Emergency call method, system and device for abnormal state of user

Abstract

The invention provides an emergency call method, system and device for a user in an abnormal state, and the method comprises the steps: obtaining the body detection information, behavior detection information and positioning change information of a patient, recognizing the current body state and current behavior information of the patient, and based on the current behavior information of the patient, carrying out the recognition of the current behavior information of the patient through a form recognition network, analyzing the critical behavior information of the patient; analyzing positioning abnormal information of the patient based on the positioning change information of the patient, and identifying a current abnormal state of the patient through an abnormal state analysis network based on the current physical state of the patient, the critical behavior information of the patient and the positioning abnormal information of the patient; and based on the current abnormal state of the patient, generating abnormal distress call information of the patient, and sending the abnormal distress call information to a medical staff client. By adopting the scheme, the medical staff contact efficiency can be improved when the patient is in the sudden abnormal state.

Description

Technical Field

[0001] The present invention relates to the technical field of abnormal state analysis and emergency rescue, and in particular to an emergency rescue method, system and device for a user in an abnormal state. Background Art

[0002] When elderly people or children are alone in hospital wards, their illnesses often cause them to have more inconveniences in their normal actions, especially when going to the toilet, walking, squatting, or getting emotional, which often leads to sudden abnormal conditions that require medical staff to rush to the scene for emergency treatment. However, when patients are alone in the ward, their abnormal conditions make it impossible for them to contact or assist in contacting medical staff in time, resulting in delayed treatment of patients in sudden abnormal conditions, which may lead to the death of the patients or serious illness. Therefore, how to improve patients' emergency contact or assist patients in contacting medical staff in emergencies is the current focus of medical care security research.

[0003] The traditional way to assist patients in contacting medical staff in an emergency is to set an emergency call button on the patient's clothing or a portable bracelet, so as to ensure that the patient can contact the medical staff in an emergency. However, when an abnormal state occurs, the patient may not have time or lose consciousness and cannot contact the medical staff in an emergency, resulting in low efficiency in contacting the medical staff when the patient is in an abnormal state. Summary of the invention

[0004] The main purpose of the present invention is to provide an emergency call method, system and device for a user in an abnormal state, aiming to solve the problem of low efficiency in contacting medical staff when the patient is in an abnormal state, because the patient may not have time or lose consciousness in the event of an emergency, resulting in low efficiency in contacting medical staff when the patient is in an abnormal state.

[0005] To achieve the above object, the present invention provides an emergency call method for a user in an abnormal state, the method comprising:

[0006] Acquire the patient's physical detection information, the patient's behavior detection information, and the patient's position change information, and identify the patient's current physical state based on the patient's physical detection information;

[0007] Based on the behavior detection information of the patient, identifying the current behavior information of the patient, and based on the current behavior information of the patient, analyzing the critical behavior information of the patient through a morphology recognition network;

[0008] Based on the positioning change information of the patient, analyzing the positioning abnormality information of the patient, and based on the current physical state of the patient, the critical behavior information of the patient, and the positioning abnormality information of the patient, identifying the current abnormal state of the patient through an abnormal state analysis network;

[0009] Based on the current abnormal state of the patient, abnormal distress information of the patient is generated, and the abnormal distress information is sent to a medical staff client.

[0010] Optionally, the identifying the current physical condition of the patient based on the physical detection information of the patient includes:

[0011] Splitting the body detection information into detection data of each body detection type, and performing data distribution processing on each detection data to obtain detection data distribution information;

[0012] Based on the detection data distribution information, identifying the data distribution range of the detection type and the data distribution trend of the detection type, and based on the data distribution range of the detection type and the data distribution trend of the detection type, identifying the sub-body state corresponding to the detection type through the state recognition strategy of the detection type;

[0013] The sub-physical states corresponding to all detection types are taken as the current physical state of the patient.

[0014] Optionally, the identifying the current behavior information of the patient based on the behavior detection information of the patient includes:

[0015] Based on the patient's behavior monitoring information, identifying the patient's body vibration monitoring information and the patient's behavior duration information, and based on the patient's body vibration monitoring information, identifying the patient's body vibration amplitude and the body vibration intensity endured by the patient;

[0016] Based on the behavior duration information of the patient, the duration of the patient's behavior and the current behavior content of the patient are identified, and based on the body vibration amplitude of the patient and the body vibration intensity endured by the patient, the abnormal body vibration information of the patient is identified through a vibration analysis strategy;

[0017] Based on the duration of the patient's behavior and the current content of the patient's behavior, the patient's abnormal behavior information is identified through a behavior abnormality analysis strategy, and the patient's abnormal body vibration information and the patient's abnormal behavior information are used as the patient's current behavior information.

[0018] Optionally, the morphology recognition network includes a vibration analysis network and a behavior analysis network, and the analyzing the critical behavior information of the patient through the morphology recognition network based on the current behavior information of the patient includes:

[0019] Based on the abnormal body vibration information of the patient, analyzing the cause of the patient's body vibration through the vibration analysis network, and based on the abnormal behavior information of the patient, identifying the abnormal behavior type of the patient through the behavior analysis network;

[0020] In the abnormal behavior database, query each initial critical behavior information including the cause of the body vibration and the type of abnormal behavior, and based on the duration of the patient's behavior and the amplitude of the patient's body vibration, filter the critical behavior information corresponding to the patient in each initial critical behavior information.

