A sleep wake-up control method, device, computer device and system

Abstract

The application provides a sleep wake-up control method, device, computer equipment and system, the method comprises the following steps: obtaining sleep monitoring data of a user, calculating a sleep state of the user based on the sleep monitoring data; obtaining a wake-up mode corresponding to the sleep state, waking up the user based on a pre-stored alarm time and the wake-up mode; receiving voice data of the user after being woken up, calculating an emotional state of the user based on the voice data; updating the wake-up mode based on the emotional state. The method provided by the application can effectively identify the emotion and sleep cycle of the user, thereby gradually waking up the user, realizing the effect of not affecting the emotion of the user and guaranteeing the mental state of the user; further, the emotion of the user is identified based on the voice instruction of the user after being woken up, the wake-up mode is continuously corrected, and the use experience of the user is optimized.

Description

Technical Field

[0001] This application relates to the field of Internet of Things (IoT) technology, and in particular to a sleep wake-up control method, device, computer equipment, and system. Background Technology

[0002] Sleep is a common and natural state of rest. In modern life, with its fast pace and high work pressure, good rest and sleep are crucial for both health and career. The human sleep cycle generally consists of five stages: the sleep onset stage, light sleep, deep sleep, and REM sleep. If awakened gradually according to the sleep cycle, one's mental state and mood upon waking will be at a better level. However, being suddenly awakened from deep sleep can lead to a bad mood upon waking, even increased drowsiness, and morning grumpiness.

[0003] On the other hand, with the continuous development of sensors and information technology, traditional information transmission methods can no longer meet people's actual needs, and Internet of Things (IoT) systems with wireless, high-speed, secure, and convenient communication have emerged.

[0004] However, ordinary alarm clocks can only wake users up according to the preset time, which cannot match the actual sleep stage, and can easily cause users to have poor mood and mental state after being woken up. Summary of the Invention

[0005] To address the issue of poor user experience when waking up from sleep using existing alarm clocks, this application provides a sleep wake-up control method, device, computer equipment, and system that can improve the user experience during sleep wake-up.

[0006] On the one hand, a sleep-wake method is provided, the method comprising:

[0007] Acquire the user's sleep monitoring data and calculate the user's sleep state based on the sleep monitoring data;

[0008] Obtain the wake-up method corresponding to the sleep state, and wake up the user based on the pre-stored alarm time and the wake-up method;

[0009] Receive voice data after the user is woken up, and calculate the user's emotional state based on the voice data;

[0010] The arousal method is updated based on the emotional state.

[0011] In some embodiments, calculating the user's sleep state based on the sleep monitoring data includes:

[0012] A sleep feature vector is constructed based on the sleep monitoring data;

[0013] The sleep feature vector is assigned to a pre-trained sleep state long short-term memory network to calculate the sleep state.

[0014] In some embodiments, calculating the user's emotional state based on the voice data includes:

[0015] Construct a speech feature vector based on the speech data;

[0016] The speech feature vector is input into a pre-trained emotion support vector machine to calculate the emotion state.

[0017] In some embodiments, the sleep state includes deep sleep and light sleep, and the wake-up method corresponding to the sleep state includes:

[0018] If the sleep state is light sleep, the wake-up method includes waking up a first time period earlier than the alarm clock time, and the wake-up process uses a first type of linkage device;

[0019] If the sleep state is deep sleep, the wake-up method includes waking up a second time period earlier than the alarm clock time, and the wake-up process uses a second type of linkage device;

[0020] The second time period is longer than the first time period, and the types of the second type of linkage equipment are greater than or equal to the types of the first type of linkage equipment.

[0021] In some embodiments, the emotional state includes a positive state and a negative state, and updating the arousal mode based on the emotional state includes:

[0022] When the emotional state is negative, the first time period and / or the second time period shall be extended.

[0023] If the emotional state is positive, then the first time period and / or the second time period shall be shortened.

[0024] In some embodiments, the sleep wake-up control method further includes:

[0025] The system provides sleep reminders to the user based on their sleep state and emotional state.

