Biofeedback-based bruxism reduction system and method

Abstract

A biofeedback-based bruxism relief system and method are disclosed. a user recognition unit that receives a bruxism diagnosis request signal generated from at least one of a pre-designated user terminal and a wearable device attached to the user's skin, extracts a unique number assigned to the wearable device included in the bruxism diagnosis request signal, and retrieves user information corresponding to the unique number from a pre-designated database; a data collection unit that receives electromyogram data collected from at least one sensor provided in the wearable device; a bruxism diagnosis unit that diagnoses the occurrence of bruxism by determining whether the electromyogram data collected from the data collection unit satisfies a pre-designated condition; a biofeedback generation unit that applies a vibration stimulus to the user's skin via a vibration motor provided in the wearable device if the bruxism diagnosis unit determines that bruxism has occurred; and a user monitoring unit that monitors the user's bruxism symptoms based on the bruxism diagnosis data derived by the bruxism diagnosis unit and the vibration stimulus data generated by the biofeedback generation unit.

Description

Technical Field

[0001] The present invention relates to a teeth grinding diagnosis and relaxation system. More specifically, the present invention relates to a biofeedback-based teeth grinding relaxation system and method capable of diagnosing teeth grinding symptoms by analyzing the temporal muscle signals of a user during sleep and providing a biofeedback signal including vibration stimulation to the user to relieve the teeth grinding symptoms.

Background Art

[0002] Recently, various sleep disorders and sleep disturbances have been found based on physiological and physical signals emitted from the body of a subject during sleep, and based on this, the direction of diagnosis and treatment for sleep problems has been set, and specific treatment methods such as drug therapy, cognitive behavioral correction, and surgical operations have been proposed.

[0003] For reference, electroencephalogram is used as basic data for grasping the progress and structure of sleep, the safety of measuring eye movement is useful for judging the sleep stage, and electromyogram must be measured because the muscle tension changes according to the sleep stage. In particular, the electromyogram of the leg is measured to diagnose a sleep disorder called periodic limb movement disorder, and furthermore, the electromyogram of the jaw muscle is necessary to clarify teeth grinding.

[0004] In particular, in the case of teeth grinding, in addition to chewing and softening movements, strong movements of the jaw worsen the teeth or include teeth grinding, and usually, the teeth are ground with a force 2 to 10 times or more greater than when chewing food, and teeth grinding mainly occurs during sleep, but teeth grinding may also occur during the day.

[0005] Teeth grinding is known to be experienced by about 10% of the total population in Korea, and often appears when a person is sensitive and in an unstable mental state, and stress is the cause. Other causes include malocclusion where the teeth do not fit well, drinking alcohol, etc., and genetics, taking certain drugs, central nervous system disorders, etc. are also known as causes.

[0006] Because teeth grinding applies strong force to specific teeth, it can damage periodontal tissues, cause wear and tear on the tooth surface, and damage the surrounding tissues. This can lead to tooth sensitivity when eating cold foods, and in severe cases, teeth may even become loose.

[0007] Bruxism (teeth grinding) can sometimes be treated professionally at a hospital, with options including psychological therapy, the use of occlusal stabilization devices between the upper and lower teeth, and medication.

[0008] In recent years, there has been a demand for devices that can easily diagnose and prevent teeth grinding during sleep at home. One such device for diagnosing teeth grinding, Korean Registered Patent Publication No. 10-1621500, discloses a teeth grinding and tooth clenching analysis device and method that is attached to the subject's head to detect and output tilt signals associated with changes in sleep posture and electromyogram signals generated by the subject's teeth grinding and clenching. When it receives a treatment signal from an analysis terminal, it outputs a pre-set sleep posture correction signal. However, there are limitations to accurately diagnosing the symptoms of teeth grinding and tooth clenching, and it does not exert a significant awakening effect during sleep, resulting in insufficient therapeutic effect against teeth grinding and tooth clenching.

