Mastication monitoring system and method

Abstract

A mastication monitoring system and method are disclosed. The mastication monitoring system according to one embodiment of the present invention comprises: a data collection unit for collecting electromyography data by using an electromyography sensor provided in a predetermined wearable device; a masticatory muscle activation determination unit for determining whether the masticatory muscles are activated on the basis of the electromyography data collected by the data collection unit; a mastication cycle counting unit for counting mastication cycles by analyzing the electromyography data when the masticatory muscle activation determination unit determines that the masticatory muscles are activated; a mastication history generation unit for, when the mastication cycle counting unit terminates the counting of mastication cycles, generating mastication history data by collecting the electromyography data from a time point at which the masticatory muscles are activated to a time point at which the counting of mastication cycles is terminated; and a data transmission unit for transmitting the mastication history data generated by the mastication history generation unit to a user terminal paired with the wearable device.

Description

Authorship monitoring system and method thereof

[0001] The present invention relates to a chewing monitoring system and method thereof, and more particularly, to a chewing monitoring system and method thereof that collects a user's electromyography data through a wearable device and analyzes the electromyography data to monitor the number of chewing operations and chewing force.

[0002] In relation to health, which is one of the main concerns of modern society, the habit of masticating food is closely related to not only dental health but also digestive function.

[0003] Finely chewing food is crucial for proper gastric function. Furthermore, alpha-amylase (α-amylase) is not secreted without chewing, so proper chewing is crucial. Furthermore, parotin, an anti-aging hormone secreted by saliva, strengthens bone and dental tissues. The more the upper and lower teeth rub against each other during chewing, the more parotin is secreted.

[0004] In this regard, Korean Patent Publication No. 10-1951541, a prior art, discloses a chewing detection system and a providing method, but has the problem that it is difficult to provide optimized chewing habit feedback to the user by considering problems such as wear of the user's teeth based on the user's chewing force.

[0005] Therefore, in order to solve the above-mentioned problems, there is a need for research on a chewing monitoring system and method that can monitor the user's usual chewing habits, measure the chewing power of each user, monitor the number of chewing times, and guide the user to form healthy eating habits by reaching the chewing target number set by the user, and provide customized chewing habit feedback to the user to prevent problems such as tooth wear and temporomandibular joint damage that may occur due to abnormal chewing habits.

[0006] The purpose of the present invention is to provide a chewing monitoring system and method capable of providing user-customized chewing habit feedback to recognize and correct chewing habits that the user was not normally aware of by collecting electromyography data from an electromyography sensor provided in a wearable device to measure and monitor the number of chewing cycles and chewing force.

[0007] In addition, the purpose is to provide a chewing monitoring system and method that can provide chewing force detection information and warning signals to the user to prevent problems such as tooth wear and temporomandibular joint damage that may occur due to abnormal chewing habits in advance by detecting abnormal chewing force (chewing food with excessive chewing force) by calculating the appropriate chewing force required of the user by considering the differences in electromyography signals that differ from person to person.

[0008] In addition, the purpose is to provide a chewing monitoring system and method that can calculate and manage the number of chewing more accurately by supplementing the difference in signals generated by each user's food intake by calculating and setting the appropriate chewing force required differently depending on the degree of hardness of the food consumed by the user, and by correcting the number of chewing times with the diet weight based on the diet information entered by the user.

[0009] In addition, the purpose is to provide a chewing monitoring system and method that can effectively manage a user's meal time and diet by automatically calculating, recording, and managing the calories consumed through a meal based on the total meal time and dietary information collected in the process of monitoring the number of times the user chews.

[0010] The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems to be solved by the present invention that are not mentioned herein will be clearly understood by a person having ordinary skill in the technical field to which the present invention belongs from the description below.

