Information processing method of massage equipment and massage equipment

Abstract

The invention provides an information processing method of massage equipment and the massage equipment, and the method comprises the steps: collecting biological sign data of a target user using the massage equipment in real time through a plurality of sensors on the massage equipment, the biological sign data comprising actual sign values of multiple dimensions; determining the physical state of the target user according to the biological sign data of the target user; if the body state of the target user is a relaxed state, a target alpha-wave music track is determined from an alpha-wave music track library stored in a storage module of the massage equipment, the target alpha-wave music track is played, the alpha-wave music track library comprises a plurality of alpha-wave music tracks, and the alpha-wave music tracks are used for playing the target alpha-wave music track. The frequency of each alpha wave sound music is matched with the frequency of the alpha brain wave of the human brain. The user can be helped to stably enter the sleep state, and the experience of the user using the massage equipment is greatly improved.

Description

Technical Field

[0001] This application relates to the field of massage equipment technology, and more specifically, to an information processing method for a massage device and a massage device. Background Technology

[0002] As a health device, massage chairs can relieve fatigue and relax the mind and body by massaging multiple parts of the body, and are therefore popular with users and widely used in various scenarios.

[0003] Currently, massage chairs primarily focus on massage functionality. For example, they offer a variety of flexible massage techniques to suit different user needs. However, current massage chairs have relatively limited functionality and certain limitations. Summary of the Invention

[0004] The purpose of this application is to address the shortcomings of the prior art by providing an information processing method and a massage device, thereby solving the problem that massage chairs in the prior art have relatively limited functions.

[0005] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows: In a first aspect, this application provides an information processing method for a massage device, applied to the massage device, the method comprising: The massage device collects biometric data of the target user in real time through multiple sensors, and the biometric data includes actual biometric values ​​in multiple dimensions. The target user's physical condition is determined based on their biometric data. If the target user's physical state is relaxed, a target alpha wave music track is determined from the alpha wave music track library stored in the storage module of the massage device, and the target alpha wave music track is played. The alpha wave music track library includes multiple alpha wave music tracks, and the frequency of each alpha wave music track matches the frequency of the human brain's alpha brainwaves.

[0006] As one possible implementation, determining the target user's physical condition based on the target user's biometric data includes: Obtain the baseline vital signs data of the predetermined target user, wherein the baseline vital signs data includes baseline vital signs values ​​in multiple dimensions; Based on the actual vital sign values ​​and baseline vital sign values ​​for each dimension, determine the corresponding deviation information for each dimension; The target user's physical condition is determined based on the deviation information corresponding to each dimension.

[0007] As one possible implementation, the process for determining the baseline vital signs data includes: Acquire sample vital sign data of the target user at multiple time points within a target time period, wherein the target user is in a relaxed state during the target time period, and each sample vital sign data includes sample vital sign values ​​of multiple dimensions. Based on the sample vital sign values ​​of each dimension at each time point, the baseline vital sign values ​​of each dimension are determined.

[0008] As one possible implementation, determining the target user's physical state based on the deviation information corresponding to each dimension includes: Based on the deviation information and state thresholds corresponding to each dimension, determine the candidate states for each dimension. If the candidate states corresponding to each dimension are the same, then the candidate state is taken as the physical state of the target user. If the candidate states for each dimension are different, then the number of each candidate state is determined, and the candidate state with the most numbers is taken as the target user's physical state.

[0009] As one possible implementation, determining the target user's physical condition based on the target user's biometric data includes: The actual vital sign values ​​of each dimension in the biological vital sign data are standardized to obtain standardized vital sign values ​​for each dimension. Based on the standardized phenotypic values ​​of each dimension and the membership functions of each level of each dimension, the membership degree of the target user at each level of each dimension is determined, wherein each membership function is used to characterize the degree to which the target user belongs to the level corresponding to the membership function. Based on the membership degree of the target user at each level in each dimension and multiple preset fuzzy rules, the trigger intensity of the target user under each fuzzy rule is determined. Each fuzzy rule includes: fuzzy condition, physical state and score value. The fuzzy condition includes a level in each dimension, and the levels in each dimension are connected by logical symbols. The target score is determined based on the trigger intensity of the target user under each fuzzy rule and the score value corresponding to each fuzzy rule. The target user's physical condition is determined based on the target score and the preset score range corresponding to each physical condition.

[0010] As one possible implementation, determining the trigger strength of the target user under each fuzzy rule based on the target user's membership degree at each level of each dimension and multiple preset fuzzy rules includes: Obtain the target level of each dimension corresponding to the fuzzy conditions in the current fuzzy rule; Extract the membership degree of the target user at each level of each dimension; The minimum value among the membership degrees of all extracted target levels is taken as the trigger strength of the target user under the current fuzzy rule.

[0011] As one possible implementation, determining the target score based on the trigger intensity of the target user under each fuzzy rule and the corresponding score value of each fuzzy rule includes: Calculate the product of the trigger strength and the score value of the fuzzy rule under each fuzzy rule to obtain the sub-score value corresponding to each fuzzy rule; Calculate the first sum of the sub-scores corresponding to all fuzzy rules; Calculate the second sum of the trigger strengths under all fuzzy rules; Calculate the quotient of the first sum divided by the second sum, and use the quotient as the target score.

[0012] As one possible implementation, determining the target alpha wave music track from the alpha wave music track library stored in the storage module of the massage device includes: Obtain the target user's track preference information; Based on the target user's track preference information, the target alpha wave music track is determined from the alpha wave music track library stored in the storage module of the massage device.

[0013] As one possible implementation, the method further includes: Based on the sleep vital signs data of the target user, the sleep index of the target user is determined, and the sleep index includes: sleep latency index, sleep depth index and sleep continuity index; Based on the sleep index, the type of sleep disorder of the target user is determined; Based on the type of sleep disorder, determine at least one target sleep stage to be massaged and the corresponding massage techniques for each target sleep stage. The system collects the target user's biometric data in real time. If the target user is determined to be in the target sleep stage based on the biometric data, the system performs a massage on the target user according to the massage technique corresponding to the target sleep stage.

[0014] Secondly, this application provides an information processing device for a massage device, applied to the massage device, the device comprising: The acquisition module is used to collect biometric data of the target user using the massage device in real time through multiple sensors on the massage device. The biometric data includes actual biometric values ​​in multiple dimensions. The determination module is used to determine the physical condition of the target user based on the target user's biometric data; The playback module is used to determine a target alpha wave music track from the alpha wave music track library stored in the storage module of the massage device when the target user's body is in a relaxed state, and to play the target alpha wave music track. The alpha wave music track library includes multiple alpha wave music tracks, and the frequency of each alpha wave music track matches the frequency of the human brain's alpha brainwaves.