[0021] Optionally, analyzing the abnormal positioning information of the patient based on the positioning change information of the patient includes:

[0022] Arrange the patient's location change information in chronological order to generate the patient's movement trajectory and the patient's movement area, and query the patient's movement types in the movement area in the patient's historical movement database based on the patient's movement area;

[0023] Based on the motion trajectory of the patient and the historical motion trajectory of the patient in each motion type, the motion trajectory adapted to the patient is identified, and when there is no motion trajectory adapted to the patient, the positioning change information of the patient is determined to be positioning abnormality information.

[0024] Optionally, the identifying the current abnormal state of the patient through an abnormal state analysis network based on the current physical state of the patient, the critical behavior information of the patient, and the abnormal positioning information of the patient includes:

[0025] Based on the current physical state of the patient, analyzing the abnormal physical state information of the patient through a state analysis network, and based on the critical behavior information of the patient and the abnormal physical state information of the patient, identifying each initial abnormal state corresponding to the patient through an abnormal state recognition network, and extracting the action trajectory feature of each initial abnormal state and the patient trajectory feature of the action trajectory of the patient respectively;

[0026] The similarity between the patient trajectory feature and each action trajectory feature is calculated, and the initial abnormal state corresponding to the maximum similarity is selected as the current abnormal state of the patient.

[0027] In addition, to achieve the above-mentioned purpose, the present invention further provides an emergency rescue system for a user in an abnormal state, the emergency rescue system for a user in an abnormal state comprising:

[0028] an acquisition module, used to acquire the patient's physical detection information, the patient's behavior detection information, and the patient's position change information, and identify the patient's current physical state based on the patient's physical detection information;

[0029] an analysis module, for identifying the current behavior information of the patient based on the behavior detection information of the patient, and analyzing the critical behavior information of the patient through a morphology recognition network based on the current behavior information of the patient;

[0030] an identification module, configured to analyze the abnormal positioning information of the patient based on the positioning change information of the patient, and identify the current abnormal state of the patient through an abnormal state analysis network based on the current physical state of the patient, the critical behavior information of the patient, and the abnormal positioning information of the patient;

[0031] The help calling module is used to generate abnormal help calling information of the patient based on the current abnormal state of the patient, and send the abnormal help calling information to the medical staff client.

[0032] Optionally, the acquisition module is specifically used to:

[0033] Splitting the body detection information into detection data of each body detection type, and performing data distribution processing on each detection data to obtain detection data distribution information;

[0034] Based on the detection data distribution information, identifying the data distribution range of the detection type and the data distribution trend of the detection type, and based on the data distribution range of the detection type and the data distribution trend of the detection type, identifying the sub-body state corresponding to the detection type through the state recognition strategy of the detection type;

[0035] The sub-physical states corresponding to all detection types are taken as the current physical state of the patient.

[0036] Optionally, the analysis module is specifically used to:

[0037] Based on the patient's behavior monitoring information, identifying the patient's body vibration monitoring information and the patient's behavior duration information, and based on the patient's body vibration monitoring information, identifying the patient's body vibration amplitude and the body vibration intensity endured by the patient;

[0038] Based on the behavior duration information of the patient, the duration of the patient's behavior and the current behavior content of the patient are identified, and based on the body vibration amplitude of the patient and the body vibration intensity endured by the patient, the abnormal body vibration information of the patient is identified through a vibration analysis strategy;

[0039] Based on the duration of the patient's behavior and the current content of the patient's behavior, the patient's abnormal behavior information is identified through a behavior abnormality analysis strategy, and the patient's abnormal body vibration information and the patient's abnormal behavior information are used as the patient's current behavior information.

[0040] Optionally, the analysis module is specifically used to:

[0041] Based on the abnormal body vibration information of the patient, analyzing the cause of the patient's body vibration through the vibration analysis network, and based on the abnormal behavior information of the patient, identifying the abnormal behavior type of the patient through the behavior analysis network;

[0042] In the abnormal behavior database, query each initial critical behavior information including the cause of the body vibration and the type of abnormal behavior, and based on the duration of the patient's behavior and the amplitude of the patient's body vibration, filter the critical behavior information corresponding to the patient in each initial critical behavior information.

[0043] Optionally, the identification module is specifically used to:

[0044] Arrange the patient's location change information in chronological order to generate the patient's movement trajectory and the patient's movement area, and query the patient's movement types in the movement area in the patient's historical movement database based on the patient's movement area;

[0045] Based on the motion trajectory of the patient and the historical motion trajectory of the patient in each motion type, the motion trajectory adapted to the patient is identified, and when there is no motion trajectory adapted to the patient, the positioning change information of the patient is determined to be positioning abnormality information.

