Information system, information processing method, and program

Abstract

To detect the degree of a physical function or ability based on the relationship between measurement results of exercise items and the physical function or ability.SOLUTION: An information system comprises a control unit configured to: measure an achievement value for each of predetermined exercise items from an image capturing a person's motion; and determine the degree of physical vitality of the person corresponding to a second exercise item, which is different from a first exercise item and has been confirmed to have a correlation with the first exercise item, based on the achievement values for the respective exercise items.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information system, an information processing method, and a program. [Background technology]

[0002] In response to the decline in physical and mental functions that accompanies aging, for example, a method for measuring physical fitness data has been proposed (see, for example, Patent Document 1 below). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-204451 [Patent Document 2] International Publication No. 2020 / 208944 [Patent Document 3] Special Publication No. 2016-540527 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned conventional techniques do not necessarily clearly identify the relationship between physical fitness data, such as the measurement results of exercise items, and the decline in mental and physical functions that occurs with aging. In particular, sufficient consideration is not given to data items of physical fitness data that are difficult to measure.

[0005] The objective of the disclosed technology is to detect the level of physical function or ability based on the relationship between the measurement results of exercise items and physical function or ability. [Means for solving the problem]

[0006] One aspect of the disclosed technology is exemplified by an information system including a control unit that measures achievement scores for each predetermined exercise item from images of a person exercising, and determines, based on the achievement scores for each exercise item, a level of physical vitality for the person corresponding to a second exercise item that is different from a first exercise item and that has been confirmed to have a correspondence relationship with the first exercise item. [Effects of the Invention]

[0007] According to the information system of the present disclosure, the level of physical function or ability can be detected based on the relationship between the measurement results of exercise items and physical function or ability. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating the configuration of this information system. [Figure 2] FIG. 2 is a schematic flowchart illustrating a process for determining the physical vitality of a user in this information system. [Figure 3] FIG. 3 is a diagram illustrating an example of the relationship between the achievement score for each exercise item measured by an information processing device and the physical vitality of a user who has achieved the achievement score. [Figure 4] FIG. 4 is a diagram illustrating an example of the relationship between the achievement score for each exercise item measured by an information processing device and the physical vitality of a user who has achieved the achievement score. [Figure 5] FIG. 5 is a diagram illustrating an example of the relationship between the achievement score for each exercise item measured by an information processing device and the physical vitality of a user who has achieved the achievement score. [Figure 6] FIG. 6 is a diagram illustrating an example of the relationship between the achievement score for each exercise item measured by an information processing device and the physical vitality of a user who has achieved the achievement score. [Figure 7] FIG. 7 is a diagram illustrating a generalized example of the measurement data and physical vitality results. [Figure 8] FIG. 8 is a flowchart illustrating the processing of the information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0009] An information system, an information processing method, and a program according to an embodiment will be described below with reference to the drawings. The configurations of the following embodiment are examples, and the information system, the information processing method, and the program are not limited to the configurations of the embodiment.

[0010] This information system includes a control unit that measures the achievement value for each predetermined exercise item from an image of a person exercising, and determines the level of physical vitality of the person (user) corresponding to a second exercise item that is different from the first exercise item and has been confirmed to have a correspondence with the first exercise item based on the achievement value for each exercise item.

[0011] Here, the motion items include both dynamic and static items. Examples of dynamic items include walking, vertical jumping, and standing up from a chair. Static items include, for example, neck rotation to the maximum rotation angle position and maintaining the rotation for a predetermined period of time, shoulder rotation to the maximum rotation angle position and maintaining the rotation for a predetermined period of time, standing on one leg with eyes closed, standing on one leg with eyes open, moving the hands while bending forward in a seated position and maintaining the bending position for a predetermined period of time, moving the hands while bending forward in a standing position and maintaining the bending position for a predetermined period of time, spreading the legs to the maximum hip joint angle and maintaining the position for a predetermined period of time, extending the knee joint to the maximum knee joint angle while sitting and maintaining the position for a predetermined period of time, and maintaining the ankle joint at the maximum angle relative to the axis of the lower leg for a predetermined period of time. This information system recognizes the head, eyes, nose, ears, mouth, shoulders, hands, feet, etc. as feature points from images of a person's motion and measures the person's achievement score for these motion items. Dynamic motion items can be defined as motion items whose achievement score is speed, such as walking speed, and acceleration. Furthermore, dynamic exercises can be defined as exercises that involve changes in the user's position due to muscle strength. On the other hand, static exercises can be defined as exercises that involve maintaining a constant state, such as the body angle or the time required to maintain a position, or exercises in which a parameter indicating body flexibility is the achieved value. Static exercises can also be defined as exercises in which the body state is maintained due to muscle strength.

