Intelligent pacifying equipment and method

Abstract

The embodiment of the invention provides an intelligent pacifying device and method, the device comprises a device assembly and a device carrier, and the device assembly comprises a state recognition assembly, a heartbeat simulation assembly, an audio control assembly and a processor; wherein the state recognition assembly is configured to analyze sensing data related to the equipment carrier to determine the current state of the equipment carrier; the heartbeat simulation assembly is configured to generate simulated heartbeat through the vibration motor; the audio control component is configured to perform audio playing according to the playing parameters; and the processor is configured to send a control instruction based on the current state of the equipment carrier so as to control the heartbeat simulation component to generate simulated heartbeat and / or control the audio control component to play audio.

Description

Technical Field

[0001] This specification relates to the field of intelligent soothing, and in particular to an intelligent soothing device and method. Background Art

[0002] The global aging population is accelerating. Loneliness and mental health issues among older adults, caused by shrinking social circles and reduced intergenerational communication, have become major social challenges. Furthermore, the number of young people living alone continues to grow, and the psychological care needs of groups like those with disabilities and those recovering from surgery are becoming increasingly prominent. Traditional soothing devices offer limited functionality, rigid interactions, and minimalist designs that don't meet user needs.

[0003] Therefore, there is an urgent need for an intelligent soothing device and method to provide intelligent and personalized soothing and companionship. Summary of the Invention

[0004] One or more embodiments of the present specification provide an intelligent soothing device, which includes a device component and a device carrier, wherein the device component includes a state recognition component, a heartbeat simulation component, an audio control component and a processor; wherein the state recognition component is configured to analyze sensor data related to the device carrier to determine the current state of the device carrier; the heartbeat simulation component is configured to generate a simulated heartbeat through a vibration motor; the audio control component is configured to play audio according to playback parameters; and the processor is configured to: issue a control instruction based on the current state of the device carrier to control the heartbeat simulation component to generate the simulated heartbeat, and / or control the audio control component to play audio.

[0005] One or more embodiments of the present specification also provide an intelligent soothing method, characterized in that the method is executed based on an intelligent soothing device, including: analyzing sensor data to determine the current state of a device carrier of the intelligent soothing device; issuing a control instruction based on the current state of the device carrier to control the heartbeat simulation component to generate the simulated heartbeat, and / or control the audio control component to play audio.

[0006] One or more embodiments of this specification also provide a computer-readable storage medium, which stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the intelligent soothing method described in the above embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein: Figure 1is a module diagram of a smart soothing device according to some embodiments of this specification; Figure 2 This is a schematic diagram of generating real-time control instructions according to some embodiments of this specification; Figure 3 is a schematic diagram of determining playback parameters according to some embodiments of this specification; Figure 4 This is a schematic diagram of determining control instructions according to some embodiments of this specification. DETAILED DESCRIPTION

[0008] To more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this specification. Those skilled in the art can apply this specification to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.

[0009] It should be understood that the terms "system," "device," "unit," and / or "module" used herein are a method for distinguishing different components, elements, parts, portions, or assemblies at different levels. However, if other terms can achieve the same purpose, the terms may be replaced by other expressions.

[0010] Unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not refer to the singular but include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements specifically identified, and these steps and elements do not constitute an exclusive list. A method or apparatus may also include other steps or elements.

[0011] Flowcharts are used throughout this specification to illustrate the operations performed by systems according to embodiments of this specification. It should be understood that preceding or following operations do not necessarily need to be performed in exact order. Instead, the steps may be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0012] In some embodiments of this specification, intelligent soothing devices and methods are provided for providing intelligent, personalized soothing and companionship services, offering emotional support to users of the intelligent soothing devices. The term "user" refers to the user of the intelligent soothing device. In some embodiments, users may include, but are not limited to, the elderly or other individuals with usage needs (e.g., children, young adults, individuals with disabilities, those recovering from surgery, and others requiring psychological care).

[0013] Figure 1 This is an exemplary module diagram of a smart soothing device according to some embodiments of this specification. Figure 1 As shown, the smart soothing device 100 may include a device carrier 110 and a device component 120 .

[0014] The device carrier 110 is an object that houses the various components of the smart soothing device 100. For example, the device carrier 110 may include, but is not limited to, objects such as a doll or a pillow. For another example, the device carrier 110 may be the housing of the smart soothing device 100.

[0015] The device component 120 is the hardware component that the smart soothing device 100 relies on to perform its functions.

[0016] In some embodiments, the device component 120 may include a state recognition component 121 , a heartbeat simulation component 122 , an audio control component 123 , and a processor 124 .

[0017] The state recognition component 121 is a component that recognizes the state of the device carrier 110 .

[0018] In some embodiments, the state recognition component 121 is configured to analyze sensory data associated with the device carrier 110 to determine the current state of the device carrier.

[0019] Sensor data is data related to the state of the device carrier. For example, the device carrier's motion state and holding conditions. Motion state may include, but is not limited to, the acceleration and angular velocity of the device carrier's motion, while holding conditions may include, but are not limited to, the holding force and holding posture of the device carrier.

[0020] The current state refers to the interaction between the device carrier and the user. For example, holding, shaking, and being placed can also be considered as the device carrier being in use, while being placed can be considered as the device carrier being in an unused state.

[0021] In some embodiments, the state recognition component 121 may include a sensing unit, a processing unit, etc. The sensing unit is used to obtain sensing data related to the device carrier, and the processing unit determines the state of the device carrier by analyzing the sensing data.

[0022] In some embodiments, the sensing unit of the state recognition component 121 may include an accelerometer, a gyroscope, etc. The accelerometer is used to obtain the acceleration of the device carrier 110 when it moves, and the gyroscope is used to obtain the angular velocity of the smart soothing device 100 when it moves.

[0023] In some embodiments, the sensing unit of the state recognition component 121 may further include a pressure sensor. The pressure sensor is used to obtain pressure data at at least one location on the surface of the device carrier. The processing unit can determine the holding force and holding posture of the device carrier by analyzing the pressure data at at least one location on the surface of the device carrier.

[0024] In some embodiments, the sensing unit of the state recognition component 121 may also include other components capable of acquiring sensor data related to the device carrier, such as a speed sensor and a temperature sensor. The speed sensor may acquire the moving speed of the device carrier, and the temperature sensor may acquire the temperature distribution on the surface of the device carrier.