[0015] As one possible implementation, the determining module is specifically used for: Obtain the baseline vital signs data of the predetermined target user, wherein the baseline vital signs data includes baseline vital signs values ​​in multiple dimensions; Based on the actual vital sign values ​​and baseline vital sign values ​​for each dimension, determine the corresponding deviation information for each dimension; The target user's physical condition is determined based on the deviation information corresponding to each dimension.

[0016] As one possible implementation, the process for determining the baseline vital signs data includes: Acquire sample vital sign data of the target user at multiple time points within a target time period, wherein the target user is in a relaxed state during the target time period, and each sample vital sign data includes sample vital sign values ​​of multiple dimensions. Based on the sample vital sign values ​​of each dimension at each time point, the baseline vital sign values ​​of each dimension are determined.

[0017] As one possible implementation, the determining module is specifically used for: Based on the deviation information and state thresholds corresponding to each dimension, determine the candidate states for each dimension. If the candidate states corresponding to each dimension are the same, then the candidate state is taken as the physical state of the target user. If the candidate states for each dimension are different, then the number of each candidate state is determined, and the candidate state with the most numbers is taken as the target user's physical state.

[0018] As one possible implementation, the determining module is specifically used for: The actual vital sign values ​​of each dimension in the biological vital sign data are standardized to obtain standardized vital sign values ​​for each dimension. Based on the standardized phenotypic values ​​of each dimension and the membership functions of each level of each dimension, the membership degree of the target user at each level of each dimension is determined, wherein each membership function is used to characterize the degree to which the target user belongs to the level corresponding to the membership function. Based on the membership degree of the target user at each level in each dimension and multiple preset fuzzy rules, the trigger intensity of the target user under each fuzzy rule is determined. Each fuzzy rule includes: fuzzy condition, physical state and score value. The fuzzy condition includes a level in each dimension, and the levels in each dimension are connected by logical symbols. The target score is determined based on the trigger intensity of the target user under each fuzzy rule and the score value corresponding to each fuzzy rule. The target user's physical condition is determined based on the target score and the preset score range corresponding to each physical condition.

[0019] As one possible implementation, the determining module is specifically used for: Obtain the target level of each dimension corresponding to the fuzzy conditions in the current fuzzy rule; Extract the membership degree of the target user at each level of each dimension; The minimum value among the membership degrees of all extracted target levels is taken as the trigger strength of the target user under the current fuzzy rule.

[0020] As one possible implementation, the determining module is specifically used for: Calculate the product of the trigger strength and the score value of the fuzzy rule under each fuzzy rule to obtain the sub-score value corresponding to each fuzzy rule; Calculate the first sum of the sub-scores corresponding to all fuzzy rules; Calculate the second sum of the trigger strengths under all fuzzy rules; Calculate the quotient of the first sum divided by the second sum, and use the quotient as the target score.

[0021] As one possible implementation, the playback module is specifically used for: Obtain the target user's track preference information; Based on the target user's track preference information, the target alpha wave music track is determined from the alpha wave music track library stored in the storage module of the massage device.

[0022] As one possible implementation, the determining module is further configured to: Based on the sleep vital signs data of the target user, the sleep index of the target user is determined, and the sleep index includes: sleep latency index, sleep depth index and sleep continuity index; Based on the sleep index, the type of sleep disorder of the target user is determined; Based on the type of sleep disorder, determine at least one target sleep stage to be massaged and the corresponding massage techniques for each target sleep stage. The system collects the target user's biometric data in real time. If the target user is determined to be in the target sleep stage based on the biometric data, the system performs a massage on the target user according to the massage technique corresponding to the target sleep stage.

[0023] Thirdly, this application provides a massage device, including: a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the massage device is running, the processor executes the machine-readable instructions to perform the steps of the information processing method of the massage device as described in the first aspect above.

[0024] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the information processing method for the massage device as described in the first aspect above.

[0025] The information processing method and massage device provided in this application, by collecting actual vital sign values ​​of the target user in multiple dimensions, can accurately determine the target user's physical state based on these values. When the target user's physical state is relaxed, a target alpha wave music track is selected from the alpha wave music track library of the massage device and played. Since the brainwaves of a person in a relaxed state are mainly alpha waves, this application, by accurately identifying the target user's physical state and playing alpha wave music tracks that match the frequency of alpha waves in the brainwaves when the target user is relaxed, enables the brain's alpha waves to resonate with the alpha waves of the music track. Simultaneously, the soothing characteristics, psychological suggestion, and tranquil atmosphere created by the alpha wave music itself are conducive to the brain spontaneously generating more alpha waves, creating an auditory environment for the user to focus on inner peace or relaxation, thereby enabling the user to achieve a deeper state of relaxation. This, in turn, helps the user smoothly enter a sleep state, greatly enhancing the user's experience of using the massage device. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A schematic diagram of the structure of the massage device provided in this application; Figure 2 A flowchart illustrating the information processing method for the massage device provided in this application; Figure 3 A schematic flowchart illustrating the method for determining body state in the information processing of the massage device provided in this application; Figure 4 A schematic diagram illustrating the specific process of determining the body state using the information processing method for the massage device provided in this application; Figure 5 Another flowchart illustrating the determination of body state in the information processing method for the massage device provided in this application; Figure 6 A schematic diagram of the massage control process for the information processing method of the massage device provided in this application; Figure 7 A modular structure diagram of the information processing device for the massage equipment provided in this application; Figure 8 This is another structural schematic diagram of the massage device 80 provided in an embodiment of this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0029] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0030] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0031] Current massage chairs primarily focus on massage functionality. This function is relatively singular and has certain limitations.

[0032] This application addresses the aforementioned issues by providing an information processing method for a massage device. This method monitors the user's physical state in real time and plays corresponding alpha wave music tracks when the user is in a relaxed state. Since the brainwaves of a person in a relaxed state are primarily alpha waves, playing alpha wave music tracks in this state allows the brain's alpha waves to resonate with the alpha waves of the music, thereby enabling the user to achieve a deeper state of relaxation. This, in turn, helps the user smoothly enter a sleep state, greatly enhancing the user experience.

[0033] The massage device mentioned in the following embodiments of this application may specifically be a massage chair or other massage devices, such as a massage bed or massager.

[0034] Figure 1 A schematic diagram of the structure of the massage device provided in this application, such as... Figure 1 As shown, the massage device may include a controller and multiple sensors, which may include, for example, a bio-radar sensor and a pressure sensor. Each sensor can be communicatively connected to the controller, sending the collected signals to the controller. Based on the data collected by each sensor, the controller outputs a suitable alpha wave music track to the user using the method of the embodiments of this application.

[0035] Optionally, continue to refer to Figure 1 The massage device may also include a storage module. This storage module is communicatively connected to the controller. The storage module can store an alpha wave music library, and the control module can read the target alpha wave music track to be played from the storage module.

