Sleep state information processing method and related device

Abstract

The present application provides a method for processing sleep state information and a related device, the method comprising: when detecting that a target user is in a sleep state, collecting the first sleep sound data of the target user in the current sleep event; when detecting that the target user's current sleep event is an event of accompanying a child to sleep, obtaining a pre-stored first pre-alert decibel; analyzing that the target user has snoring behavior based on the collected first sleep sound data, and the snoring sound decibel of the snoring behavior is greater than or equal to the first pre-alert decibel; and executing a first reminder operation. The embodiment of the present application can vibrate the smart watch to prompt the user to change the sleeping position and adjust the breathing when it is detected that the target user is snoring and the snoring sound decibel is high, thereby reducing the snoring sound decibel, avoiding affecting the child's sleep, and improving the user's experience.

Description

Technical Field

[0001] The present application belongs to the technical field of sleep state information processing, and specifically relates to a sleep state information processing method and related devices. Background Art

[0002] At present, smart watches can collect some sleep status information of users, and users can also view this sleep status information, but the actual smart watch does not have the function of analyzing the user's snoring behavior based on the sleep status information, nor does it have a specific function to alleviate the user's snoring behavior. Summary of the invention

[0003] The embodiment of the present application provides a sleep status information processing method and related devices. When a smart watch detects that a target user is snoring and the snoring decibel is high, the smart watch vibrates to prompt the user to change sleeping posture and adjust breathing, thereby reducing the snoring decibel, avoiding affecting children's sleep, and improving the user experience.

[0004] In a first aspect, an embodiment of the present application provides a method for processing sleep state information, which is applied to a smart watch of a target user; the method comprises:

[0005] Acquire a sleep sound data set of the target user, the sleep sound data set comprising a plurality of historical sleep sound data, wherein a single historical sleep sound data comprises ambient sound data of the target user in a sleeping state and / or snoring sound data of the target user; determine at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his / her snoring sound while accompanying the child to sleep; determine a first pre-alert decibel according to the at least one historical sleep sound data;

[0006] When it is detected that the target user is in a sleeping state, collecting the first sleeping sound data of the target user in the current sleeping event;

[0007] When it is detected that the target user's current sleep event is an event of accompanying a child to sleep, the first pre-stored pre-alert decibel is obtained, where the first pre-alert decibel is smaller than the lowest decibel that wakes up the child due to the snoring behavior of the target user;

[0008] Analyzing the first sleep sound data collected to determine that the target user has snoring behavior, and the snoring sound decibel of the snoring behavior is greater than or equal to the first pre-warning decibel;

[0009] A first reminder operation is performed to interrupt the trend of the snoring sound of the target user's snoring behavior increasing from the current decibel to the minimum decibel. The first reminder operation is a vibration operation performed according to a preset vibration strategy.

[0010] In a second aspect, an embodiment of the present application provides a sleep state information processing device, which is applied to a smart watch of a target user; the sleep state information processing device includes: a collection unit, an acquisition unit, a determination unit, an analysis unit and an execution unit, wherein:

[0011] The determination unit is used to obtain a sleep sound data set of the target user, wherein the sleep sound data set includes a plurality of historical sleep sound data, and a single historical sleep sound data includes ambient sound data of the target user in a sleeping state and / or snoring sound data of the target user; determine at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his snoring sound while accompanying the child to sleep; and determine a first pre-alert decibel according to the at least one historical sleep sound data;

[0012] The collecting unit is used to collect the first sleep sound data of the target user in the current sleep event when detecting that the target user is in a sleep state;

[0013] The acquisition unit is further configured to acquire the first pre-alert decibel stored in advance when it is detected that the target user's current sleep event is an event of accompanying a child to sleep, wherein the first pre-alert decibel is smaller than the lowest decibel that causes the target user's snoring behavior to wake up the child;

[0014] The analysis unit is used to analyze, based on the collected first sleep sound data, whether the target user has snoring behavior, and the decibel of the snoring sound of the snoring behavior is greater than or equal to the first pre-warning decibel;

[0015] The execution unit is used to execute a first reminder operation to interrupt the snoring sound of the target user's snoring behavior and the trend of the snoring sound continuously increasing from the current decibel to the minimum decibel. The first reminder operation is a vibration operation executed according to a preset vibration strategy.

[0016] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

[0017] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps in the first aspect of the embodiment of the present application.

[0018] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0019] It can be seen that in the embodiment of the present application, the smart watch first obtains a sleep sound data set of the target user, and determines at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his snoring sound when accompanying the child to sleep, and determines the first pre-reminder decibel based on the at least one historical sleep sound data, and then when it is detected that the target user is in a sleeping state, the first sleep sound data of the target user in the current sleep event is collected, and then when it is detected that the target user's sleep event this time is an event of accompanying the child to sleep, the pre-stored first pre-reminder decibel is obtained, and the first pre-reminder decibel is less than the lowest decibel that wakes up the child due to the snoring behavior of the target user, and then, based on the collected first sleep sound data, it is analyzed that the target user has snoring behavior, and the snoring sound decibel of the snoring behavior is greater than or equal to the first pre-reminder decibel, and finally, the first reminder operation is executed to interrupt the trend that the snoring sound of the target user's snoring behavior continues to increase from the current decibel to the lowest decibel, and the first reminder operation is a vibration operation performed according to a preset vibration strategy. When the target user is detected snoring and the snoring sound is high in decibels, the smart watch will vibrate to prompt the user to change sleeping posture and adjust breathing, thereby reducing the decibels of snoring sound, avoiding affecting children's sleep, and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them,

[0021] Figure 1 It is a schematic diagram of the architecture of a sleep state information processing system provided by an embodiment of the present application;

[0022] Figure 2 It is a flowchart of a sleep state information processing method provided by an embodiment of the present application;

[0023] Figure 3 This is a schematic diagram of a snoring reminder setting display interface of a smart watch provided in an embodiment of the present application;

[0024] Figure 4This is a schematic diagram of a sleep event setting display interface of a smart watch provided in an embodiment of the present application;

[0025] Figure 5 It is a schematic diagram of a display interface for setting vibration parameters of a smart watch provided in an embodiment of the present application;

[0026] Figure 6 This is a schematic diagram of a display interface of a snoring control report of a smart watch provided in an embodiment of the present application;

[0027] Figure 7 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application;

[0028] Figure 8 It is a block diagram of the functional units of a sleep state information processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0030] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0031] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0032] In the embodiments of the present application, "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent the following three situations: A exists alone; A and B exist at the same time; B exists alone. Among them, A and B can be singular or plural.