[0011] A chewing monitoring system according to an embodiment of the present invention includes a data collection unit that collects electromyography data collected through an electromyography sensor provided in a predetermined wearable device, a chewing muscle activation determination unit that determines whether a chewing muscle is activated based on the electromyography data collected in the data collection unit, a chewing count counting unit that analyzes the electromyography data to count the number of chewing operations when the chewing muscle activation determination unit determines that the chewing muscle is activated, a chewing history generation unit that, when the counting of the number of chewing operations in the chewing counting unit ends, collects electromyography data from the time when the chewing muscle is activated to the time when the counting of the number of chewing operations ends to generate chewing history data, and a data transmission unit that transmits the chewing history data generated by the chewing history generation unit to a user terminal paired with the wearable device.

[0012] In addition, the masticatory muscle activation determination unit determines whether the masticatory muscle is activated by determining whether the voltage and duration of the electromyography data collected through the data collection unit exceed a preset threshold voltage and a preset first reference time, and further includes a reference data correction unit that corrects the threshold voltage and the preset threshold voltage based on the electromyography data, and the reference data correction unit is characterized in that it includes a correction request signal receiving unit that receives a correction request signal from a user terminal, a masticatory force calculation unit that analyzes the electromyography data collected from the wearable device when the correction request signal is received to calculate a standard masticatory force and a maximum masticatory force, and a voltage condition correction unit that corrects the threshold voltage and the threshold voltage based on the standard masticatory force and the maximum masticatory force.

[0013] In addition, the mastication counting unit counts the number of mastication based on the number of times the voltage of the electromyography data exceeds a threshold voltage, and if the duration of the electromyography data from the time when the voltage of the electromyography data exceeds the threshold voltage to the time when it becomes below the threshold voltage exceeds a first reference time, the number of mastication is counted once, and if a signal to end a meal is received from a user terminal, the counting of the number of mastication is terminated, and the first counting unit counts the total number of mastication from the time when the masticatory muscle is activated to the time when the counting of the number of mastication is terminated, and a second counting unit counts the number of mastication times when the voltage of the electromyography data exceeds the threshold voltage among the total number of mastication times counted by the first counting unit.

[0014] In addition, the history generation unit is characterized by including a history generation unit that generates history data based on at least one of diet information input from a user terminal, target number of chewing information, and number of chewing and total meal time information calculated by a number of chewing counting unit, and a feedback generation unit that generates eating habit feedback data based on total meal time, number of chewing, and diet information.

[0015] In addition, the masticatory muscle activation determination unit is characterized by further including a diet weight correction unit that reflects a preset weight on at least one of the threshold voltage and the critical voltage based on diet information input from a user terminal and then determines whether the masticatory muscle is activated.

[0016] According to the present invention, by collecting electromyography data from an electromyography sensor provided in a wearable device and measuring and monitoring the number of chewing operations and chewing force, it is possible to provide user-customized chewing habit feedback to enable the user to recognize and correct chewing habits that the user was not normally aware of.

[0017] In addition, by considering the differences in electromyography signals that vary from person to person, the appropriate chewing force required of the user is calculated and abnormal chewing force (chewing food with excessive chewing force) is detected, thereby providing chewing force detection information and warning signals to the user to prevent problems such as tooth wear and temporomandibular joint damage that may occur due to abnormal chewing habits.

[0018] In addition, it has the effect of calculating and managing the number of chewing times more accurately by compensating for differences in signals generated by each user's food intake by searching for and setting the appropriate chewing force required differently depending on the degree of hardness of the food consumed by the user, and by adjusting the diet weight to the number of chewing times based on the diet information entered by the user.

[0019] In addition, it has the effect of effectively managing the user's meal time and diet by automatically calculating, recording, and managing the calorie intake through the meal based on the total meal time and dietary information collected in the process of monitoring the user's number of writings.

[0020] Figure 1 is a configuration diagram of a copyright monitoring system according to an embodiment of the present invention.

[0021] FIGS. 2 to 5 are drawings for explaining a masticatory muscle activation determination unit of a masticatory monitoring system according to an embodiment of the present invention.

[0022] FIGS. 6 to 8 are drawings for explaining a number of times of writing counting unit of a writing monitoring system according to an embodiment of the present invention.

[0023] FIGS. 9 to 11 are drawings for explaining a copyright history generation unit of a copyright monitoring system according to an embodiment of the present invention.