[0009] Therefore, in order to solve the aforementioned problems, research on biofeedback-based bruxism reduction systems and methods is necessary. [Overview of the Initiative] [Problems that the invention aims to solve]

[0010] The present invention aims to provide a biofeedback-based bruxism reduction system and method that can more effectively detect whether or not a user experiences bruxism during sleep by collecting electromyogram data of the muscles around the user's face and head via a wearable device attached to the user's skin, and determining whether or not the user is sleeping and whether or not a bruxism event is occurring based on the collected electromyogram data.

[0011] Furthermore, the biofeedback-based Eigal aims to provide a relief system and method that can more effectively interfere with and alleviate teeth grinding symptoms by receiving input of the minimum intensity of vibration stimulation provided via a wearable device through a user terminal, and gradually increasing the intensity of the stimulation from the minimum vibration stimulation input via the user terminal, thereby providing a biofeedback stimulation signal optimized for the user.

[0012] Furthermore, the objective is to provide a biofeedback-based bruxism reduction system and method that collects and stores user-specific data by collecting and storing user sleep patterns and bruxism event information, and then uses this data to construct bruxism learning data and quickly calculate user-customized biofeedback data.

[0013] The problems that this invention aims to solve are not limited to those mentioned above. Other problems that this invention aims to solve, not described herein, can be clearly understood by a person with ordinary skill in the art to which this invention belongs from the following description. [Means for solving the problem]

[0014] A biofeedback-based bruxism relief system according to one embodiment of the present invention includes a user recognition unit that receives a bruxism diagnosis request signal generated from at least one of a previously designated user terminal and a wearable device attached to the user's skin, extracts a unique number assigned to the wearable device included in the bruxism diagnosis request signal, and retrieves user information corresponding to the unique number from a previously designated DB; a data collection unit that receives electromyogram data collected from at least one sensor provided on the wearable device; a bruxism diagnosis unit that diagnoses the presence or absence of bruxism by determining whether the electromyogram data collected from the data collection unit satisfies previously set conditions; a biofeedback generation unit that applies vibration stimulation to the user's skin via a vibration motor provided on the wearable device if the bruxism diagnosis unit determines that bruxism has occurred; and a user monitoring unit that monitors the user's bruxism symptoms based on the bruxism diagnosis data derived from the bruxism diagnosis unit and the vibration stimulation data generated by the biofeedback generation unit.

[0015] Furthermore, the data acquisition unit includes a first sensor that collects first electromyogram data during a pre-set time period, and a second sensor that is provided at a pre-set distance from the first sensor and collects second electromyogram data. The teeth grinding diagnosis unit includes a sleep state determination unit that determines the user's sleep state by comparing the first electromyogram data collected via the first sensor with a pre-set first reference voltage, V_th1, and a teeth grinding occurrence detection unit that, if the sleep state determination unit determines that the user is asleep, compares the second electromyogram data collected via the second sensor with a pre-set second reference voltage, V_th2, to determine whether or not a teeth grinding event has occurred in the user.

[0016] Furthermore, the teeth grinding occurrence detection unit generates a window mask for a pre-set time range and superimposes the window mask on the second electromyogram data to determine whether or not a teeth grinding event has occurred. The determination of whether or not a teeth grinding event has occurred is based on the time within the window mask that the second electromyogram data exceeds V_th2. The biofeedback generation unit, if the teeth grinding occurrence detection unit determines that a teeth grinding event has occurred, generates a first pattern of vibration stimulation at T_winend, which is the time when the window mask ends. The biofeedback generation unit includes a user stimulation provision unit that provides the first pattern of vibration stimulation to the user via a wearable device, and a user stimulation correction unit that corrects the second electromyogram data collected via the data collection unit after the first pattern of vibration stimulation has been generated and the first pattern of vibration stimulation collected via the data collection unit before the first pattern of vibration stimulation has been generated. The first pattern is characterized in that the initial value of the vibration stimulation is determined based on the minimum stimulation intensity set from the user terminal, and the intensity of the vibration stimulation is corrected by one level at a time via the user stimulation correction unit.

