Sleep state analysis information and improvement guide provision system, and method thereof.

Abstract

The present invention relates to a sleep state analysis information and improvement guide provision system and method, and more specifically, to a layer unit comprising a plurality of components, a detection unit provided within the layer unit for detecting the user's biometric information, a memory unit for storing the user's biometric information detected by the detection unit, and an analysis unit for analyzing the user's sleep state based on the user's biometric information stored in the memory unit and generating sleep state analysis information for the user.

Description

Technical Field

[0001] The present invention relates to a sleep state analysis information and improvement guide providing system and a method thereof. More specifically, it relates to a sleep state analysis information and improvement guide providing system and a method thereof that analyze the sleep state of a user based on biological information detected while the user is sleeping, provide sleep state analysis information, and provide an improvement guide that can change the sleep state.

Background Art

[0002] InInIn In recent years, as people's living standards and quality of life have improved, interest in "good quality sleep" has increased. In particular, the industry that provides various sleep induction devices or services using the latest science and technology has grown significantly. As a result, many devices and services for improving the quality of sleep, such as sleep care services that guide sleep environments, habits, postures, etc. through consultations with experts, and services that monitor the sleep state by detecting the user's breathing sounds, etc. when wearing a wearable device, have been commercialized. Specifically, information such as the user's physical information, status information, and sleep habits is input, or information such as the user's status information and sleep habits is collected through individual devices that are connected to the user in contact or non-contact, and various devices and services that function to induce "good quality sleep" based on such user information have been developed. Through this, the sleep state can be induced based on the status information for each user.

[0003] However, accurately understanding a user's sleep state requires equipment to measure the user's state information and biometric data. This necessitates the user wearing additional equipment, which inevitably causes inconvenience during sleep. Furthermore, conventionally, when the results of monitoring a user's sleep state via such equipment are provided to the user, they are presented as information such as whether they are asleep or not, and the duration of each sleep and non-sleep state. This format of information makes it difficult for users to understand the specifics of their own sleep state and to conceive concrete measures to improve their sleep.

[0004] This invention was proposed to overcome the limitations of the prior art, and aims to provide a sleep state analysis information and improvement guide provision system and method that can more accurately analyze a user's sleep state based on biometric information detected while the user is sleeping, within a range that does not disturb the user's sleep, and provide an improvement guide that can change the user's sleep state. [Overview of the Initiative] [Problems that the invention aims to solve]

[0005] The present invention aims to provide a sleep state analysis information and improvement guide provision system and method that can more accurately analyze a user's sleep state and provide analysis information based on biological information detected while the user is sleeping, within a range that does not disturb the user's sleep.

[0006] Furthermore, the present invention aims to provide a sleep state analysis information and improvement guide provision system and method that can analyze and provide information on a user's sleep state in either a short-term or long-term manner.

[0007] Furthermore, the present invention aims to provide a sleep state analysis information and improvement guide provision system, as well as a method thereof, which can provide an improvement guide that can change the sleep state of a user by referring to the detected user biometric information.

[0008] It should be noted that the technical problems of the present invention are not limited to those mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0009] The sleep state analysis information and improvement guide provision system according to the present invention includes at least one layer section comprising a plurality of components; a detection unit provided within the layer section for detecting the user's biometric information; a memory unit for storing the user's biometric information detected by the detection unit; and an analysis unit for analyzing the user's sleep state based on the user's biometric information stored in the memory unit and generating sleep state analysis information for the user.

[0010] Furthermore, in the sleep state analysis information and improvement guide provision system according to the present invention, the detection unit is characterized in that it includes at least one of the following: a pressure sensor, a vibration sensor, a position sensor, an acoustic sensor, an infrared sensor, a motion sensor, a face recognition sensor, a biometric recognition sensor, and a fingerprint recognition sensor.

[0011] Furthermore, in the sleep state analysis information and improvement guide provision system according to the present invention, the memory unit is characterized in that the user's biometric information collected by the detection unit is mapped and stored for each of multiple users.

[0012] Furthermore, in the sleep state analysis information and improvement guide provision system according to the present invention, the analysis unit is characterized in that it analyzes the user's biological information stored in the memory unit in a short term, calculates the results as numerical indicators, and includes them in the user's sleep state analysis information.

[0013] Furthermore, in the sleep state analysis information and improvement guide provision system according to the present invention, the analysis unit analyzes the user's biological information stored in the memory unit over a long term, determines the user's sleep state type based on the differences in sleep states within the analysis period, and generates the user's sleep state analysis information by including this type of sleep state.

[0014] Furthermore, in the sleep state analysis information and improvement guide provision system according to the present invention, the memory unit is characterized in that the user's sleep state analysis information analyzed by the analysis unit is stored in the memory unit.

[0015] Furthermore, in the sleep state analysis information and improvement guide provision system according to the present invention, the memory unit is characterized in that the sleep state analysis information of users analyzed by the analysis unit is mapped and stored for multiple users.

[0016] Furthermore, in the sleep state analysis information and improvement guide provision system according to the present invention, the analysis unit is characterized in that it generates an improvement guide that can change the user's sleep state based on the user's biological information and the user's sleep state analysis information stored in the memory unit.

[0017] Furthermore, the sleep state analysis information and improvement guide provision system according to the present invention is characterized by further including a feedback receiving unit that monitors the user's actions taken in response to the improvement guide generated by the analysis unit.

[0018] Furthermore, in the sleep state analysis information and improvement guide provision system according to the present invention, the user's improvement guide execution information, which is monitored through the feedback receiving unit, is stored in the memory unit.

[0019] The sleep state analysis information and improvement guide provision method according to the present invention is a sleep state analysis information and improvement guide provision method performed in a sleep state analysis information and improvement guide provision system including a layer unit, a detection unit, a memory unit, and an analysis unit, and includes the steps of: detecting the user's biological information from a detection unit provided in the layer unit; storing the user's biological information detected by the detection unit in the memory unit; and analyzing the user's sleep state based on the user's biological information stored in the memory unit in the analysis unit, thereby generating sleep state analysis information for the user.

[0020] Furthermore, in the sleep state analysis information and improvement guide provision method according to the present invention, the step of detecting the user's biological information from the detection unit is performed by a detection unit that includes at least one of the following sensors: a pressure sensor, a vibration sensor, a position sensor, an acoustic sensor, an infrared sensor, a motion sensor, a face recognition sensor, a biometric recognition sensor, and a fingerprint recognition sensor.

[0021] Furthermore, in the sleep state analysis information and improvement guide provision method according to the present invention, the step of storing the user's biometric information in the memory unit is performed such that the user's biometric information collected by the detection unit is mapped and stored separately for each of the multiple users.

[0022] Furthermore, in the sleep state analysis information and improvement guide provision method according to the present invention, the step of generating the user's sleep state analysis information in the analysis unit is characterized by including the steps of: analyzing the user's biological information stored in the memory unit in a short term; calculating the results of the short-term analysis as numerical indicators; and generating the user's sleep state analysis information by including the calculated numerical indicators.

[0023] Also, in the method for providing sleep state analysis information and improvement guidance according to the present invention, the stage in which the analysis unit generates the sleep state analysis information of the user includes: analyzing the biometric information of the user stored in the memory unit in the long term (Long term); determining the sleep state type of the user based on the differences between sleep states within the analysis period; and generating the determined sleep state type of the user included in the sleep state analysis information of the user. It is characterized by including these steps.

[0024] Also, in the method for providing sleep state analysis information and improvement guidance according to the present invention, after the stage in which the analysis unit generates the sleep state analysis information of the user, it further includes the stage in which the analyzed sleep state analysis information of the user is stored in the memory unit. It is characterized by this.