[0025] The processing unit can determine the current state of the device carrier by analyzing the sensor data obtained by the sensor unit. For example, when the moving speed of the device carrier is not 0 and there is pressure at multiple locations on the surface, but the acceleration and / or angular velocity is 0, the processing unit can determine that the device carrier is in a held state. For another example, when the acceleration / angular velocity of the device carrier is not 0 and there is pressure at multiple locations on the surface, the processing unit can determine that the device carrier is in a shaken state. For another example, when the moving speed, acceleration, and angular velocity of the device carrier are all 0, and there is no pressure at multiple locations on the surface, the processing unit can determine that the device carrier is in a placed state. Alternatively, the processing unit can determine whether the device carrier is being held by a user based on the temperature distribution on the surface of the device carrier, and then determine the current state of the device carrier.

[0026] It is understood that the above description is only for illustration and not limitation, and the state identification component 121 can also determine the current state of the device carrier based on various possible methods.

[0027] The heartbeat simulation component 122 is a component that generates a simulated heartbeat.

[0028] A simulated heartbeat is a process of reproducing the heartbeat through technical means.

[0029] In some embodiments, the smart soothing device 100 can generate a simulated heartbeat based on the heartbeat simulation component 122. The simulated heartbeat can be the heartbeat of someone with whom the user has an emotional connection, such as a family member or pet. By allowing the user to experience a familiar and familiar heartbeat rhythm, the device can soothe the user's emotions and provide them with a sense of security and happiness.

[0030] In some embodiments, the heartbeat simulation component 122 is configured to generate a simulated heartbeat via a vibration motor.

[0031] In some embodiments, the heartbeat simulation component 122 can generate a simulated heartbeat based on the current state of the device carrier. For example, the heartbeat simulation component 122 can be pre-set with multiple sets of preset heartbeat parameters. In response to the device carrier being in use, the heartbeat simulation component 122 can randomly select one of the multiple sets of preset heartbeat parameters and generate a simulated heartbeat according to the preset heartbeat parameters. For another example, the heartbeat simulation component 122 can receive control instructions from the processor and generate a simulated heartbeat with a corresponding vibration amplitude and frequency according to the control instructions.

[0032] For more information on controlling the heartbeat simulation component to generate simulated heartbeats, please refer to this manual. Figure 2 、 Figure 4 Related description in .

[0033] The audio control component 123 is a component for playing audio.

[0034] In some embodiments, the audio control component 123 is configured to play audio through a speaker according to the playback parameters.

[0035] Playback parameters are used to control the audio playback of the audio control component, such as audio type, playback speed, and volume.

[0036] In some embodiments, the playback parameters may include preset playback parameters and real-time playback parameters. Preset playback parameters are pre-set playback parameters that can be preset by the processor or determined by obtaining input from the user terminal. Real-time playback parameters are playback parameters determined in real time and can be determined in real time based on the user's emotions and physical signs when using the smart soothing device.

[0037] In some embodiments, the audio control component 123 can play audio based on the current state of the device carrier. For example, the audio control component 123 can pre-set multiple sets of preset playback parameters. In response to the device carrier being in use, the audio control component 123 can randomly select one of the multiple sets of preset playback parameters and play audio according to the preset playback parameters. For another example, the audio control component can receive control instructions from the processor and play audio according to the control instructions.

[0038] For more information on determining preset playback parameters and real-time playback parameters, please refer to this manual. Figure 2-Figure 3 Related description in .

[0039] The processor 124 is a component used to process data generated during the operation of the intelligent soothing device and control its operation.

[0040] In some embodiments, the processor is configured to issue a control instruction based on the current state of the device carrier to control the heartbeat simulation component to generate a simulated heartbeat and / or control the audio control component to play audio. The control instruction may include at least one of a real-time control instruction and a target control instruction.

[0041] The real-time control instruction is a control instruction determined in real time, and may include at least one of a real-time heartbeat parameter and a real-time playback parameter.

[0042] The target control instruction is a predetermined control instruction and may include at least one of a preset heartbeat parameter and a preset playback parameter.

[0043] Exemplarily, in response to the device carrier being in use, the processor may issue a control instruction.

[0044] The control instruction may be a real-time control instruction determined based on the user's real-time state. For example, in response to the device carrier entering the use state, the processor may obtain the holding force and holding posture determined by the state recognition component and determine the real-time control instruction based on the holding force and holding posture. For another example, the processor may determine the real-time control instruction based on at least one of the user's real-time physical signs and emotional characteristics, as well as the holding force and holding posture of the device carrier.

[0045] The aforementioned control instructions may also be pre-set target control instructions. For example, the processor may determine the most frequently used historical heartbeat parameters and historical playback parameters based on the user's historical data on the soothing device, and then determine the target control instruction. For another example, the processor may randomly generate candidate control instructions and screen them based on the user's steady-state physical signs and emotional baseline to determine the target control instruction.

[0046] In some embodiments, the processor may also update parameters in the control instructions based on real-time acquired user data, wherein the user data may include but is not limited to at least one of user physical signs, emotional characteristics, crosstalk data, heart rate changes, and respiratory rate changes.

[0047] For more information on determining the parameters in real-time control instructions, target control instructions, and update control instructions, please refer to this manual. Figure 2-Figure 4 Related description in .

[0048] In some embodiments, the smart soothing device 100 may further include a clock component 130. The clock component may be configured to obtain time information.

[0049] In some embodiments, the clock component may include at least one of hardware and software. For example, the hardware may include, but is not limited to, one or more of an oscillator, a real-time clock chip, and a timer, and the software may include, but is not limited to, one or more of a system clock, a network time protocol, and clock application software.

[0050] In some embodiments, the processor 124 can obtain time information through the clock component, and select preset playback parameters based on the time information and the current state of the device carrier, and control the audio control component 123 to play audio according to the preset playback parameters. For example, in the morning, play light music with the volume appropriately increased, and in the evening, play soothing music to help sleep with the volume appropriately reduced, etc. For another example, in response to the current time being consistent with the preset time, the processor 124 can also control the audio control component 123 to issue a reminder, wherein the preset time can include various important times, such as important dates, user medication time, important schedules, etc.

[0051] In some embodiments, the smart soothing device 100 may further include an ambient light collection component 140 . The ambient light collection component may be configured to obtain light intensity outside the device carrier 110 .

[0052] In some embodiments, the ambient light collection component may include but is not limited to a photosensitive sensor, a light intensity sensor, or other sensor or element that can obtain light intensity.