[0012] The information system also determines a person's physical vitality corresponding to a second exercise item that is different from the first exercise item and has been confirmed to have a correspondence with the first exercise item. Here, the first exercise item is, for example, an exercise item performed in a sitting position, and the second exercise item is an exercise item performed in a standing position. The first exercise item is, for example, a static exercise item, and the second exercise item is a dynamic exercise item. For such a second exercise item that is different from the first exercise item, the information system estimates the physical vitality corresponding to the second exercise item from the achievement value of the first exercise item based on the correspondence with the first exercise item. Physical vitality can also be referred to as physical ability or function.

[0013] <Embodiment> (Configuration) An information system according to one embodiment will be described below with reference to Figures 1 to 8. Figure 1 is a diagram illustrating the configuration of this information system. This information system includes an information processing device 1 that measures the achievement score for each exercise item of a user from an image and determines the physical vitality of the user, and an information acquisition device 2 that is connected to the information processing device 1 via a network N1. Note that in this embodiment, measurement is synonymous with measurement.

[0014] The information processing device 1, also called a server, reports the results of the physical vitality assessment to the user. The configuration of the information processing device 1 is similar to that of a normal computer. The information processing device 1 includes a CPU 101, a memory 102, an external storage device 103, a display device 104, an input device 105, and a communication device 106.

[0015] The CPU 101 executes a computer program that has been loaded in an executable manner into the memory 102, and provides the functions of the information processing device 1. The memory 102 is also called a main storage device. The memory 102 stores computer programs executed by the CPU 101, data processed by the CPU 101, etc. The CPU 101 is also called a processor. The CPU 101 and the memory 102 can be called a control unit.

[0016] However, the CPU 101 is not limited to a single processor, and may have a multi-processor configuration. The CPU 101 may also be a single processor connected via a single socket and have a multi-core configuration. Furthermore, at least a part of the processing of the information processing device 1 may be provided by a dedicated processor such as a digital signal processor (DSP), a graphics processing unit (GPU), a numerical calculation processor, a vector processor, or an image processing processor, an application specific integrated circuit (ASIC), or the like. At least a part of the information processing device 1 may be a dedicated large scale integration (LSI) such as a Field-Programmable Gate Array (FPGA) or other digital circuit. At least a part of the processing device 1 may include an analog circuit.

[0017] The memory 102 may be a Dynamic Random Access Memory (DRAM), a Static Random Access Memory (SRAM), or a External storage devices include static random access memory (SRAM), read-only memory (ROM), etc. The external storage device 103 is used, for example, as a storage area that supplements the memory 102, and stores computer programs executed by the CPU 101, data processed by the CPU 101, etc. The external storage device 103 is a hard disk drive, a solid state drive (SSD), etc. A drive device for a removable storage medium may be provided in the information processing device 1. The removable storage medium is, for example, a Blu-ray disc, a Digital Versatile Disc (DVD), a Compact Disc (CD), a flash memory card, or the like.

[0018] The display device 104 is, for example, a liquid crystal display, an electroluminescence panel, etc. The input device 105 is, for example, a keyboard, a pointing device, etc. In this embodiment, examples of pointing devices include a mouse and a touch panel, etc. The communication device 106 exchanges data with other devices on the network N1.

[0019] The information acquisition device 2 has a terminal 201 and a camera 202. Although the configuration of the terminal 201 differs in scale, the hardware configuration itself is the same as that of the information processing device 1. The terminal 201 transmits an image of the user taken by the camera 202 to the information processing device 1 via the network N1, and receives the assessment result of the user's physical vitality from the information processing device 1. The terminal 201 may be, for example, what is called a smartphone or a mobile terminal. The terminal 201 may also be what is called a personal computer.

[0020] The terminal 201 has an output device including a device similar to the display device 104 of the information processing device 1 and a speaker, etc. The terminal 201 guides the user with images and sounds from this output device, causing the user to perform the movements of the exercise items to be measured.