[0025] Also, in the method for providing sleep state analysis information and improvement guidance according to the present invention, the stage in which the sleep state analysis information of the user is stored in the memory unit is executed such that the sleep state analysis information of the user is mapped and stored for each of a plurality of users. It is characterized by this.

[0026] Also, in the method for providing sleep state analysis information and improvement guidance according to the present invention, after the stage in which the sleep state analysis information of the user is stored in the memory unit, in the analysis unit, based on the biometric information of the user and the sleep state analysis information of the user stored in the memory unit, it further includes the stage of generating an improvement guidance that can change the sleep state of the user. It is characterized by this.

[0027] Also, in the method for providing sleep state analysis information and improvement guidance according to the present invention, after the stage in which the analysis unit generates the improvement guidance, in the feedback receiving unit, it further includes the stage of monitoring the execution information of the user with respect to the improvement guidance generated by the analysis unit. It is characterized by this.

[0028] In addition, in the method for providing sleep state analysis information and improvement guidance according to the present invention, after the step of monitoring the improvement guidance execution information of the user by the feedback receiving unit, the method further includes a step of storing the improvement guidance execution information of the user monitored by the feedback receiving unit in the memory unit.

Effects of the Invention

[0029] According to the present invention, by analyzing the sleep state of the user based on the user's biological information detected by the mattress detection unit while the user is sleeping, the sleep state of the user can be analyzed more accurately within a range that does not interfere with the user's sleep, and analysis information can be provided.

[0030] In addition, according to the present invention, by analyzing the sleep state of the user based on the detected user biological information in the short term (Short term) and providing it as a numerical index, the degree to which the user's activities are affected after sleep can be intuitively recognized.

[0031] Furthermore, according to the present invention, by analyzing the sleep state of the user based on the detected user biological information in the long term (Long term) and providing it including differences in sleep states within a period, the sleep type information of the user can be provided together.

[0032] In addition, according to the present invention, an improvement guide that can change the sleep state of the user can be provided by referring to the detected user biological information and the analyzed sleep state analysis information of the user.

[0033] On the other hand, the effects of the present invention are not limited to those mentioned above, and other technical effects not mentioned can be clearly understood by those skilled in the art from the following description.

Brief Description of the Drawings

[0034] [Figure 1]This is a diagram illustrating a sleep state analysis information and improvement guide provision system according to an embodiment of the present invention. [Figure 2] This figure provides a more detailed explanation of the memory section of the sleep state analysis information and improvement guide provision system according to an embodiment of the present invention. [Figure 3] This figure illustrates a sleep state analysis information and improvement guide provision system according to another embodiment of the present invention. [Figure 4] This figure illustrates a method for providing sleep state analysis information and improvement guides according to an embodiment of the present invention. [Figure 5] This is a diagram illustrating a method for providing sleep state analysis information according to one embodiment of the present invention. [Figure 6] This figure illustrates in more detail the method for providing sleep state analysis information according to one embodiment of the present invention. [Figure 7] This is a diagram illustrating a method for providing sleep state analysis information according to one embodiment of the present invention. [Figure 8] This figure illustrates in more detail the method for providing sleep state analysis information according to one embodiment of the present invention. [Figure 9] This figure illustrates a method for providing sleep state analysis information and improvement guides according to another embodiment of the present invention. [Figure 10] This figure illustrates a method for providing sleep state analysis information and improvement guides according to yet another embodiment of the present invention. [Figure 11] This figure shows the sleep type calculated in a system according to one embodiment of the present invention. [Modes for carrying out the invention]

[0035] Details regarding the object, technical configuration, and associated effects of the present invention will be more clearly understood by the following detailed description based on the drawings attached to the specification of the present invention. Embodiments according to the present invention will be described in detail with reference to the attached drawings.

[0036] The embodiments disclosed herein should not be construed as limiting the scope of the invention. For a person ordinary in the art, the description, including the embodiments described herein, will naturally have a variety of applications. Therefore, any embodiments described in the detailed description of the invention are illustrative for better illustrating the invention and are not intended to limit the scope of the invention.

[0037] The functional blocks shown in the drawings and described below are merely examples of possible embodiments. Other functional blocks may be used in other embodiments, without departing from the spirit and scope of the detailed description. Furthermore, although one or more functional blocks of the present invention are shown as separate blocks, one or more of the functional blocks of the present invention may be a combination of various hardware and software configurations that perform the same function.

[0038] Furthermore, expressions indicating the inclusion of a certain component are "open" expressions, merely indicating the existence of that component and should not be understood as excluding additional components. Moreover, when a component is referred to as being "linked" or "connected" to another component, it may be directly linked or connected to that other component, but it should be understood that other components may exist in between.

[0039] Figure 1 is a diagram illustrating a sleep state analysis information and improvement guide provision system according to an embodiment of the present invention.

[0040] Referring to Figure 1, the sleep state analysis information and improvement guide provision system 100 according to the present invention includes at least one layer section 110 having a plurality of components, a detection unit 120 provided within the layer section 110 for detecting the user's biological information, a memory unit 130 for storing the user's biological information detected by the detection unit 120, and an analysis unit 140 for analyzing the user's sleep state based on the user's biological information stored in the memory unit 130 and generating sleep state analysis information for the user.

[0041] The layer portion 110 can be understood as a member having a accommodating space on which components described later can be placed, and as long as it has an accommodating space, there are no limitations on the material or shape of the layer portion 110. The layer portion 110 may be a space on which the user sleeps, such as a mattress, or it may be one of the multiple surfaces that make up a mattress. Furthermore, the layer portion 110 may be a mat that can be placed on a mattress, and it may be a component made of wood or metal rather than a surface made of fiber. Thus, as long as the layer portion 110 has a certain accommodating space, there are no limitations on its material or shape. However, in this detailed description, in order to aid in understanding the invention, we will continue the explanation assuming that the layer portion 110 is a mattress.

[0042] The detection unit 120 is provided within the layer unit 110 and plays a role in detecting the user's biological information. The detection unit 120 may be provided in a form that can be attached to and detached from the surface or inside the layer unit, or it may be composed of various wearable devices that can be attached to and detached directly or indirectly by the user on their body. It can be provided in a variety of forms and positions, and as long as it can detect the user's biological information without disturbing the user's sleep while the user is sleeping, its form, type, position, number, arrangement, etc., are not limited to embodiments of the present invention.

[0043] Furthermore, the detection unit 120 may include at least one of several diverse types of sensors, such as pressure sensors, vibration sensors, position sensors, acoustic sensors, infrared sensors, motion sensors, face recognition sensors, biometric recognition sensors, and fingerprint recognition sensors. Specifically, the detection unit 120 can acquire state information such as heart rate, respiratory status, and body movement status by detecting the user's weight and position information via the pressure sensor, or by detecting the user's vibration signal via the vibration sensor. The detection unit 120 can also recognize the user's voice or detect snoring sounds via the acoustic sensor, and can further receive body movement information by detecting the user's gestures via the motion sensor.

[0044] Thus, the detection unit 120 of the present invention is configured to detect various biometric information of the user located on the layer unit 110, and the type, number, layout, etc. of sensors used to detect more precise and specific user biometric information are not limited to the embodiments of the present invention. That is, the detection unit 120 of the present invention may include a configuration in which one or more of these various types of sensors are combined, and the user biometric information detected via the detection unit 120 can be transmitted to the memory unit 130 of the sleep state analysis information and improvement guide provision system 100 of the present invention via a communication unit (not shown).

[0045] The memory unit 130 is configured to store user biometric information detected by the detection unit 120, and may be built into the sleep state analysis information and improvement guide provision system 100 of the present invention, or it may be an external device connected to the sleep state analysis information and improvement guide provision system 100 via a communication method such as wired or wireless.