[0033] In the embodiment of the present application, the symbol " / " can indicate that the objects associated with each other are in an "or" relationship. In addition, the symbol " / " can also indicate a division sign, that is, performing a division operation. For example, A / B can indicate A divided by B.

[0034] In the embodiments of the present application, "at least one item" or similar expressions refer to any combination of these items, including any combination of single items or plural items, and refer to one or more, and multiple refers to two or more. For example, at least one item of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0035] In the embodiments of the present application, "equal to" can be used in conjunction with greater than, and is applicable to the technical solution adopted when greater than, and can also be used in conjunction with less than, and is applicable to the technical solution adopted when less than. When equal to is used in conjunction with greater than, it is not used in conjunction with less than; when equal to is used in conjunction with less than, it is not used in conjunction with greater than.

[0036] In order to better understand the solutions of the embodiments of the present application, the electronic devices that may be involved in the embodiments of the present application are first introduced below.

[0037] The electronic devices involved in the embodiments of the present application may include various handheld devices with wireless communication functions, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem, as well as various forms of user equipment (UE), mobile stations (MS), electronic devices (terminal devices), etc. For the convenience of description, the above-mentioned devices are collectively referred to as electronic devices. The electronic device can also be a smart watch.

[0038] See also Figure 1 , Figure 1 Schematic diagram of the architecture of a sleep state information processing system provided by an embodiment of the present application. Figure 1 As shown, the system includes a smart watch 10.

[0039] Among them, the smart watch 10 includes a vibration module 101 and an electric shock module 102. The vibration module 101 can vibrate with a certain number of vibrations, vibration amplitude and vibration duration to assist the target user to change the sleeping posture. The electric shock module 102 can electrically stimulate the user with a certain intensity to assist the user to change the sleeping posture, change the breathing frequency and relieve snoring.

[0040] Among them, the smart watch 10 includes a sleep monitoring module 103 and an audio acquisition module 104. The sleep monitoring module 103 is used to detect whether the target user has fallen asleep. When it is detected that the target user has fallen asleep, a collection instruction is sent to the audio acquisition module 104. The audio acquisition module 104 responds to the collection instruction and collects the first sleep sound data and the second sleep sound data of the target user.

[0041] The smart watch 10 includes a memory, which is used to store the first pre-alert decibel, the lowest decibel at which the target user's snoring behavior wakes up the child, and the second pre-alert decibel.

[0042] Among them, users can choose to turn on vibration reminders and electrical stimulation reminders when snoring on the snoring reminder setting display interface of the smart watch, for example: Figure 3 As shown, Figure 3 This is a schematic diagram of a snoring reminder setting display interface of a smart watch provided in an embodiment of the present application. The snoring reminder setting display interface of the smart watch in the figure includes display time, smart watch battery power, snoring vibration reminder function on / off button, snoring electrical stimulation reminder function on / off button. The snoring vibration reminder function of the current display interface is on, the snoring electrical stimulation reminder function is on, the displayed time is 10:32, and the smart watch battery power is 60%.

[0043] In one possible example, the smart watch 10 first obtains a sleep sound data set of the target user, and determines at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his or her snoring while accompanying the child to sleep, and determines the first pre-reminder decibel based on the at least one historical sleep sound data. Then, when it is detected that the target user is in a sleeping state, the first sleep sound data of the target user in the current sleep event is collected. Then, when it is detected that the target user's sleep event this time is an event of accompanying the child to sleep, the pre-stored first pre-reminder decibel is obtained, and the first pre-reminder decibel is less than the lowest decibel that wakes up the child due to the snoring behavior of the target user. Then, based on the collected first sleep sound data, it is analyzed that the target user has snoring behavior, and the decibel of the snoring sound of the snoring behavior is greater than or equal to the first pre-reminder decibel. Finally, the first reminder operation is performed to interrupt the trend of the snoring sound of the target user's snoring behavior continuously increasing from the current decibel to the lowest decibel. The first reminder operation is a vibration operation performed according to a preset vibration strategy. When the target user is detected snoring and the snoring sound is high in decibels, the smart watch will vibrate to prompt the user to change sleeping posture and adjust breathing, thereby reducing the decibels of snoring sound, avoiding affecting children's sleep, and improving the user experience.

[0044] See also Figure 2 , Figure 2 : is a flowchart of a sleep state information processing method provided by an embodiment of the present application, which is applied to a smart watch of a target user, and the method includes:

[0045] Step S201 : when it is detected that the target user is in a sleeping state, first sleeping sound data of the target user in a current sleeping event is collected.

[0046] The first sleeping sound data includes the ambient sound data of the target user in the current sleeping state and / or the snoring sound data of the target user.

[0047] The target user may be the child's parent, including but not limited to parents, grandfather, grandmother, etc.

[0048] Step S202, when it is detected that the target user's current sleep event is an event of accompanying a child to sleep, a pre-stored first pre-alert decibel is obtained, where the first pre-alert decibel is smaller than the lowest decibel that causes the target user's snoring behavior to wake up the child.

[0049] The target user's sleeping time may include events of accompanying children to sleep and events of not accompanying children to sleep.

[0050] Among them, the smart watch includes a memory, and the memory is used to store the first pre-reminder decibel and the second pre-reminder decibel. The second pre-reminder decibel can be an empirical value obtained through big data analysis, or it can be a preset fixed value.

