Information processing method and apparatus, and electronic device and computer-readable storage medium

Abstract

An information processing method and apparatus, and an electronic device and a computer-readable storage medium. The information processing method comprises: acquiring emotional information of a target object, and a target scene in which the target object is located; on the basis of the emotional information, determining an emotional state of the target object; and on the basis of the emotional state and the target scene, providing assistance information to the target object. By means of the method provided in the embodiments of the present disclosure, provided assistance information can better match a scene in which a user is located, and can be tailored to the emotion of the user, such that by means of the assistance information, the emotion of the user is regulated and psychological support and intervention are provided to the user, thereby improving the comfort of the user in the scene and enhancing the user experience.

Description

Information processing methods, apparatuses, electronic devices and computer-readable storage media Technical Field

[0001] Embodiments of this disclosure relate to an information processing method, apparatus, electronic device, and computer-readable storage medium. Background Technology

[0002] With the development of artificial intelligence (AI) technology, significant progress has been made in its application in areas such as natural language processing and understanding. For example, AI technology can interact with users through dialogue to provide corresponding answers and suggestions. Summary of the Invention

[0003] At least one embodiment of this disclosure provides an information processing method, including: acquiring emotional information of a target object and a target scene in which the target object is located; determining the emotional state of the target object based on the emotional information; and providing assistance information to the target object based on the emotional state and the target scene.

[0004] For example, in at least one embodiment of the information processing method provided in this disclosure, providing assistance information to the target object based on the emotional state and the target scene includes: determining a virtual character based on the emotional state; determining the interactive action of the virtual character based on the emotional state and the target scene; and providing the target object with the virtual character that performs the interactive action.

[0005] For example, in the information processing method provided in at least one embodiment of this disclosure, determining a virtual character based on the emotional state includes: determining the virtual character based on the emotional state and the preference information of the target object.

[0006] For example, at least one embodiment of the information processing method provided in this disclosure further includes: in response to detecting a change in the emotional state of the target object, adjusting the interactive action based on the change in the emotional state so that the adjusted interactive action matches the changed emotional state.

[0007] For example, in the information processing method provided in at least one embodiment of this disclosure, the emotional information includes information from at least two modalities; determining the emotional state of the target object based on the emotional information includes: extracting features of the information of each of the at least two modalities to obtain emotional features corresponding to each modality; and processing the at least two emotional features corresponding to the at least two modalities using a machine learning model, and determining the emotional state of the target object based on the output of the machine learning model.

[0008] For example, in the information processing method provided in at least one embodiment of this disclosure, obtaining the target scene where the target object is located includes: determining the target scene where the target object is located based on at least one of the target object's location information, the target object's medical treatment status, and information obtained in response to the target object's input operation, wherein the target scene includes one of the following scenes: triage scene, scene of going to medical treatment location, medical treatment waiting scene, medical treatment scene, and post-medical treatment scene.

[0009] For example, at least one embodiment of the information processing method provided in this disclosure further includes: acquiring physiological data of the target object; determining intervention information based on the physiological data and the emotional state; and providing the intervention information so that the target object adjusts its health state based on the intervention information.

[0010] For example, at least one embodiment of the information processing method provided in this disclosure further includes: acquiring at least one of the target object's medical information and life data; determining intervention information for the target object based on the physiological data and the emotional state includes: determining the intervention information based on at least one of the medical information and the life data, the physiological data, and the emotional state.

[0011] For example, in the information processing method provided in at least one embodiment of this disclosure, determining intervention information based on the physiological data and the emotional state includes: processing the physiological data and the emotional state respectively using a self-attention mechanism to obtain physiological features and state features; processing the physiological features and the state features using a bidirectional attention mechanism to obtain fused features; and determining intervention information for the target object based on the fused features.

[0012] For example, in the information processing method provided in at least one embodiment of this disclosure, the step of providing assistance information to the target object based on the emotional state and the target scenario includes: in response to the emotional state indicating that the target object has an emotional abnormality, providing the target object with first prompt information that matches both the emotional state and the target scenario, so as to regulate the target object's emotions.

[0013] For example, in at least one embodiment of the information processing method provided in this disclosure, the scenario includes a triage scenario; the method further includes: in response to obtaining first conversation information provided by the target object in the triage scenario, determining symptom information included in the first conversation information; the step of providing assistance information to the target object based on the emotional state and the target scenario includes: in response to the target scenario being a triage scenario, providing recommendation information to the target object based on the emotional state and the symptom information, wherein the recommendation information includes a recommended destination.

[0014] For example, in the information processing method provided in at least one embodiment of this disclosure, providing recommendation information to the target object based on the emotional state and the symptom information includes: determining a target department for the target object based on the emotional state and the symptom information; and determining a recommended destination among multiple alternative destinations based on the emotional state and the target department, wherein the recommendation information further includes the target department.

[0015] For example, in the information processing method provided in at least one embodiment of this disclosure, providing recommendation information to the target object based on the emotional state and the symptom information further includes: determining a designated object among a plurality of candidate objects included in the target department based on the symptom information, wherein the recommendation information also includes the designated object.

[0016] For example, in at least one embodiment of the information processing method provided in this disclosure, the target scenario includes a scenario of going to a medical treatment location; the step of providing assistance information to the target object based on the emotional state and the scenario includes: in response to the target scenario being a scenario of going to a medical treatment location, obtaining the current location of the target object and the medical treatment location; determining a guidance path from the current location to the medical treatment location based on the emotional state; and providing the guidance path; wherein, the method further includes: during the process of the target object moving along the guidance path, adjusting the guidance path in response to changes in the emotional state.

[0017] For example, at least one embodiment of the information processing method provided in this disclosure further includes: acquiring physiological data of the target object; wherein, determining a guidance path from the current location to the medical treatment location based on the emotional state includes: determining a guidance path from the current location to the medical treatment location based on the physiological data and the emotional state; wherein, the method further includes: adjusting the guidance path in response to changes in the physiological data as the target object moves along the guidance path.

[0018] For example, at least one embodiment of the information processing method provided in this disclosure further includes: acquiring behavioral data of the target object; wherein, determining a guidance path from the current location to the medical treatment location based on the physiological data and the emotional state includes: determining a guidance path from the current location to the medical treatment location based on the behavioral data, the physiological data, and the emotional state; wherein, the method further includes: adjusting the guidance path in response to changes in the behavioral data as the target object moves along the guidance path.

[0019] For example, in the information processing method provided in at least one embodiment of this disclosure, the medical treatment location includes at least two locations; the method further includes: acquiring environmental information of each of the at least two locations; the step of determining a guidance path from the current location to the medical treatment location based on the emotional state includes: determining the arrival order of the at least two locations based on the environmental information; and determining a guidance path from the current location to the at least two locations based on the arrival order and the emotional state.

[0020] For example, at least one embodiment of the information processing method provided in this disclosure further includes: in response to detecting that the target object has moved to the target location, providing the target object with second prompting information to prompt the target object to perform a target activity at the medical treatment location.

[0021] For example, in at least one embodiment of the information processing method provided in this disclosure, the target scenario includes a waiting scenario for medical treatment; the step of providing assistance information to the target object based on the emotional state and the target scenario includes: in response to the target scenario being a waiting scenario for medical treatment and the emotional state indicating an emotional abnormality in the target object, providing real-time waiting information to the target object.

[0022] For example, in the information processing method provided in at least one embodiment of this disclosure, the step of providing assistance information to the target object based on the emotional state and the target scenario further includes: in response to obtaining second conversation information provided by the target object in the medical waiting scenario, extracting key information of the second conversation information; and providing report information to the target object based on the key information and the emotional state.

[0023] For example, at least one embodiment of the information processing method provided in this disclosure further includes: in response to the target scenario being a medical visit scenario, providing the report information to a designated object interacting with the target object.

[0024] For example, in the information processing method provided in at least one embodiment of this disclosure, the target scenario includes a medical visit scenario; the step of providing assistance information to the target object based on the emotional state and the target scenario includes: in response to the target scenario being a medical visit scenario and the emotional state indicating an emotional abnormality in the target object, providing third prompt information to a designated object interacting with the target object, so as to prompt the designated object to adjust the interaction method with the target object.

[0025] For example, in at least one embodiment of the information processing method provided in this disclosure, the step of providing assistance information to the target object based on the emotional state and the target scenario includes: in response to the target scenario being a medical visit scenario and detecting third conversation information provided by the target object and any one of the specified objects interacting with the target object, converting the three conversation information based on the emotional state to obtain first converted information; and providing the first converted information, wherein the first converted information includes information for interpreting the third conversation information.

[0026] For example, in the information processing method provided in at least one embodiment of this disclosure, the step of providing assistance information to the target object based on the emotional state and the target scenario further includes: in response to the target scenario being a post-medical visit scenario and obtaining reference information provided by a designated object interacting with the target object, converting the reference information based on the emotional state to obtain second converted information, wherein the second converted information includes information interpreting the reference information.

[0027] For example, at least one embodiment of the information processing method provided in this disclosure further includes: in response to obtaining target information to be converted provided by the target object, converting the target information to obtain third converted information; and providing the third converted information.

[0028] For example, at least one embodiment of the information processing method provided in this disclosure further includes: in the process of providing the assistance information to the target object, in response to detecting a change in the emotional state of the target object, adjusting the assistance information so that the adjusted assistance information matches the changed emotional state.

[0029] For example, at least one embodiment of the information processing method provided in this disclosure further includes: in response to detecting that the emotional state of the target object changes to a state indicating abnormal emotion, sending a third prompt message to an associated object associated with the target object to prompt the associated object to assist the target object.

[0030] At least one embodiment of this disclosure also provides an information processing apparatus, including: an information acquisition module configured to acquire emotional information of a target object and a target scene in which the target object is located; a state determination module configured to determine the emotional state of the target object based on the emotional information; and an information providing module configured to provide assistance information to the target object based on the emotional state and the target scene.

[0031] At least one embodiment of this disclosure also provides an electronic device, including: a processor; and a memory including one or more computer program instructions; wherein the one or more computer program instructions are executed by the processor to implement the information processing method provided in at least one embodiment of this disclosure.

[0032] At least one embodiment of this disclosure also provides a computer-readable storage medium for non-transitory storage of computer-readable instructions, wherein the information processing method provided in at least one embodiment of this disclosure is implemented when the computer-readable instructions are executed by a processor. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments will be briefly described below. Obviously, the drawings described below only relate to some embodiments of this disclosure, and are not intended to limit this disclosure.

[0034] Figure 1 schematically illustrates an application scenario of the information processing method provided by at least one embodiment of the present disclosure;

[0035] Figure 2 schematically illustrates a flowchart of an information processing method provided in at least one embodiment of the present disclosure;

[0036] Figure 3 schematically illustrates the principle of providing assistance information according to at least one embodiment of the present disclosure;

[0037] Figure 4 schematically illustrates the implementation principle of the information processing method provided in at least one embodiment of this disclosure;

[0038] Figure 5 schematically illustrates the principle of providing assistance information in a triage scenario;

[0039] Figure 6 schematically illustrates the principle of providing assistance information in the scenario of traveling to a medical location;

[0040] Figure 7 schematically illustrates the process of determining assistance information in a medical visit scenario;

[0041] Figure 8 schematically illustrates a structural block diagram of an intelligent medical escort system provided according to at least one embodiment of the present disclosure;

[0042] Figure 9 schematically illustrates a structural block diagram of an information processing apparatus provided according to at least one embodiment of the present disclosure;

[0043] Figure 10 schematically illustrates a structural block diagram of an electronic device provided in at least one embodiment of the present disclosure; and

[0044] Figure 11 schematically illustrates a computer-readable storage medium provided in at least one embodiment of the present disclosure. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0046] Unless otherwise defined, the technical or scientific terms used in this disclosure shall have the ordinary meaning understood by one of ordinary skill in the art to which this disclosure pertains. The terms “first,” “second,” and similar terms used in this disclosure do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms “an,” “a,” or “the,” and similar terms do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms “including,” “comprising,” or “containing,” and similar terms mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. The terms “connected,” “linked,” or similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms “upper,” “lower,” “left,” and “right,” etc., are used only to indicate relative positional relationships, and these relative positional relationships may change accordingly when the absolute position of the described objects changes.

[0047] With the development of artificial intelligence (AI) technology, significant progress has been made in its application in areas such as natural language processing and understanding. For example, AI technology can interact with users through dialogue to provide corresponding answers and suggestions. In the process of a user seeking medical treatment, AI technology can be used to improve efficiency. However, when faced with physical discomfort or unfamiliar intelligent medical procedures, users often experience anxiety or emotional breakdowns. The answers and suggestions provided by AI technology are often rather rigid and general, resulting in a poor user experience.

[0048] To at least partially solve the above problems, embodiments of this disclosure provide an information processing method, including: acquiring emotional information of a target object and the target scene in which the target object is located; determining the emotional state of the target object based on the emotional information; and providing assistance information to the target object based on the emotional state and the target scene.

[0049] Some embodiments of this disclosure also provide information processing apparatus, electronic devices, and computer-readable storage media corresponding to the above-described information processing methods.

[0050] The information processing method provided in at least one embodiment of this disclosure can provide assistance information to users based on the analyzed emotional state and the user's situation. This makes the provided assistance information more suitable to the user's situation and adaptable to the user's emotions. The assistance information can then regulate the user's emotions, provide psychological support and intervention, thereby improving the user's comfort level and enhancing the user experience.

[0051] The embodiments and some examples of this disclosure will now be described in detail with reference to the accompanying drawings.

[0052] The application scenarios of the information processing method provided in the embodiments of this disclosure will be described below with reference to Figure 1.