[0046] Here, the memory unit 130 can store user biometric information detected by the detection unit 120, mapped to each of multiple users. For example, the memory unit 130 can store physical information such as user A's height and weight, or identification information that allows multiple users to be mutually identified, mapped to each user. Furthermore, it can store collected biometric information such as user A's face information, voice information, and heart rate information, mapped to each user. The memory unit 130 is specifically shown in Figure 2, and a description of Figure 2 will follow later.

[0047] The analysis unit 140 analyzes the user's sleep state based on the user's biometric information stored in the memory unit 130 and generates sleep state analysis information for the user. The analysis unit 140 can be understood as a central processing unit on which predetermined data analysis and calculation processes are performed. The central processing unit may also be called a controller, microcontroller, microprocessor, or microcomputer. Furthermore, the central processing unit may be implemented by hardware, firmware, software, or a combination thereof. If implemented by hardware, it may consist of application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), etc. If implemented by firmware or software, the firmware or software may be configured to include modules, procedures, or functions that perform the above-mentioned functions or actions. The present invention is not interpreted as being limited to such embodiments of the implementation form and data processing method of the analysis unit 140.

[0048] The analysis unit 140 analyzes at least one piece of user biometric information stored in the memory unit 130 and generates sleep state analysis information for the user. More specifically, the analysis can analyze the user's sleep state through the user's heart rate information (e.g., heart rate variability), respiratory rate information (e.g., respiratory rate variability), pulse rate information, body movement information, sound information, etc., stored in the memory unit 130.

[0049] For example, the analysis unit 140 of the present invention can analyze state information such as the user's lying position, turning over, and getting up (such as getting off the mattress) through information detected by the pressure sensor of the detection unit 120, analyze the user's heart rate information, respiratory rate information, body movement information, etc. through information detected by the vibration sensor of the detection unit 120, and further analyze sound information such as snoring by detecting various sounds of the user with the acoustic sensor of the detection unit 120. As a result, the analysis unit 140 of the present invention can analyze sleep states such as heart rate variability, respiratory rate variability, and whether or not the user is awake (getting off the mattress) based on the various information of the user detected by the detection unit 120.

[0050] Furthermore, the analysis unit 140 can also analyze the user's sleep state in stages. When analyzing sleep stages, various parameters can be used, such as total recording time (TRT), total sleep time (TST), time in bed (TIB), sleep latency (SL), REM sleep latency (RL), wake after sleep onset (WASO), sleep efficiency (SE), duration of each sleep stage, and percentage of each sleep stage. The following describes how to actually calculate some of these parameters.

[0051] Formulas 1 and 2 are formulas for calculating SE and SEw according to one embodiment of the present invention.

[0052]

number

[0053] On the other hand, Equation 2 is an equation for calculating weighted sleep efficiency (SEw) according to one embodiment of the present invention. While the efficiency of human sleep can be evaluated by objective and subjective factors, the SE in Equation 1 shown above is a parameter that reflects only objective factors, whereas Equation 2 below can be said to be a parameter that reflects subjective factors as well.

[0054]

number

[0055] In formula 2 above, [Deep Sleep Duration] refers to the time the sleeper is in deep sleep, [Light Sleep Duration] refers to the time the sleeper is in light sleep, and [REM Sleep Duration] refers to the time the sleeper is in REM sleep. Also, a1~a3 and b1~b3 are weight values ​​that can be arbitrarily set by the designer or system operator, WT1 is the total time the sleeper was awake in any given time (e.g., minutes) after falling asleep, WT2 is the total time the sleeper was awake in the interval excluding any given time (e.g., minutes) after falling asleep and any given time (e.g., minutes) before waking up, and WT3 is the total time the sleeper was awake in any given time (e.g., minutes) immediately before waking up. The parameters included in the denominator are intended to reflect the subjective elements of the sleeper's sleep, and if a person is awake for a long time during the sleep onset period or before waking up, they generally feel that they did not sleep well, and these parameters can be said to reflect such subjective elements. Furthermore, for reference, the above categories of deep sleep, light sleep, and REM sleep can be classified according to predefined criteria (criteria based on biometric information obtainable from the sleeper, such as heart rate variability and respiratory rate variability).

[0056] Thus, in this invention, weighted sleep efficiency (SEw) can be calculated by changing the weights for each sleep stage, and further by applying an arithmetic formula that changes the weights for sleep duration in any given situation.

[0057] On the other hand, formula 3 is a formula for calculating a sleep score according to one embodiment of the present invention.

[0058] [Formula 3] Sleep Score (%) =SEw×100+c1·min(POSITIVE,A)-c2·min(NEGATIVE,B)+c3·Subjective Sleep Score[-5,5] Sleep score = max(min(sleep score, 100), 0)

[0059] In formula 3 above, the Subjective Sleep Score may be a subjective sleep satisfaction score measured by receiving input from the sleeper (user) via questionnaire, and this can be converted to a value from -5 to 5.

[0060] Furthermore, in formula 3 above, a sleep score greater than 90 can be evaluated as "good," a value greater than 70 and less than or equal to 90 can be evaluated as "average," and a value of 70 or less can be evaluated as "poor."

[0061] On the other hand, the POSITIVE variable in formula 3 above is intended to reflect factors that have a positive effect on the sleep score. According to one embodiment of the present invention, if the calculated sleep efficiency (SE) is greater than d1, the analysis unit 140 may add (SE-d1)·d2 to the POSITIVE variable. Hereinafter, d1 represents the reference point and d2 represents the weight value, where the reference point d1 is based on predetermined values ​​for normal sleep, good sleep, etc., and the weight value can be set arbitrarily (e.g., d1=0.9, d2=20).

[0062] An example of how a positive variable is reflected is when a sleeper maintains a regular sleep pattern. For example, if the sleeper went to bed at a certain time of day at least L (e.g., 3) times in the past week, the analysis unit 140 may add that number of days to the positive variable. For example, the analysis unit 140 may determine whether a sleeper went to bed at a certain time of day based on whether abs(time to go to bed - average time to go to bed over M (e.g., 7) days) is less than α (e.g., 30) minutes, and if the sleeper went to bed at a certain time of day, the number of times this occurred may be determined as the number of days the sleeper went to bed at a certain time of day.

[0063] Furthermore, if the sleeper woke up during a certain time period N (e.g., 3) or more times in the past week, the analysis unit 140 may add that number of days to the POSITIVE variable. For example, the analysis unit 140 may determine whether the sleeper woke up during a certain time period based on whether abs(wake-up time - average wake-up time over 0 (e.g., 7) days) is less than β (e.g., 30) minutes, and if the sleeper woke up during a certain time period, it may determine the number of times this happened as the number of days the sleeper woke up during that time period.

[0064] On the other hand, the NEGATIVE variable in formula 3 above is intended to reflect factors that negatively affect the sleep score.

[0065] According to one embodiment of the present invention, the analysis unit 140 may add min(abs((TST-MEAN) / SD+1),e1) to the "NEGATIVE" variable if the total sleep time (TST) is 1 SD (standard deviation; a predetermined value) or more smaller than the average sleep time for a given sex or age group. The value of e1 may be, for example, 5.

[0066] Furthermore, if the average sleep time (AST) over the most recent N (e.g., 2) days is 1 SD or more smaller than the average sleep time for the sex / age group, the analysis unit 140 may add min(abs((AST-MEAN) / SD+1),e2) to the "NEGATIVE" variable. The value of e2 may be, for example, 3.

[0067] Furthermore, if sleep efficiency (SE) is less than average sleep time (AST), the analysis unit 140 may add abs(SE-e3)*e4 to the "NEGATIVE" variable. The value of e3 could be, for example, 0.85, and the value of e4 could be, for example, 10.