[0026] On the other hand, a sleep wake-up control device is provided, the device comprising:

[0027] The sleep state acquisition module is used to acquire the user's sleep monitoring data and calculate the user's sleep state based on the sleep monitoring data;

[0028] The wake-up module is used to obtain the wake-up method corresponding to the sleep state and wake up the user based on the pre-stored alarm time and the wake-up method;

[0029] The emotional state acquisition module is used to receive the user's voice data after the user is awakened, and calculate the user's emotional state based on the voice data.

[0030] The wake-up method update module is used to update the wake-up method based on the emotional state.

[0031] In some embodiments, the sleep state acquisition module is specifically used for:

[0032] A sleep feature vector is constructed based on the sleep monitoring data;

[0033] The sleep feature vector is assigned to a pre-trained sleep state long short-term memory network to calculate the sleep state.

[0034] In some embodiments, the emotion state acquisition module is specifically used for:

[0035] Construct a speech feature vector based on the speech data;

[0036] The speech feature vector is input into a pre-trained emotion support vector machine to calculate the emotion state.

[0037] In some embodiments, the sleep state includes deep sleep and light sleep, and the wake-up method corresponding to the sleep state includes:

[0038] If the sleep state is light sleep, the wake-up method includes waking up a first time period earlier than the alarm clock time, and the wake-up process uses a first type of linkage device;

[0039] If the sleep state is deep sleep, the wake-up method includes waking up a second time period earlier than the alarm clock time, and the wake-up process uses a second type of linkage device;

[0040] The second time period is longer than the first time period, and the types of the second type of linkage equipment are greater than or equal to the types of the first type of linkage equipment.

[0041] In some embodiments, the emotional state includes a positive state and a negative state, and the arousal mode update module is specifically used for:

[0042] When the emotional state is negative, the first time period and / or the second time period shall be extended.

[0043] If the emotional state is positive, then the first time period and / or the second time period shall be shortened.

[0044] In some embodiments, the sleep wake-up control device further includes a sleep reminder module for reminding the user to fall asleep based on the sleep state and the emotional state.

[0045] On the other hand, a computer device is provided, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The processor can load and execute at least one instruction, at least one program, code set, or instruction set to implement the sleep-wake control method provided in the above-mentioned embodiments.

[0046] On the other hand, a sleep wake-up control system is provided, including an alarm clock, a linkage device, and the aforementioned computer device;

[0047] The linked devices include at least one of the following: smart bed, smart lamps, smart curtains, air conditioner, and humidifier.

[0048] On the other hand, a computer-readable storage medium is provided, which stores at least one instruction, at least one program, code set, or instruction set. A processor can load and execute at least one instruction, at least one program, code set, or instruction set to implement the sleep-wake control method provided in the embodiments of this application.

[0049] On the other hand, a computer program product or computer program is provided, the computer program product or computer program including computer program instructions stored in a computer-readable storage medium. A processor reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform any of the sleep-wake control methods described in the above embodiments.

[0050] The beneficial effects of the technical solution provided in this application include at least the following: Embodiments of the present invention provide a sleep wake-up control method, device, computer equipment, and system. The method includes acquiring a user's sleep monitoring data and calculating the user's sleep state based on the sleep monitoring data; acquiring a wake-up method corresponding to the sleep state and waking the user based on a pre-stored alarm time and the wake-up method; receiving voice data after the user is woken up and calculating the user's emotional state based on the voice data; and updating the wake-up method based on the emotional state. The method provided by embodiments of the present invention can effectively identify the user's emotions and sleep cycle, thereby gradually waking the user without affecting the user's emotions and ensuring the user's mental state. Furthermore, after the user is woken up, the wake-up method is continuously corrected based on the user's voice commands to optimize the user experience. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A schematic diagram illustrating the implementation flow of a sleep wake-up control method provided in an exemplary embodiment of this application is shown.

[0053] Figure 2 This illustration shows another implementation flow diagram of a sleep wake-up control method provided in an exemplary embodiment of this application;

[0054] Figure 3 This invention provides a structural diagram of a sleep wake-up control device according to an exemplary embodiment of the present application.

