A smart companion robot with sleep monitoring and sleep-aid guidance functions

Abstract

The present invention provides an intelligent accompanying robot with sleep monitoring and sleep-aiding guidance functions, including: an intelligent monitoring module for collecting the user's sleep-related data in real time and uploading it to the cloud; a cloud processing module for analyzing the user's sleep-related data, determining the user's sleep state and combining the user's personal sleep rhythm to determine whether the user's current sleep quality is good; a function matching module for matching the best sleep-aiding means for the user based on the user's actual sleep situation combined with synchronized environmental data after receiving a sleep-aiding request; a sleep-aiding control module for determining the target-related device and its corresponding sleep-aiding measures according to the best sleep-aiding means to generate control instructions, and controlling the target-related device to complete the corresponding sleep-aiding measures. The present invention evaluates the user's current sleep quality based on the user's current sleep situation combined with the user's personal sleep rhythm, and automatically completes the sleep-aiding guidance when the user does not sleep well to help the user quickly enter a good sleep state.

Description

Technical Field

[0001] The present invention relates to the technical field of sleep assistance control, and in particular to an intelligent accompanying robot with sleep monitoring and sleep assistance guiding functions. Background Art

[0002] Sleep is a spontaneous and reversible resting state that occurs periodically in higher vertebrates, characterized by a decrease in the body's responsiveness to external stimuli and a temporary interruption of consciousness. About one-third of a person's life is spent in sleep. When people are in a state of sleep, their brains and bodies can rest, recuperate and recover. A proper amount of sleep helps people's daily work and study. Scientifically improving sleep quality is the guarantee for people's normal work, study and life.

[0003] With the accelerated pace of life, many people suffer from insomnia. Night is the physiological rest time of the human body. Failure to rest will lead to dark circles, eye bags, and dry skin. When sleep is severely lacking, people will often feel dizzy, unable to concentrate, and even have headaches when working or in class. The existing sleep aid method is to monitor the user's sleep data at night, and then determine whether the user needs sleep aid based on the sleep data and then play sleep-aid music to induce the user to quickly fall asleep. However, this method is not combined with the user's personal sleep habits. For example, after going to bed, the user does not rest immediately but reads or handles some work content, which may easily lead to misjudgment of poor sleep. Therefore, the present invention proposes an intelligent accompanying robot with sleep monitoring and sleep-aid guidance functions. Summary of the invention

[0004] The present invention provides an intelligent companion robot with sleep monitoring and sleep-aiding guidance functions to solve the above problems. The present invention evaluates the user's current sleep quality based on the user's current sleep condition and the user's personal sleep rhythm, which is conducive to improving the accuracy of sleep quality evaluation, and automatically completes sleep-aiding guidance when the user does not sleep well, providing the user with a comfortable sleeping environment and helping the user quickly enter a good sleep state.

[0005] The present invention provides an intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions, comprising:

[0006] Intelligent monitoring module, used to collect users' sleep-related data in real time and upload it to the cloud;

[0007] The cloud processing module is used to analyze the user's sleep-related data, determine the user's sleep state, and combine the user's personal sleep rhythm to determine whether the user's current sleep quality is good. If not, a sleep-aiding request is sent to the sleep-aiding control module;

[0008] The function matching module is used to match the best sleep aid method for the user based on the user's actual sleep situation and the synchronized environment data after receiving the sleep aid request;

[0009] The sleep-aiding control module is used to determine the target-related device and its corresponding sleep-aiding measure according to the best sleep-aiding means, generate a control instruction, and control the target-related device to complete the corresponding sleep-aiding measure through the control instruction.

[0010] Preferably, in an intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions, the cloud processing module includes:

[0011] A sleep data processing unit, used to analyze sleep-related data, obtain user breathing data and heart rate data, compare the user's breathing data and heart rate data with standard breathing data and standard heart rate data, and determine the user's current sleep depth based on the comparison results;

[0012] A sleep quality assessment unit, used to determine whether the user's current sleep quality is good based on the current sleep depth and with reference to the user's personal sleep rhythm;

[0013] The sleep guidance trigger unit is used to generate a sleep assistance request and send it to the sleep assistance control module when determining that the user's current sleep quality is poor.

[0014] Preferably, in an intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions, the cloud processing module further includes:

[0015] A personalized adaptive unit is used to obtain historical sleep data corresponding to multiple sleep cycles of the user, and respectively determine the sleep start time point and sleep end time point corresponding to multiple sleep microcycles in each sleep macrocycle;

[0016] Perform synchronous alignment processing on the sleep micro-cycles corresponding to the multiple sleep macro-cycles, and compare the sleep start time points and the sleep end time points of the sleep micro-cycles according to the alignment results to obtain time comparison results;

[0017] Based on the time comparison result, determine the cycle start and end range corresponding to the same sleep micro-cycle, intercept the data of each sleep micro-cycle based on the cycle start and end range distribution, and obtain the effective sleep data of the cycle;

[0018] Generate a breathing change curve and a heart rate change curve of the user based on the effective sleep data of the cycle, determine the sleep state change corresponding to the sleep micro-cycle based on the breathing change curve and the heart rate change curve, and generate a sleep state change graph;

[0019] The initial and end ranges of all sleep microcycles are compared to obtain cycle similarity. Based on the cycle similarity, the sleep microcycles are clustered to obtain several microcycle sets.