[0017] Furthermore, the teeth grinding diagnosis unit determines whether or not to use electromyogram data collected from the first and second sensors based on the teeth grinding diagnosis mode input from the user terminal. The teeth grinding diagnosis mode is characterized by including a first diagnostic mode in which the sleep state determination unit determines the user's sleep state, and if it is determined that the user is asleep, the teeth grinding occurrence detection unit determines whether or not a teeth grinding event has occurred with the user; and a second diagnostic mode in which a pre-set sleep waiting time is counted, and if the sleep waiting time is exceeded, it is automatically determined that the user is asleep, and the teeth grinding occurrence detection unit determines whether or not a teeth grinding event has occurred with the user.

[0018] Furthermore, the user monitoring unit is characterized by including a user data generation unit that measures the user's daily sleep time and generates daily user data that includes at least one of the following: the number of times teeth grinding occurred during the daily sleep time, the duration of teeth grinding, the number of times vibration stimuli were generated, and the maximum intensity of vibration stimuli; a teeth grinding diagnosis learning unit that learns the number of times teeth grinding occurred during the daily sleep time and the maximum intensity of vibration stimuli included in the daily user data through a pre-configured artificial intelligence learning algorithm, and optimizes the teeth grinding diagnosis criteria of the teeth grinding diagnosis unit based on the result data derived through the artificial intelligence learning algorithm; and a user data transmission unit that transmits the daily user data generated by the user data generation unit to the user terminal based on a request signal received from the user terminal. [Effects of the Invention]

[0019] According to the present invention, electromyographic data of the muscles around the user's face and head is collected via a wearable device attached to the user's skin, and based on the collected electromyographic data, it is possible to determine whether the user is sleeping and whether or not a teeth grinding event is occurring, thereby enabling a more effective detection of whether or not a teeth grinding event is occurring during sleep.

[0020] Furthermore, by receiving input of the minimum intensity of vibration stimulation provided via a wearable device through a user terminal, and gradually increasing the intensity of the stimulation from the minimum vibration stimulation input via the user terminal, the system provides a biofeedback stimulation signal optimized for the user, which has the effect of more effectively interfering with and alleviating teeth grinding symptoms.

[0021] Furthermore, by collecting and storing user sleep patterns and teeth grinding event information, it is possible to collect user-specific data, build teeth grinding learning data based on this data, and quickly calculate user-customized biofeedback data. [Brief explanation of the drawing]

[0022] [Figure 1]It is a configuration diagram of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention. [Figure 2] It is a configuration diagram of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention. [Figure 3] It is a diagram for explaining a data collection unit of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention. [Figure 4] It is a diagram for explaining a teeth grinding diagnosis unit of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention. [Figure 5] It is a diagram for explaining a biofeedback generation unit of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention. [Figure 6] It is a diagram for explaining a biofeedback generation unit of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention. [Figure 7] It is a diagram for explaining a biofeedback generation unit of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention. [Figure 8] It is a diagram for explaining a biofeedback generation unit of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention. [Figure 9] It is a diagram for explaining a user monitoring unit of a biofeedback-based teeth grinding relaxation system according to an embodiment of the present invention.

Embodiments for Carrying Out the Invention

[0023] Specific matters including the problems to be solved, the means for solving the problems, and the effects of the invention for the present invention as described above are included in the examples and drawings described below. The advantages and features of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described in detail later together with the attached drawings.

[0024] The scope of the present invention is not limited to the embodiments described below, and can be modified and implemented in various ways by persons with ordinary skill in the art without departing from the technical spirit of the invention.

[0025] The title of the present invention will be described in detail below with reference to the attached Figure 1.