[0036] Optionally, continue to refer to Figure 1The massage device may also include a playback module. This playback module is communicatively connected to the controller. The controller reads the target alpha wave music track from the storage module and can play the target alpha wave music track through the playback module.

[0037] Figure 2 This is a flowchart illustrating the information processing method for the massage device provided in this application. The executing entity of this method can be the aforementioned massage device, specifically a controller within the massage device. Figure 2 As shown, the method includes: S201. Real-time collection of biometric data of the target user using the massage device through multiple sensors on the massage device. The biometric data includes actual biometric values ​​in multiple dimensions.

[0038] Optionally, the multiple sensors may include, for example, the aforementioned bioradar sensor and pressure sensor. The bioradar sensor can collect the user's respiratory signals, heart rate signals, and body movement signals. The pressure sensor can collect the user's muscle pressure signals. Each sensor sends the collected signals to the controller. The controller performs conversion, analysis, and other processing on the received signals to obtain the aforementioned biometric data.

[0039] For example, the above-mentioned biometric data may include: actual heart rate value in the heart rate dimension, actual respiratory rate value in the respiratory dimension, actual body movement rate value in the body movement dimension, and actual pressure value in the muscle pressure dimension.

[0040] The heart rate value described above represents the target user's heart rate, for example, 70 beats per minute. The respiratory rate value described above represents the target user's respiratory rate, for example, 15 breaths per minute. The body movement rate value described above represents the user's body movement rate, for example, 2 breaths per minute. The pressure value described above represents the user's muscle tension, for example, 0.45 mV.

[0041] S202. Based on the biometric data of the target user, determine the physical condition of the target user.

[0042] Optionally, multiple levels of physical condition can be predefined, and a corresponding score range can be assigned to each level. Then, in this step, the target user's physical score can be obtained by analyzing and calculating the actual vital signs values ​​across multiple dimensions. The score range into which the physical score falls is then determined, and the physical condition corresponding to that score range is taken as the target user's physical condition.

[0043] It is worth noting that when calculating the target user's physical score based on actual vital signs across multiple dimensions, the calculation must be performed using the predefined score range mentioned above as a benchmark to ensure the reliability of the calculated physical score. For example, the score range of 40-80 points corresponds to a general state of tension. Therefore, if the calculated physical score is 50 points, it will be classified as a general state of tension and will not be classified as any other state.

[0044] Table 1 below shows examples of multiple levels of physical condition and their corresponding score ranges.

[0045] Table 1

[0046] S203. If the target user's physical state is relaxed, then the target alpha wave music track is determined from the alpha wave music track library stored in the storage module of the massage device, and the target alpha wave music track is played.

[0047] The aforementioned alpha wave music library includes multiple alpha wave music tracks, the frequency of which matches the frequency of the human brain's alpha brainwaves.

[0048] Optionally, multiple alpha wave music tracks can be pre-collected and stored in the aforementioned alpha wave music track library. Specifically, before the massage device leaves the factory, the collected alpha wave music tracks can be stored in the alpha wave music track library, allowing users to directly use the alpha wave music tracks already stored in the library. Furthermore, after the massage device leaves the factory, new alpha wave music tracks can be retrieved from the cloud using the communication module within the massage device, and these new tracks can be updated in the alpha wave music track library, allowing users to use continuously updated alpha wave music tracks.

[0049] Once the target user's physical state is determined to be relaxed, a target alpha wave music track can be selected from the alpha wave music library and played. This target alpha wave music track can be a single track or multiple tracks. If it's a single track, it can be played on a loop. If it's multiple tracks, they can first be sorted, and then played sequentially according to the sorted order. The sorting of multiple tracks can be based on factors such as track name, track popularity, and the degree to which the tracks match the target user's preferences.

[0050] Optionally, target alpha music tracks can be determined from the alpha music track library based on information such as the release time of the track and its match with the target user's preferences. In one example, the most recently released alpha music track in the library is played as the target alpha music track. In another example, if the target user prefers instrumental music, an instrumental alpha music track can be selected from the library as the target alpha music track for playback.

[0051] Optionally, when playing the aforementioned target alpha wave music track, a fade-in playback method can be used. For example, after starting the track, it can be played at a preset minimum volume. As the playback time increases, the volume gradually increases, and then stops increasing when it reaches a preset maximum volume. This playback method avoids sudden sounds that might startle the user and disrupt their relaxed state.

[0052] Optionally, when there are multiple tracks in the target alpha wave music collection, they can be played in a seamless loop to maintain a stable and continuous acoustic environment and avoid disrupting the user's relaxed state.

[0053] Optionally, the frequency of the target alpha wave music track played by the massage device matches the frequency of the human brain's alpha brainwaves. Specifically, the brainwaves of the human brain change with the state of consciousness. For example, when a person is in deep sleep or unconscious, the brainwave band is mainly delta waves; when a person is relaxed, the brainwave band is mainly alpha waves; and when a person is tense, the brainwave band is mainly beta waves. The frequency range of alpha is 8-13 Hz, and correspondingly, the frequency range of the aforementioned target alpha wave music track can also be 8-13 Hz, thus matching the frequency of the target alpha wave music track with the frequency of the human brain's alpha brainwaves.

[0054] In this embodiment, by collecting the target user's actual vital signs values ​​across multiple dimensions, the target user's physical state can be accurately determined based on these values. When the target user is in a relaxed state, a target alpha wave music track is selected from the alpha wave music library of the massage device and played. Since the brainwaves of a person in a relaxed state are primarily alpha waves, this application, by accurately identifying the target user's physical state and playing alpha wave music tracks that match the frequency of alpha waves in the brainwaves when the target user is relaxed, enables the brain's alpha waves to resonate with the alpha waves of the music track. Simultaneously, the soothing characteristics of alpha wave music, its psychological suggestion, and the tranquil atmosphere it creates encourage the brain to spontaneously generate more alpha waves, creating an auditory environment for the user to focus on inner peace or relaxation. This allows the user to achieve a deeper state of relaxation, which in turn helps the user smoothly enter a sleep state, greatly enhancing the user experience.

[0055] Figure 3 A flowchart illustrating the method for determining body state in the information processing of the massage device provided in this application, such as... Figure 3 One possible approach to step S202 is as follows: S301. Obtain the baseline vital signs data of the predetermined target user, which includes baseline vital signs values ​​in multiple dimensions.

[0056] Optionally, the aforementioned baseline vital signs data may refer to the vital signs data of the target user when they are in a relaxed state. Corresponding to the aforementioned actual vital signs data, the baseline vital signs data may include: baseline heart rate value in the heart rate dimension, baseline respiratory rate value in the respiratory dimension, baseline body movement rate value in the body movement dimension, and baseline pressure value in the muscle stress dimension.

[0057] For example, if the target user's heart rate is typically 70 beats per minute when at rest and relaxed, then 70 can be used as the baseline heart rate value in the heart rate dimension.