[0020] Compare the sleep state change graphs corresponding to all sleep micro-cycles in the same micro-cycle set, determine the change node interval corresponding to each sleep state change node, and determine the standard sleep state change node corresponding to each sleep state change node of each sleep micro-cycle according to the change node interval and the user's sleep fluctuation.

[0021] Based on the standard sleep state change nodes, the personal sleep rhythm of the user in the sleep cycle is generated.

[0022] Preferably, in an intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions, the sleep guidance triggering unit includes:

[0023] A type determination subunit, used to determine the type of poor sleep of the user according to the sleep micro-cycle corresponding to the current date;

[0024] A request generating subunit, for generating a request for enhanced sleep assistance if the current sleep condition is of the first poor type;

[0025] If the current sleep condition is of the second poor type, a regular sleep assistance request is generated;

[0026] The request generating subunit is used to send an enhanced sleep-aiding request or a conventional sleep-aiding request to the sleep-aiding control module.

[0027] Preferably, in an intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions, the function matching module includes:

[0028] A synchronous data acquisition unit, for acquiring environmental monitoring data corresponding to the associated equipment of the accompanying robot after receiving a sleep-aiding request, to obtain synchronous environmental data;

[0029] An environmental data processing unit, used to compare the synchronized environmental data with the corresponding preset comfort value, determine whether there is an environmental parameter that needs to be adjusted, and if so, use the environmental parameter as a parameter to be adjusted, and determine a basic sleep aid based on the parameter to be adjusted;

[0030] A music level determination unit, used to determine a target level corresponding to the sleep-aiding music based on the user's current sleep quality;

[0031] The sleep aid means determination unit is used to generate the best sleep aid means corresponding to the user's current sleep quality based on the target levels corresponding to the basic sleep aid means and the sleep aid music required.

[0032] Preferably, in an intelligent accompanying robot with sleep monitoring and sleep aid guidance functions, the function matching module further includes:

[0033] a request parsing processing unit, configured to parse the received sleep-aiding request, determine the type of the sleep-aiding request, and when the sleep-aiding request is a request for enhanced sleep-aiding, automatically increase the target level corresponding to the sleep-aiding music required determined by the sleep-aiding level determining unit by one;

[0034] When the sleep-aiding request is a regular sleep-aiding request, the target level corresponding to the sleep-aiding music determined by the sleep-aiding level determining unit will be maintained.

[0035] Preferably, in an intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions, the music level determination unit includes:

[0036] A state difference determination subunit, used to obtain a state time difference between a user's current sleep state and a target sleep state;

[0037] An error evaluation subunit, used for obtaining a sleep instruction evaluation coefficient based on a state time difference and a user state transition cycle;

[0038] a music level determination subunit, configured to determine that the target level of the music for the current sleep-aiding requirement is primary when the sleep instruction evaluation coefficient is in the first interval;

[0039] When the sleep instruction evaluation coefficient is in the second interval, it is determined that the target level of the current sleep-aiding music is intermediate;

[0040] When the sleep instruction evaluation coefficient is in the third interval, it is determined that the target level for the current sleep-aiding music is high.

[0041] Preferably, in an intelligent accompanying robot with sleep monitoring and sleep aid guidance functions, the sleep aid control module includes:

[0042] A target determination unit, used to determine the target-related device that needs to be regulated and its corresponding sleep-aiding measure according to the best sleep-aiding means;

[0043] A control instruction generating unit, used for generating corresponding control instructions based on the sleep-aiding measures;

[0044] A sending control unit, used to send a control instruction to a corresponding target-related device, and control the target-related device to complete a corresponding sleep-aiding measure;

[0045] Before the sleep-aiding music is played, the music list of corresponding levels in the music database is screened according to the user's listening preferences, a list to be played is obtained, and random playback is performed based on the list to be played.