[0021] The camera 202 is a photographing device having an image sensor such as an SSD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor). The image of the user is acquired at a fixed frame period, stored in the terminal 201, and transferred to the information processing device 1. In FIG. 1, the camera 202 is externally attached to the terminal 201, but it may be built into the terminal 201. The network N1 includes a wired or wireless public network. The network N1 may be a wireless access network such as LTE (Long Term Evolution), 5G (5th Generation Mobile Communication System), or a later wireless access network. The network N1 includes the Internet and a core network. However, the network N1 does not include private networks such as VPNs (Virtual Private Networks). This may include a dedicated network or a dedicated line for each operator.

[0022] FIG. 2 is a schematic flowchart illustrating a process for determining a user's physical vitality in this information system. In this embodiment, the information processing device 1 outputs guidance via the terminal 201 and prompts the user to perform a predetermined exercise. The information processing device 1 also registers user attribute information and performs calibration (S1). The user attribute information includes, for example, height, weight, gender, and age. The information processing device 1 sets parameters such as the user's head length and limb lengths based on the height and weight. More specifically, the information processing device 1 selects a model that is closest to the user from the parameters of an internal model group formed in memory 102, and determines parameters such as the dimensions of each part of the user based on parameters such as the dimensions of each part of the body of the model, and reflects these parameters in the measurement of the user's exercise items in the image.

[0023] Calibration is a process of, for example, determining in advance the amount of change in the depth direction (also called the depth direction) of the image relative to the amount of change in the left-right direction (plane direction) of the user's feature points when the user rotates his / her head on the image. Through such calibration, the information processing device 1 determines the measured values ​​of the movement of each part of the user in three-dimensional space from the user's movement on the image, and further calculates the angle, length, etc. of the rotational state, extension state, and bending state of each part of the human body, such as the rotation angle of the head from a state facing forward.

[0024] The information processing device 1 may store calibration parameters for a plurality of model users having different body types, and may interpolate the calibration parameters for each user based on individual values ​​such as height, weight, etc. Strictly speaking, the amount of change in the depth direction (also called the depth direction) relative to the amount of change in the up, down, left, and right directions (within a plane) on the screen may be measured in advance for each user.

[0025] Next, the information processing device 1 outputs guidance via the terminal 201, has the user perform each exercise item, and collects images of the user performing the exercise items from the camera 202 (S2). Difficult exercise items are appropriately selected based on the user's response. The information processing device 1 guides the user to omit exercise items that are difficult for the user to perform based on the user's response from among the predetermined exercise items prepared in advance, and to perform the remaining exercise items. The information processing device 1 measures and records the achievement score for each exercise item from the collected images. The information processing device 1 then analyzes and assesses the user's physical vitality based on the measured achievement score for each exercise item. The information processing device 1 then outputs the assessment results of the user's physical vitality from the terminal 201 in the form of a result report (S3).

[0026] (Example of measurement data) 3 to 6 are diagrams illustrating the relationship between the achievement value for each exercise item measured by the information processing device 1 and the physical vitality of the user who achieved that achievement value. In each of FIGS. 3 to 6, the horizontal axis represents the achievement value for each exercise item, the vertical axis represents the user's physical vitality, and the measurement results are plotted with black dots. Each diagram also includes a regression line illustrating the relationship between the values ​​on the horizontal axis and the values ​​on the vertical axis, and a correlation coefficient (R 2 ) is illustrated. Here, a large number of users perform each of the exercise items shown in Fig. 3 to Fig. 6, and the information processing device 1 measures the achievement value of each user from an image of the user performing each of the exercise items.

[0027] Meanwhile, the physical vitality of each user shown in Figs. 3 to 6 is measured from each user before or after performing an exercise item. In Figs. 3 to 6, maximum walking speed (m / s) is used as the physical vitality. The maximum walking speed (m / s) can be obtained by measuring the travel time when each user walks a specified distance, for example, 10 m to 100 m, at the maximum speed. The maximum walking speed (m / s) is calculated by the information processing device 1. It is not necessary for the maximum walking speed (or shortest walking time) of each user to be measured offline, and an administrator who manages users may separately measure the maximum walking speed (or shortest walking time) of each user offline and input the measured value into the information processing device 1.

