CN111032163B

CN111032163B - Weight tracking device and method

Info

Publication number: CN111032163B
Application number: CN201980003825.XA
Authority: CN
Inventors: 李康圭; 金素情; 姜旻紀; 柳成澔
Original assignee: Irvine Music Co ltd
Current assignee: Irvine Music Co ltd
Priority date: 2018-06-28
Filing date: 2019-06-28
Publication date: 2021-05-28
Anticipated expiration: 2039-06-28
Also published as: KR102053578B1; KR102053576B1; WO2020005036A1; KR20200002017A; CN111032163A; CN111032164B; CN111032164A

Abstract

A weight tracking device that, in a weight lifting machine including a plurality of weight plates to which NFC tags are respectively attached, is inserted to a pin hole formed in any one of the plurality of weight plates or to between vertically adjacent weight plates of the plurality of weight plates to set a weight of a weight plate and track the weight of the weight plate, the weight tracking device comprising: a housing; a pin protruding from the housing and inserted into the pin hole or between the vertically adjacent weight plates; an NFC reading module which is disposed inside the housing and which detects weight data indicating the weight of the weight plate set by the pin by reading the NFC tag detected when the pin is inserted; a memory configured inside the housing; and a processor disposed inside the housing, the processor receiving the weight data detected by the NFC reading module from the NFC reading module and storing the weight data in the memory.

Description

Weight tracking device and method

Technical Field

The present invention relates to a weight tracking apparatus and method, and more particularly, to a weight tracking apparatus which reads an NFC tag attached to a weight plate of a weight machine by having an NFC reading module and tracks the weight of a weight plate that a user needs to lift so that the tracked weight information can be applied to various purposes.

Background

The Fitness technology (Fitness Tech) market, which combines sports with IT technology, is becoming a global trend.

For aerobic sports, such as Running (Running) or Cycling (Cycling), a smartphone or a smartwatch is utilized to automatically track the movement details of movement routes, movement speeds, movement times, etc., and to provide a variety of personalized fitness based on the collected data.

However, in the case of Weight Training (Weight Training), there is no system or service that can automatically track the movement details thereof. In the case of weight training, the details of exercise such as exercising which part of the body is exercised by using a certain exercise machine, several times of exercise with a weight of several kilograms, several groups of exercise, etc. become important factors, and these factors cannot be automatically tracked in the conventional weight training system or service (see korean laid-open patent No. 10-2011 0066432).

Hereinafter, a background art for explaining the weight tracking device according to the present invention will be described.

Fig. 1 is a view showing a conventional weight lifting machine and a weight setting pin used for the same. Fig. 2 is a diagram showing various weight setting pins used in a conventional weight lifting machine.

Referring to fig. 1, a Weight Lifting Machine (Weight Lifting Machine)70 is an exercise Machine that enhances muscular strength by a user Lifting a Weight plate 20 having a prescribed Weight in a vertical direction.

A plurality of

weight plates

20, 22 may be provided in a stacked manner in the weight lifting machine 70. Each

weight plate

20, 22 may have a specified weight (e.g., 5 kg). According to embodiments, the respective weight plates may have the same weight or may have different weights from each other.

Weight marker stickers

33, 34 may be attached to each

weight plate

20, 22.

For example, the weight label 33 on which 5k g is recorded may be attached to the uppermost weight plate 20 among the overlapped weight plates, and the weight label 34 on which 10kg of two weights of the weight plates is recorded may be attached to the weight plate 22 immediately below. That is, a weight label paper in which the cumulative weight from the top is recorded may be attached to any of the weight plates.

The user can set the number of

weight plates

20, 22 or the weight of weight plates (weight stack) he or she needs to lift using the weight setting pin (weight selector pin) 15. The weight plate 30 means a block body of a prescribed number of weight plates set by the weight setting pin 15.

Specifically, the weight setting pin 15 is inserted between the vertically adjacent weight plates of the plurality of

weight plates

20, 22, so that the number of

weight plates

20, 22 or the weight of the weight plate, which the user needs to lift, can be set. Alternatively, the weight setting pin is inserted into a pin hole formed in any one of the plurality of weight plates, so that the number of weight plates or the weight of the weight plate, which the user needs to lift, can be set.

Referring to fig. 2, the

weight setting pins

35 and 37 for setting the weight of the weight plate 30 may have various forms.

The weight setting Pin may be constituted by parts of a Head (Head) and a Pin (Pin). The head (He ad Part) and the Pin (Pin Part) may have various forms. For example, the weight setting pin 35 according to an embodiment may be formed of one rod-shaped pin and a head portion at an end of the pin (see fig. 2 (a)), and the weight setting pin 37 according to another embodiment may have a form of two flat pins (see fig. 2 (b)).

According to the embodiment, the weight setting pin 35 having one rod shape may set the weight of the weight plate by being inserted into the pin hole formed in the weight plate, and the weight setting pin 37 having two flat pins may set the weight of the weight plate 30 by being inserted between the upper and lower

adjacent weight plates

20, 22.

Disclosure of Invention

Technical scheme

In a weight tracking apparatus according to an embodiment of the present invention for solving the above-mentioned problems, in a weight lifting machine including a plurality of weight plates to which NFC tags are respectively attached, a weight piece weight is set by inserting into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent ones of the plurality of weight plates to track the weight piece weight, the weight tracking apparatus including: a housing; a pin protruding from the housing and inserted into the pin hole or between the vertically adjacent weight plates; an NFC reading module which is disposed inside the housing and which detects weight data indicating the weight of the weight plate set by the pin by reading the NFC tag detected when the pin is inserted; a memory configured inside the housing; and a processor disposed inside the housing, the processor receiving the weight data detected by the NFC reading module from the NFC reading module and storing the weight data in the memory.

In a weight tracking apparatus according to another embodiment of the present invention for solving the technical problem, in a weight lifting machine including a plurality of weight plates to which NFC tags are respectively attached, a weight setting pin is inserted into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent weight plates of the plurality of weight plates to track a set weight of a weight piece, the weight tracking apparatus including: a housing detachably mounted in the weight setting pin; an N FC reading module which is disposed inside the housing and detects weight data indicating the weight of the weight stack set by the weight setting pin by reading the NFC tag detected when the weight setting pin is inserted; a memory configured inside the housing; and a processor disposed inside the housing, the processor receiving the weight data detected by the NFC reading module from the NFC reading module and storing the weight data in the memory.