[0053] Figure 1 schematically illustrates an application scenario of the information interaction method and information processing method provided in at least one embodiment of the present disclosure.

[0054] As shown in Figure 1, in the exemplary application scenario 100, there is a terminal device 101, a user of the terminal device 101 (e.g., user 102), and a location 103 (i.e., destination) that user 102 wants to go to.

[0055] For example, terminal device 101 can be a smartphone, tablet, laptop, desktop computer, wearable device, or smart appliance. Terminal device 101 can provide assistance information to user 102 during the process of user 102 determining location 103, moving to location 103, staying at location 103, and leaving location 103.

[0056] For example, terminal device 101 may integrate an image acquisition device to capture facial images of user 102, thereby determining user 102's emotional state based on the captured facial images. Terminal device 101 may also integrate location tracking and environmental information acquisition functions, and determine the user 102's location based on the data collected by these functions. Terminal device 101 may also provide assistance information to user 102 based on user 102's emotional state and the surrounding environment, thereby regulating user 102's emotions based on this assistance information.

[0057] For example, user 102 may also wear sensors for monitoring physiological signals. The monitored physiological signals can serve as reference information for determining the emotional state of user 102, thereby improving the accuracy of the determined emotional state. For example, the monitored physiological signals may include heart rate, brain waves, skin conductivity, etc., and this embodiment of the disclosure does not limit the scope of the data.

[0058] Location 103 can be any location, such as a hospital, office, school building, or examination room, or a public place that the user is unfamiliar with or unwilling to go to. This embodiment of the present disclosure does not limit this. Terminal device 101 can provide assistance information to user 102 in various scenarios, such as during the user's journey to location 103, after arriving at location 103, or after leaving location 103, in order to regulate the user's emotions.

[0059] It should be noted that the information processing method provided in at least one embodiment of this disclosure can be executed by the terminal device 101. The information processing apparatus provided in at least one embodiment of this disclosure can be disposed in the terminal device 101.

[0060] The implementation principle of the information processing method provided in at least one embodiment of this disclosure will be explained and described below with reference to Figures 2 to 8.

[0061] Figure 2 schematically illustrates a flowchart of an information processing method provided in at least one embodiment of the present disclosure.

[0062] As shown in Figure 2, the information processing method 200 of this embodiment may include steps S210 to S230. This information processing method 200 may be executed by, for example, the aforementioned terminal device.

[0063] Step S210: Obtain the emotional information of the target object and the target scene in which the target object is located.

[0064] Step S220: Determine the emotional state of the target object based on the emotional information.

[0065] Step S230: Provide assistance information to the target object based on the emotional state and target scenario.

[0066] For example, the target object can be the aforementioned user, and the acquired emotional information may include physiological signals detected by a wearable device worn by the target object. For example, physiological signals may include brain waves, heart rate, skin conductivity, etc.

[0067] For example, brainwave activity can be recorded using an electroencephalogram (EEG) headband, specifically recording different frequency bands of brainwaves such as alpha waves, beta waves, theta waves, and / or delta waves. Based on these brainwaves, patterns of brain activity associated with different emotional states can be identified. For instance, an increase in alpha waves is usually associated with relaxation, while an increase in beta waves may be associated with anxiety or stress.

[0068] For example, heart rate monitors can detect changes in heart rate intervals (HRV). HRV is an important indicator of cardiac rhythm variability. A higher HRV generally indicates better adaptability and lower stress levels, while a lower HRV may indicate high stress or anxiety. Heart rate monitors can be implemented using techniques such as photoplethysmography (PEP) or electrocardiography (ECG).

[0069] For example, changes in skin conductivity can be measured using a Galvanic Skin Response (GSR) sensor. For instance, when an individual is in a state of stress, anxiety, or excitement, activity of the sympathetic nervous system leads to increased sweat gland secretion, thereby increasing skin conductivity. GSR sensors can capture these subtle changes in conductivity, providing valuable information about emotional states.

[0070] For example, after acquiring a user's physiological signals, signal processing algorithms can be used to convert these signals into emotional state indicators. The processing of physiological signals may include, for example, the following steps: preprocessing, feature extraction, time-frequency analysis, and emotional state assessment.

[0071] For example, preprocessing steps can be used to preprocess the acquired physiological signals, such as denoising, baseline drift correction, and artifact removal, to improve signal quality and reliability. For instance, baseline drift can cause low-frequency curves to superimpose onto the original signal, resulting in slow, slight fluctuations. Correction can reduce this fluctuation, preventing the signal accuracy from being affected by baseline drift. Artifacts refer to unrealistic or unnecessary parts of an image, which may be caused by various factors such as imaging equipment, imaging environment, and improper data processing. Removing artifacts can improve the visual appeal and usability of the image.

[0072] For example, the feature extraction step can extract meaningful features from the preprocessed signal. For instance, features such as power spectral density (PSD) and frequency band energy ratio can be extracted from EEG; time domain features (such as the standard deviation of the time interval between two consecutive R-wave peaks), frequency domain features (such as the low-frequency / high-frequency ratio), and / or nonlinear features (such as the shape index of a Poincare scatter plot) can be extracted from HRV signals; and peak frequency and average conductivity can be extracted from GSR signals.

[0073] For example, the time-frequency analysis step can process dynamically changing physiological signals to analyze signal characteristics simultaneously in the time and frequency domains, capturing instantaneous changes in emotional state. The video analysis techniques used in this step may include, for example, short-time Fourier transform, wavelet transform, etc., and the embodiments disclosed herein are not limited to these.

[0074] For example, machine learning models can be used to process the data obtained from feature extraction and time-frequency analysis, such as performing classification and regression analysis, thereby converting physiological signals into emotional state indicators. Machine learning models may include support vector machines, random forests, or convolutional neural networks. The converted emotional state indicators may include, for example, stress levels, anxiety levels, and levels of pleasure. The machine learning model learns from the training dataset and can identify physiological signals under different emotional states. For example, emotional state indicators can be used as a definite emotional state, or an emotional state can be determined based on multiple converted emotional state indicators.

[0075] In one embodiment, the emotional information may include information from at least two modalities. For example, it may include the aforementioned at least two physiological signals, or, in addition to the aforementioned physiological signals, it may include voice signals and / or facial images. Voice signals and facial images may be, for example, voice signals and facial images of a user acquired by a terminal device. For instance, this embodiment may extract features from the information of each modality to obtain emotional features corresponding to each modality. After obtaining the emotional features, a machine learning model may be used, for example, to process the at least two emotional features corresponding to the at least two modalities, and the emotional state of the target object may be determined based on the output of the machine learning model. This embodiment, by determining the emotional state based on information from at least two modalities, integrates signal processing techniques and machine learning algorithms, thereby significantly improving the accuracy and reliability of the obtained emotional state assessment.

[0076] For example, the principle of extracting features from physiological signals is similar to that described above and will not be repeated here. For instance, for speech signals, statistical modeling can be used to extract at least one of the following features: prosodic features, energy features, speech quality, and spectral features. Statistical modeling methods can include Gaussian mixture models, hidden Markov models, etc. For speech signals, deep learning-based methods can also be used to extract features. For example, a convolutional neural network encoder can first encode the speech signal into a feature vector, and then significant distinguishing feature analysis can be used to extract emotion-related components from the feature vector, thereby obtaining emotional features. For example, for facial images, local binary pattern recognition, principal component analysis, or deep learning models can be used to extract emotional features. Deep learning models can be, for example, convolutional neural networks or recurrent neural networks. It is understood that the above principles for extracting emotional features are merely examples to facilitate understanding of this disclosure, and the embodiments of this disclosure are not limited thereto.

[0077] For example, the sentiment features of at least two modalities can be concatenated and input into a machine learning model, which then outputs an emotion classification result indicating the sentiment state. For example, sentiment states can include calm, anxious, sad, angry, excited, etc. The machine learning model can include, for example, convolutional neural networks and fully connected networks, or attention networks and fully connected networks. Other networks besides the fully connected network are used to fuse at least two sentiment features corresponding to at least two modalities. The fully connected network is used to perform classification and regression analysis on the features output by the other networks, thereby obtaining the sentiment classification result indicating the sentiment state. For example, the sentiment state index determined by the fully connected network through classification and regression analysis can be the aforementioned sentiment state index, and the sentiment state can be determined based on the sentiment state index.

[0078] For example, the values ​​of emotional state indicators are mapped to emotional states; based on the determined values ​​of emotional state indicators, emotional states can be determined.

[0079] For example, the scenario in which the target object is located can be determined based on at least one of the target object's location information, the information input by the target object, and the target object's medical treatment status. For instance, if the target object's location is a hospital, the scenario can be determined as a medical treatment scenario; if the target object's location is an office building, the scenario can be determined as an office scenario; and if the target object's location is a shopping mall, the scenario can be determined as an offline shopping scenario. For example, if the target object's input is a request for hospital recommendations, the scenario can be determined as a patient guidance scenario; if the target object's input is a request for item recommendations, the scenario can be determined as an online shopping scenario; and if the target object's input is about how to improve work efficiency, the scenario can be determined as an office scenario. For example, based on the target object's medical treatment status, the scenario in which the target object is located can be determined to include pre-medical treatment scenarios, during-medical treatment scenarios, and post-medical treatment scenarios.

[0080] For example, the target scenario can include one of the following: a triage scenario, a scenario of heading to a medical location, a waiting scenario, a medical visit scenario, or a post-visit scenario. For instance, if the target person enters symptom information and there is no registration information for the target person, the target scenario can be determined as a triage scenario. For instance, if the target person has registration information and their location changes in real time as they approach the hospital, the target scenario can be determined as a scenario of heading to a medical location. Alternatively, if the target person moves within the hospital, the target scenario can be determined as a scenario of heading to a medical location, where the medical location can include the hospital's outpatient room, examination room, etc. For instance, if the target person is located within the hospital and their registration information indicates they have not yet received treatment, the target scenario can be determined as a waiting scenario. For instance, if the target person is located in an examination room or other indoor space, the target scenario can be determined as a medical visit scenario. For instance, if the target person's registration information indicates they have received treatment, but they are not located in an examination room or other indoor space, the target scenario can be determined as a post-visit scenario. It is understood that the above-described target scenarios and methods for determining target scenarios are merely examples to aid in understanding this disclosure, and the embodiments of this disclosure do not limit them.

[0081] For example, after acquiring the target scenario and determining the emotional state, assistance information can be provided to the target object based on the target scenario and emotional state. For instance, multiple assistance information sets can be pre-defined, each corresponding to a different emotional state and a different target scenario. This embodiment can filter out assistance information that matches both the acquired target scenario and the determined emotional state from these multiple sets of assistance information and provide it to the target object. For example, this assistance information can help regulate the target object's emotional state.

[0082] For example, within the same target scenario, the assistance information provided will differ depending on the target's emotional state. For instance, if the emotional state is anxiety-inducing, the assistance information might include information that helps alleviate anxiety. In a patient guidance scenario, if the emotional state is anxiety-inducing, the assistance information might include prompts such as "We can register on the registration platform; the hospital has professional doctors to help you alleviate your discomfort, please don't be anxious," while in a calm state, the assistance information might include prompts such as "We can register on the registration platform to provide you with a more accurate diagnosis." Similarly, even within the same emotional state, the assistance information provided will differ depending on the target's specific target scenario. For example, if the emotional state is anxiety, in the scenario of going to a medical appointment, the assistance information provided may include the prompt text "Don't worry, you are only XX kilometers away from the medical appointment, you will definitely make it in time"; in the scenario of waiting for the appointment, the assistance information provided may include the prompt text "You will be waiting X people before it is your turn, don't worry, you can listen to some music first"; in the scenario of the appointment, the assistance information provided may include the prompt text "The examination will be over soon, it will not cause you any discomfort, please don't be anxious"; in the scenario after the appointment, the assistance information provided may include the prompt text "Based on your medical results, it is certain that you will recover soon, remember that maintaining a good mindset is very important," etc. It is understood that the prompt text and information types included in the above assistance information are only examples to facilitate understanding of this disclosure. For example, assistance information may also be provided to the target object in the form of voice, etc., and the embodiments of this disclosure do not limit this.

[0083] For example, assistance information can also be used to guide the target user to perform operations corresponding to the target scenario. For instance, in a triage scenario, assistance information can guide the target user to input symptom information and perform the following operations: selecting a hospital, department, doctor, and registering. For instance, in a scenario of going to a medical appointment, assistance information can guide the target user to move to the appointment location. For instance, in a waiting scenario, assistance information can guide the target user to provide more detailed symptom information to improve the efficiency of subsequent medical visits; through this guidance, the target user can understand in advance the symptoms that the doctor is concerned about. For instance, in a medical appointment scenario, assistance information can guide the target user to undergo relevant examinations. In a post-medical appointment scenario, assistance information can guide the target user home, etc.

[0084] This embodiment of the disclosure analyzes the emotional information of the target object to obtain its emotional state, and combines the emotional state with the target object's target scenario to provide assistance information to the target object. This makes the provided assistance information more consistent with the user's scenario and can be adapted to the user's emotions. This assistance information can regulate the user's emotions, provide psychological support and intervention, thereby improving the user experience and the user's comfort in the scenario.

[0085] Figure 3 schematically illustrates the principle of providing assistance information according to at least one embodiment of the present disclosure.

[0086] In at least one embodiment of this disclosure, assistance information can be provided to the target in the form of a virtual character, thereby enhancing the appeal and effectiveness of the emotional support provided through the assistance information.

