Nurse emotion monitoring method and system, storage medium and program product

Abstract

The invention discloses a nurse emotion monitoring method and system, a storage medium and a program product, and relates to the technical field of intelligent wearable device.The nurse emotion monitoring method comprises the steps that heart rate data and blood pressure data of a target nurse are collected through the intelligent wearable device based on the preset collection frequency, the acquisition frequency of the intelligent wearable device in a night time period is higher than that in a day time period, and the night time period and the day time period are defined and determined by a user; determining whether the target nurse has emotional fluctuation or not according to the heart rate data and the blood pressure data through the data processing equipment; if yes, recording a time point when emotion fluctuation occurs; according to at least one time point recorded in the preset period, the psychological state of the target nurse is evaluated, and an emotion monitoring result is obtained. The technical problem that the emotional state of a nurse lacks attention and monitoring is solved.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent wearable devices, and in particular to a nurse emotion monitoring method, a nurse emotion monitoring system, a computer-readable storage medium, and a computer program product. Background Art

[0002] The emotional stability of nurses is an important factor in ensuring the normal operation of the medical system. Nurses also play an extremely important and indispensable role in the development of the medical system. As China's population ages, the shortage of nursing staff has gradually become prominent, and nursing staff are experiencing more and more stress, emotional and psychological problems. At present, most people pay attention to the health of patients, but ignore the emotional abnormalities of medical workers themselves. In particular, there are more women in the nursing industry. In addition to the high-intensity pressure at work, there are also pressures from family and pregnancy. However, there is a lack of relevant smart wearable device products on the market that monitor the emotions and psychological states of nurses themselves, and there is a lack of attention and monitoring of the emotional state of nurses.

[0003] The above information disclosed in this Background section is only for understanding the background of the present application concept and therefore it may contain information that does not constitute prior art. Summary of the invention

[0004] The main purpose of this application is to provide a nurse emotion monitoring method, a nurse emotion monitoring system, a computer-readable storage medium and a computer program product, aiming to solve the technical problem of lack of attention and monitoring of nurses' emotional state.

[0005] To achieve the above objectives, the present application provides a nurse emotion monitoring method, which is applied to a nurse emotion monitoring system. The nurse emotion monitoring system includes at least a smart wearable device and a data processing device. The nurse emotion monitoring method includes:

[0006] Collecting the heart rate data and blood pressure data of the target nurse based on a preset collection frequency through the smart wearable device, and uploading the heart rate data and the blood pressure data to a data processing device, wherein the collection frequency of the smart wearable device in the night time period is higher than the collection frequency in the day time period, and the night time period and the day time period are determined by the user;

[0007] Determining whether the target nurse has emotional fluctuations according to the heart rate data and the blood pressure data by the data processing device;

[0008] If so, record the time when the mood swings occurred;

[0009] According to at least one time point recorded within a preset period, the psychological state of the target nurse is evaluated to obtain an emotion monitoring result.

[0010] In one embodiment, the step of determining whether the target nurse has emotional fluctuations according to the heart rate data and the blood pressure data comprises:

[0011] Inputting the heart rate data and the blood pressure data into a preset emotion analysis model, and predicting the emotion fluctuation result of the target nurse through the emotion analysis model;

[0012] Among them, the heart rate data and the blood pressure data at least include fluctuation amplitude and fluctuation duration, the emotion analysis model is trained by multiple groups of heart rate data and blood pressure data with real labels, and the emotion fluctuation result is one of fluctuation or no fluctuation.

[0013] In one embodiment, the step of evaluating the target nurse's mental state based on at least one time point recorded within a preset period to obtain an emotion monitoring result includes:

[0014] According to the frequency of time points at which emotional fluctuations occur within the preset period, the psychological state of the target nurse is evaluated to obtain an emotional monitoring result;

[0015] The emotion monitoring result at least includes the level of the emotion problem, and the frequency is proportional to the level of the emotion problem.

[0016] In one embodiment, the nurse emotion monitoring method further comprises:

[0017] Collect the target nurse's sleep quality data, number of steps, blood oxygen saturation, and breathing data through the smart wearable device;

[0018] sending the sleep quality data, the number of steps, the blood oxygen saturation and the breathing data to the data processing device;

[0019] The sleep quality data, the number of steps, the blood oxygen saturation, the breathing data and at least one time point of the emotional fluctuation within the preset period are input into a pre-trained emotion type prediction model through the data processing device to determine the emotion type of the target nurse, wherein the emotion type includes at least one of stress type, negative type, anxious type and excited type.

[0020] In one embodiment, after the step of evaluating the target nurse's mental state according to at least one time point recorded within a preset period to obtain an emotion monitoring result, the method further includes:

[0021] According to the emotion monitoring result, determining whether the target nurse has an emotional problem;

[0022] If so, push at least one of the music, video, and course corresponding to the emotion monitoring result to the smart wearable device or mobile communication device of the target nurse;

[0023] Performing voice interaction with the target nurse through a preset intelligent chat robot on the intelligent wearable device or mobile communication device;

[0024] Based on a preset mapping table of emotion types and theme colors, the current theme color of the smart wearable device or the mobile communication device is adjusted to the theme color corresponding to the emotion type of the target nurse.