[0026] Figure 1 is a diagram illustrating the configuration of a biofeedback-based bruxism relief system according to one embodiment of the present invention. Figures 1 and 2 are diagrams illustrating the configuration of a biofeedback-based bruxism relief system according to one embodiment of the present invention. Figure 3 is a diagram illustrating the data collection unit of a biofeedback-based bruxism relief system according to one embodiment of the present invention. Figure 4 is a diagram illustrating the bruxism diagnosis unit of a biofeedback-based bruxism relief system according to one embodiment of the present invention. Figures 5 to 8 are diagrams illustrating the biofeedback generation unit of a biofeedback-based bruxism relief system according to one embodiment of the present invention. Figure 9 is a diagram illustrating the user monitoring unit of a biofeedback-based bruxism relief system according to one embodiment of the present invention. [Examples]

[0027] Referring to Figures 1 and 2, a biofeedback-based bruxism relief system 100 according to one embodiment of the present invention collects electromyogram (EMG) data necessary for diagnosing bruxism via a wearable device 10 attached to the user's skin or to one side of the user's head. The EMG data collected via the wearable device 10 is transmitted to the biofeedback-based bruxism relief system 100, which analyzes the EMG data to diagnose the user's bruxism symptoms and generates a biofeedback signal that can alleviate the bruxism symptoms in accordance with the diagnosis. At this time, the biofeedback signal generated by the biofeedback-based bruxism relief system 100 can control a vibration motor provided in the wearable device 10 to provide vibration stimulation to the user.

[0028] This allows biofeedback, such as vibrational stimulation, to be provided to the user, thereby regulating the function of the user's autonomic nervous system and inducing the user to actively alleviate teeth grinding symptoms.

[0029] Furthermore, data regarding the user's teeth grinding symptoms generated via the biofeedback-based teeth grinding relief system 100 can be transmitted to a user terminal 20 linked to the wearable device 10. Also, based on a request signal received from the user terminal 20, the data transmitted to the user terminal 20 can be stored in a previously designated DB 30.

[0030] More specifically, the biofeedback-based bruxism relief system 100 may include a user recognition unit 110, a data acquisition unit 120, a bruxism diagnosis unit 130, a biofeedback generation unit 140, and a user monitoring unit 150.

[0031] The user recognition unit 110 receives a teeth grinding diagnosis request signal generated from at least one of the previously designated user terminal 20 and the wearable device 10 attached to the user's skin, extracts a unique number assigned to the wearable device 10 included in the teeth grinding diagnosis request signal, and can retrieve user information corresponding to the unique number from the previously designated DB 30.

[0032] Furthermore, the data acquisition unit 120 receives electromyogram data collected from at least one sensor provided on the wearable device 10, and the teeth grinding diagnosis unit 130 receives the electromyogram data collected from the data acquisition unit 120. The unit determines whether the electromyogram data satisfies pre-set conditions to diagnose whether teeth grinding has occurred, and if the teeth grinding diagnosis unit 130 determines that teeth grinding has occurred, the biofeedback generation unit 140 applies vibration stimulation to the user's skin via a vibration motor provided on the wearable device 10, and the user monitoring unit 150 can monitor the user's teeth grinding symptoms based on the teeth grinding diagnosis data derived from the teeth grinding diagnosis unit 130 and the vibration stimulation data generated by the biofeedback generation unit 140.

[0033] More specifically, as shown in Figure 3, the data acquisition unit 120 may include a first sensor 121 for acquiring first electromyogram data during a predetermined time period, and a second sensor 122 provided at a predetermined distance from the first sensor 121 for acquiring second electromyogram data.

[0034] For example, if the wearable device 10 is provided in a form that is attached to one side of the user's head, it may be attached near the user's temple.

[0035] When the wearable device 10 is attached to one side of the user's temple, electromyogram data of the user's face can be collected via the first sensor 121 and the second sensor 122 provided on the wearable device 10.

[0036] For example, the first sensor 121 can collect the user's eye-edge electromyogram signal, and the second sensor 122 can collect the user's temporal electromyogram signal.

[0037] On the other hand, referring to Figure 4, the teeth grinding diagnostic unit 130 may include a sleep state determination unit 131 that determines the user's sleep state by comparing the first electromyogram data collected via the first sensor 121 with a pre-set first reference voltage V_th1, and a teeth grinding occurrence detection unit 132 that, if the sleep state determination unit 131 determines that the user is asleep, compares the second electromyogram data collected via the second sensor 122 with a pre-set second reference voltage V_th2 to determine whether or not a teeth grinding event has occurred for the user.

