Intelligent relieving control management method and system based on puncture pain

Abstract

The invention discloses an intelligent relieving control management method and system based on puncture pain, and relates to the technical field of intelligent relieving control management, and the method comprises the steps: setting a pain threshold value and a sensitive tension threshold value of a patient based on the individual difference information and the specific puncture position of the patient; the physiological indexes and the language content of the patient are analyzed according to the sensitive tension threshold value of the patient, whether the patient has excessive tension or not is judged, then an intelligent voice pacifying mechanism is triggered, and intelligent voice content is selected according to individual differences of the patient; triggering an intelligent pain relief control mechanism according to the physiological indexes of the patient and a pain threshold value; based on real-time monitoring of physiological indexes of a patient, control parameters of an intelligent pain relief control mechanism are adjusted and optimized in real time, and the control parameters are recorded. Intelligent and personalized pain management and pacification are realized, and the comfort and satisfaction of the patient are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent relief control management, and in particular to an intelligent relief control management method and system based on puncture pain. Background Art

[0002] Puncture pain refers to the pain caused by acupuncture, injection, blood drawing, puncture operation, etc. This pain usually occurs during medical procedures, and patients often experience varying degrees of discomfort or pain during these operations. Puncture pain is common in clinical practice. Whether it is common blood drawing, infusion, injection, or more complex medical operations (such as puncture biopsy, puncture catheterization, etc.), it may cause discomfort to patients, especially for children, the elderly or patients with psychological pressure. The pain caused by puncture may be more obvious, and even cause patients to avoid necessary medical operations in the future, thus affecting the overall treatment effect. With the advancement of modern medical technology, more and more medical operations rely on precise puncture technology, and puncture pain management has gradually become an important issue in clinical medicine.

[0003] Traditional pain relief methods are usually based on universal standards and treatment plans, which means that all patients are treated in almost the same way without taking into account individual differences among patients, such as tolerance and sensitivity to pain. In addition, in traditional pain management, the focus is usually on the relief of physical pain, while ignoring the impact of emotions such as anxiety and tension on pain perception. Most existing pain relief technologies are passive and will only take relevant relief measures when the patient clearly expresses pain. They are unable to respond to the patient's physiological changes or emotional fluctuations in a timely manner. At the same time, existing pain relief technologies rely on a single method, such as drug therapy or a single physical therapy (such as cold compress, hot compress, etc.), resulting in limited treatment effects and may cause side effects or discomfort in some cases.

[0004] Therefore, in response to the above problems, there is an urgent need for an intelligent relief control management method and system based on puncture pain. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an intelligent relief control management method and system based on puncture pain, which solves the problems of inaccurate pain management, lack of immediate response and personalized comfort during the patient's puncture process.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent relief control management method based on puncture pain, comprising the following steps: obtaining the patient's individual difference information based on the patient's authorization, and determining the patient's specific puncture position; setting the patient's pain threshold and sensitivity tension threshold based on the patient's individual difference information and the specific puncture position; real-time monitoring of the patient's physiological indicators, and capturing the patient's language content, using the patient's sensitivity tension threshold to analyze the patient's physiological indicators and language content, to determine whether the patient is overly nervous, and then triggering an intelligent voice soothing mechanism, and selecting intelligent voice content according to the patient's individual differences; triggering an intelligent pain relief control mechanism based on the patient's physiological indicators and pain thresholds, the intelligent pain relief control mechanism including automatic contraction of the watch ring, vibration of the watch ring and cooling; based on real-time monitoring of the patient's physiological indicators, real-time adjustment and optimization of the control parameters of the intelligent pain relief control mechanism, and recording the control parameters, the control parameters including the contraction strength of the watch ring, vibration intensity and cooling intensity.

[0007] Furthermore, the specific analysis of setting the patient's pain threshold and sensitivity-stress threshold based on the patient's individual difference information and specific puncture position is as follows: obtaining historical puncture record information based on the authorization of each historical puncture patient, the historical puncture record information including the pain threshold, sensitivity-stress threshold and individual difference information and specific puncture position of each historical puncture patient; quantifying the individual difference information and specific puncture position of each historical puncture patient, and then using multiple regression to analyze the individual difference information, specific puncture position and pain threshold, sensitivity-stress threshold, respectively, to identify the relationship between individual difference information, specific puncture position and pain threshold, as well as the relationship between individual difference information, specific puncture position and sensitivity-stress threshold; simulating the patient's individual difference information and specific puncture position using the relationship between individual difference information, specific puncture position and pain threshold to obtain the patient's pain threshold; simulating the patient's individual difference information and specific puncture position using the relationship between individual difference information, specific puncture position and sensitivity-stress threshold to obtain the patient's sensitivity-stress threshold.

[0008] Furthermore, the individual difference information includes patient age, patient gender, patient body fat percentage, patient medical history and patient pain sensitivity history; the specific puncture locations include bone marrow puncture, thoracic puncture, abdominal puncture, lumbar puncture and punctures at other sites.

