A temperature control method, device, apparatus, and storage medium

Abstract

The application discloses a temperature control method, device, equipment and storage medium, comprising: obtaining sleep sign data of a target object collected by a monitoring device; determining a heart rate trend, a breathing trend and sleep state data of the target object during sleep according to the sleep sign data; and performing environment temperature regulation according to the heart rate trend, the breathing trend and the sleep state data. The above technical solution can meet the demand of physiological parameter changes of different sleep stages of the human body on the environment temperature, dynamically control a sleep environment air conditioning system, provide a comfortable sleep temperature environment, realize rapid sleep and improve the deep sleep proportion, and improve the flexibility and practicality of temperature regulation control, thereby ensuring the comfort of sleep of the target object.

Description

Technical Field

[0001] This invention relates to the field of temperature control technology, and in particular to a temperature control method, apparatus, device, and storage medium. Background Technology

[0002] With the rapid development of smart home technology, a wide variety of smart home devices are emerging. Air conditioners, as an essential household appliance, have become a common sight in many homes.

[0003] Currently, air conditioners operate continuously based on parameters set by users before sleep. During sleep, the perceived temperature can often be too low or too high, leading to poor sleep quality. To ensure better sleep and improve user comfort, more and more air conditioners have added sleep modes, adjusting the temperature at different times to enhance sleep quality. However, using sleep mode to regulate ambient temperature still relies on pre-set parameters, resulting in limited flexibility and practicality. Summary of the Invention

[0004] This invention provides a temperature control method, device, equipment, and storage medium that can adjust the ambient temperature in real time based on the sleep vital signs and sleep state data of the target object, thereby improving the flexibility and practicality of temperature regulation and control and ensuring the comfort of the target object's sleep.

[0005] In a first aspect, embodiments of this disclosure provide a temperature control method, including:

[0006] Acquire sleep vital signs data of the target subject collected by monitoring equipment;

[0007] Based on the sleep vital signs data, determine the heart rate trend, respiratory trend, and sleep state data of the target subject during sleep;

[0008] The ambient temperature is regulated based on the heart rate trend, breathing trend, and sleep state data.

[0009] Secondly, embodiments of this disclosure provide a temperature control device, comprising:

[0010] The vital signs data acquisition module is used to acquire sleep vital signs data of the target object collected by the monitoring equipment;

[0011] The status data determination module is used to determine the heart rate trend, respiratory trend, and sleep status data of the target object during sleep based on the sleep vital signs data.

[0012] An ambient temperature control module is used to control the ambient temperature based on the heart rate trend, breathing trend, and sleep state data.

[0013] Thirdly, embodiments of this disclosure provide an electronic device, including:

[0014] At least one processor; and

[0015] A memory that is communicatively connected to at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor can perform a temperature control method provided in the first aspect embodiment described above.

[0017] Fourthly, embodiments of this disclosure provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement a temperature control method provided in the first aspect of the embodiments described above.

[0018] This invention discloses a temperature control method, apparatus, device, and storage medium that acquires sleep vital sign data of a target subject collected by a monitoring device; determines the target subject's heart rate trend, respiratory trend, and sleep state data during sleep based on the sleep vital sign data; and regulates the ambient temperature based on the heart rate trend, respiratory trend, and sleep state data. This technical solution can meet the environmental temperature requirements of physiological parameter changes at different stages of human sleep, dynamically control the sleep environment air conditioning system, provide a comfortable sleep temperature environment, facilitate rapid sleep onset and increase the proportion of deep sleep, improve the flexibility and practicality of temperature regulation control, and ensure the comfort of the target subject's sleep.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a temperature control method provided in Embodiment 1 of the present invention;

[0022] Figure 2 This is a flowchart of a temperature control method provided in Embodiment 2 of the present invention;

[0023] Figure 3This is an example illustration of the fitting curve involved in a temperature control method provided in Embodiment 2 of the present invention;

[0024] Figure 4 This is a schematic diagram of the structure of a temperature control device provided in Embodiment 3 of the present invention;

[0025] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," and "target," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Example 1

[0029] Figure 1 This is a flowchart of a temperature control method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where the ambient temperature is adaptively adjusted based on the sleep status of the target object. The method can be executed by a temperature control device, which can be implemented in hardware and / or software.