In terms of a weight tracking method according to an embodiment of the present invention for solving the technical problem, in a weight lifting machine including a plurality of weight plates to which NFC tags are respectively attached, a weight of a weight plate formed by the weight plates lifted by a user is tracked using a weight tracking device, the weight tracking method includes: inserting a pin into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent ones of the plurality of weight plates; a step in which the NFC read module detects weight data indicating the weight of the weight stack set by the pin by reading the NFC tag detected when the pin is inserted; a step in which the processor receives weight data detected by the NFC reading module from the NFC reading module; and a step in which the processor stores the weight data in the memory.

In terms of a weight tracking method according to another embodiment of the present invention for solving the technical problem, in a weight lifting machine including a plurality of weight plates to which NFC tags are respectively attached, a weight of a weight plate formed by the weight plates lifted by a user is tracked using a weight tracking device, the weight tracking method includes: inserting a weight setting pin into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent ones of the plurality of weight plates; a step of mounting the weight tracking device on the weight setting pin; a step in which the NFC read module detects weight data indicating the weight of the weight stack set by the weight setting pin by reading the detected NFC tag; a step of receiving, by the processor, weight data detected by the NFC reading module from the NFC reading module; and a step in which the processor stores the weight data in the memory.

Advantageous effects

According to the present invention, the exact weight of the weight plate that the user utilizes in weight training can be known.

Drawings

Fig. 1 is a view showing a conventional weight lifting machine and a weight setting pin used for the same.

Fig. 2 is a diagram showing various weight setting pins used in a conventional weight lifting machine.

Fig. 3 and 4 are diagrams illustrating a state in which a weight tracking apparatus according to an embodiment of the present invention is applied to a weight lifting machine.

Fig. 5 is a perspective view of a weight tracking device according to an embodiment of the invention.

Fig. 6 is a structural diagram of a weight tracking device according to an embodiment of the invention.

Fig. 7 is a diagram illustrating a state in which an NFC reading module disposed in a weight tracking device communicates with a plurality of NFC tags according to an embodiment of the present invention.

Fig. 8 is a diagram illustrating a setup position of an NFC reading module in a weight tracking device according to an embodiment of the present invention.

Fig. 9 is a view showing a setting position of a metal plate in the weight tracking apparatus according to an embodiment of the present invention.

Fig. 10 is a diagram illustrating a process of deriving weight data of a weight stack actually lifted by a user from weight data read by an NFC tag while an NF C reading module provided in a weight tracking apparatus according to an embodiment of the present invention alternately maintains a standby mode and an active mode.

Fig. 11 is a diagram showing the arrangement position of an acceleration sensor in the weight tracking apparatus according to an embodiment of the present invention.

Fig. 12 is a diagram illustrating a method of an NF C reading module provided in the weight tracking apparatus according to an embodiment of the present invention communicating with one NFC tag using an acceleration sensor.

Fig. 13 and 14 are diagrams illustrating a signal processing method performed by a processor provided in the weight tracking device according to an embodiment of the present invention.

Fig. 15 and 16 are diagrams illustrating a first machine learning method performed by a processor provided in the weight tracking device according to an embodiment of the present invention.

Fig. 17 and 18 are diagrams illustrating a second machine learning method performed by a processor provided in the weight tracking device according to an embodiment of the present invention.

Fig. 19 is a diagram illustrating position data of the weight tracking apparatus finally generated by a processor provided in the weight tracking apparatus according to an embodiment of the present invention using acceleration data that has been input.

Fig. 20 is a perspective view of a weight tracking device according to another embodiment of the present invention.

Fig. 21 is a view showing a state in which a weight tracking device according to another embodiment of the present invention is mounted in a weight setting pin.

FIG. 22 is a flow chart illustrating a weight tracking method according to an embodiment of the invention.

Fig. 23 is a flowchart illustrating a weight tracking method according to another embodiment of the present invention.

Detailed Description

The advantages and features of the present invention and the methods of accomplishing the same will become more apparent by reference to the several embodiments that are described in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various forms different from each other, and the embodiments are provided only for the purpose of making the disclosure of the present invention complete and informing a person skilled in the art of the present invention of the scope of the present invention, and the present invention is defined only by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In this specification, the singular forms also include the plural forms unless the context clearly dictates otherwise. The use of "comprising" and/or "including" herein is meant to specify the presence of stated features, steps or acts, but does not exclude the presence or addition of one or more other features, steps or acts.

Referring to fig. 3 to 6, a weight tracking apparatus according to an embodiment of the present invention is described. Fig. 3 and 4 are diagrams illustrating a state in which a weight tracking apparatus according to an embodiment of the present invention is applied to a weight lifting machine. Fig. 5 is a perspective view of a weight tracking device according to an embodiment of the invention. Fig. 6 is a structural diagram of a weight tracking device according to an embodiment of the invention.

Referring to fig. 3 to 6, the weight tracking device 60 according to an embodiment of the present invention may be a device for tracking weight data of the weight plate 30 by reading the NFC tag 40 attached to the

weight plates

20, 25 of the weight lifting machine 70.

A plurality of

weight plates

20, 25 may be provided in the weight machine 70, and an NFC tag 40 may be attached to each

weight plate

20, 25 provided. At this time, when the Pin (Pin) of the weight setting device or the weight setting Pin combined with the weight setting device is inserted between the Pin hole or the vertically adjacent weight plates, the NFC tag can be attached so as to be located in a region readable by the NFC reading module in the weight setting device. According to an embodiment, the NFC tag may be attached to a position where the NFC reading module is superimposed with the NFC tag when inserted.

