JP2004094337A - Human body model generation system for aging effect prediction - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a human body model generation system for aging effect prediction capable of evaluating change due to aging. <P>SOLUTION: This system for generating a human body model on which difference in the physical characteristics, motion capability, or sensing capability of a human body due to a change in ages is provided with a human body model generating part for generating a human body in a standard age based on applied information and an aging effect processing part for adding a change in the physical features, motion capability or sensing capability due to aging to the human body model in the standard age generated by the human model generating part. <P>COPYRIGHT: (C)2004,JPO

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an aging effect prediction human body model generation system that generates a human body model reflecting a difference in physical characteristics, motor ability, or perception ability of a human body due to a difference in age.
[0002]
[Prior art]
Conventionally, in Japanese Patent Application No. 2002-58706, a technology has been proposed in which a human body model is created on a computer based on the user's current body shape and physical strength, and the usability of the product is simulated on the computer using this human body model. ing.
[0003]
[Problems to be solved by the invention]
With conventional technology, it is possible to evaluate the usability of products based on the user's physical shape and physical strength at the present time, but in the future, the usability of the product will change when the user's physical shape changes or the ability to exercise or perceive declines. The change could not be predicted.
[0004]
The present invention has been made in view of these points, and evaluates changes due to aging by generating a human body model that reflects differences in physical characteristics, motor ability, or perception ability of the human body due to differences in age. It is an object of the present invention to provide an aging effect prediction human body model generation system that can be used.
[0005]
[Means for Solving the Problems]
The invention of claim 1 is a system for generating a human body model that reflects a difference in physical characteristics, motor ability or perception ability of a human body due to a difference in age, and is based on given information at a reference age Aging effect that adds changes in physical characteristics, motor ability, or perceptual ability due to aging to the human body model generation unit that generates the human body model and the human body model at the reference age generated by the human body model generation unit And a processing unit.
The invention according to claim 2 and claim 1, wherein the human body model generation unit generates a human body model at a reference age based on current information of a user of the product, and the aging effect processing unit uses the product It is characterized by adding at least a change related to the difference in the usability of the product due to aging among changes in physical characteristics, motor ability or perception ability due to aging of the person.
Invention of Claim 3 outputs the information which can be utilized when the prospective purchaser of a product selects one or more products from a plurality of products in Claim 1 or 2 It is characterized by.
The invention of claim 4 is characterized in that, in claim 3, the information used for selecting a product is information related to a force applied in a horizontal direction to the surface of the product.
According to a fifth aspect of the present invention, in the third or fourth aspect, the information used for selecting a product is information related to a force applied in a direction perpendicular to the surface of the product.
The invention of claim 6 is characterized in that, in claim 1, the aging effect processing unit outputs information that can be used when creating or changing a design.
[0006]
The invention of claim 7 is characterized in that, in claim 1, the aging effect processing unit outputs information that can be used when evaluating safety during evacuation.
The invention of claim 8 is the human body model generation unit according to claim 1, wherein the human body model generation unit generates a plurality of human body models based on different information, and the aging effect processing unit is a body by aging for each of the plurality of human body models. It is characterized by creating a crowd model by adding a change in the mental characteristics, motor ability or perceptual ability.
The invention of claim 9 is characterized in that, in any one of claims 1 to 8, the virtual reality generating device outputs a processing result by the aging effect processing unit.
A tenth aspect of the present invention is characterized in that, in the ninth aspect, the virtual reality generating device includes a dome-type display device that displays the human body model on a real scale.
The invention of claim 11 is characterized in that, in claim 1, the human body model generation unit and the aging effect processing unit are arranged on a server that can be used via the Internet.
According to a twelfth aspect of the present invention, in the first aspect, the aging effect processing unit varies the degree of change in physical characteristics, motor ability or perceptive ability due to aging according to the current lifestyle of the human body model. Features.
The invention of claim 13 is characterized in that, in claim 1, the human body model generation unit generates a human body model of a child generation based on information of generations before the parent.
