Biofeedback-based bruxism alleviation system and method therefor

Abstract

Disclosed are a biofeedback-based bruxism alleviation system and a method therefor. According to the present invention, electromyogram data regarding muscles around the face and head of a user is collected through a wearable device attached to the skin of the user, and it is determined whether or not the user sleeps and whether or not a bruxism event occurs on the basis of the collected electromyogram data, thereby more effectively detecting whether or not a bruxism event occurs to the sleeping user.

Description

Biofeedback-based bruxism relief system and method thereof

[0001] The present invention relates to a bruxism diagnosis and relief system, and more particularly, to a biofeedback-based bruxism relief system and method thereof, which diagnoses bruxism symptoms by analyzing temporalis muscle signals of a sleeping user and provides a biofeedback signal including vibration stimulation to the user to relieve bruxism symptoms.

[0002] Recently, various sleep disorders and sleep disorders have been identified based on physiological and physical signals from the body of the subject during sleep, and based on these signals, diagnosis and treatment directions for sleep problems have been established, and specific treatment methods such as drug therapy, cognitive behavioral correction, and surgical procedures have been proposed.

[0003] For reference, brain waves are used as basic data to understand the progression and structure of sleep, eye movement measurements are useful for determining sleep stages, and electromyography (EMG) must be measured because muscle tension varies depending on the sleep stage. In particular, leg EMG is measured to diagnose a sleep disorder called periodic limb movement disorder, and jaw EMG is also necessary to identify bruxism.

[0004] In particular, in the case of bruxism, it includes clenching or grinding the teeth due to strong jaw movements other than chewing or swallowing movements, and usually grinding the teeth with 2 to 10 times more force than when chewing food. Teeth grinding mainly occurs during sleep, but there are also cases of grinding teeth during the day.

[0005] Bruxism is known to affect approximately 10% of the Korean population, and it often occurs in sensitive and psychologically unstable situations, often triggered by stress. Other contributing factors include malocclusion, poorly aligned teeth, alcohol consumption, genetics, certain medications, and central nervous system disorders.

[0006] Bruxism partially damages the periodontal tissues because strong force is applied to the teeth, and the surface of the teeth is worn down due to wear and tear, and the tissues around the teeth are damaged, causing teeth to feel sensitive when eating cold food, and in severe cases, the teeth may even become loose.

[0007] Bruxism can be treated professionally at a hospital, including psychological therapy, the installation of occlusal stabilization devices between the upper and lower teeth, or medication.

[0008] Recently, there is a demand for a device that can easily diagnose and prevent bruxism during sleep at home. As one of the technologies for such a bruxism diagnosis method, Korean Patent Publication No. 10-1621500 discloses a bruxism and teeth clenching analysis device and method that is mounted on the head of the examinee to detect and output a tilt signal according to a change in sleeping posture and an electromyography signal generated by the examinee's bruxism and teeth clenching, and when a treatment signal is received from an analysis terminal, a preset sleeping posture correction signal is output. However, there is a limit to accurately diagnosing the symptoms of bruxism and teeth clenching, and there is a problem that the treatment effect for bruxism and teeth clenching is minimal in that it does not have a significant awakening effect during sleep.

[0009] Therefore, in order to solve the above problems, research on a biofeedback-based bruxism relief system and method is necessary.

[0010] The present invention aims to provide a biofeedback-based bruxism relief system and method capable of more effectively detecting whether a bruxism event occurs in a sleeping user by collecting electromyography data on muscles around the user's face and head through a wearable device attached to the user's skin and determining whether the user is sleeping and whether a bruxism event occurs based on the collected electromyography data.

[0011] In addition, the purpose is to provide a biofeedback-based bruxism relief system and method that can more effectively interfere with and alleviate bruxism symptoms by inputting the minimum intensity of vibration stimulation to be provided through a wearable device through a user terminal and gradually increasing the intensity of stimulation from the minimum vibration stimulation input through the user terminal, thereby providing an optimized biofeedback stimulation signal to the user.

[0012] In addition, the purpose is to provide a biofeedback-based bruxism relief system and method that can quickly produce user-customized biofeedback data by collecting and storing user-specific data and constructing bruxism learning data based on the collected data, thereby collecting and storing user-specific sleep status and bruxism event information.

