Massage control method, massager, equipment and readable storage medium

Abstract

The invention discloses a massage control method, a massager, equipment and a readable storage medium, and relates to the technical field of head massage, the massage control method comprises the following steps: obtaining a first real-time electroencephalogram signal, and determining a first target massage mode according to the first real-time electroencephalogram signal and a preset mode recommendation model; acquiring a second real-time electroencephalogram signal collected under the control of the first target massage mode, and determining a second target massage mode according to the second real-time electroencephalogram signal; and performing massage control according to the second target massage mode. The massage effect of the massager is improved.

Description

Technical Field

[0001] This application relates to the technical field of head massage, and particularly to a massage control method, a massager, a device, and a readable storage medium. Background Art

[0002] With the increasingly wide application of massagers, users have put forward higher requirements for the control methods of massagers.

[0003] The traditional massage control method is to directly control the internal massage components to massage the massage area in a fixed control manner (such as relying on mechanical massage and simple preset programs to relieve fatigue). This massage control method has great defects. Due to the single massage control method, there is a phenomenon that it is impossible to massage different users specifically. That is, this massage control method will cause the problem of poor massage effect of the massager due to the inability to massage different users specifically.

[0004] The above content is only used to assist in understanding the technical solution of this application, and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a massage control method, a massager, a device, and a readable storage medium, aiming to solve the technical problem of poor massage effect of the massager.

[0006] To achieve the above purpose, this application provides a massage control method, and the massage control method includes:

[0007] Obtain a first real-time electroencephalogram (EEG) signal, and determine a first target massage mode according to the first real-time EEG signal and a preset mode recommendation model;

[0008] Obtain a second real-time EEG signal collected under the control of the first target massage mode, and determine a second target massage mode according to the second real-time EEG signal;

[0009] Perform massage control according to the second target massage mode.

[0010] In one embodiment, the step of determining the first target massage mode according to the first real-time EEG signal and the preset mode recommendation model includes:

[0011] Determine first brain region feature data corresponding to the first real-time EEG signal, and determine a first nerve fatigue level corresponding to the first brain region feature data in a preset nerve fatigue classification model;

[0012] Determine the massage mode corresponding to the first nerve fatigue level in the preset mode recommendation model as the first target massage mode.

[0013] In one embodiment, after the step of determining the first target massage mode according to the first real-time EEG signal and a preset mode recommendation model, the following steps are included:

[0014] Obtain the information of the control terminal currently connected to the massager, and determine the historical control terminal corresponding to the control terminal information in the historical control terminal data;

[0015] Determine the historical massage characteristics corresponding to the historical control terminal, and update the first target massage mode based on the historical massage characteristics.

[0016] In one embodiment, after the step of performing massage control according to the second target massage mode, the following steps are included:

[0017] Determine the massage duration of the massager, and detect whether the massage duration is equal to a preset set duration;

[0018] When the massage duration is equal to the preset set duration, determine all the nerve fatigue levels within the massage duration, obtain the first massage score value input by the user at the nerve fatigue level, and update the historical control terminal data based on the first massage score value;

[0019] When the massage duration is less than the preset set duration, obtain the third real-time EEG signal collected under the control of the second target massage mode, use the third real-time EEG signal as the second real-time EEG signal, and execute the step of determining the second target massage mode according to the second real-time EEG signal.

[0020] In one embodiment, the step of determining the second target massage mode according to the second real-time EEG signal includes:

[0021] Obtain the collected fourth real-time EEG signal, where the fourth real-time EEG signal includes the EEG signal collected most recently before collecting the second real-time EEG signal;

[0022] Determine the second nerve fatigue level corresponding to the second real-time EEG signal, and determine the fourth nerve fatigue level corresponding to the fourth real-time EEG signal;

[0023] When the second nerve fatigue level is greater than or equal to the fourth nerve fatigue level, use a preset fatigue reduction instruction as the second target massage mode;

[0024] When the second nerve fatigue level is less than the fourth nerve fatigue level, use a preset level reduction instruction as the second target massage mode.

[0025] In one embodiment, the step of performing massage control according to the second target massage mode includes:

[0026] Determine the massage control instruction for controlling the massage control unit in the second target massage mode, and perform massage control on the massage control unit based on the massage control instruction.

[0027] In one embodiment, the massage control method further includes:

[0028] Obtain the training parameter information corresponding to the training EEG signal, where the training parameter information includes the training neural fatigue level corresponding to the training EEG signal and the second massage score value input by the user under different massage modes;

[0029] Perform model training based on the training neural fatigue level and the second massage score value to obtain a preset mode recommendation model.

[0030] In addition, to achieve the above object, the present application further provides a massager, which includes a massage controller, and the massage controller includes:

[0031] A signal acquisition module, configured to acquire a first real-time EEG signal, and determine a first target massage mode according to the first real-time EEG signal and the preset mode recommendation model;

[0032] A first control module, configured to acquire a second real-time EEG signal collected under the control of the first target massage mode, and determine a second target massage mode according to the second real-time EEG signal;

[0033] A second control module, configured to perform massage control according to the second target massage mode.

[0034] In addition, to achieve the above object, the present application further provides a massage control device, including a processor, a memory, and a massage control method program stored on the memory and executable by the processor. When the massage control method program is executed by the processor, the steps of the massage control method described above are implemented.

[0035] The present application further provides a readable storage medium, on which a massage control method program is stored. When the massage control method program is executed by a processor, the steps of the massage control method described above are implemented.