[0053] In some embodiments, the processor 124 can obtain the light intensity outside the device carrier 110 through the ambient light collection component, and control the heartbeat simulation component to generate a simulated heartbeat based on the light intensity, and / or control the audio component to play audio. For example, in a dim environment, sleep-inducing music is played, and in a bright environment, light music is played. For another example, in a dim environment, the intensity of the simulated heartbeat is reduced to guide the user to relax, or in a bright environment, the intensity of the simulated heartbeat is increased to ensure that the user can clearly perceive the simulated heartbeat.

[0054] In some embodiments, the smart soothing device 100 may further include a light component 150. The light component may be configured to operate according to light parameters.

[0055] In some embodiments, when the smart soothing device 100 includes a lighting component, the control instruction may further include lighting parameters, and the processor may issue a control instruction based on the current state of the device carrier to control the lighting component to operate according to the lighting parameters in the control instruction.

[0056] In some embodiments, the smart soothing device 100 may further include a communication component. The communication component is used to enable communication between the smart soothing device and a mobile terminal and / or other smart soothing devices. The mobile terminal may include at least one of a user terminal used by the user and an associated terminal used by the user's family.

[0057] The smart soothing device can achieve data transmission and communication with the user terminal and / or associated terminals through the communication component. For example, based on the communication component, the smart soothing device can connect to the user terminal and / or associated terminals via a wireless network or Bluetooth, and obtain data that the user or his / her family can upload through the application of the user terminal and / or associated terminals. For another example, based on the communication component, the smart soothing device can obtain voice messages or voice requests that the user of the associated terminal can send through the application, and through the built-in microphone and speaker of the smart soothing device, the user can interact with his / her family through voice.

[0058] Smart soothing devices can communicate and transmit data with other smart soothing devices through the communication component. For example, based on the communication component, multiple smart soothing devices can form a community circle, allowing their corresponding users to communicate and share with other users.

[0059] In some embodiments of this specification, the intelligent soothing device can determine and adjust control parameters in real time according to the environment and the user's status, and intelligently provide the user with personalized soothing and companionship services.

[0060] Figure 2 This is an exemplary schematic diagram of generating real-time control instructions according to some embodiments of this specification.

[0061] In some embodiments, the current state 210 includes the holding force 211 and the holding posture 212 of the device carrier, and the state recognition component includes a pressure sensor, which is configured to identify the holding force 211 and the holding posture 212. The processor can generate real-time control instructions 220 based on the holding force 211 and the holding posture 212 to control the heartbeat simulation component 230 to adjust the simulated heartbeat 250, and / or control the audio control component 240 to adjust the audio playback 260.

[0062] Holding force refers to the strength with which the device carrier is held. Holding force can be expressed as a numerical value. The larger the numerical value, the greater the holding force.

[0063] In some embodiments, the processor can determine the user's grip strength using a state recognition component. The state recognition component can include a pressure sensor (e.g., a strain gauge pressure sensor, a capacitive pressure sensor, etc.). For example, the processor can determine the user's grip strength based on the pressure applied to the pressure sensor in the device carrier when the user holds the device carrier.

[0064] The holding posture refers to the way a user holds the device carrier. For example, holding postures can include horizontal holding, vertical holding, etc. Another example is the holding posture, which can also include the holding angle (e.g., the angle between the centerline of the device carrier and the horizontal and / or vertical directions).

[0065] In some embodiments, the processor can determine the user's holding posture through the state recognition component. For example, the processor can determine multiple pressures at different positions on the surface of the device carrier based on multiple pressure sensors in the device carrier, and determine the holding range and holding force of the user holding the device carrier based on the multiple pressures, and determine the user's holding posture by querying the first preset table based on the holding range and holding force. The holding range refers to the range in which the user holds the device carrier. In some embodiments, the processor can determine the part of the device carrier that is under pressure through the pressure sensor on the device carrier, and determine the holding range based on the part of the device carrier that is under pressure. The first preset table may include the relationship between the holding range, holding force and holding posture. The first preset table can be preset by a technician based on experience.

[0066] Real-time control instructions refer to instructions for real-time control of the smart soothing device, for example, real-time control of at least one of a heartbeat simulation component and an audio control component.

[0067] In some embodiments, the real-time control instruction may include real-time heartbeat parameters and real-time playback parameters. The real-time heartbeat parameters are parameters used to control the heartbeat simulation component to generate simulated heartbeats in real time. The real-time playback parameters are parameters used to control the audio control component to play audio in real time.

[0068] In some embodiments, the real-time heartbeat parameter and the real-time playback parameter are related to the holding posture and holding force. For example, when the holding posture is horizontal, the audio type in the real-time playback parameter tends to be soothing, the playback speed can be slower, and the volume can be lower. When the holding posture is vertical, the intensity of the simulated heartbeat in the real-time heartbeat parameter can be appropriately increased. The greater the holding force, the more lively the audio type in the real-time playback parameter tends to be, the faster the playback speed, and the stronger the intensity of the simulated heartbeat in the real-time heartbeat parameter.

[0069] In some embodiments, the real-time playback parameters are related to the change in the holding force. For example, the greater the change in the holding force, the lighter the audio type in the real-time playback parameters and the faster the speed.

[0070] In some embodiments, the processor can generate real-time control instructions based on the holding force and holding posture according to a preset correspondence table. The aforementioned correspondence table may include at least one set of correspondences between reference holding force, reference holding posture and reference control instructions, which can be preset based on experience. For example, when the reference holding posture is horizontal holding and the reference holding force is relatively small, the corresponding reference control instruction may be "the audio control component plays audio at a low volume and slow speed according to the real-time playback parameter of soothing music, and the heartbeat simulation component generates a simulated heartbeat according to the real-time heartbeat parameter of medium force". It can be understood that the above examples are only used to illustrate the correspondence between holding force, holding posture and reference control instructions. In fact, other correspondences may also be included, which can be determined based on prior experience.

[0071] In some embodiments, the processor may query a correspondence table according to the holding force and the holding posture, determine a reference holding force and a reference holding posture for approaching, and determine a real-time control instruction based on the corresponding reference control instruction.

[0072] In some embodiments, the processor may send real-time control instructions to the heartbeat simulation component and / or the audio control component to control the heartbeat simulation component to adjust the simulated heartbeat, and / or control the audio control component to play audio.

