A data processing method for anaesthesia breath control

Abstract

The application relates to the technical field of anesthesia monitoring, and discloses a data processing method for anesthesia respiratory control, which comprises the following steps: obtaining respiratory data and individual data of a target patient, establishing a respiratory database, forming prediction data according to the respiratory database and the individual data of the target patient, forming judgment data according to the prediction data and the respiratory frequency of the target patient, forming adjustment data according to the judgment data, forming analysis data according to the respiratory data, and forming comparison conclusions according to the analysis data. The data processing method for anesthesia respiratory control can predict whether the patient will change from mechanical ventilation to autonomous respiration due to insufficient anesthesia depth during the operation process, adjust the collection frequency of the respiratory detection equipment on the patient's respiration during the operation process, judge whether the patient changes from mechanical ventilation to autonomous respiration, timely adjust the anesthesia depth of the patient, and actively judge whether the patient can leave the respiratory equipment after anesthesia recovery.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of anesthesia monitoring, in particular to a data processing method for anesthesia respiratory control. BACKGROUND

[0002] The anesthesia respiratory control method based on respiratory monitoring is to monitor the patient's respiratory condition in the anesthesia state by using modern technology to ensure the safety of the patient during surgery or other medical procedures, including sensor monitoring of respiratory signals, data acquisition and processing, alarm system, data recording and analysis, and real-time feedback and adjustment, etc., which can improve the safety of patients during anesthesia and reduce the incidence of respiratory-related complications, and can provide more timely and accurate medical intervention to improve the treatment effect of patients.

[0003] The sensor is placed near the patient's respiratory tract, and the data captured by the sensor is transmitted to the monitoring system, which can process the data in real time and analyze the respiratory pattern using algorithms, and can identify abnormal respiratory patterns. When the monitoring system detects an abnormal respiratory pattern, it will trigger an alarm to notify medical staff or doctors for intervention. The monitoring system can record the patient's respiratory data and store it in the database for subsequent analysis and evaluation, which can be used to improve the method of anesthesia management and provide more information about the patient's condition for doctors. Medical staff can obtain real-time feedback through the monitoring system to adjust the dose of anesthetic drugs or other treatment methods according to the patient's respiratory condition to ensure the patient's respiratory safety.

[0004] The existing data processing method for anesthesia respiratory control cannot predict whether the patient will change from mechanical ventilation to spontaneous breathing due to insufficient depth of anesthesia during the operation process according to the individual differences of the patient, so as to adjust the collection frequency of the respiratory detection device for the patient's breathing during the operation process, cannot judge whether the patient changes from mechanical ventilation to spontaneous breathing according to the change of the patient's respiratory frequency during the operation, so as to adjust the depth of anesthesia of the patient during the operation process, and cannot actively judge whether the patient has a tendency of spontaneous breathing after anesthesia recovery according to the patient's postoperative respiratory frequency and blood pressure data, so as to determine whether the respiratory equipment can be removed. The practicability has certain limitations. SUMMARY

[0005] The present application provides a data processing method for anesthesia respiratory control to promote the solution to the problems in the background art.

[0006] The present application provides the following technical scheme: a data processing method for anesthesia respiratory control, comprising:

[0007] Obtaining the respiratory data and individual data of the target patient;

[0008] The respiratory data includes respiratory rate, blood oxygen saturation, blood pressure and heart rate;

[0009] The individual data includes age, weight, health condition and operation type;

[0010] A respiratory database is established, in which the individual data and intraoperative and postoperative respiratory data of all patients are stored, for predicting whether the target patient will have spontaneous breathing due to individual difference caused by insufficient anesthesia depth during operation;

[0011] According to the respiratory database and the individual data of the target patient, prediction data are formed to predict whether the target patient will have spontaneous breathing due to individual difference caused by insufficient anesthesia depth during operation;

[0012] According to the prediction data and the respiratory rate of the target patient, determination data are formed by a data determination strategy to determine whether the target patient has spontaneous breathing due to insufficient anesthesia depth during operation;

[0013] According to the determination data, adjustment data are formed by a data adjustment strategy to timely adjust the anesthesia depth of the patient with spontaneous breathing during operation, so that the patient's breathing remains stable;

[0014] According to the respiratory data, analysis data are formed by a data analysis strategy to analyze the postoperative respiratory condition of the target patient, determine whether the target patient has spontaneous breathing consciousness after operation, and thus determine whether the mechanical ventilation can be removed and the patient can breathe spontaneously;

[0015] According to the analysis data, comparison conclusions are formed by a data comparison strategy to determine whether the mechanical ventilation can be removed and the patient can breathe spontaneously.

[0016] As an optional solution of the data processing method for anesthesia respiratory control, wherein:

[0017] The individual data, operation duration, spontaneous breathing rate and mechanical breathing rate of all patients are obtained and integrated into a first data set;

[0018] The first anesthesia depth and the second anesthesia depth of each patient during operation are obtained and integrated into a second data set;

[0019] The duration of the first anesthesia depth and the duration of the second anesthesia depth of each patient are extracted respectively and defined as the first duration and the second duration respectively, and integrated into a third data set;

[0020] The first data set, the second data set and the third data set are integrated to form the respiratory database.

