JP6980249B2 - Exercise equipment, controls, and programs - Google Patents

Description

The present invention relates to exercise equipment.

There are various devices for performing strength training. The content of the training performed using these devices is preferably set according to the physical characteristics, motor function, purpose and goal of the training, and the like. In this regard, Document 1 discloses that the type of exercise to be performed, the number of repetitions, and the intensity are set according to the needs of each user.

Japanese Unexamined Patent Publication No. 2015-83105

As an example of a training device, consider a leg press machine for repeatedly performing a series of exercises of stretching a leg from a bent state. Some leg press machines have a built-in spring, weight, control circuit, etc. in order to enhance the training effect, and have a function of adjusting the load (exercise intensity) given to the user.
In general, in a series of movements, there are points where it is easy to apply force (it is better to increase the load) and points where it is difficult to apply force (it should not be applied a lot of load), so the effect of training is maximized. In order to achieve this, it is preferable that the load amount can be adjusted in a series of movements. And this point may vary depending on, for example, the physical and functional characteristics (skeleton and muscles) of the user. When training is performed using a device in which the above points are improperly adjusted, not only the desired effect cannot be obtained, but also there is a risk of damaging the muscles.

Further, the above points may be influenced by the psychological state of the user (for example, as a result of feeling pain due to an injury or the like, it becomes difficult to exert power). In addition, the above points may differ depending on the purpose of training (diet, rehabilitation, improvement of competitiveness for a specific sport, etc.). As described above, there are various circumstances on the side of the user who performs training. For example, in the invention of Document 1, it is difficult to appropriately adjust the load amount in a series of movements according to the individual circumstances of each user. Is.

An object of the present invention is to adjust the load amount in a series of movements according to the individual circumstances of the user.

In one embodiment, in a series of exercises performed using an exercise device with an adjustable load, the present invention represents a relationship between a force applied to the exercise device and a displacement amount by a user during the exercise. Based on the first acquisition means for acquiring the above, the second acquisition means for acquiring the attribute information of the user, the kinetic characteristics of one user who has been trained using the exercise equipment, and the attribute information of the one user. A determination means for determining a load characteristic representing the relationship between the load and the amount of displacement when the one user exercises using the exercise equipment, and an instruction for setting a load based on the determined load characteristic. Provided is a control device having an output means for outputting to an exercise device.
From another point of view, the present invention determines the relationship between the force applied to the exercise device by the user during the exercise and the amount of displacement in a series of exercises performed on the computer using the exercise device with an adjustable load. Based on the step of acquiring the kinetic characteristics to be represented, the step of acquiring the attribute information of the user, the kinetic characteristics of one user who has been trained using the exercise equipment, and the attribute information of the one user. A step of determining a load characteristic representing the relationship between the load and the amount of displacement when the user exercises using the exercise equipment, and an instruction of load setting based on the determined load characteristic are output to the exercise equipment. Provides a program to execute the steps to be performed.
From another point of view, the present invention provides a movable portion whose load can be adjusted, a first acquisition means for acquiring a kinetic characteristic representing a relationship between a force applied to the movable portion and a displacement amount, and user attribute information. A load representing the relationship between the load and the amount of displacement when the one user exercises, based on the second acquisition means to be acquired, the exercise characteristics of the one user who has performed the training, and the attribute information of the one user. Provided is an exercise device having a determination means for determining a characteristic and an adjustment means for adjusting the movable load based on the determined load characteristic.

According to the present invention, the load amount in a series of movements can be adjusted according to the individual circumstances of the user.

The figure which shows the outline of the control system 100. The figure which shows the functional composition of the exercise equipment 200. The figure which shows the example of the exercise equipment 200. The figure which shows the other example of the exercise equipment 200. Enlarged view of another example of the exercise equipment 200. The figure which shows the functional structure of a server 300. The figure which shows the example of the information stored in the user DB 321. The figure which shows the example of the information stored in the machine DB 323. The figure which shows the example of the information stored in the exercise history DB 322. An example of the motor characteristic curve acquired at the start of training (No. 1). Example of load characteristic curve (1). Example of load characteristic curve (2). An example of the motor characteristic curve acquired at the start of training (Part 2). Example of load characteristic curve (3). Example of load characteristic curve (4). The schematic diagram (the 1) which shows the process of determining the similarity with the motor characteristic data of another person. The schematic diagram (2) which shows the process of determining the similarity with the motor characteristic data of another person. An example of the database 324 stored in the server 300. An operation example of the control system 100.

FIG. 1 shows an outline of the control system 100. The control system 100 includes exercise equipment 200-1, 200-2, 200-3, and a server 300.
Each exercise device 200 is an exercise device having at least a movable portion whose load can be adjusted, and is, for example, a pedaling machine, a leg press, a bench press, or the like. The content, type, and main body part of the exercise realized by the exercise equipment 200 are not particularly limited. In short, it is a device that gives a load to muscles by repeatedly causing a user to perform a series of movements (a unit of movement defined by a movement start point and a movement end point of a movable part). The unit of movement is typically the movement from the most bent state to the most extended state (or vice versa) of the legs and arms, but from the extended state to the further bent state. It may be regarded as one unit. Alternatively, the operation of pedaling the pedal only once can be said to be a series of operations.
In addition, each exercise device 200 has a function of adjusting parameters related to training in addition to the load amount (magnitude of force). Specifically, it has a function of adjusting the direction and timing of exerting force, as well as a function of setting and changing the number of times a series of exercises are repeated and the length of one training time.

