Method, apparatus and sleep intervention device for sleep intervention

Abstract

The application relates to the technical field of sleep intervention, and discloses a method for sleep intervention, which comprises the following steps: periodically acquiring a body sign parameter value of a user under the condition that it is determined that the user falls asleep; determining a falling asleep state of the user according to the periodically acquired body sign parameter value; determining a sleep intervention strategy for improving the post-drinking sleep of the user under the condition that the falling asleep state of the user is drunken falling asleep; and controlling a target sleep intervention device to execute the sleep intervention strategy. In this way, the falling asleep state of the user can be accurately judged in combination with the periodically acquired body sign parameter value, so that the accurate determination of the sleep intervention strategy can be realized when the falling asleep state of the user is drunken falling asleep, thereby realizing the sleep intervention of the drunken user under the condition that the target sleep intervention device is controlled to execute the sleep intervention strategy, effectively improving the sleep quality of the drunken user, and meeting the accurate control demand of the drunken user on the sleep intervention device. The application also discloses an apparatus for sleep intervention and a sleep intervention device.

Description

Technical Field

[0001] This application relates to the field of sleep intervention technology, such as a method, apparatus, and device for sleep intervention. Background Technology

[0002] As people's living standards continue to improve, more and more people are paying attention to their sleep quality, leading to the development of various sleep intervention devices. Currently, these devices can intervene in a user's sleep after they fall asleep, and how to more accurately control these devices has become a key focus for users.

[0003] Currently, if a user drinks alcohol before going to sleep, the alcohol intake causes the throat muscles to relax during sleep, leading to breathing difficulties and severely impacting sleep quality. Therefore, how to accurately intervene in sleep after a user has fallen asleep while intoxicated is a pressing technical problem that needs to be solved.

[0004] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0006] This disclosure provides a method, apparatus, and device for sleep intervention, which can accurately perform sleep intervention after a user has fallen asleep while intoxicated.

[0007] In some embodiments, the method for sleep intervention includes: periodically acquiring the user's vital signs parameters when it is determined that the user has fallen asleep; determining the user's sleep state based on the periodically acquired vital signs parameters; determining a sleep intervention strategy to improve the user's sleep after drinking alcohol when the user's sleep state is sleep while intoxicated; and controlling a target sleep intervention device to execute the sleep intervention strategy.

[0008] In some embodiments, the method for sleep intervention includes: acquiring the user's historical sleep data; determining the user's sleep confidence interval based on the user's historical sleep data; and determining the user's sleep state based on periodically acquired vital sign parameter values ​​and the user's sleep confidence interval.

[0009] In some embodiments, the method for sleep intervention includes: calculating the average value and variance of historical sleep data; and determining the user's sleep confidence interval based on the average value and variance of historical sleep data.

[0010] In some embodiments, the method for sleep intervention includes:

[0011]

[0012] Where X is the average value of historical sleep data, Z is the reference factor, S is the variance of historical sleep data, and n is the number of samples in historical sleep data.

[0013] In some embodiments, the method for sleep intervention includes: determining that the user's sleep state is sleep while intoxicated when the periodically acquired respiratory rate values ​​are all outside the respiratory confidence interval, the periodically acquired body temperature values ​​are all above the maximum value of the body temperature confidence interval, and the periodically acquired heart rate values ​​are all above the maximum value of the heart rate confidence interval.

[0014] In some embodiments, the method for sleep intervention includes: obtaining relevant information about the user; and determining a sleep intervention strategy to improve the user's sleep after drinking alcohol based on the relevant information about the user.

[0015] In some embodiments, the method for sleep intervention includes: when the user's sleeping posture information indicates that the user is in a poor sleeping posture, determining that the sleep intervention strategy for improving the user's sleep after drinking is a smart mattress that raises the position of the user's back to guide the user to change their sleeping posture.