[0021] As an optional solution of the data processing method for anesthesia respiratory control, wherein the forming prediction data, in particular:

[0022] Obtaining individual data of the target patient, referred to as target individual data;

[0023] Extracting all patients corresponding to the target individual data in the respiratory database, referred to as target analysis patients;

[0024] Extracting the initial anesthesia depth of each target analysis patient;

[0025] Calculating the target initial anesthesia depth, target initial anesthesia depth = sum of initial anesthesia depths of all target analysis patients ÷ number of target analysis patients;

[0026] Then the target initial anesthesia depth is the initial anesthesia depth of the target patient;

[0027] Extracting the initial duration corresponding to the target initial anesthesia depth, referred to as target initial duration;

[0028] Extracting the operation duration of each target analysis patient;

[0029] Calculating the target operation duration, target operation duration = sum of operation durations of all target analysis patients ÷ number of target analysis patients;

[0030] If the target initial duration is greater than or equal to the target operation duration, it is predicted that the target patient will be mechanically ventilated throughout the operation;

[0031] If the target initial duration is less than the target operation duration, it is predicted that the target patient will have spontaneous breathing during the operation.

[0032] As an optional solution of the data processing method for anesthesia respiratory control, wherein the data determination strategy, in particular:

[0033] Obtaining the mechanical respiratory frequency of each target analysis patient in each respiratory cycle;

[0034] Calculating the target mechanical respiratory frequency, target mechanical respiratory frequency = sum of mechanical respiratory frequencies of all target analysis patients ÷ number of target analysis patients;

[0035] Controlling the respiratory equipment to mechanically ventilate the target patient at the target mechanical respiratory frequency;

[0036] If it is predicted that the target patient will be mechanically ventilated throughout the operation, obtaining a monitoring frequency;

[0037] Real-time monitoring the respiratory frequency of the target patient in each respiratory cycle at the monitoring frequency, referred to as the first monitoring respiratory frequency;

[0038] If the first monitored respiratory frequency in each respiratory cycle = the target mechanical respiratory frequency in each respiratory cycle, it is determined that the patient's breathing is normal;

[0039] If the first monitored respiratory frequency in each respiratory cycle ≠ the target mechanical respiratory frequency in each respiratory cycle, it is determined that the patient's breathing is abnormal, and the autonomous breathing determination strategy is executed;

[0040] If it is predicted that the target patient will have autonomous breathing during the operation, the operation start time point is obtained;

[0041] The predicted autonomous breathing time point is calculated, and the predicted autonomous breathing time point = the operation start time point + [the target initial duration × (1-10%)];

[0042] The first monitoring period is formed with the operation start time point as the starting time point and the predicted autonomous breathing time point as the ending time point;

[0043] The period between the predicted autonomous breathing time point and the end of the operation is determined as the second monitoring period;

[0044] The respiratory frequency of the target patient in each respiratory cycle in the first monitoring period is monitored in real time at the monitoring frequency, which is determined as the second monitored respiratory frequency;

[0045] If the second monitored respiratory frequency in each respiratory cycle = the target mechanical respiratory frequency in each respiratory cycle, it is determined that the patient's breathing is normal;

[0046] If the second monitored respiratory frequency in each respiratory cycle ≠ the target mechanical respiratory frequency in each respiratory cycle, it is determined that the patient's breathing is abnormal, and the autonomous breathing determination strategy is executed;

[0047] The adjusted monitoring frequency is obtained;

[0048] The respiratory frequency of the target patient in each respiratory cycle in the second monitoring period is monitored in real time at the adjusted monitoring frequency, which is determined as the third monitored respiratory frequency;

[0049] If the third monitored respiratory frequency in each respiratory cycle = the target mechanical respiratory frequency in each respiratory cycle, it is determined that the patient's breathing is normal;

[0050] If the third monitored respiratory frequency in each respiratory cycle ≠ the target mechanical respiratory frequency in each respiratory cycle, it is determined that the patient's breathing is abnormal, and the autonomous breathing determination strategy is executed.

[0051] As an optional solution of the data processing method for anesthesia respiratory control, the autonomous breathing determination strategy specifically includes:

[0052] acquiring a monitoring respiratory frequency in each respiratory cycle, the monitoring respiratory frequency including a first monitoring respiratory frequency, a second monitoring respiratory frequency and a third monitoring respiratory frequency;

[0053] performing a respiratory cycle comparison step;

[0054] if it is determined that the target patient respiratory frequency tends to be consistent in the abnormality determination cycle, it is determined that the patient is switched from mechanical ventilation to spontaneous breathing, and a data adjustment strategy is performed;

[0055] if it is determined that the target patient respiratory frequency fluctuates in the abnormality determination cycle, it is determined that the patient's respiratory abnormality is caused by surgical operation, at which time the depth of anesthesia of the target patient is not adjusted, and the doctor is prompted that the patient's respiratory abnormality is caused by surgical operation.

