Disease monitoring system for intelligent nursing

Abstract

The invention discloses an intelligent nursing illness state monitoring system, and relates to the technical field of intelligent nursing, the intelligent nursing illness state monitoring system comprises a collection module, an analysis module, an early warning module and a display module, illness state development information is obtained through analysis, a physical sign early warning signal is sent out, patient emotion information and patient posture information are judged, and a posture early warning signal is generated; warning lamps with different brightness and different colors are emitted, the emotion information of the patient, the attribute information of the first warning lamp, the attribute information of the second warning lamp and the corresponding patient number are displayed, and medical care feedback information is received. Through multi-level preprocessing and analysis, the development trend of the illness state is accurately judged, the life health of the patient is guaranteed, the emotional state and posture stability of the patient are judged, the psychological health and life health of the patient are facilitated, warning lamps with different brightness and colors are sent out to send out sign and posture early warning signals, and the early warning effect is improved. Information transmission is more intuitive and effective, the expert platform is accessed, and the individuation level of nursing is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent nursing, and in particular to a disease condition monitoring system for intelligent nursing. Background Art

[0002] In recent years, the application of intelligent nursing technology in medical image analysis, medical record data mining and other fields can help doctors make diagnosis and treatment decisions more quickly and accurately, improving the quality and efficiency of medical services.

[0003] At present, a Chinese invention patent with publication number CN 113436717 B discloses a smart medical condition monitoring and management system based on big data. The method associates the patient's symptoms with his previous diseases, so as to quickly understand whether the patient has complications of the previous diseases, thereby facilitating in-depth monitoring of the patient's condition. However, the relevant technology does not analyze the real-time collected data, lacks the continuity and timeliness of monitoring, does not provide decision-making recommendations to patients based on the real-time collected data, and lacks the affinity of monitoring. Summary of the invention

[0004] The technical problem solved by the present invention is that the related technology does not analyze the data collected in real time, lacks the continuity and timeliness of monitoring, does not provide decision-making suggestions to patients based on the data collected in real time, and lacks the affinity of monitoring.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a disease monitoring system for intelligent nursing, comprising a collection module, an analysis module, an early warning module and a display module;

[0006] The acquisition module acquires vital sign data, laboratory data, facial image data and motion trajectory data, and transmits the vital sign data, laboratory data, facial image data and motion trajectory data to the analysis module;

[0007] The analysis module performs a first preprocessing on the vital sign data, a second preprocessing on the facial image data, and a third preprocessing on the motion trajectory data, stores and analyzes the first preprocessed vital sign data to obtain disease progression information, issues a vital sign warning signal according to the disease progression information, extracts a feature quantity of the second preprocessed facial image data, determines the patient's emotional information according to the feature quantity of the second preprocessed facial image data, transmits the patient's emotional information to the display module, extracts a key frame of the motion trajectory after the third preprocessing, determines the patient's posture information based on the key frame of the third preprocessed motion trajectory, and generates a posture warning signal according to the patient's posture information;

[0008] The warning module emits a first warning light of different brightness and color according to different vital sign warning signals, and transmits the attribute information of the first warning light to the display module; the warning module emits a second warning light of different brightness and color according to different posture warning signals, and transmits the attribute information of the second warning light to the display module;

[0009] The display module is used to display the patient's emotional information, the attribute information of the first alarm light, the attribute information of the second alarm light and the corresponding patient number, and receive medical feedback information.

[0010] As a preferred solution of the intelligent nursing disease monitoring system described in the present invention, the acquisition module acquires vital signs data, laboratory data, facial image data and motion trajectory data within a first time period, the vital signs data include body temperature, heart rate, pulse, respiratory rate, blood pressure and blood oxygen concentration, the laboratory data include white blood cell technology and platelet concentration, obtains the patient's number and acquisition time, and transmits the patient's number and acquisition time to the analysis module and the display module.

[0011] As a preferred solution of the intelligent nursing condition monitoring system of the present invention, wherein: the first preprocessing includes outlier removal processing and normalization processing, the second preprocessing includes filtering processing and normalization processing, and the third preprocessing includes frame segmentation and windowing processing and key frame extraction processing;

[0012] The analysis module retrieves a nursing database, inputs a patient number into the nursing database, obtains a nursing record sheet corresponding to the patient number, and stores the first preprocessed vital sign data and collection time in the nursing data sheet.