[0016] In some embodiments, the device for sleep intervention includes: an acquisition module configured to periodically acquire vital sign parameter values ​​of the user when it is determined that the user has fallen asleep; a first determination module configured to determine the user's sleep state based on the periodically acquired vital sign parameter values; a second determination module configured to determine a sleep intervention strategy for improving the user's sleep after drinking alcohol when the user's sleep state is sleep while intoxicated; and a control module configured to control a target sleep intervention device to execute the sleep intervention strategy.

[0017] In some embodiments, the apparatus for sleep intervention includes a processor and a memory storing program instructions, the processor being configured to execute the aforementioned method for sleep intervention when the program instructions are executed.

[0018] In some embodiments, the sleep intervention device includes the aforementioned means for sleep intervention.

[0019] The method, apparatus, and sleep intervention device provided in this disclosure can achieve the following technical effects: By periodically acquiring the user's vital signs parameters when the user is determined to be asleep; determining the user's sleep state based on the periodically acquired vital signs parameters; determining a sleep intervention strategy to improve the user's sleep after drinking when the user's sleep state is that of someone who has been intoxicated; and controlling the target sleep intervention device to execute the sleep intervention strategy. This solution can accurately determine the user's sleep state by combining the periodically acquired vital signs parameters, so that when the user's sleep state is that of someone who has been intoxicated, a sleep intervention strategy to improve the user's sleep after drinking can be accurately determined. Therefore, by controlling the target sleep intervention device to execute the sleep intervention strategy, sleep intervention can be performed on intoxicated users, effectively improving their sleep quality and meeting their need for precise control of the sleep intervention device.

[0020] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0021] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein:

[0022] Figure 1 This is a schematic diagram of a method for sleep intervention provided in an embodiment of this disclosure;

[0023] Figure 2 This is a schematic diagram of a method for determining a sleep state provided in an embodiment of this disclosure;

[0024] Figure 3 This is a schematic diagram of a method for determining a sleep confidence interval provided in an embodiment of this disclosure;

[0025] Figure 4 This is a schematic diagram of a method for determining a sleep intervention strategy provided in an embodiment of this disclosure;

[0026] Figure 5 This is a schematic diagram of a device for sleep intervention provided in an embodiment of this disclosure;

[0027] Figure 6 This is a schematic diagram of another device for sleep intervention provided in an embodiment of this disclosure. Detailed Implementation

[0028] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0029] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0030] Unless otherwise stated, the term "multiple" means two or more.

[0031] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0032] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0033] The term "correspondence" can refer to an association or binding relationship. The correspondence between A and B means that there is an association or binding relationship between A and B.

[0034] In this embodiment of the disclosure, the sleep intervention device refers to a home appliance product formed by introducing microprocessor, sensor technology and network communication technology into home appliances. It has the characteristics of intelligent control, intelligent sensing and intelligent application. The operation of the sleep intervention device often relies on the application and processing of modern technologies such as the Internet of Things, the Internet and electronic chips. For example, the sleep intervention device can be connected to electronic devices to realize the remote control and management of the sleep intervention device by the user.

[0035] In this embodiment of the disclosure, the terminal device refers to an electronic device with wireless connectivity. The terminal device can communicate with the sleep intervention device described above by connecting to the Internet, or it can directly communicate with the sleep intervention device described above via Bluetooth, Wi-Fi, or other methods. In some embodiments, the terminal device may be, for example, a mobile device, a computer, or an in-vehicle device built into a hovercraft, or any combination thereof. Mobile devices may include, for example, mobile phones, smart home devices, wearable devices, smart mobile devices, virtual reality devices, or any combination thereof. Wearable devices may include, for example, smartwatches, smart bracelets, pedometers, etc.

[0036] Figure 1 This is a schematic diagram of a method for sleep intervention provided in an embodiment of this disclosure; combined with Figure 1 As shown, this disclosure provides a method for sleep intervention, comprising:

[0037] S11: Once it is confirmed that the user has fallen asleep, the server periodically obtains the user's vital signs parameters.

[0038] S12, the server determines the user's sleep state based on the periodically acquired vital sign parameter values.