[0038] At this time, the teeth grinding diagnosis unit 130 determines whether or not to use the data collected from the first sensor 121 and the second sensor 122 based on the teeth grinding diagnosis mode input from the user terminal 20. The teeth grinding diagnosis mode may include a first diagnosis mode in which the sleep state determination unit 131 determines the user's sleep state, and if it is determined that the user is asleep, the teeth grinding occurrence detection unit 132 determines whether or not a teeth grinding event has occurred for the user, and a second diagnosis mode in which a pre-set sleep waiting time is counted, and if the sleep waiting time is exceeded, it is automatically determined that the user is asleep, and the teeth grinding occurrence detection unit 132 determines whether or not a teeth grinding event has occurred for the user.

[0039] More specifically, when the bruxism diagnosis mode is set to the first diagnosis mode, electromyogram data is collected using both the first sensor 121 and the second sensor 122. However, while the first electromyogram data is being collected through the first sensor 121, the second sensor 122 can be switched to power-saving mode.

[0040] Furthermore, the sleep state determination unit 131 of the teeth grinding diagnosis unit 130 can analyze the user's eye movement by comparing the first electromyogram data collected via the first sensor 121 with the V_th1.

[0041] As an example, the sleep state determination unit 131 generates eye-edge movement data corresponding to the interval in which the first electromyogram data exceeds V_th1, and can determine the user's sleep state by comparing the eye-edge movement data with the eye-edge movement learning data during sleep stored in the DB30.

[0042] If the sleep state determination unit 131 determines that the user is asleep, the first sensor 121 may switch to power saving mode and data collection via the first sensor 121 may be stopped.

[0043] Furthermore, when the bruxism diagnosis mode is set to the second diagnosis mode, the first sensor 121 switches to power-saving mode, and the bruxism diagnosis unit 130 can determine whether or not the user is experiencing bruxism symptoms using only the second electromyogram data collected via the second sensor 121.

[0044] In other words, in the first diagnostic mode, the user's sleep time can be accurately monitored, and during the process of determining the sleep state via the sleep state determination unit 131, the teeth grinding occurrence detection unit 132 switches to power saving mode, and when the determination of the user's sleep state is completed, the teeth grinding occurrence detection unit 132 switches the sleep state determination unit 131 to power saving mode, thereby improving the battery power efficiency of the wearable device 10. In the second diagnostic mode, the data processing process of the sleep state determination unit 131 can be omitted, thereby improving the speed of the data calculation process.

[0045] On the other hand, the teeth grinding detection unit 132 collects second electromyogram data related to the movement of the user's temporalis muscle via the second sensor 122, and can determine whether or not a teeth grinding event has occurred in the user by comparing the second electromyogram data with V_th2.

[0046] More specifically, as shown in Figure 5, the teeth grinding detection unit 132 generates a window mask 510 for a pre-set time range, and superimposes the window mask 510 onto the second electromyogram data to determine whether or not the teeth grinding event has occurred.

[0047] Based on the time that the second electromyogram data exceeds V_th2 within the window mask 510, it is possible to determine whether or not the teeth grinding event has occurred.

[0048] For example, the time range of the window mask 510 is initially set to a system setting of 2 seconds and can be optimized through artificial intelligence learning by the user monitoring unit.

[0049] As shown in Figure 6, the biofeedback generation unit 140 may include a user stimulus provision unit 141 that, when the teeth grinding occurrence detection unit 132 determines that a teeth grinding event has occurred, generates one pattern of vibration stimulus at T_winend, which is the time when the window mask 510 ends, and provides the first pattern of vibration stimulus to the user via the wearable device 10, and a user stimulus correction unit 142 that, after the first pattern of vibration stimulus has ended, corrects the first pattern of vibration stimulus if the teeth grinding event is detected via the teeth grinding diagnosis unit 130 within a previously set time range.