[0058] In one alternative approach, the baseline vital sign values ​​for the aforementioned multiple dimensions can be manually input by the target user. For example, after the massage device is activated, the target user can be prompted to input baseline vital sign values ​​via voice, text, or other means. Accordingly, the target user can input vital sign values ​​for multiple dimensions via voice or by pressing certain buttons. Alternatively, the target user can also configure baseline vital sign data through a massage device application on a mobile terminal.

[0059] Alternatively, the massage device can be used to collect and analyze the target user's baseline vital signs data. Specifically, after the massage device is activated, it prompts the target user to sit quietly on the device for 5 minutes. During these 5 minutes, the massage device collects the target user's vital signs values ​​across multiple dimensions at a preset interval. After collection, for each dimension, the average of the multiple vital signs values ​​is calculated, and this average is used as the baseline vital sign value for that dimension. For example, if the massage device collects 5 heart rate values ​​at a frequency of once per minute during the 5 minutes of sitting, the average of these 5 heart rate values ​​is used as the baseline heart rate value for the heart rate dimension.

[0060] After obtaining the target user's baseline vital signs data through either of the two methods described above, the baseline vital signs data can be stored in the storage module of the massage device. Therefore, in this step, the target user's baseline vital signs data can be directly read from the storage module of the massage device.

[0061] Optionally, the target user's physical indicators may change dynamically; therefore, the aforementioned baseline vital signs data can also be updated periodically. For example, every three months, the target user's baseline vital signs data can be redefined using the second method described above, and the baseline vital signs data already stored in the storage module can be replaced with the redefined baseline vital signs data.

[0062] S302. Determine the deviation information corresponding to each dimension based on the actual vital sign values ​​and baseline vital sign values ​​for each dimension.

[0063] Optionally, the baseline vital sign values ​​for each dimension represent the actual vital sign values ​​of the target user in a relaxed state. Therefore, the baseline vital sign values ​​can be used as the benchmark values ​​for that dimension. The actual vital sign values ​​currently collected in real time are compared with the baseline vital sign values ​​to obtain the deviation information corresponding to that dimension. Specifically, this deviation information is used to characterize the deviation of the actual vital sign values ​​from the baseline vital sign values.

[0064] As an example, the aforementioned deviation information can refer to the deviation rate of the actual vital sign value relative to the baseline vital sign value. Specifically, this deviation rate can be calculated using the following formula (1).

[0065] (1) in, Indicates the deviation rate. Indicates actual vital sign values. This represents the baseline vital signs value.

[0066] Optionally, in the specific implementation process, for each dimension, the deviation rate of that dimension is calculated based on the baseline vital sign values ​​and the actual vital sign values ​​of that dimension. For example, if the vital sign values ​​of the heart rate dimension, breathing dimension, body movement dimension and muscle pressure dimension are collected for the target user, then in this step, the deviation rates of the heart rate dimension, breathing dimension, body movement dimension and muscle pressure dimension can be calculated respectively using the above formula (1).

[0067] S303. Determine the target user's physical condition based on the deviation information corresponding to each dimension.

[0068] Optionally, the deviation information corresponding to each dimension can reflect the deviation of the target user's body from the baseline value in different dimensions. The deviation information corresponding to all dimensions can be combined for comprehensive analysis, so as to accurately determine the target user's current physical condition.

[0069] In this embodiment, based on the baseline vital signs values ​​and actual vital signs values ​​of each dimension, the deviation information of each dimension can be determined. This deviation information can accurately characterize the difference between the user's actual vital signs and the baseline vital signs. Therefore, based on the deviation information of each dimension, the physical condition of the target user can be accurately determined.

[0070] As an optional implementation, the process for determining the baseline vital signs data may include: Acquire sample vital sign data of target users at multiple time points within a target period, where the target users are in a relaxed state during the target period. Each sample vital sign data includes sample vital sign values ​​of multiple dimensions. Based on the sample vital sign values ​​of each dimension at each time point, determine the baseline vital sign values ​​of each dimension.

[0071] Optionally, the target time period could be, for example, a period during which the user sits quietly on the massage device after it is activated, such as the aforementioned 5 minutes. During this target time period, the target user is truly in a relaxed state. As an example, the massage device can collect one or more vital sign data points as pre-collected values. Based on these pre-collected values, the massage device can determine whether there is a significant deviation from the usual vital sign values. If so, the target user may not be truly relaxed at present. For example, a person's heart rate in a relaxed state is usually no higher than 100 beats per minute. If the massage device continuously collects heart rate values ​​exceeding 100 from the target user, it can output a prompt message asking the target user if they are not in a relaxed state and suggesting that they try again later. If the deviation between the pre-collected values ​​and the usual vital sign values ​​is small, the massage device can collect sample vital sign data at multiple time points within the aforementioned target time period according to a preset cycle.

[0072] Corresponding to the aforementioned actual vital signs data, the sample vital signs data may include: sample heart rate values ​​(heart rate dimension), sample respiratory rate values ​​(respiration dimension), sample body movement rate values ​​(body movement dimension), and sample pressure values ​​(muscle pressure dimension). After acquiring the sample vital signs data at each time point, the massage device can calculate the average value of the sample vital signs values ​​at all time points for each dimension, and use this average value as the baseline vital signs value for that dimension. Optionally, if there are one or more values ​​with excessively large deviations among the sample vital signs values ​​at all time points, these one or more values ​​can be removed, and the average of the remaining values ​​can be calculated to ensure the reliability of the sample.

[0073] In this embodiment, by collecting sample vital sign values ​​at multiple time points and determining the baseline vital sign values ​​accordingly, the accuracy of the baseline vital sign values ​​can be guaranteed.

[0074] Figure 4 A schematic diagram illustrating the specific process of determining body state in the information processing method of the massage device provided in this application is shown below. Figure 4 As described above, step S303 may include: S401. Based on the deviation information and the state threshold corresponding to each dimension, determine the candidate state corresponding to each dimension.

[0075] Optionally, each dimension can correspond to one or more state thresholds, the number of which is related to the pre-defined levels of body state. For example, if body state is pre-divided into three levels as shown in Table 1 above: relaxed, moderately tense, and severely tense, then each dimension can correspond to two state thresholds. For instance, for the heart rate dimension, there could be two state thresholds: 10% and 30%. By comparing the deviation information with these two state thresholds, it can be determined which of the three levels the target user falls into in the heart rate dimension, thus identifying the candidate state corresponding to the heart rate dimension. It should be understood that the unit of the state thresholds corresponding to each dimension is consistent with the unit of the deviation information. For example, if the deviation information is a deviation rate, i.e., a ratio, then the state thresholds also represent ratios, such as the 10% and 30% mentioned above.