[0087] For example, the aforementioned steps of providing assistance information to the target object based on emotional state and target scenario may include: first determining the virtual character based on emotional state, then determining the interactive actions of the virtual character based on emotional state and target scenario, and finally providing the target object with the virtual character that performs the interactive actions.

[0088] For example, as mentioned earlier, the emotional state of a target can be determined in various ways. These include technologies such as speech analysis, facial expression recognition, and physiological signal monitoring, which can capture the target's emotional state in real time. Speech analysis can identify emotional states by analyzing the target's tone of voice, speech rate, and emotional keywords. Facial expression recognition can use a camera to capture the target's facial expressions (e.g., facial images) and then use a deep learning model to identify these expressions, thereby determining the emotional state. Physiological signal monitoring can use wearable devices to monitor the target's physiological signals in real time, such as heart rate and blood pressure, and further assist in emotion recognition based on these signals.

[0089] For example, a corresponding virtual companion character can be generated based on the identified emotional state. For example, a mapping relationship between emotional states and virtual character types can be pre-maintained; this mapping relationship can be set in response to user actions or can be a default setting. For example, when the target's emotional state is depressed, the determined virtual character can be a virtual pet. When the target's emotional state is anxious, the determined virtual character can be a virtual family member or virtual friend, etc. For example, the emotional state determines the virtual character's type, while the character's appearance can be a pre-set appearance. For example, it supports rendering the character's appearance based on user-uploaded images, or it can provide users with a material library, allowing users to design the character's appearance by selecting materials from the library, and the character's appearance corresponds to the character type. The embodiments of this disclosure do not limit this.

[0090] In at least one embodiment, the character's appearance may be, for example, approachable and fun, to attract the attention of the target audience.

[0091] In at least one embodiment, as shown in FIG3, the virtual character 303 can also be determined by combining the target object's preference information 302 based on the emotional state 301. The target object's preference information 302 can be determined based on the target object's selection of pre-provided tabs, or it can be determined based on the target object's browsing history, etc. Tabs may include, for example, "Anime," "Animal," "People," "Family," etc. For example, if it is determined from the browsing history that the target object likes to browse animal-related multimedia data when in a low mood, then the virtual character type can be determined to be animal type when the emotional state is low. By combining the target object's preference information to determine the virtual character, personalized assistance services and personalized emotional support can be provided to the user.

[0092] It should be noted that the types, scope of use, and usage scenarios of personal information involved in the embodiments of this disclosure have been informed to users and authorized by users before the implementation of the technical solutions of the embodiments of this disclosure, and the data involved in the embodiments of this disclosure all comply with the requirements of relevant laws, regulations and related provisions.

[0093] For example, the interactive action can be determined based on the emotional state and the target scene. For instance, the principle described above can be used to determine the prompt information 305 based on the emotional state 301 and the target scene 304. Then, the interactive action 306 of the virtual character can be determined to be either emitting voice information corresponding to the prompt information or performing a physical action corresponding to the prompt information. For example, if the prompt information is comforting, the physical action could include an outstretched arm to hug. Or, if the prompt information includes soothing music, the determined interactive action could include the virtual character humming the soothing music; depending on the actual needs, the interactive action could also include the virtual character dancing gracefully to the humming soothing music.

[0094] In at least one embodiment, when the target object's emotional state is low, the interactive actions performed by the virtual character provided to the target object may include telling the target object an inspirational story or playing soothing music. Depending on actual needs, the interactive actions performed by the virtual character can also be determined based on the target object's preference information and historical interaction data. The interactive actions performed by the virtual character may include multimodal interactive actions; for example, the virtual character can interact with the target object through multiple methods such as voice, animation, and text to enhance the diversity and fun of the interaction.

[0095] In at least one embodiment of this disclosure, during the process of providing a virtual character to a target object to perform interactive actions, the target object's emotional state can be continuously monitored, and the interactive actions performed by the virtual character can be adjusted according to changes in the emotional state, so that the interactive actions performed by the virtual character match the target object's real-time emotions. This provides the user with a feeling of being accompanied in real time, thus improving the user experience.

[0096] For example, when the target's mood improves, the virtual character can guide them through relaxing activities, such as playing a game or meditating. When the target's mood is lower, the virtual character can provide deeper emotional support by performing interactive actions, such as sharing inspirational stories or playing soothing music.

[0097] In at least one embodiment of this disclosure, the effect of virtual companionship provided to users through virtual characters can be continuously optimized based on user feedback. For example, users can evaluate the interactive actions performed by the virtual characters through voice or touch feedback, and the system providing the virtual characters can adjust the interactive actions and content performed by the virtual characters based on the evaluation, such as adding new interactive actions to the virtual characters. For example, evaluation information can also be collected through questionnaires, and natural language processing and sentiment analysis technologies can be used to analyze the evaluation information to determine the satisfaction of the target audience and suggestions for improvement.

[0098] The technical solution for providing auxiliary information via virtual characters, as provided in this disclosure, can be applied to various target scenarios. For example, in a medical consultation scenario, the target individual may feel lonely and anxious, and can receive emotional support and companionship through virtual family members or virtual pets. For instance, some users have low acceptance of technological products, but the friendliness and fun of virtual characters can help these users better adapt to the operation of intelligent medical consultation. For example, virtual characters can encourage and help these users relax through warm dialogue, and can also alleviate loneliness through cute animations and interactions. For example, in a post-medical consultation scenario, the target individual may feel frustrated and helpless, and can receive encouragement and psychological support by sharing inspirational stories or humming soothing music through virtual friends, thereby helping the target individual regain confidence and actively cooperate with treatment. Furthermore, the technical solution for providing auxiliary information via virtual characters is characterized by personalization, dynamism, and fun. For example, by combining emotional states identified through emotion recognition technology, the system providing virtual characters can provide personalized emotional support based on the target individual's real-time emotional state; that is, through dynamic interactive design, the system can adjust the behavior and interactive content of the virtual characters according to the target individual's emotional changes. For example, by generating engaging virtual characters, the system can enhance the appeal and effectiveness of emotional support.

[0099] Figure 4 schematically illustrates the implementation principle of the information processing method provided in at least one embodiment of this disclosure.

[0100] In at least one embodiment of this disclosure, the health status of a target individual can be predicted based on monitored physiological data and determined emotional states, and intervention information can be provided to remind the target individual to adjust their health status based on the intervention information. This can help users better understand their health status and assist them in maintaining a healthy physical condition.

[0101] For example, physiological data of the target object can be obtained first, and then intervention information can be determined based on the physiological data and emotional state. The intervention information can then be provided to the target object so that the target object can adjust its health status based on the intervention information.

[0102] For example, physiological data may include at least one of the following: heart rate, blood pressure, body temperature, blood oxygen level, etc. For example, wearable devices may be used to monitor physiological data, and wearable devices may include at least one of the following: smartwatches, fitness trackers, portable blood pressure monitors, digital thermometers, and pulse oximeters.

[0103] For example, smartwatches or fitness trackers can be used to monitor heart rate, using technologies such as photoplethysmography (PPG) or electrocardiography (ECG). PPG calculates heart rate by monitoring changes in light absorption caused by blood circulation, while ECG measures heart rate and heart rate variability by recording the heart's electrical activity, providing important information about heart health.

[0104] For example, portable blood pressure monitors can be used to monitor blood pressure. Portable blood pressure monitors measure systolic and diastolic blood pressure by applying pressure through a cuff and using sensors to detect pressure changes. Portable blood pressure monitors can, for example, have built-in storage and Bluetooth connectivity, allowing measurement results to be transmitted in real time to a terminal device or cloud database for long-term data tracking and analysis.

[0105] For example, digital thermometers can be used to monitor body temperature. Digital thermometers use infrared technology or contact sensors to measure body temperature quickly and accurately.

[0106] For example, a pulse oximeter can be used to monitor blood oxygen levels. A pulse oximeter, for instance, measures blood oxygen saturation using a photoelectric sensor and can be worn via a finger clip or wristband.

[0107] For example, multimodal data fusion technology can be used to fuse physiological data 401 with emotional state indicators 402 to obtain fused data. Then, a deep neural network is used to process the fused data to predict health risks and provide intervention information. For example, intervention information may include reminders to the target individual to exercise, adjust dietary intake, or reduce mood fluctuations through relaxation training.

[0108] For example, features can be extracted and embedded from physiological data 401 and emotional state indicators 402. For instance, physiological data from multiple continuously monitored moments can be represented as a sequence of physiological signal vectors, where each vector can be in the form of [heart rate, blood pressure, body temperature, blood oxygen level]. Similarly, emotional state indicators from multiple continuously monitored moments can be represented as a sequence of emotional signal vectors, where each vector can be in the form of [stress level, anxiety level, pleasure level]. This embodiment can use a time-series encoder to process the physiological signal vector sequence and the emotional signal vector sequence separately to obtain feature representations of physiological signals (e.g., physiological features) and emotional states (e.g., state features). The time-series encoder can, for example, include a Long Short-Term Memory (LSTM) network, a Gated Recurrent Unit (GRU), or a Transformer. Through the time-series encoder, emotional states and physiological data can be mapped to the same latent space, facilitating the processing of these data under a unified dimension. Subsequently, for example, physiological features and state features can be concatenated and input into a convolutional neural network, which can then fuse these two features to obtain fused data.

[0109] In at least one embodiment of this disclosure, a self-attention mechanism 410 can be used to process physiological data 401 and emotional states (e.g., emotional state indicators 402 that indicate emotional states) to obtain physiological features 403 and state features 404. Using a self-attention mechanism allows for the capture of temporal dependencies and correlations between features within both the physiological data and the emotional state indicators, uncovering patterns in each. For example, different dimensions of the emotional state indicator 402 often exhibit interdependencies; for instance, an increase in anxiety may be accompanied by an increase in stress, while a decrease in pleasure may reflect emotional fluctuations. The self-attention mechanism can identify these dependencies and assign more weight to key emotional changes, thereby effectively capturing the temporal dynamics of emotional states. Similarly, different dimensions of physiological signals are interconnected. The self-attention mechanism can identify important physiological changes by analyzing the fluctuations in these signals; for example, changes in heart rate may be accompanied by fluctuations in blood pressure, while an increase in body temperature may indicate increased physiological stress. The self-attention mechanism can highlight these key physiological signals.

[0110] In at least one embodiment, after obtaining physiological features and state features, a bidirectional attention mechanism (also known as a cross-modal self-attention mechanism) 420 can be used to fuse physiological features 403 and state features 404. This allows for deep fusion of physiological data and emotional states, capturing the correlation and mutual influence between them. This is because changes in emotional state indicators (e.g., stress or anxiety levels) often affect an individual's physiological signals (e.g., heart rate or blood pressure). When using a bidirectional attention mechanism, state features can be used as a "query" signal, dynamically focusing on physiological features related to that state feature to identify the impact of emotional states on physiological signals. For example, when stress levels rise, changes in heart rate and blood pressure are monitored to better capture the impact of emotional states on physical health. Similarly, changes in physiological signals also affect an individual's emotional state; for example, a sharp increase in heart rate may reflect increased anxiety. When using a bidirectional attention mechanism, physiological features can be used as a "query" signal, dynamically adjusting the focus on emotional states for those physiological features to identify the impact of changes in physiological signals on emotional states. Thus, through the bidirectional attention mechanism, the complex interaction between physiological signals and emotional states can be effectively captured.

[0111] For example, two features obtained through bidirectional attention can be concatenated to obtain a fused feature 405. This fused feature 405 can then be input into a deep neural network 430, which outputs predicted health risks and intervention information 406.

[0112] In at least one embodiment of this disclosure, when predicting health risks and determining intervention information, at least one of the target subject's medical records and lifestyle data may be considered, for example. That is, intervention information is determined by comprehensively considering at least one of these pieces of information, physiological data, and emotional state.

[0113] For example, the target individual's medical information may include imaging data and / or electronic medical record data. Lifestyle data may include data representing lifestyle habits, such as sleep data, dietary data, exercise data, smoking data, and alcohol consumption data.

[0114] For example, when determining intervention information, the method described above can be used to extract and embed features from physiological data 401 and emotional state indicators 402.

[0115] For example, image data (such as X-ray and CT scan results) can be preprocessed to uniformly adjust the image data size to the same resolution, such as 224×224 or 256×256, and the pixel values ​​can be normalized to the range [0,1]. The preprocessed image data can then be input into a feature extraction model, which outputs a feature representation of the image data. The feature extraction model can be, for example, a pre-trained convolutional neural network model. This can be obtained by removing the last layer of a Residual Neural Network (ResNet), a Deep Convolutional Network (VGG), or a Deep Convolutional Neural Network (Inception), and then pre-training it. Alternatively, a new CNN model can be trained directly to obtain the feature extraction model.

[0116] For example, electronic medical record (EMR) data can include medical history, visit records, medication records, and laboratory test results. When determining the feature representation of EMR data, text data can be converted into a structured format to extract important medical information. Numerical data (such as laboratory test results, age, height, etc.) can be used directly. Categorical data (such as gender, disease type, medication records, etc.) can be encoded using one-hot encoding or label encoding. For unstructured text information (such as doctor's notes, diagnostic reports, etc.), natural language processing techniques can be used to extract features. For example, text vectors can be calculated using Term Frequency–Inverse Document Frequency (TFIDF) or a pre-trained word embedding model can be used to convert text into vector representations.

[0117] For example, lifestyle data can be processed in a manner similar to that used for medical records to obtain feature representations. For instance, categorical data (such as dietary habits, smoking patterns, and drinking frequency) can be encoded using one-hot coding or label coding. Numerical data (such as daily exercise duration and nightly sleep duration) can be directly represented. If the data has time-series properties, statistical features (such as variance, mean, etc.), trend features, or periodic features can also be extracted.