[0013] 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 pertains from the description below.

[0014] A biofeedback-based bruxism relief system according to an embodiment of the present invention includes 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 calls user information corresponding to the unique number from a pre-designated database, a data collection unit that receives electromyography data collected from at least one sensor provided in the wearable device, a bruxism diagnosis unit that determines whether the electromyography data collected from the data collection unit satisfies a pre-designated condition and diagnoses whether bruxism has occurred, a biofeedback generation unit that applies a vibration stimulus to the user's skin via a vibration motor provided in the wearable device when 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 stimulus data generated by the biofeedback generation unit.

[0015] In addition, the data collection unit includes a first sensor that collects first electromyography data for a preset period of time and a second sensor that is provided at a preset interval from the first sensor and collects second electromyography data, and the bruxism diagnosis unit includes a sleep state determination unit that compares the first electromyography data collected through the first sensor with a preset first reference voltage, V_th1, to determine the sleep state of the user, and a bruxism occurrence detection unit that compares the second electromyography data collected through the second sensor with a preset second reference voltage, V_th2, to determine whether a user's bruxism event has occurred when the sleep state determination unit determines that the user is sleeping.

[0016] In addition, the bruxism occurrence detection unit generates a window mask in a preset time range, and determines whether a bruxism event has occurred by superimposing the window mask on the second electromyography data, and determines whether a bruxism event has occurred based on a time during which the second electromyography data exceeds V_th2 within the window mask, and the biofeedback generation unit generates a vibration stimulus of a first pattern at T_winend, which is a time when the window mask ends, when the bruxism occurrence detection unit determines that a bruxism event has occurred, and includes a user stimulus providing unit that provides the vibration stimulus of the first pattern to the user through a wearable device, and a user stimulus correction unit that corrects the second electromyography data collected through the data collection unit after the vibration stimulus of the first pattern has been generated and the vibration stimulus of the first pattern collected through the data collection unit before the vibration stimulus of the first pattern is generated, wherein the first pattern is characterized in that an initial value of the vibration stimulus is determined based on a minimum stimulus intensity set from a user terminal, and the intensity of the vibration stimulus is corrected by one level through the user stimulus correction unit.

[0017] In addition, the bruxism diagnosis unit determines whether to use electromyography data collected from the first sensor and the second sensor based on a bruxism diagnosis mode input from a user terminal, wherein the bruxism diagnosis mode includes a first diagnosis mode in which a sleep state of the user is determined through a sleep state determination unit, and if the user is determined to be sleeping, a bruxism occurrence detection unit determines whether a user's bruxism event has occurred, and a second diagnosis mode in which a preset sleep waiting time is counted, and if the sleep waiting time is exceeded, the user is automatically determined to be sleeping, and if the sleep waiting time is exceeded, a bruxism occurrence detection unit determines whether a user's bruxism event has occurred.

[0018] In addition, 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 including at least one of the number of times of bruxism occurred during the daily sleep time, the duration of bruxism, the number of times of vibration stimulation generated, and the maximum intensity of vibration stimulation; a bruxism diagnosis learning unit that learns the number of times of bruxism occurred during the daily sleep time, the duration of bruxism, and the maximum intensity of vibration stimulation included in the daily user data through a preset artificial intelligence learning algorithm, and optimizes the bruxism diagnosis criteria of the bruxism 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.

[0019] According to the present invention, electromyography data on the muscles around the user's face and head is collected through a wearable device attached to the user's skin, and based on the collected electromyography data, it is determined whether the user is sleeping and whether a bruxism event has occurred, thereby having the effect of more effectively detecting whether a bruxism event has occurred in a sleeping user.

[0020] In addition, by inputting the minimum intensity of vibration stimulation to be provided through a wearable device through a user terminal and gradually increasing the intensity of the stimulation from the minimum vibration stimulation input through the user terminal, it is possible to provide an optimized biofeedback stimulation signal to the user and more effectively prevent and alleviate bruxism symptoms.

[0021] In addition, by collecting and storing the user's sleep status and bruxism event information, it has the effect of collecting user-specific data and constructing bruxism learning data based on the collected data, thereby quickly producing user-customized biofeedback data.