The NFC tag 40 may store the total weight data of the

weight plates

20, 25 to which it is attached and the

weight plates

20, 25 superimposed on

such weight plates

20, 25. That is, the NFC tag 40 may have weight data of the weight plate 30 when the weight plate to which the NFC tag 40 is set becomes the weight plate located at the bottommost portion. In other words, the NFC tag 40 attached to the top-to-nth weight plate may take the sum of the weights of all weight plates from the top to the first weight plate through to the nth weight plate as weight data.

For example, referring to fig. 3, when each of the plurality of weight plates has a weight of 5kg, (i) the NFC tag 40 attached to the weight plate located at the topmost position may have weight data of 5kg, (i i) the NFC tag 40 attached to the weight plate located from the top to the second may have weight data of 10kg, which is the sum of the weights of the first weight plate and the second weight plate.

The NFC tag 40 may be in the form of a sticker that can provide the weight data to an external device, but is not limited thereto, and may be applied to various forms as long as it can be attached to the

weight plates

20 and 25.

Again, the weight tracking device 60 according to an embodiment may include a housing 125, a pin 10, an NFC reading module 80, a processor 100, a memory 110, and a communication module 120.

The housing 125 is in the shape of the weight tracking device 60 and may have room for various structures of the weight tracking device 60 to be built in.

The pin 10 may be a member protruding from the housing 125 and having a prescribed length. As described above, the pin 10 is configured to form the weight plate 30 in a form in which the

weight plates

20 and 25 are stacked, and may have various forms.

According to an embodiment, as shown in fig. 3, the pin may be formed of two flat plates, and after the user inserts the pin 10 between the vertically

adjacent weight plates

20 and 22 among the plurality of weight plates, the

weight plates

20 and 22, i.e., the weight plate 30, stacked on the upper portion of the inserted pin 10 may be lifted.

Alternatively, as shown in fig. 4, the pin may have a rod shape, and after the user inserts the pin into the pin hole 45 formed in any one of the weight plates 25 among the plurality of weight plates, the weight plate 25 forming the pin hole 45 and the weight plate, i.e., the weight plate, stacked on the upper portion of the weight plate 25 forming the pin hole 45 may be lifted up.

That is, the pin 10 may be inserted between the vertically

adjacent weight plates

20, 22 of the plurality of weight plates 20, or may be inserted into the pin hole 45 formed in any one of the weight plates 25 of the plurality of weight plates 25.

In this manner, the weight plate 30 can be formed by inserting the pin 10 into the pin hole 45 or between the vertically

adjacent weight plates

20 and 22.

The NFC reading module 80 is disposed inside the housing 125, and is a module that detects weight data indicating the weight of the weight plate 30 by reading the NFC tag 40.

Specifically, when the pin 10 is inserted, the NFC reading module 80 approaches the NFC tag 40 attached to the

weight plates

20, 25, and detects weight data indicating the weight of the weight plate 30 set by the pin 10 by reading the NFC tag 40 detected during the approach or after the completion of the insertion.

The processor 100 is disposed inside the housing 125, and may receive weight data detected by the NFC reading module 80 from the NFC reading module 80. That is, the NFC reading module 80 may transmit the identified weight data to the processor 100.

Additionally, the interior of the housing 125 may configure the memory 110, and the processor 100 may store weight data in the memory 110.

Alternatively, the memory 110 may be located inside or outside the processor 100 and may be connected to the processor 100 in a variety of well-known ways. Such a memory 110 is a large-capacity storage medium such as a semiconductor device or a hard disk known as a RAM, a ROM, an EEPROM, or the like, which can record and erase data, and is a generic name of a device storing information regardless of the type of the device, and does not refer to a specific memory 110 device.

Also, the inside of the housing 125 may further include a communication module 120 for communicating with an external device. The processor 100 may transmit the weight data to an external device by controlling the communication module 120. Here, the external device may include a user's mobile phone, a management server, other terminal equipment, and the like.

That is, the weight data may be provided to the outside under the control of the processor 100, and the provided weight data is processed to provide useful information to the user.

Hereinafter, in order to facilitate understanding of the invention, a description will be given of a weight lifting machine of a type in which a pin is inserted between upper and lower weight plates, from among the above-described types of weight lifting machines (see fig. 3).

Referring to fig. 7 to 10, there is seen a method of acquiring weight data of the weight plate 30 set by the weight setting pin during communication with the NFC tag 40 by the NFC reading module 80.

Fig. 7 is a diagram illustrating a state in which an NFC reading module provided in the weight tracking apparatus according to an embodiment of the present invention communicates with a plurality of NFC tags. Fig. 8 is a diagram illustrating a setup position of an NFC reading module in a weight tracking device according to an embodiment of the present invention. Fig. 9 is a view showing a setting position of a metal plate in the weight tracking apparatus according to an embodiment of the present invention.

Fig. 10 is a diagram illustrating a process of deriving weight data of a weight stack set by a weight setting pin from weight data read by an NFC tag while an NF C reading module provided in a weight tracking apparatus according to an embodiment of the present invention alternately maintains a standby mode and an active mode.

First, referring to fig. 7, NFC tags 40 and 43 may be attached to a plurality of weight plates 20, respectively, and during the insertion of the weight tracking device 60, it may occur that the NFC reading module 80 communicates with other NFC tags 43 in addition to the NFC tag 40 closest to itself (i.e., the NFC tag 40 of the weight plate 20 located directly above the inserted weight tracking device 60).

In this case, the weight recognition by the NFC read module 80 cannot be performed normally or erroneous weight data is recognized even if the weight recognition is performed, and thus the accuracy and reliability of the weight recognition are lowered.

In consideration of the above-described problems, the NFC read module 80 may be disposed in the housing 125 so as to be in contact with the inner side 155 of the front surface 150 of the housing 125, the front surface 150 of the housing 125 facing the weight plate 30, with reference to fig. 8 and fig. 9 in a state of being viewed in the L direction in fig. 8.

NFC read module 80 communicates with NFC tag 40 of weight plate 20 and therefore needs to be disposed adjacent to NFC tag 40 as much as possible in housing 125. In this regard, the NF C reading module 80 can be disposed in the housing 125 in contact with the inner side 155 of the front face 150 of the housing 125, the front face 150 of the housing 125 facing the weight plate 30.