[0046] Optionally, the identification module is specifically used to:

[0047] Based on the current physical state of the patient, analyzing the abnormal physical state information of the patient through a state analysis network, and based on the critical behavior information of the patient and the abnormal physical state information of the patient, identifying each initial abnormal state corresponding to the patient through an abnormal state recognition network, and extracting the action trajectory feature of each initial abnormal state and the patient trajectory feature of the action trajectory of the patient respectively;

[0048] The similarity between the patient trajectory feature and each action trajectory feature is calculated, and the initial abnormal state corresponding to the maximum similarity is selected as the current abnormal state of the patient.

[0049] In a third aspect, the present application provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0050] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0051] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0052] The present invention provides an emergency call method, system and device for an abnormal state of a user, the method comprising: obtaining a patient's physical detection information, the patient's behavior detection information, and the patient's positioning change information, and identifying the patient's current physical state based on the patient's physical detection information; identifying the patient's current behavior information based on the patient's behavior detection information, and analyzing the patient's critical behavior information through a morphological recognition network based on the patient's current behavior information; analyzing the patient's positioning abnormality information based on the patient's positioning change information, and identifying the patient's current abnormal state through an abnormal state analysis network based on the patient's critical behavior information and the patient's positioning abnormality information; generating the patient's abnormal call for help information based on the patient's current abnormal state, and sending the abnormal call for help information to a medical staff client. This solution collects the patient's physical detection information, behavior monitoring information, and positioning change information in real time through the sensor equipment set on the patient, so that the patient's current abnormal state is comprehensively analyzed from the three perspectives of the patient's physical state, abnormal behavior, and abnormal positioning. Among them, the physical state represents whether the patient's physiological state is abnormal, the abnormal behavior represents whether the patient's actions are abnormal, and the abnormal positioning represents whether the patient has special circumstances such as fainting, fainting, and falling. Then, this solution comprehensively analyzes and judges the patient's current abnormal state from the above three perspectives, improving the accuracy and comprehensiveness of the analysis of the patient's physical abnormal state. It greatly avoids misjudgment, missed judgment, and abnormal analysis caused by abnormal judgment. Therefore, when the patient is unaccompanied, acts alone, and is in an abnormal state, it can accurately judge the abnormal state of the patient and call for help from medical staff in time, improving the efficiency of emergency calls for patients and the accuracy of emergency call judgment, and comprehensively improving the efficiency of medical staff contact when the patient suddenly has an abnormal state. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 is a flow chart of an emergency call method for a user in an abnormal state provided by an embodiment of the present invention;

[0055] Figure 2 It is a structural schematic diagram of an emergency rescue system for a user in an abnormal state provided by an embodiment of the present invention;

[0056] Figure 3An internal structure diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The emergency call method for abnormal user status provided by the embodiment of the present invention is applied to the emergency call system for abnormal user status. Unless otherwise defined, all technical and scientific terms used in this document have the same meaning as those generally understood by technicians in the technical field of this application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned drawings and any variations thereof are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0058] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0059] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0060] The emergency call method for abnormal user status provided by the embodiment of the present application can be applied to the configuration guidance application environment of dialysis replacement fluid. Among them, the method can be applied to the terminal, can also be applied to the server, can also be applied to the system including the terminal and the server, and is realized through the interaction between the terminal and the server. Among them, the terminal can be, but not limited to, various personal computers, laptops, etc. Among them, the terminal collects the patient's physical detection information, behavior monitoring information, and positioning change information in real time through the sensor device set on the patient, so that the patient's current abnormal state is comprehensively analyzed from the three perspectives of the patient's physical state, abnormal behavior, and abnormal positioning. Among them, the physical state characterizes whether the patient's physiological state is abnormal, the abnormal behavior characterizes whether the patient's action is abnormal, and the abnormal positioning characterizes whether the patient has a special situation such as fainting, fainting, and falling. Then, this scheme analyzes and judges the patient's current abnormal state from the above three perspectives, which improves the accuracy and comprehensiveness of the analysis of the patient's abnormal physical state. It greatly avoids misjudgment, missed judgment, and abnormal analysis caused by abnormal judgment. Therefore, when the patient is unaccompanied, acts alone, and is in an abnormal state, the patient's abnormal state can be accurately judged and medical staff can be called for help in a timely manner, which improves the efficiency of emergency calls for patients and the accuracy of emergency call judgments, and comprehensively improves the efficiency of contact with medical staff when patients are in sudden abnormal states.

[0061] In one embodiment, Figure 1 As shown, a method for emergency calling for help in abnormal state of a user is provided, and the method is applied to a terminal as an example for explanation, and includes the following steps:

[0062] Step S101, obtaining the patient's physical detection information, the patient's behavior detection information, and the patient's position change information, and identifying the patient's current physical state based on the patient's physical detection information.