[0025] In addition, the present application also provides a nurse emotion monitoring system, the nurse emotion monitoring system comprising:

[0026] A smart wearable device, used for collecting heart rate data and blood pressure data of a target nurse based on a preset collection frequency, and sending the heart rate data and the blood pressure data to a data processing device, wherein the collection frequency of the smart wearable device in the nighttime period is higher than that in the daytime period, and the nighttime period and the daytime period are determined by user customization;

[0027] A data processing device is communicatively connected to the smart wearable device, and is used to determine whether the target nurse has emotional fluctuations based on the heart rate data and the blood pressure data; if so, record the time point when the emotional fluctuations occur; and evaluate the psychological state of the target nurse based on at least one time point recorded within a preset period to obtain an emotional monitoring result.

[0028] In one embodiment, the data processing device is also used to input the heart rate data and the blood pressure data into a preset emotion analysis model, and predict the emotion fluctuation result of the target nurse through the emotion analysis model, wherein the emotion analysis model is trained by multiple groups of heart rate data and blood pressure data with real labels, and the emotion fluctuation result is one of fluctuation or no fluctuation; the smart wearable device is also used to collect the sleep quality data, number of steps, blood oxygen saturation, and breathing data of the target nurse, and send the sleep quality data, the number of steps, the blood oxygen saturation, and the breathing data to the data processing device; the data processing device is also used to input the sleep quality data, the number of steps, the blood oxygen saturation, the breathing data, and at least one time point when the emotion fluctuation occurs within the preset period into a pre-trained emotion type prediction model to determine the emotion type of the target nurse, wherein the emotion type includes at least stress type, negative type, irritability type, and excitement type.

[0029] In one embodiment, the nurse emotion monitoring system also includes a mobile communication device, the emotion monitoring result also includes an emotion type, and the data processing device is further used to determine whether the target nurse has an emotional problem based on the emotion monitoring result; the smart wearable device and / or the mobile communication device are also used to play at least one of the music, video, and course corresponding to the emotion monitoring result when an emotional problem exists, and to perform voice interaction with the target nurse through a preset intelligent chat robot on the smart wearable device or the mobile communication device; the smart wearable device and / or the mobile communication device are also used to adjust the current theme color to the theme color corresponding to the emotion type of the target nurse based on a preset mapping table of emotion type and theme color.

[0030] In addition, the present application also provides a nurse emotion monitoring device, which includes at least: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the nurse emotion monitoring method as described above.

[0031] In addition, to achieve the above-mentioned purpose, the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the nurse emotion monitoring method as described above are implemented.

[0032] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned nurse emotion monitoring method when executed by a processor.

[0033] The present application discloses a nurse emotion monitoring method applied to a nurse emotion monitoring system, the nurse emotion monitoring system comprising at least a smart wearable device and a data processing device, the nurse emotion monitoring method comprising: firstly, collecting the heart rate data and blood pressure data of a target nurse based on a preset collection frequency through the smart wearable device, and uploading the heart rate data and the blood pressure data to the data processing device, wherein the collection frequency of the smart wearable device during the night time period is higher than that during the day time period, the night time period and the day time period are user-defined, and the different collection frequencies during the day time period and the night time period can better adapt to the scenario where the nurse group often works at night, because in the scenario of working at night, the nurse's emotion is more likely to have problems, so through a higher collection frequency, the target nurse's emotion during the night time period is increased. The target nurse's emotional state is paid attention to and the mental health of the nurse is protected. Then, the data processing device determines whether the target nurse has emotional fluctuations according to the heart rate data and the blood pressure data. If so, the time point of the emotional fluctuation is recorded. According to at least one time point recorded within a preset period, the mental state of the target nurse is evaluated to obtain the emotional monitoring result. The present application evaluates the state of the target nurse by collecting the time points of emotional fluctuations within a period, thereby avoiding the error of evaluating emotions only through short-term vital sign data. The emotional state of the nurse is reflected according to the vital sign data of the emotional fluctuation time points recorded by the nurse within the preset period, thereby realizing all-weather and comprehensive monitoring of the emotional state of the nurse, which is conducive to timely discovering the emotional problems of nurses and provides a strong data foundation for maintaining the mental health and emotional state of the nurse group. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 This is a flow chart of an embodiment of a method for monitoring nurse emotions in an embodiment of the present application;

[0037] Figure 2 A schematic diagram of a process of analyzing the vital sign data of a target nurse to determine a corresponding emotion type in an embodiment of the present application;

[0038] Figure 3 This is a schematic diagram of the process of emotional intervention for a target nurse in an embodiment of the present application;

[0039] Figure 4 A schematic diagram of the structure of a feasible nurse emotion monitoring system in an embodiment of the present application;

[0040] Figure 5 Schematic diagram of the device structure of the hardware operating environment of the nurse emotion monitoring device involved in the nurse emotion monitoring method in the embodiment of the present application.

[0041] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0042] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of this application.

[0043] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0044] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0045] Nursing workers are facing more and more stress and professional emotional problems. At present, people mostly focus on the health problems of patients, but ignore the emotional and psychological problems of medical workers. In particular, there are more women in the nursing industry. In addition to the high-intensity pressure at work, there are also pressures such as family and pregnancy. Therefore, the purpose of this application is to pay attention to the emotions and psychological state of nurses themselves, and to improve the psychological pressure and emotional state of nurses through intervention devices (bracelets, mobile phones, etc.), and remind nurses to pay attention to their own emotional problems.

