Intelligent health-care health chair and production method

Abstract

The invention belongs to the technical field of computer systems, and mainly relates to an intelligent health-care health chair which comprises a control module, a biological sensing module electrically connected with the control module and health-care health hardware. The control module is connected with a control terminal through a communication network; a storage module in the control terminal is used for storing human body biological information; the processing module is used for operating the neural network to perform classification processing on the to-be-identified human body biological information; the control terminal trains the neural network through the initial set and the additional set; the analysis module is used for reprocessing the human body biological information to obtain target data; the control module is used for receiving target data transmitted by the control terminal and adjusting the target data into vibration signals through the data processing unit; by means of the design, self-adaptive adjustment of massage frequencies of different users is achieved. Meanwhile, the invention further designs a production method of the intelligent health-care health chair by training the neural network model, and the self-adaptive capability of the intelligent health-care health chair is further improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of computer systems, and mainly relates to an intelligent health care chair and a production method thereof. Background Art

[0002] As the pace of modern life accelerates, the public's attention to their health has increased significantly. As an innovative product, the health chair has replaced the traditional manual massage method to a certain extent through its built-in automatic massage mechanism. However, since its massage principle mainly relies on the mechanized adjustment of the pressing frequency of the pressing device, the massage effect is still difficult to fully match the delicacy and precision of manual massage.

[0003] In order to cope with the above technical difficulties, the existing technology has adopted a series of preset programs in the health chair to provide users with a more detailed massage experience. However, it is worth noting that this technical means fails to fully take into account the individual differences between users, especially the differences in biological information, during the implementation process, resulting in the same set of massage programs may not be applicable to all users, thus affecting the universal applicability of the massage effect.

[0004] Based on this, it is urgent to improve the existing intelligent health care chair and production method to solve the defects of the above-mentioned technology. Summary of the invention

[0005] One of the purposes of the present invention is to design an intelligent health care chair that can adjust the massage mode according to the user's biological information in order to address the deficiencies of the prior art.

[0006] The technical solution to achieve the above technical purpose is as follows:

[0007] An intelligent health care chair includes a main body portion and a control terminal connected to the main body portion;

[0008] The main body includes:

[0009] The control module is connected to the control terminal and is provided with a data processing unit;

[0010] The biological sensing module is electrically connected to the control module and is used to detect the user's human biological information to be identified and transmit the human biological information to the control module;

[0011] The health care hardware is electrically connected to the control module and includes at least one vibrator capable of changing the vibration frequency by receiving different vibration signals;

[0012] The control terminal includes:

[0013] A processing module, used to operate a neural network to classify and process the biological information of the human body to be identified;

[0014] A storage module is used to store an initial set and an additional set of human biological information, each human biological information in the initial set is represented by a different category by a designated first feature vector; each human biological information in the additional set is divided into different categories by a designated second feature vector according to the similarity between the second feature vector and the first feature vector by the neural network; the control terminal trains the neural network through the initial set and the additional set;

[0015] The analysis module is used to match the human biological information processed by the processing module to the corresponding data processing algorithm; the data processing algorithm reprocesses the human biological information to obtain target data;

[0016] Furthermore, the control module is used to receive the target data transmitted by the control terminal and adjust it into a vibration signal through the data processing unit.

[0017] The technical effects of the above technical solution are as follows:

[0018] By acquiring or monitoring the user's biological information in real time through the network, the smart health care chair can automatically adjust the massage frequency of the health care device for users with individual differences through a neural network, thereby providing a more personalized and accurate massage experience.

[0019] As a further improvement to the intelligent health care chair of the present invention, the data processing algorithm includes a first data processing algorithm and a second data processing algorithm;

[0020] Further, the first data processing algorithm is used to match different categories of human biological information in the initial set with different target data transmitted by the corresponding network end;

[0021] Furthermore, the second data processing algorithm is used to match the target data of the human biological information in the initial set to the human biological information in the additional set of the same category as the human biological information in the initial set.