[0055] Figure 4 The diagram shows a schematic representation of a computer device corresponding to a sleep-wake control method provided in an exemplary embodiment of this application. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0057] The sleep wake-up control method provided in this application can improve the user experience during sleep wake-up.

[0058] Example 1

[0059] Figure 1 The diagram illustrates the implementation flow of a sleep-wake control method provided in an embodiment of the present invention.

[0060] See Figure 1 The sleep wake-up control method provided in this embodiment of the invention may include steps 101 to 104.

[0061] Step 101: Obtain the user's sleep monitoring data and calculate the user's sleep state based on the sleep monitoring data.

[0062] In some embodiments, prior to step 101, the sleep wake-up control method further includes determining whether the user is in bed.

[0063] Specifically, using smart beds or other pressure sensors, the system detects whether there is pressure on the bed and determines whether the user is in bed.

[0064] Optionally, multiple small pressure sensors can be installed throughout the bed to detect whether the pressure area is in the shape of a human body, thus more accurately determining whether the user is on the bed and avoiding misjudgments caused by placing heavy objects.

[0065] Optionally, the entire bed can be tested in three parts: upper, middle, and lower. If pressure is detected in all three parts, the user is considered to be in bed.

[0066] Furthermore, users can set up smart home linkage control in the IoT system after lying in bed, automatically turning off lights, closing curtains, and performing other operations.

[0067] In some embodiments, step 101 includes: the user's sleep monitoring data includes various physiological signals, such as the user's electrocardiogram, heart rate, respiratory rate, body temperature, exercise status and other information during sleep.

[0068] Specifically, an electrocardiogram (ECG) monitoring module is used to acquire the user's ECG and heart rate, a respiratory monitoring module is used to acquire the user's respiratory rate, and an infrared body temperature sensor is used to acquire the user's body temperature data. Additionally, a pressure sensor can be used to collect pressure changes and record the number of times the user turns over.

[0069] In some embodiments, step 101 includes preprocessing the sleep monitoring data. Optionally, the physiological signals are preprocessed using a signal amplification module and a noise reduction module.

[0070] In some embodiments, step 101 includes constructing a sleep feature vector based on the sleep monitoring data;

[0071] The sleep feature vector is assigned to a pre-trained Long-short-term memory (LSTM) network for sleep state calculation to obtain the sleep state.

[0072] Specifically, feature vectors are constructed based on preprocessed physiological signals, and these feature vectors are then input into a pre-trained Long Short-Term Memory (LSTM) network according to time sequence. The physiological signal saliency waveforms of different sleep cycles are then identified based on the AASM sleep standard.

[0073] Long Short-Term Memory (LSTM) networks are a type of recurrent neural network that can effectively solve the problems of vanishing and exploding gradients that are prone to occur in long sequence training, such as sleep duration.

[0074] Optionally, a long short-term memory network can be trained using a pre-stored public sleep dataset.

[0075] In a specific example, a user's sleep state can be divided into three levels: awake, light sleep, and deep sleep. To further improve the accuracy of sleep state recognition, more than three levels can also be set.

[0076] In some embodiments, physiological signals are uploaded to a cloud server for data processing.

[0077] Step 102: Obtain the wake-up method corresponding to the sleep state, and wake up the user based on the pre-stored alarm time and the wake-up method.

[0078] In some embodiments, the sleep state includes deep sleep and light sleep, and the wake-up method corresponding to the sleep state includes:

[0079] If the sleep state is light sleep, the wake-up method includes waking up a first time period earlier than the alarm clock time, and the wake-up process uses a first type of linkage device;

[0080] If the sleep state is deep sleep, the wake-up method includes waking up a second time period earlier than the alarm clock time, and the wake-up process uses a second type of linkage device;

[0081] The second time period is longer than the first time period, and the types of the second type of linkage equipment are greater than or equal to the types of the first type of linkage equipment.

[0082] Specifically, it continuously acquires sleep cycles during a preset period before the alarm time and wakes the user up before the alarm time based on the sleep cycle.

