CN111899878B - Old person health detection system, method, computer device and readable storage medium - Google Patents
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Abstract
The invention discloses a health detection system for old people, which can be applied to a smart medical scene so as to promote the construction of smart cities. The system comprises: the user data acquisition module is used for acquiring physical parameter data and voice data of a user; the organization module is used for collecting service data generated when different service institutions serve users; the application program module is used for acquiring the body parameter data, the voice data and the service data, and evaluating the body health condition of the user according to the body parameter data and the service data to generate a body health evaluation result; the automatic machine learning module is used for analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result, and feeding back the psychological health evaluation result to the response program module; and the block chain module is used for synchronizing the body parameter data, the voice data and the service data into each node of the block chain, so that the data sharing can be realized, and the physical and mental health of the old can be comprehensively and actively ensured.
Description
Technical Field
The present invention relates to the field of artificial intelligence, and in particular, to a system, a method, a computer device, and a readable storage medium for detecting health of an elderly person.
Background
Population aging is a very serious realistic problem faced by China, and a long-term challenge is properly solved for social problems brought by population aging. By 2018, the aged people aged 60 years and older in China are 2.49 hundred million, and the proportion is 17.9%. The elderly aged 65 years and older 1.66 billion, with a ratio of 11.9%. Wherein, the aged with chronic diseases is 1.5 hundred million, accounting for 65% of the total aged. The elderly who are disabled and semi-disabled 4400 ten thousand. The monitoring of the condition of incapacitation and intelligence loss (impaired life processing ability and cognitive function) of the old provides convenience and safety guarantee for the old community, reduces the accident rate, lightens the pressure for the caregivers and families, and improves the working efficiency.
Remote medical management realized by means of big data, internet, artificial intelligence and other technologies improves the utilization rate and convenience of medical resources, but has a plurality of challenges in practical application. First, community and hospital, hospital to hospital data sharing is required for better detection and assessment of the health status of the elderly. Meanwhile, a machine learning model needs a large amount of learning training data, and in order to obtain a better model, different cities of different communities should share monitoring data. Medical data contains personal and sensitive information, and with the expansion of the field of remote patient monitoring, there are significant challenges in protecting privacy of users, secure sharing of data, and efficient transmission. Finally, the existing telemedicine systems pay more attention to the physical characteristics of the old and ignore the mental health of the old.
Disclosure of Invention
In view of the above, the invention provides a health detection system for the elderly, which realizes the sharing of detection data among service institutions, better detects mental health while detecting physical health of the elderly, and comprehensively and actively ensures physical and mental health of the elderly.
First, to achieve the above object, the present invention proposes an old person health detection system, the system comprising:
the user data acquisition module is used for acquiring physical parameter data and voice data of a user;
the organization module is used for collecting service data generated when different service institutions serve users;
the application program module is used for acquiring the body parameter data, the voice data and the service data, and evaluating the body health condition of the user according to the body parameter data and the service data to generate a body health evaluation result;
the automatic machine learning module is used for analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result, and feeding back the psychological health evaluation result to the application program module;
and the block chain module is used for synchronizing the physical parameter data, the voice data, the service data, the physical health evaluation result and the psychological health evaluation result into each node of a block chain.
Preferably, the system further comprises:
the data desensitization module is used for carrying out data desensitization on the body parameter data, the voice data and the service data acquired by the application program module so as to eliminate identifiable characteristics in sensitive data, sending the desensitized data to the automatic machine learning module for analysis by the automatic machine learning module, and sending the desensitized data to the blockchain module to realize data sharing.
Preferably, the application program module comprises a user-oriented application program and an organization-oriented application program; wherein,,
the application program facing the user is used for feeding back the physical health evaluation result and the psychological health evaluation result to the user, and providing health risk early warning and countermeasure for the user according to the physical health evaluation result and the psychological health evaluation result;
the organization-oriented application program is used for providing the physical health evaluation results and the mental health evaluation results of all the old people in the service mechanism to the service mechanism and providing the physical health evaluation results and the mental health evaluation results of the user to the medical mechanism.
Preferably, the organization-oriented application program is further configured to classify all the elderly people in the service organization according to the physical health evaluation results and the mental health evaluation results of the all the elderly people, and remind the staff of the service organization to take different countermeasures for the elderly people in different health classes.