[0022] As a further improvement to the intelligent health care chair of the present invention, the initially concentrated human biological information is obtained through a network terminal;

[0023] Furthermore, the additional concentrated human biological information is collected by the biological sensing module and transmitted to the storage module by the control module.

[0024] As a further improvement to the intelligent health care chair of the present invention, the processing module includes a confirmation module and a training module;

[0025] Further, the confirmation module is used to confirm the similarity between the second vector of the human biological information in one or more additional sets and the first vector of the human biological information in any initial set, and confirm the human biological information pointed to by the second vector with a similarity greater than a first threshold as the category expressed by the relative first vector;

[0026] Furthermore, the training module is used to output one or more pieces of human biological information referred to by the second vector classified into the category represented by the first vector to the initial set.

[0027] As a further improvement to the intelligent healthcare chair of the present invention, the confirmation module is used to determine the second vector whose similarity is less than the second threshold as the first vector, and the human biological information is represented by different categories by the first vector determined by the second vector whose similarity is less than the second threshold.

[0028] As a further improvement to the intelligent healthcare chair of the present invention, the training module outputs the human biological information of different categories represented by the first vector determined by the second vector whose similarity is less than the second threshold into the initial set.

[0029] As a further improvement to the intelligent health care chair of the present invention, the processing module calculates the average value of the first vector of the same category of human biological information in the initial set. When the similarity between any human biological information in the initial set and the average value is greater than a third threshold, the human biological information is confirmed as a classification of the same category of human biological information referred to by the average value.

[0030] As a further improvement to the intelligent health care chair of the present invention, the network end is a mobile device, and the user uploads the user's human biological information through the mobile device.

[0031] As a further improvement to the intelligent health care chair of the present invention, the human biological information includes: weight, height, disease type, heart rate, and blood pressure.

[0032] The second purpose of the present invention is to design a production method of an intelligent health care chair that can efficiently debug a neural network model in response to the deficiencies in the prior art.

[0033] The technical solutions for solving the above technical objectives are as follows:

[0034] A method for producing any of the above-mentioned intelligent health care chairs comprises the following steps:

[0035] S101, the control terminal obtains a set of human biological information stored in an initial set through a network terminal, and divides the human biological information into different categories, which are represented by different first vectors;

[0036] S202, the control module transmits a set of human biological information obtained from the user by the biological sensing module to an additional set of the control terminal, where the category of the human biological information is represented by a second vector;

[0037] S303, outputting the human biological information indicated by the second vector that is not similar to the first vector of the human biological information in the initial set to the initial set, and changing the second vector to the first vector to form a new category of human biological information;

[0038] S404, using the above integrated initial set to train the neural network, and debugging the accuracy of the intelligent health care chair in classifying human biological information and adjusting the vibration frequency of the vibrator.

[0039] The technical effects of the above technical solution are as follows:

[0040] By providing a smart health care chair production method for efficiently debugging a neural network model, it can be ensured that the smart health care chair has higher accuracy and personalized experience during the production process. The implementation of the production method enables the smart health care chair to automatically adjust the massage method according to the individual differences of the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0042] Figure 1 This is one of the structural schematic diagrams of Example 1 of the present invention;

[0043] Figure 2 This is the second structural diagram of Example 1 of the present invention;

[0044] Figure 3 This is a flowchart of the operation of the control module in Example 1 of the present invention;

[0045] Figure 4 This is a schematic diagram of the structure of the control terminal in Example 1 of the present invention;

[0046] Figure 5 This is a flow chart of a method for acquiring target data in Example 1 of the present invention;

[0047] Figure 6 This is a flow chart of the data processing algorithm in Example 2 of the present invention;

[0048] Figure 7 It is a structural schematic diagram of the processing module in Example 2 of the present invention;

[0049] Figure 8 A flowchart of the operation of the neural network model in Example 2 of the present invention;

[0050] Fig. 9 This is a flow chart of the production method of the intelligent health care chair in Example 4 of the present invention.