[0083] For example, if a user sets an alarm for 8:00 AM, the alarm will start waking the user at 7:45 AM and continue until the user turns off the alarm.

[0084] Optionally, if the user is in a light sleep state, they can be woken up at 7:50 AM by playing music at a gradually increasing volume and slowly raising the upper part of the bed to reduce the difficulty of getting out of bed after being woken up.

[0085] If the user is in deep sleep, wake them up at 7:40, open the curtains, play music at a low volume to wake them from deep sleep to light sleep, increase the volume, and activate smart bed and other devices to slowly raise the upper part of the bed to reduce the discomfort of being woken up from deep sleep.

[0086] Step 103: Receive the user's voice data after being woken up, and calculate the user's emotional state based on the voice data.

[0087] Optionally, users can turn off the alarm clock via voice command; the voice data is the user's voice command to turn off the alarm clock.

[0088] In some embodiments, step 103 includes:

[0089] Construct a speech feature vector based on the speech data;

[0090] The speech feature vector is input into a pre-trained emotion support vector machine to calculate the emotion state.

[0091] Specifically, the voice data is input into a pre-trained emotion support vector machine (SVM) classifier for recognition in order to classify the user's state after being awakened.

[0092] Optionally, the CASIA Chinese speech emotion dataset is used to extract Mel-frequency cepstral coefficient features from each speech data point and input into a support vector machine for training. Optionally, the trained classifier can recognize six emotions, including anger, happiness, fear, sadness, surprise, and neutrality.

[0093] Furthermore, the emotion support vector machine classifier is updated based on the user's voice commands, further improving the accuracy of user state recognition. SVM belongs to machine learning rather than complex neural networks; by collecting real user data, it can achieve optimal results using a simple network.

[0094] Step 104: Update the arousal method based on the emotional state.

[0095] In some embodiments, step 104 includes:

[0096] When the emotional state is negative, the first time period and / or the second time period shall be extended.

[0097] If the emotional state is positive, then the first time period and / or the second time period shall be shortened.

[0098] In a specific example, if the system detects that the user is angry after waking up, the wake-up time will be moved forward, reducing the intensity of the wake-up-related home appliances. For instance, if a user sets an alarm for 8:00 AM to wake up at 7:45 AM, and the user is angry after waking up, the wake-up time will be moved forward to 7:30 AM, and more soothing music will be played, etc.

[0099] In one specific example, if a user is in a good mood after being woken up, the number of devices that need to be activated during wake-up can be reduced, thus delaying the wake-up time and achieving energy-saving effects.

[0100] In some embodiments, the method provided by the present invention may further include:

[0101] The system provides sleep reminders to the user based on their sleep state and emotional state.

[0102] The system provides sleep reminders based on the user's actual sleep patterns. For example, it can synchronize lighting with the alarm clock eight hours in advance and remind the user to fall asleep.

[0103] In a specific example, if a user is in a bad mood after being woken up, a sleep reminder can be given in advance to encourage the user to arrange sufficient sleep time.

[0104] The method provided in this invention can effectively identify a user's emotions and sleep cycles, thereby gradually waking the user without affecting their emotions and ensuring their mental state. Furthermore, after the user is awakened, the method continuously modifies the wake-up method based on the user's voice commands to optimize the user experience.

[0105] Example 2

[0106] Figure 2 This diagram illustrates another implementation flow of the sleep-wake control method provided in an embodiment of the present invention.

[0107] See Figure 2 In a specific example, the method implementation process provided by the embodiment of the present invention is as follows.

[0108] First, determine whether the user is in bed. If the user is in bed, collect the user's physiological signals to identify the sleep cycle.

[0109] The system gradually wakes the user based on their set alarm and current sleep cycle.

[0110] It receives the user's voice command to turn off the alarm, performs emotion recognition on the voice command, and adjusts the wake-up method according to the emotion recognition result.

[0111] Example 3

[0112] Figure 3 A schematic diagram of the sleep-wake control device provided in an embodiment of the present invention is shown.