[0007]
DETAILED DESCRIPTION OF THE INVENTION
(Embodiment 1)
FIG. 1 is a diagram showing an overall configuration of an aging effect prediction human body model generation system of the present invention. This system is a system for generating a human body model that reflects a difference in physical characteristics, motor ability or perception ability of a human body due to a difference in age. In the figure, reference numeral 1 denotes a human body model generation unit, which generates a human body model at a reference age based on given information. Reference numeral 2 denotes an aging effect processing unit, which performs a process of adding changes in physical characteristics, motor ability or perceptive ability due to aging to the human body model at the reference age generated by the human body model generation unit 1. . Reference numeral 3 denotes an age-specific database, which includes a physical feature database 31, an athletic ability database 32, and a perceptual ability database 33. A control unit 4 controls the operation of the entire system. Reference numeral 5 denotes a GUI (Graphical User Interface), which obtains information necessary for generating a human body model from a user using peripheral devices such as a computer screen and a mouse / keyboard.
[0008]
FIG. 2 shows a schematic configuration of the human body model generation unit 1. 11 is an input unit, 12 is a CG creation unit, 13 is a storage unit, and 14 is an output unit. The input unit 11 inputs information such as the user's height, weight, sex, and age as parameters of the human body model to be generated. The CG creation unit 12 creates a CG image of the human body model using CG (computer graphics) technology based on the input information. As the CG image, a plurality of images are created according to movements such as “walking” and “slide”. The storage unit 13 stores the created CG image. The output unit 14 reproduces the CG image stored in the storage unit 13 as a moving image. As a result, an arbitrary operation such as “walking” or “sitting” can be performed on the computer screen based on the human body model corresponding to the height, weight, sex, age, etc. of the user.
[0009]
Here, since the specific content of the CG creation unit 12 is a well-known technique, only the outline will be described. First, a skeleton model is created based on information related to the user's physique, and a surface model is added thereto. In addition, clothes and facial information are added. Default information is used for clothes and face, but it may be replaced with information obtained from the user using a digital camera or the like. With regard to operations such as “walking” and “slide”, the muscle strength and the operating range of the joint change with aging, so the movement registered in advance according to the age of the user is reproduced.
[0010]
An example of the simplest human body model is illustrated in FIG. In the figure, S1 is an upper arm segment, S2 is a lower arm segment, and J1 is an upper arm joint. Similarly, 18 segments and 16 joints are provided. The shape of each segment Si (i = 1,..., 18) is stored as numerical data such as length Li (mm) × width Wi (mm). Further, initial coordinates of each joint Jn (n = 1,..., 16) are stored as numerical data such as (Xn, Yn, Zn), and a plurality of segments are connected to a plurality of joints based on these numerical data. It is possible to convert the human body model combined in 3D into a 3D image. In the example illustrated in FIG. 3, each segment of the human body model is drawn in a rectangular shape to simplify the description, but it goes without saying that the segment may be round or thick.
[0011]
The shape data of the human body model is corrected based on physique information such as height and weight obtained from a user in the real world. For example, if the person is taller or heavier than the standard, the size of each segment is corrected to be larger than the standard size stored in advance. On the other hand, if the person is shorter than the standard person or light in weight, the size of each segment is corrected to be smaller than the standard size stored in advance. FIGS. 4A to 4C illustrate the shape data of the human body model before and after correction. FIG. 4A shows an example of a person with a small body shape, FIG. 5B shows an example of a person with a standard body shape, and FIG. 5C shows an example of a person with a large body shape.
[0012]
The behavior of the human body model at each age is registered in advance as a temporal change in the relative positional relationship of each segment, that is, as a temporal change in the rotation angle of the joints connecting the segments in the X-axis, Y-axis, and Z-axis directions. ing. As a specific means for registering the motion of the human body model, for example, a method called motion capture can be used. In this method, for example, a plurality of markers are attached to the human body, and the positions of the markers are detected from images taken from a plurality of directions, and the three-dimensional movement of the human body is converted into data. Basic operations such as “walking” and “sitting” of people of different ages are registered in advance.