[0056] As an optional solution of the data processing method for anesthesia respiratory control, the respiratory cycle comparison step is specifically:

[0057] S1, extracting a respiratory cycle in which the patient's respiratory abnormality is determined as a starting abnormality cycle;

[0058] acquiring a collection threshold value;

[0059] S2, taking the starting abnormality cycle as a starting cycle, acquiring a subsequent respiratory cycle, and taking the respiratory cycle as an abnormality determination cycle, the number of abnormality determination cycles being the collection threshold value;

[0060] the respiratory frequency collected in the abnormality determination cycle is determined as an abnormality determination respiratory frequency;

[0061] S3, if the number of respiratory cycles in which the abnormality determination respiratory frequency is consistent with the monitoring respiratory frequency data of the starting abnormality cycle in the abnormality determination cycle is greater than 80% of the collection threshold value, it is determined that the target patient respiratory frequency tends to be consistent in the abnormality determination cycle;

[0062] S4, if the number of respiratory cycles in which the abnormality determination respiratory frequency is consistent with the monitoring respiratory frequency data of the starting abnormality cycle in the abnormality determination cycle is less than or equal to 80% of the collection threshold value, it is determined that the target patient respiratory frequency fluctuates in the abnormality determination cycle.

[0063] As an optional solution of the data processing method for anesthesia respiratory control, the data adjustment strategy is specifically:

[0064] if it is determined that the patient is switched from mechanical ventilation to spontaneous breathing, acquiring a secondary depth of anesthesia of each target analysis patient;

[0065] calculating a target secondary depth of anesthesia, the target secondary depth of anesthesia being the sum of the secondary depths of anesthesia of all target analysis patients divided by the number of target analysis patients;

[0066] The target secondary anesthetic depth is the secondary anesthetic depth of the target patient.

[0067] The anesthetic depth of the target patient is adjusted to the secondary anesthetic depth.

[0068] As an optional solution of the data processing method for anesthetic respiratory control, the data analysis strategy is specifically:

[0069] The end time point of the surgery of the target patient is obtained as the anesthetic wake-up determination time point.

[0070] The preoperative spontaneous breathing frequency of the target patient at each breathing cycle is obtained as the preoperative breathing frequency.

[0071] The postoperative spontaneous breathing frequency of the target patient at each breathing cycle is collected in real time as the postoperative breathing frequency, with the anesthetic wake-up determination time point as the starting time point.

[0072] The preoperative breathing frequency at each breathing cycle = the postoperative breathing frequency at each breathing cycle is determined as the first determination result.

[0073] The blood oxygen saturation, blood pressure and heart rate of the target patient before the surgery are obtained and integrated as preoperative respiratory data.

[0074] The blood oxygen saturation, blood pressure and heart rate of the target patient after the surgery are collected in real time as postoperative respiratory data, with the anesthetic wake-up determination time point as the starting time point.

[0075] The preoperative respiratory data = the postoperative respiratory data is determined as the second determination result.

[0076] As an optional solution of the data processing method for anesthetic respiratory control, the data comparison strategy is specifically:

[0077] The first determination result and the second determination result are obtained.

[0078] If the first determination result and the second determination result are both satisfied, it indicates that the target patient can perform spontaneous breathing.

[0079] The respiratory equipment is controlled to be disconnected, so that the target patient performs spontaneous breathing.

[0080] If the first determination result or the second determination result is satisfied, it indicates that the target patient has a tendency of spontaneous breathing.

[0081] An artificial judgment diagnosis opinion is pushed to the doctor, and whether to remove the respiratory equipment is determined according to the artificial diagnosis conclusion of the doctor.

[0082] If neither the first determination result nor the second determination result is satisfied, it indicates that the target patient cannot perform spontaneous breathing.

[0083] The respiratory apparatus is then continued to be controlled to mechanically ventilate the target patient at the target mechanical ventilation frequency.

[0084] The present application has the following advantages:

[0085] 1. The data processing method for anesthesia respiratory control, by acquiring individual data of the target patient, extracting diagnosis and treatment data of the same type of patient in the respiratory database, and calculating the predicted initial anesthesia depth, initial duration and operation duration of the target patient, if the predicted initial duration is greater than the predicted operation duration, the prediction conclusion is that the target patient is always mechanically ventilated during the operation process, and the acquisition frequency of the respiratory detection device for the target patient's respiration is unchanged during the operation process, if the predicted initial duration is less than the predicted operation duration, the prediction conclusion is that the target patient may change to spontaneous respiration during the operation process, and the acquisition frequency of the respiratory detection device for the target patient's respiration is changed when the target patient may change to spontaneous respiration during the operation process, the respiratory change of the target patient during the operation process is determined in time, and the complications or sequelae caused by poor respiration of the patient during the operation process are prevented, and the situation that the patient has sequelae due to improper use of anesthetics is also prevented.