[0024] Specific details, including the problems to be solved, means of solving the problems, and effects of the invention, related to the present invention are included in the following examples and drawings. The advantages and features of the present invention, and methods for achieving them, will become clearer with reference to the detailed examples described below, along with the accompanying drawings.

[0025] The scope of the present invention is not limited to the embodiments described below, and various modifications may be made by a person having ordinary knowledge in the relevant technical field without departing from the technical spirit of the present invention.

[0026]

[0027] Hereinafter, the title of the invention of the present invention is described in detail with reference to the attached drawing 1.

[0028] FIG. 1 is a configuration diagram of a chewing monitoring system according to an embodiment of the present invention, FIGS. 2 to 5 are diagrams for explaining a chewing muscle activation determination unit of a chewing monitoring system according to an embodiment of the present invention, FIGS. 6 to 8 are diagrams for explaining a chewing count counting unit of a chewing monitoring system according to an embodiment of the present invention, and FIGS. 9 to 11 are diagrams for explaining a chewing history generation unit of a chewing monitoring system according to an embodiment of the present invention.

[0029]

[0030] Example 1

[0031] Referring to FIG. 1, a chewing monitoring system (100) according to an embodiment of the present invention may include a data collection unit (110), a chewing muscle activation determination unit (120), a chewing count counting unit (130), a chewing history generation unit (140), and a data transmission unit (150).

[0032] More specifically, the data collection unit (110) collects electromyography data collected through an electromyography sensor provided in a predetermined wearable device (10), the masticatory muscle activation determination unit (120) determines whether the masticatory muscle is activated based on the electromyography data collected in the data collection unit (110), the masticatory muscle counting unit (130) counts the number of masticatory movements by analyzing the electromyography data when the masticatory muscle activation determination unit (120) determines that the masticatory muscle is activated, and the masticatory history generation unit (140) collects the electromyography data from the time when the masticatory muscle is activated to the time when the counting of the number of masticatory movements ends in the masticatory muscle counting unit (130) to generate masticatory history data, and the data transmission unit (150) generates the masticatory muscle generated in the masticatory history generation unit (140). The history data can be transmitted to a user terminal (20) paired with the wearable device (10).

[0033] For example, the electromyography data collected through the wearable device (10) includes at least one of masticatory muscle (masseter muscle) electromyography data and temporalis muscle electromyography data, and preferably, temporalis muscle electromyography data can be collected through the wearable device (10).

[0034] As another example, when the wearable device (10) and the user terminal (20) are paired and the wearable device (10) is worn by the user, the data collection unit (110) can collect electromyography data collected through the wearable device (10) in real time without requesting a separate measurement start signal from the user terminal (20).

[0035]

[0036] As shown in FIGS. 2 to 4, the masticatory muscle activation determination unit (120) can determine whether the masticatory muscle is activated by determining whether the voltage and duration of the electromyography data collected through the data collection unit (110) exceed a preset threshold voltage (Vth) and a preset first reference time.

[0037] In addition, the masticatory muscle activation determination unit (120) may include a reference data correction unit (121) that corrects the threshold voltage (Vth) and a preset threshold voltage (Vcri) based on the electromyography data, and a diet weight correction unit (122) that corrects the threshold voltage (Vth) by reflecting a preset weight based on diet information input from the user terminal and then determines whether the masticatory muscle is activated.

[0038] For example, the user's electromyography data collected through the wearable device (10) includes a voltage value, and when the voltage value exceeds the threshold voltage (Vth), it can be determined that the user is chewing food using the masticatory muscles.

[0039] In addition, it is possible to determine whether the time exceeding the threshold voltage (Vth) exceeds the first reference time so as to distinguish the habit of the user applying force to the masticatory muscles even when the user does not chew food.

[0040] More specifically, the first reference time can be set to 3 seconds, and the muscle activation determination unit (120) can determine whether a user wearing the wearable device (10) is consuming food by analyzing the pattern of the electromyography data for 3 seconds from the time when the electromyography data exceeds the threshold voltage (Vth).