[0009] Furthermore, the patient's sensitivity and tension threshold is used to analyze the patient's physiological indicators and language content to determine whether the patient is overly nervous, thereby triggering an intelligent voice soothing mechanism and selecting intelligent voice content according to the patient's individual differences. The specific analysis is as follows: the patient's real-time sensitivity and tension value is obtained based on the patient's physiological indicators and language content; the patient's real-time sensitivity and tension value is compared with the patient's sensitivity and tension threshold; when the patient's real-time sensitivity and tension value exceeds the patient's sensitivity and tension threshold, the intelligent voice soothing mechanism is triggered; the intelligent voice library is searched based on the patient's individual difference information to identify the patient's intelligent voice content, wherein the intelligent voice content includes personalized voice style and personalized soothing content.

[0010] Furthermore, the specific analysis of obtaining the patient's real-time sensitivity and tension value based on the patient's physiological indicators and language content is: obtaining the patient's physiological indicators, the patient's physiological indicators specifically include the patient's heart rate, the patient's respiratory rate and the patient's skin electrical response; monitoring the patient's language, and then converting the patient's language into text, capturing the patient's language content in real time; performing emotion recognition on the converted language content to obtain the patient's language characteristics, the patient's language characteristics include language emotion, speaking speed and language confusion; generating a patient physiological assessment index based on the patient's physiological indicators, and generating a patient language assessment index based on the patient's language characteristics; combining the patient's physiological assessment index and the patient's language assessment index to obtain the patient's real-time sensitivity and tension value.

[0011] Furthermore, the method of triggering the intelligent pain relief control mechanism based on the patient's physiological indicators and pain threshold is specifically as follows: obtaining the patient's physiological assessment index based on the patient's physiological indicators, comparing the patient's physiological assessment index with the pain threshold, and when the patient's physiological assessment index exceeds the pain threshold, triggering the intelligent pain relief control mechanism.

[0012] Furthermore, the specific analysis of the real-time monitoring of the patient's physiological indicators, real-time adjustment and optimization of the control parameters of the intelligent pain relief control mechanism is as follows: obtaining the target physiological indicator, and then taking the difference between the target physiological indicator and the patient's physiological evaluation index as a pain regulation deviation value; obtaining historical pain relief records based on the authorization of each historical puncture patient, and the historical pain relief records include each historical puncture patient's physiological evaluation index and the corresponding control parameters; obtaining the target physiological indicator, and then taking the difference between the target physiological indicator and the physiological evaluation index of each historical puncture patient as a pain regulation deviation value for each historical puncture patient; identifying the relationship model between the pain regulation deviation value and each control parameter based on the pain regulation deviation value of each historical puncture patient and the corresponding control parameters; obtaining the patient's physiological evaluation index in real time, taking the target physiological indicator and the patient's physiological evaluation index as the patient's pain regulation deviation value, and then identifying the control parameters based on the relationship model between the pain regulation deviation value and each control parameter.

[0013] An intelligent relief control management system based on puncture pain, using the above-mentioned intelligent relief control management method based on puncture pain, includes: a data acquisition module, used to obtain the patient's individual difference information based on the patient's authorization, and determine the patient's specific puncture position; a threshold setting module, used to set the patient's pain threshold and sensitivity tension threshold based on the patient's individual difference information and the specific puncture position; a voice soothing module, used to monitor the patient's physiological indicators in real time, and capture the patient's language content, use the patient's sensitivity tension threshold to analyze the patient's physiological indicators and language content, determine whether the patient is overly nervous, and then trigger the intelligent voice soothing mechanism, and select intelligent voice content according to the patient's individual differences; an intelligent pain relief control module, used to trigger the intelligent pain relief control mechanism according to the patient's physiological indicators and pain thresholds, the intelligent pain relief control mechanism includes automatic contraction of the watch ring, vibration of the watch ring and cooling; an optimization and adjustment module, used to adjust and optimize the control parameters of the intelligent pain relief control mechanism in real time based on the real-time monitoring of the patient's physiological indicators, and record the control parameters, the control parameters include the contraction strength of the watch ring, the vibration intensity and the cooling intensity.

[0014] The present invention has the following beneficial effects:

[0015] The intelligent relief control management method and system based on puncture pain can formulate tailored relief measures for each patient according to the individual difference information of the patient. Different patients have different perceptions, tolerance and tension reactions to pain. Therefore, personalized settings can improve the relief effect and reduce the discomfort of patients. By real-time monitoring of the patient's physiological indicators and language content, the treatment strategy can be dynamically adjusted. The monitoring of physiological indicators and language content can provide real-time data for the system and make timely adjustments according to the patient's state changes. The patient's sensitivity and tension threshold is used to analyze its language content and physiological data to determine whether there is excessive tension, thereby triggering an intelligent voice soothing mechanism, which can soothe the patient through intelligent voice content, relieve his emotional tension and reduce anxiety. Through technical means such as automatic contraction of the watch ring, vibration of the watch ring and cooling, the patient's pain can be relieved from multiple aspects, which can be triggered according to the patient's pain threshold and personalized adjustments can be made. The diversified relief methods can avoid the side effects that may be caused by traditional drug interventions, and according to the real-time monitoring of the patient's physiological indicators, the control parameters of the intelligent pain relief control mechanism can be adjusted and optimized in real time to improve the treatment effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of an intelligent relief control management method based on puncture pain.