[0036] The embodiment of the present application provides a massage control method. By acquiring the first real-time electroencephalogram (EEG) signal and determining the first target massage mode according to the first real-time EEG signal and a preset mode recommendation model; acquiring the second real-time EEG signal collected under the control of the first target massage mode, and determining the second target massage mode according to the second real-time EEG signal; performing massage control according to the second target massage mode. By determining the first target massage mode through the first real-time EEG signal, and under the control of the first target massage mode, acquiring the second real-time EEG signal collected by the signal acquisition unit, and then determining the second target massage mode based on the second real-time EEG signal, and finally performing massage control based on the second target massage mode, the purpose of targeted massage can be achieved, thereby avoiding the phenomenon that it is impossible to perform targeted massage on different users due to the single massage control method. This massage control method determines the first target massage mode through the first real-time EEG signal, and then performs massage control based on the second real-time EEG signal under the first target massage mode, thus avoiding the problem of single massage control, and further improving the massage effect of the massager. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic flowchart of the first embodiment of the massage control method of the present application;

[0038] Figure 2 It is a schematic diagram of a physical object of the massager of the present application;

[0039] Figure 3 It is a schematic flowchart of the first stage in the massage control method of the present application;

[0040] Figure 4a It is a schematic diagram of a result of the massage control method of the present application;

[0041] Figure 4b It is another schematic diagram of a result of the massage control method of the present application;

[0042] Figure 5 It is a schematic flowchart of the third stage in the massage control method of the present application;

[0043] Figure 6 It is a schematic flowchart of the second stage in the massage control method of the present application;

[0044] Figure 7 It is a schematic flowchart of model training in the massage control method of the present application;

[0045] Figure 8 It is a schematic flowchart of the overall process of the massage control method of the present application;

[0046] Figure 9 It is a schematic diagram of the modules of the massage controller of the present application;

[0047] Figure 10 This is a schematic diagram of the device structure of the hardware operating environment involved in the device in this application.

[0048] The realization of the purpose of this application, functional features and advantages will be further described in conjunction with the embodiments with reference to the accompanying drawings.

[0049] Explanation of the reference numerals in the accompanying drawings:

[0050] 100, massager; 110, signal acquisition unit; 120, massage control unit. Specific embodiments

[0051] It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0052] In order to better understand the technical solution of this application, the following will be described in detail in conjunction with the drawings of the specification and specific embodiments.

[0053] Current head massage devices mainly rely on mechanical massage and simple preset programs. Although they can relieve local muscle tension to a certain extent, there are obvious technical limitations as follows: First, such devices lack objective evaluation means for the fatigue state of the user's brain and cannot accurately identify and quantify the degree of fatigue; Second, the massage programs often adopt a unified preset mode, failing to consider individual differences and dynamic needs, and it is difficult to provide accurate intervention effects.

[0054] Therefore, based on the deficiencies of the above massage control scheme, the massage control method of this application is proposed. The solution of the embodiment of this application is: determine the first target massage mode through the first real-time electroencephalogram signal, and under the control of the first target massage mode, obtain the second real-time electroencephalogram signal collected by the signal acquisition unit, and then determine the second target massage mode based on the second real-time electroencephalogram signal, and finally perform massage control based on the second target massage mode to achieve the purpose of targeted massage, so as to avoid the phenomenon that due to the single massage control method, it is impossible to massage different users targeted. This massage control method determines the first target massage mode through the first real-time electroencephalogram signal and then performs massage control based on the second real-time electroencephalogram signal under the first target massage mode, thus avoiding the problem of single massage control and improving the massage effect of the massager.

[0055] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or a device, a massage control device and a massager that can realize the above functions. The following takes the massager as an example to illustrate this embodiment and the following embodiments.

[0056] Based on this, an embodiment of the present application provides a massage control method. Refer to Figure 1 , Figure 1 which is a schematic flowchart of the first embodiment of the massage control method of the present application.

[0057] Refer to Figure 1 , the present application provides a massage control method. The massage control method is applied to a massager. The massager includes a signal acquisition unit. The massage control method includes:

[0058] Step S10, obtaining a first real-time electroencephalogram (EEG) signal, and determining a first target massage mode according to the first real-time EEG signal and a preset mode recommendation model;

[0059] Exemplarily, refer to Figure 2 , Figure 2 which is a schematic diagram of a physical object of the massager of the present application (the massager 100 can be a head massager or a massage device for other parts, and the functions of the massager are not limited herein). By designing a signal acquisition unit 10 on the massager 100 to collect EEG signals, the signal acquisition unit can be conductive foam or other instruments for collecting EEG signals. In this embodiment, conductive foam is taken as an example for illustration. The electrodes of the conductive foam are made of low-impedance materials to ensure good contact with the user's skin, so as to stably and efficiently collect EEG signals and improve the quality and accuracy of the signals. Among them, the EEG signal acquisition adopts a single-channel scheme, and FP2 at the forehead massage part of the massager 100 is used as the active electrode, FP1 as the reference electrode, and FPz as the ground electrode to realize EEG signal acquisition. Of course, other installation methods are also possible and are not limited herein. At the same time, there is also a massage control unit 120 on the massager 100. The massage control unit 120 is located inside the massager 100. By accurately positioning the Fengchi acupoint and the Taiyang acupoint, targeted massage intervention is realized. Through the airbag structure design in the massager 100, the pressing mode of the airbag can be adaptively and dynamically adjusted according to the user's nerve fatigue degree, including controlling the inflation time, holding time and release time, so as to provide a personalized massage experience. It is worth noting that the massage control unit 120 can be an airbag structure, an electric pulse, vibration, a mechanical kneading structure, etc., and then different massage methods, such as kneading, hot compress, cold compress and other visual and auditory relief massage methods, can be controlled and realized through specific control methods, which will be described one by one herein. Of course, there are also other components on the massager 100, which will not be described one by one herein.