[0041] That is, the voltage pattern of electromyography data will be different when the user simply exerts force on the masticatory muscles due to the user's habits and when the user exerts force on the masticatory muscles to chew food after eating. In addition, when the user exerts force on the masticatory muscles to chew food after eating, the masticatory muscles may repeatedly exceed and not exceed the threshold voltage (Vth).

[0042] Accordingly, the above-mentioned masticatory muscle activation determination unit (120) calculates the average voltage (Vavg) of the electromyography data during the first reference time, and determines whether the average voltage (Aavg) exceeds a preset reference voltage (Vref), thereby determining whether masticatory muscles are activated due to food intake.

[0043] For example, if the masticatory muscle activation determination unit (120) determines that the masticatory muscle is activated due to the ingestion of food, a masticatory activity recording request signal is transmitted to the user terminal (20), and if a masticatory activity recording approval signal corresponding to the masticatory activity recording request signal is received from the user terminal (20), a masticatory muscle activation signal may be generated.

[0044]

[0045] Meanwhile, the reference data correction unit (121) may include a correction request signal receiving unit (1211) that receives a correction request signal from the user terminal (20), a masticatory force calculation unit (1212) that analyzes the electromyography data collected from the wearable device (10) when the correction request signal is received to calculate a standard masticatory force and a maximum masticatory force, and a voltage condition correction unit (1213) that corrects the threshold voltage (Vth) and the critical voltage (Vcri) based on the standard masticatory force and the maximum masticatory force.

[0046] More specifically, since there is a difference in chewing force depending on the user wearing the wearable device (10), when the wearable device (10) is first paired with the user terminal (20) for more accurate chewing activity tracking, the standard chewing force and maximum chewing force can be measured to calculate a user-customized threshold voltage (Vth) and threshold voltage (Vcri).

[0047] Accordingly, when the wearable device (10) and the user terminal (20) are initially paired, and a correction request signal is received by the correction request signal receiving unit (1211) through the user terminal (20), the chewing force calculation unit (1212) can transmit guidance data for measuring standard chewing force and maximum chewing force to the user terminal.

[0048] For example, the guidance data may include information guiding the user to naturally chew food (e.g., gum, etc.) for 10 seconds while wearing the wearable device (10), information guiding the user to rest for 5 seconds when the collection of electromyography data for 10 seconds is completed, and information guiding the user to repeat clenching for 2 seconds and resting for 3 seconds three times when the 5-second rest is completed.

[0049] Accordingly, as illustrated in FIG. 5, the masticatory force calculation unit (1212) can calculate standard masticatory force based on electromyography data (510) collected for 10 seconds corresponding to a 'natural chewing state' and electromyography data (520) collected for 5 seconds corresponding to a 'resting state (masticatory muscle inactivation state)', and can calculate maximum masticatory force based on electromyography data (530) collected corresponding to a 'teeth clenching state'.

[0050] In addition, the voltage condition correction unit (1213) can correct the threshold voltage (Vth) based on the standard work force calculated by the work force calculation unit (1212), and can correct the threshold voltage (Vcri) based on the maximum work force.

[0051] For example, the standard masticatory force may be calculated as an average value of electromyography data collected for 10 seconds, and the threshold voltage (Vth) may be set as a minimum value among values ​​exceeding the maximum value of electromyography data (520) collected for 5 seconds among the electromyography data (510) collected for 10 seconds, and the threshold voltage (Vcri) may be set as a median value of the standard masticatory force and the maximum masticatory force, but may preferably be set in a range of ±20% of the median value of the standard masticatory force and the maximum masticatory force.

[0052] At this time, the threshold voltage (Vth) and the critical voltage (Vcri) can be additionally corrected through the user terminal (20) even after being corrected through the reference data correction unit (121).

[0053]

[0054] Meanwhile, the counting unit (130) counts the number of times the voltage of the electromyography data exceeds the threshold voltage (Vth), and when the duration of the electromyography data from the time the voltage of the electromyography data exceeds the threshold voltage (Vth) to the time the voltage of the electromyography data becomes lower than the threshold voltage (Vth) exceeds a preset second reference time, the number of times ...