That is, among the plurality of structures configured in the housing 125, the NFC reading module 80 may be closest to the weight plate 30.

Also, according to the embodiment, the metal plate 140 may be attached to an upper portion of a portion of the inner side 155 of the front face 150 of the housing 125, which is in contact with the NFC reading module 80, so that the NFC reading module 80 communicates with only one NFC tag 40.

According to circumstances, in the inner side 155, the metal plate 140 may be further attached in all portions except a portion in contact with the NFC reading module 80. Alternatively, the metal plate 140 may be attached in a portion other than the position of the NF C tag as a target.

As such, the metal plate 140 is attached to the upper or strategic position of the NFC reading module 80, so that communication with other NFC tags 43 except the NFC tag 40 intended to communicate is blocked, and thus the NFC reading module 80 can recognize the exact weight of the weight plate 30.

According to another embodiment, referring to fig. 10, the NFC read module 80 may repeat the standby mode S and the active mode a. At this time, the NFC reading module 80 may determine the weight data with the highest frequency among the weight data read in the active mode a as the weight of the weight stack 30.

Specifically, in the process of the user moving the weight tracking device 60 toward the weight stack 30, the nfc reading module 80 is switched to the active mode a after being in the standby mode S for a prescribed time (e.g., 1 second), and is again switched to the active mode a after being in the standby mode S for a prescribed time, whereby the standby mode S and the active mode a can be repeated.

In this process, the NFC reading module 80 may identify the NFC tags 40, 43 different from each other in the active mode a to read and make more communication with the nearest NFC tag, and thus judge the weight data having the highest frequency among the read weight data as the weight of the weight stack 30 to be lifted.

For example, in the active mode a, when the NFC reading module 80 reads 5kg, 10kg, and 5kg as the weight data, the weight data having the highest frequency among the read weight data is 5kg, and thus the weight of the weight plate 30 that needs to be lifted is determined to be 5kg, and information that the weight of the weight plate 30 is 5kg may be transmitted to the processor 100 described later.

According to another embodiment, the range over which communications with NFC tag 40 may be made may be reduced by reducing the size of NFC tag 40 attached to weight plate 20 to a specified size (e.g., 10-15 mm in width and length) or less.

In this case, the NFC reading module 80 needs to be close to the NFC tag 40 to read the NFC tag 40, and after the weight tracking device 60 is inserted, the NFC reading module 80 can recognize only the closest NFC tag 40.

Additionally, referring to fig. 6 and 11, the weight tracking device 60 according to an embodiment of the invention may further include an acceleration sensor 90. Fig. 11 is a diagram showing the arrangement position of an acceleration sensor in the weight tracking apparatus according to an embodiment of the present invention.

The acceleration sensor 90 is disposed inside the housing 125, and may be a sensor for sensing acceleration data representing acceleration values of the weight tracking device 60. The acceleration sensor 90 according to the embodiment may be a three-axis acceleration sensor.

That is, the user lifts up or down the weight plate 30, and in the process, the weight plate 30 also moves up and down, and the weight tracking device 60 that moves integrally with the weight plate 30 also moves up and down.

In this process, the acceleration sensor 90 may sense an acceleration value or change in acceleration of the weight tracking device 60.

Processor 100 may then receive acceleration data from acceleration sensor 90 sensed by acceleration sensor 90 and perform signal processing on the received acceleration data to generate position data representing a change in position of weight tracking device 60.

Also, the processor 100 transmits the position data to an external device by controlling the communication module 120 and stores the position data in the memory 110.

As described above, the NFC reading module 80 may be disposed so as to be in contact with the inner side 155 of the front surface 150 of the housing 125, and the front surface 150 of the housing 125 may face the weight plate 30, and at this time, the acceleration sensor 90 may be located at a position immediately behind the NFC reading module 80 with reference to the front surface 150 of the housing 125 (see part (a) of fig. 11). The acceleration sensors 90 according to another embodiment may be located side by side above, below, or to the left and right of the NFC reading module 80 so as to be in contact with the inner side 155 of the front face 150 of the housing 125.

The acceleration sensor 90 according to another embodiment may be located at the middle of the width of the front face 150 of the casing 125 (refer to part (b) of fig. 11).

In this connection, the weight tracking device 60 may move up and down as the weight plate 30 moves up and down after the pin 10 is inserted between the vertically adjacent weight plates 20 among the plurality of weight plates 20.

At this time, the degree of vertical fluctuation of the acceleration sensor 90 increases as the acceleration sensor 90 moves away from the weight plate 30 with reference to the longitudinal direction of the weight tracking device 60. Therefore, the accuracy of the measured acceleration value may be reduced as the acceleration sensor 90 is away from the weight plate 30.

Further, with the width direction of the weight tracking device 60 as a reference, the degree of fluctuation of the acceleration sensor 90 in the up-down direction or the left-right direction increases as the acceleration sensor 90 moves away from the neutral position. Therefore, as the acceleration sensor 90 is away from the width neutral position, the accuracy of the measured acceleration value may decrease.

In view of these circumstances, the acceleration sensor 90 is located immediately behind the NFC read module 80 with reference to the front face 150 of the housing 125, and may be located in the middle of the width of the front face 150 of the housing 125.

Next, referring to fig. 12, a method is seen in which the NFC reading module 80 uses the acceleration sensor 90 to communicate only with the NFC tag 40 of the weight plate 20 located directly above the weight tracking device 60.

Referring to fig. 12, the NFC reading module 80 may be disabled from reading the NFC tag 40 during movement for insertion of the weight tracking device 60, and the NFC reading module 80 may be enabled to read the NFC tag 40 after the weight tracking device 60 is inserted.

In other words, upon completion of insertion of the weight tracking device 60, the NFC reading module 80 may switch to active mode a and the likelihood of communicating with the closest NFC tag 40 is high, at which point the closest NFC tag 40 may be the NFC tag 40 of the weight plate 20 located directly above the inserted weight tracking device 60.

Thus, the NFC reading module 80 can read the NFC tag 40 of the weight plate 20 directly above the inserted weight tracking device 60 and can achieve accurate weight data identification that the user needs to lift.