[0017] Figure 2This is a structural diagram of an intelligent relief control management system based on puncture pain according to the present invention. DETAILED DESCRIPTION

[0018] The embodiment of the present application realizes intelligent and personalized pain management and soothing through an intelligent relief control management method and system based on puncture pain, which significantly improves the comfort and satisfaction of patients.

[0019] The overall idea of ​​the embodiment of the present application is: through precise physiological data collection and analysis, combined with intelligent feedback mechanism (voice soothing, pain relief device), customized intervention is carried out according to the specific needs of the patient, so as to relieve pain and tension during the puncture process and provide a more comfortable and effective medical experience.

[0020] See also Figure 1 The embodiment of the present invention provides a technical solution: an intelligent relief control management method based on puncture pain, comprising the following steps: obtaining the patient's individual difference information based on the patient's authorization, and determining the patient's specific puncture position; setting the patient's pain threshold and sensitivity tension threshold based on the patient's individual difference information and the specific puncture position; real-time monitoring of the patient's physiological indicators, and capturing the patient's language content, using the patient's sensitivity tension threshold to analyze the patient's physiological indicators and language content, to determine whether the patient is overly nervous, and then triggering an intelligent voice soothing mechanism, and selecting intelligent voice content according to the patient's individual differences; triggering an intelligent pain relief control mechanism based on the patient's physiological indicators and pain thresholds, the intelligent pain relief control mechanism including automatic contraction of the watch ring, vibration of the watch ring and cooling; based on real-time monitoring of the patient's physiological indicators, real-time adjustment and optimization of the control parameters of the intelligent pain relief control mechanism, and recording the control parameters, the control parameters including the contraction strength of the watch ring, vibration intensity and cooling intensity.

[0021] Specifically, the specific analysis of setting the patient's pain threshold and sensitivity-stress threshold based on the patient's individual difference information and specific puncture position is as follows: based on the authorization of each historical puncture patient, the historical puncture record information is obtained, and the historical puncture record information includes the pain threshold, sensitivity-stress threshold and the individual difference information and specific puncture position of each historical puncture patient; the individual difference information and specific puncture position of each historical puncture patient are quantified, and then the individual difference information, specific puncture position and the pain threshold, sensitivity-stress threshold are analyzed respectively by multivariate regression to identify the relationship between the individual difference information, the specific puncture position and the pain threshold, as well as the relationship between the individual difference information, the specific puncture position and the sensitivity-stress threshold; the individual difference information and specific puncture position of the patient are simulated using the relationship between the individual difference information, the specific puncture position and the pain threshold to obtain the patient's pain threshold; the individual difference information and specific puncture position of the patient are simulated using the relationship between the individual difference information, the specific puncture position and the sensitivity-stress threshold to obtain the patient's sensitivity-stress threshold.

[0022] In this implementation scheme, individual difference information includes patient age, patient gender, patient body fat percentage, patient past medical history and patient pain sensitivity history, which is obtained through the patient's health record or detailed inquiries during the consultation; specific puncture locations include bone marrow puncture, thoracic puncture, abdominal puncture, lumbar puncture and punctures at other sites, which are usually determined by the actual location of the clinical operation or imaging examination.

[0023] The pain threshold indicates the maximum pain intensity that the patient can bear. If the intensity exceeds this, the patient begins to feel obvious discomfort; the sensitivity tension threshold indicates the patient's tolerance to the psychological or physiological tension reaction during the puncture process.

[0024] The specific multiple regression analysis models are:

[0025] Pain threshold prediction model:

[0026] P=β0+β1*Age+β2*Gen+β3*BF+β4*PPH+β5*DH+β6*Loc+ε, where P represents the patient's pain threshold, β0 is the intercept term, which represents the expected value of the pain threshold when all independent variables are zero, represents the starting point or benchmark value of the pain threshold, and is estimated by fitting the data using the least squares method (OLS) to minimize the sum of squared errors between the model predicted value and the actual observed value. β1, β2, β3, β4, β5, and β6 represent regression coefficients, which are estimated by estimating the historical puncture record information using the least squares method and are used to describe the impact of different factors on the pain threshold. ε represents the error term, which is obtained by observing the historical puncture record information using the least squares method and identifying the difference between the actual observed value and the predicted value, which is the part that the pain threshold prediction model cannot fully explain. Age represents the patient's age, Gen represents the patient's gender, BF represents the patient's body fat percentage, PPH represents the patient's medical history, DH represents the patient's pain sensitivity history, and Loc represents the puncture location.