Regarding the load setting, each exercise device 200 has a function (referred to as a training mode) for training the user in a state where the load characteristic based on the information instructed from the server 300 is set, and in order to determine the load characteristic. It has a function (referred to as a measurement mode) of generating motion characteristic data of the user used in the server 300 and providing the data to the server 300. In the measurement mode, for example, under control that the speed of equal load (the amount of load given to the user in a series of movements is constant) or constant speed (movement / rotation of moving parts, movements such as twisting) is constant. , By exercising the user.

A user who uses the exercise equipment 200 for the first time first exercises in the measurement mode, acquires a load characteristic reflecting his / her own exercise ability, etc., and trains for a predetermined period (for example, 3 months) in the training mode of the acquired load characteristic. After repeating, the measurement is performed again using the measurement mode, and the load characteristics are acquired (updated). By repeating the training mode and the measurement mode in this way, the user aims at the target physical state.

The function of each exercise device 200 (contents of the exercise to be realized) may be the same or different. Further, the number of the exercise devices 200 shown is merely an example, and it is sufficient that at least one or more of the exercise devices 200 are present in the control system 100. Each exercise device 200 may be installed in the same facility and used by the same user, or may be installed in a distant place.

The server 300 is realized as a general-purpose server device or computer, and is managed by the operator of the control system 100.
The exercise equipment 200 and the server 300 are connected via the network 900. The network 900 is composed of, for example, the Internet, a LAN, a base station, a wireless access point, and the like.

FIG. 2 shows the functional configuration of the exercise equipment 200. The exercise device 200 includes a movable mechanism 210, a control unit 220, a communication unit 230, a user identification unit 240, an input unit 250, a storage unit 260, and a notification unit 270.

The notification unit 270 is an output means such as a liquid crystal display or a speaker, and notifies the user of the information determined by the adjustment unit 223 by characters, images, voices, and the like.

The storage unit 260 is a storage device such as a semiconductor memory, and includes information for authenticating a user to be trained, information acquired by the sensor 211, and setting information necessary for controlling the load of the movable mechanism 210 (storage unit 260). Parameters and algorithms), and a program for realizing the functions described later in the exercise equipment 200 are stored.

The movable mechanism 210 includes a displacement mechanism such as a spring, a shaft, and a crank, and a motor, a control circuit, and the like for setting a load (drag) applied to the mechanism based on a control signal supplied from the load setting unit 221. .. By applying a force to the displacement mechanism against this load, the user can move the displacement mechanism and the user can perform a predetermined motion. The motion realized by the displacement mechanism is, for example, rotational motion or translation. In this embodiment, the type of exercise realized by the exercise equipment 200, the displaceable direction (degree of freedom of exercise) and the variable amount, and the body part to be trained are not particularly limited.

The movable mechanism 210 includes the sensor 211 and detects the result of the exercise performed by the user. Specifically, the sensor 211 is a sensor that measures the displacement amount (movement amount, rotation amount, etc.) of the movable mechanism 210 by a mechanical, electrical, or magnetic method, and the force received from the user in the displacement. Includes measuring sensors (acceleration sensor, angular velocity sensor, strain sensor, capacitance sensor, etc.).

The timing at which the sensor 211 acquires the measurement may be at predetermined sampling timings (for example, every 10 milliseconds), or a predetermined change amount (position change amount 1 cm, angle change amount 1 °, etc.) of the movable part. ) May be detected every time. In the latter case, if the displacement amount related to a series of exercises (distance from the exercise start point to the exercise end point) differs depending on the physique of the user, for example, the displacement amount related to the series of exercises is measured or registered in advance for each user. However, by dividing the displacement amount into equal parts by a predetermined method, a point for measurement by the sensor 211 may be set.

The measured information is sequentially stored in the storage unit 260, and is read out by the analysis unit 222 as needed. The displacement amount and momentum to be detected may be a one-dimensional value (scalar amount) or a multidimensional value (vector amount).

The input unit 250 is an input device such as a touch panel, and is used for inputting information for identifying a user who uses the exercise equipment 200, such as an ID and a password. In addition, the input unit 250 may be used to input the attribute information of the user. Attribute information includes basic or quantifiable objective information related to age / gender, physical characteristics, and motor function, as well as current body parts related to a series of exercises performed by the exercise device 200. Or information specific to the user, such as information on past failures (injuries and illnesses), information on the purpose of exercising, information on the user's feelings felt during exercise, the situation in which the user is placed, the background of training, etc. Can contain information about.

The above information may be input by a training user or a staff member of a facility that manages the exercise equipment 200. In the latter case, for example, even if the staff inputs the information obtained by hearing from the user using a computer (not shown) connected to the server 300 and sends the input information to the server 300. good. In this case, the server 300 is assigned to each user, and when it receives information about the user, it functions as an identifier of the user and issues information (QR code (registered trademark), etc.) for accessing the information about the user. , Exercise equipment 200 or a mobile terminal owned by the user (not shown) may be transmitted. Alternatively, the server 300 may acquire attribute information from a terminal carried by the user or an external server (such as a database that manages the user's medical history).

The purpose of exercising is, for example, strengthening muscle strength, improving exercise movement, improving sports skills, dieting (fat burning), recovery of muscle strength decreased due to aging or breakdown (so-called rehabilitation), and the like. The information regarding sensation is related to, for example, pain and discomfort associated with exercise.

The input unit 250 may be mounted as a device for performing voice input instead of the touch panel, or may be mounted as a device for reading information stored in an ID card carried by the user.

