KR20240055471A - Personalized muscle strength measurement device and strength exercise method using the same - Google Patents

Abstract

Disclosed is a personalized muscle strength measurement device and a strength exercise method using the same. The personalized muscle strength measuring device of the present invention includes a handle that the user can hold with one hand or both hands; a connection strip portion having a predetermined elastic force connected to one side of the handle portion; a measuring unit connected to the other side of the connection strip unit and measuring an external force pulled by the connection strip unit; and a fixing strip part connected to the other side of the measuring part and capable of being fixed to a part of the user's body or an object, wherein the measuring part adjusts the maximum value of the force for pulling the connecting strip part by the handle part to a constant level. Measurements can be made multiple times over a time period.

Description

Personalized muscle strength measurement device and strength exercise method using the same {Personalized muscle strength measurement device and strength exercise method using the same}

The present invention relates to a personalized muscle strength measuring device and a strength exercise method using the same. More specifically, the present invention relates to a personalized strength measurement device that enables effective strength exercise by precisely measuring individual exercise intensity and using it as a reference intensity during repetitive exercise. It relates to a device and a method of strength training using the same.

Interest in home training is increasing due to changes in external environments and social awareness such as the COVID-19 pandemic. Home training has the advantage of being less restricted by location and time, and various contents for home training are being developed and shared so that people can exercise sufficiently on their own. When referring to home training content at home, you can follow the exercise method and exercise posture to some extent.

However, in the case of home training, the problem is that it is difficult to quantitatively measure exercise intensity and exercise effectiveness. In particular, even though there are differences in individual exercise abilities, when exercising with reference to standardized home training videos, it is impossible to measure the exact muscle use or maximum available strength, so it is impossible to know how much exercise the exerciser has done. It is difficult to record exercise results, and problems are being pointed out in establishing exercise plans.

Therefore, there is a need for the development of a standardized muscle strength measuring device that can accurately measure the amount of muscle strength used and quantitatively confirm the amount of exercise when performing home training, and a strength exercise method using the same.

Patent Document 1: Korean Patent Publication No. 10-2022-0097846 (Published Date: 2022.07.08.) Patent Document 2: Korean Patent No. 10-2277220 (Announcement Date: 2021.07.16.) Patent Document 3: Korean Patent No. 10-1842514 (Announcement Date: 2018.03.27.) Patent Document 4: Korean Patent No. 10-1457353 (Public Notice Date: 2014.11.03.) Patent Document 5: Korean Registered Utility Model No. 20-0471720 (Announcement Date: 2014.03.14.)

The present invention, created in response to the above-described need, can precisely measure the maximum strength of each user and systematically manage exercise effects and exercise plans by presenting exercise targets to the user to perform repetitive exercises in accordance with the measured maximum strength. The purpose is to provide a personalized muscle strength measurement device and a strength exercise method using the same.

A personalized muscle strength measuring device according to an embodiment of the present invention for achieving the above object includes a handle that the user can hold with one hand or both hands; a connection strip portion having a predetermined elastic force connected to one side of the handle portion; a measuring unit connected to the other side of the connection strip unit and measuring an external force pulled by the connection strip unit; and a fixing strip part connected to the other side of the measuring part and capable of being fixed to a part of the user's body or an object, wherein the measuring part adjusts the maximum value of the force for pulling the connecting strip part by the handle part to a constant level. Measurements can be made multiple times over a time period.

In this case, the measuring unit may measure the maximum value of the pulling force by correcting the predetermined elastic force of the connecting strip portion and the force pulled by the fixing strip portion.

Meanwhile, the personalized muscle strength measurement device may further include a calculation unit that receives the maximum value and measurement time measured by the measurement unit and calculates the user's 1 RM (1 Repetition Maximum).

In this case, the calculation unit may predict new 1RM data based on the user's past 1RM data using a machine learning model.

In this case, the calculation unit may visually provide the predicted new 1RM data to the user and establish the new 1RM data by reflecting it in the user's exercise plan.

