A digital companion interaction method and system based on multi-parameter skin detection

Abstract

This invention relates to a digital companionship interaction method and system based on multi-parameter skin detection in the field of digital companionship intervention. The method includes: collecting and storing historical baseline data of a user's individual skin parameters; periodically collecting the user's current multi-parameter skin data; performing comparisons; inputting the comparison results into a preset emotion mapping model to map them to the user's emotional state; determining whether the emotional state meets preset triggering conditions; when the triggering conditions are met, proactively initiating digital companionship interaction with the user through an interactive terminal, executing preset digital companionship interaction behaviors, including sequentially outputting progressive vibration feedback, visual feedback, and audio feedback; and recording the interaction effect data. This invention achieves accurate identification of emotional states and proactive companionship through individualized baseline comparison and progressive multimodal interaction, improving empathy and adaptability.

Description

Technical Field

[0001] This invention relates to the field of digital companionship intervention, specifically to a digital companionship interaction method and system based on multi-parameter skin detection. Background Technology

[0002] With the fast pace of modern life and increasing social competition, sub-optimal emotional health is becoming increasingly prominent, making emotional health management a crucial issue in public health. One of the core needs facing current affective computing and wearable health monitoring technologies is how to objectively and continuously monitor an individual's emotional state and provide effective digital support and intervention at appropriate times.

[0003] Current technologies primarily rely on two types of approaches to achieve emotion recognition and digital companionship. One type is the subjective report method, which obtains emotional data through psychological scales or user self-assessments, such as PANAS and SCL-90. Although this method is easy to operate, it is highly dependent on the user's self-perception and expression ability, and the data is easily affected by subjective bias, social expectation effect, and recall bias, making it difficult to obtain objective, quantitative, and continuous tracking results. The other type is the physiological signal monitoring method, where existing wearable devices mostly collect data through single sensors such as heart rate variability (HRV), electrical skin activity (EDA), or accelerometers, and infer emotional state through threshold judgment or machine learning models.

[0004] However, emotional responses involve the coordinated changes of multiple systems, including the autonomic nervous system, endocrine system, and peripheral circulation. A single physiological signal, under the interference of motion artifacts, environmental temperature and humidity, and individual baseline differences, has a limited signal-to-noise ratio and cannot comprehensively and robustly reflect the true fluctuations of emotional state. In addition, most existing digital companionship solutions adopt a passive response architecture, requiring users to manually trigger the application or wake it up by voice to receive text comfort, static music push, or simple notification reminders. This not only makes it easy to miss the best time window for emotional relief, but also results in a single form of interaction, lacking multimodal coordination of touch, vision, and hearing, making it difficult to form an immersive emotional transmission and limiting the actual comforting effect.

[0005] In view of this, there is an urgent need in the field for a technical solution that can objectively and continuously monitor multiple skin parameters and actively trigger multimodal immersive companionship interaction when abnormal emotions are detected, so as to overcome problems such as subjective self-evaluation bias, single signal limitation, passive response lag and weak companionship experience, and achieve accurate perception and timely intervention of the user's emotional state. Summary of the Invention

[0006] To address the shortcomings of the existing technology, this invention provides a digital companion interaction method and system based on multi-parameter skin detection.

[0007] The technical solution of this invention is as follows: In a first aspect, the present invention provides a digital companion interaction method based on multi-parameter skin detection, comprising: Step S1: Under the user's normal emotional state, collect and store the user's individual skin multi-parameter historical baseline, including skin blood oxygen saturation, skin hydration index and skin perfusion index; Step S2: Periodically collect the user's current skin multi-parameter data; Step S3: Compare the current skin multi-parameter data with the user's individual historical baseline parameters, and calculate the deviation of blood oxygen saturation ΔSpO2, the deviation of hydration ΔH, and the deviation of perfusion index ΔPI respectively. Step S4: Input the comparison results into the preset emotion mapping model and map them to the user's emotional state based on the preset association rules; Step S5: Determine whether the emotional state meets the preset triggering conditions; the triggering conditions include a dynamic threshold that is adaptively adjusted based on the user's historical emotional data and interaction feedback results; Step S6: When the triggering condition is met, the system actively initiates a digital companionship interaction with the user through the interactive terminal and executes a preset digital companionship interaction behavior. The digital companionship interaction behavior includes progressive vibration feedback, visual feedback and audio feedback output sequentially along the time sequence. Step S7: Record the interaction effect data for this interaction, and adaptively update the dynamic threshold and / or the individual user's historical baseline parameters based on the interaction effect data.