[0046] Compared with the prior art, the present invention has at least the following beneficial effects:

[0047] The present invention collects the user's sleep-related data in real time through the intelligent monitoring module and uploads it to the cloud, so as to realize real-time monitoring of the user's sleep. Then, the cloud processing template analyzes the uploaded data to evaluate the user's current sleep quality. When the user's current sleep quality is not good, a sleep-aiding request is generated. The function matching module matches the best sleep-aiding means for the user based on the user's actual sleep condition in combination with the synchronized environmental data. Finally, the sleep-aiding control module determines the target-associated device and its corresponding sleep-aiding measures according to the best sleep-aiding means, generates a control instruction, and controls the target-associated device to complete the corresponding sleep-aiding measures through the control instruction, so as to realize sleep-aiding guidance for the user. The present invention evaluates the user's current sleep quality according to the user's current sleep condition in combination with the user's personal sleep rhythm, which is conducive to improving the accuracy of sleep quality evaluation. When the user sleeps poorly, the sleep-aiding guidance is automatically completed, so as to provide the user with a comfortable sleeping environment and help the user quickly enter a good sleep state.

[0048] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0049] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0051] Figure 1 This is a structural diagram of an intelligent accompanying robot with sleep monitoring and sleep-aiding guidance functions according to the present invention;

[0052] Figure 2 This is a structural diagram of a cloud processing module of an intelligent accompanying robot with sleep monitoring and sleep-aiding guidance functions according to the present invention;

[0053] Figure 3 This is a structural diagram of a function matching module of an intelligent accompanying robot with sleep monitoring and sleep-aiding guidance functions according to the present invention;

[0054] Figure 4 This is a structural diagram of a sleep-aiding control module of an intelligent accompanying robot with sleep monitoring and sleep-aiding guidance functions according to the present invention. DETAILED DESCRIPTION

[0055] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0056] Embodiment 1:

[0057] The present invention provides an intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions, such as Figure 1 As shown, including:

[0058] Intelligent monitoring module, used to collect users' sleep-related data in real time and upload it to the cloud;

[0059] The cloud processing module is used to analyze the user's sleep-related data, determine the user's sleep state, and combine the user's personal sleep rhythm to determine whether the user's current sleep quality is good. If not, a sleep-aiding request is sent to the sleep-aiding control module;

[0060] The function matching module is used to match the best sleep aid method for the user based on the user's actual sleep situation and the synchronized environment data after receiving the sleep aid request;

[0061] The sleep-aiding control module is used to determine the target-related device and its corresponding sleep-aiding measure according to the best sleep-aiding means, generate a control instruction, and control the target-related device to complete the corresponding sleep-aiding measure through the control instruction.

[0062] In this embodiment, the sleep-related data includes user breathing data and user heart rate data.

[0063] In this embodiment, the sleep-aiding means include but are not limited to playing soothing music, adjusting indoor lighting, and providing comfortable temperature and humidity.

[0064] The beneficial effects of the above technical solution are as follows: the present invention collects the user's sleep-related data in real time through the intelligent monitoring module and uploads it to the cloud, so as to realize real-time monitoring of the user's sleep. Then, the cloud processing template analyzes the uploaded data to evaluate the user's current sleep quality. When the user's current sleep quality is not good, a sleep-aiding request is generated. The function matching module matches the best sleep-aiding means for the user based on the user's actual sleep condition and the synchronized environmental data. Finally, the sleep-aiding control module determines the target-associated device and its corresponding sleep-aiding measures according to the best sleep-aiding means, generates a control instruction, and controls the target-associated device to complete the corresponding sleep-aiding measures through the control instruction, so as to realize sleep-aiding guidance for the user. The present invention evaluates the user's current sleep quality according to the user's current sleep condition and the user's personal sleep rhythm, which is conducive to improving the accuracy of sleep quality evaluation. When the user sleeps poorly, the sleep-aiding guidance is automatically completed to provide the user with a comfortable sleeping environment and help the user quickly enter a good sleep state.

[0065] Embodiment 2:

[0066] Based on Example 1, the cloud processing module, such as Figure 2 As shown, including:

[0067] A sleep data processing unit, used to analyze sleep-related data, obtain user breathing data and heart rate data, compare the user's breathing data and heart rate data with standard breathing data and standard heart rate data, and determine the user's current sleep depth based on the comparison results;

[0068] A sleep quality assessment unit, used to determine whether the user's current sleep quality is good based on the current sleep depth and with reference to the user's personal sleep rhythm;

[0069] The sleep guidance trigger unit is used to generate a sleep assistance request and send it to the sleep assistance control module when determining that the user's current sleep quality is poor.

[0070] The beneficial effects of the above technical solution are as follows: the present invention determines the current sleep depth of the user through the sleep-related data through the sleep data processing unit, and then judges whether the current sleep quality of the user is good through the sleep instruction evaluation unit, and when it is determined that the current sleep quality of the user is not good, the sleep guidance trigger unit generates a sleep aid request and sends it to the sleep aid control module, thereby providing the user with a more comfortable sleeping environment.

