Remote monitoring system for nursing in psychiatry department

Abstract

The invention discloses a remote monitoring system for nursing in the psychiatry department, relates to the field of nursing, solves the problem of poor monitoring effect of the existing remote monitoring system for nursing in the psychiatry department, and comprises a physiological index module which is used for analyzing historical physiological indexes of a target patient, selecting a plurality of historical abnormal items according to an analysis result, and sending the historical abnormal items to a server; the emotional monitoring module is used for setting an emotional index monitoring period and a plurality of emotional indexes, monitoring the change condition of each emotional index of the target patient in the emotional index monitoring period to obtain emotional stability monitoring data, and sending the emotional stability monitoring data to the emotional monitoring module; and the monitoring and early warning module is used for performing remote early warning on the target patient according to the emotional stability monitoring data and the physiological index abnormality. The nursing remote monitoring system can improve the pertinence and comprehensiveness of nursing remote monitoring.

Description

Technical Field

[0001] The invention belongs to the field of nursing and relates to remote technology, in particular to a remote monitoring system for psychiatric nursing. Background Art

[0002] Existing remote monitoring systems for psychiatric nursing have the following drawbacks when remotely monitoring patients: 1. Existing remote monitoring systems for psychiatric nursing are unable to analyze patients' historical physiological indicators and set up targeted remote monitoring projects based on the analysis results, resulting in a lack of targeted remote monitoring process; 2. The existing remote monitoring system for psychiatric nursing can only monitor the physiological indicators of patients, but cannot monitor the emotional stability of psychiatric patients, resulting in a lack of comprehensiveness in the monitoring results.

[0003] To this end, we propose a remote monitoring system for psychiatric nursing. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a remote monitoring system for psychiatric nursing, aiming to improve the pertinence and comprehensiveness of remote monitoring results.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a remote monitoring system for psychiatric nursing, wherein the specific working process of each module is as follows: Physiological indicator module: Analyze the historical physiological indicators of the target patient, select several historical abnormal items based on the analysis results, and periodically monitor each historical abnormal item to obtain the abnormality degree of the physiological indicator; Emotion monitoring module: sets an emotion index monitoring cycle and several emotion indexes, monitors the changes of each emotion index of the target patient during the emotion index monitoring cycle, and divides the target patient into a first emotion stability interval and a second emotion stability interval according to the monitoring results, and obtains emotion stability monitoring data; Monitoring and early warning module: remotely warn target patients based on emotional stability monitoring data and abnormalities of physiological indicators.

[0006] Furthermore, physiological indicators of target students were monitored as follows: Randomly select a target patient from the monitored patients corresponding to the remote monitoring system and obtain the historical physiological index examination records corresponding to the target patient; Obtain historical abnormal items based on historical physiological index examination records to obtain historical abnormal items Y1 to Ya; In the process of monitoring physiological indicators of historical abnormal items, the current moment is marked as the cycle end time point, and in the period before the current moment, a cycle start time point is marked, and the period between the cycle start time point and the cycle end time point is marked as the historical abnormality monitoring period; Monitor the Y1 historical abnormal items for target patients who are in the historical abnormality monitoring period, and obtain the Y1 indicator abnormal value and Y1 indicator baseline value based on the monitoring results; Repeat the process of obtaining the indicator abnormal value corresponding to the Y1 historical abnormal item, and obtain the indicator abnormal values corresponding to the Y2 historical abnormal item to the Ya historical abnormal item respectively, and obtain the Y2 indicator abnormal value to the Ya indicator abnormal value; Repeat the process of obtaining the Y1 indicator benchmark value, and obtain the indicator benchmark values corresponding to the Y2 historical abnormal items to the Ya historical abnormal items respectively, and obtain the Y2 indicator benchmark value to the Ya indicator benchmark value; The abnormality degree of the physiological indicator is obtained according to the abnormal value of the Y1 indicator to the abnormal value of the Ya indicator and the reference value of the Y1 indicator to the reference value of the Ya indicator.

[0007] Furthermore, the historical abnormal items from Y1 to Ya are obtained, as follows: Acquire the physiological examination items involved in the historical physiological index examination record to obtain multiple physiological examination items, respectively obtain the examination results of each physiological examination item in the historical physiological index examination record, and if there is an abnormal examination result for the physiological examination item, mark the corresponding physiological examination item as a historical abnormal item; if there is no abnormal examination result for the physiological examination item, mark the corresponding physiological examination item as a non-historical abnormal item; The historical abnormal items in the historical physiological index examination records are obtained, and the obtained several historical abnormal items are marked as Y1 historical abnormal items to Ya historical abnormal items.