[0086] 2. The data processing method for anesthesia respiratory control, by monitoring the respiratory frequency of mechanical ventilation during the operation process, and judging whether the patient's respiration during the operation process is abnormal, since the mechanical ventilation is controlled by the respiratory equipment to drive the patient to exchange air, the respiratory frequency of the patient during the respiratory cycle is almost consistent during the mechanical ventilation, if the respiratory frequencies of the patient during two respiratory cycles before and after are inconsistent, it indicates that the patient's respiration is abnormal, at this time, a certain number of respiratory frequencies during the respiratory cycle are continuously collected, if the respiratory frequencies during the respiratory cycle collected backward tend to be consistent, it indicates that the patient changes from mechanical ventilation to spontaneous respiration during the operation process due to insufficient anesthesia depth, and the anesthesia depth of the patient is adjusted in time to make the patient return to mechanical ventilation, if only a small number of respiratory frequencies during the respiratory cycle are inconsistent with the respiratory frequency during the respiratory cycle of mechanical ventilation, it indicates that the abnormal respiration of the patient may be caused by some necessary operations during the operation process, and the situation that the patient has sequelae due to improper use of anesthetics caused by misjudgment is prevented.

[0087] 3. The data processing method for anesthesia respiratory control, by monitoring the patient's postoperative respiration, judging whether the patient's respiratory function gradually recovers after anesthesia recovery, if the patient does not appear spontaneous breathing, and the postoperative blood pressure, heart rate and blood oxygen saturation and other data are not consistent with the data before the operation, it is indicated that the respiratory function of the patient has not recovered, then continue to assist the patient to breathe through the respiratory equipment, if the patient appears spontaneous breathing, and the postoperative blood pressure, heart rate and blood oxygen saturation and other data are consistent with the data before the operation, it is indicated that the patient's respiratory function begins to recover, then automatically disconnect the respiratory equipment, if the patient appears spontaneous breathing, or the postoperative blood pressure, heart rate and blood oxygen saturation and other data are consistent with the data before the operation, the doctor needs to artificially diagnose whether the respiratory equipment can be removed, and the respiratory equipment is removed in time, to prevent the patient from depending on the respiratory equipment, and to reduce the occurrence of respiratory equipment related complications. BRIEF DESCRIPTION OF DRAWINGS

[0088] Figure 1 The flowchart of the data processing method for anesthesia respiratory control. DETAILED DESCRIPTION

[0089] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0090] Embodiment one, a data processing method for anesthesia respiratory control, referring to Figure 1 , comprising:

[0091] obtaining the respiratory data and individual data of the target patient;

[0092] The respiratory data includes respiratory rate, blood oxygen saturation, blood pressure and heart rate;

[0093] The individual data includes age, weight, health status and operation type;

[0094] establishing a respiratory database, the respiratory database stores individual data and intraoperative and postoperative respiratory data of all patients, to predict whether the target patient will appear spontaneous breathing due to individual differences during the operation because of insufficient depth of anesthesia;

[0095] According to the respiratory database and the individual data of the target patient, form prediction data to predict whether the target patient will appear spontaneous breathing due to individual differences during the operation because of insufficient depth of anesthesia;

[0096] According to the prediction data and the respiratory frequency of the target patient, the determination data is formed by the data determination strategy to determine whether the target patient has spontaneous breathing due to insufficient depth of anesthesia during the operation;

[0097] According to the determination data, the adjustment data is formed by the data adjustment strategy to timely adjust the depth of anesthesia for the patient with spontaneous breathing during the operation, so that the patient's breathing remains stable;

[0098] According to the respiratory data, the analysis data is formed by the data analysis strategy to analyze the postoperative breathing of the target patient, determine whether the target patient has spontaneous breathing after the operation, and determine whether the mechanical ventilation can be removed to allow the patient to breathe spontaneously;

[0099] According to the analysis data, the comparison conclusion is formed by the data comparison strategy to determine whether the mechanical ventilation can be removed to allow the patient to breathe spontaneously.

[0100] Through the above method, according to the individual differences of the patient, it is predicted whether the patient will change from mechanical ventilation to spontaneous breathing due to insufficient depth of anesthesia during the operation, so as to adjust the collection frequency of the patient's breathing by the respiratory detection equipment during the operation, and to judge whether the patient changes from mechanical ventilation to spontaneous breathing according to the change of the patient's respiratory frequency during the operation, so as to adjust the depth of anesthesia of the patient during the operation, prevent the patient from causing complications or sequelae due to poor breathing during the operation, prevent the patient from appearing sequelae due to improper use of anesthetic, and actively judge whether the patient has the tendency of spontaneous breathing after anesthesia according to the postoperative respiratory frequency and blood pressure of the patient., so as to determine whether the respiratory equipment can be removed, remove the respiratory equipment in time, prevent the patient from depending on the respiratory equipment, and reduce the occurrence of respiratory equipment related complications of the patient.