In this case, if the measured muscle strength does not reach the reference value during the user's exercise performed according to the user's newly established exercise plan, the calculation unit may generate notification information notifying the user of information about 1RM not being reached. .

In a method according to another embodiment of the present invention, a handle portion that a user can hold with one hand or both hands, a connection strip portion having a predetermined elastic force connected to one side of the handle portion, and a connection strip portion connected to the other side of the connection strip portion and A measuring unit that measures the external force pulled by the connection strip unit, a fixed strip unit that is connected to the other side of the measuring unit and can be fixed to a part of the user's body or an object, and the maximum value measured by the measuring unit. A strength exercise method using a personalized muscle strength measuring device that includes a calculation unit that receives time and calculates the user's 1RM (1 Repetition Maximum), wherein the measuring unit is pulled by the predetermined elastic force of the connection strip unit and the fixing strip unit. measuring the maximum value of the pulling force by correcting the losing force; The calculation unit predicts a new 1RM according to a machine learning model using the user's past 1RM data, the maximum value of the newly measured force, and the measurement time; The calculation unit establishes a new exercise plan for the user according to the new 1RM; and providing, by the calculation unit, a new exercise plan to the user.

In this case, in the step of establishing the new exercise plan, the calculation unit may establish a new exercise plan by reflecting the predicted new 1RM data to the user's existing exercise plan.

In this case, in the step of providing the new exercise plan to the user, if the measured muscle strength during the user's exercise performed according to the user's newly established exercise plan does not reach the reference value, the calculation unit determines the 1RM not reached. A further step may be performed to generate notification information that notifies the user of information.

A storage medium for storing code for executing a method according to another embodiment of the present invention, comprising: a handle portion that a user can hold with one hand or both hands; a connection strip portion having a predetermined elastic force connected to one side of the handle portion; , a measuring part connected to the other side of the connection strip part to measure an external force pulled by the connection strip part, and a fixing strip part connected to the other side of the measuring part so that it can be fixed by hanging on a part of the user's body or a part of an object, and the The code for executing a strength exercise method using a personalized muscle strength measurement device including a calculation unit that receives the maximum value and measurement time measured by the measurement unit and calculates the user's 1RM (1 Repetition Maximum) is the measurement unit, the connection measuring the maximum value of the pulling force by correcting the predetermined elastic force of the strip portion and the force pulled by the fixed strip portion; The calculation unit predicts a new 1RM according to a machine learning model using the user's past 1RM data, the maximum value of the newly measured force, and the measurement time; The calculation unit establishes a new exercise plan for the user according to the new 1RM; And the calculation unit executes a step of providing a new exercise plan to the user.

According to various embodiments of the present invention, the maximum strength of each user can be precisely measured, and the exercise effect is improved by presenting an exercise target to the user to perform repetitive exercises according to the measured maximum strength,

In addition, it is effective in monitoring strength development by systematically establishing exercise plans according to the user's maximum strength.

1 is a diagram illustrating a personalized muscle strength measurement device according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating the internal structure of the measuring unit shown in FIG. 1 by way of example;
Figure 3 is a block diagram illustrating an operation unit of a personalized muscle strength measurement device according to an embodiment of the present invention;
4 is a timing diagram illustrating a personalized strength exercise method according to another embodiment of the present invention;
5 is a diagram illustrating an example of a personalized strength exercise method according to another embodiment of the present invention;
6 is a diagram illustrating another example of a personalized strength exercise method according to another embodiment of the present invention;
Figure 7 is a block diagram illustrating a method of operating a personalized muscle strength measurement device according to another embodiment of the present invention;
Figure 8 is a block diagram illustrating a procedure for updating a machine learning model in the block diagram shown in Figure 7, and
FIG. 9 is a block diagram exemplarily illustrating a procedure for establishing an exercise plan in the block diagram shown in FIG. 7.