[0051] in:

[0052] 1-Ontology;

[0053] 11- control module;

[0054] 12-Bio-sensing module;

[0055] 13-Health care hardware;

[0056] 131 - vibrator;

[0057] 2-Control terminal;

[0058] 21- storage module;

[0059] 22 - Processing module;

[0060] 221-Training module;

[0061] 222-confirmation module;

[0062] 23-Analysis module. DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application. The terms used herein in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0064] In order to make the purpose, technical solution and advantages of the embodiment of the present application clearer, the embodiment of the present application will be further described in detail with reference to the accompanying drawings. Below, some terms in the embodiment of the present application are explained to facilitate understanding by those skilled in the art.

[0065] A neural network is a computational model that mimics the way the human brain works. It is a complex network composed of a large number of interconnected nodes (or neurons). Each node represents a simple processing unit that can perform some basic mathematical operations. In a neural network, information is transmitted and processed not through a single logic gate, but through the connection weights between neurons. The working principle of a neural network is mainly to receive data through the input layer, and the data is transmitted layer by layer in the network. Each layer of neurons is processed according to the weights and activation functions, and finally reaches the output layer to produce results. The process of training a neural network is to adjust these weights so that the network can make correct predictions or decisions for specific tasks. There are many types of neural networks, including feedforward neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), etc. They are widely used in image recognition, speech recognition, natural language processing and other fields.

[0066] Human bioinformation refers to information related to human physiology and biology, which involves various systems and functions of the human body. This information is of great significance for understanding the physiological processes of the human body, disease diagnosis and treatment.

[0067] Mobile devices refer to portable electronic devices that usually have wireless communication capabilities, allowing users to transfer data and communicate without physical connection. Mobile devices include but are not limited to smartphones, tablets, laptops, portable game consoles, etc. These devices usually have touch screens, wireless connection functions (such as Wi-Fi and cellular networks), and can run a variety of applications to meet users' work, entertainment and communication needs at any location.

[0068] Although the present application is disclosed as above with preferred embodiments, it is not intended to limit the claims. Any technical personnel in this field may make several possible changes and modifications without departing from the concept of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims of the present application.

[0069] The present invention is further described in detail below in conjunction with specific embodiments, but the embodiments of the present invention are not limited thereto.

[0070] Example 1

[0071] like Figure 1-4As shown, the present application aims to solve the problem in the prior art that the smart health care chair cannot be adaptively adjusted according to the biological information of different users, and further designs the following technical scheme: a smart health care chair, comprising a main body 1 and a control terminal 2 connected to the main body 1; wherein the main body 1 comprises: a control module 11 connected to the control terminal 2, and provided with a data processing unit; specifically, the control module 11 can collect human biological information collected from the biological perception module 12, and transmit the information to the control terminal 22 via wireless communication. Among them, wireless communication includes but is not limited to Bluetooth, Wi-Fi, NFC and other technologies. In addition, in a specific embodiment, the control terminal 22 is a remote server, and the communication module of the control module 11 is electrically connected to the communication module (any existing communication module) to realize communication with the server.

[0072] Furthermore, the biosensing module 12 is electrically connected to the control module 11, and is used to detect the user's human biological information to be identified and transmit the human biological information to the control module 11; the health care hardware 13 is electrically connected to the control module 11, and includes at least one vibrator that can change the vibration frequency by receiving different vibration signals; wherein the vibrator is distributed in the main body 1 to provide a massage function.

[0073] Further, the control terminal 2 includes: a processing module 22, which is used to operate the neural network to classify the human biological information to be identified; a storage module 21, which is used to store the initial set and the additional set of human biological information, each human biological information in the initial set is represented by a different category represented by a designated first feature vector; each human biological information in the additional set is divided into different categories by the neural network according to the similarity between the designated second feature vector and the first feature vector; the control terminal 2 trains the neural network through the initial set and the additional set; an analysis module is used to match the human biological information processed by the processing module 22 to the corresponding data processing algorithm; the data processing algorithm reprocesses the human biological information to obtain target data;

[0074] Furthermore, the control module 11 is used to receive the target data transmitted by the control terminal 2 and adjust it into a vibration signal through the data processing unit.