[0046] In order to achieve the above-mentioned objectives, an embodiment of the present application provides a nurse emotion monitoring method applied to a nurse emotion monitoring system. The nurse emotion monitoring system includes at least a smart wearable device and a data processing device, which are used to collect the vital signs data of the target nurse and further process and analyze these vital signs data to determine the corresponding emotion monitoring results.

[0047] Reference Figure 1 , Figure 1 This is a flow chart of an embodiment of the nurse emotion monitoring method of the present application, and the nurse emotion monitoring method includes:

[0048] Step S10, collecting the heart rate data and blood pressure data of the target nurse based on a preset collection frequency through the smart wearable device, and uploading the heart rate data and blood pressure data to the data processing device, wherein the collection frequency of the smart wearable device in the night time period is higher than the collection frequency in the day time period, and the night time period and the day time period are determined by the user;

[0049] Wherein, the smart wearable device can be a bracelet, and the target nurse is an individual nurse who needs to be monitored for emotions. After the target nurse wears the bracelet on her wrist, the bracelet can automatically collect her heart rate data and blood pressure data based on a preset collection frequency, and upload it to a data processing device, wherein the data processing device can be a cloud device or server. It can be understood that under normal circumstances, the bracelet is connected to a mobile communication device (such as a mobile phone) via Bluetooth. When it is necessary to upload heart rate data and blood pressure data, the mobile phone can be used as a transfer, and the heart rate data and blood pressure data can be uploaded to the cloud device with the help of the wireless communication capability of the mobile phone, so as to use the cloud device to use its computing power resources for further analysis and processing. It should be noted that the heart rate data and blood pressure data collected by the smart wearable device are data within a period of time, such as heart rate data and blood pressure data within the last 1min, 2min or 5min, and are recorded in the form of a waveform.

[0050] Since the user group mainly targeted by the nurse emotion monitoring method and nurse emotion monitoring system of the embodiment of the present application is nurses, considering the professional attributes of nurses, there are more cases of night shifts. Therefore, unlike ordinary users, the acquisition frequency of the smart wearable device during the night period needs to be higher than the acquisition frequency during the day period. This is because the working attributes of the night shift easily make nurses more prone to emotional problems, so a higher acquisition frequency is required to achieve more detailed and comprehensive emotion monitoring during the night period. Moreover, the starting time point and the ending time point of the night period and the day period can be customized by the user or the target nurse according to the actual work situation. For example, the day period is the time period from 6 am to 6 pm, and the night period is the time period from 6 pm to 6 am.

[0051] Step S20, determining whether the target nurse has emotional fluctuations according to the heart rate data and blood pressure data by a data processing device;

[0052] After the data processing device receives the heart rate data and blood pressure data uploaded by the smart wearable device, it further analyzes these heart rate data and blood pressure data to determine whether the target nurse has experienced emotional fluctuations, where emotional fluctuations can be understood as relatively large fluctuations in emotions. For example, under high-intensity work and high pressure, heart rate and blood pressure will rise, which can be understood as emotional fluctuations. Of course, there will also be cases where the heart rate and blood pressure rise briefly or slightly, which can be identified as normal fluctuations and are not determined to be emotional fluctuations. Therefore, in the process of judging whether the target nurse has experienced emotional fluctuations based on the heart rate data and blood pressure data, the fluctuation amplitude and fluctuation duration corresponding to the heart rate data and blood pressure data can be specifically analyzed based on the pre-established experience knowledge base or threshold, so as to determine whether the target nurse has experienced emotional fluctuations.

[0053] Step S30: If yes, then record the time point when the emotional fluctuation occurs.

[0054] Each time when the target nurse is determined to have an emotional fluctuation, the time point of the emotional fluctuation and the corresponding heart rate data and blood pressure data are recorded by the data processing equipment, so as to be used as the data basis for subsequent evaluation of the target nurse's mental state.

[0055] On the other hand, if there is no emotional fluctuation, this part of the heart rate data and blood pressure data is skipped and does not need to be recorded.

[0056] Step S40, evaluating the psychological state of the target nurse according to at least one time point recorded within a preset period, and obtaining an emotion monitoring result.

[0057] After the target nurse's heart rate data and blood pressure data are collected through smart wearable devices, as well as the time points of emotional fluctuations recorded for a certain period (e.g., one week), the target nurse's mental state can be evaluated through data processing equipment based on the recorded data about emotional fluctuations. The emotional monitoring results are qualitative descriptions of the target nurse's mental state, such as stability, emotional problems (which can be divided into a variety of different levels of problems, the higher the level, the more serious the emotional problems), and the type of emotional problems that the target nurse has can also be determined, so as to facilitate targeted intervention and protect the mental health of the nurse group.