Hereinafter, preferred embodiments of the present invention will be described with reference to separate drawings. The preferred embodiment described below is only one of various embodiments of the present invention, and a person skilled in the art may make various design changes within the scope of the technical idea of the present invention.

1 is a diagram illustrating a personalized muscle strength measuring device according to an embodiment of the present invention. Referring to FIG. 1, the personalized muscle strength measuring device 100 includes a handle portion 110, a connection strip portion 120, a measuring portion 130, and a fixing strip portion 140. Depending on the embodiment, the calculation unit 150 may be configured to be built into the measurement unit 130. Alternatively, the calculation unit 150 may be implemented by an application installed on the user terminal 200. Hereinafter, the description will focus on the calculation unit 150 implemented in the form of an execution application built into the control board 132 inside the measurement unit 130. In other words, it refers to an installation type application implementation method in which a computer executable code is pre-installed and executed on a storage medium provided in the control board 132 to perform the function of the operation unit 150.

The handle portion 110 is configured to allow the user to pull the connection strip portion 120. The handle portion 110 includes a grip member 111 where the fingers and the palm contact and a connection member 112 that is connected to both sides of the grip member 111 and secures the grip member 111 to the connection strip portion 120. It can be configured.

The connection strip portion 120 may be made of a string of elastic material. The connection strip part 120 has one side connected to the connection member 112 and detachably connected to the handle part 110, and the other side is detachably connected to the connection ring 135 of the measuring part 130. . The connection strip portion 120 has a predetermined elastic force. Here, the predetermined elastic force refers to the restoring force corresponding to the minimum tension required to vary the connection strip portion 120 in the longitudinal direction. That is, depending on the type of the connecting strip portion 120, the tension required to extend it to a predetermined length in the longitudinal direction may vary. Information on the type of the connection strip unit 120 and the elastic force required when extending it in the longitudinal direction may be separately stored in the storage member of the calculation unit 150. A detailed description of this is provided below with reference to separate drawings.

One side of the measuring unit 130 is connected to one end of the connecting strip unit 120, and the other side is connected to one end of the fixing strip unit 140. When the handle unit 110 is pulled by the user, the measuring unit 130 receives a pulling force transmitted to the measuring unit 130 through the connecting strip unit 120 and a fixed strip unit connected to the measuring unit 130 ( 140), a mechanical external force generated by the pulling force is applied, and this device converts this mechanical external force into an electrical signal to measure the user's pulling force. The measuring unit 130 may be designed to convert mechanical force into an electrical signal using a load cell. A more detailed structure will be described below with reference to separate drawings.

The fixing strip unit 140 performs the function of hanging and fixing a part of the user's body, another object, or a part of another exercise equipment. It is preferable that the fixing strip portion 140 is made of a material with low elasticity. Preferably, it may be made of synthetic resin, carbon, metal, or a combination thereof.

FIG. 2 is a diagram illustrating the internal structure of the measuring unit shown in FIG. 1 by way of example. Referring to FIG. 2, the measurement unit 130 includes a PCB board 131, a control board 132, an amplification module 133, a displacement module 134, a connection ring 135, and a communication module 136. . The PCB board 131 is a board for electrical connection to support the operation of the Zeo board 132, the amplification module 133, and the communication module 136. The control board 132 controls the overall operation of the amplification module 133, displacement module 134, and communication module 136. The control board 132 is equipped with a storage module (not shown), calculates 1RM (One Repetition Maximum) using a pre-installed application, and operates a calculation unit 150 that establishes an exercise plan using the calculated 1RM and existing exercise data. ) can also function as. This control board 132 can load a machine learning model using an edge computing method and predict 1RM based on the loaded machine learning algorithm. The amplification module 133 performs the function of amplifying a signal and converting the mechanical signal into an electrical signal in order to convert the mechanical external force into an electrical signal by the displacement module 134. One side of the connection ring 135 is connected to one side of the displacement module 134, and the other side is connected to one side of the connection strip portion 120. When the connection strip part 120 is pulled by the handle part 110, the connection ring 135 is also pulled, and a mechanical external force acts on the displacement module 134. The mechanical external force acting on the link 135 is converted into a displacement signal in the displacement module 134 and into an electrical signal in the amplification module 133. The communication module 136 converts the electrical signal converted in the amplification module 133 into a transmission packet for transmission by wireless communication and transmits it to the user terminal 200 or the service server 300. Here, the communication module 136 is preferably implemented as a short-range wireless communication module that operates with low power. For long-distance transmission, long-distance communication can be performed through a user terminal 200 located nearby. Additionally, the communication module 136 may receive a pre-trained machine learning model from the user terminal 200 and/or the service server 300.