[0071] Embodiment 3:

[0072] Based on Example 2, the cloud processing module, such as Figure 2 As shown, it also includes:

[0073] A personalized adaptive unit is used to obtain historical sleep data corresponding to multiple sleep cycles of the user, and respectively determine the sleep start time point and sleep end time point corresponding to multiple sleep microcycles in each sleep macrocycle;

[0074] Perform synchronous alignment processing on the sleep micro-cycles corresponding to the multiple sleep macro-cycles, and compare the sleep start time points and the sleep end time points of the sleep micro-cycles according to the alignment results to obtain time comparison results;

[0075] Based on the time comparison result, determine the cycle start and end range corresponding to the same sleep micro-cycle, intercept the data of each sleep micro-cycle based on the cycle start and end range distribution, and obtain the effective sleep data of the cycle;

[0076] Generate a breathing change curve and a heart rate change curve of the user based on the effective sleep data of the cycle, determine the sleep state change corresponding to the sleep micro-cycle based on the breathing change curve and the heart rate change curve, and generate a sleep state change graph;

[0077] The initial and end ranges of all sleep microcycles are compared to obtain cycle similarity. Based on the cycle similarity, the sleep microcycles are clustered to obtain several microcycle sets.

[0078] Compare the sleep state change graphs corresponding to all sleep micro-cycles in the same micro-cycle set, determine the change node interval corresponding to each sleep state change node, and determine the standard sleep state change node corresponding to each sleep state change node of each sleep micro-cycle according to the change node interval and the user's sleep fluctuation.

[0079] Based on the standard sleep state change nodes, the personal sleep rhythm of the user in the sleep cycle is generated.

[0080] In this embodiment, the default sleep cycle is seven days and the default sleep cycle is 24 hours.

[0081] In this embodiment, the time comparison result includes a start time point comparison result and an end time point comparison result.

[0082] In this embodiment, the cycle initial range refers to the interval range of the sleep start time of a certain sleep cycle; the cycle end range refers to the interval range of the sleep end time of a certain sleep cycle.

[0083] In this embodiment, the effective sleep data of the cycle refers to the sleep small cycle data except the sleep data corresponding to the initial and end ranges of the cycle.

[0084] In this embodiment, the change node interval refers to the time interval where a sleep state change node is located in the user's historical sleep data.

[0085] In this embodiment, the standard sleep state change node refers to a standard time point at which the user's sleep state changes.

[0086] In this embodiment, the synchronous alignment process refers to aligning the same sleep micro-cycles in each sleep macro-cycle, that is, aligning a plurality of sleep micro-cycle data corresponding to Monday to Sunday.

[0087] In this embodiment, the small cycle set refers to sleep small cycles with the same initial and end ranges, for example, including but not limited to multiple dates included in the working day (such as Monday to Friday, Monday to Saturday, or Tuesday to Sunday, etc.).

[0088] The beneficial effects of the above technical solution are as follows: the present invention uses the valid data of the user's historical sleep data to generate and determine the sleep state change corresponding to the sleep micro-cycle, generate a sleep state change graph, and classify the sleep micro-cycles with similar sleep needs according to the initial and end ranges of the cycle to generate a micro-cycle set, which provides a basis for determining the subsequent sleep request level and ensures that the user can maintain a similar good sleep state on dates with different sleep needs (for example, weekdays and weekends); then compare the sleep state change graphs corresponding to all sleep micro-cycles in the same micro-cycle set, determine the change node interval corresponding to each sleep state change node, and according to the change node interval, combine the user's sleep Fluctuations, determine the standard sleep state change node corresponding to each sleep state change node of each small sleep cycle respectively; based on the standard sleep state change node, generate the user's personal sleep rhythm in the large sleep cycle, use the work cycle as the basis for dividing the large sleep cycle, and divide the large sleep cycle into multiple small sleep cycles according to the weekly time, and determine the position of the standard sleep state change node corresponding to each sleep state change in the small sleep cycle, so as to obtain the user's personalized sleep rhythm, provide a basis for the sleep assistance guidance of the accompanying robot, effectively improve the sleep assistance guidance of the accompanying robot to the user to be more in line with the user's actual sleep situation, and improve the accuracy of sleep quality assessment and sleep assistance.

[0089] Embodiment 4:

[0090] On the basis of Embodiment 3, the personalized adaptive unit includes:

[0091] The standard node determination subunit is used to determine the periodic state alternation of each sleep state change diagram based on the human body sleep change law;

[0092] Based on the alternation of the cycle states, the sleep state change nodes of the multiple sleep state change graphs in the sleep graph group are aligned, and according to the alignment result, the change node intervals corresponding to the sleep state change nodes of different sleep microcycles and the node distribution discreteness in the change node intervals are determined to determine the node concentration interval;

[0093] Compare the node concentration intervals corresponding to the same sleep state change node of multiple sleep small cycles included in the small cycle set to obtain the interval overlap rate, and if the interval overlap rate is greater than or equal to a preset threshold, use the overlapped interval center as the standard sleep state change node corresponding to the sleep state change node;

[0094] If the interval overlap rate is less than a preset threshold, the centers of the node concentration intervals corresponding to the sleep mini-cycles in the mini-cycle concentration are respectively used as standard sleep state change nodes of the sleep state change nodes corresponding to the sleep mini-cycles.