[0051] Among them, the user can actively mark the sleep event as an event to accompany the child to sleep before going to bed, such as Figure 4 As shown, Figure 4 This is a schematic diagram of the sleep event setting display interface of a smart watch provided in an embodiment of the present application. The sleep event setting display interface of the smart watch in the figure includes display time, battery power of the smart watch, sleep event occurrence time, sleep event type (this sleep event is an event of accompanying a child to fall asleep / this sleep event is an event of not accompanying a child to fall asleep) and a confirmation button. The current display time of the display interface is 22:01, the battery power of the smart watch is 60%, the sleep event occurrence time selected is July 15, 2024, and the sleep event type selected is that this sleep event is an event of accompanying a child to fall asleep.

[0052] Step S203: analyzing, based on the collected first sleep sound data, whether the target user has snoring behavior and the decibel of the snoring sound of the snoring behavior is greater than or equal to the first pre-warning decibel.

[0053] Among them, the target acoustic features can be obtained by extracting the acoustic features of the first sleep sound data, and the target acoustic features can be input into a pre-trained snoring prediction model to obtain a snoring prediction result. When the snoring prediction result shows that snoring exists, it is considered that the target user has snoring behavior. Furthermore, the real-time snoring sound decibel of the user can be determined based on the first sleep sound data.

[0054] Step S204, executing a first reminder operation to interrupt the snoring sound of the target user's snoring behavior from continuously increasing from the current decibel to the minimum decibel, wherein the first reminder operation is a vibration operation executed according to a preset vibration strategy.

[0055] Optionally, if it is analyzed based on the collected first sleep sound data that the target user has snoring behavior and the snoring sound decibel of the snoring behavior is greater than or equal to the second pre-alert decibel, the first reminder operation is performed.

[0056] Among them, the smart watch vibrates to assist the target user in adjusting the sleeping posture, thereby interrupting the target user's snoring behavior and increasing the snoring sound from the current decibel to the minimum decibel.

[0057] The preset vibration strategy includes the preset number of vibrations, the preset duration of a single vibration, and the preset amplitude of a single vibration. It supports the target user's customized settings or the empirical value determined by the cloud server based on big data analysis that does not excessively interfere with the user's own sleep quality. Figure 5 As shown, Figure 5 This is a schematic diagram of a display interface for the vibration parameter setting of a smart watch provided in an embodiment of the present application. The display interface for the vibration parameter setting of the snoring vibration reminder includes display time, smart watch battery power, vibration duration setting, vibration number setting and vibration amplitude setting (high, medium and low). The current display time of the vibration parameter setting display interface is 10:32, the smart watch battery power is 60%, the set vibration duration is 30 seconds, the set vibration number is 100 times, and the set vibration amplitude is medium.

[0058] Among them, after the target user wakes up, the smart watch can display a simple report on the target user's snoring control, such as Figure 6 As shown, Figure 6 This is a schematic diagram of the display interface of the snoring control report of a smart watch provided in an embodiment of the present application. The display interface of the snoring control report on the display screen of the smart watch in the figure shows content including display time, battery power of the smart watch and snoring control report. The displayed time is 8:01, the battery power of the smart watch is 51%, and the content of the snoring control report is "It was detected that you had snoring behavior last night, and the snoring sound was very loud. After the snoring vibration reminder was given to you, the snoring behavior was interrupted."

[0059] It can be seen that in the embodiment of the present application, the smart watch first obtains a sleep sound data set of the target user, and determines at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his snoring sound when accompanying the child to sleep, and determines the first pre-reminder decibel based on the at least one historical sleep sound data, and then when it is detected that the target user is in a sleeping state, the first sleep sound data of the target user in the current sleep event is collected, and then when it is detected that the target user's sleep event this time is an event of accompanying the child to sleep, the pre-stored first pre-reminder decibel is obtained, and the first pre-reminder decibel is less than the lowest decibel that wakes up the child due to the snoring behavior of the target user, and then, based on the collected first sleep sound data, it is analyzed that the target user has snoring behavior, and the snoring sound decibel of the snoring behavior is greater than or equal to the first pre-reminder decibel, and finally, the first reminder operation is executed to interrupt the trend that the snoring sound of the target user's snoring behavior continues to increase from the current decibel to the lowest decibel, and the first reminder operation is a vibration operation performed according to a preset vibration strategy. When the target user is detected snoring and the snoring sound is high in decibels, the smart watch will vibrate to prompt the user to change sleeping posture and adjust breathing, thereby reducing the decibels of snoring sound, avoiding affecting children's sleep, and improving the user experience.

[0060] Smartwatch

[0061] In a possible example, before detecting that the target user is in a sleeping state, the method may further include the following steps: obtaining a sleep sound data set of the target user, the sleep sound data set including a plurality of historical sleep sound data, a single historical sleep sound data including ambient sound data of the target user in a sleeping state and / or snoring sound data of the target user; determining at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his or her snoring sound while accompanying the child to sleep; and determining the first pre-alert decibel based on the at least one historical sleep sound data.

[0062] Among them, the memory of the smart watch can store a set of sleep sound data of the target user; taking into account that each child has a different tolerance for snoring when sleeping, that is, the decibels of the sound woken up by snoring are different, the first pre-alert decibel can be determined based on at least one historical sleep sound data of the target user's snoring sound that woke the child up while the child was sleeping.

[0063] Among them, the environmental sound data includes but is not limited to environmental noise, the sound of the target user turning over and changing sleeping posture, children's voices, target user's voices, the sound of children pushing / shaking the target user, etc.

[0064] The first pre-warning decibel is an average decibel of snoring determined based on at least one historical sleep sound data.

[0065] It can be seen that in this example, the smart watch can first determine from the sleep sound data set at least one historical sleep sound data of the target user waking up the child due to his or her snoring when accompanying the child to sleep, and determine the first pre-alert decibel based on the at least one historical sleep sound data, which is conducive to improving the accuracy of the determined first pre-alert decibel.