[0030] like Figure 1 As shown, the method includes:

[0031] S101. Obtain sleep vital signs data of the target object collected by the monitoring equipment.

[0032] In this embodiment, the monitoring device can be understood as a device that comes into close contact with the target object and is used to collect a series of physical data of the target object, such as a smart mattress. The target object can be understood as the person whose sleep is being monitored. Sleep vital signs data can be understood as the vital signs information of the target object during sleep.

[0033] The sleep vital signs data include: heart rate data, respiratory data, and body movement count of the target subject. Heart rate data can be understood as the heart rate collected by the monitoring device during the target subject's sleep; respiratory data can be understood as the respiratory rate collected by the monitoring device during the target subject's sleep; and body movement count can be understood as the number of body movements of the target subject collected by the monitoring device during the target subject's sleep.

[0034] Specifically, during the target subject's sleep, a monitoring device in close contact with the subject will monitor the subject's sleep status in real time and collect relevant sleep vital signs data. During the target subject's sleep, a temperature control device will acquire the target subject's heart rate, respiratory rate, and number of body movements collected by the monitoring device.

[0035] S102. Determine the heart rate trend, respiratory trend, and sleep state data of the target subject during sleep based on sleep vital signs data.

[0036] In this embodiment, heart rate trend can be understood as the trend of heart rate changes during the target subject's sleep. Respiratory trend can be understood as the trend of respiratory rate changes during the target subject's sleep. Sleep state data can be understood as data that reflects the target subject's sleep state during sleep.

[0037] The sleep state data includes the target subject's sleep state, which includes the waking stage, light sleep stage I, light sleep stage II, deep sleep stage, and dreaming stage. It is understood that the criteria for determining each sleep stage are determined based on actual circumstances, and this embodiment does not impose any limitations on this.

[0038] Specifically, based on sleep symptom data such as heart rate, respiratory rate, and body movement frequency of the target subject, the changes in heart rate and respiration during sleep are determined, corresponding change curves are fitted, and the trends in heart rate and respiration during sleep are further determined. The target subject's heart rate and respiratory rate are input into a pre-set model to obtain the model's output results. The model output results are the target subject's sleep state data, that is, which stage of sleep the target subject is in: wakefulness, light sleep stage I, light sleep stage II, deep sleep, or dreaming stage.

[0039] S103. Adjust the ambient temperature based on heart rate trends, breathing trends, and sleep state data.

[0040] In this embodiment, based on the target object's heart rate trend, breathing trend, and sleep state data, and combined with the weight values ​​of each data point, the most suitable temperature change for regulating the ambient temperature is determined. A new ambient temperature is then set based on the current ambient temperature and the temperature change, and the ambient temperature is regulated according to the new ambient temperature.

[0041] This invention provides a temperature control method that acquires sleep vital sign data of a target subject collected by a monitoring device; determines the target subject's heart rate trend, respiratory trend, and sleep state data during sleep based on the sleep vital sign data; and adjusts the ambient temperature based on the heart rate trend, respiratory trend, and sleep state data. This technical solution can meet the environmental temperature requirements of changes in physiological parameters at different stages of human sleep, dynamically control the sleep environment air conditioning system, provide a comfortable sleep temperature environment, facilitate rapid sleep onset and increase the proportion of deep sleep, improve the flexibility and practicality of temperature regulation control, and ensure the comfort of the target subject's sleep.

[0042] Example 2

[0043] Figure 2 This is a flowchart of a temperature control method provided in Embodiment 2 of the present invention. This embodiment is a further optimization of any of the above embodiments and can be applied to situations where the ambient temperature is adaptively adjusted based on the sleep status of the target object. The method can be executed by a temperature control device, which can be implemented in hardware and / or software.