[0095] In this embodiment, the changing pattern of human sleep refers to the alternation pattern of deep and light sleep.

[0096] In this embodiment, the cycle state alternation refers to the alternating state of deep and light sleep in the user's sleep micro-cycle, and one alternation of deep and light sleep is a state transition cycle. There are multiple state transition cycles in one sleep micro-cycle.

[0097] In this embodiment, the node concentration interval refers to a range in which the sleep state change nodes are concentrated within the change node interval.

[0098] In this embodiment, the interval overlap rate refers to the interval range overlap rate of the change node intervals corresponding to the same sleep change node in different sleep micro-cycles.

[0099] In this embodiment, the value range of the preset threshold is within [0.85, 1].

[0100] In this embodiment, the overlapped interval center refers to the central time point of the overlapped portion of two or more sleep mini-cycles whose interval overlap rate corresponding to the same sleep state change node in the mini-cycle set is greater than or equal to a preset threshold.

[0101] The beneficial effects of the above technical solution: the present invention centrally processes multiple sleep small-cycle data in a small-cycle set, and determines the standard sleep state change node of the same sleep change node corresponding to different sleep small-cycles in the small-cycle set according to the fluctuation amplitude of historical sleep data. While ensuring the commonality of sleep state changes in the small-cycle set, the uniqueness of sleep state changes of multiple sleep small-cycles in the sleep small-cycle is retained, which is beneficial to improving the accuracy of determining the user's personalized sleep node, thereby providing the accuracy of the robot's sleep quality assessment.

[0102] Embodiment 5:

[0103] Based on Embodiment 2, the sleep quality assessment unit includes:

[0104] The rhythm determination subunit is used to obtain the personal sleep rhythm corresponding to the current date and the sleep cycle, and to filter and determine the standard sleep state change node position of each sleep state change node contained in the current date according to the current date, and generate the current sleep rhythm corresponding to the current date;

[0105] A sleep state determination subunit, used to determine the target sleep state corresponding to the user based on the current sleep rhythm and the user's sleep time, and judge whether the current sleep depth is consistent with the target sleep state;

[0106] If they are inconsistent, it is determined that the user's current sleep quality is poor;

[0107] Otherwise, obtain the respiration data and heart rate data within the preset time period, obtain the average respiration and average heart rate, and simultaneously obtain the stable respiration frequency and stable heart rate corresponding to the stable stage of deep sleep of the user;

[0108] The sleep quality assessment subunit is used to obtain a breathing ratio based on the average breathing and the file breathing frequency, and to obtain a heart rate ratio based on the robust and average heart rate, and to compare the breathing ratio with the heart rate ratio to obtain a robust ratio difference, and to determine whether the robust ratio difference is within a preset range at any time. If so, the smaller value of the breathing ratio or the heart rate ratio is used as the target ratio;

[0109] If not, the larger value of the breathing ratio or the heart rate ratio is used as the target ratio;

[0110] When the target ratio is within the preset range, it is determined that the user's current sleep quality is good;

[0111] Otherwise, it is determined that the user's current sleep quality is poor.

[0112] In this embodiment, the current sleep rhythm refers to the sleep rhythm (ie, the change in sleep state) corresponding to the sleep micro-cycle corresponding to the current date of the user.

[0113] In this embodiment, the current date refers to weekly time, including seven days from Monday to Sunday.

[0114] The beneficial effects of the above-mentioned on-board solution: the present invention determines the user's current date and the user's current sleep rhythm through a rhythm determination subunit, and then determines the user's current target sleep state based on the current sleep rhythm and the user's sleep time, and determines whether the current sleep depth is consistent with the target sleep state, thereby determining whether the user's sleep state is good, thereby realizing rapid monitoring of the user's sleep quality.

[0115] Embodiment 6:

[0116] Based on Embodiment 3, the sleep guidance triggering unit includes:

[0117] A type determination subunit, used to determine the type of poor sleep of the user according to the sleep micro-cycle corresponding to the current date;

[0118] A request generating subunit, for generating a request for enhanced sleep assistance if the current sleep condition is of the first poor type;

[0119] If the current sleep condition is of the second poor type, a regular sleep assistance request is generated;

[0120] The request generating subunit is used to send an enhanced sleep-aiding request or a conventional sleep-aiding request to the sleep-aiding control module.

[0121] In this embodiment, the first type of poor sleep refers to the situation where the user has poor sleep on weekdays (which can be Monday to Friday, or Monday to Saturday, and can also be customized by the user).

[0122] In this embodiment, the second poor sleep type refers to the situation where the user has poor sleep on rest days.