[0008] Furthermore, the abnormal value of the Y1 indicator and the baseline value of the Y1 indicator are obtained as follows: In the historical abnormality monitoring cycle, several monitoring time points are selected, and a sample monitoring time point is selected from the multiple monitoring time points obtained; Obtain the monitoring indicator value corresponding to the Y1 historical abnormal item at the sample monitoring time point to obtain the Y1 monitoring indicator value; Obtain the upper and lower limits of the benchmark indicator interval corresponding to the Y1 historical abnormal items. If the Y1 monitoring indicator value is greater than or equal to the upper limit of the benchmark indicator interval, calculate the difference between the Y1 monitoring indicator value and the upper limit of the benchmark indicator interval, and take the absolute value of the obtained difference to obtain the Y1 item abnormal value corresponding to the sample monitoring time point; If the Y1 monitoring indicator value is less than or equal to the lower limit of the benchmark indicator interval, the difference between the Y1 monitoring indicator value and the lower limit of the benchmark indicator interval is calculated, and the absolute value of the obtained difference is taken to obtain the Y1 item abnormal value corresponding to the sample monitoring time point; If the value of the Y1 monitoring indicator is greater than the lower limit of the benchmark indicator interval and less than the upper limit of the benchmark indicator interval, the value 0 is used to assign parameters to the abnormal value of the Y1 item; Repeat the process of obtaining the abnormal value of the Y1 item corresponding to the sample monitoring time point, obtain the abnormal value of the Y1 item corresponding to each monitoring time point of the Y1 historical abnormal item, and calculate the average value of the obtained multiple Y1 item abnormal values to obtain the abnormal value of the Y1 indicator; Calculate the difference between the upper limit of the benchmark indicator range and the lower limit of the benchmark indicator range to obtain the Y1 indicator benchmark value.

[0009] Furthermore, the abnormality of physiological indicators is obtained as follows: The abnormality of the physiological index corresponding to the target patient is obtained by calculating the abnormal value of the Y1 index to the abnormal value of the Ya index and the baseline value of the Y1 index to the baseline value of the Ya index; Calculate the abnormality of the physiological indicators corresponding to the target patient.

[0010] Furthermore, the emotional stability monitoring data is obtained as follows: During the process of monitoring the emotional stability of the target patient, a mood indicator monitoring period is marked; For the target patients, several emotion monitoring indicators are set, and the set emotion monitoring indicators are named Q1 emotion indicator to Qb emotion indicator: Perform Q1 mood index monitoring on the target patient in the mood index monitoring period, obtain the indicator cycle change rate corresponding to the Q1 mood index monitoring according to the monitoring results, and name it the Q1 indicator cycle change rate; Repeat the process of obtaining the periodic change rate of the Q1 indicator to obtain the periodic change rate of the indicator corresponding to the Q2 emotion index value Qb emotion index, and obtain the periodic change rate of the Q2 indicator to the periodic change rate of the Qb indicator; Obtain the index reference intervals corresponding to the Q1 emotion index to the Qb emotion index respectively, and obtain the Q1 emotion index reference interval to the Qb emotion index reference interval; The abnormality of the Q1 emotion index to the Qb emotion index is judged. If any abnormal emotion index exists among the Q1 emotion index to the Qb emotion index, the target patient is divided into the first emotion stability interval. If no abnormal emotion index exists among the Q1 emotion index to the Qb emotion index, the target patient is divided into the second emotion stability interval to obtain the emotion stability monitoring data.

[0011] Furthermore, the periodic change rate of the Q1 indicator is obtained as follows: The emotion index monitoring period is divided into several emotion monitoring time points, and the indicator value corresponding to the Q1 emotion index corresponding to each emotion monitoring time point is obtained to obtain multiple Q1 emotion index values; In the existing plane rectangular coordinate system, the emotion monitoring time point is marked as the horizontal coordinate, and the emotion index value is marked as the vertical coordinate. The Q1 emotion index value corresponding to each emotion monitoring time point is marked in the plane rectangular coordinate system in the form of a coordinate point to obtain multiple Q1 emotion coordinate points, and the obtained multiple Q1 emotion coordinate points are connected in sequence to obtain a Q1 emotion index waveform graph; In the Q1 emotion index waveform graph, bands in the Q1 emotion index waveform graph that are in the same monotonic state are acquired to obtain multiple identical monotonic waveform segments, and a sample monotonic waveform segment is arbitrarily selected; Perform peak-to-valley analysis on the monotonic waveform segments of the samples to obtain the rate of change of the sentiment index; The emotion index change rate corresponding to each identical monotonic waveform segment is obtained respectively, and the obtained multiple emotion index change rates are averaged to obtain the Q1 indicator periodic change rate.