[0008] As a preferred method, in step S4, the preset association rules include: Step S41: When the hydration deviation ΔH is lower than a preset first threshold, it is identified as a state of stress. Step S42: When the hydration deviation ΔH is lower than a preset second threshold and the perfusion index deviation ΔPI is lower than a preset third threshold, it is identified as a state of fatigue. Step S43: When the blood oxygen saturation deviation ΔSpO2 is lower than the preset fourth threshold, it is identified as a hypoxic emotional state.

[0009] As a preferred method, in step S6, the progressive vibration feedback sequentially includes: low-frequency vibration to initially establish tactile contact, vibration gradually increasing and combined with visual feedback, maintaining medium-intensity vibration and synchronous audio feedback, and vibration decreasing and stopping while outputting comforting voice.

[0010] As a preferred method, in steps S1 and S2, the multiple skin parameters are acquired through a skin detection module. The skin detection module includes a five-wavelength light source and a dual photodetector structure. The five-wavelength light source synchronously emits light signals at five wavelengths: 365nm, 660nm, 940nm, 1050nm, and 1450nm. The dual photodetector includes a first photodetector disposed on the same side of the skin detection module and a second photodetector disposed on the other side. The first photodetector acquires reflected signals at wavelengths of 365nm, 660nm, and 940nm, and the second photodetector acquires reflected signals at wavelengths of 1050nm and 1450nm. An isolation structure for physically blocking direct light crosstalk is provided between the first photodetector and the second photodetector.

[0011] As a preferred method, in step S1, the individual user's historical baseline parameters are stored in a local trusted storage area and are only accessible after user authorization.

[0012] As a preferred method, in step S6, when it is detected that the user is in a negative emotional state, a reminder message is sent to a designated contact associated with the user.

[0013] As a preferred method, in step S6, the digital companion interaction behavior further includes: pushing personalized music, visual images, or voice content to the user based on the current emotional state type.

[0014] As a preferred method, in step S3, the skin perfusion index is calculated based on the ratio of the AC component to the DC component of the reflected signal from the second photodetector.

[0015] Secondly, the present invention provides a digital companion interaction system based on multi-parameter skin detection, employing the aforementioned digital companion interaction method based on multi-parameter skin detection, the system comprising: The skin detection module is used to collect multi-parameter data of the user's skin, including skin blood oxygen saturation, skin hydration index, and skin perfusion index. The storage module is used to store the user's individual historical baseline parameters; The status analysis module is used to read the historical baseline parameters from the storage module, compare the current skin multi-parameter data with the historical baseline parameters, and calculate the deviation of blood oxygen saturation ΔSpO2, the deviation of hydration ΔH and the deviation of perfusion index ΔPI respectively. The emotion recognition module is used to map the deviation amount to an emotional state based on preset association rules; The trigger judgment module is used to determine whether the emotional state meets the preset trigger conditions. The trigger conditions include a dynamic threshold that is adaptively adjusted based on the user's historical emotional data and interaction feedback results. The interactive control module is used to initiate digital companionship interaction with the user through the interactive terminal when the triggering conditions are met, and to execute progressive vibration feedback, visual feedback and audio feedback output sequentially along the time sequence. The feedback update module is used to record the interaction effect data and adaptively update the dynamic threshold and / or the historical benchmark parameters based on the interaction effect data.

[0016] As a preferred embodiment, the interactive terminal includes at least one of wearable devices, mobile terminals, and smart home devices, and the interactive terminal is configured with a vibration feedback unit, a display unit, and an audio output unit.

[0017] According to the above-described solution, the beneficial effects of this invention are as follows: This invention establishes a user-specific multi-parameter historical baseline for skin and uses this baseline as a comparison reference. This solution transforms emotion recognition from traditional group model prediction to individual bias analysis, enabling users with different physiological baselines to obtain emotion assessment results corresponding to their normal state, significantly improving the individual adaptability of the recognition results. At the same time, by using multi-parameter joint comparison of blood oxygen saturation, hydration index, and perfusion index, compared with single HRV or EDA signal monitoring, it can cross-validate changes in emotional state from different dimensions of skin microcirculation, effectively suppressing misjudgments caused by motion artifacts and environmental interference, and improving the objectivity and robustness of emotion recognition.