Figure 3 is a block diagram illustrating an operation unit of a personalized muscle strength measuring device according to an embodiment of the present invention. Referring to FIG. 3, the calculation unit 150 may be pre-installed and executed on the control board 132 of the measurement unit 130 in a computer-executable code format. The calculation unit 150 includes a maximum strength calculation module 151, a past maximum strength database 152, a machine learning module 153, and an exercise plan establishment module 154.

The maximum strength calculation module 151 calculates 1RM (One Repetition Maximum) using the strength information and number of repetitions of multiple repetitions input by the user. That is, after the user requests maximum strength measurement, if the user inputs strength multiple times, 1RM is calculated using the number of inputs and maximum strength.

The past maximum strength database 152 refers to a database that stores information about 1RM previously calculated by the user. In other words, it means the user's 1RM database stored until the user makes a request to measure a new 1RM. In the case of the present invention, the connection strip portion 120 can be replaced, so the elastic force of the connection strip portion 120 can be changed in various ways. At this time, if information about the connection strip unit 120 is input into the user terminal 200, the predetermined elastic force of the connection strip unit 120 can be known. If the user wants to measure 1RM anew by replacing the connection strip unit 120, the user can measure the measurement unit 130 according to the characteristics of the connection strip unit 120 by calibrating the measurement unit 130 based on the elastic force of the connection strip unit 120. You can measure your 1RM even if you are not aware of how much you are increasing it.

The machine learning module 153 is a pre-trained machine learning model. As input values, the user's plural strength information, number of repetitions, and information about the connection strip unit 120 are used, and as output values, the user's 1RM predicted value can be calculated. . Here, various models such as support vector machine, logistic regression model, decision tree model, random forest model, and artificial neural network model can be applied as the machine learning model. When applying an artificial neural network model, it is desirable to apply a RNN model series capable of time series prediction. However, when predicting a new 1RM using the user's multiple strength information and past 1RM information, an ensemble model that combines a decision tree model and a random forest model can be constructed.

The machine learning module 153 is not a model that is directly trained using training data from the control board 132, but is a model that is used by loading a learning model previously learned in the user terminal 200 and/or service server 300. am. Therefore, in the case of the present invention, it has the advantage of being able to calculate a more accurate 1RM prediction value by predicting the user's 1RM using the machine learning model 153 in the control board 132, and at the same time, a separate device for learning the machine learning model. It has the advantage that resource consumption is not large because it does not require resource consumption.

When the exercise plan establishment module 154 calculates the new 1RM, it evaluates the user's strength exercise based on the calculated 1RM, and if it falls below the standard value (new 1RM), provides feedback to the user to improve the exercise method. It is delivered as a notification, and if the standard value is exceeded, feedback to measure the new 1RM is delivered to the user as a notification. Detailed information about this is explained with reference to separate drawings.