[0068] Furthermore, if the sleep latency (SL) is 1 SD or more greater than the average sleep latency for each gender / age group, the analysis unit 140 may add min(abs((SL-MEAN) / SD-1),e5) to the "NEGATIVE" variable. Here, sleep latency can represent the time required from going to bed to falling asleep. The value of e5 may be, for example, 5.

[0069] Furthermore, if the Persistent Sleep Latency (PSL) is greater than the sleep latency (SL), the analysis unit 140 may add min((PSL-SL)*e6,e7) to the "NEGATIVE" variable. In this case, the value of e6 may be, for example, 0.1, and the value of e7 may be 5. The PSL may be defined as the time required for sleep to continue for 10 minutes or more after going to bed.

[0070] On the other hand, according to another embodiment of the present invention, if the REM sleep latency (RSL) is 1 SD or more greater than the average for each age group, the analysis unit 140 may add min(abs((RSL-MEAN) / SD-1),f1) to the "NEGATIVE" variable. In this case, the value of f1 may be, for example, 5.

[0071] Furthermore, the analysis unit 140 may add f2 to the "NEGATIVE" variable if the REM sleep latency (RSL) is less than 15 minutes or if REM is absent. Here, the value of f2 may be, for example, 5, and the REM sleep latency (RSL) can be defined as the time in minutes required from sleep latency (SL) until rapid eye movement (REM) occurs.

[0072] Furthermore, if the REM sleep ratio (%REM) falls outside the range of 15-30%, the analysis unit 140 may: i) if %REM is less than 15%, add min((15-%REM) / f3,f4) to the "NEGATIVE" variable; or ii) if %REM is greater than 30%, add min((%REM-30) / f3,f4) to the "NEGATIVE" variable. Here, %REM is a value that represents the percentage (%) of REM sleep in total sleep, where f3 can be 5 and f4 can be 3.

[0073] Furthermore, if the deep sleep ratio (%DEEP) is 1 SD or more smaller than the average for each gender / age group, the analysis unit 140 may add min((%DEEP-MEAN) / SD+1, f5) to the "NEGATIVE" variable. Here, %DEEP is a value that represents the percentage of deep sleep in total sleep, and f5 can be 5.

[0074] Furthermore, if the sleep cycle (SC) is less than f6 (for example, 3 times), the analysis unit 140 may add min(abs(SC-3)*f7) to the "NEGATIVE" variable (where f7 can be, for example, 2). Here, the sleep cycle may refer to the number of times during sleep the sleep stages sequentially change from wake, light sleep, deep sleep, light sleep, and REM sleep.

[0075] Furthermore, if the Apnea-Hypopnea Index (AHI) is greater than 5, the analysis unit 140 may apply 10 to f8 if the AHI is 30 or greater, 6 to f8 if the AHI is 15 or greater, and 3 to f8 if the AHI is 5 or greater, and add these values ​​to the "NEGATIVE" variable. Here, AHI is a value that indicates the number of times apnea and hypopnea occur per hour (count / hour). Subsequently, the analysis unit 140 may calculate a physical recovery index to evaluate information on recovery through sleep. It should be understood that the f-value may be changed according to the intentions of the designer or operator.

[0076] On the other hand, according to yet another embodiment of the present invention, the analysis unit 140 may utilize the heart rate measured during sleep to calculate an autonomic nervous system activity index, which is a heart rate variability index indicating sympathetic and parasympathetic nervous system activity. For example, the analysis unit 140 may use the index to estimate the degree of refreshment after waking up (refreshing score) and the degree of fatigue the day after sleep (fatigue score).

[0077] According to one embodiment of the present invention, the analysis unit 140 can receive as input the degree of refreshment felt by the subject upon waking up after sleep. For example, the degree of refreshment may be expressed as a value close to 0 if the subject does not feel refreshed at all, and a value close to 100 if the subject feels extremely refreshed, based on 7 p.m. as the baseline for the day's fatigue level. Subsequently, the analysis unit 140 can determine a physical recovery index based on the weighted sum of the estimated "degree of refreshment after waking up" and the "degree of fatigue the day after sleep."

[0078] Formula 4 is a formula for calculating the physical recovery index (ADJ Score) according to one embodiment of the present invention.

[0079]

number

[0080] According to one embodiment of the present invention, the analysis unit 140 may use as input variables for estimating the degree of refreshment after waking up and the degree of fatigue the day after sleep the percentage of time during sleep in which various heart rate variability indices that reflect autonomic nervous system activity exceed a threshold, a heart rate variability index calculated every 30 seconds, and the percentage of time during the entire sleep period in which a specific index (e.g., HF / LF ratio, nHF, nLF) exceeds a threshold.

[0081] According to one embodiment of the present invention, the analysis unit 140 can perform modeling to generate models for the degree of refreshment after waking up and the degree of fatigue the day after sleep, respectively, by confirming the estimated degree of refreshment after waking up and the degree of fatigue the day after sleep as result variables and applying the result variables to the n-th degree polynomial of the input variables.

[0082] On the other hand, according to another embodiment of the present invention, the detection unit 120 may include an unrestrained sensor, and the analysis unit 140 may use the long-term sleep information detected via the unrestrained sensor to calculate the Sleep Regularity Index (SRI) and the Chronotype Index (MSFsc: Middle of Sleep on Free days corrected for sleep debt), and combine these to derive a sleep type. For example, it is known that if the Sleep Regularity Index is subdivided into three types and the Chronotype is subdivided into five types, 15 types of Chronotypes can be derived. The types of SRI can be subdivided, for example, into "good" if the SRI value is 84 or higher, "normal" if it is less than 84 but 60.8 or higher, and "bad" if it is less than 60.8.

[0083] The types of MSFsc can be classified by the unit of epoch, which is the elapsed time relative to midnight. In this case, one epoch may represent 30 seconds. For example, 366 epochs may represent 183 minutes after midnight, indicating 3:03 AM, and 400 epochs may represent 200 minutes after midnight, indicating 3:20 AM.

[0084] The MSFsc type can be further subdivided as follows: "extreme morning" if the epoch value is less than 366, "moderate morning" if it is between 366 and 400, "intermediate" if it is between 400 and 477, "moderate evening" if it is between 477 and 507, and "extreme evening" if it is 507 or more.

[0085] The analysis unit 140 can convert the calculated sleep score into a score ranging from a minimum of 0 to a maximum of 100. For example, the analysis unit 140 can determine the state of short-term sleep as follows: if the converted sleep score is greater than 90 points, it is "good"; if it is greater than 70 points but 90 points or less, it is "average"; and if it is 70 points or less, it is "poor".

[0086] Furthermore, the analysis unit 140 of the present invention can also analyze the user's biometric information stored in the memory unit 130 in a short term, calculate the results as a numerical index, and include it in the user's sleep state analysis information, or / or, analyze the user's biometric information stored in the memory unit 130 in a long term, determine the user's sleep state type based on the differences in sleep states within the long-term analysis period, and include it in the user's sleep state analysis information. In this specification, short term or short-term data refers to data obtained in one day or over a period of 10 days or more, and long term or long-term data refers to data obtained over a period of 10 days or more.

[0087] The user's sleep state analysis information generated by the analysis unit 140 can be stored in the memory unit 130. The memory unit 130 of the present invention will be described in more detail below with reference to Figure 2.

[0088] Figure 2 is a diagram illustrating in more detail the memory unit 130 of the sleep state analysis information and improvement guide provision system according to an embodiment of the present invention. As shown in Figure 2, the memory unit 130 can store identification information that can identify a user, as well as the user's biometric information and sleep state analysis information. In particular, according to the present invention, when the layer unit 110 is used by multiple users, the memory unit 130 can store information for multiple users mapped to each user. For example, when information for multiple users is stored in the memory unit 130, identification information that can distinguish user A and user A's biometric information can be mapped and stored, and sleep state analysis information for user A, analyzed based on the stored biometric information, can also be mapped and stored together.