[0058] The embodiment of the present application discloses a nurse emotion monitoring method applied to a nurse emotion monitoring system, the nurse emotion monitoring system comprising at least a smart wearable device and a data processing device, the nurse emotion monitoring method comprising: firstly, collecting the heart rate data and blood pressure data of the target nurse based on a preset collection frequency through the smart wearable device, and uploading the heart rate data and the blood pressure data to the data processing device, wherein the collection frequency of the smart wearable device during the night time period is higher than that during the day time period, the night time period and the day time period are user-defined, and the different collection frequencies during the day time period and the night time period can better adapt to the scenario where the nurse group often works at night, because in the scenario of working at night, the nurse's emotion is more likely to have problems, so through a higher collection frequency, the target nurse's emotion during the night time period is increased. The target nurse's mood is paid attention to and the mental health of the nurse is protected. Then, the data processing device determines whether the target nurse has mood fluctuations according to the heart rate data and the blood pressure data. If so, the time point of the mood fluctuation is recorded. According to at least one time point recorded within a preset period, the mental state of the target nurse is evaluated to obtain the mood monitoring result. The embodiment of the present application evaluates the state of the target nurse by collecting the time points of mood fluctuations within a period, thereby avoiding the error of evaluating emotions only through short-term vital sign data. The emotional state of the nurse is reflected according to the vital sign data of the mood fluctuation time points recorded by the nurse within the preset period, thereby realizing all-weather and comprehensive monitoring of the emotional state of the nurse, which is conducive to timely discovering the emotional problems of nurses and provides a strong data foundation for maintaining the mental health and emotional state of the nurse group.

[0059] Further, in a feasible embodiment, the step of determining whether the target nurse has emotional fluctuations according to the heart rate data and the blood pressure data includes:

[0060] Step S21, inputting the heart rate data and blood pressure data into a preset emotion analysis model, and predicting the emotion fluctuation results of the target nurse through the emotion analysis model;

[0061] Among them, the heart rate data and the blood pressure data at least include fluctuation amplitude and fluctuation duration, the emotion analysis model is trained by multiple groups of heart rate data and blood pressure data with real labels, and the emotion fluctuation result is one of fluctuation or no fluctuation.

[0062] An embodiment of the present application provides a method for determining the emotional fluctuation results of a target nurse based on the fluctuation amplitude and fluctuation duration of collected heart rate data and blood pressure data, that is, determining whether the target nurse has experienced emotional fluctuations. That is, a pre-trained emotion analysis model is used to process the input heart rate data and blood pressure data, so as to predict whether the target nurse has experienced emotional fluctuations at the time point corresponding to the heart rate data and blood pressure data.

[0063] The emotion analysis model can be a machine learning model with a multi-layer neural network structure, which is pre-trained with a large amount of heart rate data and blood pressure data with real labels, so that the model can learn the features in the heart rate data and blood pressure data, thereby predicting the corresponding emotion fluctuation results. The real label refers to one of the occurrence of emotion fluctuations and the absence of emotion fluctuations. The heart rate data and blood pressure data of multiple testers in the case of emotion fluctuations and no emotion fluctuations are collected in advance as a training set to train the robot learning model. The finally obtained emotion analysis model can accurately predict whether the target nurse has an emotion fluctuation based on the fluctuation amplitude and fluctuation duration of the newly input heart rate data and blood pressure data.

[0064] Furthermore, in a feasible embodiment, the step of evaluating the psychological state of the target nurse according to at least one time point recorded within a preset period to obtain an emotion monitoring result includes:

[0065] Step S41, evaluating the psychological state of the target nurse according to the frequency of time points at which emotional fluctuations occur within a preset period, and obtaining an emotional monitoring result;

[0066] The emotion monitoring result at least includes the level of the emotion problem, and the frequency is proportional to the level of the emotion problem.

[0067] The embodiment of the present application provides a method for evaluating the psychological state of a target nurse and determining an emotion monitoring result after completing a cycle of data collection. The emotion monitoring result may be the level of an emotion problem. According to a preset psychological state evaluation rule, the level of the emotion problem corresponding to the emotion monitoring result may be divided into none, low, medium, and high. "None" means that the target nurse has no emotion problem, and "low, medium, and high" respectively indicate that the target nurse has emotion problems of different severity.

[0068] In the technical solution of the present application, the frequency of the time points at which emotional fluctuations occur is used as the basis for determining emotional problems. The higher the frequency of emotional fluctuations of the target nurse within a preset period, the more serious the emotional problem. In addition, the level of the corresponding emotional problem is determined according to the frequency of emotional fluctuations. It can be determined based on a predetermined mapping relationship between the frequency of emotional fluctuations and the level of emotional problems. The mapping relationship can be determined through a user survey or field experiment conducted in advance. For example, the frequency of emotional fluctuations occurring in a large user group within a preset period can be collected, and combined with the level of emotional problems reflected by the questionnaires filled out by these user groups, a comprehensive consideration is made, and finally the mapping relationship between the frequency of emotional fluctuations and the level of emotional problems is determined.

[0069] In another feasible embodiment, in addition to determining the corresponding emotion monitoring results based on the frequency of emotional fluctuations, the level of the corresponding emotional problem can also be determined based on the fluctuation amplitude and duration of the heart rate data and blood pressure data each time the emotional fluctuation occurs, and the fluctuation amplitude and duration are both proportional to the level of the emotional problem.

