Blood pressure measuring method, device and system based on AI intelligent voice interaction

Abstract

The invention relates to the technical field of intelligent medical treatment, and discloses a blood pressure measuring method, device and system based on AI intelligent voice interaction, and the method comprises the following steps: receiving a voice signal from a user; identifying identity information of the user according to the voice signal of the user; according to the identity information of the user, physical sign parameters and historical measurement records, related to blood pressure measurement, of the user are inquired; analyzing the voice signal of the user by using a preset AI model, and judging whether the user sends a measurement instruction or not; when it is judged that the user sends the measurement instruction, measurement preparation work is executed according to the physical sign parameters and historical measurement records of the user; after the measurement preparation is completed, the blood pressure of the user is measured. By introducing the AI intelligent voice interaction technology and the personalized measurement preparation process, the convenience, accuracy and user experience of blood pressure measurement are remarkably improved, and a more intelligent and intimate health monitoring solution is provided for the user.

Description

Technical Field

[0001] The present invention relates to the field of intelligent medical technology, and more specifically, to a blood pressure measurement method, device and system based on AI intelligent voice interaction. Background Art

[0002] With the rapid development of medical technology and information technology, home health monitoring equipment has gradually become popular. Among them, blood pressure monitors, as one of the most common home medical devices, are widely used in homes and medical institutions. Traditional blood pressure measurement methods usually rely on manual operation or button control, which not only requires high technical skills from users, but is also not convenient to use in some cases (such as the elderly or people with limited mobility). In addition, traditional blood pressure monitors lack personalized settings and intelligent management functions, and cannot provide the best measurement experience based on individual differences of users.

[0003] In recent years, the development of artificial intelligence (AI) and Internet of Things (IoT) technologies has brought new opportunities for blood pressure measurement. As a natural and intuitive way of human-computer interaction, intelligent voice interaction technology has been widely used in smart homes, smart assistants and other fields. However, in the field of medical health, especially in blood pressure measurement, the application of intelligent voice interaction is still in its early stages and has not yet fully realized its potential.

[0004] In response to the above problems, the present invention proposes a blood pressure measurement method, device and system based on AI intelligent voice interaction, aiming to improve the convenience, accuracy and user experience of blood pressure measurement through advanced voice recognition technology and personalized measurement preparation process. Summary of the invention

[0005] In order to solve the above-mentioned technical problems, this application is proposed to provide a blood pressure measurement method, device and system based on AI intelligent voice interaction, aiming to improve the convenience, accuracy and user experience of blood pressure measurement through advanced voice recognition technology and personalized measurement preparation process.

[0006] In the first aspect, the present invention provides a blood pressure measurement method based on AI intelligent voice interaction, including: receiving a voice signal from a user; identifying the user's identity information based on the user's voice signal; querying the user's vital sign parameters and historical measurement records related to blood pressure measurement based on the user's identity information; using a preset AI model to analyze the user's voice signal to determine whether the user has issued a measurement instruction; when it is determined that the user has issued the measurement instruction, performing measurement preparation work based on the user's vital sign parameters and historical measurement records; after the measurement preparation is completed, measuring the user's blood pressure.

[0007] Optionally, in the aforementioned blood pressure measurement method based on AI intelligent voice interaction, a preset AI model is used to analyze the user's voice signal, including: after converting the user's voice signal into text, segmenting the text; taking any word in the text as the target word, calculating the word embedding vector of the target word; and context-aware vector , where the context-aware vector of the target word Using a convolutional neural network to calculate, the context-aware vector of the target word , The function represents the maximum pooling operation of the convolutional neural network. The function is a linear rectifier function. Function is used to extract character vectors, is the number of characters in the target word, represents the i-th character in the target word, is the number of characters covered by the convolution kernel of the convolutional neural network, is the weight matrix of the convolution kernel, is a preset bias item; according to the word embedding vector of the target word and context-aware vector , determine the characteristics of the target word; and analyze the user's voice signal based on the characteristics of each word in the text.

[0008] Optionally, in the aforementioned blood pressure measurement method based on AI intelligent voice interaction, before analyzing the user's voice signal based on the characteristics of each word in the text, it also includes: calculating the background relevance of the target word based on a preset medical knowledge base. , wherein the medical knowledge base has Knowledge items, is the jth knowledge entry, is the word embedding vector of the j-th knowledge term, is the preset time decay factor, Indicates the current time. represents the release time of the jth knowledge term; according to the background relevance of the target word , and modify the characteristics of the target word.