[0089] Herein, according to the present invention, since the memory unit 130 stores user identification information along with biometric information, sleep state analysis information, etc., mapped to each of multiple users, even when the sleep state analysis information and improvement guide provision system 100 according to the present invention is shared and used by multiple users, it becomes possible to accurately detect biometric information, analyze sleep state, and provide improvement guides for each specific user.

[0090] In other words, according to the present invention, the memory unit 130 can store identification information, biometric information, and sleep state analysis information mapped to each user, and an optimal improvement guide that can change the user's sleep state based on the user's biometric information can be generated for a single user and / or for multiple users, separately for each user.

[0091] Hereinafter, with reference to Figure 3, a sleep state analysis information and improvement guide provision system according to another embodiment of the present invention will be described.

[0092] Figure 3 is a diagram illustrating a sleep state analysis information and improvement guide provision system according to another embodiment of the present invention. As shown in Figure 3, the analysis unit 140 generates sleep state analysis information for a user based on the user's biometric information stored in the memory unit 130, and can also generate an improvement guide that can change the user's sleep state based on the user's biometric information and sleep state analysis information stored in the memory unit 130.

[0093] The user's sleep improvement guide generated by the analysis unit 140 can be provided to the user in various different ways. Furthermore, according to another embodiment of the present invention, a feedback receiving unit 150 may be further included for monitoring the user's actions in response to the improvement guide generated by the analysis unit 140. The feedback receiving unit 150 is a component capable of monitoring the user's behavioral information and / or the user's sleep state information, and may be provided inside or outside the layer unit 110, or may be a component included in the detection unit, or may be the same component as the detection unit.

[0094] For example, if a user's sleep state numerical index is calculated to be 50 points but the user wants to improve it to 70 points or higher, or / or if the user's sleep state is analyzed as a type I sleep state but the user wants to change it to a type II sleep state, the analysis unit 140 can provide an improvement guide necessary to change the user's sleep state, such as an improvement guide that includes daily life behaviors and actions to be taken before going to bed. Furthermore, via the feedback receiving unit 150, it is possible to track and observe whether the user is appropriately taking actions according to the provided improvement guide, and whether the user's behavioral patterns, environment, etc. have improved accordingly to be suitable for changing their sleep state to type II.

[0095] As described above, the sleep state analysis information and improvement guide provision system according to the present invention detects the user's biological information and analyzes the user's sleep state based on the detected biological information. It is characterized by either performing a short-term analysis and calculating the results as a numerical index, or / or performing a long-term analysis to determine the sleep state type, and providing the user's sleep state analysis information.

[0096] As a result, the present invention allows users to more intuitively recognize the content of their own sleep state through sleep state analysis information provided in the form of numerical indicators and / or sleep state type, enabling them to quickly and easily understand their sleep state without the help of a professional, and to easily predict the impact of their sleep state on their daily life. This allows them to prepare in advance for problems in daily life that may arise due to a decline in the quality of their sleep.

[0097] Furthermore, the present invention is characterized by providing an improvement guide that includes specific actions that can change the sleep state if the user wishes to change their sleep state, thereby offering the advantage that the user can improve their sleep state to the optimal sleep state type that suits them simply by following the improvement guide provided by the system of the present invention.

[0098] Furthermore, the present invention also has the effect of providing an even better improvement guide that can more effectively change the sleep state type of a user by receiving feedback on whether the user has followed the action guidelines of the improvement guide provided to the user, and by monitoring to what extent such changes in the user's behavior have actually affected changes in the user's sleep state type.

[0099] The following describes a method for providing sleep state analysis information and improvement guides according to an embodiment of the present invention, with reference to Figure 4.

[0100] Figure 4 is a diagram illustrating a method for providing sleep state analysis information and improvement guides according to an embodiment of the present invention.

[0101] Referring to Figure 4, the sleep state analysis information and improvement guide provision method performed in the sleep state analysis information and improvement guide provision system, which includes a layer unit, a detection unit, a memory unit, and an analysis unit, includes the steps of: detecting the user's biological information from the detection unit provided in the layer unit (S100); storing the user's biological information detected by the detection unit in the memory unit (S200); and analyzing the user's sleep state in the analysis unit based on the user's biological information stored in the memory unit, thereby generating sleep state analysis information for the user (S300).

[0102] The aforementioned layer portion may be the space in which the user sleeps, for example, a mattress, or one of the multiple surfaces that make up a mattress. Furthermore, the layer portion may be a mat placed on top of the mattress, and may be made of wood or metal, not just a surface made of fiber. Thus, as long as the layer portion has a predetermined storage space, there are no restrictions on the material or shape of the layer portion. However, in this detailed description, in order to aid in understanding the invention, we will continue the explanation assuming that the layer portion is a mattress.

[0103] Step S100, in which the user's biometric information is collected from the detection unit, is performed by a detection unit provided within the layer unit, and the detection unit includes at least one of the following sensors: pressure sensor, vibration sensor, position sensor, acoustic sensor, infrared sensor, motion sensor, face recognition sensor, biometric recognition sensor, and fingerprint recognition sensor. The type, number, layout, etc., of sensors used to detect more precise and specific user biometric information are not limited to the embodiments of the present invention.

[0104] Specifically, step S100 can be implemented in various forms, such as detecting the user's weight and position information via the pressure sensor of the detection unit, detecting the user's vibration signal via a vibration sensor to detect state information such as heart rate, respiratory state, and body movement state, recognizing the user's voice or detecting snoring sounds via an acoustic sensor, or detecting the user's gestures via a motion sensor to receive body movement information.

[0105] Next, step S200 is performed, in which the user biometric information detected by the detection unit is stored in the memory unit. Step S200 may be performed so that the user biometric information collected from the detection unit is mapped and stored for each of multiple users, so that even when multiple users share a mattress, identification information that can distinguish each user and the biometric information of that user can be mapped and stored (see Figure 2).

[0106] Subsequently, step S300 is performed, in which the analysis unit analyzes the user's sleep state based on the user's biometric information stored in the memory unit and generates sleep state analysis information for the user. Here, step S300 may be performed in a manner in which the analysis unit analyzes at least one piece of user biometric information stored in the memory unit to generate sleep state analysis information for the user. Specifically, the user's sleep state can be analyzed through the user's heart rate information (e.g., heart rate variability), respiratory rate information (e.g., respiratory variability), pulse rate information, body movement information, sound information, etc.

[0107] In other words, according to the present invention, state information such as the user's lying position, turning over, and getting up (e.g., getting off the mattress) can be analyzed through the information detected by the pressure sensor of the detection unit, the user's heart rate information, respiratory rate information, body movement information can be analyzed through the information detected by the vibration sensor of the detection unit, and furthermore, sound information such as snoring can be analyzed by detecting various sounds of the user with the acoustic sensor of the detection unit. As a result, in step S300 of the present invention, the analysis unit can analyze sleep states such as heart rate variability, respiratory rate variability, and whether or not the user is awake (getting off the mattress) based on the user's biological information stored in the memory unit.

[0108] Furthermore, the S300 step may be performed in a manner in which the analysis unit analyzes the user's sleep state in stages. When analyzing sleep stages, various parameters such as total recording time (TRT), total sleep time (TST), sleep latency (SL), REM sleep latency (RL), wake after sleep onset (WASO), sleep efficiency (SE), duration of each sleep stage, and percentage of each sleep stage may be used.