[0066] In one possible example, the method may further include the following steps for determining at least one historical sleep sound data in the sleep sound data set in which the target user woke up the child due to his or her snoring while accompanying the child to sleep: performing the following processing on each historical sleep sound data in the sleep sound data set to obtain the at least one historical sleep sound data in which there is an event of accompanying the child to sleep: performing sound feature analysis and extraction on the currently processed historical sleep sound data to obtain snoring features characterizing snoring behavior and ambient sound features characterizing non-snoring behavior; if it is determined according to the ambient sound features that there is an event of accompanying the child to sleep in the currently processed historical sleep sound data, marking the currently processed historical sleep sound data as historical sleep sound data in which there is an event of accompanying the child to sleep; if it is determined according to the ambient sound features that there is no event of accompanying the child to sleep in the currently processed historical sleep sound data, continuing to process the next historical sleep sound data to be processed until all the historical sleep sound data in the sleep sound data set are processed.

[0067] Among them, determining based on the ambient sound characteristics that the currently processed historical sleep sound data contains an event of accompanying a child to sleep can be identifying the voice of a child asking the target user to stop snoring after being woken up, and identifying the sound of a child pushing / shaking the target user to wake the user up. The child’s speaking voice can be “Grandma, stop snoring.”

[0068] Among them, sound features may include acoustic features, including but not limited to energy concentration areas representing timbre, resonance peak frequency, resonance peak intensity, bandwidth, duration representing speech prosodic characteristics, fundamental frequency, average speech power, filter group features, sensory weighted linear prediction features and Mel-frequency cepstral coefficients, etc.

[0069] Specifically, snoring features can be extracted from historical sleep sound data to extract snoring features that characterize snoring behavior, and sound features other than non-snoring features can be used as environmental sound features that characterize non-snoring behavior.

[0070] It can be seen that in this example, the smart watch can analyze and extract sound features of the historical sleep sound data in the sleep sound data set, obtain snoring features that characterize snoring behavior and environmental sound features that characterize non-snoring behavior, and further mark at least one historical sleep sound data in which the target user wakes up the child due to his snoring while accompanying the child to sleep. This is conducive to improving the intelligence of information processing of the smart watch.

[0071] In a possible example, the method for determining the first pre-alert decibel according to the at least one historical sleep sound data may further include the following steps: if the at least one historical sleep sound data is a single data, statistically analyzing the reference decibel mean of the snoring signal of the single historical sleep sound data in the target time period; and determining the first pre-alert decibel according to the reference decibel mean, wherein the target time period is the time range in which the audio signal representing the child's voice in the environmental sound feature of the single historical sleep sound data is located, the duration of the child's voice is less than a preset duration, and the time starting point of the single historical sleep sound data and the time starting point of the time range contain sound features other than the child's voice; if the at least one historical sleep sound data is at least two, performing the following processing on each of the at least two historical sleep sound data to obtain at least two reference decibel means: statistically analyzing the reference decibel mean of the snoring signal of the currently processed historical sleep sound data in the target time period; and determining the target decibel mean according to the at least two reference decibel means; and determining the first pre-alert decibel according to the target decibel mean.

[0072] Among them, when at least one historical sleep sound data is single, the reference decibel average can be used as the first pre-warning decibel; optionally, the first pre-warning decibel can also be obtained by the following formula, first pre-warning decibel = reference decibel average * preset ratio, the preset ratio is manually set or system default, and is not limited here, for example: the preset ratio can be 80%.

[0073] The preset duration may be manually set or a system default, and is not limited here.

[0074] The child's voice in the target time period may be the child's voice that tells the target user not to snore, and the target time period may be a fixed time range, such as 10 seconds.

[0075] The target decibel mean is a mean value calculated from at least two reference decibel mean values.

[0076] It can be seen that in this example, the smart watch determines the first pre-alert decibel based on at least one historical sleep sound data, which is conducive to improving the accuracy of the determined first pre-alert decibel.

[0077] In one possible example, after the first reminder operation is executed to interrupt the snoring behavior of the target user and the volume of the snoring sound continues to increase from the current decibel to the minimum decibel, the above method may include the following steps: continue to collect second sleep sound data of the target user; analyze that the decibel of the snoring sound of the target user is greater than or equal to the minimum decibel based on the second sleep sound data that continues to be collected; and execute a second reminder operation to further interrupt the snoring behavior of the target user, the second reminder operation being an electrical stimulation reminder operation that outputs an electrical stimulation signal.

[0078] The second sleeping sound data includes the ambient sound data of the target user in the current sleeping state and / or the snoring sound data of the target user.

[0079] Among them, when the smart watch performs the vibration operation, the snoring sound that fails to interrupt the target user's snoring behavior continues to increase from the current decibel to the minimum decibel. At this time, stronger electrical stimulation needs to be applied to the target user to assist the target user in adjusting his sleeping position and breathing to interrupt the snoring behavior.

[0080] Optionally, the smart watch can monitor whether the current sleep state of the target user is a light sleep state or a deep sleep state. If it is detected that the current sleep state is a light sleep state, the smart watch determines to output an electrical stimulation reminder operation of an electrical stimulation signal with a first electrical stimulation intensity; if it is detected that the current sleep state is a deep sleep state, the smart watch determines to output an electrical stimulation reminder operation of an electrical stimulation signal with a second electrical stimulation intensity; the first electrical stimulation intensity is less than the second electrical stimulation intensity.