[0118] For example, in this embodiment, the aforementioned physiological features, state features, and at least one of the feature representations from medical information and lifestyle data can be concatenated and input into a convolutional neural network (CNN). The CNN then fuses these features to obtain fused features. Alternatively, a multimodal attention mechanism can be used to perform intermodal information interaction and fusion of these features to obtain fused features. Subsequently, a deep neural network is used to process the fused features to predict health risks and determine intervention information.

[0119] For example, when training a feature extraction network, data augmentation techniques such as rotation, scaling, and flipping can be applied to image data to expand the training set of the feature extraction network and improve its robustness. During the training of a deep neural network, the cross-entropy loss function can be used as the loss function. To avoid overfitting, L1 / L2 regularization or the regularization technique Dropout (which increases the model's generalization ability by randomly shutting down some neurons during training) can be used during the training of a deep neural network. Optimizers such as Adaptive Moment Estimation (Adam) or Stochastic Gradient Descent (SGD) can be used during the training of a deep neural network. It is understood that the above-mentioned loss functions, regularization techniques, and optimizers are merely examples to facilitate understanding of this disclosure, and the embodiments of this disclosure are not limited thereto.

[0120] In at least one embodiment of this disclosure, for example, the model used in the process of obtaining the feature representation (e.g., a feature extraction model) and the deep neural network used to process the fused data can be integrated into a digital twin model. For example, reinforcement learning algorithms can be used to adaptively update the digital twin model to ensure that the health status predicted by the model is consistent with the health status of the target object. The core of adaptively updating the digital twin model through reinforcement learning lies in utilizing the continuous interaction between the target object's health data and the model, enabling the model to continuously optimize and dynamically adjust. For example, data reflecting the health status of the target object (e.g., physiological data, emotional state indicators, etc.) can be used as input to the digital twin model and regarded as the "state" in the current environment. The best "action" can be selected through reinforcement learning algorithms (such as Q-Learning or deep Q-networks), i.e., how to adjust the model's parameters or update the prediction strategy. Each time the model makes an adjustment based on the data reflecting the health status, the effect of the adjustment is evaluated through a reward function. The reward function is usually related to the achievement of health goals, such as whether health indicators have improved or emotional state has stabilized. If the model's adjustment improves the health status of the target object, a positive reward is given; otherwise, negative feedback is given. Through this continuous feedback mechanism, the model can adaptively learn the optimal parameter adjustment strategy under different health states, thereby ensuring that the health status predicted by the model and the intervention information provided are consistent with the health status of the target object. Over time, reinforcement learning enables the digital twin model to be gradually optimized, and it can automatically adjust prediction and intervention strategies when faced with long-term changes in the target object's health data, so as to achieve personalized health management and precision medicine.

[0121] Technical solutions that provide intervention information facilitate long-term health management of target individuals. Two examples are provided below for illustration.

[0122] For example, in one embodiment, if the target subject has anxiety disorder accompanied by physiological problems such as elevated blood pressure, their emotional state can be monitored in real time through wearable devices and smartphone applications. Simultaneously, physiological data, including heart rate, blood pressure, body temperature, and sleep quality, can be collected through smartwatches or other wearable physiological monitoring devices. When fluctuations in the target subject's emotional state are detected, such as a significant increase in anxiety levels (i.e., heightened anxiety), the target subject's digital twin model can be dynamically adjusted in conjunction with changes in physiological data (such as increased heart rate and blood pressure). This model uses reinforcement learning algorithms to update the target subject's health status predictions in real time, such as predicting further aggravation of anxiety disorder or potential physiological problems. Based on these predictions, personalized intervention strategies can be generated, such as suggesting the target subject to perform deep breathing exercises, take short breaks, or contact a psychologist for further emotional support. Furthermore, the long-term trends in the target subject's emotional and physiological data can help doctors optimize long-term treatment plans. Doctors can also intuitively understand changes in the target subject's emotional state and physiological data through a visual interface, thereby providing more precise medical interventions. In this way, the target audience can not only receive real-time emotional support in their daily lives, but the dynamic adjustment function can also effectively avoid physiological crises caused by emotional breakdown, ultimately achieving more precise health management and emotional guidance.

[0123] For example, in another embodiment, if the target subject has a chronic disease (such as diabetes), during the target subject's rehabilitation process, a smart wearable device worn by the target subject can be used to monitor the target subject's physiological data (such as blood sugar levels, heart rate, blood pressure, etc.) in real time, while continuously tracking the target subject's emotional state, such as anxiety, depression, or emotional fluctuations due to life stress. If an abnormally high blood sugar level is detected, and the target subject's emotional state is found to be relatively low and anxious, which may be related to the target subject's daily life stress or emotional instability, then a digital twin model can be used to analyze the current physiological data and emotional state to predict the health risks the target subject may face, such as acute hyperglycemic reactions or further deterioration of the psychological state. Based on this prediction, personalized intervention strategies can be generated, such as reminding the target subject to engage in appropriate exercise, adjust the daily dietary intake, or reduce emotional fluctuations through relaxation training. If the target subject's mood remains low, it can also be suggested that the target subject contact family or doctors, or arrange an online psychological counseling session. Furthermore, the digital twin model can be adjusted based on the target individual's long-term physiological data and emotional state trends to better adapt to their individual needs. This includes adjusting blood glucose control targets, optimizing medication regimens, and even recommending more precise diet and exercise plans. In addition, doctors can obtain data on the target individual's emotional and physiological changes over different time periods, gaining a better understanding of the impact of emotions on their condition and adjusting treatment plans accordingly. This not only helps the target individual receive more nuanced support in emotional management and physiological health control but also prevents health problems such as blood glucose dysregulation caused by emotional fluctuations through two-way regulation of emotions and physiology, ultimately improving the target individual's quality of life and recovery outcomes.

[0124] In at least one embodiment of this disclosure, assistance information for regulating the emotional state of a target object may be provided only when the emotional state indicates that the target object is experiencing an emotional abnormality. For example, the assistance information may include a first prompt that matches both the emotional state and the target scenario. This is because the target object particularly needs emotional support when experiencing an emotional abnormality. Depending on actual needs, the first prompt may also be provided when the target object is experiencing a normal emotional state, such as happiness or calmness, and this first prompt can be used to remind the target object to maintain the current state.

[0125] The following will further describe the assistance information provided for different scenarios. It is understood that the system implementing the information processing method provided in the embodiments of this disclosure can have the function of providing assistance information in different scenarios.

[0126] Figure 5 schematically illustrates the principle of providing assistance information in a triage scenario.

[0127] For example, in a triage scenario, a function can be provided to engage in conversation with the target object to obtain the target object's symptom information through the conversation and provide the target object with assistance information such as recommended hospitals based on the symptoms.

[0128] For example, in response to obtaining the first conversation information 501 provided by the target object in a triage scenario, the system can determine the symptom information 502 included in the first conversation information. For instance, the system can communicate with the target object through dialogue and guide the target object to provide information such as symptom information, symptom duration, past medical history, allergy history, and medication history. For example, keyword extraction can be performed on the information provided by the target object to extract the symptom information. Alternatively, a sequence labeling model can be used to label the first conversation information provided by the target object, and the symptom information included in the first conversation information can be determined based on the labeling results.

[0129] For example, after obtaining symptom information, recommended destinations can be provided directly to the target audience based on that information. For instance, a hospital with a proven track record of effective treatment for a given symptom can be selected from multiple alternative hospitals as the recommended destination. Alternatively, the corresponding department can be identified based on the symptom, i.e., the department that can treat diseases including those symptoms. Then, the multiple alternative hospitals can be ranked according to their respective departments, and the hospital ranked highest can be selected as the preferred destination.

[0130] In at least one embodiment, after obtaining symptom information, the recommended destination can also be determined by combining emotional state. For example, the aforementioned step of providing assistance information to the target object may include, in response to the target scenario being a triage scenario, providing the target object with recommendation information including a recommended destination based on emotional state 503 and symptom information. For example, the recommended destination may be a hospital.

[0131] For example, you can first determine the corresponding department based on symptom information, and then rank multiple candidate hospitals according to the ranking of the corresponding departments. Finally, the ranking results of multiple candidate hospitals and the emotional state 503 are used to determine the recommended destination. For example, if the emotional state 503 is a calm state, you can choose the hospital that is closer and ranked higher from multiple candidate hospitals. If the emotional state 503 is an anxious state, you can choose the hospital that is ranked highest from multiple candidate hospitals.

[0132] In at least one embodiment, the target department 504 for the target individual can be determined first based on the emotional state 503 and symptom information 502. For example, if the emotional state 503 indicates that the target individual is very anxious, the target department 504 can be determined to be the emergency department; if the emotional state 503 indicates that the target individual is less anxious, the target department 504 can be determined to be the department corresponding to the symptom information, for example, if the symptom is abdominal pain, the department corresponding to the symptom information can be determined to be gastroenterology, etc. Subsequently, a recommended destination can be determined from multiple alternative destinations (i.e., alternative hospitals) based on the target department. For example, the hospital with the highest-ranked target department among multiple alternative destinations can be used as the recommended destination. For example, the recommended destination 505 can also be selected from multiple alternative destinations by combining the target department 504 and the emotional state 503, so that the determined recommended destination is more in line with the needs.

[0133] In one embodiment, both the identified target department and the recommended destination can be used as recommendation information. This can provide a reference for the target person to register, making it easier for them to quickly select a department when registering and reducing the chance of registering for the wrong appointment.

[0134] In at least one embodiment of this disclosure, after the target department is determined, for example, a specific object can be determined from a plurality of candidate objects included in the target department based on symptom information, and the specified object can be provided to the target object as recommendation information.

[0135] For example, the target department can include multiple candidate doctors who are doctors in the target department. This embodiment can match the symptoms of diseases that doctors in the target department specialize in treating with symptom information, and select the doctor with the highest matching degree as the designated candidate. For example, the designated candidate can also be determined based on the symptoms of diseases that each doctor in the department specializes in treating and the number of patients each doctor sees. For example, the candidate whose symptoms of diseases they specialize in treating match the determined symptom information and who has a large number of patients can be selected as the designated candidate. For example, when recommending doctors, only doctors with remaining appointment slots can be recommended to improve the effectiveness of the recommendation. This embodiment provides more reference information for the target candidate's registration by providing designated candidates, which helps to improve the registration efficiency of the target candidate.

[0136] For example, the system providing assistance information can also connect to the registration system of the recommended destination. In this way, the target user can directly perform the registration operation based on the target department and specified object included in the assistance information, without having to open other applications, thus further improving registration efficiency. For instance, in response to the target user's selection of the recommended destination and target department, the system can directly redirect to the registration interface of the target department in the registration system of the recommended destination.

[0137] In at least one embodiment of this disclosure, when a recommended destination is selected, a guiding path from the target object's current location to the recommended destination can also be determined, and the guiding path can be provided to the target object as assistance information. Based on the provided guiding path, the target object can easily understand the distance to the recommended destination and can also easily choose a more suitable mode of transportation.

[0138] For example, when there are at least two recommended destinations, a first navigation path from the target object's current location to any of those destinations can be determined in response to the selection of any of the recommended destinations. For instance, the target object's current location can be determined using methods such as Bluetooth beacons or Wi-Fi positioning.

[0139] For example, emotional state can also be considered when determining the guidance path. For instance, if the emotional state is anxious, the guidance path that avoids congested areas and has the shortest travel time can be selected. If the emotional state is calm, the guidance path with the shortest journey can be selected. For example, there is a correspondence between emotional state and the characteristics of the guidance path, which can include congestion levels, time duration levels, path length levels, etc. For example, the target can use the provided guidance path as navigation information and move to their destination according to the guidance path.

[0140] For example, as the target scene moves along the guidance path to any destination, the guidance path can be adjusted based on the real-time monitored emotional state, and the adjusted guidance path can be provided to the target object.

[0141] For example, guidance paths can be provided to the target audience via voice and / or visual mapping to guide them to their destination. The target audience's emotional state can be monitored in real time; for instance, if the target audience's emotional state indicates anxiety, the guidance path can be adjusted to the shortest possible time. Furthermore, the guidance path can be adjusted by incorporating physiological signals. For example, if physiological signals include an excessively fast heart rate or high blood pressure, the guidance path can be adjusted to a rest area, guiding the target audience to that area to rest.

[0142] By adjusting the guidance path based on emotional state, the path can be dynamically optimized, which is beneficial for providing personalized path suggestions to the target audience and improving the user experience.

[0143] Figure 6 schematically illustrates the principle of providing assistance information in a scenario where someone is traveling to a medical facility.

[0144] For example, in a scenario where someone is heading to a medical appointment, the target's current location and the medical appointment location can be obtained, and the guidance path from the current location to the medical appointment location can be provided to the target as assistance information.

[0145] For example, the target scenario can be determined as heading to a medical facility when the target object invokes the navigation function or when the target object inputs items to be examined. Depending on actual needs, the target scenario can also be determined as heading to a medical facility when the target object's registration information exists and the target object is detected moving towards the hospital during the time period indicated by the registration information, or when the target object has already received medical treatment and has items to be examined. This disclosure does not limit the scope of the embodiments.

[0146] For example, the current location of a target can be determined using methods such as Bluetooth beacons or Wi-Fi positioning. The system can respond to the target's input of a location name and use that location as the appointment location. Alternatively, the appointment location can be determined based on imported examination reports, prescriptions, etc., from the target. The appointment location can include, for example, the selected destination from the recommended destinations, or it can include departments, examination rooms, pharmacies, etc.