In connection with this, when looking at the manner in which the NFC reading module 80 is switched to the active mode a after the insertion of the weight tracking device 60 is completed, the NFC reading module 80 may be switched from the standby mode S to the active mode a to read the NFC tag 40 at the point in time when the acceleration value of the axis X parallel to the direction D in which the pin 10 is inserted becomes the preset reference value or less.

That is, when the acceleration value of the axis X parallel to the direction D in which the pin 10 is inserted is equal to or less than the preset reference value, it is considered that the weight tracking device 60 is completely inserted, and the NFC reading module 80 is shifted to the active mode a and can read the nearest NFC tag 40.

As another way, when the acceleration values of two or more axes among the three-axis acceleration values above the reference value fall below the reference value, NFC reading module 80 may switch from standby mode S to active mode a to read NFC tag 40.

Specifically, when the user moves the weight tracking device 60 in order to use the weight tracking device 60, the triaxial acceleration values change, and the triaxial acceleration values may become the reference values or more.

Then, when the insertion of the weight tracking device 60 is completed, the motion of the weight tracking device 60 is reduced, and the acceleration values of two or more axes out of the three-axis acceleration values may become the reference value or less. Accordingly, when the acceleration values of two or more axes of the three-axis acceleration values above the reference value fall below the reference value, it is considered that the weight tracking device 60 is completely inserted, and the NFC reading module 80 may be switched from the standby mode S to the active mode a to read the nearest NFC tag 40.

On the other hand, the reason why the time of completion of insertion of the weight tracking device 60 is selected as the case where the acceleration values of two or more axes are equal to or less than the reference value, rather than three axes, is that it is considered that the weight training may be performed to move the weight plate 30 up and down after a predetermined time has elapsed after the weight tracking device 60 is inserted, but if the weight training is performed to move the weight plate 30 up and down immediately after the weight tracking device 60 is inserted, the acceleration value of one axis (for example, Z axis) may become equal to or more than the reference value.

Next, referring to fig. 13 and 14, the signal processing method of the processor is examined. Fig. 13 and 14 are diagrams illustrating a signal processing method performed by a processor provided in the weight tracking device according to an embodiment of the present invention.

As described above, the processor 100 receives acceleration data sensed by the acceleration sensor 90 from the acceleration sensor 90, and performs signal processing on the received acceleration data to generate position data representing a change in position of the weight tracking device 60.

Also, the processor 100 may transmit the location data to an external device by controlling the communication module 120 or store the location data in the memory 110.

Referring to fig. 13 and 14, when looking at the signal processing manner of the processor 100, the processor 100 may apply filtering or integration operation to the sensed acceleration data for signal processing. The processor 100 according to an embodiment may generate purified acceleration data by filtering the acceleration data and then performing an integration operation on the purified acceleration data to generate position data.

As another example, the processor 100 receives acceleration data sensed by the acceleration sensor 90 from the acceleration sensor 90, and filters the received acceleration data to remove noise. Alternatively, the processor 100 may remove the effect due to the weight acceleration from the acceleration data.

The processor 100 may then derive velocity data by integrating the noise-removed acceleration data once.

The processor 100 applies filtering or integration to the velocity data to perform signal processing, and acquires position data from the velocity data by signal processing.

Hereinafter, referring to fig. 15 and 16, a manner in which the processor acquires the position data using machine Learning (machine e Learning) is examined. Fig. 15 and 16 are diagrams illustrating a first machine learning method performed by a processor provided in the weight tracking device according to an embodiment of the present invention.

Referring to fig. 15 and 16, in order to acquire the advanced position data through Machine Learning, the processor 100 according to an embodiment of the present invention may perform (i) a Learning step of Learning a pre-selected Machine Learning Model (Machine Learning Model) and (ii) an identification step of inputting the position data P subjected to signal processing to the learned Machine Learning Model to acquire the advanced position data P'.

Referring to FIG. 15, in the case of a learning step, the processor 100 may select any one of a plurality of machine learning models. The processor 100 according to the embodiment selects (i) one of a plurality of Neural Network models (Neural Network models) such as a Deep Neural Network (DNN), a Convolutional Neural Network (CNN), a Deep Neural Network (DNN), a Recurrent Neural Network (RNN), and (ii) sets a Hyper parameter (Hyper parameter) to the selected Neural Network Model, thereby selecting a machine learning Model to be learned.

When the machine learning model requiring learning is selected, the processor 100 inputs a previously prepared learning Data Set (Training Data Set) to the selected machine learning model to cause the selected machine learning model to learn. At this time, the learning data set may include (i) measured position data Q at which the measurement is performed and (ii) sensed position data P obtained by signal-processing the sensed value sensed by the acceleration sensor 90 for the position of the weight plate 30 that moves up and down. The measured position data Q is data for measuring the height change of the weight plate 30 with a ruler, an encoder (encoder)160, or the like, and may be required to have a high accuracy of a predetermined standard or more.

When learning is complete, the processor 100 may evaluate performance of the learned machine learning model by inputting test data to the learned machine learning model. For example, the processor 100 inputs a part of the sensed position data P obtained by signal-processing the sensed value sensed by the acceleration sensor 90 to the learned machine learning model, and confirms the degree of correspondence between the output value thereof and a part of the measured position data corresponding to the input part, thereby making it possible to evaluate the performance of the learned machine learning model.

When the performance evaluation value is higher than a preset criterion, the processor 100 may acquire the learned machine learning model as a machine learning model for acquiring the highly-ranked position data. However, when the performance evaluation value is less than or equal to the preset criterion, the processor 100 returns to the step of selecting the machine learning model again, and repeats the above steps until the learned machine learning model satisfying the performance evaluation value is acquired.

Referring to fig. 16, in the identifying step, the processor 100 may perform signal processing on the sensing value sensed by the acceleration sensor 90 to generate sensing position data P. Also, the processor 100 may input the generated sensed position data P to the learned machine learning model to acquire the heightened position data P'.

Referring now to fig. 17 and 18, another way in which the processor acquires location data using machine learning is seen. Fig. 17 and 18 are diagrams illustrating a second machine learning method performed by a processor provided in the weight tracking device according to an embodiment of the present invention.