[0081] Optionally, the electrical stimulation signal corresponds to multiple intensities, for example: a first electrical stimulation intensity, a second electrical stimulation intensity and a third electrical stimulation intensity, wherein the first electrical stimulation intensity < the second electrical stimulation intensity < the third electrical stimulation intensity; if the second reminder operation is an electrical stimulation reminder operation that outputs an electrical stimulation signal of the first electrical stimulation intensity, after the smart watch executes the second reminder operation, it continues to collect the third sleep sound data of the target user and detects whether the target user has changed his sleeping position. If the third sleep sound data analyzes that the decibel of the target user's snoring has not decreased and the target user's sleeping position has not changed, the electrical stimulation signal of the first electrical stimulation intensity output in the second reminder operation is gradually increased to an electrical stimulation signal of the second electrical stimulation intensity and an electrical stimulation signal of the third electrical stimulation intensity to assist the target user in changing his sleeping position and reducing the decibel of snoring.

[0082] It can be seen that in this example, the smart watch can also perform a second reminder operation to interrupt the target user's snoring behavior when the first reminder operation fails to effectively interrupt the target user's snoring behavior and the snoring sound continues to increase from the current decibel to the minimum decibel, so as to avoid disturbing the child's sleep, which is conducive to improving the user experience.

[0083] In one possible example, it is detected that the target user's sleep event this time is an event of accompanying a child to sleep. The above method may include the following steps: obtaining discrete information from a mobile terminal device, the discrete information including call records and target schedule information, the target schedule information being a schedule for the target user to accompany the child to sleep; determining a predicted result that the target user is currently accompanying the child to sleep based on the discrete information; when the predicted result is that the target user is currently accompanying the child to sleep, determining that the target user's sleep event this time is an event of accompanying the child to sleep.

[0084] Among them, the smart watch is connected to the mobile terminal device for communication and can obtain discrete information from the mobile terminal device.

[0085] For example, the target schedule information analyzes that the child lives in the school from Monday to Thursday, and sleeps with the target user at home from Friday to Sunday, and the call record information of the target user and the child analyzes that the target user picks the child up on Friday afternoon. Based on this, it can be predicted that the target user is currently sleeping with the child. The prediction result is that the target user is currently sleeping with the child; if the target user is the child’s father, the target schedule information analyzes that the child lives in the school from Monday to Thursday, and sleeps with the parents at home from Friday to Sunday, and the call record information of the target user and the child analyzes that the target user does not pick up the child, and the grandfather picks the child up and takes him back to his hometown on Friday afternoon. Based on this, it can be predicted that the target user is currently sleeping with the child. The prediction result is that the target user is not currently sleeping with the child.

[0086] It can be seen that in this example, the smart watch analyzes whether the target user's sleep event is an event of accompanying the child to sleep based on the acquired discrete information, which is conducive to improving the intelligence of the smart watch's information processing.

[0087] In one possible example, in terms of detecting that the target user's sleep event this time is an event of accompanying a child to sleep, the above method may include the following steps: acquiring historical sampled sound data before the target user was in a sleeping state; and analyzing based on the historical sampled sound data that the target user's sleep event this time is an event of accompanying the child to sleep.

[0088] The historical sampled sound data includes the target user's voice and / or the child's voice and / or environmental sound.

[0089] For example, historical sampled sound data: the target user says "Xiao Shuai, it's past 10 o'clock, stop playing with your phone and go to bed", the child says "Okay, I'll go to bed now", and the ambient sound is the sound of the child putting down the phone and adjusting his sleeping position to prepare for bed. It is analyzed that the target user's sleep event this time is an event of accompanying the child to sleep.

[0090] It can be seen that in this example, the smart watch determines whether the target user's current sleep event is an event of accompanying the child to sleep based on the historical sampled sound data before the target user was in a sleeping state, which is conducive to improving the intelligence of information processing of the smart watch.

[0091] See also Figure 7 , Figure 7 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, which is applied to a smart watch of a target user; Figure 7 As shown, the electronic device includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs are configured to execute the following steps by the processor:

[0092] Acquire a sleep sound data set of the target user, the sleep sound data set comprising a plurality of historical sleep sound data, wherein a single historical sleep sound data comprises ambient sound data of the target user in a sleeping state and / or snoring sound data of the target user; determine at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his / her snoring sound while accompanying the child to sleep; determine a first pre-alert decibel according to the at least one historical sleep sound data;

[0093] When it is detected that the target user is in a sleeping state, collecting the first sleeping sound data of the target user in the current sleeping event;

[0094] When it is detected that the target user's current sleep event is an event of accompanying a child to sleep, the first pre-stored pre-alert decibel is obtained, where the first pre-alert decibel is smaller than the lowest decibel that wakes up the child due to the snoring behavior of the target user;

[0095] Analyzing the first sleep sound data collected to determine that the target user has snoring behavior, and the snoring sound decibel of the snoring behavior is greater than or equal to the first pre-warning decibel;

[0096] A first reminder operation is performed to interrupt the trend of the snoring sound of the target user's snoring behavior increasing from the current decibel to the minimum decibel. The first reminder operation is a vibration operation performed according to a preset vibration strategy.

[0097] It can be seen that in the embodiment of the present application, the smart watch first obtains a sleep sound data set of the target user, and determines at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his snoring sound when accompanying the child to sleep, and determines the first pre-reminder decibel based on the at least one historical sleep sound data, and then when it is detected that the target user is in a sleeping state, the first sleep sound data of the target user in the current sleep event is collected, and then when it is detected that the target user's sleep event this time is an event of accompanying the child to sleep, the pre-stored first pre-reminder decibel is obtained, and the first pre-reminder decibel is less than the lowest decibel that wakes up the child due to the snoring behavior of the target user, and then, based on the collected first sleep sound data, it is analyzed that the target user has snoring behavior, and the snoring sound decibel of the snoring behavior is greater than or equal to the first pre-reminder decibel, and finally, the first reminder operation is executed to interrupt the trend that the snoring sound of the target user's snoring behavior continues to increase from the current decibel to the lowest decibel, and the first reminder operation is a vibration operation performed according to a preset vibration strategy. When the target user is detected snoring and the snoring sound is high in decibels, the smart watch will vibrate to prompt the user to change sleeping posture and adjust breathing, thereby reducing the decibels of snoring sound, avoiding affecting children's sleep, and improving the user experience.