[0123] The beneficial effects of the above technical solution: the present invention determines the type of the user's current poor sleep according to the sleep micro-cycle corresponding to the current date and then generates different types of sleep-aid requests, while ensuring that poor sleep can get effective sleep guidance in time, ensuring that the first type of poor sleep (for example, poor sleep on weekdays) gets better sleep-aid measures, urging the user to quickly enter deep sleep, ensuring that the user has good sleep quality, and providing a basis for the user to work efficiently the next day.

[0124] Embodiment 7:

[0125] Based on Example 1, the function matching module, such as Figure 3 As shown, including:

[0126] A synchronous data acquisition unit, for acquiring environmental monitoring data corresponding to the associated equipment of the accompanying robot after receiving a sleep-aiding request, to obtain synchronous environmental data;

[0127] An environmental data processing unit, used to compare the synchronized environmental data with the corresponding preset comfort value, determine whether there is an environmental parameter that needs to be adjusted, and if so, use the environmental parameter as a parameter to be adjusted, and determine a basic sleep aid based on the parameter to be adjusted;

[0128] A music level determination unit, used to determine a target level corresponding to the sleep-aiding music based on the user's current sleep quality;

[0129] The sleep aid means determination unit is used to generate the best sleep aid means corresponding to the user's current sleep quality based on the target levels corresponding to the basic sleep aid means and the sleep aid music required.

[0130] In this embodiment, the preset comfort values ​​include the illumination suitable for sleeping (the value is 10 lx), the humidity suitable for the human body (the value is 35%) and the temperature (the value is 23° C.).

[0131] When the ambient light intensity is greater than 10lx, lower the brightness of the lamp.

[0132] When the ambient humidity is less than 35%, the humidifier is controlled to humidify, and when the ambient humidity is greater than 60%, the humidifier is controlled to stop working.

[0133] When the ambient temperature is greater than or less than 23℃, the air conditioner is controlled to cool to room temperature to 23℃.

[0134] In this embodiment, basic sleep assistance means include but are not limited to lamp illumination control, color temperature control (default control to blue light when the user does not sleep well), temperature control and humidity control.

[0135] In this embodiment, the best sleeping aids include basic sleeping aids and music sleeping aids.

[0136] The beneficial effects of the above technical solution are as follows: the present invention completes the acquisition of synchronous environmental data through the synchronous data acquisition unit, and then determines the environmental parameters that need to be regulated through the environmental data processing unit, thereby determining the basic sleep aid means, and then determines the target level corresponding to the sleep-aid music based on the user's current sleep quality through the music level determination unit, and finally generates the best sleep aid means corresponding to the user's current sleep quality based on the basic sleep aid means and the target level corresponding to the sleep-aid music through the sleep aid means determination unit, intelligently completes the matching of the sleep aid means for the user's current sleep quality, and provides a basis for the user's sleep aid guidance.

[0137] Embodiment 8:

[0138] Based on Example 6, the function matching module, such as Figure 3 As shown, it also includes:

[0139] a request parsing processing unit, configured to parse the received sleep-aiding request, determine the type of the sleep-aiding request, and when the sleep-aiding request is a request for enhanced sleep-aiding, automatically increase the target level corresponding to the sleep-aiding music required determined by the sleep-aiding level determining unit by one;

[0140] When the sleep-aiding request is a regular sleep-aiding request, the target level corresponding to the sleep-aiding music determined by the sleep-aiding level determining unit will be maintained.

[0141] The beneficial effects of the above technical solution are as follows: the received sleep-aid request is parsed by the request parsing processing unit to determine the type of sleep-aid request, and then the target level of the sleep-aid music corresponding to the sleep-aid request type is processed, thereby effectively accelerating the speed at which users enter deep sleep on weekdays, ensuring that users have good sleep quality on weekdays, and providing a basis for users to work efficiently the next day.

[0142] Embodiment 9:

[0143] Based on Embodiment 8, the music level determination unit includes:

[0144] A state difference determination subunit, used to obtain a state time difference between a user's current sleep state and a target sleep state;

[0145] An error evaluation subunit, used for obtaining a sleep instruction evaluation coefficient based on a state time difference and a user state transition cycle;

[0146] a music level determination subunit, configured to determine that the target level of the music for the current sleep-aiding requirement is primary when the sleep instruction evaluation coefficient is in the first interval;

[0147] When the sleep instruction evaluation coefficient is in the second interval, it is determined that the target level of the current sleep-aiding music is intermediate;

[0148] When the sleep instruction evaluation coefficient is in the third interval, it is determined that the target level for the current sleep-aiding music is high.

[0149] In this embodiment, the sleep instruction evaluation refers to the ratio of the state time difference to the duration corresponding to the user state transition cycle.

[0150] In this embodiment, the first interval value range is (0, 0.2]; the second interval value range is (0.2, 0.7]; the third interval value range is (0.7, +∞).