[0044] like Figure 2 As shown, the method includes:

[0045] S201. Obtain sleep vital signs data of the target object collected by the monitoring equipment.

[0046] S202. Based on the heart rate and respiratory data included in the sleep vital signs data, determine the heart rate trend and respiratory trend of the target subject during sleep.

[0047] In this embodiment, based on the heart rate data and respiratory data of the target subject included in the sleep vital signs data, the average heart rate is calculated for a preset number of heart rate data, and the average respiratory rate is calculated for a preset number of respiratory data. The heart rate trend of the target subject during sleep is fitted based on the average heart rate, and the respiratory trend of the target subject during sleep is fitted based on the average respiratory rate.

[0048] S203. Input the sleep signs data into the pre-trained sleep state determination model to obtain the sleep state data of the target object during sleep.

[0049] In this embodiment, the sleep state determination model can be understood as a model used to determine the sleep state of the object corresponding to the input data based on the input data, and it is an XGBOOST decision tree model.

[0050] Specifically, the heart rate and respiratory data of the target subject from the sleep vital signs data are input into a pre-trained sleep state determination model to obtain the model's output results. The model output results are the sleep state data of the target subject during sleep, including the waking stage, light sleep stage I, light sleep stage II, deep sleep stage, and dream stage.

[0051] S204. Determine the current temperature change based on heart rate trends, respiratory trends, and sleep status data.

[0052] In this embodiment, the current temperature change can be understood as the most suitable temperature change for the target object's current sleep state, determined based on the most recent monitoring of the target object. The temperature change can be positive, indicating an increase in the controlled environment temperature, or negative, indicating a decrease in the controlled environment temperature.

[0053] Specifically, a weighted calculation is performed based on the heart rate trend and its corresponding heart rate data weight, the breathing trend and its corresponding breathing data weight, and the sleep state data and its corresponding state data weight to obtain the current temperature change that is most suitable for the target's current physical condition and sleep state.

[0054] S205. The sum of the current temperature value and the current temperature change is determined as the temperature value to be controlled.

[0055] In this embodiment, the current temperature value can be understood as the current ambient temperature. The temperature value to be adjusted can be understood as the temperature value most suitable for the target object's current sleep state.

[0056] Specifically, the sum of the current temperature value and the current temperature change is calculated, and this sum is determined as the optimal temperature to be regulated that best suits the target subject's current sleep state. The current temperature change rate can be positive or negative. When the current temperature change is positive, the temperature to be regulated is increasing relative to the current temperature, indicating a warming effect; when the current temperature change is negative, the temperature to be regulated is decreasing relative to the current temperature, indicating a cooling effect.

[0057] S206. Adjust the ambient temperature according to the temperature value to be adjusted.

[0058] In this embodiment, based on the determined temperature value that is most suitable for the target object's current sleep state, the air conditioner is controlled to blow air according to the temperature value to be adjusted, thereby achieving the regulation of the current ambient temperature.

[0059] This invention provides a temperature control method in Embodiment 2, which involves acquiring sleep vital sign data of a target subject collected by a monitoring device; determining the heart rate trend and respiratory trend of the target subject during sleep based on the heart rate and respiratory data included in the sleep vital sign data; inputting the sleep vital sign data into a pre-trained sleep state determination model to obtain sleep state data of the target subject during sleep; determining the current temperature change based on the heart rate trend, respiratory trend, and sleep state data; determining the sum of the current temperature value and the current temperature change as the temperature to be controlled; and regulating the ambient temperature based on the temperature to be controlled. This technical solution can meet the needs of human physiological parameters changing at different stages of sleep for ambient temperature, dynamically control the sleep environment air conditioning system, provide a comfortable sleep temperature environment, achieve rapid sleep onset and increase the proportion of deep sleep, improve the flexibility and practicality of temperature regulation control, and ensure the comfort of the target subject's sleep.