[0109] The process for generating user sleep state analysis information according to the present invention will be explained in more detail below with reference to Figures 5 to 9.

[0110] Figure 5 is a diagram illustrating a method for providing sleep state analysis information according to one embodiment of the present invention. As shown in Figure 5, the step (S300) in which the user's sleep state analysis information is generated in the analysis unit can be performed by analyzing the user's biological information stored in the memory unit in a short term, calculating the results as numerical indicators, and including them in the user's sleep state analysis information.

[0111] Specifically, the step (S300) of generating user sleep state analysis information according to one embodiment of the present invention may include the steps of: analyzing the user's biometric information stored in the memory unit in a short term; calculating the results of the short-term analysis as numerical indicators; and generating the user sleep state analysis information by including the calculated numerical indicators.

[0112] In other words, according to the present invention, by analyzing the user's biological information in the short term, it is possible to provide the user with various sleep state analysis information that has been accurately analyzed on a daily basis. Thus, the present invention has the advantage that the user can more productively and effectively plan their life, goals, and plans for the following day based on their daily sleep state analysis information.

[0113] Furthermore, the present invention can provide the analyzed user sleep state analysis information not as redundant explanatory material, but by summarizing it into a single numerical index, i.e., by calculating and providing it as a score.

[0114] Figure 6 is a diagram illustrating in more detail the sleep state analysis information provision method according to one embodiment of the present invention. As shown in Figure 6, based on the user A's biological information (e.g., heart rate, respiratory rate, body movement, sound generation, etc.), the user A's sleep state information (e.g., heart rate variability, respiratory rate variability, body movement frequency, snoring information, etc.) can be specifically obtained and provided as a single numerical index.

[0115] In analyzing sleep state information and calculating numerical indicators, subjective and / or objective information can be used in a variety of ways. For example, when calculating a user's sleep state information as a numerical indicator, weighted sleep efficiency (WSE) can be calculated based on known or predefined formulas according to the present invention. The formulas used in calculating the numerical indicators of the present invention may be one or a combination of at least two formulas, and embodiments of the present invention are not limited to the number and combination methods of such formulas.

[0116] Furthermore, such a formula may utilize at least one of various subjective pieces of information that can be empirically recognized, such as information that if a user is unable to fall asleep while lying down in the early stages of a sleep interval and remains awake for a long period, this strongly remains in the user's memory and leads to the perception that they did not get enough sleep; information that if a user frequently wakes up from sleep before getting up in the later stages of a sleep interval, this strongly remains in the user's memory and leads to the perception that they did not get enough sleep; and information that if there are many periods in a sleep interval during which the user remains awake for a predetermined amount of time or longer, this strongly remains in the user's memory and leads to the perception that they did not get enough sleep. In addition, such a formula may utilize objective information that has been demonstrated through numerous papers and research results, such as information that deep sleep is a sleep state that affects physical recovery, promotion of growth hormone, and consolidation of declarative memory, or information that deep sleep is a sleep state that affects mental recovery and consolidation of procedural memory.

[0117] On the other hand, sleep status is closely related to a user's daily life, and numerous studies have shown that poor sleep the previous day can affect a user's daily life, leading to increased accidents, decreased attention span, and reduced cognitive activity the following day. Tests such as the Epworth Sleepiness Scale (ESS) exist to evaluate this relationship between sleep status and daily life. In this invention, it is also possible to analyze the impact of sleep on a user's daily life through analysis of their sleep status and self-assessment of sleepiness.

[0118] Self-assessment of sleepiness can be conducted by having the user numerically evaluate the degree of sleepiness they experience while performing each of the activities listed as examples, and then summing up these scores. For example, when a user is sitting and reading, they might rate it as "0" if they are not sleepy at all, "1" if they are slightly sleepy, "2" if they are quite sleepy, and "3" if they are very sleepy. The total score for sleepiness in all other activities can then be added up to assess the degree of daytime sleepiness.

[0119] Here, according to the present invention, after an analysis of the user's sleep state is performed, such a self-assessment of sleepiness is conducted, and by analyzing the user's sleep state analysis information and the results of the self-assessment of sleepiness together, it is possible to analyze the impact of the user's sleep state on their daily life (e.g., a daytime sleepiness scale) based on the user's self-assessment history of sleepiness. For example, if the sleep state analysis result for user A is calculated to be 75 points, the user's self-assessment index of sleepiness can be predicted to be approximately 11 points (a state of mild daytime hypersomnia). By including such predictive information in the sleep state analysis information and providing it to the user, the user is not only provided with information about their sleep state, but also with information on how that sleep state may affect their daily life.

[0120] In other words, the present invention is characterized by estimating a self-assessment of sleepiness using information related to sleep state and deriving the result, and in particular by utilizing a regression model based on a large amount of data accumulated over multiple trials, to provide users with analytical information on their sleep state, along with a specific evaluation scale for daytime hypersomnia regarding the extent to which that sleep state may affect the user's daily life.

[0121] In other words, the present invention is characterized not only by providing the results of analyzing the user's sleep state as a numerical index for intuitive understanding, but also by providing the results of an analysis of how that sleep state affects daily life as a self-assessment of sleepiness. As a result, the user is provided with not only information about their own sleep state, but also predictive information on how much sleepiness and fatigue that sleep state may cause in daily life. Therefore, the user can more productively and effectively plan their life, goals, and plans for the next day based on their own sleep state analysis information.

[0122] The above has illustrated and described an embodiment that utilizes self-assessment of sleepiness as an indicator showing the impact of the user's sleep state on daily life. However, the embodiments of the present invention are not limited to this, and other embodiments of the present invention may utilize various evaluation indicators that show the relationship between the user's sleep state and daily life, and at least one of these evaluation indicators may be used in combination.

[0123] Furthermore, according to one embodiment of the present invention, information regarding the user's sleep state can be accumulated, collected, and stored, and the accumulated and stored information can be used to analyze the user's sleep state over the long term. That is, if a user sleeps using the layer portion of the sleep state analysis information and improvement guide provision system of the present invention multiple times or more, the user's biological information and / or sleep state analysis information can be accumulated and stored, thereby enabling the user's long-term sleep state analysis information to be grasped.

[0124] Figure 7 is a diagram illustrating a sleep state analysis information provision method according to one embodiment of the present invention. As shown in Figure 7, the step (S300) in which the user's sleep state analysis information is generated in the analysis unit can be performed by analyzing the user's biological information stored in the memory unit over a long period, classifying (typing) the sleep state during the long-term analysis period, and including this in the user's sleep state analysis information.

[0125] Specifically, the step (S300) in which user sleep state analysis information of this embodiment of the present invention is generated may include the steps of: analyzing the user's biological information stored in the memory unit over a long term; determining the user's sleep state type based on the differences in sleep states within the long-term analysis period; and generating the user's sleep state analysis information in which the determined user sleep state type is included.

[0126] In other words, according to the present invention, by analyzing the user's cumulative stored biometric information and / or sleep state analysis information over the long term, the user's sleep state type can be determined based on the differences in the user's sleep state. For example, long-term sleep state analysis information such as whether the user's sleep state is regular or irregular, or what differences exist when comparing weekday sleep state with weekend sleep state, can be extracted. Furthermore, the present invention can also determine the user's sleep type based on such long-term sleep state analysis information.

[0127] Figure 8 is a diagram illustrating the sleep state analysis information provision method according to this embodiment of the present invention. As shown in Figure 8, based on the user A's biological information (e.g., heart rate, respiratory rate, body movement, sound generation, etc.), the user A's sleep state information (e.g., average sleep duration, bedtime / wake-up time, sleep regularity, sleep pattern, etc.) can be specifically determined. This information can be defined as various types of sleep states and included in the long-term sleep state analysis information provided.