The control unit 220 is implemented as one or more general-purpose or dedicated processors, processors, or control circuits, and includes a load setting unit 221, an analysis unit 222, and an adjustment unit 223. The control unit 220 switches between the training mode and the measurement mode. It is executed by referring to the setting information provided from the server 300 at the time of user authentication, or is executed according to the setting information stored in the storage unit 260.

The analysis unit 222 acquires motion characteristic data representing the characteristics of the force exerted in the exercise of the user performed by using the exercise device 200. The motion characteristic data is defined as, for example, the relationship between the force (at least one of the magnitude and the direction) applied to the movable part of the movable mechanism 210 and the displacement amount of the movable part in a series of movements performed by the user. Can be done. Specifically, if the horizontal axis is defined as the displacement and the vertical axis is defined as the force exerted by the user, the motion characteristics can be expressed as a curve (characteristic curve). The method of expressing the motor characteristics is an example, and may show, for example, the relationship between the timing (time point) during a series of movements and the force exerted at that time point. For example, kinetic characteristics are expressed not by force (for example, the unit is Newton) itself, but by the period during which the force is applied (for example, watt unit) or power (for example, joule unit). May be good.
The acquired motion characteristic data is transmitted to the server 300 via the communication unit 230 and is supplied to the adjustment unit 223.
Further, the directly measured value (for example, voltage value / current value) of the sensor 211 may be output to the server 300 as it is without being converted into a quantity representing force. In this case, the server 300 may perform a predetermined conversion process in order to determine the load characteristic described later, or may determine the load characteristic without performing the conversion process.

The timing of transmitting the exercise characteristic data may be, for example, every time one cycle of exercise is completed, or at the time when a predetermined number of exercise cycles are completed, and a predetermined time has elapsed from the start of training. It may be at the time when it is done. When the motion characteristic data is transmitted through a plurality of cycles, for example, predetermined statistical processing is performed on the motion characteristic data obtained for each motion cycle, and the motion characteristic data is transmitted to the server 300 as one motion characteristic data. The predetermined statistical processing includes, for example, averaging and processing for extracting a part of measured data. The excerpt process is, for example, a process of extracting features such as a maximum value and a minimum value from data.

In the measurement mode, the load setting unit 221 generates a signal for controlling the load characteristics realized by the movable mechanism 210 and supplies the signal to the movable mechanism 210. When the load characteristic data acquired from the server 300 via the communication unit 230 is supplied to the load setting unit 221, the load setting unit 221 sets the load based on the load characteristic data at a predetermined timing. Instructions are supplied to the movable mechanism 210. The timing for outputting the load instruction may be in the middle of training (for example, every time one cycle of exercise is performed, or at the time when a predetermined number of exercise cycles are completed, or a predetermined time from the start of training. It may be set to always be the start of training.

The adjusting unit 223 controls parameters related to training other than the load characteristics. Specifically, the adjusting unit 223 is based on the information output from the analysis unit 222, and according to a predetermined algorithm, the position, orientation (posture), and speed (of the pedal in the pedaling machine) of the movable unit constituting the movable mechanism 210. Set the angle, the height of the sitting chair in the leg press machine, etc.). The set information is output to the movable mechanism 210. It should be noted that this parameter may affect the load amount, but the one that defines the load characteristic (how the load is changed during one cycle of exercise) is excluded.

Further, the adjusting unit 223 sets parameters related to the training content (time, number of repetitions, etc.) based on the information stored in the storage unit 260 and the exercise characteristics output from the analysis unit 222, and outputs the parameters to the notification unit 270. do. The timing for executing the setting of this parameter may be after the end of one cycle of exercise, may be after the end of one training consisting of a predetermined exercise cycle, or may be freely determined.
Parameters other than the load characteristics may be generated by the server 300 in the same manner as the load characteristics, and the adjusting unit 223 may acquire the information from the server 300.
Further, the adjusting unit 223 may set the above parameters in consideration of the information related to the user input to the exercise equipment 200 or acquired from the server 300 in addition to the information output from the analysis unit 222. ..

The user identification unit 240 is realized as a processor or a data reading device, and collates the information input by the input unit 250 and the information read from the ID card presented by the user with the information stored in the storage unit 260. For example, identify the user who is training (or is about to do so).
As another aspect, the user identification unit 240 is realized as an information reading device such as an IC card reader or a barcode reader, and the identification information such as the QR code issued by the server is transmitted to the user identification unit 240 before the user starts training. When held over, the user may be specified (authenticated), and information used for generating information to be set in the exercise equipment 200 for the user may be acquired from the server 300. In this case, the input unit 250 can be omitted.

The communication unit 230 is a communication interface for exchanging information with the server 300 in accordance with a predetermined communication standard. Specifically, the communication unit 230 transmits the motion characteristic data supplied from the analysis unit 222 to the server 300 together with the identification information for identifying the exercise device 200 and the identification information for identifying the user. Further, the communication unit 230 has load characteristic data determined based on at least one of the user attributes of the user to be trained and the exercise characteristics of users other than the user, in addition to the exercise characteristics of the user to be trained, and the load characteristic data thereof. When the accompanying information accompanying the above is acquired from the server 300, it is supplied to the load setting unit 221.

Further, when the training is completed, information indicating the content of the training is transmitted to the server 300. In addition, the communication unit 230 transmits the user attribute information input by the input unit 250 to the server 300, or receives the user attribute and setting information from the server 300, if necessary.

FIG. 3A shows an example of the appearance of the exercise equipment 200. In this example, the exercise device 200 is a so-called leg press machine and includes a user specifying unit 240 and a movable mechanism 210.