[0063] In this embodiment, the terminal obtains the patient's physical detection information by receiving sensor data transmitted in real time by a detection sensor set on the patient's body surface, wherein the physical detection information includes but is not limited to detection data of various physical detection types, wherein the physical detection types include but are not limited to pulse detection type, breathing detection type, blood pressure monitoring type, etc. Among them, the sensor of each body detection type is a portable sensor, such as a smart bracelet, which can detect pulse and blood pressure at the same time. The sensor corresponding to the breathing detection type is an airflow sensor set at the user's mouth. Then, the terminal collects the patient's behavior monitoring information through devices such as vibration sensors and displacement sensors, wherein the vibration sensors and joint displacement sensors are set on the patient's limbs, head, and chest and abdomen. Finally, the terminal collects the patient's positioning information in real time through a locator set on the patient's body surface to obtain the patient's positioning change information. Then, the terminal identifies the patient's current physical state based on the patient's physical detection information, wherein the patient's current physical state is the patient's physiological state, which is used to characterize the patient's physiological characteristics, so as to determine whether the patient has an emergency physiological abnormality. The specific identification process will be described in detail later

[0064] Step S102, based on the patient's behavior detection information, identifying the patient's current behavior information, and based on the patient's current behavior information, analyzing the patient's critical behavior information through a morphology recognition network.

[0065] In this embodiment, the terminal identifies the patient's current behavior information based on the patient's behavior detection information, and analyzes the patient's critical behavior information through a morphological recognition network based on the patient's current behavior information. The morphological recognition network includes a vibration analysis network and a behavior analysis network. The vibration analysis network analyzes the vibration intensity of the vibration to which the patient's body is subjected, and the vibration cause corresponding to the vibration amplitude, while the behavior analysis network analyzes the duration of the patient's behavior and the type of abnormal behavior corresponding to the behavior content. The specific recognition process will be described in detail later, wherein the above network is a neural network based on reinforcement learning.

[0066] Step S103, based on the patient's positioning change information, analyzing the patient's positioning abnormality information, and based on the patient's current physical state, the patient's critical behavior information, and the patient's positioning abnormality information, identifying the patient's current abnormal state through an abnormal state analysis network.

[0067] In this embodiment, the terminal analyzes the patient's abnormal positioning information based on the patient's positioning change information, and identifies the patient's current abnormal state through the abnormal state analysis network based on the patient's critical behavior information and the patient's abnormal positioning information. Among them, the abnormal state analysis network is an artificial neural network. The specific analysis process will be described in detail later. Among them, the abnormal positioning information, for example, maintaining a fixed posture for a long time, a short-time long-distance change, a long-time short-distance change, or maintaining an abnormal posture for a long time.

[0068] Step S104: Generate abnormal distress information of the patient based on the current abnormal state of the patient, and send the abnormal distress information to the medical staff client.

[0069] In this embodiment, the terminal fills the patient's current abnormal state into the patient's abnormal call template to obtain the patient's abnormal call information, wherein the abnormal call template includes but is not limited to abnormal state information, patient location information, duration of the patient's abnormal state, and the urgency level corresponding to the patient's abnormal state. Finally, the terminal sends the patient's abnormal call information to the medical staff client.

[0070] Based on the above scheme, the patient's body detection information, behavior monitoring information, and positioning change information are collected in real time by the sensor equipment set on the patient, so that the patient's current abnormal state is comprehensively analyzed from the three perspectives of the patient's body state, abnormal behavior, and abnormal positioning, wherein the body state represents whether the patient's physiological state is abnormal, the abnormal behavior represents whether the patient's action is abnormal, and the abnormal positioning represents whether the patient has a special situation such as fainting, fainting, and falling. Then, this scheme analyzes and judges the patient's current abnormal state from the above three perspectives, which improves the accuracy and comprehensiveness of the analysis of the patient's abnormal body state. It greatly avoids misjudgment, missed judgment, and abnormal analysis caused by abnormal judgment. Therefore, when the patient is unaccompanied, acts alone, and is in an abnormal state, the abnormal state of the patient can be accurately judged, and medical staff can be called for help in time, which improves the efficiency of emergency calls for patients and the accuracy of emergency call judgment, and comprehensively improves the efficiency of medical staff contact when the patient suddenly has an abnormal state.

[0071] Optionally, based on the patient's physical detection information, the patient's current physical state is identified, including: splitting the physical detection information into detection data of each physical detection type, and performing data distribution processing on each detection data to obtain detection data distribution information; based on the detection data distribution information, identifying the data distribution range of the detection type, and the data distribution trend of the detection type, and based on the data distribution range of the detection type, identifying the sub-physical state corresponding to the detection type through a state identification strategy of the detection type; and taking the sub-physical states corresponding to all detection types as the patient's current physical state.

[0072] In this embodiment, the terminal divides the body detection information into detection data of each body detection type, and performs data distribution processing on each detection data to obtain detection data distribution information. The detection data distribution information is the distribution information obtained by distributing and sorting the detection data collected in real time in chronological order.

[0073] Then, the terminal identifies the data distribution range and the data distribution trend of the detection type based on the detection data distribution information. The data distribution trend is identified by performing curve fitting processing on the data distribution curve corresponding to the detection data distribution information through a curve fitting algorithm to obtain the data distribution trend information.