[0028] FIG. 3(A) shows the results of measuring the maximum neck rotation angle in a sitting position as a motor item. The maximum neck rotation angle in a sitting position is the maximum rotation angle when the user rotates their head left and right while sitting in a chair. The information processing device 1 measures the head rotation angle when the user turns right or left, using an image of the user's upper body taken from the front, with the user facing forward as the origin. The information processing device 1 identifies the positions of the user's eyes, nose, mouth, ears, etc. as features and measures the angle when the user turns right or left based on changes in the positions of these feature points. The information processing device 1 may also average the maximum right rotation angle and the maximum left rotation angle. The information processing device 1 may also use the larger or smaller value of the maximum right rotation angle or the maximum left rotation angle as the maximum neck rotation angle in a sitting position. Furthermore, the information processing device 1 may measure only one of the maximum right rotation angle and the maximum left rotation angle. In any case, Figure 3(A) shows that there is a clear correlation (correlation coefficient R 2 =0.3322), which means that there is a linear correlation.

[0029] Figure 3(B) shows the results of measuring the maximum shoulder rotation angle in a sitting position as an exercise item. The maximum shoulder rotation angle in a sitting position is the maximum rotation angle when the user rotates the upper body left and right while sitting.

[0030] The measurement method is the same as for the maximum neck rotation angle in a sitting position. However, for the maximum shoulder rotation angle in a sitting position, characteristic points that can be used include, for example, the centers of the eyes on the head, the midpoint between the ears, the center of the mouth, the tips of the shoulders, the center positions of the joints between the shoulders and the arms, the tips of the sleeves when wearing short-sleeved clothing, the positions of the elbows, the center positions of the wrists, and the tips of the hands. In any case, Figure 3(B) shows that there is a clear correlation (correlation coefficient R 2 =0.2649).

[0031] FIG. 4(A) shows the results of measuring the maximum hip joint flexion angle in the supine position as an exercise item. The maximum hip joint flexion angle in the supine position is the maximum angle when the user lies on their back and bends one knee, opening the upper leg (femur) forward (upward). More specifically, the user keeps one of their legs (e.g., the right leg) on ​​the floor parallel to the trunk, bends the knee of the other leg (e.g., the left leg) at a predetermined angle (e.g., 90 degrees), and then lifts the knee toward the upper body. At this time, the angle of the hip joint when the lifted knee moves to its maximum and the hip joint angle is at its maximum is the maximum hip joint flexion angle in the supine position.

[0032] The measurement method is the same as for the maximum neck rotation angle in the sitting position. However, when measuring the maximum hip flexion angle in the supine position, feature points such as the head, waist, knees, and toes can be used. Figure 4(A) shows that the correlation between the maximum hip flexion angle in the supine position and the maximum walking speed is weaker than the correlation between the maximum neck rotation angle in the sitting position and the maximum walking speed in Figure 3(A) and the correlation between the maximum shoulder rotation angle in the sitting position and the maximum walking speed in Figure 3(B).

[0033] FIG. 4(B) shows the results of measuring the maximum hip joint extension angle in the supine position as an exercise item. The maximum hip joint extension angle in the supine position is the maximum angle when the user lies on their back, straightens both knees, and opens the two upper thighs (femurs) forward and backward. More specifically, the user keeps one of their legs (e.g., the right leg) on ​​the floor parallel to the trunk, and straightens the other knee (e.g., the left leg) and pulls the knee up toward the upper body. At this time, the angle between the pulled-up knee and the trunk when the pulled-up knee has moved to its maximum and the hip joint angle is at its maximum is the maximum hip joint extension angle in the supine position.

[0034] The measurement method was the same as for the maximum hip flexion angle in the supine position in Figure 4(A). Figure 4(B) shows that the correlation between the maximum hip extension angle in the supine position and maximum walking speed is weaker than the correlation between the maximum neck rotation angle in the sitting position and maximum walking speed in Figure 3(A) and the correlation between the maximum shoulder rotation angle in the sitting position and maximum walking speed in Figure 3(B).

[0035] Figures 5(A) and 5(B) show the results of measuring the maximum knee joint extension angle in a seated position as an exercise item. The maximum knee joint extension angle in a seated position refers to the angle of the knee joint when the user is sitting in a chair or the like and the knee is extended, i.e., the angle between the upper leg (femur) and the lower leg (fibula and tibia). The maximum knee joint extension angle is, for example, 180 degrees when the knee is extended in a straight line. Note that Figure 5(A) shows data from a user whose maximum knee joint extension angle is close to 180 degrees, and Figure 5(B) shows data from a user whose maximum knee joint extension angle is close to 100 degrees.