The exercise device 200 is composed of a footrest, a seat surface and a backrest joined to a movable mechanism 210 capable of translation, and is mainly intended to strengthen the muscle strength of the legs. The distance d from the footrest to the seat surface changes depending on the force applied to the footrest. The movable mechanism 210 has a built-in servo mechanism and the like, and can freely control the resistance force for moving the frame according to the position of the seat surface. That is, it is possible to control the amount of load to be generated according to the degree of bending of the legs. The distance d is the minimum when the foot is most flexed, and the distance d is the maximum when the foot is the most extended. Starting from the most flexed state of the foot and reaching the most extended state of the foot, one cycle of exercise is completed.

FIG. 3B shows another example of the appearance of the exercise equipment 200. In this example, the exercise device 200 is a pedaling machine that includes a user-specific portion 240 and a movable mechanism 210, and is mainly intended to strengthen the muscle strength of the foot by repeatedly rowing the movable mechanism 210.
FIG. 3C is an enlarged view of the pedal portion. The movable mechanism 210 includes a crank 215 and a pedal 216. The movable mechanism 210 has a built-in drive mechanism that can adjust the load amount according to the rotation angle of the crank 215 (the position of the pedal 216). One rotation of the pedal 216 (0≤θ≤360 °) corresponds to one cycle of motion. The initial movement position (θ = 0) is arbitrary.

FIG. 4 shows the functional configuration of the server 300. The server 300 has a function as a general information processing device having information input / output and arithmetic processing, and includes a determination unit 310, a communication unit 330, and a storage unit 320.

The determination unit 310 is realized as one or more general-purpose or dedicated processors, and determines the load characteristic to be set in the exercise equipment 200 based on at least the attribute information about a certain user provided by the exercise equipment 200. For example, the determination unit 310 determines the position of the maximum value, the position of the inflection point, the position of the minimum value, the value of the maximum value, the value of the minimum value, and the inflection point appearing in the motion characteristic curve according to a predetermined algorithm. The load characteristics are determined so that at least one of the values in is changed.
In a preferred embodiment, the determination unit 310 determines the load characteristics using the motion characteristics measured for the user and the user attributes of the user.

Further, the determination unit 310 may determine the load characteristic in consideration of the attribute information other than the user. Further, the determination unit 310 may determine the load characteristic in consideration of the motion characteristics of the user other than the user.
Specific examples of determining the load characteristics based on the attribute information of oneself and the exercise data of oneself or another person will be described later.

The determination unit 310 may further determine the load characteristic based on the result of comparing the first motion characteristic and the second motion characteristic acquired at different time points for the same user.
For example, in order to determine the load characteristic, the motion characteristic currently acquired for a certain user is compared with the motion characteristic already acquired for the user in the past (for example, three months ago) and stored in the storage unit 320. The load characteristics are determined by taking into account the motion characteristics just acquired and the result of the comparison. Specifically, the determination unit 310 uses a predetermined algorithm or the result of analyzing changes in the motor characteristics of another person and changes in the user attributes of another person accumulated in the storage unit 320, and changes in the motor characteristics of the user. Estimate the cause of. Then, the load characteristics are determined according to the estimated cause. For example, if it is estimated that the cause is an improvement in muscle strength, a load characteristic curve that increases the overall load is determined. Alternatively, if the user is suspected of being injured or otherwise in poor physical condition, a load characteristic curve that reduces the load is determined. The past motor characteristics to be compared may be data at one time point in the past (time before a predetermined period from the present or at the time when the measurement was last performed), or may be measured at two or more past time points. The given kinetic characteristics may be used. In the latter case, it is possible to determine the load characteristics to be set now by taking into account the transition of the exercise characteristics from the start of training to the present.
The comparison between one's current motor characteristics and past motor characteristics can be said to be one indicator of the effect of training accumulated in the past or the willingness to train. Therefore, it is possible to provide training with contents that take into account the motivation, potential ability, and function of the user, which is difficult to estimate only from the currently obtained motor characteristics and the user attributes indicating the current state of the user.

The timing for determining the load characteristic may be each time the exercise characteristic data is received from the exercise equipment 200, or a predetermined timing (when a predetermined number of exercise cycles are achieved, the elapsed time from the start of one training). , The number of times the training was performed, the predetermined elapsed time (20 days, 3 months, etc.).

The communication unit 330 is a communication interface for exchanging information with each exercise equipment 200 in accordance with a predetermined communication standard, and information for specifying the exercise equipment 200 from each exercise equipment 200, training with the exercise equipment 200. Acquire information, exercise characteristic data, and attribute information for identifying the user who performs the exercise. Further, the communication unit 330 transmits the load characteristic data generated by the server 300 to the exercise equipment 200.

The storage unit 320 is a storage device such as a hard disk or a semiconductor memory, and stores a user DB 321, an exercise history DB 322, and a machine DB 323 in addition to a program for realizing the functions of the server 300 described above. The user DB 321 and the machine DB 323 are referred to when the determination unit 310 generates the load characteristic data. The exercise history DB 322 is referred to when the determination unit 310 refers to the training history to generate load characteristic data.

FIG. 5 shows an example of information stored in the user DB 321. The user DB 321 stores setting information and user attributes (basic attributes and status information (information other than training content such as background and circumstances for training)) for each user. The setting information stores information related to training other than information related to load characteristics such as the position, angle, and speed of moving parts, in addition to training plans, schedules, contents, and policies.
The setting information and the attribute information may be registered in advance by the user, or may be input by the exercise equipment 200 at the start of each training and transmitted to the server 300 together with the exercise characteristic data. Either one of the basic attribute and the status information may be omitted.