[0113] See Figure 3 The sleep-wake control device provided in this embodiment of the invention may include:

[0114] The sleep state acquisition module 201 is used to acquire the user's sleep monitoring data and calculate the user's sleep state based on the sleep monitoring data.

[0115] The wake-up module 202 is used to obtain the wake-up method corresponding to the sleep state and wake up the user based on the pre-stored alarm time and the wake-up method;

[0116] The emotion state acquisition module 203 is used to receive the user's voice data after the user is awakened, and calculate the user's emotion state based on the voice data.

[0117] The wake-up method update module 204 is used to update the wake-up method based on the emotional state.

[0118] In some embodiments, the sleep state acquisition module 201 is specifically used for:

[0119] A sleep feature vector is constructed based on the sleep monitoring data;

[0120] The sleep feature vector is assigned to a pre-trained sleep state long short-term memory network to calculate the sleep state.

[0121] In some embodiments, the emotion state acquisition module 203 is specifically used for:

[0122] Construct a speech feature vector based on the speech data;

[0123] The speech feature vector is input into a pre-trained emotion support vector machine to calculate the emotion state.

[0124] In some embodiments, the sleep state includes deep sleep and light sleep, and the wake-up method corresponding to the sleep state includes:

[0125] If the sleep state is light sleep, the wake-up method includes waking up a first time period earlier than the alarm clock time, and the wake-up process uses a first type of linkage device;

[0126] If the sleep state is deep sleep, the wake-up method includes waking up a second time period earlier than the alarm clock time, and the wake-up process uses a second type of linkage device;

[0127] The second time period is longer than the first time period, and the types of the second type of linkage equipment are greater than or equal to the types of the first type of linkage equipment.

[0128] In some embodiments, the emotional state includes a positive state and a negative state, and the arousal mode update module 204 is specifically used for:

[0129] When the emotional state is negative, the first time period and / or the second time period shall be extended.

[0130] If the emotional state is positive, then the first time period and / or the second time period shall be shortened.

[0131] In some embodiments, the sleep wake-up control device further includes a sleep reminder module for reminding the user to fall asleep based on the sleep state and the emotional state.

[0132] In summary, the device provided in this embodiment of the invention can effectively identify the user's emotions and sleep cycle, thereby gradually waking the user without affecting the user's emotions and ensuring the user's mental state. Furthermore, after the user is awakened, the device can continuously correct the wake-up method based on the user's voice commands to optimize the user experience.

[0133] Example 4

[0134] Figure 4 This application shows a schematic diagram of the structure of a computer device provided in an exemplary embodiment, the computer device comprising:

[0135] The processor 301 includes one or more processing cores. The processor 301 executes various functional applications and data processing by running software programs and modules.

[0136] The receiver 302 and transmitter 303 can be implemented as a communication component, which can be a communication chip. Optionally, this communication component can include signal transmission functionality. That is, the transmitter 303 can be used to transmit control signals to the image acquisition device and the scanning device, and the receiver 302 can be used to receive corresponding feedback commands.

[0137] The memory 304 is connected to the processor 301 via the bus 305.

[0138] The memory 304 can be used to store at least one instruction, and the processor 301 is used to execute the at least one instruction to implement steps 101 to 102 in the above-described sleep-wake control method embodiment.

[0139] Those skilled in the art will understand that Figure 4 This is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than shown, or combine certain components, or different components. For example, the computer device may also include network access devices, etc.

[0140] The processor 301 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0141] The memory 304 can be an internal storage unit of the computer device, such as a hard drive or RAM. The memory 304 can also be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 304 can include both internal and external storage units. The memory 304 is used to store the computer program and other programs and data required by the terminal device. The memory 304 can also be used to temporarily store data that has been output or will be output.

[0142] Example 5

[0143] This application embodiment also provides a sleep wake-up control system, including an alarm clock, linkage devices, and the aforementioned computer equipment;

[0144] The linked devices include at least one of the following: smart bed, smart lamps, smart curtains, air conditioner, and humidifier.

[0145] Example 6

[0146] This application also provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, which can be loaded and executed by a processor to implement the above-described sleep-wake control method.