[0101] Embodiment two, this embodiment is an improvement based on embodiment one, the data processing method for anesthesia and respiratory control, the respiratory database is established, specifically:

[0102] Obtain individual data, operation time, spontaneous breathing frequency and mechanical breathing frequency of all patients, and integrate them into a first data set;

[0103] Obtaining the first anesthesia depth and the second anesthesia depth of each patient in the operation, integrating into a second data set, the first anesthesia depth is the anesthesia depth formed by the first time of taking anesthetics by inhalation or other ways before or during the operation, and when the patient is gradually transferred from mechanical ventilation to spontaneous breathing due to insufficient first anesthesia depth, the anesthesia depth formed by increasing the anesthetic content again is the second anesthesia depth, if the patient has no spontaneous breathing during the operation, it means that the first anesthesia depth of the patient during the operation is sufficient to support to the end of the operation, and the anesthesia depth is not increased, so there is no data of the second anesthesia depth, at this time the second anesthesia depth is 0;

[0104] Respectively extracting the duration of the first anesthesia depth and the duration of the second anesthesia depth of each patient, respectively as the first duration and the second duration, integrating into a third data set, if the patient has no spontaneous breathing during the operation, it means that the first anesthesia depth of the patient during the operation is sufficient to support to the end of the operation, and the anesthesia depth is not increased, so there is no data of the second anesthesia depth, at this time the second anesthesia depth is 0, then the second duration is 0, and the first duration is the time length from the onset of anesthesia to the failure of anesthesia;

[0105] Integrating the first data set, the second data set and the third data set to form a respiratory database.

[0106] The embodiment also provides that the prediction data is formed, in particular:

[0107] Obtaining the individual data of the target patient, as target individual data;

[0108] Extracting all patients corresponding to the target individual data in the respiratory database, as target analysis patients;

[0109] Extracting the first anesthesia depth of each target analysis patient;

[0110] Calculating the target first anesthesia depth, target first anesthesia depth = sum of first anesthesia depths of all target analysis patients ÷ number of target analysis patients;

[0111] The target first anesthesia depth is the first anesthesia depth of the target patient;

[0112] Extracting the first duration corresponding to the target first anesthesia depth, as target first duration;

[0113] Extracting the operation time of each target analysis patient;

[0114] Calculating the target operation time, target operation time = sum of operation times of all target analysis patients ÷ number of target analysis patients;

[0115] If the target initial duration is greater than or equal to the target surgery duration, it is predicted that the target patient is always mechanically ventilated during the surgery.

[0116] If the target initial duration is less than the target surgery duration, it is predicted that the target patient will have spontaneous breathing during the surgery.

[0117] In embodiment three, the data determination strategy is specifically:

[0118] The mechanical breathing frequency of each target analysis patient in each breathing cycle is obtained, and the breathing cycle is a cycle formed by taking inspiration as the starting point and expiration as the ending point.

[0119] The target mechanical breathing frequency is calculated, and the target mechanical breathing frequency is the sum of the mechanical breathing frequencies of all target analysis patients divided by the number of target analysis patients.

[0120] The breathing device is controlled to mechanically ventilate the target patient at the target mechanical breathing frequency.

[0121] If it is predicted that the target patient is always mechanically ventilated during the surgery, the monitoring frequency is obtained, which is the frequency at which the breathing monitoring device collects the breathing data of the target patient. For example, if the monitoring frequency is 1 time / s, the breathing monitoring device collects the breathing data of the target patient every second.

[0122] The breathing frequency of the target patient in each breathing cycle is monitored in real time at the monitoring frequency, and is defined as the first monitoring breathing frequency.

[0123] If the first monitoring breathing frequency in each breathing cycle is equal to the target mechanical breathing frequency in each breathing cycle, it is determined that the patient's breathing is normal, i.e. each first monitoring breathing frequency of the target patient in each breathing cycle is compared with each target mechanical breathing frequency. If the numerical values of each first monitoring breathing frequency and each target mechanical breathing frequency are equal, it means that the patient is breathing with the aid of the breathing device and the breathing is normal.

[0124] If the first monitoring breathing frequency in each breathing cycle is not equal to the target mechanical breathing frequency in each breathing cycle, it is determined that the patient's breathing is abnormal, and the spontaneous breathing determination strategy is executed, i.e. all first monitoring breathing frequencies of the target patient in each breathing cycle are inconsistent with all target mechanical breathing frequencies in each breathing cycle. It means that the patient's breathing function is in opposition to the breathing device, so the first monitoring breathing frequency is different from the target mechanical breathing frequency data, and it is necessary to further determine whether the reason for the opposition is that the patient has spontaneous breathing due to insufficient depth of anesthesia or that the breathing frequency fluctuates due to some necessary operations during the surgery.