[0074] Then, the terminal identifies the sub-body state corresponding to the detection type based on the data distribution range and data distribution trend of the detection type and the state recognition strategy of the detection type. Each detection type corresponds to a state recognition strategy, and each state recognition strategy includes the detection data range corresponding to each body state. Then, the terminal identifies the body state corresponding to the patient based on the detection data range to which the patient's detection data belongs.

[0075] Finally, the terminal takes the sub-body states corresponding to all detection types as the patient's current body state.

[0076] Based on the above scheme, the detection data of each detection type is split to identify each sub-body state, thereby improving the comprehensiveness and accuracy of identifying the patient's current body state.

[0077] Optionally, based on the patient's behavior detection information, the patient's current behavior information is identified, including: based on the patient's behavior monitoring information, identifying the patient's body vibration monitoring information and the patient's behavior duration information, and based on the patient's body vibration monitoring information, identifying the patient's body vibration amplitude and the intensity of body vibration experienced by the patient; based on the patient's behavior duration information, identifying the patient's behavior duration and the patient's current behavior content, and based on the patient's body vibration amplitude and the intensity of body vibration experienced by the patient, identifying the patient's abnormal body vibration information through a vibration analysis strategy; based on the patient's behavior duration and the patient's current behavior content, identifying the patient's abnormal behavior information through a behavior abnormality analysis strategy, and using the patient's abnormal body vibration information and the patient's abnormal behavior information as the patient's current behavior information.

[0078] In this embodiment, the terminal identifies the patient's body vibration monitoring information and the patient's behavior duration information based on the patient's behavior monitoring information, and identifies the patient's body vibration amplitude and the body vibration intensity borne by the patient based on the patient's body vibration monitoring information. Among them, the body vibration monitoring information includes vibration monitoring information of various body position ranges, wherein the position range includes but is not limited to the head range, hand range, leg range, chest and abdomen range and other position ranges. The body vibration intensity of different position ranges is different from the actual vibration intensity borne by the range. For example, the body vibration intensity corresponding to the head bearing a 10kg impact is a level 3 vibration intensity, and the body vibration intensity corresponding to the leg bearing a 10kg impact is a level 1 vibration intensity. Among them, the body vibration intensity can be divided into ten levels, and the higher the level, the higher the body vibration intensity. The more critical the body position range, the easier it is for the body vibration intensity to reach a high level; the less critical the body position range, the less likely it is for the body vibration intensity to reach a high level. Among them, the critical body position range includes the head range, the chest and abdomen range, and the non-critical body position range includes the hand range, and the leg range, and the criticality of the head range is greater than that of the chest and abdomen range.

[0079] Then, the terminal identifies the duration of the patient's behavior and the current behavior content of the patient based on the patient's behavior duration information. The device for collecting the patient's behavior duration information may be a motion capture sensor set at each joint of the patient. Based on the motion capture sensor, the patient's motion behavior can be collected in real time. The motion behavior includes but is not limited to simple motion content such as walking, squatting, moving, jumping, climbing, etc. At the same time, the motion behavior can also be the patient's current posture, such as lying posture, sitting posture, prone posture, semi-lying posture, and irregular posture.

[0080] Afterwards, the terminal identifies the abnormal body vibration information of the patient through a vibration analysis strategy based on the body vibration amplitude of the patient and the body vibration intensity to which the patient is subjected. The vibration analysis strategy is the vibration information corresponding to the body vibration amplitude range of different body ranges and the body vibration intensity range of different body ranges, wherein the vibration information includes normal vibration information and abnormal vibration information, wherein the body vibration amplitude range of each body range includes the body vibration amplitude range corresponding to the normal vibration information and the body vibration amplitude range corresponding to the abnormal vibration information; the body vibration intensity range of each body range includes the body vibration intensity range corresponding to the normal vibration information and the body vibration intensity range corresponding to the abnormal vibration information. The normal vibration information and abnormal vibration information corresponding to different body ranges are different, and then the terminal summarizes all the vibration information into the body range of the abnormal vibration information and the body vibration intensity or body vibration amplitude corresponding to the abnormal vibration information of the body range as the abnormal body vibration information of the patient.

[0081] Finally, based on the duration of the patient's behavior and the patient's current behavior content, the terminal identifies the patient's abnormal behavior information through the abnormal behavior analysis strategy, and uses the patient's abnormal body vibration information and the patient's abnormal behavior information as the patient's current behavior information. Among them, each current behavior content corresponds to different behavior information in different behavior duration ranges, and the behavior information includes normal behavior information and abnormal behavior information. When the behavior information corresponding to the behavior duration range to which the behavior duration of the current behavior content belongs is abnormal behavior information, the terminal uses the patient's current behavior content and the behavior duration corresponding to the current behavior content as the patient's abnormal behavior information.

[0082] Based on the above scheme, by identifying the patient's different behavioral information corresponding to non-continuous time ranges, and the body vibration intensity or body vibration amplitude corresponding to different body ranges, the patient's abnormal body vibration information and abnormal behavior information are determined, thereby improving the accuracy and comprehensiveness of the identification.