[0013] As a preferred solution of the intelligent nursing disease monitoring system of the present invention, wherein: the analysis module sets a standard vital sign data interval, compares the first pre-processed vital sign data with the standard vital sign data, obtains disease progression information, and issues a vital sign warning signal according to the disease progression information;

[0014] The analysis module extracts the feature quantity of the second preprocessed facial image data, calls the expression database, obtains any facial image in the expression database, extracts the feature quantity of the facial image, sets the feature quantity of the facial image as the standard feature quantity, calculates the similarity between the feature quantity of the second preprocessed facial image data and the standard feature quantity, traverses the similarity, selects the facial image corresponding to the similarity with the largest value, sets the facial image corresponding to the similarity with the largest value as the patient's emotional information, and transmits the patient's emotional information to the display module;

[0015] The analysis module extracts the key frame of the motion trajectory after the third preprocessing. When the angle between the body and the ground is not within the range of the first value and the second value, the corresponding frame is set as the key frame, the patient's posture information is judged based on the key frame, and a posture warning signal is generated according to the patient's posture information.

[0016] As a preferred solution of the intelligent nursing condition monitoring system of the present invention, the judgment logic of the patient posture information is: when the angle between the body and the ground corresponding to the key frame decreases continuously in a continuous time period, the patient posture information is set to fall, otherwise it is set to not fall;

[0017] When the posture information is set to fall, a posture warning signal is generated, and the posture warning signal is transmitted to the warning module.

[0018] As a preferred solution of the intelligent nursing disease monitoring system of the present invention, the logic of the occurrence of the vital sign warning signal is: obtaining body temperature, heart rate, pulse, respiratory rate, blood pressure and blood oxygen concentration, setting a standard body temperature interval, a standard heart rate interval, a standard pulse interval, a standard respiratory rate interval, a standard blood pressure interval and a standard blood oxygen concentration interval;

[0019] When the body temperature is not within the standard body temperature range, an abnormal body temperature signal is issued; when the heart rate is not within the standard heart rate range, an abnormal heart rate signal is issued; when the pulse is not within the standard pulse range, an abnormal pulse signal is issued; when the respiratory rate is not within the standard respiratory rate range, an abnormal respiratory rate signal is issued; when the blood pressure is not within the standard blood pressure range, an abnormal blood pressure signal is issued; when the blood oxygen concentration is not within the standard blood oxygen concentration range, an abnormal blood oxygen concentration signal is issued.

[0020] As a preferred solution of the intelligent nursing condition monitoring system of the present invention, the similarity between the feature quantity of the second preprocessed facial image data and the standard feature quantity is calculated as follows:

[0021]

[0022] Wherein, XS is the similarity between the feature quantity of the facial image data after the second preprocessing and the standard feature quantity, x i is the i-th feature value of the facial image data after the second preprocessing, n is the number of feature values ​​of the facial image data after the second preprocessing, y i is the i-th standard feature quantity.

[0023] As a preferred solution of the intelligent nursing condition monitoring system described in the present invention, wherein: the alarm light generation logic of the early warning module is: when an abnormal body temperature signal is issued, the early warning module emits a first alarm light of a first brightness and a first color, when an abnormal heart rate signal is issued, the early warning module emits a first alarm light of a second brightness and a second color, when an abnormal pulse signal is issued, the early warning module emits a first alarm light of a third brightness and a third color, when an abnormal respiratory rate signal is issued, the early warning module emits a first alarm light of a fourth brightness and a fourth color, when an abnormal blood pressure signal is issued, the early warning module emits a first alarm light of a fifth brightness and a fifth color, when an abnormal blood oxygen concentration signal is issued, the early warning module emits a first alarm light of a sixth brightness and a sixth color, and transmits the attribute information of the first alarm light to the display module, the attribute information of the first alarm light including the first attribute light color and the first attribute light brightness;

[0024] When a posture warning signal is generated, the warning module emits a second warning light of the seventh brightness and the seventh color, and transmits attribute information of the second warning light to the display module, wherein the attribute information of the second warning light includes a second attribute light color and a second attribute light brightness.

[0025] As a preferred solution of the intelligent nursing disease monitoring system described in the present invention, the display module includes a patient-side display unit and a medical-side display unit, the medical-side display unit is used to display the patient's emotional information, the attribute information of the first alarm light, the attribute information of the second alarm light and the corresponding patient number, and the patient-side display unit is used to display medical advice.