[0060] As a first optional embodiment of the embodiments, based on the above embodiments, this first optional embodiment further optimizes and adds a step of determining the heart rate trend and respiratory trend of the target subject during sleep based on the heart rate data and respiratory data included in the sleep vital signs data, including:

[0061] a1) Based on the heart rate data and respiratory data included in the preset number of sleep vital signs data, fit the heart rate change curve corresponding to the heart rate data and the respiratory change curve corresponding to the respiratory data respectively.

[0062] In this embodiment, the heart rate change curve can be understood as a curve used to characterize the heart rate changes of the target subject during sleep. The respiratory change curve can be understood as a curve used to characterize the respiratory rate changes of the target subject during sleep.

[0063] Specifically, based on a preset number of heart rate data points, a weighted moving average is used to calculate the average heart rate. The heart rate data is then smoothed, and the resulting average heart rate values ​​are combined with a sixth-order polynomial to fit a heart rate variation curve. Similarly, based on a preset number of respiratory data points, a weighted moving average is used to calculate the average respiratory rate. The respiratory data is then smoothed, and the resulting average respiratory rate values ​​are combined with a sixth-order polynomial to fit a respiratory variation curve.

[0064] For example, when the preset number is 5, the formula for calculating the average heart rate is: Where hr represents heart rate; the formula for calculating mean respiratory rate is: Here, br represents respiratory rate. For example, if the monitoring device collects 50 heart rate data points, it calculates 10 average heart rates from these 50 data points based on a preset quantity of 5. Then, based on these 10 smoothed average heart rates, a sixth-order polynomial is used to fit the heart rate change curve.

[0065] Figure 3 This is an example illustration of the fitting curve involved in a temperature control method provided in Embodiment 2 of the present invention, as shown in the figure. Figure 3 As shown, the horizontal axis represents the number of average data points (average heart rate or average respiratory rate) obtained from sleep vital signs data arranged chronologically, and the vertical axis represents the amplitude of the average heart rate or average respiratory rate. The lowest heart rate / respiratory rate value is reached at point A, and the highest heart rate / respiratory rate value is reached at point B. It is understandable that, as... Figure 3 The example diagram of the fitted curve shown can represent either a respiratory change curve or a heart rate change curve. The specific curve type is determined based on the actual data, and this embodiment does not impose any limitations on it.

[0066] b1) Determine the heart rate trend and respiratory trend of the target subject during sleep based on the heart rate change curve and respiratory change curve.

[0067] In this embodiment, when the target object changes from cold discomfort to comfort, heart rate and respiration show a decreasing trend; conversely, when changing from comfort to hot discomfort, heart rate and respiration increase. Therefore, the first derivatives of the fitted heart rate and respiration curves are calculated to obtain their current first derivatives, thus determining the heart rate trend and the respiration trend. Specifically, a first derivative greater than 0 indicates an upward trend, while a first derivative less than 0 indicates a downward trend.

[0068] As a second optional embodiment of the embodiments, based on the above embodiments, this second optional embodiment further optimizes and adds the training steps of the sleep state determination model, including:

[0069] a2) Obtain the vital signs data of the sample objects collected by the monitoring equipment, and the sample status data of the sample objects collected by the standard testing equipment.

[0070] In this embodiment, the sample subject can be understood as the person whose vital signs data are being monitored by the monitoring device. Sample vital signs data can be understood as the vital signs information of the sample subject during sleep, including the sample subject's heart rate data, respiratory data, and number of body movements. The standard testing device can be understood as a polysomnography monitor, a medical device capable of accurately acquiring the subject's sleep state. Sample status data can be understood as data that reflects the sleep state of the sample subject during sleep, and is standard sleep status data corresponding to the sample vital signs data.

[0071] Specifically, the system acquires heart rate, respiratory data, and body movement data of the sample subjects from monitoring equipment, as well as sample status data from a polysomnography (PSG) system. The sample status data includes the sleep state of the sample subjects, encompassing the waking stage, light sleep stage I, light sleep stage II, deep sleep stage, and dreaming stage.