[0060] In this embodiment, when performing massage control, it can be controlled based on the pressing of the power-on button or based on the first acquisition of the electroencephalogram (EEG) signal. After the EEG signal is acquired, real-time preprocessing is performed through relevant algorithms, including operations such as noise filtering, artifact removal, and feature extraction. The EEG feature data is transmitted to the cloud server via wireless transmission (assuming that the entire massage control method is executed in the cloud server, or it can also be executed in the massage controller inside the massager. This embodiment is described with the massage controller and is not limited here). The preprocessing method can be the same as the existing preprocessing methods and is not limited here, but the preprocessing process will be executed every time the EEG signal is acquired. By obtaining the first real-time EEG signal collected by the signal acquisition unit (the unit in the massager for collecting the EEG signal), the first target massage mode is then determined based on the first real-time EEG signal and the preset mode recommendation model. Here, the first real-time EEG signal refers to the EEG signal collected by the signal acquisition unit at the beginning of the entire massage process, which is also the basis for initially starting the massage control. The preset mode recommendation model refers to the massage control model trained by the user. For example, if the corresponding fatigue level is determined to be S based on the first real-time EEG signal, the massage mode corresponding to the fatigue level S will be determined in the mode recommendation model. The first target massage mode refers to the corresponding massage mode determined based on the first real-time EEG signal, such as the intensity being A and the frequency being M, etc. At this time, the massage operation of the massager can be controlled based on the first target massage mode, accurately reflecting the user's massage demands in combination with the EEG signal, and avoiding the need for the user to perform manual operations, thereby greatly improving the intelligence of the entire massage control.

[0061] Step S20: Obtain the second real-time EEG signal collected under the control of the first target massage mode, and determine the second target massage mode according to the second real-time EEG signal;

[0062] In this embodiment, after the first massage control is completed, intelligent control of the entire massage process will continue. At this time, by obtaining the second real-time EEG signal collected by the signal acquisition unit under the control of the first target massage mode, that is, the second real-time EEG signal refers to the EEG signal collected again under the control of the first target massage mode. That is, at this time, it is to control the massage process. Among them, a collection interval duration can be set for the second real-time EEG signal, such as 5 minutes. That is, after starting the massage control based on the first target massage mode, time for 5 minutes, and collect the second real-time EEG signal after 5 minutes to be used as the control basis for entering the next stage. It should be noted that at this time, before a new massage mode is determined based on the second real-time EEG signal, the first target massage mode is still used for control. After the second real-time EEG signal is determined, the second target massage mode required under the second real-time EEG signal will be determined, that is, the massage mode in the second stage. Among them, the determination method of the second target massage mode at this time can be the same as the determination method of the first target massage mode, or the massage effect of the previous stage (which can be the first stage or the previous second stage) can be determined based on the second real-time EEG signal, and then massage control can be performed based on the massage effect to ensure the massage control effect in the second stage, thereby improving the massage effect of the entire massage control.

[0063] Step S30, perform massage control according to the second target massage mode.

[0064] In this embodiment, after determining the second target massage mode, massage control is performed based on the second target massage mode, that is, the corresponding massage components in the massager are controlled according to the relevant control instructions in the determined second target massage mode. It should be noted that, in order to ensure the massage effect, it can be set to re-acquire the EEG signal collected by the signal acquisition unit under the control of the second target massage mode after a certain period of time, and use this signal as the second real-time EEG signal to re-execute the step of determining the second target massage mode according to the second real-time EEG signal (that is, the number of times of executing the step of determining the second target massage mode according to the second real-time EEG signal can be determined according to the set total massage duration and the interval duration for acquiring the EEG signal), so as to improve step by step based on the massage effect of each time period, thereby ensuring the massage effect and intelligence of the entire massage process. Moreover, a massage duration can also be set, and the massager can be directly controlled to stop massaging after the massage duration ends. The entire head massage process realizes massage control by combining EEG signal monitoring and intelligent intervention technology (the second stage determines the massage mode based on the EEG signal). On the one hand, the user's EEG signal is collected in real time and the nerve fatigue state is evaluated to intelligently recommend the best massage mode; on the other hand, during the massage process, the system collects the EEG signal and evaluates the fatigue multiple times to adaptively adjust the massage parameters of components such as airbags to achieve personalized intervention, thereby improving the user's experience while ensuring the massage effect.

[0065] In this embodiment, a massage control method is provided. By acquiring the first real-time EEG signal and determining the first target massage mode according to the first real-time EEG signal and a preset mode recommendation model; acquiring the second real-time EEG signal collected under the control of the first target massage mode, and determining the second target massage mode according to the second real-time EEG signal; performing massage control according to the second target massage mode, determining the first target massage mode through the first real-time EEG signal, and under the control of the first target massage mode, acquiring the second real-time EEG signal collected by the signal acquisition unit, and then determining the second target massage mode based on the second real-time EEG signal, and finally performing massage control based on the second target massage mode to achieve the purpose of targeted massage, thereby avoiding the phenomenon that it is impossible to massage different users specifically due to the single massage control method. This massage control method determines the first target massage mode through the first real-time EEG signal and then performs massage control based on the second real-time EEG signal under the first target massage mode, avoiding the problem of single massage control, and thus improving the massage effect of the massager.

[0066] Further, based on the first embodiment of the present application described above, a second embodiment of the massage control method of the present application is proposed. In this embodiment, the above step S10, the step of determining the first target massage mode according to the first real-time EEG signal and the preset mode recommendation model, includes:

[0067] Step S101, determining the first brain region feature data corresponding to the first real-time EEG signal, and determining the first nerve fatigue level corresponding to the first brain region feature data in the preset nerve fatigue classification model;

[0068] Step S102, determining the massage mode corresponding to the first nerve fatigue level in the preset mode recommendation model as the first target massage mode.