Referring to fig. 17 and 18, in order to acquire the heightened position data through Machine Learning, the processor 100 according to an embodiment of the present invention may perform (i) a Learning step of Learning a pre-selected Machine Learning Model (Machine Learning Model) and (i i) a recognition step of inputting sensed acceleration data R sensed by the acceleration sensor 90 to the learned Machine Learning Model to acquire the heightened acceleration data R'. In this case, when the processor 100 acquires the heightened acceleration data R ', signal processing such as filtering, integration operation, and the like is performed on the heightened acceleration data R ' to acquire heightened position data P '.

Referring to fig. 17, in the case of the learning step, the processor 100 may select a machine learning model that needs to be learned in the same manner as described in fig. 15 and cause the machine learning model to perform learning.

However, at this time, the learning data set may include (i) measured acceleration data S measured actually and (ii) sensed acceleration data R sensed by the acceleration sensor 90 for the acceleration of the weight plate 30 moving up and down. The actually measured acceleration data R is not suitable for the configuration of the weight tracking device 60 because of its high price or large size, but data for measuring the acceleration change of the weight plate 30 by another acceleration sensor or the like having high accuracy may be required to have high accuracy of a predetermined standard or more.

When learning is complete, the processor 100 inputs test data to the machine learning model that has completed learning to evaluate performance of the machine learning model that has completed learning. When the performance evaluation value is higher than a preset criterion, the processor 100 may acquire the learned machine learning model as a machine learning model for acquiring the highly-ranked position data.

Referring to fig. 18, in the identifying step, the processor 100 may acquire sensed acceleration data R sensed by the acceleration sensor 90. Also, the processor 100 may acquire the heightened acceleration data R' by inputting the acquired sensed acceleration data R to the learned machine learning model. The processor 100 may perform signal processing such as filtering and integration on the heightened acceleration data R 'to acquire heightened position data P'.

Referring to fig. 19, position data of the weight tracking device generated by signal processing or machine learning of the processor is viewed. Fig. 19 is a diagram illustrating position data of the weight tracking apparatus finally generated by a processor provided in the weight tracking apparatus according to an embodiment of the present invention using input acceleration data.

As described above, the NFC reading module 80 identifies the NFC tag 40 having the weight data of the weight plate 30 and provides the identified weight data to the processor 100.

Through these operations, the processor 100 can grasp which degree of weight the user has lifted.

Also, the acceleration sensor 90 provides acceleration data to the processor 100 by sensing an acceleration value of the weight tracking device 60 (or weight plate 30).

The processor 100 may then perform signal processing or machine learning on the acceleration data received to generate position data for the weight tracking device 60 or weight plate 30.

By using such position data, the number of exercise groups, the number of weightlifting times per group, the range of motion of joints, the amount of exercise, the amount of heat consumption, the time of exercise, the time of rest, and the like can be grasped.

As shown in fig. 19, more specifically, when the time when the position data is 0 or equal to or less than the predetermined value is equal to or longer than the predetermined time, it is determined that one group is ended, and the total number of groups can be grasped with the predetermined time as a reference.

The number of peaks in the graph indicates the number of times, and it can be understood that the number of times per group is four times, and it can be seen in fig. 19.

Since the height of the peak is the amount of positional change, the joint movement range of the user can be grasped from the height of the peak.

Also, the area T below the peak represents the amount of motion, which can be grasped by calculating the area T below the peak, and the amount of heat consumption can be calculated by T.

In addition, the X axis of the potential energy diagram represents time, and the exercise time and the rest time can be checked.

In this manner, a variety of information can be grasped from the position data, and such information can be provided to the user or further processed to be suitable for various purposes.

The weight tracking device according to an embodiment of the present invention is described above. Hereinafter, a weight tracking device according to another embodiment of the present invention will be described with reference to fig. 20 and 21. Fig. 20 is a perspective view of a weight tracking device according to another embodiment of the present invention. Fig. 21 is a view showing a state in which a weight tracking apparatus according to another embodiment of the present invention is mounted on a weight setting pin.

Referring to fig. 20 to 21, the weight tracking apparatus 200 according to another embodiment of the present invention may be a device that is detachably installed in the weight setting pin 230 and tracks the weight of the weight plate 30 installed in the weight setting pin 230.

The weight tracking device 200 may include the same structure as the weight tracking device 200 according to an embodiment of the present invention described above, and the housing 190 constituting the outer shape of the weight tracking device 200 may be attached to and detached from the weight setting pin 230.

More specifically, the weight setting pin 230 may include a pin portion 215 inserted into a pin hole of the weight plate or between the upper and lower weight plates and a head portion 210 at one end of the pin portion 215.

The housing 190 of the weight tracking device 200 may include a mounting/dismounting portion 180 mounted to the weight-setting pin 230, and the mounting/dismounting portion 180 may have a shape conforming to the head 210 of the weight-setting pin 230.

For example, if the head 210 is spherical, the attachment and detachment portion 180 may have a concave shape that can receive the spherical head 210. In this shape, in order to couple the weight tracking device 200 to the weight setting pin 230, the attachment/detachment portion 180 of the housing 190 receives the head portion 210, and the head portion 210 is fitted into the attachment/detachment portion 180.

Alternatively, the weight tracking device may be attached to the weight setting pin by forming one or more protrusions on the head of the weight setting pin, forming a fitting hole into which the protrusion can be fitted in the attachment/detachment portion of the weight tracking device, and fitting the protrusion into the fitting hole.

That is, the weight tracking device 200 according to another embodiment of the present invention is high in utilization efficiency in that it can be applied to the weight setting pin 230 as an existing product.

In the above, the weight tracking apparatus according to the present invention is examined, and in the following, referring to fig. 22, a weight tracking method according to an embodiment of the present invention is examined. FIG. 22 is a flow chart illustrating a weight tracking method according to an embodiment of the invention.

The weight tracking method according to an embodiment of the present invention may be a method of tracking a weight of a weight plate formed by weight plates lifted by a user, in a weight lifting machine including a plurality of weight plates to which NFC tags are respectively attached, using the weight tracking device according to an embodiment of the present invention.