[0083] Optionally, the morphological recognition network includes a vibration analysis network and a behavior analysis network. Based on the patient's current behavior information, the patient's critical behavior information is analyzed through the morphological recognition network, including: based on the patient's abnormal body vibration information, analyzing the cause of the patient's body vibration through the vibration analysis network, and based on the patient's abnormal behavior information, identifying the patient's abnormal behavior type through the behavior analysis network; in the abnormal behavior database, querying each initial critical behavior information including the cause of the body vibration and the abnormal behavior type, and based on the duration of the patient's behavior and the amplitude of the patient's body vibration, screening the critical behavior information corresponding to the patient in each initial critical behavior information.

[0084] In this embodiment, the terminal analyzes the cause of the patient's body vibration based on the patient's abnormal body vibration information through a vibration analysis network, and identifies the patient's abnormal behavior type based on the patient's abnormal behavior information through a behavior analysis network.

[0085] Then, the terminal searches the abnormal behavior database for each initial critical behavior information including the cause of body vibration and the type of abnormal behavior, and based on the duration of the patient's behavior and the amplitude of the patient's body vibration, screens the critical behavior information corresponding to the patient in each initial critical behavior information. Each initial critical behavior information corresponds to a body vibration amplitude range for each body area and a behavior duration range for the behavior content. Then, the terminal determines the initial critical behavior information corresponding to the patient based on the behavior duration range to which the patient's behavior duration belongs and the body vibration amplitude range to which the body vibration amplitude of each body area of ​​the patient belongs.

[0086] Based on the above scheme, after identifying the cause of the patient's abnormal vibration and the type of abnormal behavior, the patient's critical behavior information is screened, thereby improving the accuracy of identifying the critical behavior information.

[0087] Optionally, based on the patient's positioning change information, the patient's positioning abnormality information is analyzed, including: arranging the patient's positioning change information in chronological order to generate the patient's movement trajectory and the patient's movement area, and based on the patient's movement area, querying the patient's movement types in the movement area in the patient's historical movement database; based on the patient's movement trajectory and the patient's historical movement trajectory in each movement type, identifying the movement trajectory adapted to the patient, and when there is no movement trajectory adapted to the patient, determining that the patient's positioning change information is positioning abnormality information.

[0088] In this embodiment, the terminal arranges the patient's location change information in chronological order, generates the patient's movement trajectory and the patient's movement area, and based on the patient's movement area, queries the patient's movement types in the movement area in the patient's historical movement database. The patient's movement area is one of the movement areas corresponding to the various position ranges preset by the medical staff, for example, the movement area is a rest area, a bathroom area, a corridor area, a garden area, an office area, a consultation area, a diagnosis and treatment area, a detection area, etc.

[0089] Finally, the terminal identifies the patient's adapted motion trajectory based on the patient's motion trajectory and the patient's historical motion trajectory in each motion type, and determines the patient's positioning change information as positioning abnormality information when there is no motion trajectory adapted to the patient. Specifically, medical staff collect the motion trajectories of each patient in different motion types and store them in the database. Due to the regularity of the patient's behavior, by matching the overlap between different motion trajectories and historical motion trajectories, it can be determined whether the patient's motion in each area is normal. When the patient does not belong to the normal motion in the motion area, the terminal regards the patient's positioning change information as the patient's positioning abnormality information.

[0090] Based on the above scheme, by adapting the action area where the patient's action trajectory is located, and then identifying the overlap based on the patient's historical action trajectory, it is determined whether the patient is in a positioning abnormality, thereby improving the recognition efficiency and accuracy of the patient's positioning abnormality information.

[0091] Optionally, based on the patient's current physical state, the patient's critical behavior information, and the patient's positioning abnormality information, the patient's current abnormal state is identified through an abnormal state analysis network, including: based on the patient's current physical state, analyzing the patient's physical state abnormality information through a state analysis network, and based on the patient's critical behavior information and the patient's physical state abnormality information, identifying each initial abnormal state corresponding to the patient through an abnormal state identification network, and extracting the motion trajectory features of each initial abnormal state and the patient's trajectory features of the patient's motion trajectory respectively; calculating the similarity between the patient's trajectory features and each motion trajectory feature, and selecting the initial abnormal state corresponding to the maximum similarity as the patient's current abnormal state.

[0092] In this embodiment, the terminal analyzes the abnormal physical state information of the patient through the state analysis network based on the patient's current physical state, and identifies the initial abnormal states corresponding to the patient through the abnormal state recognition network based on the patient's critical behavior information and the abnormal physical state information of the patient, and extracts the motion trajectory features of each initial abnormal state and the patient trajectory features of the patient's motion trajectory. The state analysis network and the abnormal state recognition network are neural networks based on reinforcement learning, and the motion trajectory feature extraction method is to extract the motion trajectory features and patient trajectory features by performing image feature extraction on the trajectory image corresponding to the patient's motion trajectory through the image feature extraction network. The image feature extraction network is a convolutional neural network based on the self-attention mechanism.