[0012] Furthermore, the change rate of the sentiment index is obtained as follows: Obtain the peak value, trough value and peak-to-trough interval duration between the peak value and trough value of each identical monotonic waveform segment; The peak value Qfz, trough value Qgz and peak-to-trough interval Qfg corresponding to the sample monotonic waveform segment are used to calculate the emotion index change rate Qbx.

[0013] Furthermore, the abnormality of the Q1 to Qb sentiment indicators is judged as follows: If the Q1 indicator periodic change rate is within the Q1 sentiment index benchmark range, the Q1 sentiment index is marked as a normal sentiment index; if the Q1 indicator periodic change rate is not within the Q1 sentiment index benchmark range, the Q1 sentiment index is marked as an abnormal sentiment index; If the Q2 indicator periodic change rate is within the Q2 sentiment index benchmark range, the Q2 sentiment index is marked as a normal sentiment index; if the Q2 indicator periodic change rate is not within the Q2 sentiment index benchmark range, the Q2 sentiment index is marked as an abnormal sentiment index; By analogy, if the Qb indicator periodic change rate is within the Qb sentiment indicator benchmark range, the Qb sentiment indicator is marked as a normal sentiment indicator; if the Qb indicator periodic change rate is not within the Qb sentiment indicator benchmark range, the Qb sentiment indicator is marked as an abnormal sentiment indicator.

[0014] Furthermore, remote early warning is carried out for target patients, as follows: Acquire emotional stability monitoring data, and if the target patient is in the first emotional stability range, issue a remote monitoring result abnormal warning to the target patient; If the target patient is in the second emotional stability range, the abnormality of the physiological indicator corresponding to the target patient is obtained; Obtain the preset range of physiological indicator abnormality. If the physiological indicator abnormality is within the preset range, there is no need to issue a remote monitoring result abnormality warning to the target patient. If the physiological indicator abnormality is not within the preset range, a remote monitoring result abnormality warning is issued to the target patient.

[0015] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. The present invention analyzes the historical physiological indicators of the target patient, selects several historical abnormal items according to the analysis results, and periodically monitors each historical abnormal item, thereby ensuring the pertinence of remote physiological indicator monitoring.

[0016] 2. While monitoring the physiological indicators of the target patient, the present invention sets an emotional indicator monitoring cycle and several emotional indicators, and monitors the changes of each emotional indicator of the target patient during the emotional indicator monitoring cycle, which can improve the comprehensiveness of the remote monitoring results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0018] Figure 1 is a block diagram of the overall system of the present invention; Figure 2 This is the Q1 emotion index waveform diagram of the present invention. DETAILED DESCRIPTION

[0019] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] Example 1 See also Figure 1The present invention provides a technical solution: a remote monitoring system for psychiatric nursing, comprising a physiological indicator module, an emotion monitoring module, a monitoring and early warning module, and a server, wherein the physiological indicator module, the emotion monitoring module, and the monitoring and early warning module are respectively connected to the server, and the server controls the physiological indicator module, the behavior monitoring module, and the monitoring and early warning module respectively; The physiological indicator module analyzes the historical physiological indicators of the target patient, selects several historical abnormal items based on the analysis results, and periodically monitors each historical abnormal item to obtain the abnormality degree of the physiological indicator; The details are as follows: Randomly select a target patient from the monitored patients corresponding to the remote monitoring system and obtain the historical physiological index examination records corresponding to the target patient; It should be noted here that: In this application, the monitored patients involved here are specifically mentally ill patients who are currently taking mental illness drugs.