[0013]
FIG. 5 shows a schematic configuration of the aging effect processing unit 2. 21 is an input unit, 22 is a DB search unit, 23 is a parameter correction unit, and 24 is an output unit. The input unit 21 receives the parameters of the current human body model and the age to be aged. For example, a case will be described in which information such as the user's height, weight, sex, and age is input as parameters of the current human body model, and “age 10 years” is input as the age to be aged. In the DB search unit 22, the age-specific database 3 is searched, and as shown in FIG. 6 (a), the position of the current value of the user in the same age / sex group is statistically determined. Investigate. Next, as shown in FIG. 6 (b), the age-specific database 3 is searched by adding the age to 10 years, and the person who is statistically in the same position in the group having the same age and sex after 10 years. Are read as predicted values after 10 years. The parameter correction unit 23 replaces the parameters of the current human body model with predicted values after 10 years. The output unit 24 outputs the corrected parameters as parameters of the human body model after 10 years. Here, the method of obtaining the predicted value after 10 years is exemplified, but the predicted value after 20 years can also be obtained by the same principle as shown in FIG. In FIG. 6, the horizontal axis represents data obtained by quantifying the body shape, physical strength, etc., and the vertical axis represents the frequency.
[0014]
FIG. 7 shows a schematic configuration of the age-specific database 3. This database 3 has the physical characteristics (height, weight, sitting height, chest circumference, waist circumference, joint position, body type, etc.) of thousands of real people for each age from 1 to 90 years old, Information on motor ability (joint range, muscle strength, style of movement, etc.) and sensory ability (sight, hearing, pain, taste, smell, temperature sensitivity, etc.) are stored separately for men and women. The aging effect processing unit 2 searches these databases 3 to predict how the physical characteristics, motor ability, and sensory ability of the input user's current human body model will change with aging. The parameter of the human body model after aging is output.
[0015]
It should be noted that how the physical characteristics, motor ability, and perceptual ability of the human body change as the age increases can be obtained in advance as an aging effect curve as shown in FIGS. Since the operation of the aging effect processing unit 2 is possible, the age-specific database 3 is not essential for the operation of the system. For example, FIG. 8A shows a state in which the body weight increases from the young age to the middle age and decreases from the middle age to the old age. Similarly, FIG. 8 (b) shows how the hearing decreases with aging, and FIG. 8 (c) shows how the blood pressure increases with aging. These are merely examples, and it goes without saying that aging effect curves can be obtained in the same manner for various other physical characteristics, motor skills, and sensory skills.
[0016]
(Embodiment 2)
In this embodiment, a case will be described in which how the user-friendliness of a product changes is predicted when the physical characteristics, motor ability, or sensory ability of the user of the product changes with aging. If the product to be purchased is to be used for a long time, according to the physical characteristics, motor ability, or perception ability of the product user at the present time, even if there is no problem in the usability of the product, As the population ages, there may be a problem with the usability of the product. Therefore, when selecting a product, information that is a reference for decision making is provided by using CG (computer graphics) and VR (virtual reality) technologies.
[0017]
That is, using the system of FIG. 1, information on a user who uses a product is input, and a human body model at the present time is created by the human body model generation unit. By synthesizing this human body model with the CG image of the product, the manner in which the human body model uses the product in the virtual space is displayed as shown in FIGS. 9 (a) and 10 (a). Next, a human body model when the user ages is created by the aging effect processing unit. Then, by synthesizing this human body model with the CG image of the product, the state in which the human body model uses the product in the virtual space is displayed as shown in FIGS. 9B and 10B. In this way, it is possible to check whether there is a problem in the usability of the product not only now but also in the future, and it is possible to provide information useful for decision making when selecting the product.
[0018]
FIG. 9 shows an operation in which a person who purchased the system kitchen opens the cupboard T near the ceiling. FIG. 6A shows a case where the current human body model uses a product, and it can be confirmed that the cupboard near the ceiling can be opened by reaching out. However, when the operating range of the joint becomes narrower due to aging, it can be seen that the cupboard near the ceiling cannot be opened even if the hand is extended as shown in FIG.
[0019]
FIG. 10 shows an operation in which a person who purchased a unit bath straddles the step D of the bathtub. The figure (a) is a case where the present human body model uses a product, and it can be confirmed that the step of the bathtub can be straddled. However, it can be seen that when the operating range of the joint becomes narrower due to aging, the step of the bathtub cannot be straddled as shown in FIG.
[0020]
In addition, in the examples of Fig. 9 and Fig. 10, the usability of the product is visualized and presented on the computer screen, but simply by numerical calculation, "There is a possibility that the hand near the ceiling will not reach after 30 years" A message such as “There is a possibility that the step of the bathtub may not be crossed in 40 years” may be output in a text format. Further, these messages may be displayed together with the images of FIGS. Furthermore, in response to these outputs, the design height can be changed a little lower or higher, or a product with a slightly larger or smaller size can be selected, so that the design can be changed interactively, and the results can be fed back. May be.