[0125] If it is predicted that the target patient will have spontaneous breathing during the operation, the operation start time point is obtained;

[0126] The predicted spontaneous breathing time point is calculated, and the predicted spontaneous breathing time point = operation start time point + [target initial duration × (1-10%)];

[0127] The first monitoring period is formed with the operation start time point as the starting time point and the predicted spontaneous breathing time point as the ending time point;

[0128] The period between the predicted spontaneous breathing time point and the end of the operation is defined as the second monitoring period;

[0129] The respiratory frequency of the target patient in each breathing cycle is monitored in real time in the first monitoring period at the monitoring frequency, which is defined as the second monitoring respiratory frequency;

[0130] If the second monitoring respiratory frequency in each breathing cycle = the target mechanical respiratory frequency in each breathing cycle, it is determined that the patient's breathing is normal, that is, each second monitoring respiratory frequency of the target patient in each breathing cycle is compared with each target mechanical respiratory frequency, and if the numerical values of each second monitoring respiratory frequency and each target mechanical respiratory frequency are equal, it is indicated that the patient is breathing with the aid of a breathing device and the breathing is normal;

[0131] If the second monitoring respiratory frequency in each breathing cycle ≠ the target mechanical respiratory frequency in each breathing cycle, it is determined that the patient's breathing is abnormal, and the spontaneous breathing judgment strategy is executed, that is, all second monitoring respiratory frequencies of the target patient in each breathing cycle are inconsistent with all target mechanical respiratory frequencies in each breathing cycle, which indicates that the patient's respiratory function is in opposition to the breathing device, and therefore the first monitoring respiratory frequency different from the target mechanical respiratory frequency data appears, and it is necessary to further determine whether the reason for the opposition is that the patient has spontaneous breathing due to insufficient depth of anesthesia or that the respiratory frequency fluctuates due to the influence of some necessary operations during the operation;

[0132] The adjustment monitoring frequency is obtained, which is the frequency at which the breathing monitoring device densely collects the respiratory data of the target patient, such as 2 times / s, that is, the breathing monitoring device collects the respiratory data of the target patient twice per second, that is, the respiratory data of the target patient is collected every 0.5 seconds;

[0133] The respiratory frequency of the target patient in each breathing cycle is monitored in real time in the second monitoring period at the adjustment monitoring frequency, which is defined as the third monitoring respiratory frequency;

[0134] If the third monitoring respiratory frequency in each respiratory cycle = the target mechanical respiratory frequency in each respiratory cycle, it is determined that the patient's breathing is normal, that is, each third monitoring respiratory frequency of the target patient in each respiratory cycle is compared with each target mechanical respiratory frequency, and if the values of each third monitoring respiratory frequency and each target mechanical respiratory frequency are equal, it means that the patient is breathing with the aid of the breathing device and the breathing is normal;

[0135] If the third monitoring respiratory frequency in each respiratory cycle ≠ the target mechanical respiratory frequency in each respiratory cycle, it is determined that the patient's breathing is abnormal, and an autonomous breathing determination strategy is executed, that is, if all the third monitoring respiratory frequencies of the target patient in each respiratory cycle are inconsistent with all the target mechanical respiratory frequencies in each respiratory cycle, it means that the patient's respiratory function is in opposition to the breathing device, so the first monitoring respiratory frequency different from the target mechanical respiratory frequency data appears, and since the monitoring period is the period in which the patient may appear autonomous breathing, it is necessary to further determine whether the reason for the opposition is that the patient appears autonomous breathing due to insufficient depth of anesthesia or the respiratory frequency fluctuates due to the influence of some necessary operations in the surgical process.

[0136] The autonomous breathing determination strategy specifically includes:

[0137] The monitoring respiratory frequency in each respiratory cycle is obtained, including the first monitoring respiratory frequency, the second monitoring respiratory frequency, and the third monitoring respiratory frequency;

[0138] The respiratory cycle comparison step is executed;

[0139] If it is determined that the target patient's respiratory frequency in the abnormal determination period tends to be consistent, it is determined that the patient is switched from mechanical ventilation to autonomous breathing, and a data adjustment strategy is executed;

[0140] If it is determined that the target patient's respiratory frequency in the abnormal determination period fluctuates, it is determined that the patient's abnormal breathing is caused by surgical operation, at which time the depth of anesthesia of the target patient is not adjusted, and the doctor is prompted that the current patient's breathing is abnormal.

[0141] The respiratory cycle comparison step specifically includes:

[0142] S1, extract the respiratory cycle in which the patient's breathing is determined to be abnormal, and set it as the initial abnormal cycle;

[0143] The acquisition threshold is obtained, which is the number of respiratory cycles to be continuously acquired starting from the first abnormal respiratory cycle when the patient's breathing is abnormal, for example, if the acquisition threshold is 6, the respiratory frequency of 6 respiratory cycles is continuously acquired starting from the first abnormal respiratory cycle;

[0144] S2, taking the starting abnormal period as a starting period, acquiring a subsequent respiratory period, taking the respiratory period as an abnormal judgment period, and the number of abnormal judgment periods being a collection threshold, wherein the abnormal judgment period does not contain the starting abnormal period;

[0145] Taking the respiratory frequency collected in the abnormal judgment period as an abnormal judgment respiratory frequency;

[0146] S3, if the number of respiratory periods in which the abnormal judgment respiratory frequency is consistent with the monitoring respiratory frequency data of the starting abnormal period is greater than the collection threshold x 80%, it is determined that the target patient's respiratory frequency in the abnormal judgment period tends to be consistent;

[0147] S4, if the number of respiratory periods in which the abnormal judgment respiratory frequency is consistent with the monitoring respiratory frequency data of the starting abnormal period is less than or equal to the collection threshold x 80%, it is determined that the target patient's respiratory frequency in the abnormal judgment period fluctuates.