[0021] Acquire the physiological examination items involved in the historical physiological index examination record to obtain multiple physiological examination items, respectively obtain the examination results of each physiological examination item in the historical physiological index examination record, and if there is an abnormal examination result for the physiological examination item, mark the corresponding physiological examination item as a historical abnormal item; if there is no abnormal examination result for the physiological examination item, mark the corresponding physiological examination item as a non-historical abnormal item; It should be noted here that: The abnormal inspection involved here specifically refers to the inspection index value corresponding to the inspection item not being within the normal index range; In this application, the inspection items involved here are specifically inspection items for abnormal physiological indicators that appear in the clinical practice of psychiatric drugs. For example, clozapine, quetiapine, and chlorpromazine can cause a decrease in the patient's white blood cell count, and olanzapine and clozapine can easily cause weight gain and abnormal blood sugar and blood lipids. In this application, the physiological examination items involved here are but not limited to blood pressure, blood lipids and white blood cells.

[0022] Acquire historical abnormal items in the historical physiological index examination records, and mark the acquired several historical abnormal items as Y1 historical abnormal items to Ya historical abnormal items; It should be noted here that: In the present application, Y referred to here is the sign symbol corresponding to the historical abnormal item, a is the quantity value corresponding to the historical abnormal item, and a is an integer greater than 0.

[0023] In the process of monitoring physiological indicators of historical abnormal items, the current moment is marked as the cycle end time point, and in the period before the current moment, a cycle start time point is marked, and the period between the cycle start time point and the cycle end time point is marked as the historical abnormality monitoring period; It should be noted here that: As the current time value changes, the historical anomaly monitoring cycle can be dynamically updated.

[0024] Monitor the Y1 historical abnormal items for target patients who are in the historical abnormality monitoring period, and obtain the Y1 indicator abnormal value and Y1 indicator baseline value based on the monitoring results; The details are as follows: In the historical abnormality monitoring cycle, several monitoring time points are selected, and a sample monitoring time point is selected from the multiple monitoring time points obtained; Obtain the monitoring indicator value corresponding to the Y1 historical abnormal item at the sample monitoring time point to obtain the Y1 monitoring indicator value; It should be noted here that: If the Y1 historical abnormal item is heart rate, and the measured Y1 monitoring index value is 110, and the lower limit of the benchmark index interval corresponding to the Y1 historical abnormal item is 60, and the upper limit of the benchmark index interval corresponding to the Y1 historical abnormal item is 100, then the Y1 item abnormal value corresponding to the sample monitoring time point can be calculated to be 10; Obtain the upper and lower limits of the benchmark indicator interval corresponding to the Y1 historical abnormal items. If the Y1 monitoring indicator value is greater than or equal to the upper limit of the benchmark indicator interval, calculate the difference between the Y1 monitoring indicator value and the upper limit of the benchmark indicator interval, and take the absolute value of the obtained difference to obtain the Y1 item abnormal value corresponding to the sample monitoring time point; If the Y1 monitoring indicator value is less than or equal to the lower limit of the benchmark indicator interval, the difference between the Y1 monitoring indicator value and the lower limit of the benchmark indicator interval is calculated, and the absolute value of the obtained difference is taken to obtain the Y1 item abnormal value corresponding to the sample monitoring time point; If the value of the Y1 monitoring indicator is greater than the lower limit of the benchmark indicator interval and less than the upper limit of the benchmark indicator interval, the value 0 is used to assign parameters to the abnormal value of the Y1 item; Repeat the process of obtaining the abnormal value of the Y1 item corresponding to the sample monitoring time point, obtain the abnormal value of the Y1 item corresponding to each monitoring time point of the Y1 historical abnormal item, and calculate the average value of the obtained multiple Y1 item abnormal values to obtain the abnormal value of the Y1 indicator; Calculate the difference between the upper limit of the benchmark index interval and the lower limit of the benchmark index interval to obtain the Y1 index benchmark value; Repeat the process of obtaining the indicator abnormal value corresponding to the Y1 historical abnormal item, and obtain the indicator abnormal values corresponding to the Y2 historical abnormal item to the Ya historical abnormal item respectively, and obtain the Y2 indicator abnormal value to the Ya indicator abnormal value; Repeat the process of obtaining the Y1 indicator benchmark value, and obtain the indicator benchmark values corresponding to the Y2 historical abnormal items to the Ya historical abnormal items respectively, and obtain the Y2 indicator benchmark value to the Ya indicator benchmark value; The abnormality of the physiological index corresponding to the target patient is obtained by calculating the abnormal value of the Y1 index to the abnormal value of the Ya index and the baseline value of the Y1 index to the baseline value of the Ya index; The abnormality of the physiological indicators corresponding to the target patient is calculated. The specific formula is as follows: ; Among them, Szy is the abnormality of the physiological indicator corresponding to the target patient, Yci is the abnormal value of Yi indicator, Jzi is the baseline value of Yi indicator, and a is the quantitative value corresponding to the historical abnormal item; It should be noted here that: In the present application, the Yi indicator abnormal value involved here can be any indicator abnormal value from the Y1 indicator abnormal value to the Ya indicator abnormal value, and the Yi indicator reference value involved here can be any indicator reference value from the Y1 indicator reference value to the Ya indicator reference value.