[0147] For example, a shortest path can be used as a constraint, combined with a map, to determine a guiding route from the current location to the treatment location. The map can be a map of the target's city or an internal map of a selected hospital from the recommended hospitals; this map can be a high-definition map, for example, to improve the accuracy of the guiding route. Once the guiding route is determined, it can be provided to the target, allowing them to easily move to the treatment location.

[0148] In at least one embodiment of this disclosure, a guidance path can be determined based on the behavioral data of the target object. For example, behavioral data of the target object can be collected in real time using devices such as Bluetooth beacons, Wi-Fi positioning, and cameras. Behavioral data may include, for example, dwell time, walking speed, and path preferences. For example, the behavioral pattern of the target object can be determined based on behavioral data such as walking speed and dwell time. For example, machine learning algorithms can be used to model the behavioral pattern of the target object based on its behavioral data. Behavioral patterns may include, for example, a slow-moving mode, a disorientation mode, and a normal mode. This embodiment can determine the guidance path based on the behavioral pattern. For example, if the behavioral pattern is a slow-moving mode, the determined constraints include including a rest area in the guidance path; if the behavioral pattern is a disorientation mode, the determined constraints include excluding side paths and minimizing turns in the guidance path; if the behavioral pattern is a normal mode, the determined constraints include minimizing the path length.

[0149] In at least one embodiment, a guidance path from the current location to the medical appointment can be determined based on a defined emotional state. For example, a guidance mode can be determined first based on the emotional state, and different guidance modes may correspond to different constraints. The guidance path is then determined based on the constraints corresponding to the determined guidance mode. For instance, if the emotional state is calm, the guidance mode can be determined as the shortest path mode, with the corresponding constraint being the shortest path length. If the emotional state is anxious, the guidance mode can be determined as the congestion avoidance mode, with the corresponding constraint being avoiding congested road sections. It is understood that the above-described methods for determining the guidance mode and the corresponding constraints are merely examples to aid in understanding this disclosure, and the embodiments of this disclosure do not limit this scope.

[0150] In at least one embodiment, the guidance path can be determined by combining emotional state and the target object's behavioral data, making the determined guidance path more in line with the target object's needs and improving user experience. For example, the constraints for path planning can be determined first based on the emotional state and the target object's behavioral data. For instance, if the behavioral data corresponds to a slow-movement mode and the emotional state is anxiety, the constraints can include avoiding congested sections and ensuring a short path; if the behavioral data corresponds to a movement-impairment mode and the emotional state is anxiety, the constraints can include maximizing accessible paths and minimizing the path length. If the behavioral data corresponds to a normal mode and the emotional state is anxiety, the constraints can include minimizing travel time and avoiding congestion. It is understood that the above methods of determining constraints are merely examples to facilitate understanding of this disclosure, and this disclosure does not limit them. For example, the guidance mode can also be determined first by combining the emotional state and the target object's behavioral data, and the constraints corresponding to the guidance mode can be used as the constraints for path planning.

[0151] In at least one embodiment of this disclosure, the guidance path can also be determined by combining physiological data and / or the department type corresponding to the medical visit location. For example, if the medical visit location is the emergency department, the guidance mode is determined to be the shortest time mode; if the blood pressure in the physiological data is too high, the guidance mode can be determined to include a rest area. For example, the guidance path can be determined by combining physiological data and emotional state. For example, if the blood pressure in the physiological data is higher than the normal range and the emotional state is calm, the guidance mode can be determined to be a relatively gentle route mode; if the blood pressure in the physiological data is higher than the normal range and the emotional state is anxious, the guidance mode can be determined to be the shortest path mode, and so on.

[0152] In at least one embodiment of this disclosure, emotional state, physiological data, and behavioral data can be combined to determine the guidance path. For example, if the emotional state is anxiety, the physiological data includes high blood pressure, and the behavioral data indicates slow movement, the guidance mode can be determined to be a mode that is short in duration, avoids congested sections, and has relatively flat terrain.

[0153] It is understood that the correspondence between emotional state, physiological data and / or behavioral data and guidance mode in the foregoing embodiments is only an example to facilitate understanding of this disclosure. In practice, the correspondence between guidance mode and each data can be set according to actual needs to comprehensively consider the comfort, time and distance of the target object moving along the guidance path, so as to improve the user experience.

[0154] In at least one embodiment of this disclosure, the location for medical treatment may include at least two locations, and the guidance path determined in this embodiment may be a guidance path from the current location to the at least two locations, where one of the at least two locations is the final destination and the other locations are waypoints.

[0155] For example, when there are at least two locations for medical treatment, the arrival order of the at least two locations can be determined first based on the environmental information of each location. Then, the guidance path can be determined based on the arrival order and at least one of behavioral data, emotional state, physiological data, etc. This makes the determined guidance path more reasonable and helps improve the user experience.

[0156] For example, the system can connect to a hospital's Hospital Information System (HIS) to obtain real-time information such as the number of people queuing in each department and the number of doctors in each department at each location. For instance, locations with fewer queuing people can be prioritized, as can locations with more doctors. Different weights can also be assigned to the number of people queuing and the number of doctors. Finally, the multiple locations are ranked based on the weighted sum of the number of people queuing and the number of doctors at multiple locations, thus determining the arrival order.

[0157] For example, the distance between each location and the current location can also be used as environmental information. That is, by comprehensively considering the distance between each location and the current location, the number of people queuing in the corresponding department, and the number of doctors, the arrival order of at least two locations can be determined.

[0158] In one embodiment, as shown in FIG6, when determining the guidance path, the arrival order 606 of at least two locations included in the medical treatment location 602 can be determined first based on environmental information 605. Then, by combining behavioral data 604, emotional state 603 and arrival order 606, the guidance path 607 from the current location 601 to at least two locations included in the medical treatment location 602 can be determined.

[0159] For example, a guidance mode can be determined first based on behavioral data 604 and emotional state 603. Then, the constraints corresponding to the guidance mode and the arrival order 606 are used as constraints, and a path planning algorithm is used to determine the guidance path. Any existing algorithm can be used for path planning, and this embodiment of the disclosure does not limit it.

[0160] In at least one embodiment of this disclosure, as the target object moves along the guided path, the guided path can be adjusted in response to changes in at least one of behavioral data and emotional state. For example, if real-time behavioral data indicates that the target object's movement speed decreases and nearly stops, the guided path can be adjusted to lead to the nearest rest area to the current location. If real-time behavioral data indicates that the target object has deviated from the guided path, the guided path can be adjusted to lead from the current location to the medical appointment location. If the emotional state changes to anxiety, the guided path can be adjusted to the path with the shortest movement time, and so on. It is understood that the above adjustment methods are merely examples to facilitate understanding of this disclosure, and the embodiments of this disclosure are not limited thereto. By adjusting the guided path according to changes in at least one of behavioral data and emotional state, the guided path provided to the target object can be more in line with real-time needs, thereby improving the user experience.

[0161] For example, the technical solution of at least one embodiment of this disclosure can dynamically optimize the path based on the behavior of the target object, thereby optimizing the target object's medical treatment process. Furthermore, the system can automatically identify the potential needs of the target object based on the patient's real-time behavior, such as whether they need rest or are lost, and provide personalized path suggestions to ensure that the target object can complete their medical treatment efficiently and comfortably. The innovation of this function lies in its combination of real-time behavioral data of the target object to provide dynamic path optimization, rather than relying solely on static data for path planning like traditional systems. In addition, it can also provide personalized path suggestions based on the behavioral characteristics of the target object, such as those with mobility impairments or the elderly, further enhancing the medical treatment experience.

[0162] By employing the technical solution provided in at least one embodiment of this disclosure, if a target object stays in a certain area for too long, the system can prompt the target object whether it needs rest or assistance. If the target object deviates from the guided path, the system can replan the path and provide voice prompts. Regarding user interaction, the system can guide the target object to the medical location through voice prompts and a visual map, and supports the target object in evaluating the navigation service through voice or touch feedback, thereby continuously optimizing the path planning algorithm.

[0163] In one embodiment, environmental information can also be obtained by combining smart devices such as smart glasses. For example, in a scenario where people are queuing to pick up medicine in a lobby, smart glasses can be used to identify the number of people in the queue in real time and the number of available medicine windows.

[0164] For example, the technical solution provided in at least one embodiment of this disclosure can be applied in many scenarios. For example, it can provide barrier-free route planning for target objects with limited mobility (such as the elderly and disabled) to ensure they can reach their medical destination smoothly. For example, it can provide shortest route planning for target objects in the emergency room to ensure they can receive treatment as soon as possible. For example, it can provide real-time route adjustment for target objects who are lost to help them find the correct route. Through these application scenarios, the dynamic route optimization function can significantly improve the system's usability and user experience. In terms of technical advantages, this function has the characteristics of real-time, personalization, and intelligence. Path optimization based on real-time behavioral data ensures the accuracy and timeliness of navigation services; personalized route suggestions are provided based on the behavioral characteristics of the target object to improve the medical experience; and more intelligent navigation services are provided through behavioral data analysis and dynamic route planning algorithms. For example, if an elderly patient spends too much time on their way to the internal medicine department, the system recognizes that the patient may need to rest, automatically adjusts the route, recommends the nearest rest area, and provides a voice prompt: "Do you need to rest? There is a rest area 20 meters ahead." For example, if an emergency patient needs to get to the emergency department as soon as possible, the system will plan the shortest route based on real-time environmental data and provide a voice prompt: "Please walk straight for 100 meters along the current route. The emergency department is on your left."

[0165] In at least one embodiment of this disclosure, upon detecting that a target object has moved to a target location, a second prompt can be provided to the target object to prompt it to perform a target activity at the location. The target activity corresponds to the location. For example, if the location is a consultation room or examination room, the target activity may include checking in and obtaining a number at a self-service check-in machine or nurse's desk. If the location is a pharmacy, the target activity may include submitting a prescription to the dispensing window. Providing a second prompt can improve the efficiency of medical visits and avoid wasting time due to users' unfamiliarity with the medical process.

[0166] In one embodiment of this disclosure, in a scenario where the target is traveling to a medical facility, if the system detects anxiety or tension in the target individual, it can gently guide them to take deep breaths via the vehicle's loudspeaker, with a voice prompt such as, "Let's take a deep breath together, inhale slowly, and then exhale slowly. Relax your shoulders and arms and feel your mood gradually calm down." For example, the system can also automatically play the target individual's favorite soft music to alleviate tension. For example, to further reassure the target individual, the system can also provide a prompt such as, "We will arrive at the hospital in ten minutes. There are many professional doctors and friendly nurses there who will take good care of you." Such prompts aim to reduce the target individual's fear and uncertainty about the hospital environment. For example, the system can also provide simple meditation guidance to help them focus their attention, reduce anxiety, and ensure they are in a relatively relaxed state before arriving at the hospital.

[0167] In at least one embodiment of this disclosure, when the target scenario is a waiting scenario for medical treatment, real-time waiting information can be provided to the target object when it is determined that the emotional state indicates that the target object's emotions are abnormal, so as to facilitate the target object to understand the progress of medical treatment and help regulate abnormal emotions.

[0168] For example, the emotional state indicating an abnormal mood in the target individual may include anxiety, anger, and sadness. Even if the target individual has completed triage but has not yet received treatment, the target scenario can be determined as a waiting scenario. The real-time waiting information provided may include, for example, the remaining number of people in the queue, the current queue number, etc., but this embodiment of the disclosure does not limit this.

[0169] For example, in addition to providing real-time waiting information, the aforementioned initial prompt information can also be provided to the target audience to better regulate their emotions.

[0170] In at least one embodiment of this disclosure, when the target scenario is a waiting scenario for medical treatment, when the second session information provided by the target object is obtained, key information of the second session information can be extracted, and the key information can be used to provide report information to the target object.

[0171] For example, in a waiting scenario for medical treatment, the system can communicate with the target person through dialogue to obtain more detailed symptom information. For instance, if abdominal pain is identified as a symptom in the triage scenario, the system can ask the target person the following information through conversation while waiting: whether the pain is sharp or dull, its severity, and factors that aggravate or alleviate it. After obtaining the conversation information provided by the target person, a keyword extraction algorithm can be used to extract key information from the conversation. For example, the extracted key information can be structured information. Subsequently, the extracted key information can be filled into a pre-set report template to obtain report information. For example, the report information can be structured report information.

[0172] Schematic representation: The generated report information may include the following:

[0173] Gender: Female;

[0174] Age: XX;

[0175] Chief complaint: Abdominal pain for two days, characterized by intermittent, paroxysmal stabbing pain, mainly after meals, without nausea.

[0176] Vomit.

[0177] For example, report information can also be generated by combining emotional states. That is, report information is provided to the target audience based on key information and emotional states. For example, in addition to the aforementioned information, the report information may also include information on the current emotional state as its theme. The theme may include the type of emotional state, or emotional information that determines the emotional state, etc., which is not limited in this embodiment. By combining emotional states to generate report information, it is convenient for a designated object (e.g., a doctor) to interact with the target audience in different ways, thereby improving the interaction experience and reducing conflicts.

[0178] In one embodiment of this disclosure, in a waiting scenario for a medical appointment, the target individual may easily feel anxious or irritable due to the potentially long wait time. At this point, the system can initiate an interactive dialogue upon detecting abnormal emotions in the target individual, speaking in a gentle voice: "I know waiting can be uncomfortable, but I'm here with you. Let's watch this beautiful garden video together and feel the tranquility of nature." For example, the system can also automatically play a favorite TV program based on the elderly person's previous preferences and provide some light reading material, such as an electronic version of a health magazine. If the system detects persistent agitation in the target individual, it can also guide them through simple cognitive games or provide relaxing videos to help divert their attention. For example, the system can also continuously update the target individual's appointment status, prompting them through screen display and voice prompts such as "Your number is about to be called, please prepare." This real-time information update reduces the anxiety caused by a lack of awareness, helping them maintain a more peaceful mood during the waiting period.