The weight tracking method comprises the following steps: a step S10 of inserting a pin into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent ones of the plurality of weight plates; step S20, the NFC reading module detects weight data representing the weight of the weight plate set by the pin by reading the NF C tag detected by the pin when the pin is inserted; step S30, the processor receives the weight data detected by the NFC reading module from the NFC reading module; and step S40, the processor stores the weight data in the memory.

In step S10, a user inserts a pin into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent ones of the plurality of weight plates, and inserts the pin 10 of the weight tracking device 60 into the pin hole 45 formed in any one of the plurality of weight plates 25 or between vertically adjacent ones of the plurality of

weight plates

20, 22 in order to set up the weight plate 30 lifted by the user.

In this way, the weight plate 30 in the form of the stacked weight plates 20 can be provided, and as a result, the weight lifted by the user can be set.

In step S20, the NFC reading module detects weight data representing the weight of the weight plate set by the pin by reading the NFC tag detected by the pin when the pin is inserted, and in order to set the weight plate 30, the user moves the weight tracking device 60 to the weight plate, may insert the pin 10 into the pin hole 45 or between the upper and

lower weight plates

20, 22, during which the NFC reading module 80 of the weight tracking device 60 may read the NFC tag 40 attached to the weight plate 20 to detect the weight data representing the weight of the weight plate 30 set by the pin 10.

In step S30, after the processor receives the weight data detected by the NFC reading module from the NFC reading module and the NFC reading module 80 detects the weight data representing the weight of the weight plate 30, the processor 100 of the weight tracking device 60 may receive the weight data detected by the NFC reading module 80 from the NFC reading module 80.

After the processor 100 receives the weight data detected by the NFC reading module 80 from the NFC reading module 80 in step S40 where the processor stores the weight data in the memory, the weight data is stored in the memory 110 and may be transmitted to an external device by controlling the communication module 120 of the weight tracking device 60.

Additionally, the acceleration sensor 90 of the weight tracking device 60 senses acceleration data of the weight tracking device 60, and the processor 100 may receive the sensed acceleration data from the acceleration sensor 90 and then perform signal processing on the received acceleration data to generate position data representing a change in position of the weight tracking device 60.

Also, the processor 100 may store the position data in the memory 110 and transmit the position data to an external device through the communication module 120 controlling the weight tracking device 60.

Alternatively, the processor 100 receives acceleration data sensed by the acceleration sensor 90 from the acceleration sensor 90 and integrates the received acceleration data to generate position data, which may be generated by applying the position data to the machine learning model 170.

Also, the processor 100 may store the machining position data in the memory 110 and transmit the machining position data to an external device by controlling the communication module 120.

Alternatively, the processor 100 receives acceleration data sensed by the acceleration sensor 90 from the acceleration sensor 90 and applies the acceleration data to the machine learning model 170 to generate machining acceleration data, which may be integrated to generate machining position data.

In the above, the weight tracking method according to an embodiment of the present invention is examined, and in the following, referring to fig. 23, the weight tracking method according to another embodiment of the present invention is examined. Fig. 23 is a flowchart illustrating a weight tracking method according to another embodiment of the present invention.

A weight tracking method according to another embodiment of the present invention may be a method of tracking a weight of a weight plate formed by weight plates lifted by a user using a weight tracking device according to another embodiment of the present invention in a weight lifting machine including a plurality of weight plates to which NFC tags are respectively attached.

Such weight tracking methods may include: a step S50 of inserting a weight setting pin into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent ones of the plurality of weight plates; step S60, mounting the weight tracking device in the weight setting pin; step S70, the NFC reading module detects weight data indicating the weight of the weight stack set by the weight setting pin by reading the detected NFC tag; step S80, the processor receives the weight data detected by the NFC reading module from the N FC reading module; and step S90, the processor stores the weight data in the memory.

In step S50, a weight setting pin is inserted into a pin hole formed in any one of the plurality of weight plates or into a space between vertically adjacent ones of the plurality of weight plates, and a user inserts the weight setting pin 230 into a pin hole 45 formed in any one of the plurality of weight plates 25 or into a space between vertically adjacent ones of the plurality of

weight plates

20 and 22 in order to set a weight plate 30 that the user needs to lift.

In this way, the weight plate 30 in the form of stacked weight plates can be provided, and as a result, the weight that the user needs to lift can be set.

In step S60 of mounting the weight tracking device in the weight setting pin, the weight tracking device 200, which is a structure different from that of the weight setting pin 230, is mounted on the weight setting pin 230 so that the weight tracking device 200 and the weight setting pin 230 form an integrated body.

On the other hand, unlike the above case, after the weight tracking device 200 is attached to the weight setting pin 230, the weight setting pin 230 may be inserted into the pin hole 45 or between the vertically

adjacent weight plates

20 and 22.

In step S70, the NFC reading module detects weight data indicating the weight of the weight plate set by the weight setting pin by reading the detected NFC tag, and after the process or installation of the weight tracking device 200 on the weight setting pin 230 by the user is completed, the NFC reading module 80 of the weight tracking device 200 may read the NFC tag 40 attached to the

weight plate

20, 25 to detect weight data indicating the weight of the weight plate 30 set by the weight setting pin 230.

In step S80, after the processor receives the weight data detected by the NFC reading module from the NFC reading module and the NFC reading module 80 detects the weight data indicating the weight of the weight plate 30, the processor 100 of the weight tracking device 200 may receive the weight data detected by the NFC reading module 80 from the NFC reading module 80.

In step S90, the processor stores the weight data in the memory, and the processor 100 may store the weight data in the memory 110 after receiving the weight data detected by the NFC reading module 80 from the NFC reading module 80, and control the communication module 120 of the weight tracking device 200 to transmit the weight data to an external device.

Additionally, the acceleration sensor 90 of the weight tracking device 200 senses acceleration data of the weight tracking device 200, and the processor 100 may receive the sensed acceleration data from the acceleration sensor 90 and then perform signal processing on the received acceleration data to generate position data representing a change in position of the weight tracking device 200.