[0098] In one possible example of the smart watch, in determining at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to the snoring sound of the target user while accompanying the child to sleep, the program includes instructions for performing the following steps:

[0099] The following processing is performed for each historical sleep sound data in the sleep sound data set to obtain the at least one historical sleep sound data having an accompanying child sleep event:

[0100] Analyze and extract sound features of the historical sleep sound data currently being processed to obtain snoring sound features that characterize snoring behavior and environmental sound features that characterize non-snoring behavior;

[0101] If it is determined according to the environmental sound feature that the historical sleep sound data currently being processed contains an accompanying child sleep event, marking the historical sleep sound data currently being processed as historical sleep sound data containing an accompanying child sleep event;

[0102] If it is determined according to the ambient sound characteristics that the currently processed historical sleep sound data does not contain an accompanying child sleep event, then the next historical sleep sound data to be processed will continue to be processed until all the historical sleep sound data in the sleep sound data set are processed.

[0103] In a possible example, in determining the first pre-alert decibel according to the at least one historical sleep sound data, the program includes instructions for further performing the following steps:

[0104] If the at least one historical sleep sound data is single, a reference decibel mean of the snoring signal of the single historical sleep sound data in a target time period is statistically analyzed; and the first pre-warning decibel is determined according to the reference decibel mean, wherein the target time period is a time range in which an audio signal representing a child's voice in the environmental sound feature of the single historical sleep sound data is located, the duration of the child's voice is less than a preset duration, and a sound feature other than the child's voice is included between the time starting point of the single historical sleep sound data and the time starting point of the time range;

[0105] If there are at least two of the at least one historical sleep sound data, the following processing is performed for each of the at least two historical sleep sound data to obtain at least two reference decibel means: statistically analyzing the reference decibel mean of the snoring signal of the currently processed historical sleep sound data in the target time period; and, determining the target decibel mean based on the at least two reference decibel means; and, determining the first pre-warning decibel based on the target decibel mean.

[0106] In a possible example, after the first reminder operation is performed to interrupt the snoring behavior of the target user and the snoring sound level continues to increase from the current decibel to the minimum decibel, the program includes instructions for further performing the following steps:

[0107] Continuing to collect the second sleep sound data of the target user;

[0108] Analyzing, according to the second sleep sound data that is continuously collected, that the decibel of the snoring sound of the target user is greater than or equal to the minimum decibel;

[0109] A second reminder operation is performed to further interrupt the snoring behavior of the target user, and the second reminder operation is an electrical stimulation reminder operation of outputting an electrical stimulation signal.

[0110] In a possible example, in terms of detecting that the target user's sleep event is an event of accompanying a child to sleep, the program includes instructions for further performing the following steps:

[0111] Acquire discrete information from a mobile terminal device, the discrete information including call records and target schedule information, the target schedule information being a schedule for the target user to accompany the child to sleep;

[0112] Determine, based on the discrete information, a prediction result that the target user is currently accompanying the child to sleep;

[0113] When the prediction result is that the target user is currently accompanying the child to sleep, it is determined that the target user's current sleep event is an event of accompanying the child to sleep.

[0114] In a possible example, in terms of detecting that the target user's sleep event is an event of accompanying a child to sleep, the program includes instructions for further performing the following steps:

[0115] Acquire historical sampled sound data before the target user is in a sleeping state;

[0116] According to the historical sampled sound data, it is analyzed that the target user's current sleep event is an event of accompanying the child to sleep.

[0117] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that, in order to realize the above functions, the electronic device includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0118] The embodiment of the present application can divide the electronic device into functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0119] In the case of dividing each functional module into corresponding functional modules, Figure 8 is a functional unit block diagram of a sleep state information processing device provided by an embodiment of the present application, such as Figure 8 As shown, the sleep state information processing device applied to the smart watch of the target user includes: a collection unit 801, an acquisition unit 802, an analysis unit 803, an execution unit 804 and a determination unit 805, wherein:

[0120] The determining unit 805 is configured to obtain a sleep sound data set of the target user, wherein the sleep sound data set includes a plurality of historical sleep sound data, and a single historical sleep sound data includes ambient sound data of the target user in a sleeping state and / or snoring sound data of the target user; determine at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his / her snoring sound while accompanying the child to sleep; and determine the first pre-alert decibel according to the at least one historical sleep sound data;

[0121] The collecting unit 801 is used to collect the first sleep sound data of the target user in the current sleep event when detecting that the target user is in a sleep state;

[0122] The acquisition unit 802 is configured to acquire the first pre-stored pre-alert decibel when detecting that the target user's current sleep event is an event of accompanying a child to sleep, wherein the first pre-alert decibel is smaller than the lowest decibel that causes the target user's snoring behavior to wake up the child;

[0123] The analyzing unit 803 is used to analyze, based on the collected first sleep sound data, whether the target user has snoring behavior, and the decibel of the snoring sound of the snoring behavior is greater than or equal to the first pre-warning decibel;

[0124] The execution unit 804 is used to execute a first reminder operation to interrupt the snoring sound of the target user's snoring behavior from continuously increasing from the current decibel to the minimum decibel. The first reminder operation is a vibration operation executed according to a preset vibration strategy.

[0125] It can be seen that the sleep state information processing device described in the embodiment of the present application first collects the first sleep sound data of the target user in the current sleep event when it is detected that the target user is in a sleep state, and then when it is detected that the target user's sleep event this time is an event of accompanying a child to sleep, the first pre-reminder decibel stored is obtained, and the first pre-reminder decibel is less than the lowest decibel of the target user's snoring behavior that wakes up the child, and then analyzes the target user's snoring behavior based on the collected first sleep sound data, and the snoring sound decibel of the snoring behavior is greater than or equal to the first pre-reminder decibel, and finally performs the first reminder operation to interrupt the trend of the snoring sound of the target user's snoring behavior from the current decibel to the lowest decibel. The first reminder operation is a vibration operation performed according to a preset vibration strategy. When the target user is detected to be snoring and the snoring sound decibel is high, the smart watch is vibrated to prompt the user to change the sleeping posture and adjust the breathing, thereby reducing the snoring sound decibel, avoiding affecting the child's sleep, and improving the user's experience.