[0036] The measurement method is the same as that for the maximum hip flexion angle in the supine position in Figure 4(A). Figure 5(A) shows that for users whose maximum knee joint extension angle in the sitting position is close to 180 degrees, the correlation with maximum walking speed is weaker than the correlation between the maximum neck rotation angle in the sitting position and maximum walking speed in Figure 3(A) and the correlation between the maximum shoulder rotation angle in the sitting position and maximum walking speed in Figure 3(B). However, it can be seen that the correlation in Figure 5(A) is stronger than the correlation between the maximum hip flexion angle in the supine position and maximum walking speed in Figure 4(A) and the correlation between the maximum hip extension angle in the supine position and maximum walking speed in Figure 4(B).

[0037] On the other hand, for users whose maximum knee joint extension angle is close to 100 degrees in Figure 5(B), the correlation with maximum walking speed is as weak as the correlation between the maximum hip joint flexion angle in the supine position and maximum walking speed in Figure 4(A) and the correlation between the maximum hip joint extension angle in the supine position and maximum walking speed in Figure 4(B).

[0038] FIG. 6A shows the results of measuring the maximum plantar flexion angle in a seated position as a motor item. The maximum plantar flexion angle in a seated position refers to the maximum change in the angle of the sole of the foot when the user sits on a chair or the like, bends the knee at a predetermined angle, and presses the toes downward (toward the sole). When measuring the change in the angle of the sole of the foot, the information processing device 1 may measure the angle at which the angle of the sole of the foot changes most toward the sole of the foot, centered around the heel joint, using a reference state in which the angle between the lower leg (fibula and tibia) and the sole of the foot is 90 degrees. However, in this embodiment, the maximum plantar flexion angle in a seated position is defined by measuring the angle of the sole of the foot relative to the axis of the lower leg (fibula and tibia). As the angle of the sole of the foot increases, the angle approaches 0 degrees (parallel) from 90 degrees (FIG. 6A).

[0039] The measurement method involves, for example, identifying the positions of multiple points on the axis of the toes, heel, and lower leg (fibula and tibia), as well as the knee and hip, and measuring the angle in a changed state relative to a reference state (for example). In FIG. 6(A), it appears that there is a negative correlation between the maximum ankle plantar flexion angle in a sitting position and maximum walking speed. However, as described above, in this embodiment, the maximum ankle plantar flexion angle in a sitting position is measured by measuring the angle of the sole of the foot relative to the axis of the lower leg (fibula and tibia). As the angle of the sole of the foot increases, the angle approaches 0 degrees (parallel) from 90 degrees. Therefore, FIG. 6(A) essentially shows a positive correlation between the magnitude of change in sole angle and maximum walking speed. It can be seen that the correlation in FIG. 6(A) is comparable to the correlation between the maximum hip joint extension angle in a supine position and maximum walking speed in FIG. 4(B).

[0040] Figure 6(B) shows the results of measuring the maximum ankle dorsiflexion angle in a seated position as a movement item. The maximum ankle dorsiflexion angle in a seated position refers to the maximum angle change of the sole of the foot when the user sits on a chair or the like, bends the knee at a predetermined angle, and pulls the toes up. The angle change of the sole of the foot can be measured, for example, when the angle between the lower leg (fibula and tibia) and the sole of the foot forms a 90-degree angle as a reference, and the angle change when the angle of the sole of the foot changes to the maximum relative to the reference state can be measured. In other words, the angle change is measured as a difference value from the reference state.

[0041] The measurement method is the same as the maximum plantar flexion angle of the ankle joint, for example, by identifying the positions of the toes, heel, axis of the lower leg (fibula and tibia), knee, waist, etc., and measuring the difference in angle when changed from the standard state. Figure 6(B) shows a positive correlation between the maximum ankle dorsiflexion angle in the sitting position and maximum walking speed. Furthermore, the correlation between the maximum ankle dorsiflexion angle in the sitting position and maximum walking speed is weaker than the correlation between the maximum neck rotation angle in the sitting position and maximum walking speed (Figure 3(A)) and the correlation between the maximum shoulder rotation angle in the sitting position and maximum walking speed (Figure 3(B)). On the other hand, the correlation in Figure 6(B) is stronger than the correlation between the maximum hip flexion angle in the supine position and maximum walking speed (Figure 4(A)) and the correlation between the maximum hip extension angle in the supine position and maximum walking speed (Figure 4(B)). Furthermore, the correlation in Figure 6(B) is comparable to the correlation between the maximum knee extension angle in the sitting position and maximum walking speed (Figure 5(A)).