[0070] In one possible embodiment, referring to Figure 2 , the nurse emotion monitoring method further comprises:

[0071] Step A10, collecting the target nurse's sleep quality data, number of steps, blood oxygen saturation, and respiratory data through the smart wearable device;

[0072] Step A20, sending the sleep quality data, number of steps, blood oxygen saturation and respiration data to a data processing device;

[0073] Step A30, input the sleep quality data, number of steps, blood oxygen saturation, breathing data and at least one time point of emotional fluctuations within a preset period into a pre-trained emotion type prediction model through a data processing device to determine the emotion type of the target nurse, wherein the emotion type includes at least one of stress type, negative type, anxious type and excited type.

[0074] In the technical solution of the embodiment of the present application, in addition to collecting the target nurse's blood pressure data and heart rate data, the smart wearable device can also collect the target nurse's sleep quality data, step count, blood oxygen saturation and breathing data, wherein the sleep quality data includes the sleep duration and the duration corresponding to deep sleep and sleep respectively, and the breathing data includes the breathing frequency and the breathing frequency per minute. The above vital signs data can also reflect the psychological state of the target nurse to a certain extent. For example, when the sleep quality data reflects that the target nurse's sleep quality is poor, it means that the target nurse's emotional problems are more serious at that time, and there is a lot of pressure, anxiety or emotional excitement; too high a step count may reflect that the target nurse is under great work pressure, and too low a step count may reflect that the target nurse has a negative and depressed psychological state; too low blood oxygen saturation or too high a breathing rate also reflects that the target nurse has certain emotional problems.

[0075] In the embodiment of the present application, after the above vital sign data is collected by the smart wearable device, it is uploaded to the data processing device. The data processing device can determine the specific emotional type of the target nurse based on these vital sign data, the collected blood pressure data and heart rate data, and the pre-trained emotional type prediction model, wherein the target nurse's emotional type can include only one or multiple types. The emotional type prediction model can be a neural network model trained by pre-collected multi-dimensional vital sign data of a large number of users, which can identify the user's emotional type characteristics from the input multi-dimensional vital sign data, thereby determining the target nurse's emotional type. Among them, the stress type refers to the emotional state of the nurse when facing pressure from work, family or other aspects, the negative type refers to the emotional state of the nurse when she loses confidence and motivation in work and life, the restless type refers to the emotional state of the nurse in a restless or anxious state, and the excited type refers to the emotional state of the nurse in a relatively excited and impulsive state for something. In actual application scenarios, other types of emotional types can also be set according to actual conditions, or the emotional types can be further subdivided to adapt to different application scenarios and improve the effect of emotional monitoring.

[0076] In the embodiment of the present application, the emotional problems of the target nurses are further subdivided and specific emotional types are determined, so as to facilitate targeted and personalized intervention measures for emotional problems of different emotional types and maintain the mental health of the nurse group.

[0077] Further, after the step of evaluating the psychological state of the target nurse according to at least one time point recorded within the preset period to obtain the emotion monitoring result, referring to Figure 3 , the method further comprises:

[0078] Step S50, judging whether the target nurse has emotional problems according to the emotion monitoring results;

[0079] Step S60: If yes, at least one of the music, video and course corresponding to the emotion monitoring result is pushed to the smart wearable device or mobile communication device of the target nurse;

[0080] Step S70, voice interaction with the target nurse is performed through a preset intelligent chat robot on the intelligent wearable device or mobile communication device;

[0081] Step S80: Based on a preset mapping table of emotion types and theme colors, the current theme color of the smart wearable device or mobile communication device is adjusted to a theme color corresponding to the emotion type of the target nurse.

[0082] In order to maintain a good emotional state of the nurse group, when the emotion monitoring results meet certain intervention conditions (i.e., there are emotional problems), certain emotional intervention measures need to be taken to eliminate and solve emotional problems for nurses and ensure the positive working state of the nurse group. Step S60, step S70, and step S80 are three independent emotional intervention measures that can be implemented simultaneously to alleviate and solve the emotional problems of the target users. If the target nurse does not have emotional problems, no intervention measures are required.

[0083] First, the condition for taking intervention measures may be that the target nurse has emotional problems. When the emotion monitoring results indicate that the target nurse has emotional problems, that is, the level of the emotional problem is not "none", it is determined that the emotion monitoring results meet the preset intervention conditions.

[0084] Specifically, when the target user has emotional problems, preset music, videos, courses, etc. for alleviating emotional problems can be pushed to the target nurse's corresponding smart wearable device or mobile communication device (such as a mobile phone or tablet). Specifically, the mobile phone is installed with a corresponding APP (Application), which is used to display the life feature data received from the bracelet and the control data sent from the cloud, including music, videos, courses, etc. Among them, the music can be light music, white noise, etc., which are used to relieve stress and irritability. The video can be a pre-set decompression video, a video telling a spiritual story, a video of beautiful scenery, or a healing style video, etc. The course can be a text, audio, or video produced by a professional psychological counselor to teach how to relieve emotional stress. In addition, different emotional intervention methods are used for different emotional monitoring results, that is, different levels of emotional problems. For example, for low-level emotional problems, soothing music and decompression tips in text form can be pushed; for mid-level emotional problems, decompression videos and audio decompression course teaching are added on the basis of the aforementioned intervention methods; for high-level emotional problems, decompression course teaching in video form is added on the basis of the aforementioned intervention methods, and a reminder message is sent to the management account bound to the target nurse's account, such as the target nurse's superior, so that the superior can pay attention to the target nurse's emotional state in a timely manner, pay special attention to it, and take measures such as conversations and vacations to solve the target nurse's emotional problems.

