs installed in the auxiliary storage device 4.
The ROM 2 is a nonvolatile memory. The ROM 2 functions as a main storage device that stores various programs and data necessary for the CPU 1 to execute various programs installed in the auxiliary storage device 4. More specifically, the ROM 2 functions as a main storage device that stores boot programs such as BIOS (Basic Input/Output System) and EFI (Extensible Firmware Interface).
The RAM 3 is a volatile memory such as DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory). The RAM 3 functions as a main storage device that provides a work area to be expanded when various programs installed in the auxiliary storage device 4 are executed by CPU 1.
The auxiliary storage device 4 is an auxiliary storage device that stores various programs and information used when various programs are executed.
The display device 5 is a display device that displays the internal state and the like of the evaluation apparatus 10.
The operation device 6 is an input device that the manager of the evaluation apparatus 10 inputs various instructions to the evaluation apparatus 10.
The I/F device 7 is a communication device for connecting to a network and communicating with other devices.
The drive device 8 is a device for setting a storage medium 9. The storage medium 9 herein includes a medium for recording information optically, electrically, or magnetically, such as a CD-ROM, a flexible disk, a magneto-optical disk, and the like. The storage medium 9 may also include a semiconductor memory for electrically recording information, such as an EPROM (Erasable Programmable Read Only Memory), a flash memory, and the like.
The various programs installed in the auxiliary storage device 4 are installed, for example, when the distributed storage medium 9 is set in the drive device 8 and the various programs recorded in the storage medium 9 are read out by the drive device 8. Alternatively, the various programs installed in the auxiliary storage device 4 may be installed by downloading them from the network via the I/F device 7.
Although the embodiments of the present invention have been described above in detail, the present invention is not limited to the specific embodiments described above, and various modifications and changes are possible within the scope of the gist of the invention described in the claims.
This international application claims priority from Japanese Patent Application No. 2022-030316 filed on Feb. 28, 2022, and the entire contents of Japanese Patent Application No. 2022-030316 are hereby incorporated herein by reference.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022-030316 | Feb 2022 | JP | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2023/004952 | 2/14/2023 | WO |