[0025] In the specific implementation, there are the following experimental data: If the abnormal value of the Y1 indicator is 10, the baseline value of the Y1 indicator is 30, the abnormal value of the Y2 indicator is 30, the baseline value of the Y2 indicator is 56, the abnormal value of the Y3 indicator is 40, and the baseline value of the Y1 indicator is 60, then the abnormality of the physiological indicator corresponding to the target patient can be calculated to be 0.51.

[0026] The physiological indicator module obtains the abnormality of physiological indicators and transmits it to the monitoring and early warning module; The emotion monitoring module sets an emotion index monitoring cycle and several emotion indexes, monitors the changes of each emotion index of the target patient during the emotion index monitoring cycle, and divides the target patient into a first emotion stability interval and a second emotion stability interval according to the monitoring results, thereby obtaining emotion stability monitoring data; The details are as follows: During the process of monitoring the emotional stability of the target patient, a mood indicator monitoring period is marked; For the target patients, several emotion monitoring indicators are set, and the set emotion monitoring indicators are named Q1 emotion indicator to Qb emotion indicator: It should be noted here that: In this application, Q is the symbol corresponding to the emotion monitoring indicator, b is the numerical value corresponding to the emotion monitoring indicator, and b is an integer greater than 0; In this application, the emotion monitoring indicators involved herein are specifically clinical medical indicators that can be used to quantify the emotional changes of patients with mental illness; Perform Q1 mood index monitoring on the target patient in the mood index monitoring period, obtain the indicator cycle change rate corresponding to the Q1 mood index monitoring according to the monitoring results, and name it the Q1 indicator cycle change rate; The details are as follows: The emotion index monitoring period is divided into several emotion monitoring time points, and the indicator value corresponding to the Q1 emotion index corresponding to each emotion monitoring time point is obtained to obtain multiple Q1 emotion index values; See also Figure 2 In the existing plane rectangular coordinate system, the emotion monitoring time point is marked as the horizontal coordinate, and the emotion index value is marked as the vertical coordinate. The Q1 emotion index value corresponding to each emotion monitoring time point is marked in the plane rectangular coordinate system in the form of a coordinate point to obtain multiple Q1 emotion coordinate points, and the obtained multiple Q1 emotion coordinate points are connected in sequence to obtain a Q1 emotion index waveform graph; In the Q1 emotion index waveform graph, bands in the same monotonic state are obtained to obtain multiple identical monotonic waveform segments, and the peak value, trough value, and peak-to-trough interval duration between the peak value and the trough value of each identical monotonic waveform segment are obtained; The peak value Qfz, trough value Qgz, and peak-to-trough interval Qfg corresponding to the same monotonic waveform segment are used to calculate the emotion index change rate Qbx. The specific formula is as follows: ; The change rate of the emotion index corresponding to each identical monotonic waveform segment is obtained respectively, and the average of the obtained multiple emotion index change rates is calculated to obtain the Q1 indicator periodic change rate; Repeat the process of obtaining the periodic change rate of the Q1 indicator to obtain the periodic change rate of the indicator corresponding to the Q2 emotion index value Qb emotion index, and obtain the periodic change rate of the Q2 indicator to the periodic change rate of the Qb indicator; Obtain the index reference intervals corresponding to the Q1 emotion index to the Qb emotion index respectively, and obtain the Q1 emotion index reference interval to the Qb emotion index reference interval; It should be noted here that: In the specific implementation, the Qi emotion index baseline interval is obtained as follows: Obtaining Qi indicator periodic change rates of several mentally ill patients known to be emotionally normal during an emotional indicator monitoring period to obtain multiple Qi indicator periodic change rates, calculating an average of the multiple obtained Qi indicator periodic change rates to obtain a first Qi indicator characteristic value, calculating a standard deviation of the multiple obtained Qi indicator periodic change rates to obtain a second Qi indicator characteristic value, calculating a difference between the first Qi indicator characteristic value and the second Qi indicator characteristic value to obtain a lower limit of a Qi emotional indicator benchmark interval, calculating a sum of the first Qi indicator characteristic value and the second Qi indicator characteristic value to obtain an upper limit of a Qi emotional indicator benchmark interval, and marking a numerical range between the lower limit of the Qi emotional indicator benchmark interval and the upper limit of the Qi emotional indicator benchmark interval as a Qi emotional indicator benchmark interval; The Qi emotion index reference interval involved here may be any emotion index reference interval from the Q1 emotion index reference interval to the Qb emotion index reference interval.