[0085] In addition, when the target nurse has emotional problems, the target nurse can also be interacted with by voice through the intelligent chat robot pre-installed on the smart wearable device (such as a bracelet) and the mobile communication device (such as a mobile phone), that is, the intelligent chat robot can be a voice assistant trained based on the currently commonly used large language model. When it is determined that the target nurse has emotional problems, the intelligent chat robot can adaptively make a chat request based on the level and type of emotional problems in the emotional monitoring results, and interact with the target nurse by voice, enlighten the target nurse, provide reliable and effective suggestions for solving the problem, soothe the target nurse's mood, and ensure that the target nurse is in a positive and positive working state.

[0086] In addition, the emotional problems of the target users can be alleviated by adjusting the theme colors of the target nurses' smart wearable devices (bracelets with display screens) and mobile communication devices (mobile phones). Since color works through human vision, different colors emit different wavelengths of light. When the human eye is exposed to different colors, the brain nerves will make different associations and reactions. Therefore, color has a direct impact on human psychology. Among them, the mapping table of preset emotion types and theme colors indicates that different theme colors can be used when intervening in different emotion types. For example, green can make people feel stable and comfortable, and has the effects of calming nerves, reducing intraocular pressure, relieving eye fatigue, and improving muscle movement ability. Moreover, natural green has a certain soothing effect on fainting, fatigue, nausea and negative emotions, and can be used to intervene in the emotional state of target nurses with stress, anxiety, excitement and negative emotional problems; blue can make people focus and concentrate more easily, which is related to the fact that blue can suppress the excitement of the brain and calm people down, corresponding to anxiety and excitement emotional problems; orange can produce vitality and induce appetite. It is a representative color in the warm color system and also a color representing health. Red is a more stimulating color that will stimulate and excite the nervous system, increase adrenaline secretion and enhance blood circulation. These two colors correspond to negative emotional problems. It should be noted that in actual application scenarios, the theme color can include more than one color. In order to achieve a better visual effect, two or more colors with pre-adjusted numbers can be used as the theme colors of the bracelet and mobile phone to intervene in the emotions of the target nurses from the perspective of visual color and alleviate the nurses' emotional problems.

[0087] It should be noted that this example is only used to assist in understanding the present application and does not constitute a limitation on the nurse emotion monitoring method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0088] The embodiment of the present application also provides a nurse emotion monitoring system, the nurse emotion monitoring system at least comprising:

[0089] A smart wearable device, used for collecting heart rate data and blood pressure data of a target nurse based on a preset collection frequency, and sending the heart rate data and the blood pressure data to a data processing device, wherein the collection frequency of the smart wearable device in the nighttime period is higher than that in the daytime period, and the nighttime period and the daytime period are determined by user customization;

[0090] A data processing device is communicatively connected to the smart wearable device, and is used to determine whether the target nurse has emotional fluctuations based on the heart rate data and the blood pressure data; if so, record the time point when the emotional fluctuations occur; and evaluate the psychological state of the target nurse based on at least one time point recorded within a preset period to obtain an emotional monitoring result.

[0091] The smart wearable device may be a wristband, and the data processing device may be a cloud device. In a feasible embodiment, Figure 4 As shown in the figure, the nurse emotion monitoring system includes three parts: a bracelet, a mobile phone, and a cloud device. After the bracelet collects the vital signs data of the target nurse (including heart rate data, blood pressure data, etc.), it can upload the data to the cloud device through a mobile communication device (such as a mobile phone) that has established a Bluetooth connection with the bracelet for emotion monitoring. Similarly, the cloud device can also send corresponding control instructions to the bracelet via the mobile phone or push relevant data for intervention in the nurse's emotional problems.

[0092] In a feasible embodiment, the data processing device is also used to input the heart rate data and the blood pressure data into a preset emotion analysis model, and predict the emotion fluctuation result of the target nurse through the emotion analysis model, wherein the emotion analysis model is trained by multiple groups of heart rate data and blood pressure data with real labels, and the emotion fluctuation result is one of fluctuation or no fluctuation; the smart wearable device is also used to collect the sleep quality data, number of steps, blood oxygen saturation, and breathing data of the target nurse, and send the sleep quality data, the number of steps, the blood oxygen saturation, and the breathing data to the data processing device; the data processing device is also used to input the sleep quality data, the number of steps, the blood oxygen saturation, the breathing data, and at least one time point of the emotion fluctuation within the preset period into a pre-trained emotion type prediction model to determine the emotion type of the target nurse, wherein the emotion type includes at least stress type, negative type, irritability type, and excitement type.