[0069] In this embodiment, the first target massage mode is determined based on the preset mode recommendation model. Since there is no reason to compare the massage effects before and after at this time, the first brain region feature data corresponding to the first real-time EEG signal will be determined, and then the first nerve fatigue level corresponding to the first brain region feature data will be determined in the preset nerve fatigue classification model. The first brain region feature data refers to the feature data in the first real-time EEG signal that can significantly represent the fatigue level, and the first nerve fatigue level refers to the fatigue level defined for each feature data. That is, at this time, the fatigue level is determined based on the relevant features in the first real-time EEG signal. For example, when the EEG signal feature data is defined as A1 in the preset nerve fatigue classification model, the corresponding fatigue level is S level, and when the EEG signal feature data is A2, the corresponding fatigue level is A level. It should be noted that the nerve fatigue classification model can be pre-trained, such as collecting the EEG signals of a large number of experimental personnel, and at the same time combining the fatigue values filled in by each experimental personnel for training to obtain the fatigue values corresponding to different EEG signals, and then determining that there is a certain relationship between the fatigue value and a certain feature in the EEG signal, such as a positive linear relationship. Then, this feature can be used as the brain region feature data in the future, such as the signal fluctuation situation and the signal fluctuation frequency, etc. After determining the fatigue level, the massage mode corresponding to the first nerve fatigue level will be determined in the preset mode recommendation model as the first target massage mode. Among them, the preset mode recommendation model is a model of the corresponding relationship between the fatigue level and the massage mode obtained by the user through training. At this time, the massager can be intelligently controlled based on the EEG signal to ensure the massage effect of the massager. Further, refer to Figure 3 , Figure 3This is a schematic flowchart of the first stage in the massage control method of this application. In the stage of controlling the massager for massage, first, after detecting that the user is wearing the massager (i.e., detecting that the user is wearing the massager at this time), the electroencephalogram (EEG) signals of the brain regions are obtained. Then, the obtained EEG signals are processed by an algorithm (such as the above-mentioned preprocessing algorithm) to obtain the brain region feature data. Since this is the feature data of the first stage at this time, it is the above-mentioned first brain region feature data. After that, the brain region feature data is input into a pre-trained neural fatigue classification model to obtain the current first neural fatigue level of the user. At this time, the first neural fatigue level can be input into the mode recommendation model to obtain the corresponding recommended massage mode, that is, the first target massage mode. Then, the entire massager performs massage control based on the first target massage mode.

[0070] Further, based on the first embodiment and / or the second embodiment of this application above, a third embodiment of the massage control method of this application is proposed. In this embodiment, after the step S10 of determining the first target massage mode according to the first real-time EEG signal and the preset mode recommendation model, it includes:

[0071] Step S111, obtain the control terminal information currently connected to the massager, and determine the historical control terminal corresponding to the control terminal information in the historical control terminal data;

[0072] Step S112, determine the historical massage features corresponding to the historical control terminal, and update the first target massage mode based on the historical massage features.

[0073] In this embodiment, after determining the first target massage mode, the massager can be directly controlled based on the first target massage mode, or the first target massage mode can be comprehensively adjusted in combination with the user's historical data. When controlling in combination with historical data, by obtaining the control terminal information currently connected to the massager, the historical control terminal corresponding to the control terminal information is determined in the historical control terminal data. Here, the control terminal information refers to the user information of the current user of the massager, that is, the terminal connected to the massager can be determined based on this information, such as a mobile phone, etc. Here, the control terminal information refers to the identification number related to the mobile phone, etc. The user can input relevant information on this terminal to control the massager. The historical control terminal data refers to the terminals that have been historically connected to the massager, and different identification numbers can be used to determine which terminal it is. Furthermore, it can be determined whether the current connected terminal has been connected to the massager in the historical control terminal data. The historical control terminal refers to the terminal in the historical control terminal data that is the same as the control terminal information (such as the identification number of the terminal). After determining the historical control terminal, the historical massage characteristics corresponding to the historical control terminal are determined, and then the first target massage mode is adjusted according to the historical feature data, and the first target massage mode after the instruction adjustment is used as the first target massage mode (that is, the first target massage mode is updated). Here, the historical massage characteristics refer to the massage characteristics of the historical control terminal. For example, if the historical control terminal often gives a higher score to high-intensity massage, the historical massage characteristic is a large massage intensity. Then, the intensity instruction in the first target massage mode is appropriately increased to fit the preference of the current massage object, thereby improving the user experience. Further, reference can be made to Figure 3 , before executing the first target massage mode, the system detects whether the user has historical data. At this time, if there is historical data, the massage modes and user experience scores that have been executed at the same neural fatigue level in the historical data are searched to determine the historical massage characteristics. For example, at the same neural fatigue level, the user gives a score of 9 to the executed massage mode A, a score of 3 to massage mode B, and a score of 6 to massage mode C. Then, the massage characteristics of massage mode A will be determined. If the intensity in massage mode A is relatively large, it is determined that the massage characteristic of this user is to like a relatively large intensity. If the intensity of the current first target massage mode is smaller than that of massage mode A, the intensity can be appropriately increased. Of course, it can also be other massage characteristics, such as temperature, vibration frequency, etc. Furthermore, the currently recommended massage mode (that is, the first target massage mode) can be optimized and adjusted in combination with the historical massage characteristics. On the contrary, if there is no historical data, the massager is directly controlled to run the corresponding massage mode, and the first-stage massage is performed for five minutes (the massage duration can be customized), thereby completing the massage control of the first stage.

[0074] In one embodiment, after the step of performing massage control according to the second target massage mode, it includes:

[0075] Step S301, determine the massage duration of the massager, and detect whether the massage duration is equal to the preset set duration;

[0076] Step S302, when the massage duration is equal to the preset set duration, determine all the nerve fatigue levels within the massage duration, obtain the first massage score value input by the user at the nerve fatigue level, and update the historical control terminal data based on the first massage score value;

[0077] Step S303, when the massage duration is less than the preset set duration, obtain the third real-time EEG signal collected by the signal acquisition unit under the second target massage mode, use the third real-time EEG signal as the second real-time EEG signal, and perform the step of determining the second target massage mode according to the second real-time EEG signal.