[0055] For example, the second reference time may be set to 100 msec to distinguish the voltage of the electromyography data from noise that temporarily exceeds the threshold voltage (Vth), and the second reference time may be corrected according to the user's writing habits.

[0056] As another example, even if the meal completion signal is not received from the user terminal (20), if the electromyography data corresponding to the 'resting state (masticatory muscle inactivity state)' exceeds a preset third reference time (e.g., 30 minutes), the mastication counting unit (130) may transmit a signal requesting whether or not to complete the meal to the user terminal (20).

[0057]

[0058] In addition, as illustrated in FIG. 6, the number of mastication counting unit (130) may include a first counting unit (131) that counts the total number of mastication from the time the masticatory muscle is activated to the time when counting of the number of mastication ends, and a second counting unit (132) that counts the number of mastication abnormalities in which the voltage of the electromyography data exceeds the threshold voltage (Vth) among the total number of mastication counted by the first counting unit (131).

[0059] More specifically, as illustrated in FIG. 7, the second counting unit (132) can extract a case (710) in which the voltage of the electromyography data exceeds the threshold voltage (Vcri) and count it as the number of times of abnormal chewing in which food is consumed with excessive chewing force.

[0060] For example, as shown in the above-described FIG. 8, when the number of abnormal writings is continuously counted more than a preset number of times (e.g., 10 times), the second counting unit (132) may transmit a notification signal (810) to the user terminal (10).

[0061]

[0062] Meanwhile, the diet weight correction unit (122) can determine weights for correcting the threshold voltage (Vth) and the threshold voltage (Vcri) based on diet information input from the user terminal (10).

[0063] For example, the dietary information is input before the meal begins through the user terminal (10), and the threshold voltage (Vth) and the critical voltage (Vcri) are corrected by reflecting the weight based on the food included in the dietary information, and the dietary information may include category information of any one of a general meal, a soft meal (porridge, etc.), and a snack (snack bar, fruit, etc.).

[0064] For example, if the category information is a general food, the weight may be set to '1', if the category information is a year, the weight may be set to '0.7', and if the category information is a snack, the weight may be set to '1.2'.

[0065] That is, the minimum chewing force required may vary depending on the food consumed, and accordingly, the chewing muscle activation determination unit (120) can determine whether the chewing muscle is activated by using the electromyography data corrected by the weight.

[0066] At this time, the above category information and the above weight can be added, deleted, or modified through a designated administrator terminal.

[0067]

[0068] As illustrated in FIG. 9, the chewing history generation unit (140) may include a history generation unit (141) that generates the chewing history data based on at least one of the diet information input from the user terminal (20), target chewing frequency information, and the chewing frequency and total meal time information calculated by the chewing frequency counting unit (130), and a feedback generation unit (142) that generates eating habit feedback data based on the total meal time, the number of chewing frequencies, and the diet information.

[0069] More specifically, as illustrated in FIGS. 10 and 11, the chewing history data generated through the history generation unit (141) may include the total number of chewings and the total meal time information (1010), information on whether the target number of chewings has been achieved (1020), ranking information (1030) of the average number of chewings per meal calculated in response to the total number of chewings compared to the total meal time, eating habit history information (1040, 1050), calorie information (1060) calculated based on the diet information and the total number of chewings, etc.

[0070]

[0071] In addition, the feedback generation unit (142) calculates the number of chewings per minute based on the total number of chewings compared to the total meal time of the eating habit, and compares the calculated number of chewings per minute with a preset minimum reference value for the number of chewings per minute to determine whether or not it corresponds to a 'habit of not chewing food sufficiently'.

[0072] In addition, the abnormal chewing rate is calculated based on the number of abnormal chewing compared to the total number of chewing, and the calculated abnormal chewing rate is compared with a preset abnormal chewing standard rate to determine whether it corresponds to a 'habit of chewing food with excessive force'.