[0039] S13, if the user falls asleep while intoxicated, the server determines a sleep intervention strategy to improve the user's sleep after drinking.

[0040] S14, The server controls the target sleep intervention device to execute the sleep intervention strategy.

[0041] In this solution, the server can be a cloud server, or it can be deployed on a sleep intervention device. The sleep intervention device is a device capable of influencing and intervening in a user's sleep during the sleep phase. Here, sleep intervention devices include, but are not limited to, smart mattresses, smart speakers, smart air conditioners, smart TVs, smart pillows, and smart beds. Specifically, the server can determine whether a user has fallen asleep in various ways. As an example, the server can capture images of the user through its associated image acquisition device; if the captured image shows the user in a sleeping posture and with their eyes closed, it determines that the user has fallen asleep. In another example, the server can also collect the user's vital signs parameters in real time through wearable devices and determine the trend of these parameters; if the trend of these parameters matches a preset sleep trend, it determines that the user has fallen asleep. In this way, it is possible to accurately determine whether a user has fallen asleep.

[0042] Furthermore, once it's confirmed that the user is asleep, the server periodically acquires the user's vital signs parameters. These parameters include heart rate, respiratory rate, and body temperature. The server can accurately acquire these parameters through wearable devices or sleep monitoring devices associated with the user. It's important to note that the user's vital signs parameters are dynamic; periodically acquiring these parameters allows for the assessment of these changes. Specifically, the server periodically acquires the user's vital signs parameters at preset intervals, with each interval being 5 minutes. This allows the server to acquire the user's vital signs parameters once every 5 minutes, ensuring accurate acquisition of these parameters.

[0043] Furthermore, the server can determine the user's sleep state based on periodically acquired vital sign parameters. Here, the user's sleep state includes both normal sleep and sleep while intoxicated. Specifically, the server determines the user's sleep state based on periodically acquired vital sign parameters by: acquiring the user's historical sleep data; determining the user's sleep confidence interval based on the historical sleep data; and determining the user's sleep state based on the periodically acquired vital sign parameters and the user's sleep confidence interval. In this way, accurate judgment of the user's sleep state can be achieved by combining periodically acquired vital sign parameters and the user's sleep confidence interval.

[0044] Furthermore, when a user falls asleep while intoxicated, the server can determine a sleep intervention strategy to improve the user's sleep after drinking. Specifically, the server determines the following sleep intervention strategies: if the user's sleeping posture information indicates an unfavorable sleeping posture, the server determines that the sleep intervention strategy is to raise the smart mattress at the user's back position to guide the user to change their sleeping posture. In another scenario, the server determines the following sleep intervention strategies to improve the user's sleep after drinking, including: determining the intoxicated user's head height; if the user's head height is lower than a preset height, the server determines that the sleep intervention strategy is to raise the height of the smart pillow and / or smart bed. Here, the preset height can be set by the user based on their actual situation. In this way, by raising the intoxicated user's head height, the server can alleviate the airway obstruction caused by intoxication. In one optimized approach, the server determines a sleep intervention strategy to improve a user's sleep after drinking alcohol, including: determining that the sleep intervention strategy to improve a user's sleep after drinking alcohol is to control the temperature of the smart air conditioner in the sleep environment of the intoxicated user until the intoxicated user's vital signs parameters fall into the user's sleep confidence interval.

[0045] Furthermore, after the server determines a sleep intervention strategy to improve a user's sleep after drinking alcohol, the server controls the target sleep intervention device to execute the sleep intervention strategy. Specifically, the target sleep intervention device is matched with the determined sleep intervention strategy. For example, if the determined sleep intervention strategy is to elevate the user's back position with a smart mattress, then the matched target sleep intervention device is the smart mattress. In this way, precise selection of the target sleep intervention device can be achieved.