[0073] In some embodiments, the processor may obtain user physical signs through physiological sensors; and control the audio control component to play audio according to the user physical signs, holding strength, and holding posture.

[0074] A physiological sensor refers to a device used to obtain a user's vital signs. In some embodiments, the physiological sensor may include but is not limited to at least one of a capacitive pulse sensor, an optical respiration sensor, and a body temperature sensor.

[0075] User vital signs refer to indicators that represent the user's physiological state. User vital signs may include but are not limited to at least one of respiratory rate, heart rate, body temperature, etc.

[0076] In some embodiments, the processor may obtain the user's heart rate through a capacitive pulse sensor, obtain the user's breathing frequency through an optical respiration sensor, and obtain the user's body temperature through a body temperature sensor.

[0077] In some embodiments, the processor can determine at least one candidate preset audio parameter based on the user's vital signs, grip strength, and grip posture by querying a second preset table. The processor can then determine a preset audio parameter based on the at least one candidate preset audio parameter, and control the audio control component to play audio based on the preset audio parameter. The second preset table includes the relationship between the user's vital signs, grip strength, grip posture, and audio parameters. Audio parameters refer to audio parameters that, during historical testing by technicians, can cause positive changes in the user's vital signs (e.g., returning the heart rate to a normal rate, returning the breathing rate to a normal frequency, etc.). In some embodiments, the second preset table can be pre-constructed by technicians based on historical data.

[0078] For example, the processor can construct a first target vector based on the user's current vital signs, grip strength, and grip posture, and construct a first sample vector based on historical vital signs, grip strength, and grip posture in a second preset table. The processor determines the similarity between the first target vector and the first sample vector, and identifies the audio parameter corresponding to at least one sample vector whose similarity exceeds a similarity threshold as a candidate preset audio parameter. The processor can iterate through each candidate preset audio parameter and determine the change in the user's vital signs (e.g., heart rate change) after the processor executes the candidate preset audio parameter. If the change in the user's vital signs after execution exceeds a preset threshold (e.g., heart rate change threshold), the currently executed candidate audio parameter is determined as the preset audio parameter, and the next candidate preset audio parameter is not iterated. The similarity threshold and preset threshold can be pre-set by a technician based on experience. The processor can determine the change in the user's vital signs based on the user's vital signs before and after the execution of the candidate preset audio parameter.

[0079] In some embodiments of this specification, user vital signs are obtained through physiological sensors, and audio playback is controlled based on holding strength and holding posture, which is conducive to achieving a personalized user experience, adjusting emotions based on actual conditions, improving user experience and making the service more considerate.

[0080] In some embodiments, the processor may generate a holding feature based on the user's holding strength, holding posture, and emotional characteristics.

[0081] Holding characteristics are data reflecting the user's current grip on the device carrier. For example, holding characteristics can be represented by a vector, where the elements of the vector correspond to the user's current grip strength, grip posture, and emotional characteristics.

[0082] Emotional features refer to features used to represent the user's emotions. For example, emotional features may include but are not limited to at least one of happiness, sadness, anger, anxiety, etc.

[0083] In some embodiments, the processor can obtain user emotional characteristics through various methods. For example, the processor can obtain the user's facial expressions through a camera and determine the user's emotional characteristics using a computer recognition algorithm (e.g., Haar features and AdaBoost classifier). Another example is that the processor can obtain the user's voice through a microphone and determine the user's voice characteristics using a deep learning algorithm, thereby determining the user's emotional characteristics.

[0084] For more information about holding strength and holding posture, please refer to the relevant description in the previous part of this manual.

[0085] In some embodiments, the processor may collect the heartbeat characteristics of the associated object within a preset time period, and a hug signature when the user hugs the associated object.

[0086] An associated object refers to an object with which the user has an emotional relationship. For example, an associated object may include the user's parents, partner, children, pets, etc. In some embodiments, the processor may determine the associated object by obtaining user input.

[0087] Heartbeat features are features that reflect the heartbeat status of the associated object. For example, heartbeat features may include the heartbeat frequency, heartbeat intensity, and related change patterns of the associated object over a period of time.

[0088] In some embodiments, the processor may obtain the heartbeat characteristics of the associated subject based on a pulse sensor.

[0089] In some embodiments, the processor may further learn and record the heartbeat characteristics of an associated object with whom the user has a close emotional connection when the associated object hugs the device carrier (or collects the heartbeat characteristics through a pulse sensor).

[0090] The preset duration refers to the length of time over which the associated subject's heartbeat characteristics are determined. In some embodiments, the preset duration is related to the length of time the user holds the device carrier. For example, the longer the average length of time the user holds the device carrier, the longer the preset duration.

[0091] In some embodiments, the processor may determine a preset duration based on the length of time the user holds the device carrier. For example, the processor may determine the average holding duration of multiple holding signatures based on holding signatures of multiple users with similar holding strength and holding posture to the associated object, and determine the preset duration based on the average holding duration. The longer the average holding duration, the longer the preset duration. In some embodiments, if the user's holding signature is similar to the holding strength and holding posture of the associated object, the heartbeat frequency of the associated object is more easily accepted by the user, and the heartbeat frequency of the associated object is simulated under the preset duration determined by the user's average holding duration, so that the soothing service can better meet the user's emotional needs.

[0092] A hug signature is data that records a user's hugging status. It can reflect the state of a user hugging related users under different emotional characteristics.

[0093] In some embodiments, the hug signature may be represented by a vector, and the elements in the vector may include the hug strength, hug posture, and associated emotions when the user hugs the associated object.

[0094] The aforementioned hugging strength, hugging posture, and associated emotions are similar to the holding strength, holding posture, and emotional characteristics mentioned above, respectively. The only difference is that the object the user is supporting or hugging is different. For more details, please refer to the previous descriptions of holding strength, holding posture, and emotional characteristics.

[0095] In some embodiments, the processor may determine a hug signature based on pre-collected hug data. This hug data may include the hug strength, hug posture, and associated emotions associated with a user's hug with an associated object. For example, the processor may use sensors to pre-collect hug postures and hug strength of a user hugging an associated object under different emotions, determine the data as a record, and generate a hug signature corresponding to the associated user based on the record.

[0096] It is understandable that the hug signatures of a user hugging an associated object under different emotions are different. Therefore, the processor can collect and determine multiple records, and build a hug signature database based on this, which is used to record multiple hug signatures of a user hugging an associated object under different emotions, and establish an association relationship between different hug signatures and the heartbeat characteristics of the corresponding associated objects.