[0018] Regarding the triggering mechanism, the deviation is directly mapped to emotional state through preset association rules. An adaptive dynamic threshold based on historical emotional data and interactive feedback is introduced, enabling the system to proactively initiate companionship only when the user truly needs intervention. This avoids frequent accidental or missed triggers caused by fixed thresholds, achieving personalized convergence of the triggering strategy. At the interaction execution level, a digital companionship behavior employing progressive vibration feedback, visual feedback, and audio feedback output sequentially along a time sequence is used. Compared to traditional text reminders or static audio pushes, this creates a coherent immersive perception across tactile, visual, and auditory channels, more closely resembling the emotional delivery rhythm of a real hug, thereby enhancing the empathic effect and emotional soothing efficiency of digital companionship.

[0019] Furthermore, by recording interaction effect data and adaptively updating dynamic thresholds and / or individual historical benchmarks, the system forms a complete closed loop from data collection, state recognition, proactive triggering to effect feedback, enabling emotion monitoring and companionship strategies to be continuously optimized as the user's state changes, achieving adaptive improvement during long-term operation. Attached Figure Description

[0020] Figure 1 This is an overall flowchart of a digital companion interaction method based on multi-parameter skin detection according to the present invention.

[0021] Figure 2 This is a flowchart of the emotion mapping model of the present invention.

[0022] Figure 3 This is a timing diagram of the progressive vibration feedback in this invention. Detailed Implementation

[0023] To better understand the purpose, technical solution, and technical effects of this invention, the invention will be further explained and described below in conjunction with the accompanying drawings and embodiments. It should be noted that similar reference numerals and letters in the following drawings indicate similar items; therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. It is also stated that the embodiments described below are only for explaining this invention and are not intended to limit this invention.

[0024] It should be noted that when a component is referred to as "fixed to" or "set on" another component, it can be directly on the other component or there may be an intermediate component. When a component is referred to as "connected to" another component, it can be directly connected to the other component or there may be an intermediate component.

[0025] The indicated orientation or positional relationship is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product is usually placed when in use, or the orientation or positional relationship in which a person skilled in the art would normally understand it, or the orientation or positional relationship in which the product is usually placed when in use. It is only for the purpose of facilitating the description of this application and simplifying the description, and is not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Example

[0026] Reference Figures 1-3 A digital companion interaction method based on multi-parameter skin detection includes: Step S1: Establish individual user historical baseline parameters When a user first wears a wearable device (such as a smart bracelet or ring), the system guides the user into a relaxed state, during which multiple skin parameters are continuously collected for 30 minutes.

[0027] The skin parameters include skin oxygen saturation, skin hydration index, and skin perfusion index.

[0028] After data collection is completed, the system calculates the stable average value of each parameter under relaxed conditions, establishes the historical baseline parameters for each user, and stores them encrypted in a local trusted storage area.

[0029] The skin detection module includes a five-wavelength light source and a dual photodetector structure. The five-wavelength light source synchronously emits light signals at five wavelengths: 365 nm, 660 nm, 940 nm, 1050 nm, and 1450 nm.

[0030] Among them, the 365 nm ultraviolet band is used to detect the scattering characteristics of the skin surface and to help correct the impact of differences in epidermal thickness and skin color on subsequent calculations; the 660 nm red light and 940 nm near-infrared light are used for traditional pulse oximetry calculations, and the skin oxygen saturation is calculated based on the difference in absorbance between hemoglobin and oxyhemoglobin at the two wavelengths; 1050 nm and 1450 nm are in the strong absorption band of skin moisture, and the skin hydration index is inferred by detecting the degree of attenuation of reflected light.

[0031] The dual photodetector includes a first photodetector located on the same side of the skin detection module and a second photodetector located on the other side.

[0032] The first photodetector collects reflected signals at wavelengths of 365 nm, 660 nm, and 940 nm to calculate skin oxygen saturation; the second photodetector collects reflected signals at wavelengths of 1050 nm and 1450 nm to calculate skin hydration index and skin perfusion index.

[0033] An isolation structure is provided between the two detectors. The isolation structure is made of light-absorbing material or physical light-blocking plate to physically block direct light crosstalk and improve the signal-to-noise ratio.

[0034] The historical baseline parameters include baseline values ​​for skin oxygen saturation, skin hydration index, and skin perfusion index.

[0035] The local trusted storage area is a built-in encrypted security chip in the device or a storage partition protected by hardware isolation. It can only be accessed by subsequent steps after the user has identified the user through biometrics or authorized the user with a password.