[0009] Optionally, in the aforementioned blood pressure measurement method based on AI intelligent voice interaction, before analyzing the user's voice signal based on the characteristics of each word in the text, it also includes: calculating the occurrence frequency of the target word ,in, represents the frequency of the target word appearing in the text, represents the number of knowledge entries in the medical knowledge base where the target word appears. is a preset smoothing factor; based on the frequency of occurrence of the target word , and modify the characteristics of the target word.

[0010] Optionally, in the aforementioned blood pressure measurement method based on AI intelligent voice interaction, the user's vital sign parameters include the user's age, and measurement preparation work is performed according to the user's vital sign parameters and historical measurement records, including: generating voice broadcast content to prompt the user to perform measurement preparation work; setting the voice broadcast speed according to the user's age; and playing the voice broadcast content at the voice broadcast speed.

[0011] Optionally, in the aforementioned blood pressure measurement method based on AI intelligent voice interaction, the user's physical sign parameters include the user's arm circumference, and the measurement preparation work is performed according to the user's physical sign parameters and historical measurement records, including: calculating the initial measurement pressure when measuring blood pressure according to the user's arm circumference and historical blood pressure data; ,in, is the preset weight coefficient, is the user's arm circumference, is the preset bias value, is the number of records of the historical measurement record, , , are the systolic blood pressure, diastolic blood pressure and measurement time in the dth historical measurement record, is a linear function whose value varies with According to the calculation result, the initial measurement pressure is adjusted.

[0012] Optionally, in the aforementioned blood pressure measurement method based on AI intelligent voice interaction, after the measurement preparation is completed, the blood pressure of the user is measured, including: extracting acoustic features from the user's voice signal, including fundamental frequency and energy; detecting the signal-to-noise ratio of the user's voice signal; and calculating the user's emotional level according to the fundamental frequency, energy and signal-to-noise ratio of the user's voice signal. ,in, The function is a nonlinear action function. is the fundamental frequency of the user's speech signal, is the signal-to-noise ratio of the user's speech signal, is the energy of the user's speech signal, represents the variance of the energy of the user's speech signal, is a preset balance coefficient; according to the user's emotional level , and correct the measurement results.

[0013] Optionally, in the aforementioned blood pressure measurement method based on AI intelligent voice interaction, after the measurement preparation is completed, the user's blood pressure is measured, including: analyzing the user's blood pressure change trend based on the current measurement results and the historical measurement records; and generating suggestion information for the user based on the user's blood pressure change trend.

[0014] In a second aspect, the present invention provides a blood pressure measurement device based on AI intelligent voice interaction, comprising: a processor and a memory; the processor is used to process the program code stored in the memory, and the program code is used to implement the blood pressure measurement method based on AI intelligent voice interaction as mentioned above.

[0015] In the third aspect, the present invention provides a blood pressure measurement system based on AI intelligent voice interaction, including: a voice receiving module, receiving a voice signal from a user; an identity recognition module, identifying the identity information of the user according to the voice signal of the user; a query module, querying the vital sign parameters and historical measurement records of the user related to blood pressure measurement according to the identity information of the user; a judgment module, analyzing the voice signal of the user using a preset AI model to determine whether the user has issued a measurement instruction; a measurement preparation module, performing measurement preparation work according to the vital sign parameters and historical measurement records of the user when it is determined that the user has issued the measurement instruction; and a measurement module, measuring the user's blood pressure after the measurement preparation is completed.

[0016] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0017] According to the technical solution of the present invention, by introducing AI intelligent voice interaction technology and personalized measurement preparation process, the convenience, accuracy and user experience of blood pressure measurement are significantly improved, providing users with a more intelligent and considerate health monitoring solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0019] Figure 1 It is a flow chart of a blood pressure measurement method based on AI intelligent voice interaction according to an embodiment of the present application;

[0020] Figure 2 It is a partial flow chart of a blood pressure measurement method based on AI intelligent voice interaction according to an embodiment of the present application;

[0021] Figure 3 Another layout flow chart of a blood pressure measurement method based on AI intelligent voice interaction according to an embodiment of the present application;

[0022] Figure 4 is another partial flow chart of the blood pressure measurement method based on AI intelligent voice interaction according to an embodiment of the present application;

[0023] Figure 5 This is a block diagram of a blood pressure measurement system based on AI intelligent voice interaction according to an embodiment of the present application. DETAILED DESCRIPTION

[0024] Some embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0025] like Figure 1 As shown, in one embodiment of the present invention, a blood pressure measurement method based on AI intelligent voice interaction is provided, comprising:

[0026] Step S110: receiving a voice signal from a user.