FIG. 6 shows an example of information stored in the machine DB 323. The machine DB 323 stores parameters for adjusting the load of the exercise equipment 200 in association with the identification information for identifying each exercise equipment 200.
This parameter depends on the degree of freedom of movement that can be achieved with the exercise equipment 200. For example, in the case of a machine of 001, the load amount that can be set is a drag force (scalar amount), and by default, the load amount P is represented by a functional form of P0 (d). In the case of the machine of 002, there are two degrees of freedom of rotation about the X axis and rotation about the Y axis, and the load force W generated in the state of rotation (θ, φ) is W = W0 (θ, φ). ) Is expressed in the functional form.

FIG. 7 shows an example of information stored in the exercise history DB 322. The exercise history DB 322 stores information representing the contents of training performed in the past using the exercise equipment 200 for each user. Specifically, a record is generated each time training is performed. One record records the date and time when the training was performed, the machine ID that identifies the exercise equipment 200 that performed the training, the content of the training (applied load characteristics), the total exercise time, and the feedback (user's impression). To.

In this example, in the case of Mr. A, the exercise to which the load characteristic curve q1 is applied is performed for 10 minutes, the exercise characteristics are measured on another day to obtain the exercise characteristic curve p2, and the load characteristic curve is based on this result. q2 has been updated, indicating that the updated load characteristic curve q2 has been applied and exercised for 30 minutes.
The applied load characteristic and the measured motion characteristic do not need to be expressed as a motion characteristic curve or a load characteristic curve (continuous function). It may be a set of a combination of a discrete position (or a change amount) and a force (applied load) exerted at that position. In short, in this item, information representing the load characteristic applied by the exercise equipment 200 and information representing the result of the user's exercise acquired when updating the load characteristic are recorded.

<1. Example of determining the load characteristic curve based on its own attribute information>
FIG. 8 is a specific example of the motion characteristic curve acquired for a certain user. p1 indicates the characteristic of the force exerted when the user exercises on the leg press machine in the measurement mode. The horizontal axis is the amount of displacement (distance), and the vertical axis is the force exerted by the user or the magnitude of the force applied to the user. At the initial motion point d1, the force has a minimum value of Fmin, and as d increases (that is, as the leg is gradually extended), a large force is exerted, and the force takes a maximum value of Fmax at the displacement amount d = d2. That is, it is shown that this user exerted the most power at d = d2. When d becomes larger (the leg is stretched) from here, the exerted force gradually becomes smaller, and one cycle of exercise ends at the motion end point d3 (for example, the state where the leg is completely stretched).

FIG. 9 shows an example of a load characteristic curve q1 generated in consideration of the attribute information, training purpose, etc. of the user corresponding to the exercise characteristic curve p1 and applied in the subsequent training mode. In the load characteristic curve q1, the load applied at the initial motion point d1 and the operation end point d3 does not change, the peak position remains d2, and the peak load is higher than that of p1 in order to exert a greater force on the user near the peak position d2. The amount is set to increase by Δ = F'max −Fmax. That is, in this example, an algorithm aimed at correcting the obtained kinetic characteristics so as to change the peak intensity while maintaining the peak position is adopted.

FIG. 10 is an example of another load characteristic curve q2 generated for the motion characteristic curve p1. In this example, the point that the overall shape is convex upward does not change, but in the load characteristic curve q2, the peak position shifts to d2, but the peak value does not change. That is, the load characteristic curve q2 employs an algorithm aimed at encouraging the user to exert the strongest force in d2'(that is, at an earlier timing in a series of exercises). As a scene to make such a setting, for example, this user aims to improve the competitiveness, and for a normal person, it is ideal to exert the force as shown in the load characteristic curve q1 for increasing the muscle strength. It is conceivable that research has revealed that the method of exerting the force according to the load characteristic curve q2 contributes to the improvement of the competitiveness in the competition performed by this user. The shift direction of the peak may be opposite (report that the force is slowly exerted).
In this way, it is possible to make the user's body remember the ideal use of the muscle strength of the part to be trained according to the purpose of training and the like.

In this way, the load characteristic that is uniquely determined for the detected exercise characteristic is not determined, but the load characteristic is determined in consideration of the user's attribute, training purpose, and the like. As a result, even if there are users who exhibit similar motor characteristics, the set load characteristics will change if the basic attributes such as age and gender, the purpose of training, and the background of training are different. obtain.

FIG. 11 is another example of the acquired motion characteristic curve. As shown in the figure, the motion characteristic curve p2 has a minimum value at the displacement amount d4 and a maximum value at the displacement amounts d5 and d6. In general motion, the motion characteristics have one peak as shown in FIG. 8 and show a convex shape, but a shape like p2 is not normal. Therefore, if the load currently set on the exercise equipment 200 is continuously applied as it is, or if the load is uniformly increased or decreased (regardless of the amount of displacement), at least for this user, preferable training will be realized. It's hard to say.

FIG. 12 is an example of the load characteristic curve generated corresponding to the motion characteristic curve p2. In the load characteristic curve q3, the value Fmin at the initial motion point d1 is the same as that of the motion characteristic curve p2, but has an upwardly convex shape having one peak at the displacement amount d4. And the peak values are equal (F = q3 (d4) = p2 (d4)). That is, the load characteristic curve q3 is intended to encourage the user to perform ideal exercise characteristics (how to use the body) while lowering the exercise intensity as a whole.