[0036] Step S2: Periodically collect current skin multi-parameter data After entering the daily monitoring mode, the skin detection module collects the user's current skin multi-parameter data according to the preset cycle (default every 5 minutes, configurable), including the current skin blood oxygen saturation, the current skin hydration index, and the current skin perfusion index.

[0037] Step S3: Individualized bias comparison The status analysis module reads the user's individual historical baseline parameters from the local trusted storage area, compares the three currently collected parameters with the historical baseline item by item, and calculates the deviation of blood oxygen saturation ΔSpO2, the deviation of hydration ΔH, and the deviation of perfusion index ΔPI respectively.

[0038] The deviation is the difference or relative rate of change between the current parameter value and the corresponding historical benchmark value.

[0039] The skin perfusion index PI is calculated based on the ratio of the AC component to the DC component of the reflected signal from the second photodetector, using the following formula: PI = AC / DC × 100%; Among them, the AC component reflects the pulsatile changes in arterial blood volume, and the DC component reflects the constant light absorption of tissue and venous blood. The ratio can effectively quantify changes in peripheral blood perfusion, providing a new quantitative dimension for emotion recognition.

[0040] Step S4: Map sentiment states based on preset association rules The emotion recognition module inputs the deviation obtained in step S3 into a preset emotion mapping model, and maps it to the user's emotional state based on preset association rules. The specific mapping rules are as follows: When the hydration deviation ΔH is lower than a preset first threshold, the user is identified as being in a state of stress. When the hydration deviation ΔH is lower than a preset second threshold and the irrigation index deviation ΔPI is lower than a preset third threshold, the user is identified as being in a state of fatigue. When the blood oxygen saturation deviation ΔSpO2 is lower than the preset fourth threshold, the user is identified as being in a hypoxic emotional state.

[0041] The initial value of the above threshold can be set based on population statistics experience, and then adaptively adjusted in step S7.

[0042] Step S5: Dynamic threshold trigger judgment The trigger judgment module determines whether the emotional state identified in step S4 meets the preset trigger conditions. These trigger conditions are not fixed constants, but rather dynamic thresholds that are adaptively adjusted based on the user's historical emotional data and interaction feedback results. When the deviation meets the current dynamic threshold, the trigger condition is deemed met, and the system proceeds to step S6; otherwise, it returns to step S2 for periodic monitoring.

[0043] Specifically, let the pressure threshold be updated after the nth interaction as follows: ; Where En is the score for the interaction effect, with a value range of 0 to 1. 1 indicates that the user's emotional index has fully recovered to the baseline range after the interaction, and 0 indicates that there is no improvement. The learning rate is set to 0.05 by default.

[0044] When the interaction effect is consistently better than 0.5, that is , threshold As the stress level gradually decreases, the system becomes more sensitive to triggering stress states; when the interaction is ineffective, i.e. At that time, the threshold Adjust the setting appropriately to reduce subsequent false triggers and avoid excessively disturbing users.

[0045] Step S6: Perform digital companion interaction behavior When the triggering conditions are met, the interactive control module proactively initiates digital companionship interaction with the user through the interactive terminal.

[0046] The digital companionship interaction includes progressive vibration feedback, visual feedback, and audio feedback output sequentially along a time sequence to simulate the sensory experience of a hug.

[0047] The specific timing sequence is as follows: Phase 1 (0–2 seconds): Low-frequency vibration phase. The vibration feedback unit of the interactive terminal outputs a vibration with a frequency of 5 Hz and an intensity of 0.5 g for 2 seconds, while simultaneously displaying a preparatory animation (such as the screen gradually brightening or a virtual arm opening), initially establishing tactile contact and avoiding abruptness.

[0048] The second stage (2–4 seconds): Gradual empathy stage. The vibration frequency linearly increases from 5 Hz to 10 Hz, and the vibration intensity increases from 0.5 g to 1.5 g, while a virtual hugging scene (such as an animation of two arms embracing) is played on the display unit simultaneously to create an atmosphere of heightened emotional engagement.

[0049] Phase 3 (4–9 seconds): Stabilization and reassurance phase. Maintain a vibration frequency of 8 Hz and an intensity of 1.2 g, while the audio output unit plays white noise or soothing audio (such as ocean waves or rain) for 5 seconds to provide the user with a stable sense of security.

[0050] Phase 4 (9–11 seconds): Gentle Closing Phase. The vibration intensity gradually decreases until it stops, and the audio output unit plays a pre-recorded comforting voice (such as "I am by your side") for 2 seconds, completing the emotional transmission loop.