[0050] For example, if the vibration stimulation of the first pattern is terminated and the teeth grinding diagnostic unit 130 determines that a teeth grinding event has occurred within 5 seconds, the user stimulation correction unit 142 can modify the first pattern so that the user is provided with a stimulation of a higher intensity than the vibration stimulation of the first pattern.

[0051] In this case, the initial value of the vibration stimulus in the first pattern is determined based on the minimum stimulus intensity set by the user terminal 20, and the intensity of the vibration stimulus can be corrected by one level at a time via the user stimulus correction unit 142.

[0052] For example, if the intensity of the vibration stimulus is divided into 1 to 10 levels, and the initial value of the vibration stimulus is input at level 3 via the user terminal 20, the initial value of the first pattern may be set to level 3 at the same time that the wearable device 10 is activated (or restarted) by the user.

[0053] As shown in Figure 7, when the teeth grinding diagnostic unit 130 determines that a teeth grinding event has occurred, a first pattern of vibration stimulation 521 set to an initial value (level 3) is provided to the user via the biofeedback generation unit 140. If the teeth grinding event occurs again within 5 seconds after the first pattern of vibration stimulation 521 has ended, the user stimulation correction unit 142 can correct the first pattern of vibration stimulation to level 4 because the level 3 vibration stimulation is insufficient to alleviate the user's teeth grinding symptoms.

[0054] As a result, for any teeth grinding event that occurs within 5 seconds after the termination of the first pattern of vibration stimulation 521, the first pattern of vibration stimulation 522, corrected to the 4 levels, can be provided to the user via the wearable device 10.

[0055] Similarly, if the first pattern of vibration stimulation 522 ends and the teeth grinding event occurs again within 5 seconds, the 4 levels of vibration stimulation cannot alleviate the user's teeth grinding symptoms, so the user stimulation correction unit 142 can correct the first pattern of vibration stimulation to level 5.

[0056] In this case, the vibration stimulus of the first pattern can be corrected up to level 10, which is the maximum level of the vibration stimulus. If a teeth grinding event occurs again within 5 seconds after the vibration stimulus of the first pattern has been corrected to level 10, the user stimulus correction unit 142 can interrupt the correction of the vibration stimulus of the first pattern and send a wake-up notification signal to the user terminal 20 to wake the user.

[0057] Furthermore, depending on the settings of the user terminal, a wake-up notification signal can be sent to the user terminal after the first pattern has been corrected up to level 10. Alternatively, after two corrections, the correction of the vibration stimulus of the first pattern can be interrupted, and a wake-up notification signal can be immediately sent to the user terminal 20 to induce the user to wake up.

[0058] On the other hand, as shown in Figure 8, if a teeth grinding event does not occur within the predetermined time (5 seconds) after the first pattern of vibration stimulation is applied to the user, the user stimulation correction unit 142 does not perform correction of the first pattern of vibration stimulation. Therefore, the user stimulation generation unit 141 can apply the first pattern of vibration stimulation, set to its initial value, to the user via the wearable device 10 for teeth grinding events that occur after the predetermined time (5 seconds).

[0059] As another example, the user stimulation correction unit 142 may include a fixed pattern correction mode that increases the vibration stimulation intensity of the first pattern by one level at a time, thereby providing the user with the same level of stimulation for a predetermined period of time, and a variable pattern correction mode that corrects the vibration stimulation intensity of the first pattern so that it is variable within the predetermined period of time.

[0060] For example, if the user terminal 20 receives input of a minimum stimulation intensity of 3 levels and a maximum stimulation intensity of 6 levels, the fixed pattern correction mode can be applied to correct the vibration stimulation of the first pattern so that it is varied to any value between 3 and 6 levels for a predetermined unit time (e.g., 0.5 seconds) for a predetermined period of time and provided to the user.

[0061] Therefore, by providing the user with vibration stimuli that vary from weak to strong, rather than fixed-size vibration stimuli, it is possible to induce more effective regulation of the autonomic nervous system.