[0097] In some embodiments, in response to the user's holding characteristics and the hug signature meeting a matching condition, the processor may control the heartbeat simulation component to generate a simulated heartbeat according to the heartbeat characteristics corresponding to the hug signature.

[0098] The matching condition determines whether the holding feature matches the hug signature. In some embodiments, the matching condition may include the similarity between the holding feature and the hug signature being greater than a preset threshold. This similarity can be represented by the vector distance between the holding feature and the hug signature; the smaller the vector distance, the higher the similarity. The preset threshold can be determined based on prior experience.

[0099] In some embodiments, when a user holds a device carrier, the processor can identify the user's holding strength, holding posture, and emotional characteristics, and generate a holding feature, and match the holding feature with multiple hug signatures in the hug signature database. In response to the presence of a hug signature that matches the holding feature, the heartbeat feature associated with the hug signature is determined as the target heartbeat feature. In response to the presence of multiple hug signatures that match the holding feature, the processor can select one of them as the target hug signature according to a preset rule, and determine the heartbeat feature associated with the target hug signature as the target heartbeat feature. The preset rule can be random selection, selection of the hug signature with the highest historical frequency, etc., and can also be set based on user needs.

[0100] In some embodiments, the processor may control the heartbeat simulation component to generate a simulated heartbeat according to target heartbeat characteristics.

[0101] In some embodiments, the processor may further identify an associated object input by the user, control a heartbeat simulation component in the device carrier, and generate a simulated heartbeat according to the heartbeat characteristics of the associated object.

[0102] In some embodiments of the present specification, a holding feature is generated based on the user's holding strength, holding posture and emotional characteristics, and matched with a hug signature. Based on the result of the match between the two, the heartbeat simulation component is controlled to generate a simulated heartbeat according to the heartbeat feature corresponding to the hug signature. This can provide the user with natural comfort in an imperceptible state, meet the user's personalized emotional needs, and improve the intelligence and adaptability of the system.

[0103] In some embodiments of the present specification, real-time control instructions are generated based on holding strength and holding posture to control the heartbeat simulation component and / or audio control component, which can accurately identify user feedback and user vital signs, and then dynamically adjust the system's soothing mode to improve the level of intelligence.

[0104] In some embodiments, the processor can also determine multiple candidate control instructions, input the user's current physical signs, emotional characteristics, time information and candidate control instructions into the effect analysis model to determine the predicted soothing effect of the candidate control instructions in the current situation, and determine the candidate control instructions that meet the preset conditions as real-time control instructions.

[0105] For more information about candidate control instructions, effect analysis models, and pre-conditions, see Figure 4 Related description in .

[0106] Figure 3 This is a schematic diagram of determining playback parameters according to some embodiments of this specification.

[0107] In some embodiments, the smart soothing device may further include a facial recognition component. In some embodiments, the facial recognition component may collect facial features of the user.

[0108] Facial recognition components refer to devices that collect user facial features in real time, such as cameras.

[0109] In some embodiments, the facial recognition component may be disposed on a device carrier.

[0110] In some embodiments, the facial recognition component can be installed in a location other than the device carrier (e.g., a wall, bedside, or stand) and connected to the device via wired or wireless communication methods, including but not limited to Bluetooth, Wi-Fi, and serial bus.

[0111] In some embodiments, the facial recognition component can directly identify the user's facial features. For example, the facial recognition component captures the user's facial image and locally extracts and vectorizes key feature points (such as the distance between the eyes, the outline of the bridge of the nose, and the jawline) to obtain facial features.

[0112] In some embodiments, the facial recognition component captures a user's facial image and transmits the user's facial image data to a processor via wired or wireless means. The processor performs image analysis on the user's facial image and generates facial features using algorithms such as liveness detection and illumination compensation.

[0113] In some embodiments, the processor may generate the user's emotional features 320 based on the holding strength 211 and the holding posture 212 in combination with the user's facial features 310 .

[0114] Facial features refer to the specific expressions or states of a person's face expressed through muscle movements, such as frowning, laughing, crying, etc.

[0115] In some embodiments, different facial features can be represented by codes. The codes can be numbers or letters. For example, 1 represents laughing, and 2 represents crying. For another example, a represents laughing, and b represents crying.

[0116] Emotional features refer to features that reflect the user's inner emotional state, such as sadness, happiness, and calmness.

[0117] In some embodiments, the processor may generate the user's emotional characteristics in a variety of ways based on the holding strength and holding posture in combination with the user's facial features.

[0118] In some embodiments, the processor can construct a target feature vector based on the user's grip strength, grip posture, and facial features. There are various ways to construct the target feature vector, including using methods such as TF-IDF (Term Frequency-Inverse Document Frequency), One-Hot, and Word2Vec.

[0119] In some embodiments, the processor may build a sentiment database based on historical data.

[0120] The emotion database may include multiple reference vectors and corresponding reference emotion features. Each reference vector can be constructed based on historical holding force, historical holding posture, and historical facial features. Reference vectors are constructed in a similar manner to target feature vectors. For each holding force, holding posture, and facial feature in the historical data, corresponding historical emotion features are determined and used as reference emotion features.

[0121] In some embodiments, the processor may determine the emotional signature based on the similarity between the target feature vector and multiple reference vectors in the emotion database. For example, a reference vector whose similarity to the target feature vector satisfies a preset similarity condition is used as the target vector, and the emotional signature corresponding to the target vector is used as the final emotional signature. The preset similarity condition can be set according to the circumstances. For example, the highest similarity can be used. The similarity can be determined based on the distance between vectors, such as Euclidean distance, cosine distance, Mahalanobis distance, Chebyshev distance, and / or Manhattan distance.

[0122] In some embodiments, the processor may generate an emotion signature through a recognition model based on holding strength, holding posture, and facial features.

[0123] A recognition model refers to a model used to determine emotion characteristics. In some embodiments, the recognition model is a machine learning model, such as a neural network (NN) model.

[0124] In some embodiments, the input of the recognition model includes the user's holding strength, holding posture and facial features at at least one time point, and the output includes emotional features. For more information about holding strength and holding posture, see Figure 2 and its related descriptions.

[0125] In some embodiments, the processor may train the recognition model based on the first sample data set.

[0126] The first sample data set includes a first training sample and a corresponding first label.

[0127] In some embodiments, the first training sample and the corresponding first label may be obtained based on historical usage data.