[0075] Specifically, the working principle of the above-mentioned intelligent health care chair is as follows: when the user sits on the intelligent health care chair, the biological sensing module 12 starts to work and monitors the user's physiological parameters in real time, such as heart rate, blood pressure, body temperature, etc. These data are transmitted to the control terminal 22 through the wireless communication function of the control module 11. The processing module 22 in the control terminal 22 uses a neural network to classify and process these biological information to identify the user's health status and needs.

[0076] Furthermore, the storage module 21 stores a large amount of initial and additional sets of human biological information in the control terminal 22, and these data sets are used to train the neural network so that it can more accurately identify and classify new biological information. Through continuous learning and adjustment, the neural network can improve the accuracy of its predictions, thereby providing users with more personalized health care advice.

[0077] Furthermore, the analysis module performs an in-depth analysis of the biological information processed by the processing module 22 in the control terminal 22, and matches the corresponding data processing algorithms. These algorithms can further process the biological information, extract features that are instructive to the user's health status, and generate target data. The target data is then transmitted back to the control module 11.

[0078] Furthermore, after receiving the target data, the control module 11 converts the data into specific vibration signals through its data processing unit. These signals are sent to the vibrator 131 in the health care hardware 13, and the vibrator 131 adjusts the vibration frequency and intensity according to the received signals to achieve massage, relaxation or treatment effects.

[0079] Through the above technical solutions, the smart health care chair can make adaptive adjustments based on each user's unique biological information to provide personalized health care services. This adaptive adjustment not only improves the user's comfort and satisfaction, but also helps users better manage their health conditions.

[0080] Example 2

[0081] like Figure 5-7 As shown, the difference from Example 1 is that: in order to further reflect the processing method of human biological information by the classification module 22 of the present application, specifically, the data processing algorithm includes a first data processing algorithm and a second data processing algorithm;

[0082] Furthermore, the first data processing algorithm is used to match different categories of human biological information in the initial set with different target data transmitted by the corresponding network end; in a specific implementation, the target data covers a variety of massage modes of health care hardware 13, and the key to adjusting the massage mode is to change the vibration frequency of the health care hardware 13. In this embodiment, the human biological information in the initial set constitutes the basic data for training the neural network. By classifying the data in the initial set, the classification ability of the neural network model is improved, thereby achieving a high-precision classification effect in the real experience process; however, the classification itself cannot directly prompt the health care hardware 13 to perform adaptive adjustment of the vibration frequency. By matching a large amount of massage data (vibration frequency) information in reality with the information in the initial set, the final matching of the real information and the above massage data can be achieved.

[0083] Furthermore, the second data processing algorithm is used to match the target data of the human biological information in the initial set to the human biological information in the additional set of the same category as the human biological information in the initial set. In this way, the human biological information of the user of the smart health protection chair in the additional set is matched with the optimal massage data, thereby providing the user with a personalized massage experience. Through the second data processing algorithm, the system can effectively match these additional data with the data in the initial set, thereby customizing a massage plan for each user that best suits his or her physical condition and preferences.

[0084] To sum up, by combining the first data processing algorithm and the second data processing algorithm, the present application not only achieves high-precision classification of human biological information, but also can provide users with personalized massage experience based on their actual needs and feedback.

[0085] Furthermore, the human biological information in the initial set is obtained through the network terminal; the user inputs the user's real-time data into the network terminal server through the mobile client, and the network terminal server sends the above data to the control terminal 2, which further stores it in the initial set.

[0086] The other details that are the same as those in Example 1 are not described in detail in this example.