[0093] In a feasible embodiment, the nurse emotion monitoring system also includes a mobile communication device, the emotion monitoring result also includes an emotion type, and the data processing device is also used to determine whether the target nurse has an emotional problem based on the emotion monitoring result; the smart wearable device and / or the mobile communication device are also used to play at least one of the music, video, and course corresponding to the emotion monitoring result when an emotional problem exists, and to perform voice interaction with the target nurse through a preset intelligent chat robot on the smart wearable device or the mobile communication device; the smart wearable device and / or the mobile communication device are also used to adjust the current theme color to the theme color corresponding to the emotion type of the target nurse based on a preset mapping table of emotion type and theme color.

[0094] The nurse emotion monitoring system provided in the embodiment of the present application adopts the nurse emotion monitoring method in the above embodiment, which can solve the technical problem of lack of attention and monitoring of the nurse's emotional state. Compared with the prior art, the beneficial effects of the nurse emotion monitoring system provided in the embodiment of the present application are the same as the beneficial effects of the nurse emotion monitoring method provided in the above embodiment, and other technical features in the nurse emotion monitoring system are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0095] An embodiment of the present application also provides a nurse emotion monitoring device. For example, the nurse emotion monitoring device can be a smart wearable device, a data processing device or a mobile communication device. The nurse emotion monitoring device includes at least: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor so that the at least one processor can execute the nurse emotion monitoring method in the above embodiment.

[0096] Reference below Figure 5 , which shows a structural schematic diagram of a nurse emotion monitoring device suitable for implementing an embodiment of the present application. Figure 5 The nurse emotion monitoring device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0097] like Figure 5As shown, the nurse emotion monitoring device may include a processing device 101 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 102 or a program loaded from a storage device 103 to a random access memory (RAM: Random Access Memory) 104. In RAM104, various programs and data required for the operation of the nurse emotion monitoring device are also stored. The processing device 101, ROM102, and RAM104 are connected to each other through a bus 105. An input / output (I / O) interface 106 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 106: an input device 107 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 108 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 103 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 109. The communication device 109 can allow the nurse mood monitoring device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a nurse mood monitoring device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0098] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 103, or installed from a ROM 102. When the computer program is executed by the processing device 101, the above-mentioned functions defined in the method of the embodiment of the present application are executed.

[0099] The nurse emotion monitoring device provided in the embodiment of the present application adopts the nurse emotion monitoring method in the above embodiment, which can solve the technical problem of lack of attention and monitoring of the nurse's emotional state. Compared with the prior art, the beneficial effects of the nurse emotion monitoring device provided in the embodiment of the present application are the same as the beneficial effects of the nurse emotion monitoring method provided in the above embodiment, and the other technical features in the nurse emotion monitoring device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0100] It should be understood that each part of the embodiments of the present application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0101] The above is only a specific implementation of the embodiment of the present application, but the protection scope of the embodiment of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the embodiment of the present application. Therefore, the protection scope of the embodiment of the present application shall be based on the protection scope of the above claims.

[0102] An embodiment of the present application also provides a computer-readable storage medium storing a computer program executable on a processor, wherein the computer program is used to execute the nurse emotion monitoring method in the above embodiment.

[0103] The computer-readable storage medium provided in the embodiment of the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0104] The computer-readable storage medium may be included in the nurse emotion monitoring device; or may exist independently without being assembled into the nurse emotion monitoring device.

[0105] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the nurse emotion monitoring device, the nurse emotion monitoring device executes: collecting heart rate data and blood pressure data of the target nurse based on a preset collection frequency, and uploading the heart rate data and the blood pressure data to a data processing device, wherein the collection frequency of the smart wearable device in the night time period is higher than the collection frequency in the day time period, and the night time period and the day time period are determined by the user;

[0106] Or execute: determine whether the target nurse has emotional fluctuations based on the heart rate data and the blood pressure data; if so, record the time point when the emotional fluctuations occur; evaluate the psychological state of the target nurse based on at least one time point recorded within a preset period to obtain an emotional monitoring result.

[0107] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0108] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0109] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0110] The computer-readable storage medium provided in the embodiment of the present application stores computer-readable program instructions for executing the above-mentioned nurse emotion monitoring method, which can solve the technical problem of lack of attention and monitoring of the nurse's emotional state. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the embodiment of the present application are the same as the beneficial effects of the nurse emotion monitoring method provided in the above-mentioned embodiment, and will not be repeated here.

[0111] An embodiment of the present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned nurse emotion monitoring method when executed by a processor.

[0112] The computer program product provided in the embodiment of the present application can solve the technical problem of lack of attention and monitoring of the nurse's emotional state. Compared with the prior art, the beneficial effects of the computer program product provided in the embodiment of the present application are the same as the beneficial effects of the nurse emotion monitoring method provided in the above embodiment, which will not be repeated here.

[0113] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A method for monitoring nurse emotions, characterized in that: Applied to a nurse emotion monitoring system, the nurse emotion monitoring system at least includes a smart wearable device and a data processing device, and the nurse emotion monitoring method includes: Collecting the heart rate data and blood pressure data of the target nurse based on a preset collection frequency through the smart wearable device, and uploading the heart rate data and the blood pressure data to a data processing device, wherein the collection frequency of the smart wearable device in the night time period is higher than the collection frequency in the day time period, and the night time period and the day time period are determined by the user; Determining whether the target nurse has emotional fluctuations according to the heart rate data and the blood pressure data by the data processing device; If so, record the time when the mood swings occurred; According to at least one time point recorded within a preset period, the psychological state of the target nurse is evaluated to obtain an emotion monitoring result.