[0046] The sleep intervention method provided in this disclosure involves periodically acquiring the user's vital signs parameters when the user is confirmed to be asleep; determining the user's sleep state based on the periodically acquired vital signs parameters; determining a sleep intervention strategy to improve the user's sleep after drinking alcohol when the user's sleep state is confirmed to be sleep-associated with intoxication; and controlling a target sleep intervention device to execute the sleep intervention strategy. This approach allows for accurate determination of the user's sleep state by combining periodically acquired vital signs parameters. When the user's sleep state is confirmed to be sleep-associated with intoxication, a precise sleep intervention strategy to improve the user's sleep after drinking alcohol can be determined. This allows for sleep intervention on intoxicated users while controlling the target sleep intervention device to execute the strategy, effectively improving the sleep quality of intoxicated users and meeting their need for precise control of the sleep intervention device.

[0047] Figure 2 This is a schematic diagram of a method for determining a sleep state provided in an embodiment of this disclosure; combined with Figure 2 As shown, optionally, in S12, the server determines the user's sleep state based on periodically acquired vital sign parameter values, including:

[0048] S21, the server obtains the user's historical sleep data.

[0049] S22, the server determines the user's sleep confidence interval based on the user's historical sleep data.

[0050] S23, the server determines the user's sleep state based on the periodically acquired vital sign parameter values ​​and the user's sleep confidence interval.

[0051] In this solution, the server can obtain a user's historical sleep data through a user-linked sleep monitoring device or wearable device. Historical sleep data refers to sleep data within a preset time period before the user falls asleep. For example, historical sleep data might be the sleep data from one hour before the user falls asleep. Sleep data includes heart rate, respiratory rate, and body temperature. This allows for the accurate acquisition of historical sleep data.

[0052] Furthermore, the server determines the user's sleep confidence interval based on the user's historical sleep data. This includes: the server calculating the average and variance of the historical sleep data; and the server determining the user's sleep confidence interval based on the average and variance of the historical sleep data. This method enables accurate determination of the user's sleep confidence interval.

[0053] Furthermore, the server can combine periodically acquired vital sign parameters with the user's sleep confidence interval to determine the user's sleep state. In this way, accurate judgment of the user's sleep state can be achieved.

[0054] Figure 3 This is a schematic diagram of a method for determining sleep confidence intervals provided in an embodiment of this disclosure; combined with Figure 3 As shown, optionally, in S22, the server determines the user's sleep confidence interval based on the user's historical sleep data, including:

[0055] S31, the server calculates the average value and variance of historical sleep data.

[0056] S32, the server determines the user's sleep confidence interval based on the average value and variance of historical sleep data.

[0057] In this solution, the server can calculate the average value of historical sleep data in the following way:

[0058]

[0059] Where X represents the average value of historical sleep data, n represents the number of historical sleep data samples, and x1…xn represent historical sleep data collected at different historical times within a preset time period before falling asleep. Specifically, historical heart rate data, historical respiratory rate data, and historical body temperature data can be substituted into the formula to obtain the historical average heart rate, historical average respiratory rate, and historical average body temperature. In this way, the average value of historical sleep data can be accurately calculated.

[0060] In this solution, the server can calculate the variance of historical sleep data in the following ways:

[0061]

[0062] Where s represents the variance of historical sleep data, n represents the number of historical sleep data samples, and x1…xi represent historical sleep data collected at different historical times within a preset time period before falling asleep. Specifically, historical heart rate data, historical respiratory rate data, and historical body temperature data can be substituted into the formula to obtain the variances of historical heart rate, historical respiratory rate, and historical body temperature, respectively. In this way, the variance of historical sleep data can be accurately calculated.

[0063] Furthermore, after calculating the average and variance of historical sleep data on the server side, the user's sleep confidence interval can be accurately calculated by combining the average and variance of historical sleep data, providing an accurate data basis for judging the user's sleep state.