[0042] FIG. 7 is a diagram showing a generalized example of the measurement data and physical vitality results obtained based on the results of FIGS. 3 to 6 above. As described above, there is a correlation between the measurement data (each maximum value) of the exercise items in a sitting position and the maximum walking speed in a standing position, and between the measurement data (each maximum value) of the exercise items in a supine position and the maximum walking speed in a standing position. Each maximum value can also be considered an achieved value for each user. The maximum walking speed in a standing position can be considered an example of physical vitality.

[0043] 7 illustrates an example in which the relationship between the measurement data X of the exercise items and the physical vitality Y is expressed by a regression line, Y=A*X+B. Here, in this embodiment, * indicates multiplication. Therefore, by storing the relationship between the measurement data X of the various exercise items and the physical vitality Y in the memory 102, for example, in the form of a regression line, the information processing device 1 can obtain the measurement data X from images of the user performing the various exercise items and estimate the physical vitality Y.

[0044] Here, the exercise items on the horizontal axis of FIG. 7 are, for example, exercise items in a sitting or supine position. Therefore, by storing the relationship in FIG. 7 in memory 102, the information processing device 1 can estimate physical vitality Y in a standing position from data on the achieved values ​​for each exercise item measured in a sitting or supine position. Furthermore, the maximum walking speed in a standing position is dynamic physical vitality, and the data measured in FIGS. 3 to 6 can also be considered static measurement data for each exercise item. Therefore, by storing the relationship in FIG. 7 in memory 102, the information processing device 1 can estimate dynamic physical vitality Y from the static measurement data for the exercise items.

[0045] Furthermore, by generalizing FIG. 7, the information processing device 1 may store in the memory 102 a relationship for calculating physical vitality Y from data X1 to Xn (n is an integer indicating the number of independent variables) for each of a plurality of exercise items. For example, let X1 be the maximum neck rotation angle in the sitting position in FIG. 3(A), X2 be the maximum shoulder rotation angle in the sitting position, X3 be the maximum hip joint flexion angle in the supine position in FIG. 4(A), X4 be the maximum hip joint extension angle in the supine position in FIG. 4(B), X5 be the maximum knee joint extension angle in the sitting position in FIGS. 5(A) and 5(B), X6 be the maximum ankle joint plantar flexion angle in the sitting position in FIG. 6(A), and X7 be the maximum ankle joint dorsiflexion angle in the sitting position in FIG. 6(B). In this case, physical vitality may be determined by an empirical formula such as Y=A0+A1*X1+A2*X2+···+A7*X7. Note that the empirical formula is not limited to a linear formula and may include higher-order terms, such as quadratic or higher.

[0046] The information processing device 1 may also store in the memory 102 a correlation for estimating physical vitality Y in a sitting or supine position from measurement data X in a standing position, and estimate the physical vitality Y in a sitting or supine position from the measurement data X in a standing position. The information processing device 1 may also estimate the bench press achievement value in a sitting or supine position, for example, based on walking speed in a standing position or vertical jump distance. Similarly, the information processing device 1 may store in the memory 102 a correlation for estimating static physical vitality Y from dynamic measurement data X of an exercise item, and estimate the static physical vitality Y from the dynamic measurement data X. Note that the measurement data of the exercise item is not limited to those exemplified in FIGS. 3 to 6. For example, the exercise item may include one-leg standing time with eyes open (or eyes closed) in a standing position and vertical jump distance. Furthermore, items of physical vitality may include the time spent standing on one leg with eyes open (or eyes closed) while standing, and the vertical jump distance.

[0047] (Processing example) 8 is a flowchart illustrating the processing of the information processing device 1. As illustrated in FIG. 1, the information processing device 1 receives an image of the user performing an exercise item, analyzes the image, and measures the achievement score of the exercise item. Then, the information processing device 1 determines the user's physical vitality numerically from the measured achievement score of the exercise item, and outputs a result report to the user's terminal 201.

[0048] In the process of Fig. 8, the information processing device 1 first sends guidance to the user via the terminal 201, prompting the user to perform each exercise item, and acquires images of the user performing each exercise item (S10). Then, the information processing device 1 measures, for example, the maximum neck rotation angle X1 in a sitting position (S11). Furthermore, the information processing device 1 estimates the user's maximum walking speed Y1 from an empirical formula such as the regression line illustrated in Fig. 7 based on the measured maximum neck rotation angle X1 in a sitting position (S12).