[0076] Continuing with the deviation rate as an example, the deviation rate of the heart rate dimension is compared with the two state thresholds of the heart rate dimension. If the deviation rate is less than or equal to the smaller of the state thresholds, it indicates that the deviation rate is the smallest, and the candidate state corresponding to the heart rate dimension can be determined as the relaxed state among the three levels mentioned above. If the deviation rate is greater than the smaller value but less than the larger of the state thresholds, it indicates that the deviation rate is in the middle, and the candidate state corresponding to the heart rate dimension can be determined as the moderately tense state. If the deviation rate is greater than or equal to the larger value, it indicates that the deviation rate is the largest, and the candidate state corresponding to the heart rate dimension can be determined as the severe tense state.

[0077] S402. If the candidate states corresponding to each dimension are the same, then the candidate state shall be taken as the target user's physical state.

[0078] If the candidate states for each dimension are the same, it indicates that the body state identified from multiple dimensions is consistent. In this case, the reliability of the candidate state is high, and it can be directly used as the target user's body state. For example, if the candidate states for heart rate, respiration, body movement, and muscle stress are all determined to be relaxed, then the target user's body state can be determined to be relaxed.

[0079] S403. If there are different candidate states for each dimension, determine the number of each candidate state and take the candidate state with the most numbers as the target user's physical state.

[0080] If the candidate states for each dimension differ, the number of each candidate state can be determined statistically, and the candidate state with the most counts can be taken as the target user's physical state. For example, the candidate states for the heart rate dimension are relaxed, the respiratory dimension is relaxed, and the body movement dimension is relaxed, while the candidate state for the muscle stress dimension is moderate tension. If these candidate states are statistically analyzed and the number of relaxed states is 3 and the number of moderate tension states is 1, then relaxed state can be taken as the target user's physical state.

[0081] As an alternative approach, if statistical analysis reveals that there is more than one candidate state with the highest number of occurrences, it indicates that the reliability of the current candidate state is low. In this case, the user can be prompted to remain seated, and the target user's vital sign data can be collected again to re-determine their physical state. For example, if the candidate states for heart rate are relaxed, breathing, body movement, and muscle stress are both relaxed and generally tense, then the number of relaxed and generally tense states is 2, and the physical state can be re-determined.

[0082] In this embodiment, by determining the candidate states corresponding to each dimension and determining the target user's physical state based on the candidate states corresponding to each dimension, the accuracy and reliability of the determined physical state can be guaranteed.

[0083] Figure 5 Another flowchart illustrating the determination of body state in the information processing method for the massage device provided in this application is shown below. Figure 5 Another optional approach to step S202 described above includes: S501. Standardize the actual values ​​of each dimension of the above biological signs data to obtain standardized values ​​of each dimension.

[0084] Optionally, since the physical ranges of vital sign values ​​in different dimensions are not the same, direct subsequent calculations would result in unreliable results due to these range differences. Therefore, in this step, the actual vital sign values ​​for each dimension are standardized, mapping them to a unified standardized value range to ensure consistent ranges for each dimension.

[0085] Specifically, a standardized processing model can be constructed for each dimension based on the physical range of the vital sign values. This standardized processing model can be, for example, a standardized processing formula. The following uses the heart rate dimension as an example to illustrate the standardized processing process.

[0086] In the heart rate dimension, the range of human heart rate values ​​is usually between 40 beats / minute and 120 beats / minute. Therefore, the physical range of heart rate values ​​is 40-120. Based on this physical range, a standardized processing formula can be constructed as shown in the following formula (2).

[0087] (2) in, Represents standardized vital sign values. This indicates the actual vital signs value.

[0088] For example, if the target user's actual heart rate is 80, substituting it into the above formula (2) will yield a standardized heart rate of 50.

[0089] S502. Based on the standardized phenotypic values ​​of each dimension and the membership functions of each level of each dimension, determine the membership degree of the target user at each level of each dimension.

[0090] Each membership function is used to characterize the degree to which a target user is likely to belong to the level corresponding to that membership function.

[0091] Optionally, multiple levels can be pre-defined for each dimension, and a membership function can be constructed for each level. Each level corresponds to the degree within that dimension, and the membership function for each level represents the likelihood that the target user currently belongs to that level. The following explanation uses the heart rate dimension as an example.

[0092] For heart rate, three levels can be pre-defined: high, medium, and low. High level indicates a high heart rate, medium level indicates a medium heart rate, and low level indicates a low heart rate.

[0093] For the low level, the membership function shown in formula (3) is constructed. This membership function represents the probability that the target user currently belongs to the low level (i.e., has a low heart rate).

[0094] (3) For the intermediate level, the membership function shown in formula (4) is constructed. This membership function represents the probability that the target user currently belongs to the intermediate level (i.e., has a heart rate value in the middle).

[0095] (4) For higher levels, the membership function shown in formula (5) is constructed. This membership function represents the probability that the target user currently belongs to a higher level (i.e., has a higher heart rate).

[0096] (5) Among them, in the above formulas (3), (4), and (5) All of these represent standardized heart rate values.

[0097] For example, assuming the standardized heart rate value of the target user is 50, substituting it into the above formulas (3), (4), and (5) respectively, the calculated results are 0, 1 / 2, and 1 / 6, respectively. That is, the probability that the target user's current heart rate is low is 0, that is, the target user's membership degree at the low level of heart rate in the heart rate dimension is 0; the probability that the heart rate is in the middle is 1 / 2, that is, the target user's membership degree at the middle level of heart rate in the heart rate dimension is 1 / 2; and the probability that the heart rate is high is 1 / 6, that is, the target user's membership degree at the high level of heart rate in the heart rate dimension is 1 / 6.

[0098] S503. Based on the membership degree of the target user at each level in each dimension and multiple preset fuzzy rules, determine the trigger intensity of the target user under each fuzzy rule.

[0099] Each fuzzy rule includes: fuzzy condition, body state, and score. The fuzzy condition includes one level of each dimension, and the levels of each dimension are connected by logical symbols.

[0100] For example, the three fuzzy rules shown in Table 2 below can be pre-configured. It should be understood that Table 2 below is only a simple example, and more detailed and richer fuzzy rules can be configured in actual implementation.

[0101] Table 2

[0102] Taking the aforementioned fuzzy rule 1 as an example, the fuzzy conditions of this rule are: low heart rate ∧ low respiration ∧ low body movement ∧ low stress, where the symbol "∧" represents AND logic. That is, this fuzzy rule requires all four dimensions to be at a low level; correspondingly, the physical state corresponding to this fuzzy rule is a relaxed state, and the score is 90. It should be understood that the score values ​​of the fuzzy rules and the score ranges set in Table 1 above are established according to a unified standard. For example, a score of 90 for a fuzzy rule indicates that the fuzzy rule falls within the score range of 80-100; therefore, the corresponding physical state is a relaxed state.