Also, the processor 100 may store the position data in the memory 110 and transmit the position data to an external device by controlling the communication module 120 of the weight tracking device 200.

Alternatively, the processor 100 may receive acceleration data sensed by the acceleration sensor 90 from the acceleration sensor 90 and integrate the received acceleration data to generate position data, generating machining position data by applying the position data to the machine learning model 170.

Also, the processor 100 may store the machining position data in the memory 110 and transmit the machining position data to an external device through the control communication module 120.

The embodiments of the present invention have been described above with reference to the accompanying drawings, but it will be understood by those skilled in the art that the present invention can be embodied in other specific forms without changing the technical spirit or essential characteristics thereof. It is therefore to be understood that the above described embodiments are illustrative in all respects, not restrictive.

Claims

1. A weight tracking device that is inserted into a pin hole formed in any one of a plurality of weight plates or between vertically adjacent weight plates of the plurality of weight plates to set a weight of a weight piece and track the weight of the weight piece in a weight lifting machine including the plurality of weight plates to which NFC tags are respectively attached, the weight tracking device being characterized in that,

the method comprises the following steps:

a housing;

a pin protruding from the housing and inserted into the pin hole or between the vertically adjacent weight plates;

an NFC reading module configured inside the housing to detect weight data indicating a weight of the weight plate set by the pin by reading the NFC tag detected during or after insertion of the pin;

a memory disposed inside the housing;

a processor disposed inside the housing; and

an acceleration sensor disposed inside the housing and sensing acceleration data representing acceleration values of the weight tracking device,

the processor receives the weight data detected by the NFC reading module from the NFC reading module and stores the weight data in the memory,

the NFC reading module is switched from a standby mode to an active mode to read the NFC tag at a point when an acceleration value of an axis parallel to the pin insertion direction is a reference value or less.

2. A weight tracking device that is inserted into a pin hole formed in any one of a plurality of weight plates or between vertically adjacent weight plates of the plurality of weight plates to set a weight of a weight piece and track the weight of the weight piece in a weight lifting machine including the plurality of weight plates to which NFC tags are respectively attached, the weight tracking device being characterized in that,

the method comprises the following steps:

a housing;

a memory disposed inside the housing;

a processor disposed inside the housing; and

in the three-axis acceleration values above the reference value, when the acceleration values above the two axes drop below the reference value, the NFC reading module is changed from the standby mode to the active mode to read the NFC tag.

3. The weight tracking device of claim 2,

further comprising a communication module disposed inside the housing and communicating with an external device,

the processor transmits the weight data to the external device by controlling the communication module.

4. The weight tracking device according to claim 2, wherein the NFC reading module is disposed so as to be in contact with an inner side of a front surface of the housing, the front surface of the housing facing the weight plate.

5. The weight tracking device according to claim 4, wherein a metal plate is attached to a part or all of the inside of the front face of the housing except for a part in contact with the NFC reading module.

6. The weight tracking device of claim 2,

the NFC reading module repeats a standby mode and an active mode,

and in the weight data read in the active mode, the NFC reading module judges the weight data with the highest frequency as the weight of the counterweight plate.

7. The weight tracking device of claim 2,

further comprising an acceleration sensor disposed inside the housing and sensing acceleration data indicative of an acceleration value of the weight tracking device,

the processor receives the acceleration data sensed by the acceleration sensor from the acceleration sensor,

and signal processing the received acceleration data to generate position data indicative of a change in position of the weight tracking device.

8. The weight tracking device of claim 2,

and signal processing the acceleration data to generate position data indicative of a change in position of the weight tracking device,

applying the location data to a learned machine learning model to generate highly localized location data.

9. The weight tracking device of claim 2,

applying the acceleration data to a learned machine learning model to generate highly-instrumented acceleration data,

signal processing the heightened acceleration data to generate position data representing a change in position of the weight tracking device.

10. A weight tracking device for tracking a set weight of a weight plate by inserting a weight setting pin into a pin hole formed in any one of a plurality of weight plates or between vertically adjacent weight plates of the plurality of weight plates in a weight lifting machine including the plurality of weight plates to which NFC tags are respectively attached, the weight tracking device being characterized in that,

the method comprises the following steps:

a housing that is detachably attached to the weight setting pin;

an NFC reading module configured inside the housing to detect weight data indicating a weight of the weight stack by reading the NFC tag detected during or after insertion of the weight setting pin;

a memory disposed inside the housing;

a processor disposed inside the housing; and

11. The weight tracking device of claim 10,

the housing includes an attachment/detachment portion attached to and detached from the weight setting pin,

the mounting and dismounting part is in a shape matched with the head part of the weight setting pin.

12. A weight tracking method of tracking a weight of a weight plate using the weight tracking device of claim 1 in a weight lifting machine including a plurality of weight plates to which NFC tags are respectively attached, the weight tracking method comprising:

a step of detecting weight data representing a weight of the weight piece by the NFC read module of claim 2 by reading the NFC tag detected during or after insertion of the pin when the pin is inserted into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent ones of the plurality of weight plates;

a step of the processor of claim 2 receiving the weight data from the NFC reading module;

a step of the processor storing the weight data in the memory of claim 2; and

sensing acceleration data representing acceleration values of the weight tracking device, wherein in the three-axis acceleration values above a reference value, when the acceleration values above two axes fall below the reference value, the NFC reading module is changed from a standby mode to an active mode to read the NFC tag.

13. A weight tracking method, in a weight lifting machine comprising a plurality of weight plates to which NFC tags are respectively attached, using the weight tracking device of claim 10, the weight tracking device tracking a weight of a weight plate set by an installed weight setting pin, the weight tracking method comprising:

a step of detecting weight data representing a weight of the weight piece by the NFC reading module of claim 10 by reading the NFC tag detected during or after insertion of the weight setting pin when the weight setting pin is inserted into a pin hole formed in any one of the plurality of weight plates or between vertically adjacent ones of the plurality of weight plates;

a step of the processor of claim 10 receiving the weight data from the NFC reading module;

a step of the processor storing the weight data in the memory of claim 10; and