[0021]
(Embodiment 3)
FIG. 11 shows an example of an algorithm for selecting a product using a human body model that predicts an aging effect. If the product selection depends on the user's physical characteristics, motor ability, sensory ability, etc., even if the product to be purchased is compatible with the current user's body shape, physical strength, etc., the user's body shape, physical strength in the future If it changes, there is a possibility that usability deteriorates. Therefore, the product selection algorithm in FIG. 11 supports decision making at the time of product selection by making it possible to determine in advance whether or not a non-conformity between the product and the user will occur within the average life of the product or the user. It is.
[0022]
First, using the system of FIG. 1, based on information input from the current user, the human body model generation unit creates a human body model of the current user, selects one product to be purchased, and selects it on the computer. Perform a simulation to assess whether the product is suitable for the current user. If the product is not suitable for the current user, select another product and repeat the simulation with the current human body model to find a suitable product. When one product that matches the current user is found, the human body model after 10 years is created by the aging effect processing unit, and the simulation is performed on the computer. Evaluate whether it conforms. This process is repeated to evaluate whether the product is suitable for users after 20 or 30 years. If not, select another product and repeat the process. When the average life of the product or the average life of the user is exceeded, the simulation is terminated assuming that a suitable product is found. In this way, it is possible to select a product that does not cause a mismatch between the product and the user now and in the future.
[0023]
According to this embodiment, when the product has a long life expectancy and the selection of the product depends on the user's physical characteristics, for example, in an application such as purchasing a chair that fits the user's body shape, Can provide useful information to support decision making. Needless to say, the same applies to the case where the selection of the product depends on the user's motor ability and perceptive ability.
[0024]
(Embodiment 4)
In this embodiment, a case will be described in which the information used for product selection is information related to the force applied in the horizontal direction to the surface of the product. For example, when the user selects flooring, it is sufficient to check the surface texture on the computer screen when comparing the flooring, tiling, or carpet. I can not get information. Therefore, the user's current weight, leg strength, stride, etc. are measured by a measuring device connected to a computer, and the ease of slipping when each floor material is adopted is evaluated by the magnitude of the friction coefficient.
[0025]
Here, what the friction coefficient is will be described with reference to FIG. In the figure, S is the surface of the product, U is a part of the user's body, W is the force applied by the user in a direction perpendicular to the surface of the product, and F is the force applied by the user in the direction horizontal to the surface of the product. Represents. The coefficient of friction means the ratio of F / W when a part of the user's body that is in contact with the surface of the product slips with respect to the surface of the product.
[0026]
When evaluating the slipperiness of flooring, the force applied by the user in the direction perpendicular to the product surface from the user's current weight, leg strength, stride, etc., and the force applied by the user in the direction horizontal to the product surface Therefore, if the F / W value determined by the ratio is smaller than the friction coefficient of the floor material, it can be determined that the slip does not occur, and therefore it does not roll.
[0027]
By the way, a user's weight, leg strength, stride, etc. change gradually with aging. In addition, since the balance sensation and reflexes gradually become dull with age, even a flooring suitable for the current user may be a slippery and slippery flooring for an aging user. Therefore, the weight, leg strength, stride, etc. of the current human body model are corrected according to aging so that a floor material that does not slip and does not roll when the user ages can be selected.
[0028]
(Embodiment 5)
In this embodiment, a case will be described in which information used for product selection is information related to a force applied in a direction perpendicular to the surface of the product. For example, when a user chooses a sofa or bed, the amount of sinking caused by the user's weight when sitting on the sofa or lying on the bed greatly affects the comfort of the product. To do. Therefore, the user's current weight, body shape, and the like are measured by a measuring device connected to a computer, and the degree of subsidence when each product is selected is evaluated based on the magnitude of the elastic modulus.
[0029]
Here, what the elastic modulus is will be described with reference to FIG. In the figure, S is the surface of the product, U is a part of the user's body, W is an external force applied by the user in a direction perpendicular to the surface of the product, and d is when the repulsive force and the external force of the product surface antagonize. It represents the depth of the product surface sinking. The elastic modulus means a ratio of d / W.