[0103] Based on determining the membership degree of the target user at each level across all dimensions, the trigger strength of the target user under each fuzzy rule can be determined according to the levels defined in each fuzzy rule. This trigger strength characterizes the probability that the target user currently conforms to the fuzzy rule; the greater the trigger strength, the more likely the target user is to conform to the fuzzy rule.

[0104] S504. Determine the target score based on the trigger intensity of the target user under each fuzzy rule and the score value corresponding to each fuzzy rule.

[0105] Optionally, as shown in Table 2 above, each fuzzy rule has a corresponding score value. After determining the trigger strength of the target user under each fuzzy rule, the trigger strength and score value of each fuzzy rule can be combined for comprehensive calculation to determine the target score value.

[0106] S505. Determine the target user's physical condition based on the above target score and the preset score range corresponding to each physical condition.

[0107] The preset score range can be, for example, the score range shown in Table 1 above. Since the score values ​​corresponding to the fuzzy rules and the score ranges shown in Table 1 are formulated according to a unified standard, it is possible to determine the score range in Table 1 into which the target score value falls, and take the physical state corresponding to the score range into which it falls as the physical state of the target user.

[0108] For example, the target score is 90, so it falls into the 80-100 range, thus indicating that the target user's physical state is relaxed.

[0109] In this embodiment, membership functions are pre-constructed for each level of each dimension, and multiple fuzzy rules are also constructed. Based on this, the membership degree of the target user at each level of each dimension can be determined, and the trigger strength of the target user under each fuzzy rule can be determined according to the membership degree, thereby determining the physical state. The above process is based on the idea of ​​fuzzification, which makes the determined physical state more accurate.

[0110] As one possible implementation, step S503 above may include: Obtain the target level of each dimension corresponding to the fuzzy condition in the current fuzzy rule; extract the membership degree of the target level of each dimension from the membership degree of the target user at each level of each dimension; take the minimum value of the membership degree of the target level of all extracted dimensions as the trigger strength of the target user under the current fuzzy rule.

[0111] Optionally, this embodiment can be executed for each fuzzy rule separately, wherein the current fuzzy rule can be any fuzzy rule that has been defined.

[0112] For the current fuzzy rule, its fuzzy conditions can be parsed first to determine the target level for each dimension. For example, the fuzzy conditions are iterated through, and each time a "∧" symbol is encountered, the string between that symbol and the previous "∧" symbol is taken as the target level for a dimension. For instance, for the fuzzy rule Rule1 in Table 2, if "low breathing" is obtained during the iteration, it indicates that the target level for the breathing dimension is low. After obtaining the target levels for each dimension, the membership degree of the target level for each dimension is extracted from the calculated membership degrees of each level. Then, the minimum value among the extracted membership degrees of the target levels for all dimensions is taken as the trigger strength for the target user under the current fuzzy rule. For example, assuming the calculated low-level membership degree of the target user in the heart rate dimension is 0.75, the low-level membership degree in the breathing dimension is 0, the low-level membership degree in the body movement dimension is 0, and the low-level membership degree in the muscle pressure dimension is 0, then for the fuzzy rule Rule1, the target level in all dimensions in its fuzzy conditions is low-level. The minimum value among the low-level membership degrees of all dimensions is determined, that is, the minimum value among the four values ​​of 0.75, 0, 0, 0. The minimum value is 0. Therefore, the trigger intensity of the target user under Rule1 is 0.

[0113] In this embodiment, the minimum value among the membership degrees of all dimensions of the target level involved in the fuzzy conditions of the fuzzy rule is used as the trigger strength of the fuzzy rule. This can ensure that the trigger strength is not overestimated, thereby ensuring the accuracy of the final judgment result.

[0114] As an optional implementation, step S504 above may include: Calculate the product of the trigger intensity and the score value of the fuzzy rule under each fuzzy rule to obtain the sub-score value corresponding to each fuzzy rule; calculate the first sum of the sub-score values ​​corresponding to all fuzzy rules; calculate the second sum of the trigger intensity under all fuzzy rules; calculate the quotient of the first sum divided by the second sum, and use the quotient as the target score value.

[0115] For example, the target score can be calculated using the following formula (6).

[0116] (6) in, This represents the trigger strength of the i-th fuzzy rule. This represents the score of the i-th fuzzy rule.

[0117] The scores of the fuzzy rules, as shown in Table 2 above, are predefined scores.

[0118] In this embodiment, sub-scores for all dimensions are calculated, and a first sum of all sub-scores is calculated, along with a second sum of all trigger intensities. The quotient of the first sum divided by the second sum is taken as the target score. In this process, information from all levels of all dimensions participates in the calculation. Even if there are errors in the information at certain levels of some dimensions, they can be eliminated by information from other levels, thereby ensuring the accuracy of the target score.

[0119] As an optional implementation, step S203 above may include: Obtain the target user's music preference information; based on the target user's music preference information, determine the target alpha wave music track from the alpha wave music track library stored in the massage device's storage module.

[0120] In one approach, the target user's music preference information can be obtained by guiding the user to input it. For example, in the application interface corresponding to the massage device, the target user can be prompted to input music preference information.

[0121] Another approach is to analyze the target user's historical usage information to obtain their music preference information. For example, one could obtain the music tracks selected by the target user within the three months prior to the current time, perform statistical analysis on these tracks, and thus acquire the target user's music preference information.

[0122] Optionally, the music preference information may include, for example, the music genres that the target user is interested in, such as instrumental music, nature sounds, or music performed by specific artists. The music preference information may also include, for example, the artists that the target user likes.

[0123] Based on the target user's track preference information, target alpha music tracks can be determined from the alpha music track library. For example, if the target user prefers instrumental music, then instrumental tracks can be filtered from the alpha music track library. Furthermore, when there are many tracks selected, target alpha music tracks can be chosen based on parameters such as release date and popularity.

[0124] In this embodiment, by identifying the target user's track preference information and selecting target alpha wave music tracks from the alpha wave music track library based on the track preference information, the played alpha wave music tracks match the target user's preferences, greatly improving the user experience.

[0125] In addition to outputting alpha wave music tracks, this application can also provide more suitable massage techniques to the target user by analyzing the target user's sleep patterns. Details are as follows.

[0126] Figure 6 A flowchart illustrating the massage control process of the information processing method for the massage device provided in this application is shown below. Figure 6 The above method also includes: S601. Based on the sleep characteristics data of the target user, determine the sleep index of the target user, which includes: sleep latency index, sleep depth index and sleep continuity index.

[0127] Optionally, the sleep vital signs data of the target user can be obtained by analyzing data collected by bio-radar sensors and pressure sensors. Sleep vital signs data may include, for example, heart rate, respiratory rate, and heart rate variability. Among these, heart rate variability is a key indicator for assessing nervous system stress and sleep depth.