[0027] The Q1 to Qb emotion indicators are judged for abnormality. If any abnormal emotion indicator exists among the Q1 to Qb emotion indicators, the target patient is divided into the first emotion stability interval. If no abnormal emotion indicator exists among the Q1 to Qb emotion indicators, the target patient is divided into the second emotion stability interval to obtain emotion stability monitoring data. The details are as follows: If the Q1 indicator periodic change rate is within the Q1 sentiment index benchmark range, the Q1 sentiment index is marked as a normal sentiment index; if the Q1 indicator periodic change rate is not within the Q1 sentiment index benchmark range, the Q1 sentiment index is marked as an abnormal sentiment index; If the Q2 indicator periodic change rate is within the Q2 sentiment index benchmark range, the Q2 sentiment index is marked as a normal sentiment index; if the Q2 indicator periodic change rate is not within the Q2 sentiment index benchmark range, the Q2 sentiment index is marked as an abnormal sentiment index; Similarly, if the Qb indicator periodic change rate is within the Qb sentiment indicator benchmark range, the Qb sentiment indicator is marked as a normal sentiment indicator; if the Qb indicator periodic change rate is not within the Qb sentiment indicator benchmark range, the Qb sentiment indicator is marked as an abnormal sentiment indicator; It should be noted here that: The abnormal sentiment index includes the sentiment index baseline interval boundary.

[0028] The emotion monitoring module acquires the emotion stability monitoring data and transmits it to the monitoring and early warning module; The monitoring and early warning module provides remote early warning to target patients based on emotional stability monitoring data and abnormal physiological indicators; The details are as follows: Acquire emotional stability monitoring data, and if the target patient is in the first emotional stability range, issue a remote monitoring result abnormal warning to the target patient; If the target patient is in the second emotional stability range, the abnormality of the physiological indicator corresponding to the target patient is obtained; Obtaining a preset range of physiological indicator abnormality. If the physiological indicator abnormality is within the preset range, there is no need to issue a remote monitoring result abnormality warning to the target patient. If the physiological indicator abnormality is not within the preset range, then a remote monitoring result abnormality warning is issued to the target patient. It should be noted here that: Situations where abnormal warnings of remote monitoring results are required include the preset interval boundaries of abnormal physiological indicators; Obtaining the preset abnormality interval of physiological indicators; The details are as follows: The lower limit of the preset interval of physiological index abnormality is 0, which means that the patient has no physiological index abnormality; Obtain several historical patients who do not need to issue abnormal warnings for remote monitoring results, obtain the abnormality of physiological indicators corresponding to each historical patient, and calculate the average of the obtained abnormality of physiological indicators to obtain the upper limit of the preset range of the abnormality of physiological indicators.

[0029] In this application, if a corresponding calculation formula appears, the above calculation formula is dimensionless and its numerical calculation is performed. The weight coefficient, proportional coefficient and other coefficients in the formula are set to a result value obtained by quantifying each parameter. Regarding the size of the weight coefficient and the proportional coefficient, as long as it does not affect the proportional relationship between the parameter and the result value, it is acceptable.

[0030] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A remote monitoring system for psychiatric nursing, characterized in that: include: Physiological indicator module: Analyze the historical physiological indicators of the target patient, select several historical abnormal items based on the analysis results, and periodically monitor each historical abnormal item to obtain the abnormality degree of the physiological indicator; Emotion monitoring module: sets an emotion indicator monitoring cycle and several emotion indicators, monitors the changes of each emotion indicator during the emotion indicator monitoring cycle, and divides the target patient into a first emotion stability interval and a second emotion stability interval based on the monitoring results, thereby obtaining emotion stability monitoring data; The monitoring and early warning module provides remote early warning to target patients based on emotional stability monitoring data and abnormalities of physiological indicators.