[0064] Optionally, S32, the server determines the user's sleep confidence interval based on the average and variance of historical sleep data, including:

[0065]

[0066] In this scheme, the expression for the sleep confidence interval is:

[0067] Specifically, X represents the average of historical sleep data, Z is the reference factor, S is the variance of historical sleep data, and n is the number of historical sleep data samples. The user's sleep confidence intervals include heart rate confidence intervals, respiratory confidence intervals, and body temperature confidence intervals. Thus, the heart rate confidence interval, respiratory confidence interval, and body temperature confidence interval can be determined separately. The historical average heart rate and historical heart rate variance can be substituted into the expression for the sleep confidence interval to determine the heart rate confidence interval; the historical average respiratory rate and historical respiratory rate variance can be substituted into the expression for the sleep confidence interval to determine the respiratory confidence interval; and the historical average body temperature and historical body temperature variance can be substituted into the expression for the sleep confidence interval to determine the body temperature confidence interval. In this way, the heart rate confidence interval, respiratory confidence interval, and body temperature confidence interval can be accurately determined.

[0068] Optionally, S23, the server determines the user's sleep state based on periodically acquired vital sign parameter values ​​and the user's sleep confidence interval, including:

[0069] If the periodically acquired respiratory rate values ​​are all outside the respiratory confidence interval, the periodically acquired body temperature values ​​are all above the maximum value of the body temperature confidence interval, and the periodically acquired heart rate values ​​are all above the maximum value of the heart rate confidence interval, the server determines that the user's sleep state is that of intoxicated falling asleep.

[0070] Understandably, the sleep state of an intoxicated user can be accurately determined by combining the characteristics of changes in their vital signs. Specifically, after determining the confidence intervals for heart rate, respiration, and body temperature, the server can determine the user's sleep state as intoxicated sleep if the periodically acquired respiratory rate values ​​are all outside the respiratory confidence interval, the periodically acquired body temperature values ​​are all above the maximum value of the body temperature confidence interval, and the periodically acquired heart rate values ​​are all above the maximum value of the heart rate confidence interval. As an example, the periodically acquired respiratory rate, heart rate, and body temperature values ​​can be obtained three consecutive times at preset intervals. Thus, if the respiratory rate values ​​obtained three consecutive times at preset intervals are all outside the respiratory confidence interval, the body temperature values ​​obtained three consecutive times at preset intervals are all above the maximum value of the body temperature confidence interval, and the heart rate values ​​obtained three consecutive times at preset intervals are all above the maximum value of the heart rate confidence interval, the server can determine the user's sleep state as intoxicated sleep. This method enables accurate determination of a user's sleep state.

[0071] Figure 4 This is a schematic diagram of a method for determining sleep intervention strategies provided in an embodiment of this disclosure; combined with Figure 4 As shown, optionally, in S13, the server determines a sleep intervention strategy to improve the user's sleep after drinking, including:

[0072] S41, the server obtains relevant user information.

[0073] S42, the server determines a sleep intervention strategy to improve the user's sleep after drinking based on the user's relevant information.

[0074] In this solution, the user's relevant information includes the user's sleeping posture information and / or the volume information within the user's sleep environment. Specifically, the server can acquire the user's image information through its associated image sensing device to determine the user's sleeping posture; the server can also acquire the volume information within the user's sleep environment through its associated audio pickup device. This enables accurate acquisition of the user's relevant information.

[0075] Furthermore, the server can combine relevant user information to determine sleep intervention strategies to improve the user's sleep after drinking. This approach ensures that the determined sleep intervention strategies are more aligned with the user's sleeping posture and / or the characteristics of their sleep environment, providing a precise data foundation for the control process of the sleep intervention device.

[0076] Optionally, S42, the server determines sleep intervention strategies to improve the user's sleep after drinking, based on the user's relevant information, including:

[0077] When the user's sleeping posture information indicates that the user is in an unhealthy sleeping posture, the sleep intervention strategy determined to improve the user's sleep after drinking alcohol is to raise the position of the user's back on a smart mattress to guide the user to change their sleeping posture.