[0151] The beneficial effects of the above technical solution are as follows: the present invention obtains the state time difference between the user's current sleep state and the target sleep state through the state difference determination subunit, and then obtains the sleep instruction evaluation coefficient according to the state time difference and the user's state conversion cycle through the error evaluation subunit. Finally, the music level determination subunit determines the target level of the current sleep-aid music according to the sleep instruction evaluation coefficient, thereby achieving the purpose of determining the target level of the current sleep-aid music according to the user's sleep quality evaluation result, which is conducive to improving the progress of sleep-aid guidance and urging the user to quickly enter the target sleep state.

[0152] Embodiment 10:

[0153] Based on Example 1, the sleep aid control module, such as Figure 4 As shown, including:

[0154] A target determination unit, used to determine the target-related device that needs to be regulated and its corresponding sleep-aiding measure according to the best sleep-aiding means;

[0155] A control instruction generating unit, used for generating corresponding control instructions based on the sleep-aiding measures;

[0156] A sending control unit, used to send a control instruction to a corresponding target-related device, and control the target-related device to complete a corresponding sleep-aiding measure;

[0157] Before the sleep-aiding music is played, the music list of corresponding levels in the music database is screened according to the user's listening preferences, a list to be played is obtained, and random playback is performed based on the list to be played.

[0158] In this embodiment, the associated devices include but are not limited to temperature control devices (eg, air conditioners, fans), humidifiers, music players, lamps, etc.

[0159] The beneficial effects of the above technical solution: The present invention realizes precise control of target-associated devices through a target determination unit, a control instruction generation unit and a sending control unit. When the user does not sleep well, it automatically performs sleep-aid guidance, provides the user with a comfortable sleeping environment, and helps the user quickly enter a good sleep state.

[0160] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent accompanying robot with sleep monitoring and sleep guidance functions, characterized in that: include: Intelligent monitoring module, used to collect users' sleep-related data in real time and upload it to the cloud; The cloud processing module is used to analyze the user's sleep-related data, determine the user's sleep state, and combine the user's personal sleep rhythm to determine whether the user's current sleep quality is good. If not, a sleep-aiding request is sent to the sleep-aiding control module; The function matching module is used to match the best sleep aid method for the user based on the user's actual sleep situation and the synchronized environment data after receiving the sleep aid request; A sleep-aiding control module, used to determine the target associated device and its corresponding sleep-aiding measure according to the best sleep-aiding means, generate a control instruction, and control the target associated device to complete the corresponding sleep-aiding measure through the control instruction; The cloud processing module includes: A personalized adaptive unit is used to obtain historical sleep data corresponding to multiple sleep cycles of the user, and respectively determine the sleep start time point and sleep end time point corresponding to multiple sleep microcycles in each sleep macrocycle; Perform synchronous alignment processing on the sleep micro-cycles corresponding to the multiple sleep macro-cycles, and compare the sleep start time points and the sleep end time points of the sleep micro-cycles according to the alignment results to obtain time comparison results; Based on the time comparison result, determine the cycle start and end range corresponding to the same sleep micro-cycle, intercept the data of each sleep micro-cycle based on the cycle start and end range distribution, and obtain the effective sleep data of the cycle; Generate a breathing change curve and a heart rate change curve of the user based on the effective sleep data of the cycle, determine the sleep state change corresponding to the sleep micro-cycle based on the breathing change curve and the heart rate change curve, and generate a sleep state change graph; The initial and end ranges of all sleep microcycles are compared to obtain cycle similarity. Based on the cycle similarity, the sleep microcycles are clustered to obtain several microcycle sets. Compare the sleep state change graphs corresponding to all sleep micro-cycles in the same micro-cycle set, determine the change node interval corresponding to each sleep state change node, and determine the standard sleep state change node corresponding to each sleep state change node of each sleep micro-cycle according to the change node interval and the user's sleep fluctuation. Based on the standard sleep state change node, generate the user's personal sleep rhythm in the sleep cycle; By determining the position of the standard sleep state change node corresponding to each sleep state change in the sleep microcycle, the user's personalized sleep rhythm is obtained; Among them, the effective sleep data of the cycle refers to the sleep small cycle data except the sleep data corresponding to the initial and end ranges of the cycle; The change node interval refers to the time interval where a sleep state change node is located in the user's historical sleep data; The standard sleep state change node refers to the standard time point at which the user's sleep state changes; Synchronous alignment processing refers to aligning the same sleep micro-cycles in each sleep macro-cycle; The personalized adaptive unit includes: The standard node determination subunit is used to determine the periodic state alternation of each sleep state change diagram based on the human body sleep change law; Based on the alternation of the cycle states, the sleep state change nodes of the multiple sleep state change graphs in the sleep picture group are aligned, and according to the alignment results, the change node intervals corresponding to the sleep state change nodes of different sleep microcycles and the node distribution discreteness within the change node intervals are determined to determine the node concentration intervals; Compare the node concentration intervals corresponding to the same sleep state change node of multiple sleep small cycles included in the small cycle set to obtain the interval overlap rate, and if the interval overlap rate is greater than or equal to a preset threshold, use the overlapped interval center as the standard sleep state change node corresponding to the sleep state change node; If the interval overlap rate is less than a preset threshold, the centers of the node concentration intervals corresponding to each sleep mini-cycle in the mini-cycle collection are respectively used as standard sleep state change nodes of the sleep state change nodes corresponding to the sleep mini-cycles; The cycle state alternation refers to the alternation of deep and light sleep states within the user's sleep cycle. One alternation of deep and light sleep is a state transition cycle. The node concentration interval refers to the range where the sleep state change nodes are concentrated within the change node interval; The interval overlap rate refers to the interval range overlap rate of the change node intervals corresponding to the same sleep change node in different sleep microcycles; The overlap interval center refers to the central time point of the overlapped portion of the intervals of two or more sleep small cycles whose overlap rate of the node set intervals corresponding to the same sleep state change node in the small cycle set is greater than or equal to a preset threshold.