[0049] Next, the information processing device 1 measures, for example, the maximum shoulder rotation angle X2 in a sitting position (S13). Furthermore, the information processing device 1 estimates the user's maximum walking speed Y2 from an empirical formula such as a regression line based on the measured maximum shoulder rotation angle X2 in a sitting position (S14). Next, the information processing device 1 measures, for example, the time X3 spent standing on one leg with eyes open in a standing position (S15). Furthermore, the information processing device 1 estimates the user's maximum walking speed Y3 from an empirical formula such as a regression line based on the measured time X3 spent standing on one leg with eyes open in a standing position (S16).

[0050] Next, the information processing device 1 measures, for example, the time X4 spent standing on one leg with eyes closed while standing (S17). Furthermore, the information processing device 1 estimates the user's maximum walking speed Y4 from an empirical formula such as a regression line based on the measured time X4 spent standing on one leg with eyes closed while standing (S18). Next, the information processing device 1 measures, for example, the jumping distance X5 of a vertical jump (S19). Furthermore, the information processing device 1 estimates the user's maximum walking speed Y5 from an empirical formula such as a regression line based on the measured jumping distance X5 (S20).

[0051] Next, the information processing device 1 measures, for example, the maximum hip joint flexion angle X6 in the supine position (S21). Furthermore, the information processing device 1 estimates the user's maximum walking speed Y6 from an empirical formula such as a regression line based on the measured maximum hip joint flexion angle X6 in the supine position (S22). Next, the information processing device 1 measures, for example, the maximum knee joint extension angle X7 in a sitting position (S23). Furthermore, the information processing device 1 estimates the user's maximum walking speed Y7 from an empirical formula such as a regression line based on the measured maximum knee joint extension angle X7 in the sitting position (S24). Next, the information processing device 1 measures, for example, the maximum ankle joint plantar flexion angle X8 in a sitting position (S25). Furthermore, the information processing device 1 estimates the user's maximum walking speed Y8 from an empirical formula such as a regression line based on the measured maximum ankle joint plantar flexion angle X8 in the sitting position (S22). Note that the information processing device 1 may measure the maximum ankle joint dorsiflexion angle in a sitting position in addition to the maximum ankle joint plantar flexion angle X8 in a sitting position. Furthermore, the exercise items measured by the information processing device 1 are not limited to the example in FIG.

[0052] The information processing device 1 then compiles the user's physical vitality into a result report based on the estimated maximum walking speeds Y1 to Y8, etc., creates an overall evaluation, and outputs it from the terminal 201 (S27). The information processing device 1 stores the achievement values ​​for each exercise item measured in the past or the level of the user's physical vitality previously determined in the memory 102, the external storage device 103, etc. The information processing device 1 then compares the current achievement value for each exercise item with the achievement values ​​for each exercise item measured in the past. The information processing device 1 also compares the user's current level of physical vitality with the level of the user's physical vitality previously determined. This allows the information processing device 1 to detect, for example, a decline in physical vitality due to aging, or the maintenance and improvement of physical vitality as a result of training.

[0053] 8, the user's maximum walking speeds Y1 to Y8 are estimated from the maximum neck rotation angle X1 in a sitting position to the maximum ankle plantar flexion angle X8 in a sitting position, which are the user's achieved values ​​measured by the information processing device 1. However, instead of such processing, the information processing device 1 may calculate the physical vitality Y (e.g., the user's maximum walking speed) using an empirical formula such as physical vitality Y=A0+A1*X1+A2*X2+···+An*Xn (n is an integer).

[0054] (Effects of the embodiment) In this embodiment, the information processing device 1 measures the achievement value for each predetermined exercise item from an image captured of a person's exercise. Then, based on the achievement value for each exercise item, the information processing device 1 determines the user's level of physical vitality corresponding to a second exercise item that is confirmed to have a correspondence relationship with a first exercise item different from the first exercise item. The first exercise item is an exercise item identified from the image, and is illustrated, for example, on the horizontal axis in FIGS. 3 to 6. The second exercise item is, for example, walking, and the person's physical vitality corresponding to the second exercise item is their maximum walking speed. Therefore, the information processing device 1 can estimate the user's level of physical vitality, exemplified by their maximum walking speed, by measuring the first exercise item, even in an environment where it is difficult to measure the second exercise item or for a user for whom it is difficult to measure the second exercise item.