[0027] Step S120: Identify the user's identity information based on the user's voice signal.

[0028] In this embodiment, based on the user's identity information, the system can quickly retrieve and analyze the latest vital sign parameters and historical records related to blood pressure measurement, providing a scientific basis for subsequent measurement preparation work.

[0029] Step S130, querying the user's vital sign parameters and historical measurement records related to blood pressure measurement based on the user's identity information.

[0030] Step S140: Use a preset AI model to analyze the user's voice signal to determine whether the user issues a measurement instruction.

[0031] In this embodiment, a preset AI model is used to perform in-depth analysis of the user's voice signal and accurately identify the user's measurement intention, so that the user can control the blood pressure monitor through natural language expression without complicated operating procedures.

[0032] Step S150, when it is determined that the user issues a measurement instruction, measurement preparation is performed according to the user's physical sign parameters and historical measurement records.

[0033] Step S160, after the measurement preparation is completed, measure the user's blood pressure.

[0034] According to the technical solution of this embodiment, by introducing AI intelligent voice interaction technology and personalized measurement preparation process, the convenience, accuracy and user experience of blood pressure measurement are significantly improved, providing users with a more intelligent and considerate health monitoring solution.

[0035] like Figure 2 As shown, in one embodiment of the present invention, a blood pressure measurement method based on AI intelligent voice interaction is provided. Compared with the aforementioned embodiment, the blood pressure measurement method based on AI intelligent voice interaction in this embodiment, step S140 includes:

[0036] Step S210: After converting the user's voice signal into text, the text is segmented.

[0037] Step S220: taking any word in the text as the target word, and calculating the word embedding vector of the target word and context-aware vector , where the context-aware vector of the target word is The context-aware vector of the target word is calculated using a preset convolutional neural network. , The function represents the maximum pooling operation of the convolutional neural network. The function is a linear rectifier function. Function is used to extract character vectors, is the number of characters in the target word, represents the i-th character in the target word, is the number of characters covered by the convolution kernel of the convolutional neural network, is the weight matrix of the convolution kernel, is the preset bias item.

[0038] In this embodiment, by converting the user's voice signal into text and performing word segmentation, the system can more accurately capture the meaning of each word. The word embedding vector and context-aware vector of the target word are further calculated, so that not only the meaning of the word itself can be understood, but also its specific context in the sentence can be perceived. The use of CNN to calculate the context-aware vector and the use of operations such as maximum pooling and linear rectification functions enhance the understanding of the character sequence around the word, thereby improving the ability to capture complex contexts.

[0039] Step S230: based on the word embedding vector of the target word and context-aware vector , determine the characteristics of the target words.

[0040] Step S240, calculating the background relevance of the target word based on the preset medical knowledge base , among which, the medical knowledge base has Knowledge items, is the jth knowledge entry, is the word embedding vector of the jth knowledge term, is the preset time decay factor, Indicates the current time. Indicates the release time of the jth knowledge entry.

[0041] In this embodiment, the background relevance of the target word is calculated by comparing it with the preset medical knowledge base to ensure that the word can be accurately classified and understood based on the latest medical information. The introduction of the time decay factor makes the judgment more in line with the current level of medical development and avoids the influence of outdated information. The characteristics of the target word are modified according to the background relevance, which can better adapt to the expression habits of different users and the changes in medical terms, thereby improving the recognition accuracy.

[0042] Step S250: based on the background relevance of the target word , and modify the characteristics of the target words.

[0043] Step S260: Calculate the frequency of occurrence of the target word ,in, Indicates the frequency of the target word in the text. Indicates the number of knowledge entries in the medical knowledge base where the target word appears. is the preset smoothing factor.

[0044] In this embodiment, by introducing a smoothing factor and calculating the frequency of occurrence of the target words, the problem of low-frequency words being ignored is effectively avoided. At the same time, the importance of words in different data sources can be comprehensively considered by combining the actual frequency of occurrence in the text and the number of entries in the medical knowledge base. Based on the calculated frequency of occurrence, the characteristics of the target words are further modified, which can efficiently identify key information in large-scale texts and improve the accuracy of the overall analysis.