[0073] In addition, by comparing the minimum meal time set in response to the above dietary information with the total meal time, it is possible to determine whether or not it corresponds to a 'fast eating habit'.

[0074] Accordingly, the feedback generation unit (142) can generate the eating habit feedback data based on whether or not the eating habit of the user wearing the wearable device (10) is applicable.

[0075] At this time, the eating habit feedback data may include a guidance notification signal for correcting the eating habits of a user wearing the wearable device (10).

[0076]

[0077] As another example, when the wearable devices (10) are provided as a pair and attached to both sides of the user's temporalis muscle, the electromyography data can be collected as a pair of right-side electromyography data and left-side electromyography data.

[0078] Accordingly, the feedback generation unit (142) can compare the sizes of the right electromyography data and the left electromyography data to determine whether it corresponds to a 'habit of chewing on only one side (unilateral chewing)'.

[0079]

[0080] Example 2

[0081] The mastication monitoring method of the above mastication monitoring system (100) comprises: a first step in which, when the wearable device (10) and the user terminal (20) are paired, the correction request signal receiving unit (1211) receives a correction request signal from the user terminal; a second step in which, when the correction request signal is received, the mastication force calculating unit (1212) transmits mastication force measurement guide information to the user terminal (20) and calculates the standard mastication force and the maximum mastication force; a third step in which, based on the standard mastication force and the maximum mastication force, the voltage condition correction unit (1213) corrects the threshold voltage (Vth) and the threshold voltage (Vcri); a fourth step in which, when the threshold voltage (Vth) and the threshold voltage (Vcri) are corrected, the data collecting unit (110) collects electromyography data received from the wearable device (10); and, based on the electromyography data collected by the data collecting unit (110), the mastication muscle The method may include a fifth step in which the activation determination unit (120) determines whether the masticatory muscles are activated; a sixth step in which the masticatory number counting unit (130) analyzes electromyography data collected through the wearable device (10) to count the number of mastications when the masticatory muscles are determined to be activated through the masticatory muscle activation determination unit (120); a seventh step in which the masticatory number counting unit (130) terminates when a meal completion signal is received from the user terminal (20) and masticatory history data and eating habit feedback data are generated through the masticatory history generation unit (140); and an eighth step in which the data transmission unit (150) transmits the masticatory history data and the eating habit feedback data to the user terminal (20) when the masticatory history data and eating habit feedback data are generated through the masticatory history generation unit (140).

[0082]

[0083] Accordingly, according to the present invention as described above, a chewing monitoring system and method can be provided that can provide user-customized chewing habit feedback to recognize and correct chewing habits that the user was not normally aware of by collecting electromyography data from an electromyography sensor provided in a wearable device to measure and monitor the number of chewing operations and chewing force.

[0084] In addition, a chewing monitoring system and method can be provided that can provide chewing force detection information and warning signals to the user to prevent problems such as tooth wear and temporomandibular joint damage that may occur due to abnormal chewing habits in advance by calculating the appropriate chewing force required of the user by considering the differences in electromyography signals that differ from person to person and detecting abnormal chewing force (chewing food with excessive chewing force).

[0085] In addition, a chewing monitoring system and method can be provided that can search for and set an appropriate chewing force required differently depending on the degree of hardness of food consumed by the user, and by correcting the number of chewing times with a diet weight based on the diet information entered by the user, thereby supplementing the difference in signals generated by each user's food intake and counting and managing the number of chewing times more accurately.

[0086] In addition, a chewing monitoring system and method can be provided that can effectively manage a user's meal time and diet by automatically calculating, recording, and managing the calorie intake through a meal based on the total meal time and dietary intake information collected in the process of monitoring the number of times a user chews.

[0087]

[0088] In addition, a method for controlling a copyright monitoring system according to an embodiment of the present invention may be recorded on a computer-readable medium including program commands for performing operations implemented by various computers. The computer-readable medium may include program commands, data files, data structures, etc., alone or in combination. The program commands may be specially designed and configured for the present invention or may be known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specifically configured to store and execute program commands, such as ROMs, RAMs, and flash memories. Examples of program commands include not only machine language codes generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter, etc.