[0078] This solution allows for the pre-setting of various undesirable sleeping positions. For example, undesirable sleeping positions include prone, curled-up, and surrender-like positions. Thus, when the user's sleeping position information indicates an undesirable position, the sleep intervention strategy for improving the user's sleep after drinking alcohol is determined to be raising the smart mattress at the user's back level to guide the user to change their sleeping position. This solution, by adjusting the height of the smart mattress at a target position, guides the user to adjust from their current undesirable sleeping position to a side-lying position, effectively improving the sleep quality of intoxicated users.

[0079] Optionally, if the volume in the user's sleep environment exceeds a preset noise standard, the target smart device generating the sound is identified; the server sends a confirmation reminder to the user to turn off the target smart device; if no confirmation is received from the user within a preset time period (30 seconds), the target smart device is turned off. This method saves power while providing a quiet sleep environment for intoxicated users.

[0080] Figure 5 This is a schematic diagram of a device for sleep intervention provided in an embodiment of this disclosure; combined with Figure 5 As shown, this embodiment of the present disclosure provides a device for sleep intervention, including an acquisition module 51, a first determination module 52, a second determination module 53, and a control module 54. The acquisition module 51 is configured to periodically acquire the user's vital sign parameters when the user is determined to be asleep; the first determination module 52 is configured to determine the user's sleep state based on the periodically acquired vital sign parameters; the second determination module 53 is configured to determine a sleep intervention strategy to improve the user's sleep after drinking alcohol when the user's sleep state is sleep while intoxicated; and the control module 54 is configured to control a target sleep intervention device to execute the sleep intervention strategy.

[0081] The sleep intervention device provided in this disclosure periodically acquires the user's vital signs parameters when the user is confirmed to be asleep; determines the user's sleep state based on the periodically acquired vital signs parameters; determines a sleep intervention strategy to improve the user's sleep after drinking alcohol when the user's sleep state is confirmed to be sleep-associated with intoxication; and controls the target sleep intervention device to execute the sleep intervention strategy. This approach allows for accurate determination of the user's sleep state by combining periodically acquired vital signs parameters. When the user's sleep state is confirmed to be sleep-associated with intoxication, a precise sleep intervention strategy to improve the user's sleep after drinking alcohol can be determined. By controlling the target sleep intervention device to execute the sleep intervention strategy, sleep intervention can be performed on intoxicated users, effectively improving their sleep quality and meeting their need for precise control of the sleep intervention device.

[0082] Figure 6 This is a schematic diagram of another device for sleep intervention provided in an embodiment of this disclosure; combined with Figure 6 As shown, this disclosure provides an apparatus 200 for sleep intervention, including a processor 201 and a memory 202. Optionally, the apparatus may further include a communication interface 203 and a bus 204. The processor 201, communication interface 203, and memory 202 can communicate with each other via the bus 204. The communication interface 203 can be used for information transmission. The processor 201 can call logical instructions in the memory 202 to execute the sleep intervention method described in the above embodiments.

[0083] Furthermore, the logical instructions in the aforementioned memory 202 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0084] The memory 202, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 201 executes functional applications and data processing by running the program instructions / modules stored in the memory 202, thereby implementing the sleep intervention method in the above embodiments.

[0085] The memory 202 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 202 may include high-speed random access memory and may also include non-volatile memory.

[0086] This disclosure provides a sleep intervention device, including the aforementioned sleep intervention apparatus 200. The sleep intervention apparatus 200 is installed within the sleep intervention device. The installation relationship described herein is not limited to placement within the sleep intervention device, but also includes installation connections with other components of the sleep intervention device, including but not limited to physical connections, electrical connections, or signal transmission connections. Those skilled in the art will understand that the sleep intervention apparatus 200 can be adapted to any feasible sleep intervention device body, thereby realizing other feasible embodiments.

[0087] This disclosure provides a computer-readable storage medium storing computer-executable instructions configured to perform the above-described method for sleep intervention.

[0088] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0089] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, including: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code; it can also be a transient storage medium.