[0087] Example 3

[0088] like Figure 1-8 As shown, the difference from Example 1 is that: in order to further reflect the accurate allocation of the user's human life information by the neural network model of the present application, specifically, the processing module 22 includes a confirmation module 222 and a training module 221; the confirmation module 222 is used to confirm the similarity between the second vector of the human biological information in one or more additional sets and the first vector of the human biological information in any initial set, and confirm the human biological information pointed to by the second vector with a similarity greater than the first threshold as the category expressed by the relative first vector; in actual application, the working principle of the confirmation module 222 is as follows: when the user uses the smart health care chair, the biological perception module 12 monitors the user's physiological parameters in real time and transmits these data to the control terminal 2. The confirmation module 222 first performs a preliminary analysis on these data to determine whether they are similar to the biological information already in the initial set. Specifically, the confirmation module 222 also sets a first threshold value to determine whether the similarity of the human biological information in the additional set is high enough (through the similarity of the first vector and the second vector) to ensure that they can be accurately classified into the corresponding category of the human biological information in the initial set.

[0089] Further, the training module 221 processes the human biological information in the additional set through a neural network to enhance the accuracy of the confirmation module 222. This enables the neural network model to improve its classification ability by continuously learning the data in the initial set and the additional set. Specifically, the training module 221 is responsible for outputting one or more human biological information represented by the second vector in the category represented by the first vector to the initial set. The initial set is therefore able to obtain more human biological data information with the same classification, thereby improving the accuracy of the target data. It is worth noting that after the human biological information in the additional set is output to the initial set, its classification basis will be converted into the first vector (in view of the definition of the first vector is limited to the initial set).

[0090] Furthermore, the confirmation module 222 is also used to determine the second vector whose similarity is less than the second threshold as the first vector, and the human biometric information represented by the first vector determined by the second vector whose similarity is less than the second threshold represents different categories. In view of the fact that all types of human biometric information transmitted to the additional set through the user terminal are not fully considered during the construction of the initial data set, the present application aims to confirm whether the additional set contains human biometric information categories that are not considered in the initial set by setting a second threshold. Furthermore, the training module 221 outputs the human biometric information of different categories represented by the first vector determined by the second vector whose similarity is less than the second threshold to the initial set. At this point, the initial set realizes the supplement of the human biometric information categories that are not considered through the confirmation module 222, thereby realizing the supplement of the target data and avoiding missing some situations that should have been considered but were not considered in the initial data.

[0091] Furthermore, it is considered that after the human biological information in the additional set is incorporated into the initial set, new classification situations may be generated. Although these new human biological information actually still belong to certain categories in the initial set, they meet the classification condition of the second threshold; or, some human biological information that was originally classified as categories in the initial set has similarities with human biological information of other categories. In order to further optimize the neural network model of the present application, the processing module 22 calculates the first vector average of the human biological information of the same category in the initial set. When the similarity between any human biological information in the initial set and the average value exceeds the third threshold, the human biological information will be confirmed as the same category corresponding to the average value. Through this optimization method, the probability of misclassification can be reduced and the classification performance of the neural network can be further improved.

[0092] Furthermore, the network end is a mobile device, and the user uploads the user's human biometric information through the mobile device.

[0093] The other details that are the same as those in Example 1 are not described in detail in this example.

[0094] Example 4

[0095] like Figure 1-8 , the difference of embodiment 1 is: in order to further improve the processing capability of the health care chair of the present application on human biological information and the user experience effect, the human biological information includes: weight, height, disease type, heart rate, blood pressure, etc. The above human biological information basically meets the user experience requirements of the present embodiment, but the present application is not limited to the above exemplified information.

[0096] Furthermore, the health care hardware 13 also includes a heating device, a vibration device and an airbag; the control module 11 automatically adjusts the working state and parameters of the heating device, the vibration device and the airbag according to the target data. In a specific embodiment, when the health care hardware 13 receives the target information from the control module 11, the heating device will adjust the temperature according to the user's body temperature and body fat information to ensure that the user obtains appropriate thermal therapy effects while enjoying the massage. The vibration device will adjust the vibration frequency and intensity according to the electrocardiogram signal and the degree of force in the massage area to achieve the best relaxation effect. The airbag will be inflated and deflated according to the user's height and weight information to ensure that the massage points act accurately on the specific parts of the user.