[0072] b2) Input the sample vital signs data into the preset sleep state determination model to obtain the model output verification state data.

[0073] In this embodiment, the verification status data can be understood as the sleep status result of the sample object output by the sleep status determination model after performing model calculations based on the sample vital sign data.

[0074] Specifically, the heart rate data, respiratory data, and body movement count of the sample subjects are input into a preset sleep state determination model to obtain the sleep state results of the sample subjects output by the model. It is understandable that the sleep state determination model has not been trained at this time, and the output results will have a certain error compared with the standard results.

[0075] c2) Combine the sample state data and validation state data to perform backpropagation on the model to obtain the sleep state determination model for the next iteration.

[0076] In this embodiment, the model loss is determined by combining ideal sample state data and actual validation state data. The model is then backpropagated according to a preset loss function to train the model, resulting in the completion of the current iteration training and the sleep state determination model for the next iteration.

[0077] d2) Proceed to the next iteration until the iteration termination condition is met, in order to train the sleep state determination model.

[0078] In this embodiment, the iteration termination condition can be understood as the condition that enables the model training iteration to end. For example, under the same sample vital sign data, the current sleep state determines that the validation state data output by the model is exactly the same as or substantially the same as the sample state data.

[0079] Specifically, after obtaining the sleep state determination model for the next iteration, proceed to the next iteration and continue executing steps a2) to c2) until the validation state data output by the current sleep state determination model is exactly the same as or largely the same as the sample state data, thus completing the training of the sleep state determination model and obtaining a fully trained sleep state determination model.

[0080] As a third optional embodiment, based on the above embodiments, this third optional embodiment further optimizes and adds a step of determining the current temperature change based on heart rate trend, respiratory trend, and sleep state data, including:

[0081] a3) Determine the heart rate variation coefficient during sleep of the target subject based on the heart rate trend.

[0082] In this embodiment, the heart rate change coefficient can be understood as a reference value for heart rate change determined based on the heart rate trend of the target object, including 1, 0, and -1.

[0083] Specifically, when the heart rate trend is downward, the heart rate change coefficient a is 1; when the heart rate trend is close to being stable, the heart rate change coefficient a is 0; and when the heart rate trend is upward, the heart rate change coefficient a is -1.

[0084] b3) Determine the respiratory variation coefficient during sleep of the target subject based on respiratory trends.

[0085] In this embodiment, the respiratory change coefficient can be understood as a respiratory change reference value determined based on the respiratory trend of the target object, including 1, 0, and -1.

[0086] Specifically, when the breathing trend is downward, the breathing change coefficient b is 1; when the breathing trend is close to being stable, the breathing change coefficient b is 0; and when the breathing trend is upward, the breathing change coefficient b is -1.

[0087] c3) Determine the coefficient of state change during sleep of the target subject based on sleep state data.

[0088] In this embodiment, the state change coefficient can be understood as a state change reference value determined based on the sleep state data of the target object, including 1, 0, -1, and -2.

[0089] When the sleep state data shows that the target subject's sleep state is in the waking stage, the state change reference coefficient c is -2; when the sleep state is in the dreaming stage, the state change reference coefficient c is -1; when the sleep state is in the first stage of light sleep or the second stage of light sleep, the state change reference coefficient c is 0; and when the sleep state is in deep sleep, the state change reference coefficient c is 1.

[0090] d3) Based on the preset weight values, the heart rate change coefficient, respiratory change coefficient and state change coefficient are weighted and summed to determine the current temperature change.

[0091] In this embodiment, the preset weight values ​​are the weight values ​​of the heart rate change coefficient, the respiratory change coefficient, and the state change coefficient.

[0092] Specifically, the current temperature change is determined by weighted summation of the heart rate change coefficient (a), respiratory change coefficient (b), and state change coefficient (c) along with their respective weights. The formula for determining the current temperature change is: Current temperature change = Heart rate change coefficient * Heart rate weight + Respiratory change coefficient * Respiratory weight + State change coefficient * State weight.