[0027] Sensitivity stress threshold prediction model:

[0028] T=α0+α1*Age+α2*Gen+α3*BF+α4*PPH+α5*DH+α6*Loc+χ, where T represents the patient's sensitivity-tension threshold, α0 is the intercept term, which represents the expected value of the sensitivity-tension threshold when all independent variables are zero, represents the starting point or benchmark value of the sensitivity-tension threshold, and is estimated by fitting the data using the least squares method (OLS) to minimize the sum of squared errors between the model predicted values ​​and the actual observed values. α1, α2, α3, α4, α5, and α6 represent regression coefficients, which are estimated by using the least squares method to estimate historical puncture record information and are used to describe the impact of different factors on the sensitivity-tension threshold. χ represents the error term, which is obtained by observing historical puncture record information using the least squares method to identify the difference between the actual observed values ​​and the predicted values, which is the part that the sensitivity-tension threshold prediction model cannot fully explain.

[0029] Specific examples of quantification of each parameter are as follows: for the patient's age, age is quantified as a continuous variable, or it is divided into several groups (such as young, middle-aged, and elderly) to analyze the impact of different age groups on pain; for the patient's gender, generally speaking, women may be more sensitive to pain in some cases, which can be quantified through gender coding (such as 1=female, 0=male); for the patient's body fat percentage, it can be quantified through the numerical value of the body fat percentage, for example, the body fat percentage is used as a continuous variable to analyze its impact on the pain threshold; for the patient's medical history, it can be quantified by creating a binary variable (medical history=1, no medical history=0), and the impact of different medical histories on pain can be considered; for the patient's pain sensitivity history, it can be determined through a self-assessment questionnaire or a doctor's diagnosis, and quantified into a binary variable (such as a history of pain sensitivity=1, no history of pain sensitivity=0); for the quantification of specific puncture locations, different puncture locations can be regarded as categorical variables, and each location is assigned a unique code, for example: bone marrow puncture is 1, thoracotomy is 2

[0030] , abdominal puncture is 3, lumbar puncture is 4, and other puncture locations are 5; for pain threshold, a pain rating scale (such as visual analog scale VAS) can be used for measurement and quantified into a numerical value, for example, 0 means no pain and 10 means the most severe pain; for sensitivity tension threshold, a standardized anxiety scale (such as STAI, Hamilton Anxiety Scale, etc.) can be used to quantify the patient's tension sensitivity, for example, an anxiety score of 0 means no anxiety and 10 means extreme anxiety.

[0031] Through the analysis of individual differences of patients and specific puncture locations, the pain threshold and sensitivity tension threshold of each patient can be predicted more accurately, so that more personalized anesthesia or analgesia measures can be taken during puncture to improve treatment comfort; different puncture sites and individual differences of patients will affect the perception of pain and tension. After quantitative analysis, targeted training or adjustment of techniques can be carried out for different sites and individuals, thereby alleviating patient pain and reducing the risk of complications; through the collection of historical data and multivariate regression analysis, a specific relationship model of pain and tension thresholds can be derived, avoiding subjective judgment based on experience and improving the scientificity and accuracy of clinical decision-making.

[0032] Specifically, the patient's sensitivity and tension threshold is used to analyze the patient's physiological indicators and language content to determine whether the patient is overly nervous, thereby triggering the intelligent voice soothing mechanism and selecting the intelligent voice content according to the patient's individual differences. The specific analysis is as follows: the patient's real-time sensitivity and tension value is obtained based on the patient's physiological indicators and language content; the patient's real-time sensitivity and tension value is compared with the patient's sensitivity and tension threshold. When the patient's real-time sensitivity and tension value exceeds the patient's sensitivity and tension threshold, the intelligent voice soothing mechanism is triggered; the intelligent voice library is searched based on the patient's individual difference information to identify the patient's intelligent voice content, which includes personalized voice style and personalized soothing content.

[0033] In this implementation scheme, the specific analysis of obtaining the patient's real-time sensitivity and tension value based on the patient's physiological indicators and language content is as follows: obtaining the patient's physiological indicators, which specifically include the patient's heart rate, the patient's respiratory rate, and the patient's skin electrical response; monitoring the patient's language, and then converting the patient's language into text, capturing the patient's language content in real time; performing emotion recognition on the converted language content to obtain the patient's language characteristics, which include language emotion, speech speed, and language confusion; generating a patient physiological assessment index based on the patient's physiological indicators, and generating a patient language assessment index based on the patient's language characteristics; combining the patient's physiological assessment index and the patient's language assessment index to obtain the patient's real-time sensitivity and tension value, and an example of obtaining the patient's real-time sensitivity and tension value is as follows: Where RSSV represents the real-time sensitivity strain value, PAI represents the physiological assessment index, and LAI represents the language assessment index.

[0034] The patient's heart rate is obtained in real time through heart rate monitoring equipment (such as electrocardiogram, wearable heart rate monitor, etc.). A sharp increase in heart rate usually means that the patient may be in an emotional state such as tension or anxiety. The respiratory rate is obtained in real time through heart rate monitoring equipment (such as electrocardiogram, wearable heart rate monitor, etc.). The respiratory rate is obtained in real time through heart rate monitoring equipment (such as electrocardiogram, wearable heart rate monitor, etc.). The respiratory rate is obtained in real time through heart rate monitoring equipment (such as electrocardiogram, wearable heart rate monitor, etc.). The galvanic skin response is obtained in real time through galvanic skin response sensor (GSR sensor).