[0147] Optionally, the computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), solid-state drives (SSDs), or optical discs, etc. The random access memory may include resistive random access memory (ReRAM) and dynamic random access memory (DRAM).

[0148] Example 7

[0149] This application also provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform any of the sleep-wake control methods described in the above embodiments.

[0150] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the implementation.

[0151] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0152] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0153] 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 implementations should not be considered beyond the scope of this invention.

[0154] The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0155] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A sleep wake-up control method, characterized in that, The method includes: Acquire the user's sleep monitoring data and calculate the user's sleep state based on the sleep monitoring data; Obtain the wake-up method corresponding to the sleep state, and wake up the user based on the pre-stored alarm time and the wake-up method; Receive voice data after the user is woken up, and calculate the user's emotional state based on the voice data; The arousal method is updated based on the emotional state. The sleep state includes deep sleep and light sleep, and the wake-up methods corresponding to the sleep state include: If the sleep state is light sleep, the wake-up method includes waking up a first time period earlier than the alarm clock time, and the wake-up process uses a first type of linkage device; If the sleep state is deep sleep, the wake-up method includes waking up a second time period earlier than the alarm clock time, and the wake-up process uses a second type of linkage device; The second time period is longer than the first time period, and the types of the second type of linkage equipment are greater than or equal to the types of the first type of linkage equipment; The emotional state includes positive and negative states, and updating the arousal mode based on the emotional state includes: When the emotional state is negative, the first time period and / or the second time period shall be extended. If the emotional state is positive, then the first time period and / or the second time period shall be shortened.

2. The method according to claim 1, characterized in that, The calculation of the user's sleep state based on the sleep monitoring data includes: A sleep feature vector is constructed based on the sleep monitoring data; The sleep feature vector is assigned to a pre-trained sleep state long short-term memory network to calculate the sleep state.

3. The method according to claim 1, characterized in that, The calculation of the user's emotional state based on the voice data includes: Construct a speech feature vector based on the speech data; The speech feature vector is input into a pre-trained emotion support vector machine to calculate the emotion state.

4. The method according to any one of claims 1 to 3, characterized in that, The sleep wake-up control method further includes: The system provides sleep reminders to the user based on their sleep state and emotional state.

5. A sleep wake-up control device, characterized in that, The device includes: The sleep state acquisition module is used to acquire the user's sleep monitoring data and calculate the user's sleep state based on the sleep monitoring data; The wake-up module is used to obtain the wake-up method corresponding to the sleep state and wake up the user based on the pre-stored alarm time and the wake-up method; The emotional state acquisition module is used to receive the user's voice data after the user is awakened, and calculate the user's emotional state based on the voice data. A wake-up method update module is used to update the wake-up method based on the emotional state; The sleep state includes deep sleep and light sleep, and the wake-up methods corresponding to the sleep state include: If the sleep state is light sleep, the wake-up method includes waking up a first time period earlier than the alarm clock time, and the wake-up process uses a first type of linkage device; If the sleep state is deep sleep, the wake-up method includes waking up a second time period earlier than the alarm clock time, and the wake-up process uses a second type of linkage device; The second time period is longer than the first time period, and the types of the second type of linkage equipment are greater than or equal to the types of the first type of linkage equipment; The emotional state includes positive and negative states, and the arousal method update module is specifically used for: When the emotional state is negative, the first time period and / or the second time period shall be extended. If the emotional state is positive, then the first time period and / or the second time period shall be shortened.

6. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one instruction, at least one program, code set, or instruction set, the at least one instruction, at least one program, code set, or instruction set being loaded and executed by the processor to implement the sleep-wake control method as described in any one of claims 1 to 4.

7. A sleep wake-up control system, characterized in that, Includes alarm clocks, linked devices, and the computer equipment as described in claim 6; The linked devices include at least one of the following: smart bed, smart lamps, smart curtains, air conditioner, and humidifier.

8. A computer-readable storage medium, characterized in that, The readable storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the sleep-wake control method as described in any one of claims 1 to 4.

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