[0045] Step S270: based on the frequency of occurrence of the target word , and modify the characteristics of the target words.

[0046] Step S280: analyzing the user's voice signal based on the features of each word in the text.

[0047] According to the technical solution of this embodiment, by introducing advanced natural language processing technology and personalized background correlation evaluation, the ability to understand and analyze user voice signals is significantly improved, thereby achieving more accurate command recognition, smarter measurement preparation and better user experience. This innovative solution provides users with a more intelligent and intimate blood pressure measurement service, which has important application value and broad application prospects.

[0048] In one embodiment of the present invention, a blood pressure measurement method based on AI intelligent voice interaction is provided. Compared with the aforementioned embodiment, in the blood pressure measurement method based on AI intelligent voice interaction of this embodiment, the user's vital sign parameters include the user's age, and step S150 includes:

[0049] (1) Generate voice announcement content to prompt the user to perform measurement preparation work.

[0050] In this embodiment, specific voice announcement content is generated to clearly prompt the user to perform measurement preparation work, such as "Please relax your arms and place them on the table" or "Please remain still until the measurement is completed." This personalized prompt helps guide the user to operate correctly and ensure the stability and accuracy of the measurement environment.

[0051] (2) Set the voice broadcast speed according to the user’s age.

[0052] (3) Play the voice broadcast content at the voice broadcast speed.

[0053] According to the technical solution of this embodiment, by considering the age of the user, the system can intelligently set the voice broadcast speed suitable for different age groups. For example, for the elderly, the system can use a slower broadcast speed to ensure that they have enough time to understand and respond to the prompt information, avoiding confusion or misunderstanding caused by too fast a speech speed. For young people, a faster broadcast speed can be selected to improve interaction efficiency and reduce waiting time.

[0054] like Figure 3 As shown, in one embodiment of the present invention, a blood pressure measurement method based on AI intelligent voice interaction is provided. Compared with the aforementioned embodiment, in the blood pressure measurement method based on AI intelligent voice interaction of this embodiment, the user's physical sign parameters include the user's arm circumference, and step S150 includes:

[0055] Step S310, calculating the initial measurement pressure when measuring blood pressure based on the user's arm circumference and historical blood pressure data ,in, is the preset weight coefficient, is the user's arm circumference, is the preset bias value, is the number of records for historical measurement records, , , are the systolic blood pressure, diastolic blood pressure and measurement time in the dth historical measurement record, is a linear function whose value varies with decreases with the increase of .

[0056] In this embodiment, the preset weight coefficient and bias value are used to ensure that the influence of arm circumference on the initial measurement pressure is reasonably evaluated, and users with different arm circumferences can obtain different initial pressure settings. The more recent historical measurement records are given higher weights, while the weights of more distant data are gradually reduced, so that the calculation results are more in line with the current health status of the user. At the same time, logarithmic transformation of historical blood pressure data can effectively compress the dynamic range and avoid the influence of extreme values ​​on the calculation results.

[0057] Step S320: adjusting the initial measurement pressure according to the calculation result.

[0058] According to the technical solution of this embodiment, the function of calculating the initial measurement pressure based on the user's arm circumference and historical blood pressure data is introduced, which significantly improves the accuracy and efficiency of blood pressure measurement, and provides users with a more intelligent, convenient and personalized health monitoring solution. This innovative improvement not only optimizes the measurement preparation process, but also provides different user groups with better blood pressure management services, which has important application value and broad application prospects.

[0059] like Figure 4 As shown, in one embodiment of the present invention, a blood pressure measurement method based on AI intelligent voice interaction is provided. Compared with the aforementioned embodiment, the blood pressure measurement method based on AI intelligent voice interaction in this embodiment, step S160, includes:

[0060] Step S410: extracting acoustic features from the user's voice signal, including fundamental frequency and energy.

[0061] Step S420: Detect the signal-to-noise ratio of the user's voice signal.

[0062] Step S430, calculating the user's emotion level based on the fundamental frequency, energy and signal-to-noise ratio of the user's voice signal ,in, The function is a nonlinear action function. is the fundamental frequency of the user's voice signal, is the signal-to-noise ratio of the user's voice signal, is the energy of the user's voice signal, Represents the variance of the energy of the user's speech signal, is the preset balance factor.