[0062] On the other hand, the teeth grinding diagnostic unit 130 can determine whether or not teeth grinding is occurring from the second electromyogram data collected via the data acquisition unit 120, even while vibration stimuli generated via the biofeedback generation unit 140 are being applied to the user.

[0063] Therefore, all electromyographic data related to the user's teeth grinding can be collected without any data loss, enabling more accurate teeth grinding diagnosis and customized biofeedback.

[0064] On the other hand, referring to Figure 9, the user monitoring unit 150 may include a user data generation unit 151 that measures the user's daily sleep time and generates daily user data including at least one of the following: the number of times teeth grinding occurred during the daily sleep time, the degree of teeth grinding, the duration of teeth brushing, the number of times vibration stimulation occurred, and the maximum intensity of vibration stimulation; a teeth grinding diagnosis learning unit 152 that learns the number of times teeth grinding occurred during the daily sleep time, the duration of teeth grinding, and the maximum intensity of vibration stimulation included in the daily user data via a pre-configured artificial intelligence learning algorithm, and optimizes the teeth grinding diagnosis criteria of the teeth grinding diagnosis unit based on the result data derived via the artificial intelligence learning algorithm; and a user data transmission unit 153 that transmits the daily user data generated by the user data generation unit 151 to the user terminal 20 based on a request signal received from the user terminal 20.

[0065] For example, the bruxism diagnostic learning unit 152 can optimize the time range of the window mask using one of the mean, median, or mode of the bruxism duration included in the daily user data.

[0066] Furthermore, the degree of teeth grinding of the user can be calculated based on the second electromyogram data, and the magnitude of V_th2 can be corrected based on the degree of teeth grinding.

[0067] Therefore, the degree of teeth grinding is classified into "strong," "average," and "weak," and if the user's degree of teeth grinding is calculated to be "weak," the size of V_th2 can be reduced to guide the user towards an optimized teeth grinding diagnosis and alleviation of teeth grinding symptoms through biofeedback.

[0068] As another example, the bruxism diagnosis learning unit 152 verifies the bruxism diagnosis of the bruxism diagnosis unit 140. It can improve the accuracy of the bruxism diagnosis of the bruxism diagnosis unit 140 by utilizing a correct classification dataset that "judges bruxism as bruxism" and "judges non-bruxism as non-bruxism," and a misclassification dataset that "judges bruxism as non-bruxism" and "judges non-bruxism as bruxism."

[0069] According to the present invention as described above, electromyographic data of the muscles around the user's face and head is collected via a wearable device attached to the user's skin, and based on the collected electromyographic data, it is determined whether the user is sleeping and whether or not a teeth grinding event is occurring. This makes it possible to provide a biofeedback-based teeth grinding relief system and method that can more effectively detect whether or not a teeth grinding event is occurring in the user during sleep.

[0070] Furthermore, a biofeedback-based bruxism relief system and method can be provided that receives input of the minimum intensity of vibration stimulation provided via a wearable device through a user terminal, and gradually increases the intensity of the stimulation from the minimum vibration stimulation input via the user terminal, thereby providing a biofeedback stimulus signal optimized for the user, and more effectively interfering with and alleviating bruxism symptoms.

[0071] Furthermore, by collecting and storing user sleep patterns and bruxism event information, it is possible to collect user-specific data, build bruxism learning data based on this data, and provide a biofeedback-based bruxism reduction system and method that can quickly calculate user-customized biofeedback data.

[0072] Furthermore, a control method for a biofeedback-based bruxism relief system according to one embodiment of the present invention may be recorded on a computer-readable medium containing program instructions for performing actions that can be implemented on various computers. The computer-readable medium may include program instructions, data files, data structures, etc., individually or in combination. The medium may also contain program instructions that are specifically designed and configured for the present invention or that are publicly known and usable by 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 instructions, such as ROMs, RAMs, and flash memory. Examples of program instructions include not only machine code, such as that produced by a compiler, but also high-level language code that can be executed by a computer using an interpreter, etc.