[0078] In this embodiment, after performing massage control based on the second target massage mode, it is determined whether to continue massage control or stop the massage. By determining the massage duration of the massager, that is, the massage duration from the start of power-on to the current time, when the massage duration is equal to the preset set duration, it is determined that the massage ends at this time. To enrich subsequent massage control, on the one hand, the user can be guided to input the first massage score value for each nerve fatigue level in the entire massage process, and then update the historical control terminal data based on the first massage score value. Among them, the user can be guided to score under the nerve fatigue level, such as guiding the user to score after the end of the first stage, and this score value can be used as the control basis for the second stage. After the end of the Nth second stage, the user is guided to score, and this score value can be used as the control basis for the (N + 1)th second stage. Of course, the user can also directly score the entire process. The first massage score value refers to the score given by the user to each fatigue level under the entire process, and can be the score for different massage stages, different fatigue levels, and the entire massage process. The process of updating the historical control terminal data based on the score value can be to directly determine the score value, and then deduce the massage characteristics of the user based on the score value. For example, if the score value is 10 and the massage characteristic this time is that the strength is on the high side, it is determined that the historical massage characteristic corresponding to the currently connected connection terminal is that the strength is relatively large (that is, update the historical massage characteristic of this connection terminal in the historical control terminal data) for subsequent combined historical data control. When the massage duration is less than the preset set duration, it is determined that massage control still needs to be performed at this time. Then, the third real-time EEG signal collected by the signal acquisition unit under the control of the second target massage mode is obtained and used as the second real-time EEG signal to execute the step of determining the second target massage mode according to the second real-time EEG signal. That is, as long as the massage end time or the defined number of second stages is not reached, the control process of the second stage will continue. If the massage end time or the defined number of second stages is reached, the user's evaluation of the entire massage will be output to update the historical control terminal data. On the one hand, the massage effect can be ensured, and on the other hand, the subsequent massage can be intelligently controlled based on the historical control terminal data to ensure the effect and personalized massage control of the subsequent massage control.

[0079] In one embodiment, in addition to updating the historical control terminal data with the score of the entire massage process after the massage ends, a data report will also be generated for the entire massage process so that the user can clearly know the effect indication of the entire massage. That is, the massager sorts out the data collected during this massage process and forms a data report on a terminal connected to the massager such as a mobile phone. For example, on a mobile phone APP (Application, third-party application), the data report includes the following two main display parts: for reference Figure 4a , Figure 4aThis is a schematic diagram of the results of the massage control method of this application. The first part shows the dynamic change trend of the user's fatigue state during the massage. Through the analysis of 4 times (assuming only 2 times in the second stage) of EEG detection data, the change trajectory of the user's fatigue state from the start to the end of the massage is shown. Four classification nodes of "high fatigue", "moderate fatigue", "mild fatigue" and "good state" are visually marked in the figure, providing a global understanding for the user and intuitively reflecting the continuous improvement trend of the fatigue state during the entire massage intervention process; Refer to Figure 4b , Figure 4b This is another schematic diagram of the results of the massage control method of this application. The second part focuses on showing the difference in fatigue state before and after the massage. The system analyzes the EEG detection results of the first time (before the massage starts) and the last time (when the massage ends), highlighting the degree of improvement in the fatigue state. It should be noted that after generating the report, the mobile APP will guide the user to rate the massage experience under different degrees of nerve fatigue and save these rating data as historical data for subsequent optimization and adjustment of the massage mode, that is, the rating stage can be set after the report is generated or before the report is generated, which is not limited here. At this time, the user can clearly know their massage situation from the report, so as to improve the user's satisfaction with the use of the massager. At the same time, the change of the fatigue state is displayed through data visualization, enhancing the user's awareness of their own state. Further, refer to Figure 5 , Figure 5 This is a schematic diagram of the process of the third stage in the massage control method of this application. After the end of the second stage of the massage, the system enters the third stage of the massage. The process of collecting EEG signals and signal processing is the same as that of the second stage, but at this time, the massage time will be detected. By detecting in real time whether the massage time reaches 15 minutes or the time set by the user, it is determined whether to end the massage. When it does not reach, the subsequent execution process is the same as that of the second stage of the massage, that is, the EEG signal at this time is used as the EEG signal of the second stage and the second stage process is executed; When the preset time is reached, the system obtains the EEG signals of the brain regions again, and through algorithm processing and model calculation, the final nerve fatigue level is obtained, and a data report is formed to mark the end of this massage. At this time, the user can be guided to rate the massage experience under different degrees of nerve fatigue and save these rating data as historical data (assuming that the user does not rate after the massage ends, but the data report is generated preferentially). The entire massage control process combines EEG signal monitoring with head massage intervention, evaluates the user's fatigue state through signal acquisition and processing algorithms, adjusts the massage parameters accordingly, and also combines historical data to determine the massage mode, thereby ensuring the effect of the entire massage.

[0080] Further, based on the first embodiment, the second embodiment, and / or the third embodiment of the present application described above, a fourth embodiment of the massage control method of the present application is proposed. In this embodiment, the step of determining the second target massage mode according to the second real-time EEG signal includes:

[0081] Step S311: Obtain the fourth real-time EEG signal collected by the signal acquisition unit, where the fourth real-time EEG signal includes the EEG signal collected most recently before collecting the second real-time EEG signal;

[0082] Step S312: Determine the second nerve fatigue level corresponding to the second real-time EEG signal, and determine the fourth nerve fatigue level corresponding to the fourth real-time EEG signal;

[0083] Step S313: When the second nerve fatigue level is greater than or equal to the fourth nerve fatigue level, use the preset fatigue reduction instruction as the second target massage mode;

[0084] Step S314: When the second nerve fatigue level is less than the fourth nerve fatigue level, use the preset level reduction instruction as the second target massage mode.