[0030]
When selecting a sofa or bed, the depth d of the sink when the user is placed is a comfortable depth by the ratio of the external force W to the product surface determined by the user's body shape and weight. It can be seen that a product with a certain elastic modulus in an appropriate range should be selected.
[0031]
By the way, a user's body shape and weight change gradually with aging. Therefore, the body shape and weight of the current human body model are corrected according to aging so that products that are comfortable to use in the future can be selected.
[0032]
(Embodiment 6)
FIG. 14 shows an example of an algorithm that supports creation or change of a design of a house, a room, a kitchen, and the like using a human body model in which an aging effect is predicted. When designing for the current user at the design stage when building a new building or remodeling, there will be problems such as the user's body shape, physical strength, and feeling will change in the future, resulting in poor living comfort and usability. It can happen. Therefore, the design support algorithm shown in FIG. 14 supports design creation / change so that a design that does not cause incompatibility with the user within the service life of the house, room, kitchen, etc. or within the average life of the user is possible. It is.
[0033]
First, using the system shown in FIG. 1, based on information input from the current user, the human body model generation unit generates a human body model of the current user, and creates a new or extension / renovation design on the computer. Perform a simulation to evaluate whether the design fits the current user. If the design does not fit the current user, the design is changed and the simulation is repeated with the human model of the current user. Once a design that suits the current user is determined, a human body model after 10 years is created by the aging effect processing unit, and a simulation is performed on the computer, so that the design fits the user after 10 years. Evaluate whether or not This process is repeated to evaluate whether the design is suitable for users after 20 or 30 years. If not, change the design and repeat the process. When the average useful life of a house, room, kitchen, etc. or the average life of the user is exceeded, the simulation is terminated assuming that a suitable design has been created. In this way, it is possible to support the design of houses, rooms, kitchens, etc. that are comfortable and easy to use at present and in the future.
[0034]
In addition, although a house, a room, a kitchen, etc. were illustrated as a design object here, it is not limited to this, and it cannot be overemphasized that it can utilize widely when designing what is used over many years.
[0035]
(Embodiment 7)
In this embodiment, an application for evaluating the safety when a user who panics evacuates from the present and the future using the human body model generation system of the present invention will be described.
For example, when a fire occurs in a house or building, even if a fire alarm sounds, it may not be heard by an elderly person who is far away. In addition, when the smell of smoke or the sensitivity to temperature is weakened, the start of evacuation action may be delayed due to a delay in noticing the occurrence of a fire. Also, even if you notice the occurrence of a fire, you may be delayed because the evacuation behavior itself is slow if you are old and your physical strength is low, or because you cannot see the evacuation guide light in the smoke due to poor visual acuity .
[0036]
Therefore, the human model of the elderly is added to the current human model created by the human body model generation unit, taking into account the decline in perception ability such as hearing, olfaction, and visual acuity due to aging, and the decrease in physical strength required for evacuation. Created by the age effect processing unit, and evaluate the safety during evacuation using this human model of the elderly. In this way, when designing a house or building, even if you can evacuate safely with the current perceptive ability and athletic ability, you may not be able to evacuate safely if the perceptual ability or athletic ability declines in the future. Can be predicted.
[0037]
FIG. 15 shows a state in which perception ability such as hearing ability, olfaction, and visual acuity, and motor ability such as running speed decrease with aging. If the limits of the perceptual and motor skills required for safe evacuation are at the prescribed reference level, there is a possibility that safe evacuation may not be possible at an age that does not allow any ability to reach the prescribed reference level. I understand that there is. As a result, measures such as changing the design of a house or building can be implemented in advance.
[0038]
(Embodiment 8)
FIG. 16 shows a method of generating a crowd model using the human body model generation system of the present invention. First, a human body model generation unit generates a plurality of human body models. At this time, the generated human body model is generated based on different information, and the same human body model is not generated. Thereby, a plurality of human body models constituting a part of the crowd are generated.
[0039]
Next, an aging effect is imparted to each of the plurality of human body models generated here by the aging effect processing unit. At this time, human body models of various ages are generated by applying a plurality of aging effects to one human body model. Thereby, a crowd model can be generated substantially.