[0097] Furthermore, for patients with heart disease, the target information includes key information that will automatically reduce the massage intensity and vibration frequency to drive the vibration device to avoid placing an additional burden on the heart. For users who need to lose weight, the target information will include body fat information, which will drive the health hardware 13 to adjust the massage method to promote fat burning and metabolism.

[0098] Furthermore, the control terminal 2 also has a user interface, through which the user can view his or her biological information, historical data, health advice, and adjust the settings of the health chair. In the specific implementation process, the user can interact with the control terminal 22 through a touch screen or voice command. The interface can display the user's heart rate, blood pressure and other key biological information in real time, and provide a historical data comparison and analysis function. In addition, the user can also manually adjust parameters such as massage trajectory, strength and temperature of the heating device according to personal preferences and needs.

[0099] Specifically, the biosensing module 12 is a flexible sensor array that fits the surface of the human body and monitors and records the user's human biometric information parameters in real time.

[0100] Other details that are the same as those in Example 1 are not described in detail in this application.

[0101] Example 5

[0102] like Fig. 9As shown, in order to further improve and ensure that the smart healthcare chair has higher accuracy and personalized experience during the production process, this embodiment designs a production method of the smart healthcare chair including any of claims 1-3. Specifically, it includes the following steps:

[0103] S101, the control terminal 2 obtains a set of human biological information stored in an initial set through a network terminal, and divides the human biological information into different categories, which are represented by different first vectors;

[0104] S202, the control module 11 transmits a set of human biological information obtained from the user by the biological sensing module 12 to an additional set of the control terminal 2, where the category of the human biological information is represented by a second vector;

[0105] S303, outputting the human biological information indicated by the second vector that is not similar to the first vector of the human biological information in the initial set to the initial set, and changing the second vector to the first vector to form a new category of human biological information;

[0106] S404, using the above integrated initial set to train the neural network, and debugging the accuracy of the intelligent health care chair in classifying human biological information and adjusting the vibration frequency of the vibrator.

[0107] In step S101, its main function is to establish a basic human bio-information database, i.e., the initial set, to provide data support for the subsequent personalized customization and precise adjustment of the intelligent health care chair. Through the control terminal 2, extensive and comprehensive human bio-information is obtained from the network end. This information covers data of various dimensions such as different ages, genders, body shapes, and health conditions. These data are classified into different categories, such as height, weight, body fat percentage, muscle mass, heart rate, blood pressure, etc., and a unique first vector representation is assigned to each category. This classification and vectorized representation not only facilitates the rapid retrieval and processing of data, but also lays the foundation for subsequent similarity matching and training of machine learning models.

[0108] In step S202, the control module 11 receives real-time human biological information data from the biological sensing module 12. These data include but are not limited to key indicators such as the user's body temperature, heart rate, blood pressure, etc. The control module 11 compares these data with the data in the initial set to determine whether they belong to a known category or whether a new category needs to be created. If the data is not similar to any category in the initial set, the control module 11 marks the data as a new category and converts the corresponding second vector into a first vector for use in subsequent processing.

[0109] In step S303, the control terminal 2 outputs the human biological information represented by the second vectors that do not form a similar relationship with the data in the initial set to the initial set, and converts these second vectors into first vectors to form new categories. This process ensures that the smart healthcare chair can continuously learn and adapt to the user's new biological information, thereby providing more personalized and accurate healthcare services.

[0110] In step S404, the control terminal 2 uses the integrated initial set to train the neural network to improve the accuracy of the intelligent health care chair in classifying human biological information and adjusting the vibration frequency of the vibrator. By continuously optimizing the neural network model, the intelligent health care chair can better understand the user's physical condition and needs, thereby providing more intimate and effective health care services.