[0035] The patient's language content is converted into text by using speech recognition technology to convert the patient's language in real time, based on an automatic speech recognition system with deep learning; emotion recognition uses a sentiment analysis model (such as a sentiment classification algorithm based on natural language processing) to perform sentiment analysis on the converted text to determine the patient's emotional state (such as anxiety, anger, confusion, peace of mind, etc.); speaking speed is obtained by analyzing the speaking speed (number of words per minute) in the patient's language. Speaking too fast or too slow may reflect a state of tension or anxiety; language confusion is identified by analyzing the degree of confusion in the patient's language through grammatical analysis, semantic understanding and other technologies. If the sentences are incoherent and the expressions are vague, it means that the patient is in a state of anxiety or tension.

[0036] An example of an expression for obtaining a physiological assessment index is: PAI = η1*HR + η2*RR + η3*GSR, and an example of an expression for obtaining a language assessment index is: LAI = μ1*ER + μ2*SR + μ3*LD; wherein PAI represents a physiological assessment index, HR represents a patient's heart rate, RR represents a patient's respiratory rate, GSR represents a patient's skin galvanic response, η1, η2, and η3 represent weight coefficients of a patient's heart rate, a patient's respiratory rate, and a patient's skin galvanic response, respectively. The relative importance of different physiological indicators is determined by expert evaluation and can also be set by regression analysis or principal component analysis (PCA). ) and other statistical methods are used to analyze the relationship between different physiological indicators and the patient's tension state, and to determine the weight coefficient of each indicator. LAI represents the language assessment index, ER represents language emotion, SR represents speaking rate, LD represents language confusion, μ1, μ2, and μ3 represent the weight coefficients of language emotion, speaking rate, and language confusion, respectively. A large-scale sentiment data set is used to train the sentiment analysis model, and the weight coefficient of the sentiment score is optimized through the training process. The impact of emotion, speaking rate, and language confusion on the tension value can also be analyzed, and a regression model can be used to calculate the contribution of each feature to the final tension value and determine the weight.

[0037] The specific parameters are quantified as follows: For heart rate: heart rate is generally expressed in heart beats per minute; for respiratory rate: respiratory rate is usually expressed in breaths per minute; for galvanic skin response: galvanic skin response reflects the patient's emotional fluctuations by measuring changes in skin conductance, which are collected by sensors and converted into relative conductance values. Large changes indicate more intense emotional fluctuations; for language emotion: the patient's language is analyzed through an emotion analysis model (such as an emotion classification model based on deep learning) to identify the emotional tendencies in the language (such as happiness, sadness, anger, anxiety, etc.). The emotion recognition model converts the language into The content of speech is converted into a sentiment score, for example, a sentiment intensity score is obtained through sentiment analysis, usually between -1 (negative sentiment) and +1 (positive sentiment), for example, negative sentiment may be scored as -0.7, and positive sentiment as +0.5; for speaking rate: calculated by the number of words per minute; for language confusion: quantified by identifying filler words (such as "um", "ah") and pauses in the speech, and the confusion is calculated specifically according to the proportion of incoherent or unclear parts in the language, expressed by a "fluency score" (for example, a score from 1 to 5, 1 means very fluent, 5 means very confusing).

[0038] The specific logical steps for searching the intelligent voice library based on the individual difference information of the patient are as follows: collect the individual difference information of the patient, and select the voice style and content that best suits the patient based on the individual difference information of the patient. For example, if the patient responds better to a gentle and soft voice style, the system will give priority to voice content of this style. At the same time, the voice content will also be adjusted according to the patient's specific needs (such as relieving anxiety, providing comfort, etc.). For example, if the patient shows obvious anxiety, the system may select voice that contains relaxation techniques, deep breathing, etc. When the system detects that the patient's real-time sensitivity and tension value exceeds the patient's sensitivity and tension threshold, the system will automatically select and play appropriate intelligent voice soothing content to help the patient relieve emotions and restore calmness.

[0039] By combining physiological indicators with language content, it is possible to obtain the patient's emotional changes in real time and promptly discover whether the patient is in a state of excessive tension or anxiety. Once the patient is found to have exceeded the individual sensitivity tension threshold, the system can immediately trigger the intelligent voice soothing mechanism to avoid emotional out-of-control; each patient has different sensitivity thresholds and emotional responses, and the appropriate intelligent voice content is selected through personalized difference information, making voice soothing more targeted and effective; compared with traditional treatment methods, using technical means to evaluate the patient's tension in real time and provide timely psychological comfort can help relieve the patient's anxiety and stress, reduce the patient's physical and psychological burden, and thus improve the treatment effect.