[0179] In at least one embodiment of this disclosure, when report information is provided to the target object, if the current scenario is determined to be a medical consultation scenario, the report information can also be provided to a designated object interacting with the target object. This facilitates interaction between the designated object and the target object based on the report information, thereby improving interaction efficiency. For example, if the designated object is a doctor, the report information can reduce the doctor's consultation time, thus improving the target object's medical consultation efficiency.

[0180] In at least one embodiment of this disclosure, when the target scenario is a medical visit, a third prompt message can be provided to a designated object interacting with the target object when the emotional state indicates an abnormality in the target object's emotions. This prompts the designated object to adjust its interaction method with the target object. For example, during a medical visit, if the target object's emotional state is detected as angry, a prompt message such as "The patient is currently in a poor condition; please provide more careful and considerate consultation" can be provided to the doctor.

[0181] For example, if abnormal emotions are detected in a target person during a medical visit, a prompt message can be provided to the target person.

[0182] In one embodiment, monitoring the emotional state becomes particularly important in a medical setting when performing uncomfortable medical procedures on a target individual. For example, when the system detects an abnormal emotional state such as tension or anxiety, it can play soft music for the target individual, show them a soothing beach scene, and provide a voice prompt such as, "You're doing great. Just hang in there a little longer. Imagine yourself walking on the beach, feeling the warm sunshine and soft sand." The system can also alert medical staff to the target individual's emotional state, enabling them to communicate with the individual in a gentler voice and with more patience. Alternatively, it can provide the target individual with prompts such as, "We only need to do a small check-up, and everything will be over quickly. You've done a fantastic job." Furthermore, the system can provide explanations for each step of the medical procedure to help the target individual understand what is about to happen and reduce fear caused by the unknown.

[0183] Figure 7 schematically illustrates the process of determining assistance information in a medical visit scenario.

[0184] In at least one embodiment of this disclosure, as shown in FIG7, in a medical visit scenario, the step of determining assistance information may include steps S731 to S732.

[0185] In step S731, in response to detecting third session information provided by any of the target object and the specified objects interacting with the target object, the third session information is transformed to obtain the first transformed information.

[0186] In step S732, the first converted information is provided.

[0187] For example, the third session information can be session information between the doctor and the target patient during the consultation process. For instance, the first converted information may include information that interprets the third session information.

[0188] For example, the third conversation information can be input into a large language model, which will then output the first converted information. Alternatively, the third conversation information can be compared with a pre-defined vocabulary lookup table to determine the target vocabulary included in the third conversation information. The target vocabulary in the third conversation information can then be replaced with the corresponding vocabulary from the lookup table to obtain the first converted information.

[0189] For example, a large language model can be obtained by fine-tuning an existing large language model to output the first converted information. For example, data can be prepared first; to train the model to accurately convert between technical terms and colloquial expressions, a large amount of dialogue data can be collected. This data should include technical terms used by doctors and their corresponding colloquial explanations. Data can be collected from various sources, including medical literature and patient education materials, which contain a large number of technical terms and their colloquial explanations. For example, in medical manuals, "diarrhea" is explained as "loose stools". In addition, dialogue data between doctors and patients can be collected, especially those dialogues containing technical terms and their colloquial explanations. For example, a doctor saying "Do you have indigestion, bloating, or heartburn?" would be colloquially translated as "Do you have indigestion, bloating, or heartburn?". During the data annotation phase, professional medical personnel annotate the data. Each technical term needs a corresponding colloquial explanation to ensure the accuracy and diversity of the data. For example, "hypertension" is annotated as "high blood pressure," and "myocardial infarction" is annotated as "heart attack." The dataset needs to cover professional terms for various common illnesses and treatments; for example, "cold" is labeled as "caught a chill," and "antibiotics" is labeled as "medicine for treating bacterial infections." Next comes model fine-tuning. A pre-trained large language model is chosen as the base model, and then the pre-trained model is fine-tuned using the collected and labeled data. For example, the data can be organized into a training set, with each sample containing a professional term and its corresponding everyday expression explanation. For example, a sample could be "diarrhea - loose stools," or "hypertension - high blood pressure." Training parameters are set, including the number of training epochs, the number of samples processed per batch, and the learning rate. For example, the number of training epochs can be set to 3, with 4 samples processed per batch. Through multiple rounds of iterative training, the model learns the conversion relationship between professional terms and everyday expressions.

[0190] For example, emotional states can be incorporated into the transformation of third-party conversational information. For instance, if an emotional state indicates an abnormal mood, information that alleviates the abnormal mood can be added during information transformation, or information expressing the emotion can be removed. In this way, when providing the first-transformed information to the target object and another object besides providing the third-party conversational information, the possibility of that other object exhibiting an abnormal mood can be avoided, thus improving the interaction efficiency and user experience for both the target and designated objects.

[0191] In one embodiment, the third session information may include information from at least two modalities, such as at least two of text, speech, and images. For example, the target object may describe symptoms by speech, upload pictures of the affected area or images obtained from examinations, and / or input text describing medical history. The system may, for example, perform multimodal information fusion processing. For example, the system may convert speech input into text, recognize and annotate images, and then integrate this information into a unified input format. Then, a multimodal translation model is used to translate the integrated information. The translation model may employ deep learning-based multimodal fusion technology, such as the multimodal Transformer model, to jointly encode and decode at least two of the text, speech, and / or image information to generate an accurate and easily understandable translation result, and use this translation result as the first conversion information. By supporting multiple input methods, embodiments of this disclosure can adapt to the needs of different objects, provide more flexible conversion services (which can also be understood as translation services), and through multimodal information fusion and deep learning models, the system can generate more accurate translation results.

[0192] For example, a patient can describe their symptoms via voice and upload images of the affected area. The system can then convert the speech to text, recognize the content of the images, and generate a detailed translation report to help doctors quickly understand the condition. For elderly patients or those with limited verbal communication skills, the system can assist them in communicating with doctors through image recognition and voice translation. For complex conditions, after patients upload medical images (such as X-rays) and provide a voice description, the system can generate a detailed translation report to help doctors better understand the condition.

[0193] Based on the functions of the steps described in Figure 7, in at least one embodiment of this disclosure, when the target scenario is a post-visit scenario, in response to obtaining reference information provided by a designated object interacting with the target object, the reference information is transformed to obtain second transformed information, which includes information interpreting the reference information. For example, the reference information may include medical orders, etc. Through this embodiment, medical orders can be transformed into information that is easy for the target object to understand, thereby improving the target object's medical experience.

[0194] For example, when transforming a reference, emotional state can also be considered. For instance, if the emotional state indicates anxiety, information to soothe anxiety can be added to the transformed information.

[0195] For example, this reference information can be uploaded to the system by the target object. For example, the reference information may include the following:

[0196] Diagnosis: Acute gastroenteritis, possibly accompanied by mild gastric ulcer.

[0197] Treatment plan:

[0198] Medication:

[0199] Omeprazole 20mg, once daily before breakfast, for 4 weeks.

[0200] Mosapride 5mg, three times daily before meals, for 2 weeks.

[0201] Antibiotic treatment: Clarithromycin 500mg, twice daily for 7 days.

[0202] Dietary recommendations:

[0203] Avoid spicy, greasy, excessively cold or hot foods.

[0204] Drink plenty of water to maintain adequate hydration; it is recommended to drink at least 2 liters per day.

[0205] Eat easily digestible foods.

[0206] Lifestyle adjustments:

[0207] Avoid drinking alcohol and smoking.

[0208] Maintain a regular sleep schedule and avoid staying up late.

[0209] Engage in light exercise, such as walking, but avoid strenuous activity.

[0210] Follow-up visit:

[0211] Two weeks later, a follow-up visit was scheduled to assess the effectiveness of the medication and the improvement in symptoms.

[0212] If abdominal pain worsens or other serious symptoms (such as vomiting blood or black stools) appear, seek medical attention immediately.

[0213] Based on the above medical advice, and assuming the emotional state is determined to be anxiety, the second converted information may include, for example:

[0214] "You have been diagnosed with acute gastroenteritis and may have a mild stomach ulcer. We will work together to help you recover as quickly as possible. Here is our treatment plan:"

[0215] Regarding medication:

[0216] You need to take omeprazole. This medicine will protect your stomach lining. Take it once every morning on an empty stomach for 4 weeks. Don't worry, it's very effective.

[0217] Mosapride will help your stomach move better. You can take it before each meal for 2 weeks to make your stomach feel more comfortable.

[0218] There's also clarithromycin, an antibiotic, taken twice a day for seven days. It helps eliminate potential bacterial infections. Remember, it's important to take your medication on time.

[0219] Dietary aspects:

[0220] It's best to avoid spicy, greasy, or excessively hot or cold foods right now, as these may make your stomach feel worse. Take your time, and we'll find foods you enjoy and that suit your taste.

[0221] Drink plenty of warm water, at least 2 liters a day, to help with your digestion and recovery.

[0222] Eating easily digestible foods, such as porridge or steamed food, will make your stomach feel more comfortable.

[0223] Lifestyle habits:

[0224] It's time to say goodbye to alcohol and cigarettes; they're not good for recovery. Believe me, this temporary break is for a better future.

[0225] Maintain a regular sleep schedule and avoid staying up late; your body needs rest to fight the disease.

[0226] You can do some light exercise, such as taking a walk, which will improve your mood and is also good for your health.

[0227] Follow-up appointment schedule:

[0228] We need to meet in two weeks to see how the medication is working and how your recovery is progressing. You are not alone in this fight; we will always be here to support you.

[0229] If your abdominal pain worsens during treatment, or if you experience vomiting blood or bloody stools, please don't panic. Come to the hospital immediately, and we will treat you as soon as possible.

[0230] Please don't worry too much. Many people have encountered similar problems, and with proper treatment and lifestyle adjustments, the vast majority recover very well. If you have any questions or feel unwell, please feel free to tell me or Dr. Zhang during your follow-up appointment. We will do our best to help you recover.

[0231] In one embodiment, in a post-medical visit scenario, the target's emotional response may vary depending on the diagnosis. For example, when the system detects that the target's emotional state is sadness or anxiety, it can provide reassuring words and detailed explanations, such as the following prompt: "We know this result may not be what you expected, but many conditions can be improved through treatment. We have a good treatment plan for you, and the doctor will discuss it with you in detail."

[0232] In one embodiment, in a post-medical visit scenario, the system can, for example, provide personalized psychological support to the target individual based on their emotional state and preferences. For instance, it could provide the target individual with a prompt such as, "Sometimes, talking to family and friends about how you feel is also helpful." The system can also provide links and contact information for online psychological counseling, encouraging the target individual to seek professional help when needed.

[0233] Based on the functions of the steps described in Figure 7, in at least one embodiment of this disclosure, in response to obtaining target information to be converted provided by the target object at any time, the target information can be converted to obtain third converted information, and the third converted information can be provided to the target object. For example, the target information to be converted may include medical orders, examination reports, medication instructions, disease names, etc. For example, if the target object suspects disease A based on symptoms, it can provide disease A as the target information to be converted to the system. The system can provide the user with third converted information explaining disease A, such as the symptoms of disease A and coping measures. For example, after completing an examination and obtaining an examination report, the target object can provide the examination report as the target information to be converted to the system. The system can provide the user with third converted information explaining the examination report to facilitate the user's understanding of the examination report.

[0234] In one embodiment, when converting target information, emotional state may also be considered, for example. The specific implementation principle is similar to that of considering emotional state when converting first and second conversation information, and will not be repeated here.

[0235] Figure 8 schematically illustrates a structural block diagram of an intelligent medical escort system provided according to at least one embodiment of the present disclosure.

[0236] In at least one embodiment, this disclosure may also provide an intelligent medical companion system, which can be used to implement the technical solutions included in the various embodiments described above.

[0237] As shown in Figure 8, in one embodiment, the intelligent escort system 800 may include an intelligent triage module 810, an intelligent guidance module 820, a pre-diagnosis module 830, an intelligent translation module 840, and an intelligent education module 850.

[0238] The intelligent triage module 810 can, for example, provide assistance information in triage scenarios. The intelligent guidance module 820 can, for example, provide assistance information in scenarios involving travel to a medical location, such as providing guidance routes and optimizing those routes in real time. The pre-consultation module 830 can, for example, provide assistance information in scenarios involving waiting for medical appointments, such as providing report information. The intelligent translation module 840 can, for example, provide information conversion functionality to convert information provided during the medical appointment, post-appointment, or at any time into easily understandable information. For example, the intelligent translation module 840 can also be used to provide assistance information during the medical appointment. The intelligent education module 850 can, for example, provide assistance information in post-appointment scenarios.

[0239] In at least one embodiment of this disclosure, each module in the intelligent triage system can also adjust the provided assistance information in response to detecting a change in the target object's emotional state during the process of providing assistance information to the target object, so as to match the provided assistance information with the target object's real-time emotional state, thereby improving the user experience.

[0240] In at least one embodiment of this disclosure, the intelligent triage system may also have the function of recording emotional states. For example, the system can automatically record changes in the emotional state of the target patient during each medical visit, generating an emotional state log to help doctors and family members understand the psychological changes of the target patient.