[0089]

[0090] Although the embodiments of the present invention have been described with limited examples and drawings, the embodiments of the present invention are not limited to the embodiments described above, and various modifications and variations are possible based on this description by those skilled in the art to which the present invention pertains. Therefore, the embodiments of the present invention should be understood solely by the scope of the claims set forth below, and all equivalent or equivalent modifications thereof are deemed to fall within the scope of the present invention.

[0091]

[0092] 10: Wearable devices

[0093] 20: User terminal

[0094] 110: Data Collection Department

[0095] 120: Masticatory muscle activation judgment unit 121: Reference data correction unit

[0096] 1211: Correction request signal receiver

[0097] 1212: Copyright calculation section

[0098] 1213: Voltage condition compensation unit

[0099] 122: Diet Weight Correction Section

[0100] 130: Copyright counting section 131: First counting section

[0101] 132: Second Counting Department

[0102] 140: Copyright history generation section 141: History generation section

[0103] 142: Feedback generation unit

[0104] 150: Data transmission unit

Claims

1. A data collection unit that collects electromyography data collected through an electromyography sensor provided in a designated wearable device; A masticatory muscle activation determination unit that determines whether masticatory muscles are activated based on the electromyography data collected in the data collection unit; A masticatory counting unit that counts the number of masticatory operations by analyzing the electromyography data when the masticatory muscle activation determination unit determines that the masticatory muscle is activated; When the counting of the number of times of mastication is finished in the above mastication counting unit, a mastication history generation unit that collects the electromyography data from the time the mastication muscle is activated to the time the counting of the number of times of mastication is finished to generate mastication history data; and A data transmission unit that transmits the copyright history data generated in the copyright history generation unit to a user terminal paired with the wearable device; A copyright monitoring system including:

2. In paragraph 1, The above masticatory muscle activation judgment unit is, By determining whether the voltage and duration of the electromyography data collected through the data collection unit exceed a preset threshold voltage and a preset first reference time, it is determined whether the masticatory muscle is activated. It further includes a reference data correction unit that corrects the threshold voltage and the preset threshold voltage based on the electromyography data; The above reference data correction unit, A calibration request signal receiving unit that receives a calibration request signal from the user terminal; When the correction request signal is received, a masticatory force calculation unit that analyzes the electromyography data collected from the wearable device to calculate the standard masticatory force and the maximum masticatory force; and A work monitoring system characterized by including a voltage condition correction unit that corrects the threshold voltage and the critical voltage based on the standard work force and the maximum work force.

3. In paragraph 2, The above copyright counting section, The number of times the above-mentioned EMG data voltage exceeds the threshold voltage is counted based on the number of times the above-mentioned EMG data voltage exceeds the threshold voltage. If the duration of the EMG data from the point at which the voltage of the EMG data exceeds the threshold voltage to the point at which it falls below the threshold voltage exceeds the preset second reference time, the number of times of mastication is counted once, When a meal completion signal is received from the user terminal, the counting of the number of times of chewing is terminated. A first counting unit that counts the total number of chewing operations from the time the above chewing muscle is activated to the time when counting of the number of chewing operations ends; and A chewing monitoring system characterized by comprising a second counting unit that counts the number of chewing operations in which the voltage of the electromyography data exceeds the threshold voltage among the total number of chewing operations counted by the first counting unit.

4. In paragraph 1, The above copyright history generation unit is, A history generation unit that generates the chewing history data based on at least one of the diet information input from the user terminal, the target chewing frequency information, and the chewing frequency and total meal time information calculated by the chewing frequency counting unit; and A chewing monitoring system characterized by comprising a feedback generation unit that generates eating habit feedback data based on the total meal time, the number of chewing times, and the diet information.

5. In paragraph 2, The above masticatory muscle activation judgment unit is, A chewing monitoring system further comprising a diet weight correction unit that reflects a preset weight on at least one of the threshold voltage and the critical voltage based on the diet information input from the user terminal and then determines whether the chewing muscle is activated.

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