[0040] Specifically, the intelligent pain relief control mechanism is triggered according to the patient's physiological indicators and pain thresholds as follows: the patient's physiological assessment index is obtained according to the patient's physiological indicators, the patient's physiological assessment index is compared with the pain threshold, and when the patient's physiological assessment index exceeds the pain threshold, the intelligent pain relief control mechanism is triggered.

[0041] In this embodiment, a pain relief plan can be tailored for each patient by obtaining an individual physiological assessment index based on the patient's physiological indicators and combining it with their specific pain threshold; the aggravation of pain is automatically identified based on changes in physiological indicators, and pain relief measures are immediately initiated when the patient's physiological assessment index exceeds the set pain threshold. The automated response can be faster and more accurate than traditional manual intervention, ensuring that the patient no longer experiences excessive pain; through intelligent monitoring and active intervention in pain management, the patient's waiting time and discomfort during pain attacks can be greatly reduced, thereby enhancing the patient's comfort; the intelligent pain relief mechanism can automatically determine when intervention is needed, and start in time through a preset treatment plan, which can avoid excessive use of drugs or other treatments, and at the same time avoid wasting medical resources due to ignoring increased pain; through real-time physiological monitoring, the system can predict the trend of worsening pain and take measures to intervene in advance to reduce the risk of increased pain or related complications in patients.

[0042] Specifically, the real-time monitoring of the patient's physiological indicators, and the specific analysis of the real-time adjustment and optimization of the control parameters of the intelligent pain relief control mechanism are as follows: obtaining the target physiological indicator, and then taking the difference between the target physiological indicator and the patient's physiological evaluation index as the pain regulation deviation value; obtaining the historical pain relief records based on the authorization of each historical puncture patient, and the historical pain relief records include the physiological evaluation index of each historical puncture patient and the corresponding control parameters; obtaining the target physiological indicator, and then taking the difference between the target physiological indicator and the physiological evaluation index of each historical puncture patient as the pain regulation deviation value of each historical puncture patient; identifying the relationship model between the pain regulation deviation value and each control parameter based on the pain regulation deviation value of each historical puncture patient and the corresponding control parameters; obtaining the patient's physiological evaluation index in real time, taking the target physiological indicator and the patient's physiological evaluation index as the patient's pain regulation deviation value, and then identifying the control parameters based on the relationship model between the pain regulation deviation value and each control parameter.

[0043] In this implementation scheme, the target physiological index is an ideal physiological parameter value, which represents the ideal physiological state of the patient during the puncture process, and represents the ideal physiological response of the patient after pain relief. The patient's physiological data is obtained through real-time monitoring equipment or sensors, and the target value is set according to the treatment plan; the pain regulation deviation value is the difference between the target physiological index and the patient's physiological assessment index, which reflects the patient's current pain level or the degree of deviation of the physiological state. The closer it is to 0, the better the pain relief effect; the historical pain relief record includes the historical patient's physiological assessment index and the corresponding control parameter data, which are used to analyze and model the laws of pain relief. The detailed data of each treatment of the patient, including the control parameters during treatment (watch ring contraction force, vibration intensity, cooling intensity, etc.) and the corresponding physiological assessment index, are expressed in the form of a data table. Each record includes a timestamp, control parameters, and specific values ​​of the physiological assessment index.

[0044] The contraction strength of the ring in the control parameters indicates the contraction strength of the pain relief device (such as electrical stimulation or mechanical device), the vibration intensity is the vibration intensity used for physical stimulation, and the cooling intensity indicates the intensity of cold compress or cooling used in the pain relief process. The control parameters are set and adjusted in real time through the device control system, input by the treatment operator or automatically adjusted. The contraction strength can be expressed in units of force (such as Newton), and the vibration intensity and cooling intensity can be quantified by frequency and temperature difference, etc.

[0045] An example of a specific expression of the relationship model between the pain regulation deviation value and the control parameter is: DIPR = ι0 + ι1*CF + ι2*VI + ι3*CP, where DIPR represents the pain regulation deviation value, ι0, ι1, ι2, ι3 represent the model coefficients obtained through historical data training, which are obtained by minimizing the sum of squared errors, CF represents the contraction strength of the ring, VI represents the vibration intensity, and CP represents the cooling intensity. The specific relationship model goal is to adjust the control parameters according to the pain regulation deviation value to reduce the deviation value, thereby achieving the best pain relief effect. More complex machine learning models (such as random forests, neural networks, etc.) are also used to optimize the control parameters in real time by learning the relationship between the deviation value and the control parameters in the historical data.

[0046] By adjusting the control parameters in real time according to each patient's specific physiological data and historical responses (such as pain relief records), we ensure that the pain relief measures are most suitable for the patient's needs; by monitoring the patient's physiological state in real time and automatically adjusting the control parameters (such as the contraction force of the watch ring, vibration intensity, and cooling intensity), we can improve the timeliness and accuracy of pain relief; by using objective physiological indicators and historical data models, we can reduce human errors in clinical operations and ensure that the treatment is more scientific and accurate; by collecting more historical data, we can gradually optimize the relationship model between the pain regulation deviation value and the control parameters, so as to continuously improve the treatment effect, avoid excessive or insufficient treatment, and enable patients to obtain the best pain relief effect in the shortest time and shorten recovery time.