[0241] In at least one embodiment of this disclosure, the intelligent triage system may also have a real-time emotional feedback function. For example, based on the recognition results of emotional state, the system can promptly provide positive emotional feedback to the target object through text, sound, and / or images, such as reassurance, encouragement, and reminders. For example, the system can also adjust the interaction method and the assistance information provided based on the target object's emotional state; for example, when anxiety is detected in the target object, relaxing content such as soft music and breathing guidance can be provided. The system can also provide the target object with health information, explanations of the medical process, etc., to help the target object understand the medical process and reduce the target object's fear of the medical environment.

[0242] In at least one embodiment of this disclosure, the intelligent triage system can, for example, send a third prompt to associated objects when it detects that the target object's emotional state has changed to a state indicating abnormal emotion, so as to prompt the associated objects to assist the target object. For example, when the system detects that the target object has an extreme emotional reaction, such as an emotional state that changes to anxiety or sadness, or abnormal anxiety or sadness, it can automatically remind medical staff or contact family members to provide timely human intervention for the target object's emotional state. Through this embodiment, the occurrence of abnormal situations can be reduced.

[0243] In at least one embodiment of this disclosure, the intelligent companion system may also have a family interaction function to strengthen the connection between the target individual and their family members, ensuring that family members can promptly understand the target individual's health status and emotional changes, and provide necessary support and assistance. This function enables efficient communication and interaction between family members and the target individual through multiple channels and tools, thereby improving the target individual's sense of security and satisfaction, while also providing convenient monitoring support for family members.

[0244] For example, the main sub-functions of the family interaction function may include the following sub-functions:

[0245] The health and emotional status sharing feature allows individuals to share their health data (such as heart rate, blood pressure, blood sugar, etc.) and emotional logs with their families through a single platform. Family members can receive real-time notifications and reports that use charts and concise text to describe the individual's health trends and any unusual changes requiring special attention.

[0246] The emergency notification function automatically sends emergency notifications to pre-set family members when the system detects potential health risks or severe emotional changes, such as the target individual experiencing abnormal heartbeat, falls, or extreme anxiety. Family members can immediately understand the situation through these notifications and respond quickly through the system, such as initiating a video call to check on the target individual's condition or contacting nearby medical services.

[0247] The video calling and instant messaging features provide convenient video calling capabilities, allowing family members and the target person to communicate face-to-face anytime, helping to reduce feelings of loneliness and isolation. For example, family members can send caring greetings, daily reminders, or share interesting anecdotes and photos, making communication warmer and more personalized.

[0248] The system includes daily monitoring and reminder services. For example, family members can remotely view and set reminders for the individual's schedule, such as medication reminders, medical appointments, and regular checkups, ensuring the individual doesn't forget important health matters. The system can also provide family members with daily activity reports, including sleep quality, activity levels, and dietary records, helping them gain a comprehensive understanding of the individual's lifestyle.

[0249] The feature includes emotional support and counseling capabilities. For example, family members can view the target individual's emotional log and community activity participation, allowing them to provide more targeted support based on this information. This feature can also be used to recommend or arrange for the target individual to participate in online counseling or community support groups, helping them better manage their emotions and cope with health challenges.

[0250] The application scenarios of the intelligent medical escort system provided in at least one embodiment of this disclosure may include the following scenarios:

[0251] In a routine health monitoring and sharing scenario, for example, if family members work on the other side of the city and cannot accompany the person in need daily, they can still view the person's health data in real time through a smart medical companion system. For instance, every morning, the system automatically records the person's heart rate, blood pressure, and blood sugar, and generates a health report which is sent to the family member. The family member can then view this data via a mobile app, notice a slight increase in the person's blood pressure, and immediately inquire about the situation via instant messaging, reminding the person to pay attention to their diet and rest.

[0252] In an emergency response scenario, if a target person suddenly experiences palpitations at home, the system detects this abnormal situation and immediately notifies their family. For example, after receiving the emergency notification, the family can immediately check on the target person's condition via video call and simultaneously contact nearby medical services for emergency assistance. During the video call, the family sees the target person is pale and guides them to take deep breaths and calms them down until the ambulance arrives.

[0253] In a scenario where timely care is provided to address emotional changes, the system can analyze the target individual's emotional log. If family members discover through the system that the target individual has been experiencing low moods for several consecutive days, they can take action. For example, arranging a family video gathering where the target individual's children and grandchildren appear on screen to share recent anecdotes and pleasant family news can significantly improve the elderly person's mood.

[0254] In the health habits and daily reminders scenario, if an elderly person occasionally forgets to take medication or attend important medical appointments, family members can set up timed reminders in the system. The system will remind the elderly person to take their medication on time every morning and evening. Simultaneously, family members can set appointment reminders to ensure the elderly person doesn't forget upcoming medical checkups. Family members can also view the system's recorded activity levels and dietary diaries, providing timely reminders for the elderly to maintain a healthy lifestyle.

[0255] Sharing Life and Enhancing Connections: In this scenario, if the target individual frequently feels lonely due to their children's busy schedules, family members can use the system's sharing function to upload family photos and short videos weekly, allowing the target individual to feel the warmth of family. The target individual can also send their own daily photos and reflections. Through this interaction, emotional connections between family members are strengthened, reducing the target individual's loneliness.

[0256] The use of the intelligent medical companion system provided in this disclosure will be described below with reference to specific embodiments.

[0257] For example, in one embodiment, this intelligent medical escort system can integrate multiple functional modules to help target individuals obtain a smooth medical experience in hospitals in different regions. This addresses the problems that many patients often face when seeking medical treatment in different locations, such as language barriers, unfamiliarity with medical procedures, and information asymmetry, due to significant differences in medical procedures and environments across different hospitals. In this embodiment, the user group of the intelligent medical escort system can include: employees working in other locations, patients from different dialect regions, and patients with chronic diseases who need regular medical treatment. The usage process can include:

[0258] Appointment and triage process: Target users input their symptoms via a smartphone app. The system uses natural language processing technology to recognize the patient's dialect and convert it into standard medical terminology. Based on the symptoms, the system matches suitable departments and recommends hospitals and doctors, providing detailed information such as doctor qualifications and patient reviews. After the target user selects a hospital and department, the system assists them in making an online appointment and generates appointment confirmation information.

[0259] The pre-consultation preparation process involves the system proactively guiding the target individual through a pre-consultation after an appointment is made, collecting information such as medical history and allergies. The system can also provide personalized question descriptions and interaction methods based on the user's dialect and habits. Furthermore, the system can encrypt and transmit the collected information to the hospital for doctors to review in advance, improving consultation efficiency.

[0260] Hospital Guidance and Translation Procedures: Upon arrival at the hospital, the intelligent triage module utilizes indoor navigation technology to guide the patient to the correct department and examination room. During the consultation, the intelligent translation module translates the patient's dialect into standard medical terminology easily understood by the doctor, and translates the doctor's professional terminology into everyday language understandable to the patient. This two-way translation function ensures effective communication between doctors and patients, reducing misunderstandings.

[0261] Post-treatment education and follow-up steps: After the consultation, the system generates personalized health education content based on the doctor's treatment plan, including medication usage instructions and precautions. The system reminds the target individual to take medication on time, schedule the next follow-up appointment, and provides online consultation services to answer any subsequent questions.

[0262] For example, in one embodiment, this intelligent escort system can integrate various functional modules to help patients obtain an efficient and smooth medical experience in large hospitals. This addresses the problems patients often face in large urban hospitals, such as difficulty choosing a department, long waiting times, and poor doctor-patient communication. In this embodiment, the user group of the intelligent escort system can include: residents living in the city but unfamiliar with the procedures of large hospitals; patients with complex illnesses requiring cross-departmental visits; and elderly patients with mobility difficulties who require navigation and guidance services. The usage process can include:

[0263] Appointment and Intelligent Triage Steps: The target user inputs their symptoms via a mobile application or self-service terminal. The system uses natural language processing technology to analyze the user's input and convert it into standard medical terminology. Based on the analysis results, the system recommends suitable departments and provides detailed doctor information, such as areas of expertise, patient reviews, and available appointment times. After the target user selects a department, the system assists them in completing an online appointment and sends an appointment confirmation and reminder.

[0264] Pre-consultation and preparation steps: After appointment confirmation, the system activates the pre-consultation function, inquiring about the target individual's detailed medical history, allergies, and lifestyle habits. Based on the target individual's responses, the system generates a preliminary medical report for the doctor to review in advance. The system supports multiple input methods, including voice and text input, to accommodate different patients' usage habits.

[0265] Hospital Navigation and Queue Management Steps: Upon arrival at the hospital, the system guides the individual to their scheduled department and consultation room using indoor navigation technology (such as Bluetooth beacons or Wi-Fi positioning). The system updates the individual's queue status in real time, displays the estimated waiting time via a mobile app or terminal, and provides entertainment and health tips to alleviate waiting anxiety.

[0266] Intelligent Translation and Communication Process: During the medical visit, the system's intelligent translation module translates the patient's everyday language into medical terminology easily understood by the doctor, and vice versa. The system is specifically optimized for the diagnosis and treatment of common and chronic diseases, ensuring clear and concise communication between doctors and patients.

[0267] Post-treatment education and follow-up procedures: After the consultation, the system automatically generates personalized health education materials, including medication guidance, dietary advice, and follow-up appointment reminders. The system regularly sends health reminders and follow-up appointment suggestions, and provides real-time online consultation services to help patients answer their questions.

[0268] Based on the information processing method provided in at least one embodiment of this disclosure, at least one embodiment of this disclosure also provides an information processing apparatus. Figure 9 schematically shows a structural block diagram of the information processing apparatus provided in at least one embodiment of this disclosure.

[0269] As shown in FIG9, the information processing device 900 of this embodiment includes, for example, an information acquisition module 910, a status determination module 920, and an information provision module 930.

[0270] The information acquisition module 910 is configured to acquire the emotional information of the target object and the target scene in which the target object is located. For example, the information acquisition module 910 can implement step S210, and the specific implementation method can be referred to the relevant description of step S210, which will not be repeated here.

[0271] The state determination module 920 is configured to determine the emotional state of the target object based on the emotional information. For example, the state determination module 920 can implement step S220, and its specific implementation method can be found in the relevant description of step S220, which will not be repeated here.

[0272] The information providing module 930 is configured to provide assistance information to the target object based on the emotional state and the target scenario. For example, the information providing module 930 can implement step S230, and its specific implementation method can be found in the relevant description of step S230, which will not be repeated here.

[0273] In at least one embodiment of this disclosure, the information processing device 900 may further include, for example, a first adjustment module configured to adjust the interactive action based on the change in the emotional state of the target object in response to detecting a change in the emotional state of the target object, so that the adjusted interactive action matches the changed emotional state.

[0274] In at least one embodiment of this disclosure, the information processing device 900 may further include, for example, a data acquisition module and an information determination module. The data acquisition module is configured to acquire physiological data of the target object. The information determination module is configured to determine intervention information based on the physiological data and the emotional state. The information providing module 930 may also be configured to provide the intervention information so that the target object adjusts its health state based on the intervention information.

[0275] In at least one embodiment of this disclosure, the information processing device 900 may further include, for example, a symptom determination module configured to determine symptom information included in the first session information in response to obtaining first session information provided by the target object in the triage scenario. Specifically, the information providing module 930 may be configured to: in response to the target scenario being a triage scenario, provide recommendation information to the target object based on the emotional state and the symptom information, wherein the recommendation information includes a recommended destination.

[0276] In at least one embodiment of this disclosure, the information processing device 900 may further include, for example, a behavior acquisition module configured to acquire behavioral data of a target object. Specifically, the information providing module 930 may be configured to determine a guidance path from the current location to the medical treatment location based on the behavioral data and the emotional state.

[0277] In at least one embodiment of this disclosure, the information processing device 900 may further include, for example, an environmental information acquisition module configured to acquire environmental information for each of the at least two locations. The information providing module 930 may specifically be configured to: determine the arrival order of the at least two locations based on the environmental information; and determine a guidance path from the current location to the at least two locations based on the arrival order, the behavioral data, and the emotional state.

[0278] In at least one embodiment of this disclosure, the information processing device 900 may further include, for example, a second adjustment module configured to adjust the guidance path in response to a change in at least one of the behavioral data and the emotional state as the target object moves along the guidance path.

[0279] In at least one embodiment of this disclosure, the information processing apparatus 900 may further include, for example, an information conversion module configured to convert the target information to be converted provided by the target object in response to obtaining the target information to be converted, thereby obtaining third converted information. The information providing module 930 may further be configured to provide the third converted information.

[0280] In at least one embodiment of this disclosure, the information processing device 900 may further include, for example, a third adjustment module configured to: in the process of providing the assistance information to the target object, in response to detecting a change in the emotional state of the target object, adjust the assistance information so that the adjusted assistance information matches the changed emotional state.

[0281] In at least one embodiment of this disclosure, the information processing device 900 may further include, for example, an information sending module configured to: in response to detecting that the emotional state of the target object changes to a state indicating abnormal emotion, send a third prompt message to an associated object associated with the target object to prompt the associated object to assist the target object.

[0282] For example, the various units included in the information processing device can be implemented through hardware (e.g., circuit) modules or software modules, which will not be elaborated further. For example, these units can be implemented through a central processing unit (CPU), a graphics processing unit (GPU), a tensor processor (TPU), a field-programmable gate array (FPGA), or other forms of processing units with data processing capabilities and / or instruction execution capabilities, along with corresponding computer instructions.