[0026] As a preferred solution of the intelligent nursing disease monitoring system described in the present invention, the logic for generating the medical advice is as follows: receiving the patient's emotional information, the attribute information of the first alarm light, the attribute information of the second alarm light and the corresponding patient number, calling the case database, obtaining the type of disease corresponding to the patient number, calling the expert platform, and the expert generates medical advice for the patient by analyzing the type of disease corresponding to the patient number, the patient's emotional information, the attribute information of the first alarm light and the attribute information of the second alarm light, and the medical advice includes dietary suggestions and activity suggestions.

[0027] The beneficial effects of the present invention are as follows: by collecting vital sign data, laboratory data, facial image data and motion trajectory data, combined with the processing of the analysis module, the health status of the patient can be monitored in real time. The analysis module performs multi-level preprocessing and analysis on the data, so as to accurately judge the development trend of the disease, and issue corresponding physical sign and posture warning signals, to help medical staff to timely discover the abnormal conditions of the patient, which is beneficial to protecting the life and health of the patient. The system automatically judges the patient's emotional state, such as anxiety and depression, and the stability of the posture, such as whether there is any dangerous behavior such as falling to the ground, so as to issue corresponding alarms, which is beneficial to the patient's mental health and life health. The warning module issues physical sign and posture warning signals through alarm lights of different brightness and colors, making information transmission more intuitive and effective, improving the work efficiency of medical staff, accessing the expert platform, and improving the personalized level of nursing. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A basic flow chart of a disease condition monitoring system for intelligent nursing provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0030] Example 1, reference Figure 1 , as one embodiment of the present invention, provides a disease monitoring system for intelligent nursing, including a collection module, an analysis module, an early warning module and a display module;

[0031] The acquisition module acquires vital sign data, laboratory data, facial image data and motion trajectory data, and transmits the vital sign data, laboratory data, facial image data and motion trajectory data to the analysis module;

[0032] The analysis module performs a first preprocessing on the vital sign data, a second preprocessing on the facial image data, and a third preprocessing on the motion trajectory data, stores and analyzes the first preprocessed vital sign data to obtain disease progression information, issues a vital sign warning signal according to the disease progression information, extracts a feature quantity of the second preprocessed facial image data, determines the patient's emotional information according to the feature quantity of the second preprocessed facial image data, transmits the patient's emotional information to the display module, extracts a key frame of the motion trajectory after the third preprocessing, determines the patient's posture information based on the key frame of the third preprocessed motion trajectory, and generates a posture warning signal according to the patient's posture information;

[0033] The warning module emits a first warning light of different brightness and color according to different vital sign warning signals, and transmits the attribute information of the first warning light to the display module; the warning module emits a second warning light of different brightness and color according to different posture warning signals, and transmits the attribute information of the second warning light to the display module;

[0034] The display module is used to display the patient's emotional information, the attribute information of the first alarm light, the attribute information of the second alarm light and the corresponding patient number, and receive medical feedback information.

[0035] The present invention can monitor the health status of patients in real time by collecting vital sign data, laboratory data, facial image data and motion trajectory data, combined with the processing of the analysis module. The analysis module performs multi-level preprocessing and analysis on the data, so as to accurately judge the development trend of the disease and issue corresponding physical sign and posture warning signals to help medical staff discover abnormal conditions of patients in time, which is beneficial to protecting the life and health of patients. The system automatically judges the patient's emotional state, such as anxiety and depression, and the stability of posture, such as whether there are dangerous behaviors such as falling to the ground, and thus issues corresponding alarms, which is beneficial to the patient's mental health and life health. The warning module issues physical sign and posture warning signals through alarm lights of different brightness and colors, making information transmission more intuitive and effective, improving the work efficiency of medical staff, accessing the expert platform, and improving the personalized level of nursing.

[0036] The acquisition module acquires vital sign data, laboratory data, facial image data and motion trajectory data within a first time period, wherein the vital sign data includes body temperature, heart rate, pulse, respiratory rate, blood pressure and blood oxygen concentration, and the laboratory data includes white blood cell technology and platelet concentration, obtains the patient's number and acquisition time, and transmits the patient's number and acquisition time to the analysis module and the display module.

[0037] The vital sign data is obtained through a wearable instrument, and the test data is obtained through a medical blood test.

[0038] The first preprocessing includes outlier removal and normalization, the second preprocessing includes filtering and normalization, and the third preprocessing includes frame splitting and windowing and key frame extraction;

[0039] The analysis module retrieves a nursing database, inputs a patient number into the nursing database, obtains a nursing record sheet corresponding to the patient number, and stores the first preprocessed vital sign data and collection time in the nursing data sheet.