[0022] Figures 1 and 2 are diagrams of a biofeedback-based bruxism relief system according to an embodiment of the present invention.

[0023] FIG. 3 is a drawing for explaining a data collection unit of a biofeedback-based bruxism relief system according to an embodiment of the present invention.

[0024] FIG. 4 is a drawing for explaining a bruxism diagnosis unit of a biofeedback-based bruxism relief system according to an embodiment of the present invention.

[0025] FIGS. 5 to 8 are drawings for explaining a biofeedback generation unit of a biofeedback-based bruxism relief system according to an embodiment of the present invention.

[0026] FIG. 9 is a drawing for explaining a user monitoring unit of a biofeedback-based bruxism relief system according to an embodiment of the present invention.

[0027] Specific details, including the problems to be solved, means of solving them, and effects of the invention, are included in the embodiments and drawings described below. The advantages and features of the present invention, and methods for achieving them, will become clearer with reference to the embodiments described below in detail, along with the accompanying drawings.

[0028] 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.

[0029] Hereinafter, the title of the invention of the present invention is described in detail with reference to the attached drawing 1.

[0030]

[0031] FIG. 1 is a diagram illustrating a configuration of a biofeedback-based bruxism relief system according to an embodiment of the present invention, FIG. 1 and FIG. 2 are diagrams illustrating a configuration of a biofeedback-based bruxism relief system according to an embodiment of the present invention, FIG. 3 is a diagram illustrating a data collection unit of a biofeedback-based bruxism relief system according to an embodiment of the present invention, FIG. 4 is a diagram illustrating a bruxism diagnosis unit of a biofeedback-based bruxism relief system according to an embodiment of the present invention, FIGS. 5 to 8 are diagrams illustrating a biofeedback generation unit of a biofeedback-based bruxism relief system according to an embodiment of the present invention, and FIG. 9 is a diagram illustrating a user monitoring unit of a biofeedback-based bruxism relief system according to an embodiment of the present invention.

[0032]

[0033] Example 1

[0034] Referring to FIGS. 1 and 2, a biofeedback-based bruxism relief system (100) according to an embodiment of the present invention collects electromyography data necessary for bruxism diagnosis through a wearable device (10) attached to the user's skin or mounted on one side of the user's head, and the electromyography data collected through the wearable device (10) is transmitted to the biofeedback-based bruxism relief system (100), and the bruxism relief system (100) analyzes the electromyography data to diagnose the user's bruxism symptoms and generates a biofeedback signal capable of alleviating the bruxism symptoms in response to the diagnosis result. 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 a vibration stimulus to the user.

[0035] Accordingly, by providing biofeedback such as vibration stimulation to the user, the function of the user's autonomic nervous system can be regulated, thereby inducing the user to actively alleviate the bruxism symptom.

[0036] In addition, data on the user's bruxism symptoms generated through the biofeedback-based bruxism relief system (100) may be transmitted to a user terminal (20) linked to the wearable device (10). In addition, data transmitted to the user terminal (20) based on a request signal received from the user terminal (10) may be stored in a pre-designated DB (30).

[0037]

[0038] *

[0039] More specifically, the biofeedback-based bruxism relief system (100) may include a user recognition unit (110), a data collection unit (120), a bruxism diagnosis unit (130), a biofeedback generation unit (140), and a user monitoring unit (150).

[0040] The user recognition unit (110) may receive a bruxism diagnosis request signal generated from at least one of a pre-designated user terminal (20) and a wearable device (10) attached to the user's skin, extract a unique number assigned to the wearable device (10) included in the bruxism diagnosis request signal, and call up user information corresponding to the unique number from a pre-designated DB (30).

[0041] In addition, the data collection unit (120) receives electromyography data collected from at least one sensor provided in the wearable device (10), the bruxism diagnosis unit (130) diagnoses whether bruxism has occurred by determining whether the electromyography data collected from the data collection unit (120) satisfies a preset condition, and the biofeedback generation unit (140) applies a vibration stimulus to the user's skin through a vibration motor provided in the wearable device (10) when the bruxism diagnosis unit (130) determines that bruxism has occurred, and the user monitoring unit (150) can monitor the user's bruxism symptoms based on the bruxism diagnosis data derived from the bruxism diagnosis unit (130) and the vibration stimulus data generated by the biofeedback generation unit (140).