[0128] In some embodiments, the first training sample includes a sample holding strength, a sample holding posture, and a sample facial feature. The first label includes a sample emotion feature.

[0129] In some implementations, the first label can be determined based on manual annotation.

[0130] In some embodiments, the recognition model can be trained based on a large number of first training samples with a first label. The processor can input the plurality of first training samples with the first label into the initial recognition model, construct a loss function based on the first label and the result of the initial recognition model, and iteratively update the initial recognition model based on the loss function. Model training is completed when an end condition is met, resulting in a trained recognition model. The end condition may include convergence of the loss function, reaching a threshold number of iterations, etc.

[0131] In some embodiments, the emotion feature further includes an emotion score of the user, and the output of the recognition model includes the emotion score.

[0132] Emotional score refers to a numerical indicator that quantifies the user's emotional state.

[0133] In some embodiments, the sentiment score can be represented by a numerical value. For example, the sentiment score can be represented by a value in the interval [-1, 1], where positive values represent positive emotions (e.g., +0.8 represents high happiness), negative values reflect negative emotions (e.g., -0.5 represents moderate depression), and zero corresponds to a neutral state.

[0134] In some embodiments, the first label may further include a sample emotion feature and a sample emotion score, wherein the sample emotion feature and the sample emotion score may be determined by manual annotation.

[0135] In some embodiments of this specification, combining holding strength, holding posture and facial features to generate emotional features using a recognition model can improve the accuracy and robustness of emotion recognition, reduce misjudgments, and have good adaptability and generalization capabilities, making it suitable for different users and diverse scenarios.

[0136] In some embodiments, the processor may determine the playback parameter 330 based on the emotion feature 320 in a variety of ways.

[0137] In some embodiments, the processor may determine the playback parameters based on the emotional characteristics using a first preset table. The first preset table may be used to characterize the correspondence between the user's emotional characteristics and the playback parameters. In some embodiments, the first preset table may be constructed based on historical data showing changes in the user's corresponding emotional characteristics after applying a certain preset playback parameter.

[0138] For example only, after applying a preset playback parameter in historical data, the user's mood improves, including the emotional state changing from negative to neutral (such as sadness decreasing to calmness), the positive emotion value increasing (such as happiness increasing from +0.3 to +0.7), or the negative emotion value decreasing (such as sadness decreasing from -0.6 to -0.2). This preset parameter is used as the playback parameter corresponding to the improved mood.

[0139] In some embodiments, the processor may also dynamically adjust playback parameters based on changes in the user's emotion score.

[0140] In some embodiments, the processor may obtain user emotion scores at multiple consecutive time points, analyze the changing characteristics of the user emotion scores during the time period, and dynamically adjust the playback parameters based on the changing characteristics. The changing characteristics of the emotion scores may include the direction of change, the rate of change, etc.

[0141] The direction of change refers to the changing trend of the user's emotional state. The direction of change can be determined based on the emotion scores at multiple time points. For example, if the emotion score at the current time point is higher than the emotion score at the previous time point, the direction of change is positive. For another example, if the emotion score at the current time point is lower than the emotion score at the previous time point, the direction of change is negative.

[0142] The rate of change refers to the magnitude of the change in sentiment score per unit time. For example, rate of change = (current score - previous score) / time interval.

[0143] For example only, when the user's emotion score change rate is zero (no change in emotion) or the change direction is negative and the change rate is gradually increasing (emotions deteriorate and the deterioration trend continues to intensify), the processor adjusts the audio playback type in the playback parameters; when the change direction is positive / negative and the change rate is gradually decreasing, that is, the soothing effect is attenuated, the processor can adjust the playback speed in the playback parameters, and the adjustment range of the playback speed is positively correlated with the change range of the emotion score; in other cases, the playback parameters remain unchanged.

[0144] In some embodiments of this specification, user emotional characteristics are generated based on holding strength, holding posture and facial features, which significantly improves the accuracy of emotion recognition; at the same time, the use of non-contact facial recognition reduces interference to the user and improves usage comfort; in addition, based on the generated emotional characteristics, the device can dynamically adjust the playback parameters to achieve a rapid response to the user's emotions, thereby enhancing the optimization ability of the soothing effect.

[0145] Figure 4 This is an exemplary schematic diagram of determining control instructions according to some embodiments of this specification.

[0146] In some embodiments, as Figure 4 As shown, the processor can also generate a candidate control instruction 410, which includes at least one corresponding control parameter of the heartbeat simulation component and the audio control component; determine the predicted soothing effect 440 of the candidate control instruction 410 based on the user's steady-state physical signs 420 and emotional baseline 430; in response to the predicted soothing effect 440 meeting the preset condition 450, determine the candidate control instruction 410 as the target control instruction 460.

[0147] A target control instruction is an instruction used to control the intelligent soothing device to achieve a soothing effect. The target control instruction may include a pre-set control instruction. In some embodiments, the processor may determine a candidate control instruction whose soothing effect meets an effect threshold as the target control instruction. When the device carrier enters the use state, the processor may execute the target control instruction.

[0148] Candidate control instructions refer to instructions that may achieve a soothing effect after being used to control the operation of the intelligent soothing device.

[0149] In some embodiments, the processor may generate multiple sets of candidate control instructions based on pre-set control parameters. For example, the processor may generate multiple sets of candidate control instructions by permuting and combining different control parameters based on pre-set control parameters corresponding to different components.

[0150] Control parameters are parameters that control the operation of different components in the smart soothing device. Control parameters can include playback parameters corresponding to the audio control component and heartbeat parameters corresponding to the heartbeat simulation component.

[0151] In some embodiments, the control parameters may further include lighting parameters corresponding to the lighting components.

[0152] In some embodiments, the processor can directly obtain the playback parameters, lighting parameters, and heartbeat parameters preset by the technician through the storage device.

[0153] Steady-state vital signs refer to data that reflects the average historical vital signs of the user.

[0154] In some embodiments, the processor may obtain steady-state vital signs of the user through physiological sensors when the user is in a calm state.

[0155] The sentiment baseline refers to data that reflects the long-term average level of user sentiment.

[0156] In some embodiments, the processor can identify the user's emotions through a computer recognition algorithm when the user is in a calm state, and extract normal emotional features as an emotional baseline based on the identified emotions.

[0157] The predicted soothing effect refers to the predicted physical and emotional state of the user after soothing. The predicted soothing effect can be expressed numerically. A positive value indicates that the candidate control instruction has a positive effect. A larger value indicates that the candidate control instruction is more effective. A negative value indicates that the candidate control instruction has no positive effect.