[0051] In addition, during the execution of step S6, the system can also perform the following auxiliary interactions in parallel: when the system detects that the user is in a negative emotional state, it sends a reminder message to the user's pre-specified associated contacts; at the same time, based on the current emotional state type, it pushes personalized music, visual images or voice content to the user to enrich the companionship dimension.

[0052] Step S7: Closed-loop feedback update After the interaction is completed, the feedback update module records the interaction effect data, including changes in multiple user skin parameters before and after the interaction, and whether the user manually terminated the interaction. Based on the interaction effect data, the system adaptively updates the dynamic threshold and / or the user's individual historical baseline parameters. For example, if the user's emotional index recovers to the baseline range within 10 minutes after the interaction, the interaction is marked as effective, and the corresponding threshold is appropriately lowered to improve subsequent sensitivity; if it does not recover, the threshold is raised to avoid excessive disturbance. After the update is completed, the system returns to step S2 to continue periodic monitoring, forming a complete data flow closed loop.

[0053] A digital companion interaction system based on multi-parameter skin detection includes the following functional modules: The skin detection module is used to collect multi-parameter data of the user's skin, including skin blood oxygen saturation, skin hydration index, and skin perfusion index. The storage module is used to store the user's individual historical baseline parameters; The status analysis module is used to read the historical baseline parameters from the storage module, compare the current skin multi-parameter data with the historical baseline parameters, and calculate the deviation of blood oxygen saturation ΔSpO2, the deviation of hydration ΔH and the deviation of perfusion index ΔPI respectively. The emotion recognition module is used to map the deviation amount to an emotional state based on preset association rules; The trigger judgment module is used to determine whether the emotional state meets the preset trigger conditions. The trigger conditions include a dynamic threshold that is adaptively adjusted based on the user's historical emotional data and interaction feedback results. The interactive control module is used to initiate digital companionship interaction with the user through the interactive terminal when the triggering conditions are met, and to execute progressive vibration feedback, visual feedback and audio feedback output sequentially along the time sequence. The feedback update module is used to record the interaction effect data and adaptively update the dynamic threshold and / or the historical benchmark parameters based on the interaction effect data.

[0054] The interactive terminal includes at least one of wearable devices, mobile terminals, and smart home devices, and is equipped with a vibration feedback unit, a display unit, and an audio output unit.

[0055] In one deployment scheme, wearable devices (such as smart bracelets and rings) integrate skin detection modules, vibration feedback units, and display units, and are responsible for data collection and basic interaction; mobile terminals (such as smartphones) serve as auxiliary interaction platforms, providing rich visual animations and audio resources; smart home devices (such as smart speakers and smart screens) can collaboratively output companion content when the user is at home.

[0056] Each terminal connects via Bluetooth, Wi-Fi, or near-field communication, and the interactive control module uniformly schedules and executes digital companion interaction behaviors.

[0057] In another deployment scheme, the system uses only a smartphone as the interaction terminal. The skin detection module is implemented through an external ring accessory. The collected data is compared, mapped and triggered by the mobile application, and the phone's built-in motor, screen and speaker output progressive vibration, visual and audio feedback.

[0058] The local trusted storage area is implemented using hardware encryption or trusted execution environment (TEE) technology. The status analysis module and feedback update module can only access the historical baseline parameters after the user has authorized the data through biometric identification or password.

[0059] In addition, when the system detects that a user is in a negative emotional state, it can send a reminder message to the emergency contact that the user has pre-designated. The contact information is also stored locally, and the sending action requires authorization confirmation from the user when using the system for the first time.

[0060] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0061] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A digital companion interaction method based on multi-parameter skin detection, characterized in that, include: Step S1: Under the user's normal emotional state, collect and store the user's individual skin multi-parameter historical baseline, including skin blood oxygen saturation, skin hydration index and skin perfusion index; Step S2: Periodically collect the user's current skin multi-parameter data; Step S3: Compare the current skin multi-parameter data with the user's individual historical baseline parameters, and calculate the deviation of blood oxygen saturation ΔSpO2, the deviation of hydration ΔH, and the deviation of perfusion index ΔPI respectively. Step S4: Input the comparison results into the preset emotion mapping model and map them to the user's emotional state based on the preset association rules; Step S5: Determine whether the emotional state meets the preset triggering conditions; The triggering conditions include dynamic thresholds that are adaptively adjusted based on the user's historical emotion data and interaction feedback results; Step S6: When the triggering condition is met, the system actively initiates a digital companionship interaction with the user through the interactive terminal and executes a preset digital companionship interaction behavior. The digital companionship interaction behavior includes progressive vibration feedback, visual feedback and audio feedback output sequentially along the time sequence. Step S7: Record the interaction effect data for this interaction, and adaptively update the dynamic threshold and / or the individual user's historical baseline parameters based on the interaction effect data.