[0042]

[0043]

[0044] *More specifically, as illustrated in FIG. 3, the data collection unit (120) may include a first sensor (121) that collects first electromyography data for a preset period of time and a second sensor (122) that is provided at a preset interval from the first sensor (121) and collects second electromyography data.

[0045] 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.

[0046] When the wearable device (10) is attached to one side of the user's temple, electromyography data of the user's face can be collected through the first sensor (121) and the second sensor (122) provided on the wearable device (10).

[0047] For example, the first sensor (121) can collect the user's eye electromyography signal, and the second sensor (122) can collect the user's temporalis electromyography signal.

[0048]

[0049] Meanwhile, referring to FIG. 4, the bruxism diagnosis unit (130) may include a sleep state determination unit (131) that compares the first electromyography data collected through the first sensor (121) with a preset first reference voltage, V_th1, to determine the sleep state of the user, and a bruxism occurrence detection unit (132) that compares the second electromyography data collected through the second sensor (122) with a preset second reference voltage, V_th2, to determine whether a bruxism event of the user has occurred when the sleep state determination unit (131) determines that the user is sleeping.

[0050] At this time, the bruxism diagnosis unit (130) determines whether to use the data collected from the first sensor (121) and the second sensor (122) based on the bruxism diagnosis mode input to the user terminal (20), wherein the bruxism diagnosis mode may include a first diagnosis mode in which the sleep state of the user is determined through the sleep state determination unit (131), and if the user is determined to be sleeping, the bruxism occurrence detection unit (132) determines whether the user's bruxism event has occurred, and a second diagnosis mode in which a preset sleep waiting time is counted, and if the sleep waiting time is exceeded, the user is automatically determined to be sleeping, and if the sleep waiting time is exceeded, the bruxism occurrence detection unit (132) determines whether the user's bruxism event has occurred.

[0051] More specifically, when the bruxism diagnosis mode is set to the first diagnosis mode, electromyography data is collected using both the first sensor (121) and the second sensor (122), but while the first electromyography data is collected through the first sensor (121), the second sensor (122) can be switched to a power saving mode.

[0052] In addition, the sleep state determination unit (131) of the bruxism diagnosis unit (130) can analyze the user's eye movements by comparing the first electromyography data collected through the first sensor (121) with the V_th1.

[0053] For example, the sleep state determination unit (131) generates eye movement data corresponding to a section in which the first electromyography data exceeds V_th1, and compares the eye movement data with the eye movement learning data during sleep stored in the DB (30) to determine the sleep state of the user.

[0054] If the sleep state determination unit (131) determines that the user is sleeping, the first sensor (121) may be switched to power saving mode, and data collection through the first sensor (121) may be stopped.

[0055]

[0056] In addition, when the bruxism diagnosis mode is set to the second diagnosis mode, the first sensor (121) is switched to a power saving mode, and the bruxism diagnosis unit (130) can determine whether the user has bruxism symptoms by using only the second electromyography data collected through the second sensor (121).

[0057]

[0058] That is, in the case of the first diagnosis mode, the user's sleep time can be accurately monitored, and in the process of determining the sleep state through the sleep state determination unit (131), the bruxism occurrence detection unit (132) is switched to a power saving mode, and when the user's sleep state determination is completed, the bruxism occurrence detection unit (132) switches the sleep state determination unit (131) to a power saving mode, thereby improving the battery power efficiency of the wearable device (10), and in the case of the second diagnosis mode, by omitting the data processing process of the sleep state determination unit (131), the speed of the data calculation process can be improved.

[0059]

[0060] Meanwhile, the bruxism occurrence detection unit (132) collects second electromyography data on the movement of the user's temporalis muscle through the second sensor (122), and can determine whether a bruxism event of the user has occurred by comparing the second electromyography data with the V_th2.