[0126] In a possible example, in determining at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his snoring sound while accompanying the child to sleep, the determining unit 805 is specifically configured to:

[0127] The following processing is performed for each historical sleep sound data in the sleep sound data set to obtain the at least one historical sleep sound data having an accompanying child sleep event:

[0128] Analyze and extract sound features of the historical sleep sound data currently being processed to obtain snoring sound features that characterize snoring behavior and environmental sound features that characterize non-snoring behavior;

[0129] If it is determined according to the environmental sound feature that the historical sleep sound data currently being processed contains an accompanying child sleep event, marking the historical sleep sound data currently being processed as historical sleep sound data containing an accompanying child sleep event;

[0130] If it is determined according to the ambient sound characteristics that the currently processed historical sleep sound data does not contain an accompanying child sleep event, then the next historical sleep sound data to be processed will continue to be processed until all the historical sleep sound data in the sleep sound data set are processed.

[0131] In a possible example, in determining the first pre-alert decibel according to the at least one historical sleep sound data, the determining unit 805 is specifically configured to:

[0132] If the at least one historical sleep sound data is single, a reference decibel mean of the snoring signal of the single historical sleep sound data in a target time period is statistically analyzed; and the first pre-warning decibel is determined according to the reference decibel mean, wherein the target time period is a time range in which an audio signal representing a child's voice in the environmental sound feature of the single historical sleep sound data is located, the duration of the child's voice is less than a preset duration, and a sound feature other than the child's voice is included between the time starting point of the single historical sleep sound data and the time starting point of the time range;

[0133] If there are at least two of the at least one historical sleep sound data, the following processing is performed for each of the at least two historical sleep sound data to obtain at least two reference decibel means: statistically analyzing the reference decibel mean of the snoring signal of the currently processed historical sleep sound data in the target time period; and, determining the target decibel mean based on the at least two reference decibel means; and, determining the first pre-warning decibel based on the target decibel mean.

[0134] In a possible example, after the first reminder operation is performed to interrupt the snoring behavior of the target user and the snoring sound volume continues to increase from the current decibel to the minimum decibel, the execution unit 804 is specifically configured to:

[0135] Continuing to collect the second sleep sound data of the target user;

[0136] Analyzing, according to the second sleep sound data that is continuously collected, that the decibel of the snoring sound of the target user is greater than or equal to the minimum decibel;

[0137] A second reminder operation is performed to further interrupt the snoring behavior of the target user, and the second reminder operation is an electrical stimulation reminder operation of outputting an electrical stimulation signal.

[0138] In a possible example, in terms of detecting that the target user's sleep event this time is an event of accompanying a child to sleep, the determining unit 805 is specifically configured to:

[0139] Acquire discrete information from a mobile terminal device, the discrete information including call records and target schedule information, the target schedule information being a schedule for the target user to accompany the child to sleep;

[0140] Determine, based on the discrete information, a prediction result that the target user is currently accompanying the child to sleep;

[0141] When the prediction result is that the target user is currently accompanying the child to sleep, it is determined that the target user's current sleep event is an event of accompanying the child to sleep.

[0142] In a possible example, in terms of detecting that the target user's sleep event this time is an event of accompanying a child to sleep, the determining unit 805 is specifically configured to:

[0143] Acquire historical sampled sound data before the target user is in a sleeping state;

[0144] According to the historical sampled sound data, it is analyzed that the target user's current sleep event is an event of accompanying the child to sleep.

[0145] It should be noted that all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0146] The electronic device provided in this embodiment is used to execute the above sleep state information processing method, and thus can achieve the same effect as the above implementation method.

[0147] In the case of an integrated unit, the electronic device may include a processing module, a storage module and a communication module. The processing module may be used to control and manage the actions of the electronic device, for example, it may be used to support the electronic device to execute the steps performed by the above-mentioned functional unit. The storage module may be used to support the electronic device to execute stored program codes and data, etc. The communication module may be used to support the communication between the electronic device and other devices.

[0148] Among them, the processing module can be a processor or a controller. It can implement or execute various exemplary logic boxes, modules and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module can be a memory. The communication module can specifically be a device that interacts with other electronic devices, such as a radio frequency circuit, a Bluetooth chip, a Wi-Fi chip, etc.

[0149] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0150] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes a control platform.

[0151] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0152] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0153] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0154] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0155] In addition, each functional unit in each embodiment of the present application 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. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0156] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0157] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, which may include: a flash drive, a read-only memory, a random access memory, a magnetic disk or an optical disk, etc.

[0158] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for processing sleep state information, characterized in that: Smart watches for target users include: The smart watch obtains a sleep sound data set of the target user, wherein the sleep sound data set includes a plurality of historical sleep sound data, and a single historical sleep sound data includes ambient sound data of the target user in a sleeping state and / or snoring sound data of the target user; determines at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to the snoring sound of the target user while accompanying the child to sleep; and determines a first pre-alert decibel according to the at least one historical sleep sound data; When the smart watch detects that the target user is in a sleeping state, the smart watch collects the first sleeping sound data of the target user in the current sleeping event; When the smartwatch detects that the target user's sleep event this time is an event of accompanying a child to sleep, the smartwatch obtains the first pre-stored pre-alert decibel, which is smaller than the lowest decibel that wakes up the child due to the snoring behavior of the target user; The smart watch analyzes the first sleep sound data collected and finds that the target user has snoring behavior, and the decibel of the snoring sound of the snoring behavior is greater than or equal to the first pre-warning decibel; The smartwatch executes a first reminder operation to interrupt the snoring behavior of the target user and the snoring sound volume continues to increase from the current decibel to the minimum decibel, and the first reminder operation is a vibration operation executed according to a preset vibration strategy; The determining the first pre-alert decibel according to the at least one historical sleep sound data comprises: If the smart watch determines that the at least one historical sleep sound data is a single one, the smart watch statistically analyzes the reference decibel average of the snoring signal of the single historical sleep sound data in the target time period; and determines the first pre-warning decibel according to the reference decibel average, wherein the target time period is the time range in which the audio signal representing the child's voice in the environmental sound feature of the single historical sleep sound data is located, the duration of the child's voice is less than the preset duration, and the time starting point of the single historical sleep sound data and the time starting point of the time range contain sound features other than the child's voice; If the smart watch determines that there are at least two historical sleep sound data, the following processing is performed on each of the at least two historical sleep sound data to obtain at least two reference decibel averages: statistically analyzing the reference decibel average of the snoring signal of the currently processed historical sleep sound data in the target time period; and determining the target decibel average based on the at least two reference decibel averages; and determining the first pre-warning decibel based on the target decibel average.