For example, such a load characteristic curve is determined when the user is presumed to be in pain or has been injured in the past from the user attributes. If it is presumed to be caused by pain or breakdown, it may damage the muscles, so when features such as the motor characteristic curve p2 are measured, it is ideal without applying more load than strengthening muscle strength. It is considered preferable to set a characteristic such as the load characteristic curve q3 so that the movement can be remembered.

When the fact of pain or failure cannot be inferred from the attribute information, a load characteristic curve such as q4 is determined. This aims to improve both exercise intensity (strengthening muscle strength) and exercise characteristics (how to use muscles) at the same time.

Alternatively, when the purpose of forcing only the habit of using muscles is described in the attribute information, the exercise intensity (corresponding to the curve and the area surrounded by the two axes) is the exercise characteristic curve p2 as shown in q5. The load characteristic may be set so as to be substantially the same as the above and to correct the curved shape to a state close to the ideal state.

Alternatively, if the fact of pain or failure cannot be seen, for example, it is stated in the attribute information that the emphasis is on increasing muscle strength, there is also the idea of maintaining (not correcting) the curved shape as it is. obtain. In such a case, the determination unit 310 may set the load characteristic as shown in FIG. 13 with respect to the motion characteristic curve p2. The purpose of this is to train so that the force is exerted more in the position where the force is applied, while to be able to train without applying much force in the position where the force is not so much.

According to the above embodiment, in addition to the characteristics of the exercise performed by the user, the load characteristics of the exercise equipment 200 can be set by adding factors other than the exercise characteristics unique to each user.

<2. Example of determining the load characteristic curve by taking into account the motor characteristics of others>
FIG. 14 is a schematic diagram for explaining an example in which the server 300 determines the load characteristic curve using the information of another person. Here, it is assumed that the motion characteristic curve p2 shown in the upper figure of the same figure is obtained for the target user (here, Mr. A). Then, the determination unit 310 searches the motion history DB 322 and determines the motion characteristic data having the closest similarity to p2 by using a predetermined pattern matching algorithm.
In this example, it is assumed that the degree of similarity with the motor characteristic data of Mr. C is the highest. Then, the determination unit 310 generates the load characteristic data for Mr. A based on the load characteristic data generated for the motion characteristic data of Mr. C. Specifically, the load characteristic data generated for Mr. C may be adopted as the load characteristic data for Mr. A as it is, or as the difference between the motion characteristic data of Mr. A and the motion characteristic data of Mr. C. Based on this, the load characteristic data generated for Mr. C may be corrected.
The predetermined pattern matching algorithm is not limited to a fixed algorithm, and for example, a technique related to so-called AI (artificial intelligence) such as machine learning is applied to the motion characteristics and attribute information accumulated in the server 300. It may be obtained by. As machine learning, for example, a deep learning method can be adopted.

Further, the calculation of the load characteristic data does not necessarily have to use the load characteristic data itself generated for another person as long as it is based on other motion characteristics. For example, the server 300 analyzes the accumulated user attributes and exercise characteristics for a large number of people, and the update pattern of the load characteristics applied in the exercise equipment 200 in the past and the attributes of the user to which the pattern is applied. Is stored in the storage unit 320. Then, in response to the request from the exercise equipment 200, one update pattern corresponding to the attribute of the user and / or the past training content is determined from the predetermined patterns.

For example, the server 300 creates a database 324 as shown in FIG. 15 based on the accumulated exercise characteristics and user attributes. In this database 324, information representing the user attributes of a plurality of users to whom the pattern is applied, the frequency with which each update pattern is applied, and the frequency with which each update pattern is applied are applied in association with each update pattern (combination of load characteristics before and after the update). It describes the user's training history at the time (frequency of training, total time of training, other training performance and schedule information), and the effects of this load characteristic change.
Here, the effect in the figure may be subjective information input by a user or a trainer, or data analysis of two motion characteristics measured at two time points before and after updating the load characteristics. It may be expressed using an index showing the athletic ability or physical change due to the training performed using the load characteristic obtained. Further, this effect may be described for each user attribute. That is, an effect peculiar to a user having a predetermined user attribute may be described.
In this example, among the users who applied the load characteristic q1, the ratio of the users who changed to the load characteristic q5 after that was the highest at 50% of the whole, and half of the users who changed to the load characteristic q5 were for dieting purposes. On average, it was less than a month after starting training, indicating that many users responded that they could continue without difficulty.

The determination unit 310 determines the load characteristics by referring to this database 324. For example, the determination unit 310 determines the update pattern having the highest degree of conformity with respect to the user attributes of the target user and the training period. For example, if you are a female user for dieting purposes, the load characteristic q5 is selected.
The load characteristic (for example, q5) determined in this way may be information depending on the motion characteristic, or may be defined independently of the motion characteristic (for example, data representing the load curve itself). May be good. In the former case, for example, the shape of the load curve is an ideal shape, but the load characteristic is intended to increase the peak value of the current motion characteristic data by 5%. In the latter case, it is not necessary to measure the motion characteristics in order to determine the load characteristics, and it is sufficient that only the user attributes can be determined. Therefore, in this case, the above-mentioned measurement mode may be omitted in the exercise equipment 200.

In general, since the amount of motion characteristic data and the corresponding load characteristic data is large, a considerable amount of calculation may be required for data analysis such as matching processing of motion characteristic data. According to the mode of determining the load characteristic by using, it is sufficient to determine one update pattern that matches the user attribute etc. from a plurality of predetermined update patterns, so that the amount of calculation at the time of determining the load characteristic can be suppressed. Can be done.