[0128] By analyzing sleep-related vital signs data, a sleep index can be determined for the target user. Specifically, the sleep latency index characterizes the difficulty for the target user to fall asleep from wakefulness. It can be achieved by monitoring the target user's heart rate and respiratory rate during the initial stage of using the massage device, determining whether the heart rate and respiratory rate can quickly reach a stable state. The shorter the time to reach a stable state, the easier it is for the target user to fall asleep. The sleep depth index characterizes the sleep quality of the target user. It can be accurately calculated based on the target user's heart rate variability and body movement frequency. The sleep continuity index characterizes the ease with which the target user's sleep is interrupted. It can be calculated based on the target user's body movement frequency.

[0129] S602. Based on the above sleep index, determine the type of sleep disorder of the target user.

[0130] Optionally, the sleep latency index can be used to determine whether the target user has difficulty falling asleep; the sleep depth index can be used to determine whether the target user is a light sleeper with frequent dreams; and the sleep continuity index can be used to determine whether the target user is an intermittently awakened type. For example, if the target user's sleep latency index is higher than a preset threshold, it indicates that the target user has difficulty falling asleep, and therefore the target user can be identified as having difficulty falling asleep.

[0131] It is worth noting that the sleep disorder type of the target user may include one or more of the types mentioned above. For example, the target user may only have difficulty falling asleep, or the target user may have both difficulty falling asleep and light sleep with frequent dreams.

[0132] S603. Based on the above-mentioned sleep disorder types, determine at least one target sleep stage to be massaged and the corresponding massage techniques for each target sleep stage.

[0133] Optionally, different types of sleep disorders may correspond to different sleep stages. Specifically, difficulty falling asleep corresponds to the sleep initiation stage, light sleep with vivid dreams corresponds to the light or deep sleep stage, and intermittent awakening corresponds to the stage where one may transition from sleep to wakefulness. Since different types of sleep disorders correspond to different sleep stages, and the causes of different types of sleep disorders are different, the target sleep stage for massage can be determined first based on the type of sleep disorder. Then, corresponding massage techniques can be applied to the type of sleep disorder in that target sleep stage. These massage techniques are specifically designed to alleviate the type of sleep disorder in the target sleep stage.

[0134] S604. Collect the target user's biometric data in real time. If the biometric data determines that the target user is currently in the target sleep stage, perform a massage on the target user according to the massage technique corresponding to the target sleep stage.

[0135] For example, if difficulty falling asleep corresponds to the beginning of sleep, then during the beginning of sleep, extremely gentle and slow pressure can be applied to the head, neck, and shoulders to reduce the excitation of the sympathetic nervous system, thereby helping the target user fall asleep as soon as possible.

[0136] For example, if the light sleep and dream-filled type corresponds to the light sleep or deep sleep stage, then during the light sleep or deep sleep stage, a stable, rhythmic kneading and warming effect on the back and waist can be used to relax the core muscle groups and push the sleep to a deeper stage.

[0137] For example, the intermittent wakefulness type corresponds to the stage where the user may transition from sleep to wakefulness. Therefore, when it is detected that the target user may transition from sleep to wakefulness, gentle wrapping pressure on the limbs and soles of the feet and continuous heat application can be used to provide stable and comfortable stimulation during the period when the target user may wake up, thus maintaining the sleep state.

[0138] In this embodiment, the sleep disorder type of the target user is determined, and the target sleep stage and corresponding massage techniques are determined based on the sleep disorder type. When the target user is detected to be in the target sleep stage, the corresponding massage techniques are performed on the user. Since the sleep disorder type of the target user is accurately identified in advance, the appropriate massage can be performed at the appropriate sleep stage to address the target user's sleep problems, thereby effectively helping the target user improve sleep quality.

[0139] Based on the same inventive concept, this application also provides an information processing device for a massage device corresponding to the information processing method for the massage device. Since the principle of the device in this application is similar to the information processing method for the massage device described above in this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0140] Figure 7 This is a modular structural diagram of the information processing device for the massage device provided in this application. The device is applied to the massage device, such as... Figure 7 As shown, the device includes: The acquisition module 701 is used to acquire biometric data of the target user using the massage device in real time through multiple sensors on the massage device. The biometric data includes actual biometric values ​​in multiple dimensions.

[0141] The determination module 702 is used to determine the physical condition of the target user based on the target user's biometric data.

[0142] The playback module 703 is used to determine a target alpha wave music track from the alpha wave music track library stored in the storage module of the massage device when the target user's body is in a relaxed state, and to play the target alpha wave music track. The alpha wave music track library includes multiple alpha wave music tracks, and the frequency of each alpha wave music track matches the frequency of the human brain's alpha brainwaves.

[0143] As an optional implementation, the determining module 702 is specifically used for: Obtain the baseline vital signs data of the predetermined target user, wherein the baseline vital signs data includes baseline vital signs values ​​in multiple dimensions; Based on the actual vital sign values ​​and baseline vital sign values ​​for each dimension, determine the corresponding deviation information for each dimension; The target user's physical condition is determined based on the deviation information corresponding to each dimension.

[0144] As an optional implementation, the process for determining the baseline vital signs data includes: Acquire sample vital sign data of the target user at multiple time points within a target time period, wherein the target user is in a relaxed state during the target time period, and each sample vital sign data includes sample vital sign values ​​of multiple dimensions. Based on the sample vital sign values ​​of each dimension at each time point, the baseline vital sign values ​​of each dimension are determined.

[0145] As an optional implementation, the determining module 702 is specifically used for: Based on the deviation information and state thresholds corresponding to each dimension, determine the candidate states for each dimension. If the candidate states corresponding to each dimension are the same, then the candidate state is taken as the physical state of the target user. If the candidate states for each dimension are different, then the number of each candidate state is determined, and the candidate state with the most numbers is taken as the target user's physical state.

[0146] As an optional implementation, the determining module 702 is specifically used for: The actual vital sign values ​​of each dimension in the biological vital sign data are standardized to obtain standardized vital sign values ​​for each dimension. Based on the standardized phenotypic values ​​of each dimension and the membership functions of each level of each dimension, the membership degree of the target user at each level of each dimension is determined, wherein each membership function is used to characterize the degree to which the target user belongs to the level corresponding to the membership function. Based on the membership degree of the target user at each level in each dimension and multiple preset fuzzy rules, the trigger intensity of the target user under each fuzzy rule is determined. Each fuzzy rule includes: fuzzy condition, physical state and score value. The fuzzy condition includes a level in each dimension, and the levels in each dimension are connected by logical symbols. The target score is determined based on the trigger intensity of the target user under each fuzzy rule and the score value corresponding to each fuzzy rule. The target user's physical condition is determined based on the target score and the preset score range corresponding to each physical condition.

[0147] As an optional implementation, the determining module 702 is specifically used for: Obtain the target level of each dimension corresponding to the fuzzy conditions in the current fuzzy rule; Extract the membership degree of the target user at each level of each dimension; The minimum value among the membership degrees of all extracted target levels is taken as the trigger strength of the target user under the current fuzzy rule.