[0283] It should be noted that, in the embodiments of this disclosure, the information processing device may include more or fewer circuits or units, and the connection relationship between the various circuits or units is not limited and can be determined according to actual needs. The specific configuration of each circuit is not limited; it can be constructed from analog devices, digital chips, or other suitable methods according to circuit principles.

[0284] At least one embodiment of this disclosure also provides an electronic device, including: a processing device; and a storage device, including one or more computer program instructions; for example, the one or more computer program instructions are executed by the processing device to perform the information processing method provided in any embodiment of this disclosure.

[0285] Figure 10 is a schematic diagram of the structure of an electronic device provided in at least one embodiment of this disclosure. The terminal devices in the embodiments of this disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. The electronic device shown in Figure 10 is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this disclosure.

[0286] For example, in some examples, the electronic device includes an information processing apparatus provided in any embodiment of this disclosure (e.g., the processing apparatus 1001 and output apparatus 1007 shown in FIG. 10) to provide assistance information. For example, the processing apparatus 1001 acquires the emotional information of the target object and the target scene in which the target object is located, and determines the emotional state of the target object based on the emotional information. The output apparatus 1007 provides assistance information to the target object based on the emotional state and the target scene.

[0287] For example, as shown in Figure 10, in some examples, electronic device 1000 includes a processing unit (e.g., central processing unit, graphics processor, etc.) 1001, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 1002 or a program loaded from storage device 1008 into random access memory (RAM) 1003. The RAM 1003 also stores various programs and data required for the operation of the computer system. The processing unit 1001, ROM 1002, and RAM 1003 are connected via bus 1004. Input / output (I / O) interface 1005 is also connected to bus 1004.

[0288] For example, the following components can be connected to I / O interface 1005: input devices 1006 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 1007 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1008 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009 including, for example, network interface cards such as LAN cards, modems, etc. Communication device 1009 allows electronic device 1000 to communicate wirelessly or wiredly with other devices to exchange data and perform communication processing via networks such as the Internet. Drive 1010 is also connected to I / O interface 1005 as needed. Removable media 1011, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on drive 1010 as needed so that computer programs read from them can be installed into storage device 1008 as needed. Although FIG10 shows electronic device 1000 including various devices, it should be understood that it is not required to implement or include all the devices shown. More or fewer devices may be implemented or included alternatively.

[0289] For example, the electronic device 1000 may further include a peripheral interface (not shown in the figure). This peripheral interface can be various types of interfaces, such as a USB interface, a Lightning interface, etc. The communication device 1009 can communicate wirelessly with a network and other devices, such as the Internet, an intranet, and / or a wireless network such as a cellular telephone network, a wireless local area network (LAN), and / or a metropolitan area network (MAN). Wireless communication can use any of a variety of communication standards, protocols, and technologies, including but not limited to Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), Wideband Code Division Multiple Access (W-CDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Bluetooth, Wi-Fi (e.g., based on IEEE 802.11a, IEEE 802.11b, IEEE 802.11g, and / or IEEE 802.11n standards), Voice over Internet Protocol (VoIP), Wi-MAX, protocols for email, instant messaging, and / or Short Message Service (SMS), or any other suitable communication protocol.

[0290] For example, the electronic device can be any device such as a mobile phone, tablet computer, laptop computer, e-book reader, game console, television, digital photo frame, or navigator, or any combination of electronic devices and hardware. The embodiments disclosed herein do not limit this.

[0291] For example, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For instance, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 1009, or installed from storage device 1008, or installed from ROM 1002. When the computer program is executed by processing device 1001, the information processing methods defined in the embodiments of this disclosure are performed.

[0292] It should be noted that the computer-readable medium described above in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In embodiments of this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In embodiments of this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0293] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol), and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0294] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0295] The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: acquire emotional information of a target object and a target scene in which the target object is located; determine the emotional state of the target object based on the emotional information; and provide assistance information to the target object based on the emotional state and the target scene.

[0296] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0297] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0298] In various embodiments of this disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. 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 of the foregoing.

[0299] At least one embodiment of this disclosure also provides a storage medium. FIG11 is a schematic diagram of a storage medium provided in at least one embodiment of this disclosure. For example, as shown in FIG11, the storage medium 1100 non-transitoryly stores computer-readable instructions 1101, which, when executed by a computer (including a processor), can perform the information processing method provided in any embodiment of this disclosure.

[0300] For example, the storage medium can be any combination of one or more computer-readable storage media. For instance, one computer-readable storage medium may contain computer-readable program code for an information question-and-answer method, and another computer-readable storage medium may contain computer-readable program code for an information processing method. For example, when the program code is read by a computer, the computer can execute the program code stored in the computer storage medium to perform, for example, the information processing method provided in any embodiment of this disclosure.

[0301] For example, the storage medium may include a memory card for a smartphone, a storage component for a tablet computer, a hard disk for a personal computer, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), portable compact disc read-only memory (CD-ROM), flash memory, or any combination of the above storage media, or other suitable storage media.

[0302] The following points need to be explained:

[0303] (1) The accompanying drawings of the embodiments of this disclosure only involve the structures involved in the embodiments of this disclosure. Other structures can be referred to the general design.

[0304] (2) Where there is no conflict, the embodiments of this disclosure and the features in the embodiments can be combined with each other to obtain new embodiments.

[0305] The above description is merely an exemplary embodiment of this disclosure and is not intended to limit the scope of protection of this disclosure, which is determined by the appended claims.

Claims

1. An information processing method, comprising: Obtain the emotional information of the target object and the target scene in which the target object is located; Based on the emotional information, determine the emotional state of the target object; as well as Based on the emotional state and the target scenario, provide assistance information to the target object.

2. The method of claim 1, wherein, The step of providing assistance information to the target object based on the emotional state and the target scenario includes: Based on the emotional state, determine the virtual character; Based on the emotional state and the target scene, determine the interactive actions of the virtual character; and Provide the target object with the virtual character that performs the interactive action.

3. The method of claim 2, wherein, The process of determining the virtual character based on the emotional state includes: The virtual character is determined based on the emotional state and the target object's preference information.

4. The method according to claim 2 or 3, further comprising: In response to detecting a change in the emotional state of the target object, the interactive action is adjusted based on the change in emotional state so that the adjusted interactive action matches the changed emotional state.

5. The method of claim 1, wherein, The emotional information includes information from at least two modalities; Determining the emotional state of the target object based on the emotional information includes: For each of the at least two modalities, extract features of the information of each modality to obtain the sentiment features corresponding to each modality; and A machine learning model is used to process at least two emotional features corresponding to the at least two modalities, and the emotional state of the target object is determined based on the output of the machine learning model.

6. The method of claim 1, wherein, Obtaining the target scene where the target object is located includes: Based on at least one of the target object's location information, the target object's medical status, and information obtained in response to the target object's input operation, the target scene in which the target object is located is determined. The target scenarios include one of the following scenarios: triage scenario, scenario of going to the medical treatment location, scenario of waiting for medical treatment, scenario of medical treatment, and scenario of post-medical treatment.

7. The method according to claim 1, further comprising: Obtain the physiological data of the target object; as well as Based on the physiological data and the emotional state, intervention information is determined; as well as The intervention information is provided so that the target subject can adjust its health status based on the intervention information.

8. The method according to claim 7, further comprising: Obtain at least one of the target object's medical records and lifestyle data; The determination of intervention information for the target subject based on the physiological data and the emotional state includes: The intervention information is determined based on at least one of the medical information and the lifestyle data, the physiological data, and the emotional state.

9. The method of claim 7, wherein, The determination of intervention information based on the physiological data and the emotional state includes: The physiological data and emotional state are processed using a self-attention mechanism to obtain physiological characteristics and state characteristics, respectively; and A bidirectional attention mechanism is used to process the physiological features and the state features to obtain fused features; and Based on the fused features, intervention information for the target object is determined.

10. The method according to any one of claims 1 to 9, wherein, The step of providing assistance information to the target object based on the emotional state and the target scenario includes: In response to the emotional state indicating an abnormality in the target object's emotions, the system provides the target object with first prompting information that matches both the emotional state and the target scenario, in order to regulate the target object's emotions.

11. The method of claim 1 or 10, wherein, The scenarios include patient guidance scenarios; The method further includes: In response to obtaining first session information provided by the target object in the triage scenario, the symptom information included in the first session information is determined; The step of providing assistance information to the target object based on the emotional state and the target scenario includes: In response to the target scenario being a triage scenario, recommendation information is provided to the target object based on the emotional state and the symptom information, wherein the recommendation information includes a recommended destination.

12. The method of claim 11, wherein, Based on the emotional state and symptom information, recommendation information is provided to the target individual, including: Based on the emotional state and symptom information, the target department for the target individual is determined; and Based on the emotional state and the target department, a recommended destination is determined from multiple alternative destinations. The recommended information also includes the target department.

13. The method of claim 12, wherein, Providing recommendation information to the target subject based on the emotional state and the symptom information also includes: Based on the symptom information, a specific candidate from among multiple alternative candidates included in the target department is identified. The recommendation information also includes the specified object.

14. The method of claim 1 or 10, wherein, The target scenarios include scenarios involving going to a medical treatment location; The step of providing assistance information to the target based on the emotional state and the scenario includes: In response to the scenario where the target is to go to a medical treatment location, the current location of the target object and the medical treatment location are obtained; Based on the emotional state, a guidance path is determined from the current location to the medical treatment location; and Provide the aforementioned guidance path; The method further includes adjusting the guidance path in response to changes in the emotional state as the target object moves along the guidance path.

15. The method of claim 14, further comprising: Obtain the physiological data of the target object; The step of determining the guidance path from the current location to the medical treatment location based on the emotional state includes: Based on the physiological data and the emotional state, a guidance path is determined from the current location to the medical treatment location; The method further includes adjusting the guidance path in response to changes in the physiological data as the target object moves along the guidance path.

16. The method of claim 15, further comprising: Obtain the behavioral data of the target object; The step of determining the guidance path from the current location to the medical treatment location based on the physiological data and the emotional state includes: Based on the behavioral data, the physiological data, and the emotional state, a guidance path is determined from the current location to the medical treatment location; The method further includes: adjusting the guidance path in response to changes in the behavioral data as the target object moves along the guidance path.

17. The method of claim 14, wherein, The medical treatment locations include at least two locations; the method further includes: Obtain environmental information for each of the at least two locations; The step of determining the guidance path from the current location to the medical treatment location based on the emotional state includes: Based on the environmental information, determine the arrival order of the at least two locations; and Based on the arrival order and the emotional state, a guidance path is determined from the current location to the at least two locations.

18. The method according to any one of claims 14 to 17, further comprising: In response to detecting that the target object has moved to the target location, a second prompt is provided to the target object to prompt the target object to perform the target activity at the medical treatment location.

19. The method of claim 1 or 10, wherein, The target scenarios include waiting scenarios for medical treatment; The step of providing assistance information to the target object based on the emotional state and the target scenario includes: In response to the target scenario being a waiting scenario for medical treatment and the emotional state indicating that the target object is emotionally abnormal, real-time waiting information is provided to the target object.

20. The method of claim 19, wherein, The step of providing assistance information to the target object based on the emotional state and the target scenario also includes: In response to obtaining second session information provided by the target object in the medical appointment waiting scenario, key information of the second session information is extracted; and Based on the key information and the emotional state, report information is provided to the target object.

21. The method of claim 20, further comprising: In response to the target scenario being a medical visit scenario, the report information is provided to the designated object that interacts with the target object.

22. The method of claim 1 or 10, wherein, The target scenarios include medical treatment scenarios; The step of providing assistance information to the target object based on the emotional state and the target scenario includes: In response to the target scenario being a medical visit scenario and the emotional state indicating an abnormal emotional state of the target object, a third prompt message is provided to a designated object interacting with the target object, prompting the designated object to adjust its interaction method with the target object.

23. The method of claim 1 or 10, wherein, The step of providing assistance information to the target object based on the emotional state and the target scenario includes: In response to the target scenario being a medical visit scenario and the detection of third conversation information provided by either the target object or any of the specified objects interacting with the target object, the three conversation information is transformed based on the emotional state to obtain first transformed information; and Provide the first converted information, The first converted information includes information that interprets the third session information.

24. The method of any one of claims 1-23, wherein, The step of providing assistance information to the target object based on the emotional state and the target scenario also includes: In response to the target scenario being a post-medical visit scenario and obtaining reference information provided by a designated object interacting with the target object, the reference information is transformed according to the emotional state to obtain second transformed information, the second transformed information including information interpreting the reference information.

25. The method according to any one of claims 1 to 24, further comprising: In response to obtaining the target information to be converted provided by the target object, the target information is converted to obtain the third converted information; as well as Provide the third converted information.

26. The method according to claim 1, further comprising: In the process of providing the assistance information to the target object, in response to detecting a change in the target object's emotional state, the assistance information is adjusted so that the adjusted assistance information matches the changed emotional state.

27. The method according to claim 1, further comprising: In response to detecting that the target object's emotional state changes to a state indicating abnormal emotion, a third prompt message is sent to the associated object of the target object to prompt the associated object to assist the target object.

28. An information processing apparatus, comprising: The information acquisition module is configured to acquire the emotional information of the target object and the target scene in which the target object is located; The state determination module is configured to determine the emotional state of the target object based on the emotional information. as well as The information providing module is configured to provide assistance information to the target object based on the emotional state and the target scenario.

29. An electronic device comprising: processor; as well as Memory, which includes one or more computer program instructions; The one or more computer program instructions are executed by the processor according to any one of claims 1 to 27.

30. A computer-readable storage medium, non-transitorily storing computer- readable instructions, wherein, The method of any one of claims 1 to 27 is implemented when the computer-readable instructions are executed by a processor.

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