2. The digital companion interaction method based on multi-parameter skin detection according to claim 1, characterized in that, In step S4, the preset association rules include: Step S41: When the hydration deviation ΔH is lower than a preset first threshold, it is identified as a state of stress. Step S42: When the hydration deviation ΔH is lower than a preset second threshold and the perfusion index deviation ΔPI is lower than a preset third threshold, it is identified as a state of fatigue. Step S43: When the blood oxygen saturation deviation ΔSpO2 is lower than the preset fourth threshold, it is identified as a hypoxic emotional state.

3. The digital companion interaction method based on multi-parameter skin detection according to claim 1, characterized in that, In step S6, the progressive vibration feedback sequentially includes: low-frequency vibration to initially establish tactile contact, vibration gradually increasing and combined with visual feedback, maintaining medium-intensity vibration and synchronous audio feedback, and vibration decreasing and stopping while outputting comforting voice.

4. The digital companion interaction method based on multi-parameter skin detection according to claim 1, characterized in that, In steps S1 and S2, the multiple skin parameters are acquired through a skin detection module. The skin detection module includes a five-wavelength light source and a dual photodetector structure. The five-wavelength light source synchronously emits light signals at five wavelengths: 365nm, 660nm, 940nm, 1050nm, and 1450nm. The dual photodetector includes a first photodetector located on the same side of the skin detection module and a second photodetector located on the other side. The first photodetector acquires reflected signals at wavelengths of 365nm, 660nm, and 940nm, and the second photodetector acquires reflected signals at wavelengths of 1050nm and 1450nm. An isolation structure for physically blocking direct light crosstalk is provided between the first photodetector and the second photodetector.

5. The digital companion interaction method based on multi-parameter skin detection according to claim 1, characterized in that, In step S1, the individual user's historical baseline parameters are stored in a local trusted storage area and are only accessible after user authorization.

6. The digital companion interaction method based on multi-parameter skin detection according to claim 1, characterized in that, In step S6, when a user is identified as being in a negative emotional state, a reminder message is sent to a designated contact associated with the user.

7. The digital companion interaction method based on multi-parameter skin detection according to claim 1, characterized in that, In step S6, the digital companion interaction behavior also includes: pushing personalized music, visual images or voice content to the user based on the current emotional state type.

8. The digital companion interaction method based on multi-parameter skin detection according to claim 4, characterized in that, In step S3, the skin perfusion index is calculated based on the ratio of the AC component to the DC component of the reflected signal from the second photodetector, PI = AC / DC × 100%.

9. A digital companion interaction system based on multi-parameter skin detection, characterized in that, The system employs a digital companion interaction method based on multi-parameter skin detection as described in any one of claims 1-8, wherein the system comprises: The skin detection module is used to collect multi-parameter data of the user's skin, including skin blood oxygen saturation, skin hydration index, and skin perfusion index. The storage module is used to store the user's individual historical baseline parameters; The status analysis module is used to read the historical baseline parameters from the storage module, compare the current skin multi-parameter data with the historical baseline parameters, and calculate the deviation of blood oxygen saturation ΔSpO2, the deviation of hydration ΔH and the deviation of perfusion index ΔPI respectively. The emotion recognition module is used to map the deviation amount to an emotional state based on preset association rules; The trigger judgment module is used to determine whether the emotional state meets the preset trigger conditions. The trigger conditions include a dynamic threshold that is adaptively adjusted based on the user's historical emotional data and interaction feedback results. The interactive control module is used to initiate digital companionship interaction with the user through the interactive terminal when the triggering conditions are met, and to execute progressive vibration feedback, visual feedback and audio feedback output sequentially along the time sequence. The feedback update module is used to record the interaction effect data and adaptively update the dynamic threshold and / or the historical benchmark parameters based on the interaction effect data.

10. A digital companion interaction system based on multi-parameter skin detection according to claim 9, characterized in that, The interactive terminal includes at least one of wearable devices, mobile terminals, and smart home devices, and is equipped with a vibration feedback unit, a display unit, and an audio output unit.

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