Figure 4 is a timing diagram illustrating a personalized strength exercise method according to another embodiment of the present invention. Referring to FIG. 4, the user may transmit a request for muscle strength measurement to the muscle strength measurement device 100 through the user terminal 200 (S401). When the user uses the muscle strength measuring device 100 for the first time, the muscle strength measuring device 100 may transmit a user information request to the user terminal 200 (S402). According to the user information request, the user may transmit the user information to the muscle strength measuring device 100 through the user terminal 200 (S403). The muscle strength measuring device 100 analyzes the received user information and identifies the user (S404). The user may perform an action of inputting the user's muscle strength to the muscle strength measurement device 100 through the user terminal 200 (S405). For example, when the user pulls the handle portion 110 and the displacement module 134 by pulling the connection ring 135 connected to the connection strip portion 120, the mechanical signal is converted into an electrical signal by the amplification module 133. As it is converted, user muscle strength information is input. The user muscle strength information input in this way may be transmitted from the muscle strength measurement device 100 to the service server 300 (S406). Additionally, the muscle strength measuring device 100 may analyze the user's muscle strength information and calculate 1RM according to the muscle strength information (S407). The muscle strength measuring device 100 may request additional user strength input to the user terminal 200 until the conditions for calculating 1RM are met (S408). When the user receives a request to add user strength input through the user terminal 200, the user pulls the handle part 110 and repeatedly inputs the user strength information (S409). The muscle strength measuring device 100 may transmit the repeatedly input user muscle strength information to the service server 300 (S410). The service server 300 trains the existing ML model into a new ML model using the user's muscle strength information (S411). This ML model learning can proceed at a certain time period, and ML model learning is performed when certain data is accumulated after receiving user muscle strength information. The muscle strength measuring device 100 analyzes the user muscle strength information and calculates 1RM (S412). The service server 300 may update the ML model at a certain time period (S413). The service server 300 transmits the updated new ML model to the user terminal 200 (S414). The user terminal 200 updates the ML model by transmitting the ML model, which is updated at a constant time period from the service server 300, to the muscle strength measurement device 100 at a constant period (S415). The muscle strength measuring device 100 predicts and generates 1RM using an already loaded ML model (S416). When a new exercise activity is input to the muscle strength measurement device 100, user-customized exercise plan information is provided to the user terminal 200 (S417) or the service server 300 establishes a user-customized exercise plan and new exercise plan information. Can be provided to the user terminal 200 (S418).

Figure 5 is a diagram illustrating an example of a personalized strength exercise method according to another embodiment of the present invention. Referring to Figure 5(a), the user selects the color and material of the connection strip section 120 connected to the muscle strength measuring device 100 through the connection strip section setting screen displayed on the display 210 of the user terminal 200. The elastic force of the corresponding connection strip portion 120 can be set in advance by inputting information such as length, manufacturer, etc. In addition, referring to FIG. 5(b), the user inputs the user's maximum strength, number of repetitions, exercise time, and total calorie information through the exercise intensity setting screen displayed on the display 210 of the user terminal 200. Basic data for the user's 1RM can be set in advance.

Figure 6 is a diagram illustrating another example of a personalized strength exercise method according to another embodiment of the present invention. Referring to Figure 6(a), when the user's 1RM set in Figure 5(b) is calculated as 10.0KG, the corresponding 1RM (10KG) is set as the target value for notification settings, and after the user requests muscle strength measurement , the user pulls the handle unit 110 and the user's muscle strength information can be measured by the measuring unit 130. For example, if 9.0KG is measured, the value is lower than the preset notification setting value, so as shown in FIG. 6(b), a pop-up message (Pop_1) is displayed (210) informing the user that he or she must pull harder to achieve an exercise effect. ) is displayed. In Figure 6(c), when the user pulls the handle 110 and the measurement unit 130 measures 11KG, it can be confirmed that the weight exceeds the 10.0KG set in the notification setting. In FIG. 6(d), the muscle strength measurement device 100 displays a pop-up message (Pop_2) on the display 210 of the user terminal 200 to guide the user to measure the user's 1RM again since the user's record has been updated.