[0085] In this embodiment, in the second stage, the second target massage mode is determined directly based on the second real-time EEG signal instead of directly determining the second target massage mode in the preset mode recommendation model, because the entire second stage is a continuously controlled scenario (i.e., it is not the case of massage just started). At this time, the fourth real-time EEG signal collected by the electric foam will be obtained, wherein the fourth real-time EEG signal includes the EEG signal collected most recently before the second real-time EEG signal is collected. If the second real-time EEG signal is the EEG signal collected for the second time, then the fourth real-time EEG signal is the EEG signal collected for the first time, and then it is determined whether the two previous and subsequent EEG signals meet certain conditions, such as a decrease in the user's fatigue level, and then the second neural fatigue level corresponding to the second real-time EEG signal is determined, and the fourth neural fatigue level corresponding to the fourth real-time EEG signal is determined, wherein the method for determining the second neural fatigue level and the fourth neural fatigue level is the same as the method for determining the first neural fatigue level mentioned above, which will not be described again here. Then, the relationship between the two fatigue levels is determined. For example, when the second neural fatigue level is greater than or equal to the fourth neural fatigue level, the preset fatigue reduction instruction is used as the second target massage mode. On the contrary, when the second neural fatigue level is less than the fourth neural fatigue level, the preset downgrade instruction is used as the second target massage mode. That is, if the massage causes the user to go from severe fatigue to moderate fatigue, it is determined that the massage is effective, and the massage intensity and other parameters can be appropriately reduced. On the contrary, if the massage causes the user to go from moderate fatigue to severe fatigue, or there is no change, it is determined that the massage is not effective, and the massage intensity and other parameters can be appropriately increased. Among them, the preset fatigue reduction instruction refers to the user-defined control instruction for reducing fatigue, such as increasing the massage intensity, massage frequency, etc., and the downgrade instruction refers to the user-defined instruction for reducing the massage level, such as reducing the massage intensity, massage frequency, etc. (the two defined instructions can also be other, as long as they can increase and reduce fatigue and slow down fatigue), and then each stage can be precisely and targetedly controlled to ensure the intelligence of the entire massage. It is worth noting that if the massage effect is found to be unsatisfactory (for example, the fatigue level is reduced slightly or increased), the second target massage mode can be directly re-determined based on the second real-time EEG signal and the preset mode recommendation model, and then the step of detecting whether the fatigue level is improved is performed after control based on the second target massage mode. Figure 6 , Figure 6This is a schematic flowchart of the second stage in the massage control method of this application. After the first stage of massage ends, the electroencephalogram (EEG) signals of the brain region are acquired again. Through algorithm processing and model calculation, the second nerve fatigue level is obtained, and this fatigue level is compared with the previous nerve fatigue level to determine whether the user's nerve fatigue has improved. If the judgment result shows that the nerve fatigue has improved, the massage intensity is reduced; conversely, if the judgment result shows that the nerve fatigue has not improved, the massage intensity is increased or the original massage intensity is maintained. Then, the massager is controlled to run the corresponding massage mode for the second stage of massage, and the massage duration is maintained for five minutes, which can realize the intelligent dynamic adjustment of the massage intensity and ensure the massage effect.

[0086] In one embodiment, the steps of performing massage control according to the second target massage mode include:

[0087] Step S321, determining the massage control instruction for controlling the massage control unit in the second target massage mode, and performing massage control on the massage control unit based on the massage control instruction.

[0088] In this embodiment, the massager further includes a massage control unit disposed at the acupoints. Then, by determining the massage control instruction for controlling the massage control unit in the second target massage mode and performing massage control on the massage control unit based on the massage control instruction. Among them, the massage control unit 120 can be in the structure of an airbag, electric pulse, vibration, mechanical kneading, etc. Then, different massage methods can be controlled and realized through specific control methods, such as kneading, hot compress, cold compress, and other visual and auditory relief massage methods. Taking the massage control unit 120 as the airbag structure as an example, at this time, the massage control instructions include inflation instructions, holding instructions, and deflation instructions, so as to avoid the phenomenon that traditional massage devices use a preset program for control and lack the ability to perceive and adjust the user's real-time state. It can also be massage control instructions for other structures, which will not be elaborated one by one here. It should be noted that the control process of the first target massage mode is the same as that of the second target massage mode, which will not be repeated here. The entire massage process dynamically adjusts the airbag inflation time, pressure, and release rhythm through real-time analysis of the user's nerve fatigue state and in combination with the principle of acupoint massage, realizing precise and personalized massage intervention to ensure the massage effect.

[0089] Furthermore, based on the first embodiment, the second embodiment, the third embodiment, and / or the fourth embodiment of this application, the fifth embodiment of the massage control method of this application is proposed. In this embodiment, the massage control method further includes:

[0090] Step S40, obtaining the training parameter information corresponding to the training EEG signals, where the training parameter information includes the training nerve fatigue level corresponding to the training EEG signals and the second massage score value input by the user under different massage modes;

[0091] Step S50: Based on the training neural fatigue level and the second massage score value, perform model training to obtain a preset pattern recommendation model.