[0093] Then, the terminal calculates the similarity between the patient's trajectory features and each action trajectory feature through the cosine similarity algorithm, and selects the initial abnormal state corresponding to the maximum similarity as the patient's current abnormal state.

[0094] Based on the above solution, the patient's current abnormal state is identified from three perspectives: physical state, critical behavior information, and movement trajectory, thereby improving the accuracy and comprehensiveness of identifying the current abnormal state.

[0095] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0096] Based on the same inventive concept, the embodiment of the present application also provides an emergency rescue system for abnormal user status for implementing the emergency rescue method for abnormal user status involved above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the emergency rescue system for abnormal user status provided below can refer to the limitations of the emergency rescue method for abnormal user status above, and will not be repeated here.

[0097] Further references Figure 2 , as a response to the above Figure 1 The implementation of the method shown in the present application provides an embodiment of an emergency call system 200 for a user in an abnormal state. The emergency call system for a user in an abnormal state includes an acquisition module 210, an analysis module 220, an identification module 230 and a call module 240, wherein:

[0098] An acquisition module 210, configured to acquire the patient's physical detection information, the patient's behavior detection information, and the patient's position change information, and identify the patient's current physical state based on the patient's physical detection information;

[0099] An analysis module 220, for identifying the current behavior information of the patient based on the behavior detection information of the patient, and analyzing the critical behavior information of the patient through a morphology recognition network based on the current behavior information of the patient;

[0100] The identification module 230 is used to analyze the abnormal positioning information of the patient based on the positioning change information of the patient, and identify the current abnormal state of the patient through an abnormal state analysis network based on the current physical state of the patient, the critical behavior information of the patient, and the abnormal positioning information of the patient;

[0101] The help calling module 240 is used to generate abnormal help calling information of the patient based on the current abnormal state of the patient, and send the abnormal help calling information to the medical staff client.

[0102] Optionally, the acquisition module 210 is specifically configured to:

[0103] Splitting the body detection information into detection data of each body detection type, and performing data distribution processing on each detection data to obtain detection data distribution information;

[0104] Based on the detection data distribution information, identifying the data distribution range of the detection type and the data distribution trend of the detection type, and based on the data distribution range of the detection type and the data distribution trend of the detection type, identifying the sub-body state corresponding to the detection type through the state recognition strategy of the detection type;

[0105] The sub-physical states corresponding to all detection types are taken as the current physical state of the patient.

[0106] Optionally, the analysis module 220 is specifically used for:

[0107] Based on the patient's behavior monitoring information, identifying the patient's body vibration monitoring information and the patient's behavior duration information, and based on the patient's body vibration monitoring information, identifying the patient's body vibration amplitude and the body vibration intensity endured by the patient;

[0108] Based on the behavior duration information of the patient, the duration of the patient's behavior and the current behavior content of the patient are identified, and based on the body vibration amplitude of the patient and the body vibration intensity endured by the patient, the abnormal body vibration information of the patient is identified through a vibration analysis strategy;

[0109] Based on the duration of the patient's behavior and the current content of the patient's behavior, the patient's abnormal behavior information is identified through a behavior abnormality analysis strategy, and the patient's abnormal body vibration information and the patient's abnormal behavior information are used as the patient's current behavior information.

[0110] Optionally, the analysis module 220 is specifically used for:

[0111] Based on the abnormal body vibration information of the patient, analyzing the cause of the patient's body vibration through the vibration analysis network, and based on the abnormal behavior information of the patient, identifying the abnormal behavior type of the patient through the behavior analysis network;

[0112] In the abnormal behavior database, query each initial critical behavior information including the cause of the body vibration and the type of abnormal behavior, and based on the duration of the patient's behavior and the amplitude of the patient's body vibration, filter the critical behavior information corresponding to the patient in each initial critical behavior information.

[0113] Optionally, the identification module 230 is specifically configured to:

[0114] Arrange the patient's location change information in chronological order to generate the patient's movement trajectory and the patient's movement area, and query the patient's movement types in the movement area in the patient's historical movement database based on the patient's movement area;

[0115] Based on the motion trajectory of the patient and the historical motion trajectory of the patient in each motion type, the motion trajectory adapted to the patient is identified, and when there is no motion trajectory adapted to the patient, the positioning change information of the patient is determined to be positioning abnormality information.

[0116] Optionally, the identification module 230 is specifically configured to:

[0117] Based on the current physical state of the patient, analyzing the abnormal physical state information of the patient through a state analysis network, and based on the critical behavior information of the patient and the abnormal physical state information of the patient, identifying each initial abnormal state corresponding to the patient through an abnormal state recognition network, and extracting the action trajectory feature of each initial abnormal state and the patient trajectory feature of the action trajectory of the patient respectively;

[0118] The similarity between the patient trajectory feature and each action trajectory feature is calculated, and the initial abnormal state corresponding to the maximum similarity is selected as the current abnormal state of the patient.

[0119] Each module in the above-mentioned emergency call system for abnormal user status can be implemented in whole or in part by software, hardware and a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0120] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input system connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, an emergency call method for an abnormal state of a user is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input system of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0121] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0122] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0123] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0124] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of any one of the methods in the first aspect.