[0047] See also Figure 2 , an intelligent relief control management system based on puncture pain, using the above-mentioned intelligent relief control management method based on puncture pain, including: a data acquisition module, used to obtain the patient's individual difference information based on the patient's authorization, and determine the patient's specific puncture position; a threshold setting module, used to set the patient's pain threshold and sensitivity tension threshold based on the patient's individual difference information and the specific puncture position; a voice soothing module, used to monitor the patient's physiological indicators in real time, and capture the patient's language content, use the patient's sensitivity tension threshold to analyze the patient's physiological indicators and language content, determine whether the patient is overly nervous, and then trigger the intelligent voice soothing mechanism, and select the intelligent voice content according to the patient's individual differences; an intelligent pain relief control module, used to trigger the intelligent pain relief control mechanism according to the patient's physiological indicators and pain thresholds, and the intelligent pain relief control mechanism includes automatic contraction of the watch ring, vibration of the watch ring and cooling; an optimization and adjustment module, used to adjust and optimize the control parameters of the intelligent pain relief control mechanism in real time based on the real-time monitoring of the patient's physiological indicators, and record the control parameters, and the control parameters include the contraction strength of the watch ring, the vibration intensity and the cooling intensity.

[0048] In summary, this application has at least the following effects:

[0049] By obtaining the individual difference information of the patient and the specific puncture location, it is possible to set personalized pain thresholds and sensitivity tension thresholds, which can be optimized for each patient's unique situation, thereby improving the treatment effect and the patient's comfort; real-time monitoring of the patient's physiological indicators and language content can timely detect the patient's nervous emotions and pain reactions, which helps to take quick measures, such as triggering the intelligent voice soothing mechanism or the intelligent pain relief control mechanism to relieve the patient's pain and anxiety; the intelligent voice soothing mechanism can select appropriate voice content according to the individual differences of the patient for personalized soothing. At the same time, the intelligent pain relief control mechanism, such as automatic contraction, vibration and cooling of the watch ring, can provide multiple ways of pain relief, further enhancing the patient's comfort and satisfaction; based on the real-time monitoring of the patient's physiological indicators, the control parameters of the intelligent pain relief control mechanism, such as the contraction strength of the watch ring, the vibration intensity and the cooling intensity, can be adjusted and optimized in real time. The dynamic adjustment can ensure that the pain management plan always matches the patient's actual situation, thereby improving the effectiveness and safety of the treatment; the recording of control parameters is helpful for subsequent analysis and optimization of the pain management plan, thereby providing more accurate guidance for future pain management.

[0050] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods and systems. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0051] The present invention is described with reference to the flowcharts and structure diagrams of the methods and systems according to the embodiments of the present invention. It should be understood that each process and combination of modules in the flowcharts and structure diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts. Figure 1 process or processes and structures Figure 1 A device that specifies functionality in a module or modules.

[0052] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 process or processes and structures Figure 1 A function specified in a module or multiple modules.

[0053] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 process or processes and structures Figure 1 Steps to specify functionality in a module or multiple modules.

[0054] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0055] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent relief control management method based on puncture pain, characterized in that: The following steps are involved: Based on the patient's authorization, the patient's individual difference information is obtained and the patient's specific puncture location is determined; The patient's pain threshold and sensitivity threshold are set based on the patient's individual difference information and specific puncture location; Monitor the patient's physiological indicators in real time, capture the patient's language content, and use the patient's sensitivity and tension threshold to analyze the patient's physiological indicators and language content to determine whether the patient is overly nervous, thereby triggering the intelligent voice soothing mechanism and selecting intelligent voice content based on the patient's individual differences; triggering an intelligent pain relief control mechanism according to the patient's physiological indicators and pain threshold, wherein the intelligent pain relief control mechanism includes automatic contraction of the watch ring, vibration of the watch ring and cooling; Based on real-time monitoring of the patient's physiological indicators, the control parameters of the intelligent pain relief control mechanism are adjusted and optimized in real time, and the control parameters are recorded. The control parameters include the contraction strength of the watch ring, the vibration intensity, and the cooling intensity.

2. The intelligent pain relief control management method based on puncture pain according to claim 1 is characterized in that: The specific analysis of setting the patient's pain threshold and sensitivity threshold based on the patient's individual difference information and specific puncture position is as follows: Based on the authorization of each historical puncture patient, the historical puncture record information is obtained, wherein the historical puncture record information includes the pain threshold, sensitivity tension threshold, individual difference information and specific puncture position of each historical puncture patient; The individual difference information and specific puncture positions of each puncture patient in history were quantified, and then the individual difference information, specific puncture position and pain threshold, sensitivity and tension threshold were analyzed by multivariate regression to identify the relationship between individual difference information, specific puncture position and pain threshold, as well as the relationship between individual difference information, specific puncture position and sensitivity and tension threshold; The individual difference information and specific puncture position of the patient are simulated using the relationship between the individual difference information, the specific puncture position and the pain threshold to obtain the pain threshold of the patient; The individual difference information of the patient and the specific puncture position are simulated using the relationship between the individual difference information, the specific puncture position and the sensitivity tension threshold to obtain the sensitivity tension threshold of the patient.