[0063] In this embodiment, the fundamental frequency and energy are extracted from the user's voice signal to capture the subtle changes in the user's voice, which are closely related to the emotional state. The signal-to-noise ratio is introduced as an additional evaluation indicator to accurately evaluate the user's emotional state in a noisy environment.

[0064] Step S440, based on the user's emotional level , and correct the measurement results.

[0065] According to the technical solution of this embodiment, the measurement result is appropriately corrected according to the calculated emotional level. For example, when the user is in an anxious or excited state, the blood pressure may temporarily rise; the final measurement result can be adjusted according to the emotional level to reduce the influence of psychological factors on the measurement, thereby improving the accuracy of the measurement.

[0066] In one embodiment of the present invention, a blood pressure measurement method based on AI intelligent voice interaction is provided. Compared with the aforementioned embodiment, the blood pressure measurement method based on AI intelligent voice interaction in this embodiment, step S160, includes:

[0067] (1) Analyze the user's blood pressure change trend based on the current measurement results and historical measurement records.

[0068] (2) Generate advice information for users based on their blood pressure change trends.

[0069] According to the technical solution of this embodiment, by combining the current measurement results with historical measurement records, the user's blood pressure change trend can be comprehensively analyzed, including short-term fluctuations and long-term trends. This comprehensive evaluation helps to more accurately capture the user's health status. The user's blood pressure trend model is updated based on the data of each measurement to ensure that the analysis results always reflect the latest health status.

[0070] In one embodiment of the present invention, a blood pressure measurement device based on AI intelligent voice interaction is provided, comprising: a processor and a memory; the processor is used to process the program code stored in the memory, and the program code is used to implement the blood pressure measurement method based on AI intelligent voice interaction as in the aforementioned embodiment. According to the technical solution of this embodiment, by introducing AI intelligent voice interaction technology and personalized measurement preparation process, the convenience, accuracy and user experience of blood pressure measurement are significantly improved, providing users with a more intelligent and considerate health monitoring solution.

[0071] like Figure 5 As shown, in one embodiment of the present invention, a blood pressure measurement system based on AI intelligent voice interaction is provided, comprising:

[0072] The voice receiving module 510 receives a voice signal from a user.

[0073] The identity recognition module 520 recognizes the user's identity information according to the user's voice signal.

[0074] In this embodiment, based on the user's identity information, the system can quickly retrieve and analyze the latest vital sign parameters and historical records related to blood pressure measurement, providing a scientific basis for subsequent measurement preparation work.

[0075] The query module 530 queries the user's vital sign parameters and historical measurement records related to blood pressure measurement according to the user's identity information.

[0076] The judgment module 540 uses a preset AI model to analyze the user's voice signal to determine whether the user issues a measurement instruction.

[0077] In this embodiment, a preset AI model is used to perform in-depth analysis of the user's voice signal and accurately identify the user's measurement intention, so that the user can control the blood pressure monitor through natural language expression without complicated operating procedures.

[0078] The measurement preparation module 550 performs measurement preparation work according to the user's physical sign parameters and historical measurement records when it is determined that the user issues a measurement instruction.

[0079] The measurement module 560 measures the user's blood pressure after the measurement preparation is completed.

[0080] According to the technical solution of this embodiment, by introducing AI intelligent voice interaction technology and personalized measurement preparation process, the convenience, accuracy and user experience of blood pressure measurement are significantly improved, providing users with a more intelligent and considerate health monitoring solution.

[0081] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[0082] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0083] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0084] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0085] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A blood pressure measurement method based on AI intelligent voice interaction, including: receiving a voice signal from a user; Identifying identity information of the user according to the voice signal of the user; According to the identity information of the user, query the vital sign parameters and historical measurement records of the user related to blood pressure measurement; Using a preset AI model to analyze the user's voice signal to determine whether the user issues a measurement instruction; When it is determined that the user issues the measurement instruction, performing measurement preparation work according to the user's physical sign parameters and historical measurement records; After the measurement preparation is completed, the blood pressure of the user is measured.