[0093] For example, the weight of heart rate is 0.4, the weight of respiration is 0.4, the weight of state is 0.2, and the change in current temperature is a*0.4+b*0.4+c*0.2.

[0094] Example 3

[0095] Figure 4 This is a schematic diagram of a temperature control device provided in Embodiment 3 of the present invention. Figure 4 As shown, the device includes:

[0096] The vital signs data acquisition module 31 is used to acquire sleep vital signs data of the target object collected by the monitoring equipment.

[0097] The status data determination module 32 is used to determine the heart rate trend, respiratory trend and sleep status data of the target object during sleep based on the sleep vital signs data.

[0098] The ambient temperature control module 33 is used to control the ambient temperature based on the heart rate trend, breathing trend and sleep state data.

[0099] This technical solution employs a temperature control device that can meet the environmental temperature requirements of physiological parameter changes at different stages of human sleep. It dynamically controls the air conditioning system of the sleep environment, providing a comfortable sleep temperature environment, enabling rapid sleep onset and increasing the proportion of deep sleep, thereby enhancing the flexibility and practicality of temperature regulation and control, and ensuring the sleep comfort of the target population.

[0100] Optionally, the status data determination module 32 includes:

[0101] The sleep trend determination unit is used to determine the heart rate trend and respiratory trend of the target subject during sleep based on the heart rate data and respiratory data included in the sleep vital signs data.

[0102] The state data determination unit is used to input the sleep vital signs data into a pre-trained sleep state determination model to obtain the sleep state data of the target object during sleep.

[0103] Optionally, the sleep trend determination unit is specifically used for:

[0104] Based on a preset number of heart rate and respiratory data included in the sleep vital signs data, respectively, the heart rate change curve corresponding to the heart rate data and the respiratory change curve corresponding to the respiratory data are fitted;

[0105] The heart rate and respiratory trends of the target subject during sleep are determined based on the heart rate change curve and the respiratory change curve.

[0106] Optionally, the training steps for the sleep state determination model include:

[0107] Acquire vital sign data of sample objects collected by monitoring equipment, and sample status data of sample objects collected by standard testing equipment;

[0108] The sample vital signs data are input into a preset sleep state determination model to obtain the verification state data output by the model.

[0109] The model is backpropagated by combining the sample state data and the verification state data to obtain a sleep state determination model for the next iteration;

[0110] Proceed to the next iteration until the iteration termination condition is met, in order to train the sleep state determination model.

[0111] Optionally, the ambient temperature control module 33 includes:

[0112] The temperature change determination unit is used to determine the current temperature change based on the heart rate trend, breathing trend, and sleep state data.

[0113] A temperature value determination unit is used to determine the sum of the current temperature value and the current temperature change as the temperature value to be adjusted.

[0114] An ambient temperature control unit is used to control the ambient temperature according to the temperature value to be controlled.

[0115] Optionally, the temperature change determination unit is specifically used for:

[0116] Based on the heart rate trend, determine the heart rate change coefficient of the target subject during sleep;

[0117] Based on the breathing trend, determine the breathing variation coefficient of the target subject during sleep;

[0118] Based on the sleep state data, determine the state change coefficient of the target object during sleep;

[0119] Based on preset weight values, the heart rate change coefficient, respiratory change coefficient, and state change coefficient are weighted and summed to determine the current temperature change.

[0120] Optionally, the sleep vital signs data include: the target subject's heart rate data, respiratory data, and number of body movements; the sleep state data includes the target subject's sleep state, including the waking stage, light sleep stage I, light sleep stage II, deep sleep stage, and dream stage.

[0121] The temperature control device provided in this embodiment of the invention can execute a temperature control method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0122] Example 4

[0123] Figure 5 A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0124] like Figure 5 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded into the RAM 43 from storage unit 48. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0125] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0126] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as a temperature control method.

[0127] In some embodiments, a temperature control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of a temperature control method described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to perform a temperature control method by any other suitable means (e.g., by means of firmware).