[0148] The embodiment also provides that the data adjustment strategy is specifically:

[0149] If it is determined that the patient is switched from mechanical ventilation to spontaneous breathing, the secondary anesthetic depth of each target analysis patient is acquired;

[0150] The target secondary anesthetic depth is calculated as the sum of the secondary anesthetic depths of all target analysis patients divided by the number of target analysis patients;

[0151] The target secondary anesthetic depth is the secondary anesthetic depth of the target patient;

[0152] The anesthetic depth of the target patient is adjusted to the secondary anesthetic depth.

[0153] Embodiment four, which is an improvement based on embodiment three, in the embodiment, the data analysis strategy is specifically:

[0154] The end of surgery time point of the target patient is acquired and taken as an anesthetic awakening judgment time point;

[0155] The preoperative spontaneous respiratory frequency of the target patient under each respiratory period is acquired and taken as a preoperative respiratory frequency;

[0156] Taking the anesthetic awakening judgment time point as a starting time point, the postoperative spontaneous respiratory frequency of the target patient under each respiratory period is acquired in real time and taken as a postoperative respiratory frequency;

[0157] Taking each respiratory period under the preoperative respiratory frequency = each respiratory period under the postoperative respiratory frequency as a first determination result, that is, all preoperative respiratory frequencies under each respiratory period of the target patient are consistent with all postoperative respiratory frequencies under each respiratory period, which indicates that the patient appears spontaneous breathing.

[0158] acquire preoperative blood oxygen saturation, blood pressure and heart rate of the target patient, and integrate the preoperative blood oxygen saturation, blood pressure and heart rate into preoperative respiratory data;

[0159] acquire postoperative blood oxygen saturation, blood pressure and heart rate of the target patient in real time, and integrate the postoperative blood oxygen saturation, blood pressure and heart rate into postoperative respiratory data, with the anesthesia wake-up determination time point as a starting time point;

[0160] set the preoperative respiratory data = postoperative respiratory data as a second determination result, that is, if each preoperative respiratory data of the target patient is consistent with each postoperative respiratory data, it indicates that the patient's respiratory function starts to recover.

[0161] The embodiment further provides that the data comparison strategy specifically includes:

[0162] acquire the first determination result and the second determination result;

[0163] if the first determination result and the second determination result are both satisfied, it indicates that the target patient can perform autonomous respiration;

[0164] then control the respiratory equipment to disconnect, so that the target patient performs autonomous respiration;

[0165] if the first determination result or the second determination result is satisfied, it indicates that the target patient has a tendency of autonomous respiration;

[0166] push an artificial judgment diagnosis opinion to a doctor, and determine whether to remove the respiratory equipment according to the artificial diagnosis conclusion of the doctor;

[0167] if neither the first determination result nor the second determination result is satisfied, it indicates that the target patient cannot perform autonomous respiration;

[0168] then continue to control the respiratory equipment, so that the target patient performs mechanical ventilation at a target mechanical respiration frequency. According to individual differences of the patient, the embodiment predicts whether the patient will change from mechanical ventilation to autonomous respiration due to insufficient anesthesia depth during the operation, so as to adjust the acquisition frequency of the respiratory detection equipment on the patient's respiration during the operation, judge whether the patient changes from mechanical ventilation to autonomous respiration according to the change of the patient's respiration frequency during the operation, and thus adjust the anesthesia depth of the patient during the operation, prevent the patient from causing complications or sequelae due to poor respiration during the operation, prevent the patient from causing sequelae due to improper use of anesthetics, actively judge whether the patient has a tendency of autonomous respiration after anesthesia wake-up according to the postoperative respiration frequency and blood pressure of the patient and other data, and thus determine whether the respiratory equipment can be removed, remove the respiratory equipment in time, prevent the patient from depending on the respiratory equipment, and reduce the situation that the patient causes complications related to the respiratory equipment.

Claims

1. A data processing method for anesthesia respiratory control, characterized in that, include: Acquire respiratory and individual data of the target patient; the respiratory data includes respiratory rate, blood oxygen saturation, blood pressure, and heart rate; the individual data includes age, weight, health status, and type of surgery; A respiratory database is established, which stores individual data of all patients and respiratory data during and after surgery; Based on the respiratory database and individual data of the target patient, predictive data is generated, which is used to characterize the risk of spontaneous breathing in the target patient during surgery due to insufficient depth of anesthesia; Based on the predicted data and the respiratory rate of the target patient, judgment data is generated through a data judgment strategy. The judgment data is used to characterize whether the target patient has switched from mechanical ventilation to spontaneous breathing during the operation. When the judgment data indicates that the target patient has switched from mechanical ventilation to spontaneous breathing, adjustment parameters for adjusting the depth of anesthesia are generated through a data adjustment strategy. Based on the respiratory data collected postoperatively, analytical data is generated through data analysis strategies. Based on the analyzed data, a comparative conclusion is generated using a data comparison strategy to assess whether mechanical ventilation can be discontinued. The data determination strategy is as follows: Calculate the target mechanical respiratory rate; Real-time monitoring of the respiratory rate of the target patient during each respiratory cycle is defined as monitoring respiratory rate. If the monitored respiratory rate in each respiratory cycle is not equal to the target mechanical respiratory rate in each respiratory cycle, then the patient's breathing is determined to be abnormal, and a spontaneous breathing determination strategy is executed to generate the determination data. The spontaneous breathing determination strategy is as follows: Acquire the monitored respiratory rate for each respiratory cycle; Perform the respiratory cycle comparison step; If the respiratory rate of the target patient tends to be consistent within the abnormality judgment period, the judgment data indicates that the patient has switched from mechanical ventilation to spontaneous breathing. If the respiratory rate of the target patient fluctuates within the abnormality determination period, the determination data indicates that the patient's respiratory abnormality is caused by the surgical procedure.