2. The blood pressure measurement method based on AI intelligent voice interaction according to claim 1, wherein: The user's voice signal is analyzed using a preset AI model, including: After converting the user's voice signal into text, segmenting the text; Take any word in the text as the target word and calculate the word embedding vector of the target word and context-aware vector , where the context-aware vector of the target word The context-aware vector of the target word is calculated using a preset convolutional neural network. , The function represents the maximum pooling operation of the convolutional neural network. The function is a linear rectifier function. Function is used to extract character vectors, is the number of characters in the target word, represents the i-th character in the target word, is the number of characters covered by the convolution kernel of the convolutional neural network, is the weight matrix of the convolution kernel, is the preset bias item; According to the word embedding vector of the target word and context-aware vector , determining the characteristics of the target word; The user's voice signal is analyzed based on the features of each word in the text.

3. The blood pressure measurement method based on AI intelligent voice interaction according to claim 2, wherein: Before analyzing the user's voice signal based on the features of each word in the text, the blood pressure measurement method for AI intelligent voice interaction further includes: Based on the preset medical knowledge base, calculate the background relevance of the target word , wherein the medical knowledge base has Knowledge items, is the jth knowledge entry, is the word embedding vector of the j-th knowledge term, is the preset time decay factor, Indicates the current time. represents the release time of the j-th knowledge entry; According to the background relevance of the target word , and modify the characteristics of the target word.

4. The blood pressure measurement method based on AI intelligent voice interaction according to claim 3, wherein: Before analyzing the user's voice signal based on the features of each word in the text, the blood pressure measurement method based on AI intelligent voice interaction further includes: Calculate the frequency of occurrence of the target word ,in, represents the frequency of the target word appearing in the text, represents the number of knowledge entries in the medical knowledge base where the target word appears. is the preset smoothing factor; Based on the frequency of occurrence of the target words , and modify the characteristics of the target word.

5. The blood pressure measurement method based on AI intelligent voice interaction according to claim 1, wherein: The user's physical sign parameters include the user's age, and performing measurement preparation work according to the user's physical sign parameters and historical measurement records includes: Generate voice announcement content to prompt the user to perform measurement preparation work; Setting the voice broadcast speed according to the age of the user; The voice broadcast content is played at the voice broadcast speed.

6. The blood pressure measurement method based on AI intelligent voice interaction according to claim 1, wherein: The user's physical sign parameters include the user's arm circumference, and the measurement preparation work is performed according to the user's physical sign parameters and historical measurement records, including: Calculate the initial measurement pressure when measuring blood pressure according to the user's arm circumference and historical blood pressure data ,in, is the preset weight coefficient, is the user's arm circumference, is the preset bias value, is the number of records of the historical measurement record, , , are the systolic blood pressure, diastolic blood pressure and measurement time in the dth historical measurement record, is a linear function whose value varies with decreases with the increase of According to the calculation result, the initial measurement pressure is adjusted.

7. The blood pressure measurement method based on AI intelligent voice interaction according to claim 1, wherein: After the measurement preparation is completed, measuring the blood pressure of the user includes: Extracting acoustic features from the user's speech signal, including fundamental frequency and energy; Detecting a signal-to-noise ratio of a speech signal of the user; Calculate the user's emotional level based on the fundamental frequency, energy and signal-to-noise ratio of the user's voice signal ,in, The function is a nonlinear action function. is the fundamental frequency of the user's speech signal, is the signal-to-noise ratio of the user's speech signal, is the energy of the user's speech signal, represents the variance of the energy of the user's speech signal, is the preset balance coefficient; According to the user's emotional level , and correct the measurement results.

8. The blood pressure measurement method based on AI intelligent voice interaction according to claim 1, wherein: After the measurement preparation is completed, measuring the blood pressure of the user includes: Analyze the blood pressure change trend of the user according to the current measurement result and the historical measurement record; Generate suggestion information for the user according to the blood pressure change trend of the user.

9. Blood pressure measurement equipment based on AI intelligent voice interaction, including: Processor and memory; The processor is used to process the program code stored in the memory, and the program code is used to implement the blood pressure measurement method based on AI intelligent voice interaction according to any one of claims 1 to 8.

10. Blood pressure measurement system based on AI intelligent voice interaction, including: A voice receiving module receives a voice signal from a user; An identity recognition module, which recognizes the identity information of the user according to the voice signal of the user; A query module, for querying the user's vital sign parameters and historical measurement records related to blood pressure measurement according to the user's identity information; A judgment module, using a preset AI model to analyze the user's voice signal to determine whether the user issues a measurement instruction; A measurement preparation module, when it is determined that the user issues the measurement instruction, performs measurement preparation work according to the user's physical sign parameters and historical measurement records; The measuring module measures the blood pressure of the user after the measurement preparation is completed.

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