[0040] In a specific implementation, the normalization process makes the data distributed between 0 and 1, which is beneficial for subsequent analysis of the data and reduces the amount of calculation of the system.

[0041] The analysis module sets a standard vital sign data interval, compares the first preprocessed vital sign data with the standard vital sign data, obtains disease progression information, and issues a vital sign warning signal according to the disease progression information;

[0042] The analysis module extracts the feature quantity of the second preprocessed facial image data, calls the expression database, obtains any facial image in the expression database, extracts the feature quantity of the facial image, sets the feature quantity of the facial image as the standard feature quantity, calculates the similarity between the feature quantity of the second preprocessed facial image data and the standard feature quantity, traverses the similarity, selects the facial image corresponding to the similarity with the largest value, sets the facial image corresponding to the similarity with the largest value as the patient's emotional information, and transmits the patient's emotional information to the display module;

[0043] The analysis module extracts the key frame of the motion trajectory after the third preprocessing. When the angle between the body and the ground is not within the range of the first value and the second value, the corresponding frame is set as the key frame, the patient's posture information is judged based on the key frame, and a posture warning signal is generated according to the patient's posture information.

[0044] The judgment logic of the patient posture information is: when the angle between the body and the ground corresponding to the key frame decreases continuously in a continuous time period, the patient posture information is set to fall, otherwise it is set to not fall;

[0045] When the posture information is set to fall, a posture warning signal is generated, and the posture warning signal is transmitted to the warning module.

[0046] The generation logic of the vital sign warning signal is: obtaining body temperature, heart rate, pulse, respiratory rate, blood pressure and blood oxygen concentration, setting standard body temperature interval, standard heart rate interval, standard pulse interval, standard respiratory rate interval, standard blood pressure interval and standard blood oxygen concentration interval;

[0047] When the body temperature is not within the standard body temperature range, an abnormal body temperature signal is issued; when the heart rate is not within the standard heart rate range, an abnormal heart rate signal is issued; when the pulse is not within the standard pulse range, an abnormal pulse signal is issued; when the respiratory rate is not within the standard respiratory rate range, an abnormal respiratory rate signal is issued; when the blood pressure is not within the standard blood pressure range, an abnormal blood pressure signal is issued; when the blood oxygen concentration is not within the standard blood oxygen concentration range, an abnormal blood oxygen concentration signal is issued.

[0048] In specific implementation, by collecting vital signs data, laboratory data, facial image data and motion trajectory data, combined with the processing of the analysis module, the patient's health status can be monitored in real time. The analysis module performs multi-level preprocessing and analysis on the data, so as to accurately judge the development trend of the disease.

[0049] The calculation expression of the similarity between the feature quantity of the facial image data after the second preprocessing and the standard feature quantity is:

[0050]

[0051] Wherein, XS is the similarity between the feature quantity of the facial image data after the second preprocessing and the standard feature quantity, x i is the i-th feature value of the facial image data after the second preprocessing, n is the number of feature values ​​of the facial image data after the second preprocessing, y i is the i-th standard feature quantity.

[0052] In specific implementation, the system automatically determines the patient's emotional state, such as anxiety and depression, as well as the stability of the posture, such as whether there are dangerous behaviors such as falling down, and issues corresponding alarms, which is beneficial to the patient's mental health and life health.

[0053] The alarm light generation logic of the early warning module is as follows: when an abnormal body temperature signal is issued, the early warning module emits a first alarm light of a first brightness and a first color; when an abnormal heart rate signal is issued, the early warning module emits a first alarm light of a second brightness and a second color; when an abnormal pulse signal is issued, the early warning module emits a first alarm light of a third brightness and a third color; when an abnormal respiratory rate signal is issued, the early warning module emits a first alarm light of a fourth brightness and a fourth color; when an abnormal blood pressure signal is issued, the early warning module emits a first alarm light of a fifth brightness and a fifth color; when an abnormal blood oxygen concentration signal is issued, the early warning module emits a first alarm light of a sixth brightness and a sixth color, and transmits the attribute information of the first alarm light to the display module, the attribute information of the first alarm light including the first attribute light color and the first attribute light brightness;

[0054] When a posture warning signal is generated, the warning module emits a second warning light of the seventh brightness and the seventh color, and transmits attribute information of the second warning light to the display module, wherein the attribute information of the second warning light includes a second attribute light color and a second attribute light brightness.