2. A remote monitoring system for psychiatric nursing according to claim 1, characterized in that: Physiological indicators of target students are monitored as follows: Randomly select a target patient and obtain the historical physiological index examination records corresponding to the target patient; Obtain historical abnormal items based on historical physiological index examination records to obtain historical abnormal items Y1 to Ya; In the process of monitoring physiological indicators of historical abnormal items, a historical abnormal monitoring cycle is marked; Monitor the Y1 historical abnormal items for target patients who are in the historical abnormality monitoring period, and obtain the Y1 indicator abnormal value and Y1 indicator baseline value based on the monitoring results; Obtain the indicator abnormal values corresponding to the Y2 historical abnormal items to the Ya historical abnormal items respectively, and obtain the Y2 indicator abnormal value to the Ya indicator abnormal value; Obtain the indicator benchmark values corresponding to the Y2 historical abnormal items to the Ya historical abnormal items respectively, and obtain the Y2 indicator benchmark value to the Ya indicator benchmark value; The abnormality degree of the physiological indicator is obtained according to the abnormal value of the Y1 indicator to the abnormal value of the Ya indicator and the reference value of the Y1 indicator to the reference value of the Ya indicator.

3. A remote monitoring system for psychiatric nursing according to claim 2, characterized in that: Obtain historical abnormal items from Y1 to Ya, as follows: Acquire the physiological examination items involved in the historical physiological index examination record to obtain multiple physiological examination items, respectively obtain the examination results of each physiological examination item in the historical physiological index examination record, and if there is an abnormal examination result for the physiological examination item, mark the corresponding physiological examination item as a historical abnormal item; if there is no abnormal examination result for the physiological examination item, mark the corresponding physiological examination item as a non-historical abnormal item; Historical abnormal items are acquired, and the acquired historical abnormal items are marked as Y1 historical abnormal items to Ya historical abnormal items.

4. A remote monitoring system for psychiatric nursing according to claim 2, characterized in that: The abnormal value and benchmark value of the Y1 indicator are obtained as follows: In the historical abnormality monitoring cycle, several monitoring time points are selected, and a sample monitoring time point is selected from the multiple monitoring time points obtained; Obtain the monitoring indicator value corresponding to the Y1 historical abnormal item at the sample monitoring time point to obtain the Y1 monitoring indicator value; Obtain the upper and lower limits of the benchmark indicator interval corresponding to the Y1 historical abnormal items. If the Y1 monitoring indicator value is greater than or equal to the upper limit of the benchmark indicator interval, calculate the difference between the Y1 monitoring indicator value and the upper limit of the benchmark indicator interval, and take the absolute value of the obtained difference to obtain the Y1 item abnormal value corresponding to the sample monitoring time point; If the Y1 monitoring indicator value is less than or equal to the lower limit of the benchmark indicator interval, the difference between the Y1 monitoring indicator value and the lower limit of the benchmark indicator interval is calculated, and the absolute value of the obtained difference is taken to obtain the Y1 item abnormal value corresponding to the sample monitoring time point; If the value of the Y1 monitoring indicator is greater than the lower limit of the benchmark indicator interval and less than the upper limit of the benchmark indicator interval, the value 0 is used to assign parameters to the abnormal value of the Y1 item; Obtain the Y1 item abnormal value corresponding to each monitoring time point of the Y1 historical abnormal item, and calculate the average value of the obtained multiple Y1 item abnormal values to obtain the Y1 indicator abnormal value; Calculate the difference between the upper limit of the benchmark indicator interval and the lower limit of the benchmark indicator interval to obtain the Y1 indicator benchmark value.

5. A remote monitoring system for psychiatric nursing according to claim 2, characterized in that: The abnormality of physiological indicators is obtained as follows: The abnormality of the physiological index corresponding to the target patient is obtained by calculating the abnormal value of the Y1 index to the abnormal value of the Ya index and the baseline value of the Y1 index to the baseline value of the Ya index; Calculate the abnormality of the physiological indicators corresponding to the target patient.