[0040]
In order to visualize the crowd in the virtual world, it is conceivable to use the data of real people, but collecting data of tens of thousands of people is very labor intensive. Therefore, as in this embodiment, for the plurality of human body models generated by the human body model generation unit first, the data of the real person is used, and for the crowd model generated by the aging effect processing unit, If a human body model to which a plurality of aging effects are given to the human body model is used, a crowd model can be efficiently generated with a small amount of data.
[0041]
(Embodiment 9)
In order to experience a panic situation in a huge underground mall or a huge building using a virtual reality generator, it is necessary to simulate how a huge crowd is facing a panic situation. Therefore, the crowd model described in the eighth embodiment is arranged in an underground mall designed on a computer as illustrated in FIG. 17A, and a panic state is created in a virtual world. For example, as shown in FIG. 17B, smoke is diffused or a fire alarm is sounded. At this time, due to the difference in individual perception ability of the crowd model, the timing at which the evacuation action starts is different between the person who can hear the fire alarm and the person who cannot hear it. Also, there is a difference in the direction of escape between those who can see the evacuation guide light and those who cannot see while the smoke is trapped. Furthermore, the time required for evacuation varies depending on the physical strength and age of the crowd model. By simulating differences in evacuation behavior due to differences in individual perception ability and movement ability of such a crowd model, a panic state can be simulated realistically. By repeating the simulation with various arrangements of fire alarms and evacuation guide lights, it is possible to find an arrangement that minimizes the damage. Moreover, disaster prevention awareness can be raised by observing the behavior of the crowd which faced the panic state like FIG.17 (c) using a virtual reality production | generation apparatus.
[0042]
(Embodiment 10)
18A and 18B illustrate a schematic configuration of a dome type display device that can be used as a virtual reality generation device. This device displays a stereoscopic image on a dome-shaped screen 6 in a real scale. From a pair of left and right projectors 7 provided on the top of the screen 6, the left and right eyes are passed through polarizing filters having different polarization angles. Is projected, reflected by the plane mirror 8 and projected on the screen 6. The observer M observes an image on the screen 6 through stereoscopic glasses having a polarizing filter. Thereby, the human body model can be stereoscopically displayed on an actual scale.
[0043]
By using the dome-shaped display device to display current and future human models on a real scale, it is possible to realistically observe changes in body shape and physical strength due to aging. In addition, it is possible to experience realistically how the appearance of the world changes due to a decrease in visual acuity due to aging, using a dome type display device.
[0044]
(Embodiment 11)
In this embodiment, a case where the human body model generation system of the present invention is arranged on a server that can be used via the Internet will be described. As shown in FIG. 19, a general user connects to the Internet using an Internet terminal composed of a personal computer or the like, accesses a server with a specific URL, and uses a human body model generation system. Information input from the keyboard and mouse of the Internet terminal is input to the human body model generation system via the Internet, and the human body model information output from the human body model generation system is displayed on the screen of the user's Internet terminal via the Internet. The In this way, the general user can know his / her future body shape and physical strength by inputting his / her current body shape and physical strength.
[0045]
In addition, the age-specific database of the human body model generation system can be remotely maintained via the Internet. For example, by uploading information collected by a research institution such as a university to a server via the Internet and adding it to the age-specific database of the human body model generation system, the statistical value of the database can be increased.
[0046]
In addition, by linking to an online shopping mall on the Internet, the product to be purchased matches the current and future body shape and physical strength using the human body model generation system of the present invention at the time of product purchase. Can be considered.
[0047]
In addition, by linking with a housing design support service on the Internet, designing a comfortable home for the present and the future using the human body model generation system of the present invention when creating a new construction / expansion / renovation plan for a house. Can do.
[0048]
Of course, there are conventional electronic commerce and housing design support services using the Internet, but it is not easy to use just by checking the CG of the product or the housing on the screen of the Internet terminal. In such a case, it becomes easy to confirm the usability of the product or the house by displaying the present and future human body models created by the human body model generation system of the present invention together with the CG of the product or the house.
[0049]
(Embodiment 12)
The human body model generation system of the present invention can also be used for predicting changes in body shape and physical strength due to differences in lifestyle. People who continue to live with lack of exercise, overeating (unbiased eating), and lack of sleep, and people who have moderate exercise, nutrition, and sleep, even if their physical characteristics, motor ability, and perception ability are the same And, it seems that there will be a difference in future body shape and physical strength.