[0092] In this embodiment, the entire massage control process further includes the training processes of a preset pattern recommendation model and a preset neural fatigue classification model (that is, directly linking the EEG signal with the uniquely corresponding neural fatigue level. Here, it is similar to the pattern recommendation model and will not be repeated). During the training process of the preset pattern recommendation model, by obtaining the training parameter information corresponding to the training EEG signal, where the training parameter information includes the training neural fatigue level corresponding to the training EEG signal and the second massage score value input by the user under different massage patterns, and then it is possible to perform model training based on the training neural fatigue level and the second massage score value to obtain a preset pattern recommendation model. The training neural fatigue level refers to the determined fatigue level, and the second massage score value refers to the score given by the user based on different massage patterns at the fatigue level, and then determine which massage pattern the user rates the highest (assuming the highest score is the most comfortable) at which fatigue level, that is, the training requirement is completed. Refer to Figure 7 , Figure 7This is a schematic diagram of the process for model training in the massage control method of this application. By collecting the electroencephalogram (EEG) signals of volunteers in different fatigue states, the collected EEG signals are preprocessed, including band-pass filtering to remove power frequency interference and electromyogram (EMG) artifacts, and independent component analysis (ICA) to remove electrooculogram (EOG) artifacts, etc. The EEG signals are processed through built-in algorithms to extract the characteristic data. Among them, the characteristic data includes, but is not limited to, the frequency, amplitude, band energy, power spectrum, phase synchrony, time-frequency analysis features, approximate entropy, sample entropy and other features of the EEG waves, as well as composite features calculated from these basic parameters, such as physiological state indicators such as neural concentration, fatigue degree, and relaxation degree. Then, combined with the subjective scores of neural fatigue degree filled in by volunteers during the data collection process and label data such as the evaluation of different massage mode experiences, a training data set is constructed for machine learning model training. Among them, the training data set contains the EEG characteristic data and the subjective score records of the fatigue degree, as well as the user experience evaluation indicators of different massage modes. Finally, based on the constructed data set, a neural fatigue classification model can be constructed using a support vector machine, and the nonlinear mapping of the feature space can be realized through a radial basis kernel function to improve the classification accuracy. A massage mode recommendation model is constructed using a random forest algorithm, and stable and reliable mode recommendation is realized by integrating the voting results of multiple decision trees. During the model training process, grid search is used for hyperparameter optimization, and k-fold cross-validation is used to evaluate the model performance. It should be noted that the above is only one way of model training. Of course, other model training algorithms can also be used, which are not limited here. Furthermore, a mode recommendation model is obtained through training for subsequent massage mode recommendation to ensure the accuracy of massage recommendation and the massage effect.

[0093] In one embodiment, the entire massage control process can refer to Figure 8 , Figure 8This is the overall flowchart of the massage control method of this application. After the head massage starts, the electroencephalogram (EEG) signals are collected by the signal acquisition unit, and then the neural fatigue state at this time is detected based on a preset neural fatigue classification model to control the inflation, deflation, and holding time of the airbag through the airbag control module (assuming the massage control unit is the airbag) to achieve different massage modes. At this time, the first stage is carried out. By detecting whether it is in a severe fatigue state, when in a severe fatigue state, a strong massage mode (such as level 4 intensity) is set. On the contrary, when not in a severe fatigue state, a gentle massage mode (such as level 2 intensity) is set. At this time, the corresponding massage mode can be selected according to the fatigue state. Here, the severe fatigue state is taken as an example for illustration. The above completes the first stage of determining the first target massage mode based on the collected first real-time EEG signals and performing massage control. After the massage in the first target massage mode is completed (assuming the first stage of massage lasts for 5 minutes), the fatigue state is detected after the first stage to see if it has improved (that is, to detect whether the fatigue state corresponding to the EEG signals before and after massage has improved), which is the second stage. That is, the process of obtaining the second real-time EEG signals collected under the control of the first target massage mode and determining the second target massage mode is executed. In the second stage, if the fatigue state has improved, a more gentle mode can be selected, such as reducing the airbag intensity by 1 level. On the contrary, if the fatigue state has not improved, a mode with better massage effect can be selected, such as increasing the airbag intensity by 1 level, and the fatigue state determination and massage intensity (here it is assumed that the parameter adjusted based on whether it has improved is the massage intensity) control process is repeated again after a period of time. At this time, it will continue to be in the second stage, and the condition for exiting the second stage is to detect whether the entire massage duration has reached the set massage duration. If not, the control of the second stage continues. On the contrary, it enters the third stage (that is, after the massage control is carried out according to the second target massage mode and it is found that the massage time ends, a data report will be generated and the user will be informed, and at the same time, the user will be guided to score and this will be used as the historical data of this user). At this time, it has been determined that the entire massage has ended, and an EEG signal will be collected one last time, and then the fatigue level of the user at the end of the massage will be determined. Finally, the fatigue levels determined during the entire massage process will be generated into a data report so that the user can visualize the change of the fatigue state through data and improve the user's awareness of their own state. The entire massage control process combines EEG signal monitoring with head massage intervention, evaluates the user's fatigue state through signal acquisition and processing algorithms, adjusts the massage parameters accordingly, and also combines historical data to determine the massage mode, thus ensuring the effect of the entire massage.

[0094] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the massage control method of this application. Based on this technical concept, more forms of simple transformations are within the protection scope of this application.

[0095] The present application also provides a massager. Please refer to Figure 9 , the massager includes a massage controller and a signal acquisition unit. The massage controller is connected to the signal acquisition unit. The massage controller includes:

[0096] A signal acquisition module A10, configured to acquire a first real-time electroencephalogram signal, and determine a first target massage mode according to the first real-time electroencephalogram signal and a preset mode recommendation model;

[0097] A first control module A20, configured to acquire a second real-time electroencephalogram signal collected under the control of the first target massage mode, and determine a second target massage mode according to the second real-time electroencephalogram signal;

[0098] A second control module A30, configured to perform massage control according to the second target massage mode.

[0099] The massager provided by the present application adopts the massage control method in the above embodiment, and can solve the technical problem of poor massage effect of the massager. Compared with the prior art, the beneficial effects of the massager provided by the present application are the same as those of the massage control method provided by the above embodiment, and other technical features in the massage control device are the same as those disclosed in the above embodiment method, and will not be elaborated herein.

[0100] The present application provides a massage control device (which may be a massager). The massage control device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the massage control method in the first embodiment above.

[0101] Next, refer to Figure 10 , which shows a schematic structural diagram of a massage control device suitable for implementing the embodiments of the present application. The massage control device in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 10 The shown massage control device is only an example, and should not impose any limitation on the functions and usage scopes of the embodiments of the present application.

[0102] AsFigure 10 As shown, the massage control device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the massage control device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following devices may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the massage control device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows a massage control device having various devices, it should be understood that it is not required to implement or have all the shown devices. More or fewer devices may be alternatively implemented or had.

[0103] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above functions defined in the methods of the embodiments disclosed in the present application are executed.

[0104] The massage control device provided by the present application adopts the massage control method in the above embodiment, and can solve the technical problem of poor massage effect of the massager. Compared with the prior art, the beneficial effects of the massage control device provided by the present application are the same as those of the massage control method provided by the above embodiment, and other technical features in the massage control device are the same as those disclosed in the method of the previous embodiment, and will not be elaborated here.