[0055] Here, the predetermined exercise items include a first type of exercise item in a seated position and a second type of exercise item in a standing position. The information processing device 1 performs at least one of determining the level of physical vitality corresponding to the second type of exercise item from an image captured of the user exercising the first type of exercise item, and determining the level of physical vitality corresponding to the first type of exercise item from an image captured of the user exercising the second type of exercise item. Therefore, the information processing device 1 can estimate the level of physical vitality corresponding to at least one of the exercise items in a seated position and the standing position from the measurement results of the other exercise item.

[0056] The predetermined exercise items include a first type of exercise item that is a static exercise item and a second type of exercise item that is a dynamic exercise item. The information processing device 1 can estimate the achievement value of one of the static exercise item and the dynamic exercise item from the achievement value of the other.

[0057] Furthermore, in the comprehensive evaluation (S27), the information processing device 1 compares the current achievement score for each exercise item with the achievement score for each exercise item measured in the past. The information processing device 1 also compares the user's current level of physical vitality with the level of physical vitality of the user determined in the past. Therefore, the information processing device 1 can identify the degree of decline in each user's physical vitality or the degree to which each user's physical vitality is maintained or improved. Therefore, the information processing device 1 can detect the decline in mental and physical function associated with aging, for example, based on the relationship between the measurement results of the exercise items and the decline in mental and physical function associated with aging. Furthermore, even if the user's physical function declines and the user is weak and has difficulty performing exercise items that require physical strength, the information processing device 1 can measure the physical vitality corresponding to the second exercise item that requires more physical strength by using a first exercise item that imposes a lower load on the user.

[0058] 1, the information processing device 1 further includes a communication device 106. The information processing device 1 then measures the achievement score for each exercise item from images of the user's exercise taken remotely via the communication device 106. Therefore, the user can obtain the achievement score for each exercise item in various places and environments, regardless of the installation location of the information processing device 1, and receive a result report on the level of physical vitality. [Explanation of symbols]

[0059] 1. Information processing equipment 2 Information acquisition device 101 CPU 102 memory 103 External storage device 104 Display device 105 Input Device 106 Communication equipment 201 terminals 202 Camera

Claims

1. Measuring achievement scores for each predetermined exercise item from images of the person's exercise; An information system having a control unit that executes the following: determining the degree of physical vitality of the person corresponding to a second exercise item that is different from the first exercise item and has been confirmed to have a correspondence relationship with the first exercise item, based on the achievement value for each exercise item.

2. the predetermined exercise items include a first type of exercise item in a seated position and a second type of exercise item in a standing position; 2. The information system of claim 1, wherein the control unit performs at least one of determining a degree of physical vitality corresponding to the second type of exercise item from an image captured of a person performing the first type of exercise item, and determining a degree of physical vitality corresponding to the first type of exercise item from an image captured of a person performing the second type of exercise item.

3. The predetermined exercise items include dynamic movement exercise items and static movement items, 2. The information system according to claim 1, wherein the control unit performs at least one of determining a degree of physical vitality corresponding to the static exercise item from an image captured of the person performing the dynamic exercise item, and determining a degree of physical vitality corresponding to the dynamic exercise item from an image captured of the person performing the static exercise item.

4. Further, a storage device is provided that stores the previously measured achievement values ​​for each of the predetermined exercise items or the previously determined degree of physical vitality of the person, 2. The information system according to claim 1, wherein the control unit performs at least one of comparing the current achievement value for each of the predetermined exercise items with the achievement value for each of the predetermined exercise items measured in the past, and comparing the person's current level of physical vitality with the person's level of physical vitality determined in the past.

5. Further comprising a communication device; The information system according to claim 1 , wherein the control unit measures the achievement value for each of the predetermined exercise items from images of the person's exercise taken remotely via the communication device, and determines the degree of physical vitality of the person.

6. A computer measures achievement values ​​for each predetermined exercise item from images of the person's exercise; An information processing method that executes the steps of: determining, based on the achievement value for each exercise item, the degree of physical vitality of the person corresponding to a second exercise item that is different from the first exercise item and for which a correspondence relationship with the first exercise item has been confirmed.

7. A computer measures the achievement value for each predetermined exercise item from an image of the person's exercise; A program for executing the steps of: determining, based on the achievement value for each exercise item, the degree of physical vitality of the person corresponding to a second exercise item that is different from the first exercise item and for which a correspondence relationship with the first exercise item has been confirmed.

Images