[0050]
Therefore, in the system of FIG. 20, lifestyle information such as exercise, meal, sleep, etc. is input to the aging effect processing unit so as to be reflected in the difference in future body shape and physical strength. The lifestyle information evaluates the amount of exercise, the amount of nutrient intake, the amount of sleep, etc. by displaying and answering a plurality of questions on a computer screen, for example. In the aging effect processing unit, if the input exercise amount, nutrient intake, and sleep amount are not appropriate, the human body model so that the future physical characteristics, motor ability, and perception ability will deteriorate compared to the appropriate amount Add changes to. The output of the aging effect processing unit is displayed on a display or printed by a printer and presented to the user.
[0051]
In addition, if a user changes their lifestyle, such as exercise, food, sleep, etc., the user will be able to evaluate how the lifestyle will change in the future so that the user can evaluate how their physical characteristics, motor ability, and perceptual ability will change. You may be able to present the future image of.
[0052]
(Embodiment 13)
The human body model generation system of the present invention can also be used as a system for predicting the genetic effect from the generation before the parent to the generation of the child. As is well known, an individual's characteristics mainly depend on the characteristics inherited from their parent and previous generations.
[0053]
In the system of FIG. 21, as user information, information on the physical characteristics of a father (or a man who is scheduled to become a father), motor ability, perceptual ability, etc., and physical characteristics of a mother (or a woman who is scheduled to be a mother), Information such as motor ability and sensory ability is input. Based on these pieces of information, the genetic effect processing unit creates the parameters of the human body model of the child generation for one reference age. At this time, the sex of the child may be selectable, or either gender may be selected at random. Subsequent processing is the same as that of the system of FIG. 1, and a human body model generation unit generates a human body model of a child generation for one reference age. Thereafter, the aging effect processing unit adds information on changes in physical characteristics, exercise ability, and perception ability due to aging to the generated human body model. The output of the aging effect processing unit is displayed on a display or printed by a printer and presented to the user.
[0054]
In this way, it is possible not only to predict the child model of a child generation for one representative age, but also to predict the growth and aging processes throughout the life of the child generation.
In the illustrated embodiment, the example of generating a human body model of the child generation from the information of the father and mother has been shown. However, a human body model of the grandchild generation may be generated from the information of the grandfather and grandmother.
[0055]
【The invention's effect】
According to the first aspect of the present invention, it is possible to evaluate various changes due to aging by generating a human body model that reflects a difference in physical characteristics, motor ability or perception ability of a human body due to a difference in age.
According to the invention of claim 2, it is possible to predict how the usability of the product changes with the aging of the user of the product.
According to the invention of claim 3, a product suitable for the user can be selected not only in the present but also in the future.
According to the invention of claim 4, since the product can be selected using information related to the force applied in the horizontal direction with the surface of the product, for example, the coefficient of friction, the weight / physical strength of the user changes with aging. You can also select a product that is easy to use.
According to the invention of claim 5, since the product can be selected using information related to the force applied in the direction perpendicular to the surface of the product, for example, the elastic coefficient, the weight, physical strength, etc. of the user changes with aging. You can also select a product that is easy to use.
According to the invention of claim 6, a design suitable for the user can be created not only at the present time but also in the future.
[0056]
According to the invention of claim 7, safety at the time of evacuation can be evaluated not only for the present but also for the future.
According to the invention of claim 8, a crowd model can be efficiently created with relatively little data.
According to the ninth aspect of the present invention, it is possible to experience the situation when aging using the virtual reality generating device.
According to the invention of claim 10, by using a dome-shaped display device, a change due to aging can be experienced realistically.
According to the invention of claim 11, a general user can easily use the aging effect prediction human body model generation system via the Internet. In addition, remote maintenance of the database becomes possible.
According to the twelfth aspect of the present invention, it is possible to evaluate how future physical characteristics, athletic ability, and perceptual ability change due to differences in lifestyle.
According to the invention of claim 13, the life of the child can be simulated by generating a human body model of the child generation based on the information of the generation before the parent and providing an aging effect.
[Brief description of the drawings]
FIG. 1 is an explanatory view showing a configuration of an invention according to claim 1;
FIG. 2 is an explanatory diagram showing a configuration of a human body model generation unit.