[0105] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0106] As described above, the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0107] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the massage control method in the above embodiments.

[0108] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor massage device or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM) or a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution massage device or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0109] The above computer-readable storage medium can be included in the massage control device; it can also exist separately and not be assembled into the massage control device.

[0110] The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed by the massage control device, the massage control device is caused to:

[0111] Obtain the first real-time electroencephalogram signal, and determine the first target massage mode according to the first real-time electroencephalogram signal and a preset mode recommendation model;

[0112] Obtain the second real-time electroencephalogram signal collected under the control of the first target massage mode, and determine the second target massage mode according to the second real-time electroencephalogram signal;

[0113] Perform massage control according to the second target massage mode.

[0114] Computer program code for performing the operations of the present application can be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages - such as Java, Smalltalk, C++, and also include conventional procedural programming languages - such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network - including a local area network (LAN: Local Area Network) or a wide area network (WAN: Wide Area Network), or can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0115] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of the massager method and computer program product according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and this module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based device for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0116] The modules involved in the embodiments of the present application can be implemented in software or in hardware. Among them, the name of the module does not constitute a limitation to the unit itself in some cases.

[0117] The readable storage medium provided by this application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned massage control method, and can solve the technical problem of poor massage effect of the massager. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by this application are the same as those of the massage control method provided by the above embodiments, and will not be elaborated here.

[0118] This application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the massage control method as described above are implemented.

[0119] The computer program product provided by this application can solve the technical problem of poor massage effect of the massager. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as those of the massage control method provided by the above embodiments, and will not be elaborated here.

[0120] The above are only partial embodiments of this application, and do not limit the patent scope of this application. Any equivalent structural transformation made by using the content of the specification and drawings of this application under the technical concept of this application, or direct / indirect application in other related technical fields, is included in the patent protection scope of this application.

Claims

1. A massage control method, characterized in that: The massage control method comprises: Acquire a first real-time EEG signal, and determine a first target massage mode according to the first real-time EEG signal and a preset mode recommendation model; Acquire a second real-time EEG signal collected under the control of the first target massage mode, and determine a second target massage mode according to the second real-time EEG signal; Massage control is performed according to the second target massage mode.

2. The massage control method according to claim 1, characterized in that: The step of determining the first target massage mode according to the first real-time EEG signal and a preset mode recommendation model comprises: Determining first brain region feature data corresponding to the first real-time EEG signal, and determining a first neural fatigue level corresponding to the first brain region feature data in a preset neural fatigue classification model; The massage mode corresponding to the first nerve fatigue level is determined in a preset mode recommendation model as a first target massage mode.

3. The massage control method according to claim 1, characterized in that: After the step of determining the first target massage mode according to the first real-time EEG signal and the preset mode recommendation model, the method further comprises: Acquire the control terminal information currently connected to the massager, and determine the historical control terminal corresponding to the control terminal information in the historical control terminal data; A historical massage feature corresponding to the historical control terminal is determined, and the first target massage mode is updated based on the historical massage feature.

4. The massage control method according to claim 3, characterized in that: After the step of performing massage control according to the second target massage mode, the method further comprises: Determining the massage duration of the massager, and detecting whether the massage duration is equal to a preset set duration; When the massage duration is equal to the preset set duration, determining all nerve fatigue levels within the massage duration, obtaining a first massage score value input by the user under the nerve fatigue level, and updating the historical control terminal data based on the first massage score value; When the massage duration is less than the preset set duration, the third real-time EEG signal collected under the control of the second target massage mode is obtained, the third real-time EEG signal is used as the second real-time EEG signal, and the step of determining the second target massage mode according to the second real-time EEG signal is performed.

5. The massage control method according to claim 1, characterized in that: The step of determining the second target massage mode according to the second real-time EEG signal comprises: Acquire a fourth real-time EEG signal, wherein the fourth real-time EEG signal includes an EEG signal acquired most recently before the second real-time EEG signal is acquired; Determining a second neural fatigue level corresponding to the second real-time EEG signal, and determining a fourth neural fatigue level corresponding to the fourth real-time EEG signal; When the second nerve fatigue level is greater than or equal to the fourth nerve fatigue level, using the preset fatigue reduction instruction as the second target massage mode; When the second nerve fatigue level is lower than the fourth nerve fatigue level, a preset downgrade instruction is used as the second target massage mode.

6. The massage control method according to claim 1, characterized in that: The step of performing massage control according to the second target massage mode comprises: A massage control instruction for controlling a massage control unit in the second target massage mode is determined, and massage control is performed on the massage control unit based on the massage control instruction.

7. The massage control method according to any one of claims 1 to 6, characterized in that: The massage control method further comprises: Acquire training parameter information corresponding to the training EEG signal, wherein the training parameter information includes a training nerve fatigue level corresponding to the training EEG signal and a second massage score value input by a user in different massage modes; Model training is performed based on the training nerve fatigue level and the second massage score value to obtain a preset mode recommendation model.

8. A massager, characterized in that: The massager includes a massage controller, and the massage controller includes: A signal acquisition module, used for acquiring a first real-time EEG signal, and determining a first target massage mode according to the first real-time EEG signal and a preset mode recommendation model; A first control module is used to obtain a second real-time EEG signal collected under the control of the first target massage mode, and determine a second target massage mode according to the second real-time EEG signal; The second control module is used to perform massage control according to the second target massage mode.

9. A massage control device, characterized in that: The massage control device includes a processor, a memory, and a massage control method program stored in the memory and executable by the processor, wherein when the massage control method program is executed by the processor, the steps of the massage control method as described in any one of claims 1 to 7 are implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores a massage control method program, wherein when the massage control method program is executed by a processor, the steps of the massage control method according to any one of claims 1 to 7 are implemented.

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