[0061] More specifically, as illustrated in FIG. 5, the bruxism occurrence detection unit (132) generates a window mask (510) of a preset time range and superimposes the window mask (510) on the second electromyography data to determine whether the bruxism event has occurred.

[0062] It is possible to determine whether the bruxism event has occurred based on the time during which the second EMG data exceeds the V_th2 within the window mask (510).

[0063] For example, the time range of the above window mask (510) is initially set to 2 seconds, which is a system setting value, and can be optimized through artificial intelligence learning of the user monitoring unit.

[0064]

[0065] As illustrated in FIG. 6, the biofeedback generation unit (140) may include a user stimulus provision unit (141) that generates a first pattern of vibration stimulus at T_winend, which is the time when the window mask (510) ends, when the bruxism occurrence detection unit (132) determines that the bruxism event has occurred, and provides the first pattern of vibration stimulus to the user through the wearable device (10), and a user stimulus correction unit (142) that corrects the first pattern of vibration stimulus when the bruxism event is detected through the bruxism diagnosis unit (130) within a preset time range after the first pattern of vibration stimulus ends.

[0066] For example, if the bruxism diagnosis unit (130) determines that a bruxism event has occurred within 5 seconds after the vibration stimulus of the first pattern ends, the user stimulus correction unit (142) can correct the first pattern so that a stimulus of higher intensity than the intensity of the vibration stimulus of the first pattern is provided to the user.

[0067] At this time, the first pattern determines the initial value of the vibration stimulus based on the minimum stimulus intensity set from the user terminal (20), and the intensity of the vibration stimulus can be corrected by one level through the user stimulus correction unit (142).

[0068] For example, if the intensity of the vibration stimulus is divided into levels 1 to 10 and the initial value of the vibration stimulus is input as level 3 through the user terminal (20), the initial value of the first pattern can be set to level 3 as soon as the wearable device (10) is started (or restarted).

[0069] As illustrated in FIG. 7, when the bruxism diagnosis unit (130) determines that the bruxism event has occurred, the first pattern of vibration stimulation (521) set to an initial value (level 3) is provided to the user through the biofeedback generation unit (140), and when the first pattern of vibration stimulation (521) ends and the bruxism event occurs again within 5 seconds, the user's bruxism symptom cannot be alleviated by the level 3 vibration stimulation, so the user stimulus correction unit (142) can correct the first pattern of vibration stimulation to level 4.

[0070] Accordingly, for the teeth grinding event that occurs within 5 seconds after the vibration stimulus (521) of the first pattern ends, the vibration stimulus (522) of the first pattern corrected to the 4th level can be provided to the user through the wearable device (10).

[0071] Likewise, if the vibration stimulus (522) of the first pattern is terminated and the bruxism event occurs again within 5 seconds, the user's bruxism symptom cannot be alleviated with the vibration stimulus of level 4, so the user stimulus correction unit (142) can correct the vibration stimulus of the first pattern to level 5.

[0072] At this time, the vibration stimulus of the first pattern can be corrected to the maximum level of the vibration stimulus, which is level 10, and if the teeth grinding event occurs again within 5 seconds even after the vibration stimulus of the first pattern is corrected to level 10, the user stimulus correction unit (142) may stop the correction of the vibration stimulus of the first pattern and transmit a wake-up notification signal to the user terminal (20) to induce the user to wake up.

[0073] In addition, depending on the settings of the user terminal, a wake-up notification signal may be transmitted to the user terminal after the first pattern is corrected to level 10, and after two corrections, the correction of the vibration stimulus of the first pattern may be stopped and a wake-up notification signal may be immediately transmitted to the user terminal (20) to induce the user to wake up.

[0074]

[0075] Meanwhile, as illustrated in FIG. 8, if the bruxism event does not occur within the preset time (5 seconds) after the vibration stimulus of the first pattern is applied to the user, the user stimulus correction unit (142) does not perform correction for the vibration stimulus of the first pattern, so the user stimulus generation unit (141) can apply the vibration stimulus of the first pattern, which is set as the initial value, to the user through the wearable device (10) for the bruxism event that occurs after the preset time (5 seconds).