[0128] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0129] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0130] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0131] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0132] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0133] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0134] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0135] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A temperature control method, characterized in that, include: Acquire sleep vital signs data of the target subject collected by monitoring equipment; Based on the sleep vital signs data, determine the heart rate trend, respiratory trend, and sleep state data of the target subject during sleep; Based on the heart rate trend, breathing trend, and sleep state data, the ambient temperature is regulated. The step of regulating ambient temperature based on the heart rate trend, breathing trend, and sleep state data includes: The current temperature change is determined based on the heart rate trend, breathing trend, and sleep state data. The sum of the current temperature value and the current temperature change is determined as the temperature value to be adjusted. The ambient temperature is regulated according to the temperature value to be regulated. The step of determining the current temperature change based on the heart rate trend, respiratory trend, and sleep state data includes: Based on the heart rate trend, determine the heart rate change coefficient of the target subject during sleep; Based on the breathing trend, determine the breathing variation coefficient of the target subject during sleep; Based on the sleep state data, determine the state change coefficient of the target object during sleep; Based on preset weight values, the heart rate change coefficient, respiratory change coefficient, and state change coefficient are weighted and summed to determine the current temperature change.

2. The method according to claim 1, characterized in that, The step of determining the heart rate trend, respiratory trend, and sleep state data of the target subject during sleep based on the sleep vital signs data includes: Based on the heart rate and respiratory data included in the sleep vital signs data, determine the heart rate trend and respiratory trend of the target subject during sleep; The sleep signs data are input into a pre-trained sleep state determination model to obtain the sleep state data of the target object during sleep.

3. The method according to claim 2, characterized in that, The step of determining the heart rate trend and respiratory trend of the target subject during sleep based on the heart rate data and respiratory data included in the sleep vital signs data includes: Based on a preset number of heart rate and respiratory data included in the sleep vital signs data, respectively, the heart rate change curve corresponding to the heart rate data and the respiratory change curve corresponding to the respiratory data are fitted; The heart rate and respiratory trends of the target subject during sleep are determined based on the heart rate change curve and the respiratory change curve.

4. The method according to claim 2, characterized in that, The training steps for the sleep state determination model include: Acquire vital sign data of sample objects collected by monitoring equipment, and sample status data of sample objects collected by standard testing equipment; The sample vital signs data are input into a preset sleep state determination model to obtain the verification state data output by the model. The model is backpropagated by combining the sample state data and the verification state data to obtain a sleep state determination model for the next iteration; Proceed to the next iteration until the iteration termination condition is met, in order to train the sleep state determination model.

5. The method according to claim 1, characterized in that, The sleep vital signs data include: the target subject's heart rate data, respiratory data, and number of body movements; the sleep state data includes the target subject's sleep state, including the waking stage, light sleep stage I, light sleep stage II, deep sleep stage, and dream stage.

6. A temperature control device, characterized in that, include: The vital signs data acquisition module is used to acquire sleep vital signs data of the target object collected by the monitoring equipment; The status data determination module is used to determine the heart rate trend, respiratory trend, and sleep status data of the target object during sleep based on the sleep vital signs data. An ambient temperature control module is used to control the ambient temperature based on the heart rate trend, breathing trend, and sleep state data. The ambient temperature control module includes: The temperature change determination unit is used to determine the current temperature change based on the heart rate trend, breathing trend, and sleep state data. A temperature value determination unit is used to determine the sum of the current temperature value and the current temperature change as the temperature value to be adjusted. An ambient temperature control unit is used to control the ambient temperature according to the temperature value to be controlled. The temperature change determination unit is specifically used for: Based on the heart rate trend, determine the heart rate change coefficient of the target subject during sleep; Based on the breathing trend, determine the breathing variation coefficient of the target subject during sleep; Based on the sleep state data, determine the state change coefficient of the target object during sleep; Based on preset weight values, the heart rate change coefficient, respiratory change coefficient, and state change coefficient are weighted and summed to determine the current temperature change.

7. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform a temperature control method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute a temperature control method according to any one of claims 1-5.

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