[0158] In some embodiments, the processor may determine a predicted soothing effect of the candidate control instruction based on the user's steady-state physical signs and emotional baseline.

[0159] For example, the processor can obtain the steady-state physical signs and emotional baseline of the current user, and determine the degree of match between each set of candidate control instructions and the steady-state physical signs and emotional baseline, and use the degree of match as a prediction of the soothing effect. Among them, the processor can obtain the degree of change of the user's emotions after executing a set of candidate control instructions based on historical usage data, with positive changes recorded as positive values and negative changes recorded as negative values (for example, the degree of change of the user's emotions from sadness to happiness is 2, and the degree of change of the user's emotions from calm to sadness is -1). The degree of change of the user's emotions is the degree of match. Historical usage data can also include the degree of change of the user's emotional characteristics before and after being soothed. For more information on how to determine the degree of match, please refer to Figure 3 Related description.

[0160] In some embodiments, the processor may also determine the predicted soothing effect of the candidate control instructions through an effect analysis model based on the user's steady-state physical signs, emotional baseline, time information, and the candidate control instructions.

[0161] The effect analysis model refers to a model used to determine the predicted soothing effect of a candidate control instruction. In some embodiments, the effect analysis model can be a machine learning model, such as a convolutional neural network (CNN).

[0162] In some embodiments, the input of the effect analysis model may include the user's steady-state physical signs, emotional baseline, time information, and candidate control instructions, and the output may include the predicted soothing effect of the candidate control instructions.

[0163] In some embodiments, the emotional features output by the recognition model can be used as input to an effect analysis model. The effect analysis model can be trained using the emotional features output by the recognition model and a large number of training samples with training labels. A set of training samples can include multiple sample user vital signs, sample emotional features, sample time information, and sample candidate control instructions. The training label corresponding to a set of training samples is the ventilation time of the sample sub-area to be inspected.

[0164] Training samples can be determined based on historical data. This historical data includes historical user physical characteristics, historical emotional characteristics, historical time information, and historical candidate control instructions. For each training sample, the processor can search the historical data and use the average change in the user's emotional characteristics after applying a sample candidate control instruction in the historical usage data as the training label.

[0165] In some embodiments, the processor can perform multiple rounds of iterative joint training on the initial effect analysis model and the initial recognition model based on multiple groups of training samples with training labels, and terminate the training when the iteration conditions are met, thereby obtaining a trained effect analysis model and recognition model. A round of iterative training includes: inputting a group of training samples with training labels into the initial recognition model, and inputting the emotional features output by the initial recognition model and other training samples with training labels into the initial effect analysis model, determining the loss function value through the training labels and the output results of the initial effect analysis model, and iteratively updating the parameters of the initial effect analysis model and the initial recognition model based on the loss function value. The iteration method may include gradient descent method, etc. The iteration conditions may be that the loss function converges, the number of iterations reaches a preset number threshold, the loss function value is less than a preset function value threshold, etc.

[0166] In some embodiments of the present specification, determining the predicted soothing effect of a candidate control instruction through an effect analysis model is beneficial to utilizing the learning ability of a machine learning model to accurately predict the soothing effect, thereby ensuring the soothing effect of the candidate control instruction.

[0167] In some embodiments, in response to the predicted soothing effect of the candidate control instruction meeting a preset condition, the processor may determine the candidate control instruction as the target control instruction. The preset condition may include that the value of the predicted soothing effect is a positive number, that is, the candidate control instruction can have a positive effect.

[0168] In some embodiments of the present specification, candidate control instructions are generated, predicted soothing effects are determined, and the candidate control instructions are determined as target control instructions based on the predicted soothing effects. This is beneficial for reasonably predicting the soothing effects of the candidate control instructions, and then determining target control instructions that meet user needs, thereby improving the application effect of the soothing system.

[0169] In some embodiments, the processor can obtain the user's laughter data through a sound sensor; determine the actual soothing effect corresponding to the target control instruction based on the user's laughter data, heart rate changes, and breathing rate changes; and adjust the target control instruction based on the actual soothing effect.

[0170] The actual effect of the target control instruction may not necessarily meet expectations. The processor can determine whether the target control instruction needs to be adjusted based on the actual soothing effect obtained after the target control instruction is executed.

[0171] The sound sensor is a device for acquiring laughter data.

[0172] Laughter data refers to data related to the user's laughter after being soothed. For example, the laughter data may include the volume of the laughter, the frequency of the laughter, etc.

[0173] In some embodiments, the processor may obtain laughter data via a sound sensor.

[0174] Heart rate variability refers to the change in the user's heart rate after soothing.

[0175] In some embodiments, the processor may obtain the user's heart rate conditions before and after soothing through a physiological sensor, and determine the user's heart rate change based on the user's heart rate conditions before and after soothing.

[0176] Respiratory rate change refers to the change in the user's respiratory rate after soothing.

[0177] In some embodiments, the processor may obtain the user's breathing conditions before and after soothing through a physiological sensor, and determine the change in the user's breathing frequency based on the user's breathing conditions before and after soothing.

[0178] The actual soothing effect refers to the actual user's physical signs and / or emotions after the user is soothed.

[0179] In some embodiments, the processor may determine the actual soothing effect based on laughter data, heart rate changes, breathing rate changes, and predicted soothing effects.

[0180] For example, when the laughter data, heart rate changes, and respiratory rate changes show a positive trend (i.e., the user's laughter changes from no to no, or maintains a positive trend, while the user's heart rate changes and respiratory rate changes gradually decrease to a positive trend), the actual soothing effect can be determined based on the predicted soothing effect and the positive change amplitude (e.g., the actual soothing effect can be the product of the predicted soothing effect, the positive change amplitude, and 1). When the laughter data, heart rate changes, and respiratory rate changes show a negative trend (i.e., the user's laughter changes from no to no, while the user's heart rate changes and respiratory rate changes gradually increase to a negative trend), the actual soothing effect can be determined based on the predicted soothing effect and the negative change amplitude (e.g., the actual soothing effect can be the product of the predicted soothing effect, the negative change amplitude, and 1).