[0090] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0091] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0092] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0093] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A method for sleep intervention, characterized in that, include: Once it is determined that the user has fallen asleep, the user's vital signs parameters are periodically acquired. Determining a user's sleep state based on periodically acquired vital sign parameters includes: acquiring the user's historical sleep data; determining the user's sleep confidence interval based on the user's historical sleep data; and determining the user's sleep state based on the periodically acquired vital sign parameters and the user's sleep confidence interval. The vital sign parameters include heart rate, respiratory rate, and body temperature, and the user's sleep confidence interval includes heart rate confidence interval, respiratory rate confidence interval, and body temperature confidence interval. In the case that the user's sleep state is intoxicated, a sleep intervention strategy for improving the user's sleep after drinking is determined, including adjusting the temperature of the smart air conditioner in the sleep environment of the intoxicated user until the intoxicated user's vital signs parameters fall into the user's sleep confidence interval. Control the target sleep intervention device to execute the sleep intervention strategy; Determining the user's sleep confidence interval based on the user's historical sleep data includes: calculating the average value and variance of the historical sleep data; and determining the user's sleep confidence interval based on the average value and variance of the historical sleep data.

2. The method according to claim 1, characterized in that, Determining the user's sleep confidence interval based on the average and variance of the historical sleep data includes: [ ] Where X is the average value of historical sleep data, Z is the reference factor, S is the variance of historical sleep data, and n is the number of samples in historical sleep data.

3. The method according to claim 1, characterized in that, Determining the user's sleep state based on the periodically acquired vital sign parameter values ​​and the user's sleep confidence interval includes: If the periodically acquired respiratory rate values ​​are all outside the respiratory confidence interval, the periodically acquired body temperature values ​​are all above the maximum value of the body temperature confidence interval, and the periodically acquired heart rate values ​​are all above the maximum value of the heart rate confidence interval, then the user's sleep state is determined to be sleep while intoxicated.

4. The method according to claim 1, characterized in that, The identified sleep intervention strategies for improving a user's sleep after drinking include: Obtain the relevant information of the user; Based on the user's relevant information, determine sleep intervention strategies to improve the user's sleep after drinking alcohol.

5. The method according to claim 4, characterized in that, The user's relevant information includes the user's sleeping posture information. The step of determining a sleep intervention strategy to improve the user's sleep after drinking alcohol, based on the user's relevant information, further includes: If the user's sleeping posture information indicates that the user is in a poor sleeping posture, the sleep intervention strategy determined to improve the user's sleep after drinking is to raise the smart mattress at the position of the user's back to guide the user to change their sleeping posture.

6. A device for sleep intervention, characterized in that, include: The acquisition module is configured to periodically acquire the user's vital sign parameter values ​​when it is determined that the user has fallen asleep; The first determining module is configured to determine a user's sleep state based on periodically acquired vital sign parameter values, including: acquiring the user's historical sleep data; determining the user's sleep confidence interval based on the user's historical sleep data; and determining the user's sleep state based on the periodically acquired vital sign parameter values ​​and the user's sleep confidence interval; wherein the vital sign parameter values ​​include heart rate, respiratory rate, and body temperature, and the user's sleep confidence interval includes heart rate confidence interval, respiratory rate confidence interval, and body temperature confidence interval; The second determining module is configured to determine a sleep intervention strategy to improve the user's sleep after drinking when the user's sleep state is intoxicated, including adjusting the temperature of the smart air conditioner in the intoxicated user's sleep environment until the intoxicated user's vital signs parameters fall into the user's sleep confidence interval. The control module is configured to control the target sleep intervention device to execute the sleep intervention strategy; Determining the user's sleep confidence interval based on the user's historical sleep data includes: calculating the average value and variance of the historical sleep data; and determining the user's sleep confidence interval based on the average value and variance of the historical sleep data.

7. A device for sleep intervention, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to perform the method for sleep intervention as described in any one of claims 1 to 5 when executing the program instructions.

8. A sleep intervention device, characterized in that, Includes the device for sleep intervention as described in claim 6 or 7.

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