[0076]

[0077] As another example, the user stimulus compensation unit (142) may include a fixed pattern compensation mode that increases the vibration stimulus intensity of the first pattern by a fixed level by one and provides the same size of stimulus to the user for a preset period of time, and a variable pattern compensation mode that compensates the vibration stimulus intensity of the first pattern so that it varies within the preset period of time.

[0078] For example, when the minimum stimulus intensity is input as level 3 and the maximum stimulus intensity is input as level 6 from the user terminal (20), the fixed pattern correction mode is applied so that the vibration stimulus of the first pattern can be corrected to vary to a random value within level 3 to level 6 for a preset unit time (e.g., 0.5 seconds) and provided to the user during the preset time.

[0079] Therefore, by providing the user with a vibration stimulus that varies from weak to strong rather than a fixed size vibration stimulus, more effective control of the autonomic nervous system can be induced.

[0080]

[0081] Meanwhile, the bruxism diagnosis unit (130) can determine whether bruxism has occurred based on the second electromyography data collected through the data collection unit (120) while the vibration stimulus generated through the biofeedback generation unit (140) is applied to the user.

[0082] Therefore, all of the user's bruxism-related electromyography data can be collected without data omission, and more accurate bruxism diagnosis and customized biofeedback can be provided.

[0083]

[0084] Meanwhile, referring to FIG. 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 number of times the user bruxes during the daily sleep time, the degree of the bruxing, the duration of the bruxing, the number of times the user bruxes during the daily sleep time, the maximum intensity of the vibration stimulus, and the maximum intensity of the vibration stimulus; a bruxism diagnosis learning unit (152) that learns the number of times the user bruxes during the daily sleep time, the duration of the bruxing, and the maximum intensity of the vibration stimulus included in the daily user data through a preset artificial intelligence learning algorithm, and optimizes the bruxism diagnosis criteria of the bruxism diagnosis unit based on the result data derived through 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).

[0085] For example, the bruxism diagnosis learning unit (152) can optimize the time range of the window mask by using any one of the average, median, and mode of the bruxism duration included in the daily user data.

[0086] In addition, the degree of the user's bruxism can be calculated based on the second electromyography data, and the size of the V_th2 can be corrected based on the degree of the bruxism.

[0087] Accordingly, if the degree of bruxism is classified into 'strong', 'average', and 'weak', and the degree of bruxism of the user is calculated as 'weak', the size of V_th2 can be reduced to induce alleviation of bruxism symptoms through bruxism diagnosis and biofeedback optimized for the user.

[0088]

[0089] As another example, the bruxism diagnosis learning unit (152) verifies the bruxism diagnosis of the bruxism diagnosis unit (140), and utilizes 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', thereby verifying the bruxism diagnosis of the bruxism diagnosis unit (140), and improving the accuracy of the bruxism diagnosis of the bruxism diagnosis unit (140).

[0090]

[0091] According to the present invention as described above, by collecting electromyography data on the muscles around the user's face and head through a wearable device attached to the user's skin, and determining whether the user is sleeping and whether a bruxism event has occurred based on the collected electromyography data, a biofeedback-based bruxism relief system and method can be provided that can more effectively detect whether a bruxism event has occurred in a sleeping user.

[0092] In addition, a biofeedback-based bruxism relief system and method can be provided, which can input the minimum intensity of a vibration stimulus to be provided through a wearable device through a user terminal, and gradually increase the intensity of the stimulus from the minimum vibration stimulus input through the user terminal, thereby providing an optimized biofeedback stimulus signal to the user, and more effectively interfering with and alleviating bruxism symptoms.

[0093] In addition, a biofeedback-based bruxism relief system and method can be provided that can collect user-specific data by collecting and storing user-specific sleep status and bruxism event information, construct bruxism learning data based on the collected data, and quickly produce user-customized biofeedback data.

[0094]

[0095] In addition, a method for controlling a bruxism relief system based on biofeedback according to an embodiment of the present invention may be recorded on a computer-readable medium including program instructions for performing various computer-implemented operations. The computer-readable medium may include program instructions, data files, data structures, etc., alone or in combination. The program instructions 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 the computer-readable recording medium 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 memories. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter, etc.

[0096]

[0097] 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.