6. A remote monitoring system for psychiatric nursing according to claim 1, characterized in that: The emotional stability monitoring data is obtained as follows: During the process of monitoring the emotional stability of the target patient, a mood indicator monitoring period is marked; For the target patients, several emotion monitoring indicators are set, and the set emotion monitoring indicators are named Q1 emotion indicator to Qb emotion indicator: Perform Q1 mood index monitoring on the target patient in the mood index monitoring period, obtain the indicator cycle change rate corresponding to the Q1 mood index monitoring according to the monitoring results, and name it the Q1 indicator cycle change rate; Obtain the indicator periodic change rate corresponding to the Q2 emotion index value and the Qb emotion index respectively, and obtain the Q2 indicator periodic change rate to the Qb indicator periodic change rate; Obtain the index reference intervals corresponding to the Q1 emotion index to the Qb emotion index respectively, and obtain the Q1 emotion index reference interval to the Qb emotion index reference interval; The abnormality of the Q1 emotion index to the Qb emotion index is judged. If any abnormal emotion index exists among the Q1 emotion index to the Qb emotion index, the target patient is divided into the first emotion stability interval. If no abnormal emotion index exists among the Q1 emotion index to the Qb emotion index, the target patient is divided into the second emotion stability interval to obtain the emotion stability monitoring data.

7. A remote monitoring system for psychiatric nursing according to claim 6, characterized in that: The periodic change rate of the Q1 indicator is obtained as follows: The emotion index monitoring period is divided into several emotion monitoring time points, and the indicator value corresponding to the Q1 emotion index corresponding to each emotion monitoring time point is obtained to obtain multiple Q1 emotion index values; In the existing plane rectangular coordinate system, the emotion monitoring time point is marked as the horizontal coordinate, and the emotion index value is marked as the vertical coordinate. The Q1 emotion index value corresponding to each emotion monitoring time point is marked in the plane rectangular coordinate system in the form of a coordinate point to obtain multiple Q1 emotion coordinate points, and the obtained multiple Q1 emotion coordinate points are connected in sequence to obtain a Q1 emotion index waveform graph; In the Q1 emotion index waveform graph, bands in the Q1 emotion index waveform graph that are in the same monotonic state are acquired to obtain multiple identical monotonic waveform segments, and a sample monotonic waveform segment is arbitrarily selected; Perform peak-valley analysis on the sample monotonic waveform segment to obtain the emotion index change rate corresponding to the sample monotonic waveform segment; The emotion index change rate corresponding to each identical monotonic waveform segment is obtained respectively, and the obtained multiple emotion index change rates are averaged to obtain the Q1 indicator periodic change rate.

8. A remote monitoring system for psychiatric nursing according to claim 7, characterized in that: The change rate of the sentiment indicator is obtained as follows: Obtain the peak value, trough value, and peak-to-trough interval duration between the peak value and the trough value of each identical monotonic waveform segment; The peak value Qfz, trough value Qgz and peak-to-trough interval Qfg corresponding to the sample monotonic waveform segment are used to calculate the emotion index change rate Qbx.

9. A remote monitoring system for psychiatric nursing according to claim 7, characterized in that: The abnormality of the indicators from Q1 to Qb is judged as follows: If the Q1 indicator periodic change rate is within the Q1 sentiment index benchmark range, the Q1 sentiment index is marked as a normal sentiment index; if the Q1 indicator periodic change rate is not within the Q1 sentiment index benchmark range, the Q1 sentiment index is marked as an abnormal sentiment index; If the Qb indicator periodic change rate is within the Qb sentiment indicator benchmark range, the Qb sentiment indicator is marked as a normal sentiment indicator. If the Qb indicator periodic change rate is not within the Qb sentiment indicator benchmark range, the Qb sentiment indicator is marked as an abnormal sentiment indicator.

10. A remote monitoring system for psychiatric nursing according to claim 1, characterized in that: Remote early warning for target patients, as follows: Acquire emotional stability monitoring data, and if the target patient is in the first emotional stability range, issue a remote monitoring result abnormal warning to the target patient; If the target patient is in the second emotional stability range, the abnormality of the physiological indicator corresponding to the target patient is obtained; Obtain the preset range of physiological indicator abnormality. If the physiological indicator abnormality is within the preset range, there is no need to issue a remote monitoring result abnormality warning to the target patient. If the physiological indicator abnormality is not within the preset range, a remote monitoring result abnormality warning is issued to the target patient.

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