[0055] During the specific implementation, corresponding physical signs and posture warning signals are issued to help medical staff detect abnormal conditions of patients in a timely manner, which is beneficial to protecting the life and health of patients and making information communication more intuitive and effective.

[0056] The display module includes a patient-side display unit and a medical-side display unit. The medical-side display unit is used to display patient emotional information, attribute information of the first alarm light, attribute information of the second alarm light and the corresponding patient number. The patient-side display unit is used to display medical advice.

[0057] The logic for generating the medical advice is as follows: receiving the patient's emotional information, the attribute information of the first alarm light, the attribute information of the second alarm light and the corresponding patient number, calling the case database, obtaining the type of disease corresponding to the patient number, calling the expert platform, and the expert generates medical advice for the patient by analyzing the type of disease corresponding to the patient number, the patient's emotional information, the attribute information of the first alarm light and the attribute information of the second alarm light, and the medical advice includes dietary advice and activity advice.

[0058] During the specific implementation, access to the expert platform improved the level of personalization of nursing care.

[0059] The present invention can monitor the health status of patients in real time by collecting vital sign data, laboratory data, facial image data and motion trajectory data, combined with the processing of the analysis module. The analysis module performs multi-level preprocessing and analysis on the data, so as to accurately judge the development trend of the disease and issue corresponding physical sign and posture warning signals to help medical staff discover abnormal conditions of patients in time, which is beneficial to protecting the life and health of patients. The system automatically judges the patient's emotional state, such as anxiety and depression, and the stability of posture, such as whether there are dangerous behaviors such as falling to the ground, and thus issues corresponding alarms, which is beneficial to the patient's mental health and life health. The warning module issues physical sign and posture warning signals through alarm lights of different brightness and colors, making information transmission more intuitive and effective, improving the work efficiency of medical staff, accessing the expert platform, and improving the personalized level of nursing.

[0060] It should be understood by those skilled in the art that the embodiments of the present invention can be provided as methods, systems or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0061] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. Intelligent nursing care condition monitoring system, characterized in that: It includes acquisition module, analysis module, warning module and display module; The acquisition module acquires vital sign data, laboratory data, facial image data and motion trajectory data, and transmits the vital sign data, laboratory data, facial image data and motion trajectory data to the analysis module; The analysis module performs a first preprocessing on the vital sign data, a second preprocessing on the facial image data, and a third preprocessing on the motion trajectory data, stores and analyzes the first preprocessed vital sign data to obtain disease progression information, issues a vital sign warning signal according to the disease progression information, extracts a feature quantity of the second preprocessed facial image data, determines the patient's emotional information according to the feature quantity of the second preprocessed facial image data, transmits the patient's emotional information to the display module, extracts a key frame of the motion trajectory after the third preprocessing, determines the patient's posture information based on the key frame of the third preprocessed motion trajectory, and generates a posture warning signal according to the patient's posture information; The warning module emits a first warning light of different brightness and color according to different vital sign warning signals, and transmits the attribute information of the first warning light to the display module; the warning module emits a second warning light of different brightness and color according to different posture warning signals, and transmits the attribute information of the second warning light to the display module; The display module is used to display the patient's emotional information, the attribute information of the first alarm light, the attribute information of the second alarm light and the corresponding patient number, and receive medical feedback information.

2. The intelligent nursing condition monitoring system according to claim 1, characterized in that: The acquisition module acquires vital sign data, laboratory data, facial image data and motion trajectory data within a first time period, wherein the vital sign data includes body temperature, heart rate, pulse, respiratory rate, blood pressure and blood oxygen concentration, and the laboratory data includes white blood cell technology and platelet concentration, obtains the patient's number and acquisition time, and transmits the patient's number and acquisition time to the analysis module and the display module.

3. The intelligent nursing condition monitoring system according to claim 1, characterized in that: The first preprocessing includes outlier removal and normalization, the second preprocessing includes filtering and normalization, and the third preprocessing includes frame splitting and windowing and key frame extraction; The analysis module retrieves a nursing database, inputs a patient number into the nursing database, obtains a nursing record sheet corresponding to the patient number, and stores the first preprocessed vital sign data and collection time in the nursing data sheet.