[0128] For example, the long-term sleep state analysis information may include the user's average sleep time (evaluation of whether the user is getting enough sleep), bedtime / wake-up time (classification of the user's sleep type as night owl or morning owl), weekday sleep regularity (evaluation of whether the user sleeps regularly on weekdays), and weekday-weekend sleep pattern regularity (evaluation of whether the user's weekday and weekend sleep patterns are regular, or what differences exist between weekday and weekend sleep patterns). It is also possible to classify the time the user was not in position on the mattress as non-sleep activity time and evaluate the user's daily-sleep circadian rhythm based on this. Furthermore, in the process of generating such long-term sleep state analysis information in the present invention, it is possible to evaluate the user's activity level, sleep phase delay syndrome, etc., and it is also possible to generate graphs, etc., for evaluating sleep regularity by capturing the user's actions of going to bed and getting out of bed.

[0129] In the present invention, the long-term sleep state analysis information generated in this manner can be clustered according to predetermined criteria, defined as a single sleep state type, and included in the user's sleep state analysis information. Such sleep state classification (typing) can be performed by a single method or by combining at least two or more diverse methods, and the types, number, and combination methods of such classification (typing) methods, and / or the definition criteria, number, or types of sleep state types, etc., are not limited to embodiments of the present invention.

[0130] For example, in the present invention, a clustering method can be used to classify (type) sleep states. This clustering method is a machine learning technique that involves clustering multiple data points into multiple groups based on similarity. As shown in this embodiment of the present invention, it can be effectively used when analyzing a large amount of cumulatively stored data over a long period to define a specific sleep state type. However, it is not always necessary to use a clustering method for classifying (type) sleep states in the present invention.

[0131] As described above, the present invention analyzes the user's sleep state over the long term and provides the analysis results in a form that includes a sleep state type, allowing the user to intuitively understand their own sleep state in a classified (typed) form. Furthermore, other embodiments of the present invention can provide an improvement guide that can change the user's sleep state type.

[0132] Figure 9 is a diagram illustrating a method for providing sleep state analysis information and improvement guides according to another embodiment of the present invention.

[0133] As shown in Figure 9, the following steps may be performed: S100, a step in which user biometric information is detected from a detection unit provided in the layer unit; S200, a step in which the user biometric information detected by the detection unit is stored in the memory unit; S300, a step in which the user's sleep state is analyzed in the analysis unit based on the user biometric information stored in the memory unit and sleep state analysis information for the user is generated; S400, a step in which the analyzed sleep state analysis information for the user is stored in the memory unit; and S500, a step in which the analysis unit generates an improvement guide that can change the user's sleep state.

[0134] The step in which the user's sleep state analysis information is stored in the memory unit (S400) is performed so that the sleep state analysis information is mapped to the user's identification information and stored accordingly. In the case of a mattress shared by multiple users, the sleep state analysis information of each user may be mapped and stored accordingly (see Figure 2).

[0135] Next, in the analysis unit, the step of generating an improvement guide that can change the user's sleep state (S500) may be performed so that an improvement guide for the user is generated based on the user's biometric information and the user's sleep state analysis information stored in the memory unit. In the case of a mattress shared by multiple users, the step may be performed so that an improvement guide for each user is generated based on information (see Figure 2) that is mapped and stored in the memory unit for each user.

[0136] In the present invention, in the step (S300) in which the user's sleep state analysis information is generated, the analysis unit may provide the user's sleep state analysis information in a form that includes a numerical index converted into a score and / or a sleep state type, and the analysis unit of the present invention can generate an improvement guide that can change the user's sleep state. For example, if the user's numerical index of sleep state is calculated to be 50 points but the user wants to improve it to 70 points or more, or / or if the user's sleep state is analyzed to be a type I sleep state but the user wants to change it to a type II sleep state, the analysis unit can generate an improvement guide necessary to change the user's sleep state, and the improvement guide may include, for example, daily life activities, activities to be performed before going to bed, etc.

[0137] The sleep improvement guide generated in the S500 stage may be provided to the user in various ways, and according to other embodiments of the present invention, a process of monitoring the user's actions toward the improvement guide may be further performed.

[0138] Figure 10 is a diagram illustrating a method for providing sleep state analysis information and improvement guides according to yet another embodiment of the present invention. Referring to Figure 10, after the analysis unit performs the step of generating an improvement guide that can change the user's sleep state (S500), the feedback receiving unit may perform the step of monitoring the user's actions in response to the improvement guide (S600).

[0139] The feedback receiving unit is a component capable of monitoring the user's behavioral information and / or the user's sleep state information, and may be provided inside or outside the layer unit, and may be a component included in the detection unit, or the same component as the detection unit. Step S600 may be performed in a manner in which the feedback receiving unit tracks and observes whether the user is appropriately performing the actions included in the improvement guide, and whether the user's behavioral patterns, environment, etc. have been improved accordingly to a state suitable for changing the user's sleep state.

[0140] Furthermore, the present invention may include a process in which, after the step of monitoring user execution information in response to the improvement guide in the feedback receiving unit (S600), the process returns to the step of storing the results of the monitored user execution information in the memory unit (S200), and the subsequent steps are repeated at least once.

[0141] In other words, the results of the execution of the improvement guide for changes in the user's sleep state can be mapped and stored in the memory unit along with the user identification information for each user (see Figure 2). After the improvement guide is executed, the sleep state analysis process for that user is repeatedly executed, and it is possible to continuously observe whether the user's sleep state has actually changed as a result of the improvement guide. This can be used to generate an optimal improvement guide that can effectively change the user's sleep state.

[0142] As described above, the present invention enables users to more intuitively recognize their own sleep state by generating sleep state analysis information that includes the results of short-term and / or long-term analysis of the user's biometric information, calculated as numerical indicators, or defined as sleep state types. Furthermore, by providing a scale that specifically analyzes the extent to which the sleep state affects the user's daily life, users can predict the impact on their daily life based on their sleep state and take countermeasures.

[0143] Furthermore, the present invention provides an improvement guide that can change the user's sleep state based on the user's sleep state analysis information, thereby supporting the user in achieving the most efficient sleep state for themselves. The results of executing such an improvement guide are accumulated and stored, and utilized in the analysis of the user's sleep state and the generation of sleep state improvement guides, thereby providing the user with better sleep effects.

[0144] Figure 11 is a diagram showing the sleep type calculated in a system according to one embodiment of the present invention.

[0145] Referring to Figure 11, sleep types can include 15 different sleep types, each composed of combinations of three types of SRIs and five types of MSFscs.

[0146] According to one embodiment of the present invention, the analysis unit 140 can determine the type of SRI and the type of MSFsc based on data from bed over N weeks, and determine the sleep type. For example, the type of SRI may include "good" when the SRI value is 84 or higher, "normal" when it is less than 84 but 60.8 or higher, and "bad" when it is less than 60.8. The type of MSFsc can be further subdivided into extreme morning when the epoch value is less than 366, moderate morning when it is 366 or more but less than 400, intermediate when it is 400 or more but less than 477, moderate evening when it is 477 or more but less than 507, and extreme evening when it is 507 or higher.

[0147] According to one embodiment of the present invention, the sleep types may include early-morning types, such as the free-early-morning type, which combines the "extreme early-morning" MSFsc type with the "poor" SRI type; the regular early-morning type, which combines it with the "normal" SRI type; and the complete early-morning type, which combines it with the "good" SRI type. For reference, to help the user intuitively recognize each type, an animal corresponding to each type may be mapped. For example, the free-early-morning type may be mapped as a "mole, an early-morning burrower," the regular early-morning type as a "diligent bee," and the complete early-morning type as a "lion, the DJ of the savanna," and so on. Such mapping of animals and supplementary expressions has the effect of attracting the user's interest and improving user convenience by allowing them to intuitively understand their own sleep type.