Alternatively, the determination unit 310 may determine the update pattern to be selected based on the information about the effect when applied to another person instead of the user attribute of another person or together with the user attribute of another person. For example, for the user who is currently applying the load characteristic q5, among the update patterns q1 → q5, q1 → q6, q1 → q7, ..., The update pattern having the largest index value indicating the effect is determined. .. Alternatively, the update pattern may be determined in consideration of the similarity of user attributes and the degree of effect. For example, even if the update pattern can be expected to be highly effective for users with general attributes (in other words, it is highly universal), such effects cannot be expected so much if the user attributes are far from the general. Therefore, for a user with such an attribute, it is possible to make a determination that the similarity of the user attributes is prioritized and another update pattern is selected.

By generating load characteristic data based on the actual results applied to others in this way, there is a possibility that the reliability will be higher than when the load characteristics are calculated based only on theory. This reliability is expected to increase as the number of motion characteristic data and load characteristic data stored in the server 300 increases, in other words, as a large number of exercise devices are connected to the server 300.

In addition, both the attribute information of oneself and the motor characteristics of another person may be added. For example, when information called a diet purpose is described as self-attribute information, load characteristic data theoretically obtained according to the purpose is generated, and a load generated for another person having a high degree of similarity in motor characteristics. Correct based on the difference from the characteristic curve data.

Load characteristic data may be generated based on one's current or past attribute information, another person's present or attribute information, and another person's current or motor characteristics. For example, as shown in FIG. 16, the determination unit 310 individually determines the similarity of the motor characteristics and the similarity of the user attributes, and comprehensively determines the similarity of the motor characteristics and the similarity of the user attributes according to a predetermined algorithm. The degree of similarity is calculated, and the load characteristic is determined based on the motion characteristic data having the highest overall degree of similarity. In the figure, it is shown that the motor characteristic data of Mr. D is selected as a result of comprehensively evaluating the similarity of the motor characteristics and the similarity of the user attributes.
Alternatively, one or more users having attribute information having a certain degree of similarity with the attribute information of a certain user are first extracted, and the similarity is the highest among the motor characteristic data generated for the extracted one or more users. High exercise characteristic data may be specified, and load characteristic data for a certain user may be generated based on the load characteristic data generated for the specified exercise characteristic data.
It is expected that the validity of the load characteristics will be improved by adding the commonality with the attributes of others in this way.

In this case, the determination unit 310 further refers to the user DB 321 to acquire the attribute information of the user (in this case, Mr. C) used for generation, and generates information based on the attribute information as incidental information. May be good. For example, if it is stated that Mr. C has knee pain as the attribute information, "Mr. A may not be able to exert his strength well due to the pain in his knee." Generate textual information. The accompanying information generated in this way is transmitted to the exercise equipment 200 together with the load characteristic data. Alternatively, for example, if the user is presumed to be an athlete based on user attributes, a message such as "Your muscles are used better than others" may be generated.
Such a message may be registered in advance in association with attribute information and motor characteristics, or can be obtained by applying a reinforcement learning method to a large number of accumulated motor characteristics and attribute information. It may be generated based on the event or knowledge (correlation between load characteristic data and user attribute, causal relationship, etc.).
By using the user attributes of others in this way, it is possible to provide the user with a cause that the user is not aware of and a solution / advice for the cause.

In addition, the motor characteristics of another person and the load characteristic data generated for the other person may be included in the accompanying information. Providing information about the training of others is expected to encourage training.

As incidental information generated by the determination unit 310, information on the health condition or information on the possibility of a disease may be included. For example, the accompanying information includes information indicating that the kinetic characteristics of the one user differ from the reference kinetic characteristics by a predetermined degree or more. Specifically, the determination unit 310 stores characteristic motor characteristic data for each disease, calculates the degree of agreement between the acquired exercise characteristic and the stored exercise and the characteristic, and the degree of agreement is equal to or higher than a predetermined value. If so, generate a message indicating that there is a possibility of serious illness. Here, the motor characteristic data characteristic of the disease may be calculated by 310 by analyzing the correlation between the information related to the disease and a large number of motor characteristic data among the attribute information of a plurality of users.

FIG. 17 shows an operation example of the control system 100. At the start of training, when the user performs a login operation such as inputting a user ID or holding a QR code including user ID information (S101), the exercise equipment 200 transmits the user ID to the server 300. The server 300 authenticates whether or not the user is registered based on this user ID (S102).

Subsequently, the exercise equipment 200 determines whether to apply the training mode or the measurement mode to this user. For example, if the user is a first-time user and there is no load characteristic data to be applied to this user, or if a predetermined period has passed since the load characteristic data was set last time and the load characteristic data needs to be updated. The measurement mode is applied (S104: YES), and the training mode is applied otherwise (S104: NO).

When the measurement mode is applied, the exercise device 200 displays a guidance message or the like urging the user to perform exercise, and acquires exercise characteristic data based on the user's exercise (S106). The acquired data is transmitted to the server 300 together with the information for identifying the user and the information for identifying the exercise equipment 200 at a predetermined timing (S108).

The server 300 generates load characteristic data using this motion characteristic (S110) and transmits it to the exercise device 200 (S112). The exercise equipment 200 that has received the load characteristic data applies the training mode and sets the load based on the load characteristic data (S114). When the load characteristic data includes the above-mentioned incidental information, the incidental information is supplied to the notification unit 270 and provided to the user.