2. The data processing method according to claim 1, characterized in that: The establishment of the respiratory database specifically involves: Collect individual data, operation duration, spontaneous breathing rate, and mechanical breathing rate of all patients, and integrate them into the first dataset; The initial and secondary anesthesia depths of each patient during surgery were obtained and integrated into a second dataset; The duration of the initial anesthesia depth and the duration of the secondary anesthesia depth for each patient were extracted and designated as the initial duration and the secondary duration, respectively, and integrated into a third dataset; The first, second, and third datasets were integrated to form a respiratory database.

3. The data processing method according to claim 2, characterized in that: The formation of the prediction data specifically includes: Acquire individual data of the target patient and designate it as target individual data; Extract all patients corresponding to the target individual's data in the respiratory database and designate them as the target analysis patients; Extract the initial anesthesia depth for each target patient; Calculate the target initial anesthesia depth: Target initial anesthesia depth = Sum of initial anesthesia depths of all patients in the target analysis ÷ Number of patients in the target analysis; Extract the initial duration corresponding to the target initial anesthesia depth and define it as the target initial duration. Extract the operation time for each target patient; Calculate the target operation time: Target operation time = Sum of operation times for all patients in the target analysis ÷ Number of patients in the target analysis; If the target initial duration is greater than or equal to the target surgical duration, then the predicted data indicates that the target patient was mechanically ventilated throughout the operation. If the target initial duration is less than the target surgical duration, then the predicted data indicates that the target patient will exhibit spontaneous breathing during the surgery.

4. The data processing method according to claim 1, characterized in that: The step of performing respiratory cycle comparison is as follows: S1. Extract the respiratory cycle that indicates abnormal breathing in the patient and define it as the initial abnormal cycle; obtain the acquisition threshold. S2. Using the initial abnormal period as the starting period, obtain subsequent abnormal judgment periods. The number of abnormal judgment periods is the acquisition threshold. The respiratory rate acquired within the abnormal judgment period is defined as the abnormal judgment respiratory rate. S3. If the number of respiratory cycles in which the abnormal respiratory rate is consistent with the monitored respiratory rate data of the initial abnormal cycle is greater than the collection threshold × 80%, then the respiratory rate of the target patient in the abnormal judgment period is determined to be consistent. S4. If the number of respiratory cycles in which the abnormal respiratory rate is consistent with the monitored respiratory rate data of the initial abnormal cycle within the abnormal judgment period is ≤ 80% of the collection threshold, then it is determined that the respiratory rate of the target patient fluctuates within the abnormal judgment period.

5. The data processing method according to claim 1, characterized in that: The generation of adjustment parameters for adjusting the depth of anesthesia specifically includes: Obtain the depth of secondary anesthesia for each target patient; Calculate the target secondary anesthesia depth: Target secondary anesthesia depth = Sum of secondary anesthesia depths of all patients in the target analysis ÷ Number of patients in the target analysis; The adjustment parameter is the calculated target secondary anesthesia depth.

6. The data processing method according to claim 1, characterized in that: The data analysis strategy is as follows: The spontaneous respiratory rate of the target patient during each respiratory cycle before surgery is obtained and defined as the preoperative respiratory rate. Starting from the time point when anesthesia recovery is determined, the spontaneous respiratory rate of the target patient during each postoperative respiratory cycle is collected in real time and defined as the postoperative respiratory rate. The preoperative respiratory rate under each respiratory cycle is compared with the postoperative respiratory rate under each respiratory cycle to generate the first judgment result. Acquire the target patient’s preoperative blood oxygen saturation, blood pressure and heart rate, and integrate them into preoperative respiratory data; Starting from the time point for determining anesthesia recovery, the postoperative blood oxygen saturation, blood pressure, and heart rate of the target patients are collected in real time and integrated into postoperative respiratory data. Preoperative respiratory data is compared with postoperative respiratory data to generate a second judgment result.

7. The data processing method according to claim 6, characterized in that: The data comparison strategy is as follows: Obtain the first and second determination results; If both the first and second determination results are met, the comparison conclusion is to recommend disconnecting the breathing device. If the first or second determination result is met, the comparison conclusion is that manual judgment is recommended. If neither the first nor the second determination result is met, the comparison conclusion is that it is recommended to continue using a respiratory device for mechanical ventilation.

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