[0125] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0126] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0127] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0128] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for emergency rescue in abnormal state of a user, characterized in that: The method comprises: Acquire the patient's physical detection information, the patient's behavior detection information, and the patient's position change information, and identify the patient's current physical state based on the patient's physical detection information; Based on the behavior detection information of the patient, identifying the current behavior information of the patient, and based on the current behavior information of the patient, analyzing the critical behavior information of the patient through a morphology recognition network; Based on the positioning change information of the patient, analyzing the positioning abnormality information of the patient, and based on the current physical state of the patient, the critical behavior information of the patient, and the positioning abnormality information of the patient, identifying the current abnormal state of the patient through an abnormal state analysis network; Based on the current abnormal state of the patient, abnormal distress information of the patient is generated, and the abnormal distress information is sent to a medical staff client.

2. The method according to claim 1, characterized in that The identifying the current physical condition of the patient based on the physical detection information of the patient includes: Splitting the body detection information into detection data of each body detection type, and performing data distribution processing on each detection data to obtain detection data distribution information; Based on the detection data distribution information, identifying the data distribution range of the detection type and the data distribution trend of the detection type, and based on the data distribution range of the detection type and the data distribution trend of the detection type, identifying the sub-body state corresponding to the detection type through the state recognition strategy of the detection type; The sub-physical states corresponding to all detection types are taken as the current physical state of the patient.

3. The method according to claim 1, characterized in that The step of identifying the current behavior information of the patient based on the behavior detection information of the patient includes: Based on the patient's behavior monitoring information, identifying the patient's body vibration monitoring information and the patient's behavior duration information, and based on the patient's body vibration monitoring information, identifying the patient's body vibration amplitude and the body vibration intensity endured by the patient; Based on the behavior duration information of the patient, the duration of the patient's behavior and the current behavior content of the patient are identified, and based on the body vibration amplitude of the patient and the body vibration intensity endured by the patient, the abnormal body vibration information of the patient is identified through a vibration analysis strategy; Based on the duration of the patient's behavior and the current content of the patient's behavior, the patient's abnormal behavior information is identified through a behavior abnormality analysis strategy, and the patient's abnormal body vibration information and the patient's abnormal behavior information are used as the patient's current behavior information.

4. The method according to claim 3, characterized in that The morphology recognition network includes a vibration analysis network and a behavior analysis network. The method of analyzing the critical behavior information of the patient through the morphology recognition network based on the current behavior information of the patient includes: Based on the abnormal body vibration information of the patient, analyzing the cause of the patient's body vibration through the vibration analysis network, and based on the abnormal behavior information of the patient, identifying the abnormal behavior type of the patient through the behavior analysis network; In the abnormal behavior database, query each initial critical behavior information including the cause of the body vibration and the type of abnormal behavior, and based on the duration of the patient's behavior and the amplitude of the patient's body vibration, filter the critical behavior information corresponding to the patient in each initial critical behavior information.

5. The method according to claim 1, characterized in that The analyzing the abnormal positioning information of the patient based on the positioning change information of the patient includes: Arrange the patient's location change information in chronological order to generate the patient's movement trajectory and the patient's movement area, and query the patient's movement types in the movement area in the patient's historical movement database based on the patient's movement area; Based on the motion trajectory of the patient and the historical motion trajectory of the patient in each motion type, the motion trajectory adapted to the patient is identified, and when there is no motion trajectory adapted to the patient, the positioning change information of the patient is determined to be positioning abnormality information.

6. The method according to claim 5, characterized in that The method of identifying the current abnormal state of the patient through an abnormal state analysis network based on the current physical state of the patient, the critical behavior information of the patient, and the abnormal positioning information of the patient includes: Based on the current physical state of the patient, analyzing the abnormal physical state information of the patient through a state analysis network, and based on the critical behavior information of the patient and the abnormal physical state information of the patient, identifying each initial abnormal state corresponding to the patient through an abnormal state recognition network, and extracting the action trajectory feature of each initial abnormal state and the patient trajectory feature of the action trajectory of the patient respectively; The similarity between the patient trajectory feature and each action trajectory feature is calculated, and the initial abnormal state corresponding to the maximum similarity is selected as the current abnormal state of the patient.

7. An emergency call device for a user in an abnormal state, characterized in that: The system comprises: an acquisition module, used to acquire the patient's physical detection information, the patient's behavior detection information, and the patient's position change information, and identify the patient's current physical state based on the patient's physical detection information; an analysis module, for identifying the current behavior information of the patient based on the behavior detection information of the patient, and analyzing the critical behavior information of the patient through a morphology recognition network based on the current behavior information of the patient; an identification module, configured to analyze the abnormal positioning information of the patient based on the positioning change information of the patient, and identify the current abnormal state of the patient through an abnormal state analysis network based on the current physical state of the patient, the critical behavior information of the patient, and the abnormal positioning information of the patient; The help calling module is used to generate abnormal help calling information of the patient based on the current abnormal state of the patient, and send the abnormal help calling information to the medical staff client.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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