2. The nurse emotion monitoring method according to claim 1, characterized in that: The step of determining whether the target nurse has emotional fluctuations according to the heart rate data and the blood pressure data comprises: Inputting the heart rate data and the blood pressure data into a preset emotion analysis model, and predicting the emotion fluctuation result of the target nurse through the emotion analysis model; Among them, the heart rate data and the blood pressure data at least include fluctuation amplitude and fluctuation duration, the emotion analysis model is trained by multiple groups of heart rate data and blood pressure data with real labels, and the emotion fluctuation result is one of fluctuation or no fluctuation.

3. The nurse emotion monitoring method according to claim 2, characterized in that: The step of evaluating the psychological state of the target nurse according to at least one time point recorded within a preset period to obtain an emotion monitoring result includes: According to the frequency of time points at which emotional fluctuations occur within the preset period, the psychological state of the target nurse is evaluated to obtain an emotional monitoring result; The emotion monitoring result at least includes the level of the emotion problem, and the frequency is proportional to the level of the emotion problem.

4. The nurse emotion monitoring method according to claim 1, characterized in that: The nurse emotion monitoring method further comprises: Collect the target nurse's sleep quality data, number of steps, blood oxygen saturation, and breathing data through the smart wearable device; sending the sleep quality data, the number of steps, the blood oxygen saturation and the breathing data to the data processing device; The sleep quality data, the number of steps, the blood oxygen saturation, the breathing data and at least one time point of the emotional fluctuation within the preset period are input into a pre-trained emotion type prediction model through the data processing device to determine the emotional type of the target nurse, wherein the emotional type includes at least one of stress type, negative type, anxious type and excited type.

5. The nurse emotion monitoring method according to claim 4, characterized in that: After the step of evaluating the psychological state of the target nurse according to at least one time point recorded within a preset period to obtain an emotion monitoring result, the method further includes: According to the emotion monitoring result, determining whether the target nurse has an emotional problem; If so, push at least one of the music, video, and course corresponding to the emotion monitoring result to the smart wearable device or mobile communication device of the target nurse; Performing voice interaction with the target nurse through a preset intelligent chat robot on the intelligent wearable device or mobile communication device; Based on a preset mapping table of emotion types and theme colors, the current theme color of the smart wearable device or the mobile communication device is adjusted to the theme color corresponding to the emotion type of the target nurse.

6. A nurse emotion monitoring system, characterized in that: The nurse emotion monitoring system comprises: A smart wearable device, used for collecting heart rate data and blood pressure data of a target nurse based on a preset collection frequency, and sending the heart rate data and the blood pressure data to a data processing device, wherein the collection frequency of the smart wearable device in the nighttime period is higher than that in the daytime period, and the nighttime period and the daytime period are determined by user customization; A data processing device is communicatively connected to the smart wearable device, and is used to determine whether the target nurse has emotional fluctuations based on the heart rate data and the blood pressure data; if so, record the time point when the emotional fluctuations occur; and evaluate the psychological state of the target nurse based on at least one time point recorded within a preset period to obtain an emotional monitoring result.

7. The nurse emotion monitoring system according to claim 6, characterized in that: The data processing device is also used to input the heart rate data and the blood pressure data into a preset emotion analysis model, and predict the emotion fluctuation result of the target nurse through the emotion analysis model, wherein the emotion analysis model is trained by multiple groups of heart rate data and blood pressure data with real labels, and the emotion fluctuation result is one of fluctuation or no fluctuation; the smart wearable device is also used to collect the sleep quality data, number of steps, blood oxygen saturation, and breathing data of the target nurse, and send the sleep quality data, the number of steps, the blood oxygen saturation, and the breathing data to the data processing device; the data processing device is also used to input the sleep quality data, the number of steps, the blood oxygen saturation, the breathing data, and at least one time point when the emotion fluctuation occurs within the preset period into a pre-trained emotion type prediction model to determine the emotion type of the target nurse, wherein the emotion type includes at least stress type, negative type, irritability type, and excitement type.

8. The nurse emotion monitoring system according to claim 7, characterized in that: The nurse emotion monitoring system also includes a mobile communication device, and the emotion monitoring result also includes an emotion type. The data processing device is also used to determine whether the target nurse has an emotional problem based on the emotion monitoring result; the smart wearable device and / or the mobile communication device are also used to play at least one of the music, video, and course corresponding to the emotion monitoring result when an emotional problem exists, and to perform voice interaction with the target nurse through a preset intelligent chat robot on the smart wearable device or the mobile communication device; the smart wearable device and / or the mobile communication device are also used to adjust the current theme color to the theme color corresponding to the emotion type of the target nurse based on a preset mapping table of emotion type and theme color.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which is stored a program for implementing the nurse emotion monitoring method. The program for implementing the nurse emotion monitoring method is executed by a processor to implement the steps of the nurse emotion monitoring method as described in any one of claims 1 to 5.

10. A program product, characterized in that The program product is a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the nurse emotion monitoring method according to any one of claims 1 to 5 are implemented.

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