3. The intelligent pain relief control management method based on puncture pain according to claim 2 is characterized in that: The individual difference information includes the patient's age, the patient's gender, the patient's body fat percentage, the patient's past medical history, and the patient's pain sensitivity history; The specific puncture locations include bone marrow puncture, thoracic puncture, abdominal puncture, lumbar puncture and punctures at other locations.

4. The intelligent pain relief control management method based on puncture pain according to claim 1 is characterized in that: The patient's sensitivity and tension threshold is used to analyze the patient's physiological indicators and language content to determine whether the patient is overly nervous, thereby triggering the intelligent voice soothing mechanism and selecting the intelligent voice content according to the individual differences of the patient. The specific analysis is as follows: Obtain the patient's real-time sensitivity and tension value based on the patient's physiological indicators and language content; The patient's real-time sensitivity and tension value is compared with the patient's sensitivity and tension threshold. When the patient's real-time sensitivity and tension value exceeds the patient's sensitivity and tension threshold, the intelligent voice soothing mechanism is triggered; The intelligent voice library is searched based on the patient's individual difference information to identify the patient's intelligent voice content, which includes personalized voice style and personalized soothing content.

5. The intelligent pain relief control management method based on puncture pain according to claim 4 is characterized in that: The specific analysis of obtaining the patient's real-time sensitivity and tension value based on the patient's physiological indicators and language content is as follows: Obtaining physiological indicators of the patient, wherein the physiological indicators of the patient specifically include the patient's heart rate, the patient's respiratory rate, and the patient's skin electrical response; Monitor the patient's language, convert it into text, and capture the patient's language content in real time; Performing emotion recognition on the converted language content to obtain the patient's language characteristics, wherein the patient's language characteristics include language emotion, speech speed, and language confusion; Generate a patient physiological assessment index based on the patient's physiological indicators, and generate a patient language assessment index based on the patient's language characteristics; The patient's real-time sensitivity tension value is obtained by combining the patient's physiological assessment index and the patient's language assessment index.

6. The intelligent pain relief control management method based on puncture pain according to claim 5 is characterized in that: The specific method of triggering the intelligent pain relief control mechanism based on the patient's physiological indicators and pain threshold is as follows: obtaining the patient's physiological assessment index based on the patient's physiological indicators, comparing the patient's physiological assessment index with the pain threshold, and triggering the intelligent pain relief control mechanism when the patient's physiological assessment index exceeds the pain threshold.

7. The intelligent pain relief control management method based on puncture pain according to claim 5 is characterized in that: The specific analysis of real-time monitoring of the patient's physiological indicators, real-time adjustment and optimization of the control parameters of the intelligent pain relief control mechanism is as follows: Obtaining a target physiological index, and then taking the difference between the target physiological index and the patient's physiological assessment index as a pain regulation deviation value; Obtaining historical pain relief records based on authorization from each historical puncture patient, wherein the historical pain relief records include physiological assessment indexes of each historical puncture patient and corresponding control parameters; Obtaining the target physiological index, and then taking the difference between the target physiological index and the physiological evaluation index of each historical puncture patient as the pain regulation deviation value of each historical puncture patient; According to the pain regulation deviation values ​​of each puncture patient and the corresponding control parameters, a relationship model between the pain regulation deviation values ​​and the control parameters at each time is identified; The patient's physiological assessment index is obtained in real time, and the target physiological index and the patient's physiological assessment index are marked as the patient's pain regulation deviation value, and then the control parameters are identified based on the relationship model between the pain regulation deviation value and each control parameter.

8. An intelligent pain relief control management system based on puncture pain, using an intelligent pain relief control management method based on puncture pain according to any one of claims 1 to 7, characterized in that: include: A data acquisition module is used to obtain individual difference information of patients based on their authorization and determine the specific puncture location of the patients; A threshold setting module, used to set the patient's pain threshold and sensitivity tension threshold based on the patient's individual difference information and specific puncture position; The voice soothing module is used to monitor the patient's physiological indicators in real time and capture the patient's language content. It uses the patient's sensitivity and tension threshold to analyze the patient's physiological indicators and language content, determine whether the patient is overly nervous, and then trigger the intelligent voice soothing mechanism, and select intelligent voice content according to the individual differences of the patient; An intelligent pain relief control module, used to trigger an intelligent pain relief control mechanism according to the patient's physiological indicators and pain threshold, wherein the intelligent pain relief control mechanism includes automatic contraction of the watch ring, vibration of the watch ring and cooling; The optimization and adjustment module is used to adjust and optimize the control parameters of the intelligent pain relief control mechanism in real time based on real-time monitoring of the patient's physiological indicators, and record the control parameters, wherein the control parameters include the contraction strength of the watch ring, the vibration intensity and the cooling intensity.

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