FIG. 3 is an explanatory diagram showing an example of a human body model.
FIG. 4 is an explanatory diagram showing a difference in the physique of a human body model.
FIG. 5 is an explanatory diagram showing a configuration of an aging effect processing unit.
FIG. 6 is a diagram illustrating the principle of aging effect prediction.
FIG. 7 is an explanatory diagram showing the structure of an age-specific database.
FIG. 8 is an explanatory diagram showing an example of an aging effect curve.
FIG. 9 is an explanatory diagram showing a difference in product usability due to aging.
FIG. 10 is an explanatory diagram showing a difference in product usability due to aging.
11 is an explanatory diagram showing a product selection algorithm in the invention of claim 3. FIG.
12 is an explanatory diagram of a friction coefficient used for product selection in the invention of claim 4. FIG.
13 is an explanatory diagram of an elastic coefficient used for product selection in the invention of claim 5. FIG.
FIG. 14 is an explanatory diagram showing a design support algorithm in the invention of claim 6;
FIG. 15 is an explanatory diagram of the invention of claim 7;
FIG. 16 is an explanatory view of the invention of claim 8;
FIG. 17 is an explanatory diagram of the invention of claim 9;
18A and 18B are configuration diagrams of a dome type display device used in the invention of claim 10, wherein FIG. 18A is a side view and FIG. 18B is a front view.
FIG. 19 is an explanatory diagram of the invention of claim 11;
FIG. 20 is an explanatory diagram of the invention of claim 12;
FIG. 21 is an explanatory diagram of the invention of claim 13;
[Explanation of symbols]
1 Human body model generator
2 Aging effect treatment department
3 Age-specific database
4 Control unit
5 GUI
31 Physical feature database
32 Motor ability database
33 Perception ability database

Claims (13)

A system for generating a human body model that reflects the physical characteristics, motor ability or perceptual ability of a human body due to age differences,
A human body model generation unit that generates a human body model at a reference age based on given information;
An aging effect processing unit for adding a change in physical characteristics, motor ability or perception ability due to aging to a human body model at a reference age generated by the human body model generation unit. Age effect prediction human body model generation system. 3. The human body model generation unit according to claim 1, wherein the human body model generation unit generates a human body model at a reference age based on current information of a product user, and the aging effect processing unit is a body of the product user due to aging. An aging effect prediction human body model generation system characterized by adding at least a change related to a difference in usability of a product due to aging among changes in physical characteristics, motor ability or perception ability. 3. The aging effect according to claim 1, wherein the aging effect processing unit outputs information that can be used when a prospective purchaser selects one or more products from a plurality of products. Predictive human model generation system. 4. The aging effect prediction human body model generation system according to claim 3, wherein the information used for selecting the product is information related to a force applied in a horizontal direction to the surface of the product. 5. The aging effect prediction human body model generation system according to claim 3, wherein the information used for product selection is information related to a force applied in a direction perpendicular to the surface of the product. The aging effect prediction human body model generation system according to claim 1, wherein the aging effect processing unit outputs information that can be used when creating or changing a design. The aging effect prediction human body model generation system according to claim 1, wherein the aging effect processing unit outputs information that can be used when evaluating safety during evacuation. 2. The human body model generation unit according to claim 1, wherein the human body model generation unit generates a plurality of human body models based on different information, and the aging effect processing unit performs physical characteristics, motor ability or perception due to aging for each of the plurality of human body models. An aging effect prediction human body model generation system characterized by creating a crowd model by adding a change in ability. The aging effect prediction human body model generation system according to claim 1, further comprising a virtual reality generation device that outputs a processing result by the aging effect processing unit. 10. The aging effect prediction human body model generation system according to claim 9, wherein the virtual reality generation device includes a dome-type display device that displays the human body model in real scale. The aging effect prediction human body model generation system according to claim 1, wherein the human body model generation unit and the aging effect processing unit are arranged on a server that can be used via the Internet. The aging effect prediction unit according to claim 1, wherein the aging effect processing unit changes the degree of change in physical characteristics, motor ability, or perception ability due to aging according to the current lifestyle of the human body model. Human body model generation system. The aging effect prediction human body model generation system according to claim 1, wherein the human body model generation unit generates a human body model of a child generation based on information of generations before the parent.

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