[0073] As described above, although one embodiment of the present invention has been explained by limited embodiments and drawings, one embodiment of the present invention is not limited to the embodiments described above, and various modifications and variations can be made from such descriptions by those with ordinary skill in the art to which the invention pertains. Accordingly, one embodiment of the present invention should be understood solely by the claims described below, and all equivalent or equivalent variations thereof fall within the scope of the spirit of the invention. [Explanation of Symbols]

[0074] 10: Wearable devices 20: User terminal 30:DB 110: User Recognition Unit 120: Data Collection Department 121: First Sensor 122: Second sensor 130: Bruxism Diagnosis Department 131: Sleep state assessment unit 132: Teeth grinding detection unit 140: Biofeedback generation unit 141: User stimulus generation unit 142: User Stimulus Correction Unit 150: User Monitoring Department 151: User Data Generation Unit 152: Teeth Grinding Learning Diagnostic Department 153: User data transfer section

Claims

1. A user recognition unit receives a teeth grinding diagnosis request signal generated from at least one of the previously designated user terminals and wearable devices attached to the user's skin, extracts a unique number assigned to the wearable device included in the teeth grinding diagnosis request signal, and retrieves user information corresponding to the unique number from a previously designated database. A data acquisition unit that receives electromyogram data collected from at least one sensor provided in the wearable device, A teeth grinding diagnosis unit that determines whether the electromyogram data collected from the data acquisition unit satisfies pre-set conditions and diagnoses whether teeth grinding occurs, If the teeth grinding diagnostic unit determines that teeth grinding has occurred, a biofeedback generation unit applies vibration stimulation to the user's skin via a vibration motor provided in the wearable device. The system includes a user monitoring unit that monitors the user's teeth grinding symptoms based on teeth grinding diagnostic data derived from the teeth grinding diagnostic unit and vibration stimulation data generated by the biofeedback generation unit, The aforementioned data acquisition unit, A first sensor that collects first electromyogram data during a pre-set time period, The system includes a second sensor provided at a predetermined distance from the first sensor for collecting second electromyogram data, The aforementioned teeth grinding diagnostic unit is, A sleep state determination unit that determines the user's sleep state by comparing the first electromyogram data collected via the first sensor with a pre-set first reference voltage V_th1, The sleep state determination unit determines that the user is asleep, and the unit includes a teeth grinding occurrence detection unit that compares the second electromyogram data collected via the second sensor with a previously set second reference voltage V_th2 to determine whether or not a teeth grinding event has occurred in the user. The teeth grinding detection unit is, A window mask is generated for a pre-set time range, and the window mask is superimposed on the second electromyogram data to determine whether or not the teeth grinding event occurred. Within the window mask, the presence or absence of the teeth grinding event is determined based on the time that the second electromyogram data exceeds V_th2. The biofeedback generation unit is When the teeth grinding occurrence detection unit determines that the teeth grinding event has occurred, the user stimulus provision unit generates a first pattern of vibration stimulus at T_winend, which is the time when the window mask ends, and provides the first pattern of vibration stimulus to the user via the wearable device. The system includes a user stimulation correction unit that corrects the first vibration stimulation pattern if a teeth grinding event is detected via the teeth grinding diagnostic unit within a predetermined time range after the first pattern of vibration stimulation has ended. The first pattern is, The initial value of the vibration stimulus is determined based on the minimum stimulus intensity set from the user terminal. A biofeedback-based bruxism relief system in which the intensity of the vibration stimulus is corrected step by step via the user stimulus correction unit.

2. The aforementioned user monitoring unit, A user data generation unit measures the user's daily sleep duration and generates daily user data that includes at least one of the following: the number of times teeth grinding occurred during the daily sleep duration, the duration of teeth grinding, the degree of teeth grinding, the number of times vibration stimuli were generated, and the maximum intensity of vibration stimuli. A biofeedback-based bruxism reduction system according to claim 1, comprising: a user data transmission unit that transmits the daily user data generated by the user data generation unit based on a request signal received from the user terminal to the user terminal.

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