[0148] As an optional implementation, the determining module 702 is specifically used for: Calculate the product of the trigger strength and the score value of the fuzzy rule under each fuzzy rule to obtain the sub-score value corresponding to each fuzzy rule; Calculate the first sum of the sub-scores corresponding to all fuzzy rules; Calculate the second sum of the trigger strengths under all fuzzy rules; Calculate the quotient of the first sum divided by the second sum, and use the quotient as the target score.

[0149] As an optional implementation, the playback module 703 is specifically used for: Obtain the target user's track preference information; Based on the target user's track preference information, the target alpha wave music track is determined from the alpha wave music track library stored in the storage module of the massage device.

[0150] As an optional implementation, the determining module 702 is further configured to: Based on the sleep vital signs data of the target user, the sleep index of the target user is determined, and the sleep index includes: sleep latency index, sleep depth index and sleep continuity index; Based on the sleep index, the type of sleep disorder of the target user is determined; Based on the type of sleep disorder, determine at least one target sleep stage to be massaged and the corresponding massage techniques for each target sleep stage. The system collects the target user's biometric data in real time. If the target user is determined to be in the target sleep stage based on the biometric data, the system performs a massage on the target user according to the massage technique corresponding to the target sleep stage.

[0151] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.

[0152] This application embodiment also provides a massage device 80, such as Figure 8 The diagram shows another structural schematic of the massage device 80 provided in this application embodiment, including: a processor 81, a memory 82, and optionally, a bus 83. The memory 82 stores machine-readable instructions executable by the processor 81. When the massage device 80 is running, the processor 81 communicates with the memory 82 via the bus 83, and the processor 81 executes the machine-readable instructions to perform the steps of the information processing method of the massage device described above.

[0153] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the information processing method for the massage device described above.

[0154] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces; the indirect coupling or communication connection of devices or modules can be electrical, mechanical, or other forms.

[0155] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0156] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. An information processing method for a massage device, characterized in that, Applied to a massage device, the method includes: The massage device collects biometric data of the target user in real time through multiple sensors, and the biometric data includes actual biometric values ​​in multiple dimensions. The target user's physical condition is determined based on their biometric data. If the target user's physical state is relaxed, a target alpha wave music track is determined from the alpha wave music track library stored in the storage module of the massage device, and the target alpha wave music track is played. The alpha wave music track library includes multiple alpha wave music tracks, and the frequency of each alpha wave music track matches the frequency of the human brain's alpha brainwaves.

2. The method according to claim 1, characterized in that, The step of determining the target user's physical condition based on the target user's biometric data includes: Obtain the baseline vital signs data of the predetermined target user, wherein the baseline vital signs data includes baseline vital signs values ​​in multiple dimensions; Based on the actual vital sign values ​​and baseline vital sign values ​​for each dimension, determine the corresponding deviation information for each dimension; The target user's physical condition is determined based on the deviation information corresponding to each dimension.

3. The method according to claim 2, characterized in that, The process for determining the baseline vital signs data includes: Acquire sample vital sign data of the target user at multiple time points within a target time period, wherein the target user is in a relaxed state during the target time period, and each sample vital sign data includes sample vital sign values ​​of multiple dimensions. Based on the sample vital sign values ​​of each dimension at each time point, the baseline vital sign values ​​of each dimension are determined.

4. The method according to claim 2, characterized in that, The step of determining the target user's physical condition based on the deviation information corresponding to each dimension includes: Based on the deviation information and state thresholds corresponding to each dimension, determine the candidate states for each dimension. If the candidate states corresponding to each dimension are the same, then the candidate state is taken as the physical state of the target user. If the candidate states for each dimension are different, then the number of each candidate state is determined, and the candidate state with the most numbers is taken as the target user's physical state.

5. The method according to claim 1, characterized in that, The step of determining the target user's physical condition based on the target user's biometric data includes: The actual vital sign values ​​of each dimension in the biological vital sign data are standardized to obtain the standardized vital sign values ​​of each dimension. Based on the standardized phenotypic values ​​of each dimension and the membership functions of each level of each dimension, the membership degree of the target user at each level of each dimension is determined, wherein each membership function is used to characterize the degree to which the target user belongs to the level corresponding to the membership function. Based on the membership degree of the target user at each level in each dimension and multiple preset fuzzy rules, the trigger intensity of the target user under each fuzzy rule is determined. Each fuzzy rule includes: fuzzy condition, physical state and score value. The fuzzy condition includes a level in each dimension, and the levels in each dimension are connected by logical symbols. The target score is determined based on the trigger intensity of the target user under each fuzzy rule and the score value corresponding to each fuzzy rule. The target user's physical condition is determined based on the target score and the preset score range corresponding to each physical condition.

6. The method according to claim 5, characterized in that, The step of determining the trigger strength of the target user under each fuzzy rule based on the target user's membership degree at each level of each dimension and multiple preset fuzzy rules includes: Obtain the target level of each dimension corresponding to the fuzzy conditions in the current fuzzy rule; Extract the membership degree of the target user at each level of each dimension; The minimum value among the membership degrees of all extracted target levels is taken as the trigger strength of the target user under the current fuzzy rule.

7. The method according to claim 5, characterized in that, The step of determining the target score based on the trigger intensity of the target user under each fuzzy rule and the score value corresponding to each fuzzy rule includes: Calculate the product of the trigger strength and the score value of the fuzzy rule under each fuzzy rule to obtain the sub-score value corresponding to each fuzzy rule; Calculate the first sum of the sub-scores corresponding to all fuzzy rules; Calculate the second sum of the trigger strengths under all fuzzy rules; Calculate the quotient of the first sum divided by the second sum, and use the quotient as the target score.

8. The method according to claim 1, characterized in that, The step of determining the target alpha wave music track from the alpha wave music track library stored in the storage module of the massage device includes: Obtain the target user's track preference information; Based on the target user's track preference information, the target alpha wave music track is determined from the alpha wave music track library stored in the storage module of the massage device.

9. The method according to claim 1, characterized in that, The method further includes: Based on the sleep vital signs data of the target user, the sleep index of the target user is determined, and the sleep index includes: sleep latency index, sleep depth index and sleep continuity index; Based on the sleep index, the type of sleep disorder of the target user is determined; Based on the type of sleep disorder, determine at least one target sleep stage to be massaged and the corresponding massage techniques for each target sleep stage. The system collects the target user's biometric data in real time. If the target user is determined to be in the target sleep stage based on the biometric data, the system performs a massage on the target user according to the massage technique corresponding to the target sleep stage.

10. A massage device, characterized in that, include: The device includes a processor and a memory, the memory storing machine-readable instructions executable by the processor, which, when the massage device is in operation, are executed by the processor to perform the steps of the information processing method of the massage device as described in any one of claims 1 to 9.

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