On the other hand, when the training mode is applied, the exercise equipment 200 acquires the load characteristic data corresponding to the user from the server 300 and applies it (S111, S114).

After that, when the update time of the load characteristic data arrives during the training period (S115: YES), the exercise equipment 200 shifts to the measurement mode and updates the exercise characteristic data (S116, S108, S110, S112, S114). .. When the training of the user is completed (S116: YES), information representing the content (results) of the training is generated (S118) and transmitted to the server 300 (S120). The end time of the training may be instructed by the user, or the time when the time described in the setting information applied at the start of the training has elapsed may be determined as the end of the training. The server 300 updates the exercise history DB 322 based on the received information (S122).

The load characteristic generation function of the server 300 may be provided in each exercise device 200, or may be provided in a control device built in the exercise device or attached after the fact. That is, the present invention relates to a plurality of users in a series of exercises performed by using an exercise device provided with a movable portion whose load can be adjusted, the force applied to the movable portion and the displacement amount of the movable portion. A load on the one user based on the acquisition means for acquiring the kinetic characteristics representing the relationship, the kinetic characteristics of one user who has been trained using the exercise equipment, and the kinetic characteristics of a user other than the one user. It includes a control device having a determination means for determining a characteristic and an output means for outputting a load setting instruction based on the determined load characteristic to the exercise equipment.

In short, in the system according to the present invention, in a series of exercises performed by using an exercise device provided with a movable portion whose load can be adjusted, the relationship between the force applied to the movable portion and the displacement amount of the movable portion is determined. Based on the step of acquiring the kinetic characteristics to be represented, the step of acquiring the attribute information of the user, the kinetic characteristics of one user who has been trained using the exercise equipment, and the attribute information of the one user. The step of determining the load characteristic for the user and the step of outputting the instruction of the load setting based on the determined load characteristic to the exercise equipment may be executed.

100 ... Control system, 200 ... Exercise equipment, 300 ... Server, 900 ... Network, 210 ... Movable mechanism, 240 ... User identification unit, 215 ... Crank, 216 ... -Pedal, 211 ... Sensor, 220 ... Control unit, 230 ... Communication unit, 250 ... Input unit, 260 ... Storage unit, 270 ... Notification unit, 221 ... Load setting Unit 222 ... Analysis unit 223 ... Adjustment unit, 320 ... Storage unit, 310 ... Decision unit, 330 ... Communication unit, 321 ... User DB, 322 ... Exercise history DB, 323 ... Machine DB

Claims (10)

In the exercise performed by using the exercise equipment whose load can be adjusted, the first acquisition means for acquiring the exercise characteristics representing the relationship between the force applied to the exercise equipment and the displacement amount by the user during the exercise, and the first acquisition means.
The user's attribute information, including at least one of information about current or past injuries or illnesses in the user's body parts related to the exercise and information about the purpose of the exercise for the user. The second acquisition means to acquire and
Based on the exercise characteristics of one user who has been trained using the exercise equipment and the attribute information of the one user, the load and displacement amount when the one user exercises using the exercise equipment. Determining means for determining the load characteristics that represent the relationship,
A control device having an output means for outputting a load setting instruction based on the determined load characteristic to the exercise equipment. The first acquisition means acquires kinetic characteristics at a plurality of time points for the one user.
The determining means determines the load characteristic for the one user based on the kinetic characteristics measured at the first time point and the kinetic characteristics measured at the second time point for the one user. The control device according to claim 1. The first acquisition means acquires kinetic characteristics for a plurality of users and obtains them.
The first or second aspect of the present invention, wherein the determination means determines a load characteristic for the one user based on the exercise characteristic of the one user and the exercise characteristic of a user other than the one user. Control device. The control device according to any one of claims 1 to 3, wherein the determination means further determines the load characteristics based on attribute information other than the one user. The determination means further generates ancillary information generated based on the motor characteristics of a user other than the one user.
The control device according to claim 3 or 4, wherein the output means further outputs the determined accompanying information. The control device according to claim 5, wherein the accompanying information is further generated based on the attribute information of a user other than the one user. The control device according to claim 5 or 6, wherein the accompanying information indicates that the motion characteristics of the one user differ from the reference motion characteristics by a predetermined degree or more. The control device according to any one of claims 1 to 7 , wherein the attribute information further includes information regarding a sensation felt by the user during the exercise. On the computer
In an exercise performed using an exercise device with an adjustable load, a step of acquiring a movement characteristic representing the relationship between the force applied to the exercise device by the user and the amount of displacement during the exercise, and
The user's attribute information, including at least one of information about current or past injuries or illnesses in the user's body parts related to the exercise and information about the purpose of the exercise for the user. Steps to get and
Based on the exercise characteristics of one user who has been trained using the exercise equipment and the attribute information of the one user, the load and displacement amount when the one user exercises using the exercise equipment. Steps to determine the load characteristics that represent the relationship,
A program for executing a step of outputting a load setting instruction based on the determined load characteristic to the exercise equipment. Movable parts with adjustable load and
The first acquisition means for acquiring the motion characteristics representing the relationship between the force applied to the movable portion and the displacement amount during the exercise by the user.
The user's attribute information, including at least one of information about current or past injuries or illnesses in the user's body parts related to the exercise and information about the purpose of the exercise for the user. The second acquisition means to acquire and
Based on the exercise characteristics of one user who has undergone training and the attribute information of the one user, a determination means for determining the load characteristics representing the relationship between the load and the displacement amount when the one user exercises, and
An exercise device having an adjusting means for adjusting the load of the movable portion based on the determined load characteristic.

Images