2. The method according to claim 1, characterized in that The determining of at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to the snoring sound of the target user while accompanying the child to sleep includes: The following processing is performed for each historical sleep sound data in the sleep sound data set to obtain the at least one historical sleep sound data having an accompanying child sleep event: Analyze and extract sound features of the historical sleep sound data currently being processed to obtain snoring sound features that characterize snoring behavior and environmental sound features that characterize non-snoring behavior; If it is determined according to the environmental sound feature that the historical sleep sound data currently being processed contains an accompanying child sleep event, marking the historical sleep sound data currently being processed as historical sleep sound data containing an accompanying child sleep event; If it is determined according to the ambient sound characteristics that the currently processed historical sleep sound data does not contain an accompanying child sleep event, then the next historical sleep sound data to be processed will continue to be processed until all the historical sleep sound data in the sleep sound data set are processed.

3. The method according to claim 1, characterized in that After the first reminder operation is performed to interrupt the snoring behavior of the target user and the snoring sound volume continues to increase from the current decibel to the minimum decibel, the method further includes: Continuing to collect the second sleep sound data of the target user; Analyzing, according to the second sleep sound data that is continuously collected, that the decibel of the snoring sound of the target user is greater than or equal to the minimum decibel; A second reminder operation is performed to further interrupt the snoring behavior of the target user, and the second reminder operation is an electrical stimulation reminder operation of outputting an electrical stimulation signal.

4. The method according to claim 1, characterized in that: The detecting that the target user's sleep event is an event of accompanying a child to sleep includes: Acquire discrete information from a mobile terminal device, the discrete information including call records and target schedule information, the target schedule information being a schedule for the target user to accompany the child to sleep; Determine, based on the discrete information, a prediction result that the target user is currently accompanying the child to sleep; When the prediction result is that the target user is currently accompanying the child to sleep, it is determined that the target user's current sleep event is an event of accompanying the child to sleep.

5. The method according to claim 1, characterized in that The detecting that the target user's sleep event is an event of accompanying a child to sleep includes: Acquire historical sampled sound data before the target user is in a sleeping state; According to the historical sampled sound data, it is analyzed that the target user's current sleep event is an event of accompanying the child to sleep.

6. A sleep state information processing device, characterized in that: The smart watch applied to the target user, the sleep state information processing device comprises: a collection unit, an acquisition unit, a determination unit, an analysis unit and an execution unit, wherein: The determination unit is used to obtain a sleep sound data set of the target user, wherein the sleep sound data set includes a plurality of historical sleep sound data, and a single historical sleep sound data includes ambient sound data of the target user in a sleeping state and / or snoring sound data of the target user; determine at least one historical sleep sound data in the sleep sound data set in which the target user wakes up the child due to his snoring sound when accompanying the child to sleep; determine a first pre-alert decibel according to the at least one historical sleep sound data; the determining the first pre-alert decibel according to the at least one historical sleep sound data includes: if the at least one historical sleep sound data is single, statistically analyzing a reference decibel mean of the snoring signal of the single historical sleep sound data in a target time period; and determining the first pre-alert decibel according to the reference decibel mean. The first pre-warning decibel is determined by the decibel mean of the snoring sound signals of the historical sleep sound data currently being processed in the target period of time, the target period of time is the time range in which the audio signal representing the child's voice in the environmental sound feature of the single historical sleep sound data is located, the duration of the child's voice is less than the preset duration, and the time starting point of the single historical sleep sound data and the time starting point of the time range contain sound features other than the child's voice; if the at least one historical sleep sound data is at least two, the following processing is performed for each of the at least two historical sleep sound data to obtain at least two reference decibel mean values: statistically analyzing the reference decibel mean value of the snoring signal of the historical sleep sound data currently being processed in the target period of time; and determining the target decibel mean value according to the at least two reference decibel mean values; and determining the first pre-warning decibel according to the target decibel mean value; The collecting unit is used to collect the first sleep sound data of the target user in the current sleep event when detecting that the target user is in a sleep state; The acquisition unit is further configured to acquire the first pre-alert decibel stored in advance when it is detected that the target user's current sleep event is an event of accompanying a child to sleep, wherein the first pre-alert decibel is smaller than the lowest decibel that causes the target user's snoring behavior to wake up the child; The analysis unit is used to analyze, based on the collected first sleep sound data, whether the target user has snoring behavior, and the decibel of the snoring sound of the snoring behavior is greater than or equal to the first pre-warning decibel; The execution unit is used to execute a first reminder operation to interrupt the snoring sound of the target user's snoring behavior and the trend of the snoring sound continuously increasing from the current decibel to the minimum decibel. The first reminder operation is a vibration operation executed according to a preset vibration strategy.

7. An electronic device, characterized in that: The method comprises a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in the method according to claims 1-5.

8. A computer-readable storage medium, characterized in that: A computer program for electronic data exchange is stored, wherein the computer program causes a computer to execute the method according to claims 1-5.

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