Figure 7 is a block diagram illustrating a method of operating a personalized muscle strength measurement device according to another embodiment of the present invention. Referring to FIG. 7, the muscle strength measuring device 100 performs two-way communication with the user terminal 200 using a short-range, low-power communication method. Additionally, the muscle strength measuring device 100 can also perform two-way communication with a remote service server 300 through the network (N). The muscle strength measuring device 100 may measure the user's muscle strength information at regular time periods through the network N and transmit it to the service server 300. Alternatively, the muscle strength measurement device 100 may transmit user muscle strength information measured using a low-power communication method to the user terminal 200. The user terminal 200 may store the received user strength information in local storage as a user strength information database. Alternatively, the user terminal 200 may transmit the received user strength information along with the user information to the service server 300 connected through the network (N). The service server 300 may generate an ML model for predicting 1RM by training an ML model for the user using user information and user muscle strength information. The service server 300 may transmit the ML model created in this way to the user terminal 200 through the network (N). The user terminal 200 may load the ML model into the muscle strength measuring device 100 to configure a machine learning module for predicting 1RM.

FIG. 8 is a block diagram exemplarily illustrating a procedure for updating a machine learning model in the block diagram shown in FIG. 7. Referring to FIG. 8, the muscle strength measuring device 100 may non-temporarily store the machine learning module 153 of the calculation unit 150. The muscle strength measuring device 100 may measure data for updating the machine learning module 153 of the calculation unit 150 and transmit new data to the user terminal 200. The user terminal 200 may transmit new data to the service server 300 through the network (N). The service server 300 can learn an existing ML model using new data and update it into a new ML model. The service server 300 transmits the new ML model to the user terminal 200 through the network (N). The user terminal 200 may update the machine learning module 153 of the association unit 150 by transmitting the new ML model to the muscle strength measuring device 100 through a low-power local area network.

FIG. 9 is a block diagram exemplarily illustrating a procedure for establishing an exercise plan in the block diagram shown in FIG. 7. Referring to FIG. 9 , when new exercise activity is recorded in the muscle strength measuring device 100, the new data is transmitted to the user terminal 200 for comparison with existing exercise plan information. The user terminal 200 transmits new data to the service server 300 through the network (N). The service server 300 searches previously stored exercise plan information according to new data and transmits the retrieved exercise plan information to the user terminal 200 through the network N. The user terminal 200 compares the received exercise plan information with the new data information to determine whether the exercise activity is according to the exercise plan, and, if appropriate, provides feedback information indicating that the exercise effect is positive to the user. If the exercise activity is not appropriate, the user terminal 200 provides feedback information to the user informing the user that the exercise activity is not appropriate.

Meanwhile, just because all the components constituting the embodiment of the present invention are described as being combined or operated in combination, the present invention is not necessarily limited to this embodiment. That is, as long as it is within the scope of the purpose of the present invention, all of the components may be operated by selectively combining one or more of them. In addition, although all of the components may be implemented as a single independent hardware, a program module in which some or all of the components are selectively combined to perform some or all of the combined functions in one or more pieces of hardware. It may also be implemented as a computer program having. The codes and code segments that make up the computer program can be easily deduced by a person skilled in the art of the present invention. Such computer programs can be stored in non-transitory computer readable media and read and executed by a computer, thereby implementing embodiments of the present invention.

Here, a non-transitory computer-readable recording medium refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short period of time, such as registers, caches, and memories. do. Specifically, the above-described programs may be stored and provided on non-transitory readable recording media such as CD, DVD, hard disk, Blu-ray disk, USB, memory card, ROM, etc.

In the above, preferred embodiments of the present invention have been shown and described, but the present invention is not limited to the specific embodiments described above, and may be used in the technical field to which the invention pertains without departing from the gist of the invention as claimed in the claims. Of course, various modifications can be made by those skilled in the art, and these modifications should not be understood individually from the technical idea or perspective of the present invention.