[0148] According to one embodiment of the present invention, the sleep types may include, as regular morning types, irregular morning types (sea wake-up call specialist dolphin) in which a "poor" SRI type is combined with a "normal morning type" MSFsc type, regular morning types (lively skylark) in which a "normal" SRI type is combined, and extremely regular morning types (community specialist elephant) in which a "good" SRI type is combined.

[0149] According to one embodiment of the present invention, the sleep types may include, as regular normal types, irregular normal types (adaptive living expert dog) in which an "intermediate" type of MSFsc is combined with a "poor" type of SRI, regular normal types (clever fox) in which an "average" type of SRI is combined, and extremely regular normal types (strict living routine eagle) in which a "good" type of SRI is combined.

[0150] According to one embodiment of the present invention, the sleep types may include, as regular evening types, irregular evening types (party expert hamster) which combine the "normal evening type" MSFsc type with the "poor" SRI type, regular evening types (security expert cat) which combine the "normal" SRI type, and extremely regular evening types (logical night philosopher tiger) which combine the "good" SRI type.

[0151] According to one embodiment of the present invention, the sleep types may include, as regular night owls, irregular night owls (night explorer raccoon) in which an "extreme night owl" type of MSFsc is combined with a "poor" type of SRI, regular night owls (sea musical actor shark) in which an "average" type of SRI is combined, and extremely regular night owls (night strategist owl) in which an "adequate" type of SRI is combined.

[0152] According to one embodiment of the present invention, the analysis unit 140 can provide improvement guidance regarding sleep type based on the determined sleep type. For example, if the determined sleep type for a user is "raccoon type" and the user wants to change to a "fox type" sleep type, the analysis unit 140 can provide the user with improvement guidance that includes the step of adjusting the user's bedtime and wake-up time to fall within the range of the "fox type".

[0153] According to one embodiment of the present invention, the analysis unit 140 can set steps for changing the type of SRI. For example, in order to change the bedtime in relation to the type of SRI, the analysis unit 140 can set a range from one hour before and after the proposed time to one hour before and after the wake-up time as a first step, and a range from 40 minutes before and after the proposed time to 50 minutes before and after the wake-up time as a second step.

[0154] According to one embodiment of the present invention, the analysis unit 140 can set steps for changing the type of MSFsc. For example, in order to change the bedtime and wake-up time in relation to the type of MSFsc, the analysis unit 140 can set a range for bedtime and wake-up time by setting 15 minutes before and after the current bedtime and 20 minutes before and after the wake-up time as a first step. Alternatively, as a second step, it can set 30 minutes before and after the current bedtime and 20 minutes before and after the wake-up time.

[0155] According to one embodiment of the present invention, the analysis unit 140 can provide information as the improvement guide that enables the user to follow the set steps. For example, the analysis unit 140 can provide improvement guides for the SRI type and the MSFsc type simultaneously, or it can provide the improvement guide for the SRI type first, and then sequentially provide the improvement guide for the MSFsc type.

[0156] According to one embodiment of the present invention, the analysis unit 140 can receive feedback from the user regarding the sequentially provided improvement guides via the feedback receiving unit 150. For example, if the received feedback includes a positive response to the sequentially provided improvement guides, the analysis unit 140 can provide the improvement guides for all types simultaneously.

[0157] According to one embodiment of the present invention, if the received feedback includes a negative response to the sequentially provided improvement guide, the analysis unit 140 can adjust the range for each type of improvement guide and sequentially provide the adjusted improvement guide for each type.

[0158] According to one embodiment of the present invention, the analysis unit 140 can determine that when the sleep type changes from "raccoon dog type" to "fox type," the type of SRI changes by one step, and the type of MSFsc changes by two steps. In this case, the analysis unit 140 can provide an improvement guide for the type of SRI with a small change in steps before an improvement guide for the type of MSFsc. This makes it possible to provide the user with improvement guides in order from those with small changes to those with large changes.

[0159] The sleep state analysis information and improvement guide provision system and method according to the present invention have been described above. However, the present invention is not limited to the specific embodiments and applications described above, and it is of course possible for those skilled in the art to implement various modifications without departing from the gist of the invention as described in the claims, and these modifications are not understood separately from the technical idea and prospects of the present invention.

[0160] In particular, configurations that implement the technical features of the present invention, as shown in the block diagrams and flowcharts in the drawings attached to this specification, represent logical boundaries between such configurations. However, according to software or hardware embodiments, the illustrated configurations and their functions may be implemented in the form of standalone software modules, monolithic software structures, code, services, and combinations thereof, and their functions may be realized by storing stored program code, instructions, etc., on a medium executable in a computer equipped with an executable processor; therefore, all such embodiments also fall within the scope of the present invention.

[0161] Therefore, while the attached drawings and related descriptions illustrate the technical features of the present invention, they are not to be inferred unless a specific sequence of software for realizing these technical features is explicitly mentioned. That is, as described above, various embodiments may exist, and since these embodiments may have the same technical features as the present invention but may be partially modified, they are also considered to fall within the scope of the present invention.

[0162] Furthermore, while flowcharts depict operations in a specific order, this is done to illustrate the most desirable outcome, and it should not be understood that the operations must necessarily be performed in the specific or sequential order shown, or that all of the illustrated operations must necessarily be performed. In certain cases, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and the described program components and systems can typically be integrated as a single software product or packaged as multiple software products. [Explanation of Symbols]

[0163] 100 Sleep State Analysis Information and Improvement Guide Provision System 110 Layer section 120 Detection unit 130 Memory section 140 Analysis Department 150 Feedback receiving unit

Claims

1. A layer section comprising multiple components, A detection unit is provided within the aforementioned layer to detect the user's biometric information, A memory unit in which user biometric information detected by the detection unit is stored, An analysis unit analyzes the user's sleep state based on the user's biometric information stored in the memory unit and generates sleep state analysis information for the user. including, A sleep state analysis information and improvement guide provision system characterized by the following features.

2. The aforementioned analysis unit is The user's biometric information stored in the memory unit is analyzed in a short term, the results are calculated as numerical indicators, and these are included in the user's sleep state analysis information. The sleep state analysis information and improvement guide provision system according to claim 1.

3. The aforementioned analysis unit is The user's biometric information stored in the memory unit is analyzed over a long term, and the user's sleep state type is determined based on the differences in sleep states within the analysis period, and this is included in the user's sleep state analysis information. The sleep state analysis information and improvement guide provision system according to claim 1.

4. The memory section includes: The user's sleep state analysis information, analyzed by the aforementioned analysis unit, is stored. The sleep state analysis information and improvement guide provision system according to claim 1.

5. The memory section includes: The sleep state analysis information of the user, analyzed by the aforementioned analysis unit, is mapped and stored for multiple users. The sleep state analysis information and improvement guide provision system according to claim 4.

6. The aforementioned analysis unit is Based on the user's biometric information and sleep state analysis information stored in the memory unit, an improvement guide is generated that can change the user's sleep state. The sleep state analysis information and improvement guide provision system according to claim 5.

7. In a sleep state analysis information and improvement guide provision method performed by a sleep state analysis information and improvement guide provision system including a layer unit, a detection unit, a memory unit, and an analysis unit, The steps include: detecting the user's biometric information from a detection unit provided within the layer portion; The user's biometric information detected by the detection unit is stored in the memory unit. The analysis unit analyzes the user's sleep state based on the user's biometric information stored in the memory unit, and generates sleep state analysis information for the user. including, A method for providing sleep state analysis information and improvement guides, characterized by the following features.

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