[0111] The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An intelligent health care chair, characterized in that: including a main body portion and a control terminal connected to said main body portion; The body comprises: A control module, connected to the control terminal and provided with a data processing unit; A biological sensing module, electrically connected to the control module, for detecting the user's human biological information to be identified and transmitting the human biological information to the control module; Health care hardware, electrically connected to the control module, including at least one vibrator capable of changing the vibration frequency by receiving different vibration signals; The control terminal comprises: A processing module, used for operating a neural network to classify and process the human biological information to be identified; A storage module, used for storing an initial set and an additional set of human biological information, each human biological information in the initial set is represented by a different category by a designated first feature vector; each human biological information in the additional set is divided into different categories by the neural network according to a similarity between the designated second feature vector and the first feature vector; the control terminal trains the neural network through the initial set and the additional set; An analysis module, used for matching the human biological information processed by the processing module to a corresponding data processing algorithm; the data processing algorithm reprocesses the human biological information to obtain target data; The control module is used to receive the target data transmitted by the control terminal and adjust it into the vibration signal through the data processing unit.

2. The intelligent health care chair according to claim 1, characterized in that: The data processing algorithm includes a first data processing algorithm and a second data processing algorithm; The first data processing algorithm is used to match different categories of human biological information in the initial set with different target data transmitted by the corresponding network end; The second data processing algorithm is used to match the target data of the human biological information in the initial set to the human biological information in the additional set of the same category as the human biological information in the initial set.

3. The intelligent health care chair according to claim 1, characterized in that: The initially concentrated human biological information is obtained through a network terminal; The human biological information in the additional set is collected by the biological sensing module and transmitted to the storage module by the control module.

4. The intelligent health care chair according to claim 1, characterized in that: The processing module includes a confirmation module and a training module; The confirmation module is used to confirm the similarity between the second vector of the human biological information in one or more of the additional sets and the first vector of the human biological information in any of the initial sets, and confirm the human biological information pointed to by the second vector with the similarity greater than a first threshold as the category expressed by the relative first vector; The training module is used to output one or more pieces of human biological information referred to by the second vector that are classified into the category represented by the first vector to the initial set.

5. The intelligent health care chair according to claim 4, characterized in that: The confirmation module is used to determine the second vector whose similarity is less than a second threshold as the first vector, and the human biological information is represented by a first vector determined by the second vector whose similarity is less than the second threshold to represent different categories.

6. The intelligent health care chair according to claim 4, characterized in that: The training module outputs the human biological information of different categories represented by the first vector determined by the second vector whose similarity is less than a second threshold into an initial set.

7. The intelligent health care chair according to any one of claims 1 to 6, characterized in that: The processing module calculates the average value of the first vector of the human biological information of the same category in the initial set, and when the similarity between any human biological information in the initial set and the average value is greater than a third threshold, the human biological information is confirmed as the classification of the human biological information of the same category referred to by the average value.

8. The intelligent health care chair according to claim 1, characterized in that: The network end is a mobile device, and the user uploads the user's human biometric information through the mobile device.

9. The intelligent health care chair according to claim 1, characterized in that: The human biological information includes: weight, height, disease type, heart rate, and blood pressure.

10. A method for producing the intelligent health care chair as claimed in claims 1 to 9, characterized in that: The following steps are involved: S101, the control terminal obtains a set of human biological information stored in an initial set through a network terminal, and divides the human biological information into different categories, which are represented by different first vectors; S202, the control module transmits a set of human biological information obtained from the user by the biological sensing module to an additional set of the control terminal, where the category of the human biological information is represented by a second vector; S303, outputting the human biological information referred to by the second vector that is not similar to the first vector of the human biological information in the initial set to the initial set, and changing the second vector to the first vector to form a new category of the human biological information; S404: Using the above integrated initial set to train a neural network, so as to improve the accuracy of the intelligent health care chair in classifying human biological information and the accuracy of adjusting the vibration frequency of the vibrator.

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