100: Personalized muscle strength measurement device
110: handle part
120: Connection strip part
130: measuring unit
140: Fixed strip part
150: calculation unit
200: user terminal
300: service server

Claims (10)

In a personalized muscle strength measuring device,
A handle that the user can hold with one or both hands;
a connection strip portion having a predetermined elastic force connected to one side of the handle portion;
a measuring unit connected to the other side of the connection strip unit and measuring an external force pulled by the connection strip unit; and
A fixing strip part is connected to the other side of the measuring unit and can be fixed to a part of the user's body or an object,
The measuring unit is characterized in that the maximum value of the force pulling the connection strip unit by the handle unit is measured multiple times at a certain time period,
Personalized muscle strength measurement device.
According to claim 1,
The measuring unit measures the maximum value of the pulling force by correcting the predetermined elastic force of the connecting strip portion and the force pulled by the fixing strip portion,
Personalized muscle strength measurement device.
According to claim 1,
Characterized in that it further comprises a calculation unit that receives the maximum value and measurement time measured by the measurement unit and calculates the user's 1RM (1 Repetition Maximum).
Personalized strength measurement device.
According to clause 3,
The calculation unit predicts new 1RM data based on the user's past 1RM data using a machine learning model,
Personalized strength measurement device.
According to clause 4,
The calculation unit visually provides the predicted new 1RM data to the user and establishes the new 1RM data by reflecting it in the user's exercise plan.
Personalized strength measurement device.
According to clause 5,
The calculation unit is characterized in that, when the measured muscle strength does not reach the reference value during the user's exercise performed according to the user's newly established exercise plan, it generates notification information to inform the user of information regarding 1RM not reached,
Personalized strength measurement device.
A measurement that measures an external force pulled by a handle portion that a user can hold with one hand or both hands, a connection strip portion having a predetermined elastic force connected to one side of the handle portion, and a connection strip portion connected to the other side of the connection strip portion. A fixed strip unit that is connected to the other side of the measuring unit and can be fixed to a part of the user's body or an object, and receives the maximum value and measurement time measured by the measuring unit to determine the user's 1RM (1 Repetition Maximum) In a strength exercise method using a personalized strength measurement device including a calculation unit that calculates,
The measuring unit measures a maximum value of the pulling force by correcting a predetermined elastic force of the connecting strip portion and a force pulled by the fixing strip portion;
The calculation unit predicts a new 1RM according to a machine learning model using the user's past 1RM data, the maximum value of the newly measured force, and the measurement time;
The calculation unit establishes a new exercise plan for the user according to the new 1RM; and
The calculation unit includes providing a new exercise plan to the user.
Strength training method using a personalized strength measurement device.
According to clause 7,
In the step of establishing the new exercise plan, the calculation unit establishes a new exercise plan by reflecting the predicted new 1RM data to the user's existing exercise plan.
Strength training method using a personalized strength measurement device.
According to clause 8,
In the step of providing the new exercise plan to the user, if the measured muscle strength does not reach the reference value during the user's exercise performed according to the user's newly established exercise plan, the calculation unit provides information about 1RM not reached to the user. Characterized by further performing the step of generating notification information to notify,
Strength training method using a personalized strength measurement device.
A measurement that measures an external force pulled by a handle portion that a user can hold with one hand or both hands, a connection strip portion having a predetermined elastic force connected to one side of the handle portion, and a connection strip portion connected to the other side of the connection strip portion. A fixed strip unit that is connected to the other side of the measuring unit and can be fixed to a part of the user's body or an object, and receives the maximum value and measurement time measured by the measuring unit to determine the user's 1RM (1 Repetition Maximum) In the strength exercise method using a personalized muscle strength measuring device including a calculation unit that calculates, the measuring unit corrects the predetermined elastic force of the connection strip portion and the force pulled by the fixing strip portion to obtain a maximum value of the pulling force. measuring; The calculation unit predicts a new 1RM according to a machine learning model using the user's past 1RM data, the maximum value of the newly measured force, and the measurement time; The calculation unit establishes a new exercise plan for the user according to the new 1RM; and providing, by the operation unit, a new exercise plan to the user.