[0181] The positive change amplitude can be represented by a positive value. The greater the positive change in the user's laughter, heart rate, or breathing rate, the larger the value. For example, if the laughter starts from zero, the positive change amplitude is 1. If the laughter is maintained, the positive change amplitude is 0.5. The positive change amplitude can also be the decrease in the user's heart rate and breathing rate. The negative change amplitude can be represented by a negative value. The greater the positive change in the user's laughter, heart rate, or breathing rate, the smaller the value. For example, if the laughter stops, the negative change amplitude is -1, and if the laughter decreases, the negative change amplitude is -0.5. The negative change amplitude can also be the negative value of the increase in the user's heart rate and breathing rate.

[0182] In some embodiments, the processor may adjust the target control instruction in response to a negative change in the actual soothing effect. For example, if the actual soothing effect gradually decreases or the actual soothing effect value is negative, the processor may re-determine as the target control instruction a candidate control instruction among multiple candidate control instructions whose soothing effects meet the effect threshold, and otherwise keep the target control instruction unchanged.

[0183] In some embodiments of the present specification, the actual soothing effect corresponding to the target control instruction is determined based on the user's laughter data, heart rate changes, and breathing rate changes; and then the target control instruction is adjusted, which is conducive to dynamically adjusting the target control instruction, realizing personalized and dynamically adjusted soothing strategies, and improving user experience.

[0184] While the basic concepts have been described above, it will be apparent to those skilled in the art that the detailed disclosure is merely illustrative and does not limit this specification. Although not explicitly stated herein, various modifications, improvements, and revisions to this specification may be made by those skilled in the art. Such modifications, improvements, and revisions are suggested in this specification and remain within the spirit and scope of the exemplary embodiments of this specification.

[0185] This specification also uses specific terms to describe the embodiments of this specification. For example, "one embodiment," "an embodiment," and / or "some embodiments" refer to a feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "one embodiment," "an embodiment," or "an alternative embodiment" two or more times in different locations in this specification do not necessarily refer to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of this specification may be appropriately combined.

[0186] In addition, unless expressly stated in the claims, the order of the processing elements and sequences, the use of alphanumeric characters, or the use of other names described in this specification are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some of the invention embodiments currently considered useful through various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the spirit and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0187] Similarly, it should be noted that, in order to simplify the presentation of this specification and thus facilitate understanding of one or more embodiments of the invention, the foregoing descriptions of the embodiments of this specification sometimes combine multiple features into a single embodiment, figure, or description thereof. However, this disclosure method does not imply that the subject matter of this specification requires more features than those recited in the claims. In fact, an embodiment may have fewer features than all of the features of a single disclosed embodiment.

[0188] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise stated, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the description and claims are approximate values, which may vary according to the required features of the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the settings of such numerical values are as accurate as possible within the feasible range.

[0189] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, and documents, cited in this specification is hereby incorporated by reference in its entirety. This excludes any application history documents that are inconsistent with or conflicting with the content of this specification, as well as any documents (currently or subsequently appended to this specification) that limit the broadest scope of the claims of this specification. It should be noted that if the descriptions, definitions, and / or terminology used in the accompanying materials are inconsistent or conflicting with the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0190] Finally, it should be understood that the embodiments described in this specification are intended only to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated in this specification.

Claims

1. An intelligent soothing device, characterized in that: The device comprises a device component and a device carrier, The device components include a state recognition component, a heartbeat simulation component, an audio control component and a processor; wherein, The state recognition component is configured to analyze sensor data related to the device carrier to determine the current state of the device carrier; The heartbeat simulation component is configured to generate a simulated heartbeat via a vibration motor; The audio control component is configured to play audio according to the playback parameters; The processor is configured to: Based on the current state of the device carrier, a control instruction is issued to control the heartbeat simulation component to generate the simulated heartbeat, and / or control the audio control component to play audio; the control instruction includes at least one of a real-time control instruction and a target control instruction.

2. The intelligent soothing device according to claim 1, characterized in that The current state includes a holding force and a holding posture of the device carrier, and the state recognition component includes a pressure sensor configured to recognize the holding force and the holding posture; The processor is configured to: A real-time control instruction is generated based on the holding force and the holding posture to control the heartbeat simulation component to adjust the simulated heartbeat, and / or control the audio control component to adjust the audio playback.

3. The intelligent soothing device according to claim 1, characterized in that The smart soothing device further includes a facial recognition component configured to collect facial features of a user; The processor is further configured to: generating an emotional feature of the user based on the holding strength and holding posture and in combination with the facial features of the user; The playback parameters are determined based on the emotional characteristics.

4. The intelligent soothing device according to claim 1, characterized in that The processor is further configured to: generating a candidate control instruction, wherein the candidate control instruction includes a control parameter corresponding to at least one of the heartbeat simulation component, the audio control component, and the light component; determining a predicted soothing effect of the candidate control instruction based on the user's steady-state physical signs and emotional baseline; In response to the predicted soothing effect meeting a preset condition, the candidate control instruction is determined as a target control instruction.

5. The intelligent soothing device according to claim 1, characterized in that: The intelligent soothing device further includes a lighting component configured to operate according to lighting parameters.

6. An intelligent soothing method, characterized in that: The method is performed based on a smart soothing device and includes: Analyzing the sensor data to determine a current state of a device carrier of the intelligent soothing device; Based on the current state of the device carrier, a control instruction is issued to control the heartbeat simulation component to generate the simulated heartbeat, and / or control the audio control component to play audio; the control instruction includes at least one of a real-time control instruction and a target control instruction.

7. The intelligent soothing method according to claim 6, characterized in that: The current state includes the holding strength and holding posture of the device carrier; the method further includes: A real-time control instruction is generated based on the holding force and the holding posture to control the heartbeat simulation component to adjust the simulated heartbeat, and / or control the audio control component to adjust the audio playback.

8. The intelligent soothing method according to claim 6, characterized in that: The method further comprises: generating an emotional feature of the user based on the holding strength and holding posture and in combination with the facial features of the user; The playback parameters are determined based on the emotional characteristics.

9. The intelligent soothing method according to claim 6, characterized in that: Determining the control instruction includes: generating a candidate control instruction, wherein the candidate control instruction includes a control parameter corresponding to at least one of the heartbeat simulation component, the audio control component, and the light component; determining a predicted soothing effect of the candidate control instruction based on the user's steady-state physical signs and emotional baseline; In response to the predicted soothing effect meeting a preset condition, the candidate control instruction is determined as a target control instruction.

10. A computer-readable storage medium storing computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the intelligent soothing method according to any one of claims 6 to 9.

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