2. The intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions according to claim 1, characterized in that: Cloud processing module, including: A sleep data processing unit, used to analyze sleep-related data, obtain user breathing data and heart rate data, compare the user's breathing data and heart rate data with standard breathing data and standard heart rate data, and determine the user's current sleep depth based on the comparison results; A sleep quality assessment unit, used to determine whether the user's current sleep quality is good based on the current sleep depth and with reference to the user's personal sleep rhythm; The sleep guidance trigger unit is used to generate a sleep assistance request and send it to the sleep assistance control module when determining that the user's current sleep quality is poor.

3. The intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions according to claim 1, characterized in that: Sleep boot trigger unit, comprising: A type determination subunit is used to determine the type of poor sleep of the user according to the sleep microcycle corresponding to the current date; A request generating subunit, for generating a request for enhanced sleep assistance if the current sleep condition is of the first poor type; If the current sleep condition is of the second poor type, a regular sleep assistance request is generated; The request generating subunit is used to send an enhanced sleep-aiding request or a conventional sleep-aiding request to the sleep-aiding control module.

4. The intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions according to claim 1, characterized in that: Function matching module, including: A synchronous data acquisition unit, used to acquire environmental monitoring data corresponding to the associated equipment of the accompanying robot after receiving the sleep-aiding request, and obtain synchronous environmental data; An environmental data processing unit, used to compare the synchronized environmental data with the corresponding preset comfort value, determine whether there is an environmental parameter that needs to be adjusted, and if so, use the environmental parameter as a parameter to be adjusted, and determine a basic sleep aid based on the parameter to be adjusted; A music level determination unit, used to determine a target level corresponding to the sleep-aiding music based on the user's current sleep quality; The sleep aid determination unit is used to generate the best sleep aid corresponding to the user's current sleep quality based on the basic sleep aid and the target level corresponding to the sleep aid music.

5. The intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions according to claim 4, characterized in that: Function matching module also includes: a request parsing processing unit, configured to parse the received sleep-aiding request, determine the type of the sleep-aiding request, and when the sleep-aiding request is a request for enhanced sleep-aiding, automatically increase the target level corresponding to the sleep-aiding music required determined by the sleep-aiding level determining unit by one; When the sleep-aiding request is a regular sleep-aiding request, the target level corresponding to the sleep-aiding music determined by the sleep-aiding level determining unit will be maintained.

6. The intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions according to claim 5, characterized in that: Music grade determination unit, including: A state difference determination subunit, used to obtain a state time difference between a user's current sleep state and a target sleep state; An error evaluation subunit, used for obtaining a sleep instruction evaluation coefficient based on a state time difference and a user state transition cycle; a music level determination subunit, configured to determine that the target level of the music for the current sleep-aiding requirement is primary when the sleep instruction evaluation coefficient is in the first interval; When the sleep instruction evaluation coefficient is in the second interval, it is determined that the target level of the current sleep-aiding music is intermediate; When the sleep instruction evaluation coefficient is in the third interval, it is determined that the target level for the current sleep-aiding music is high.

7. The intelligent accompanying robot with sleep monitoring and sleep-aiding guiding functions according to claim 1, characterized in that: Sleep aid control module, including: A target determination unit, used to determine the target-related device that needs to be regulated and its corresponding sleep-aiding measure according to the best sleep-aiding means; A control instruction generating unit, used for generating corresponding control instructions based on the sleep-aiding measures; A sending control unit, used to send a control instruction to a corresponding target-related device, and control the target-related device to complete a corresponding sleep-aiding measure; Before the sleep-aiding music is played, the music list of corresponding levels in the music database is screened according to the user's listening preferences, a list to be played is obtained, and random playback is performed based on the list to be played.

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