4. The intelligent nursing condition monitoring system according to claim 2, characterized in that: The analysis module sets a standard vital sign data interval, compares the first preprocessed vital sign data with the standard vital sign data, obtains disease progression information, and issues a vital sign warning signal according to the disease progression information; The analysis module extracts the feature quantity of the second preprocessed facial image data, calls the expression database, obtains any facial image in the expression database, extracts the feature quantity of the facial image, sets the feature quantity of the facial image as the standard feature quantity, calculates the similarity between the feature quantity of the second preprocessed facial image data and the standard feature quantity, traverses the similarity, selects the facial image corresponding to the similarity with the largest value, sets the facial image corresponding to the similarity with the largest value as the patient's emotional information, and transmits the patient's emotional information to the display module; The analysis module extracts the key frame of the motion trajectory after the third preprocessing. When the angle between the body and the ground is not within the range of the first value and the second value, the corresponding frame is set as the key frame, the patient's posture information is judged based on the key frame, and a posture warning signal is generated according to the patient's posture information.

5. The intelligent nursing condition monitoring system according to claim 4, characterized in that: The judgment logic of the patient posture information is: when the angle between the body and the ground corresponding to the key frame decreases continuously in a continuous time period, the patient posture information is set to fall, otherwise it is set to not fall; When the posture information is set to fall, a posture warning signal is generated, and the posture warning signal is transmitted to the warning module.

6. The intelligent nursing condition monitoring system according to claim 4, characterized in that: The generation logic of the vital sign warning signal is: obtaining body temperature, heart rate, pulse, respiratory rate, blood pressure and blood oxygen concentration, setting standard body temperature interval, standard heart rate interval, standard pulse interval, standard respiratory rate interval, standard blood pressure interval and standard blood oxygen concentration interval; When the body temperature is not within the standard body temperature range, an abnormal body temperature signal is issued; when the heart rate is not within the standard heart rate range, an abnormal heart rate signal is issued; when the pulse is not within the standard pulse range, an abnormal pulse signal is issued; when the respiratory rate is not within the standard respiratory rate range, an abnormal respiratory rate signal is issued; when the blood pressure is not within the standard blood pressure range, an abnormal blood pressure signal is issued; when the blood oxygen concentration is not within the standard blood oxygen concentration range, an abnormal blood oxygen concentration signal is issued.

7. The intelligent nursing condition monitoring system according to claim 4, characterized in that: The calculation expression of the similarity between the feature quantity of the facial image data after the second preprocessing and the standard feature quantity is: Wherein, XS is the similarity between the feature quantity of the facial image data after the second preprocessing and the standard feature quantity, x i is the i-th feature value of the facial image data after the second preprocessing, n is the number of feature values ​​of the facial image data after the second preprocessing, y i is the i-th standard feature quantity.

8. The intelligent nursing condition monitoring system according to claim 5, characterized in that: The alarm light generation logic of the early warning module is as follows: when an abnormal body temperature signal is issued, the early warning module emits a first alarm light of a first brightness and a first color; when an abnormal heart rate signal is issued, the early warning module emits a first alarm light of a second brightness and a second color; when an abnormal pulse signal is issued, the early warning module emits a first alarm light of a third brightness and a third color; when an abnormal respiratory rate signal is issued, the early warning module emits a first alarm light of a fourth brightness and a fourth color; when an abnormal blood pressure signal is issued, the early warning module emits a first alarm light of a fifth brightness and a fifth color; when an abnormal blood oxygen concentration signal is issued, the early warning module emits a first alarm light of a sixth brightness and a sixth color, and transmits the attribute information of the first alarm light to the display module, the attribute information of the first alarm light including the first attribute light color and the first attribute light brightness; When a posture warning signal is generated, the warning module emits a second warning light of the seventh brightness and the seventh color, and transmits attribute information of the second warning light to the display module, wherein the attribute information of the second warning light includes a second attribute light color and a second attribute light brightness.

9. The intelligent nursing condition monitoring system according to claim 1, characterized in that: The display module includes a patient-side display unit and a medical-side display unit. The medical-side display unit is used to display patient emotional information, attribute information of the first alarm light, attribute information of the second alarm light and the corresponding patient number. The patient-side display unit is used to display medical advice.

10. The intelligent nursing condition monitoring system according to claim 9, characterized in that: The logic for generating the medical advice is as follows: receiving the patient's emotional information, the attribute information of the first alarm light, the attribute information of the second alarm light and the corresponding patient number, calling the case database, obtaining the type of disease corresponding to the patient number, calling the expert platform, and the expert generates medical advice for the patient by analyzing the type of disease corresponding to the patient number, the patient's emotional information, the attribute information of the first alarm light and the attribute information of the second alarm light, and the medical advice includes dietary advice and activity advice.

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