[0098]

[0099] 10: Wearable devices

[0100] 20: User terminal

[0101] 30: DB

[0102] 110: User recognition unit

[0103] 120: Data collection unit 121: First sensor

[0104] 122: Second sensor

[0105] 130: Bruxism Diagnosis Section 131: Sleep Status Assessment Section

[0106] 132: Grinding occurrence detection unit

[0107] 140: Biofeedback generation unit 141: User stimulus generation unit

[0108] 142: User Stimulus Compensation Unit

[0109] 150: User monitoring section 151: User data generation section

[0110] 152: Bruxism Learning Diagnostic Department

[0111] 153: User data transmission unit

Claims

1. 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 calls up user information corresponding to the unique number from a pre-designated DB; A data collection unit that receives electromyography data collected from at least one sensor provided in the wearable device; A bruxism diagnosis unit that diagnoses whether bruxism has occurred by determining whether the electromyography data collected from the data collection unit satisfies preset conditions; If the bruxism diagnosis unit determines that bruxism has occurred, a biofeedback generation unit that applies a vibration stimulus to the user's skin through a vibration motor provided in the wearable device; and A biofeedback-based bruxism relief system, comprising 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 from the biofeedback generation unit.

2. In paragraph 1, The above data collection unit, A first sensor that collects first electromyography data for a preset period of time; and A second sensor is provided at a preset distance from the first sensor and collects second electromyography data; The above bruxism diagnosis section is, A sleep state determination unit that determines the user's sleep state by comparing the first electromyography data collected through the first sensor with a preset first reference voltage, V_th1; and A biofeedback-based teeth grinding relief system, characterized in that it includes a teeth grinding occurrence detection unit that compares the second electromyography data collected through the second sensor with a preset second reference voltage, V_th2, to determine whether a teeth grinding event of the user has occurred, when the sleep state determination unit determines that the user is sleeping.

3. In paragraph 2, The above bruxism detection unit, Generate a window mask of a preset time range and superimpose the window mask on the second electromyography data to determine whether the bruxism event has occurred. Determine whether the bruxism event has occurred based on the time during which the second EMG data exceeds the V_th2 within the window mask, The above biofeedback generation unit, When the bruxism occurrence detection unit determines that the bruxism event has occurred, a user stimulus providing unit that generates a vibration stimulus of a first pattern at T_winend, which is the time when the window mask ends, and provides the vibration stimulus of the first pattern to the user through the wearable device; and After the vibration stimulation of the first pattern is terminated, if the bruxism event is detected through the bruxism diagnosis unit within a preset time range, a user stimulus compensation unit for compensating the vibration stimulation of the first pattern is included. The above 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 teeth grinding relief system characterized in that the intensity of the vibration stimulation is corrected by 1 level through the user stimulation correction unit.

4. In paragraph 2, The above bruxism diagnosis section is, Decide whether to use the electromyography data collected from the first sensor and the second sensor based on the bruxism diagnosis mode input from the user terminal, The above bruxism diagnosis mode is, A first diagnostic mode in which the user's sleep state is determined through the sleep state determination unit, and if the user is determined to be sleeping, the user's teeth grinding event is determined through the teeth grinding occurrence detection unit; and A biofeedback-based teeth grinding relief system, characterized by including a second diagnostic mode that counts a preset sleep waiting time, automatically determines that the user is sleeping when the sleep waiting time is exceeded, and determines whether a teeth grinding event of the user has occurred through the teeth grinding occurrence detection unit.

5. In paragraph 1, The above user monitoring unit, A user data generation unit that measures the daily sleep time of the user and generates daily user data including at least one of the number of teeth grindings that occurred during the daily sleep time, the duration of teeth grinding, the degree of teeth grinding, the number of vibration stimulations generated, and the maximum intensity of vibration stimulation; A bruxism diagnosis learning unit that learns the number of times of bruxism occurred during the daily sleep time included in the daily user data, the duration of the bruxism, and the maximum intensity of the vibration stimulus through a preset artificial intelligence learning algorithm, and optimizes the bruxism diagnosis criteria of the bruxism diagnosis unit based on the result data derived through the artificial intelligence learning algorithm; and A biofeedback-based bruxism relief system, characterized in that it comprises 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.

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