Preferably, the application program module is further used for recording the evaluation of the service quality of the service mechanism and the medical mechanism by the user and storing the evaluation result to the blockchain module.
Preferably, the service data includes voice data of a user talking, the automatic machine learning module analyzes an emotion state and a psychological state of the user according to the voice data collected by the user data module and the voice data in the service data, and evaluates psychological health condition of the user according to the emotion state and the psychological state.
Preferably, the automatic machine learning module evaluates the emotional state of the user according to the change of the sound characteristics, and evaluates the psychological state of the user by recognizing negative words contained in the voice data.
In order to realize sharing detection data among service institutions, better detect the physical health of the old people and detect mental health at the same time, comprehensively and actively ensure the physical and mental health of the old people, the invention also provides a method for monitoring the health of the old people, which comprises the following steps:
acquiring physical parameter data and voice data of a user;
acquiring service data generated when different service institutions and medical institutions serve users;
evaluating the physical health condition of the user according to the physical parameter data and the service data to generate a physical health evaluation result;
analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result;
the body parameter data, the voice data, and the service data are synchronized into respective nodes of a blockchain.
In order to realize the sharing of detection data among service institutions, better detect the old person's physical health and detect mental health simultaneously, the invention also provides a computer device which comprehensively and actively guarantees the physical and mental health of the old person, the computer device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, and the processor realizes the following steps when executing the computer program:
acquiring physical parameter data and voice data of a user;
acquiring service data generated when different service institutions and medical institutions serve users;
evaluating the physical health condition of the user according to the physical parameter data and the service data to generate a physical health evaluation result;
analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result;
the body parameter data, the voice data, and the service data are synchronized into respective nodes of a blockchain.
In order to realize the sharing of detection data among service institutions, better detect the old person's physical health and detect mental health simultaneously, the invention also provides a readable storage medium on which a computer program is stored, which when being executed by a processor realizes the following steps:
acquiring physical parameter data and voice data of a user;
acquiring service data generated when different service institutions and medical institutions serve users;
evaluating the physical health condition of the user according to the physical parameter data and the service data to generate a physical health evaluation result;
analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result;
the body parameter data, the voice data, and the service data are synchronized into respective nodes of a blockchain.
Compared with the prior art, the old people health detection system 200 provided in the present embodiment collects the physical parameter data of the user through the user data collection module and the service data generated when the user is served by different service institutions through the voice data and organization module; further, the physical health condition of the user is evaluated according to the physical parameter data and the service data through an application program module so as to generate a physical health evaluation result; and analyzing the voice data and the service data through an automatic machine learning module to evaluate the psychological health condition of the user to generate a psychological health evaluation result, and comprehensively and actively guaranteeing the physical and psychological health of the old. And the block chain module is used for storing and sharing data, so that the detection data sharing among service mechanisms is realized.
Drawings
FIG. 1 is a schematic diagram of functional modules of a first embodiment of the senior health detection system of the present invention;
FIG. 2 is a schematic diagram of functional modules of a second embodiment of the senior health detection system of the present invention;
FIG. 3 is a flow chart of an embodiment of a method for detecting health of elderly people according to the present invention;
fig. 4 is a schematic diagram of a hardware architecture of a computer device suitable for implementing the method for detecting the health of the elderly according to the present invention.
Reference numerals:
the achievement of the object, functional features and advantages of the present invention will be further described with reference to the drawings in connection with the embodiments.
Detailed Description
The present invention will be described in further detail with reference to the drawings and embodiments, in order to make the objects, technical solutions and advantages of the present invention more apparent. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the accompanying claims. It should be understood that the detailed description is presented by way of example only and is not intended to limit the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.
The terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used in this disclosure to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present disclosure. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.
In the description of the present invention, it should be understood that the numerical references before the steps do not identify the order in which the steps are performed, but are merely used to facilitate description of the present invention and to distinguish between each step, and thus should not be construed as limiting the present invention.
The invention provides a health detection system 200 for the elderly, which can be applied to smart medical scenes, thereby promoting the construction of smart cities. Referring to fig. 1, a functional block diagram of a first embodiment of an elderly health detection system 200 according to the present invention is shown. In this embodiment, the old person health detection system 200 is composed of a user acquisition module 201, an organization module 202, an application module 203, an automatic machine learning module 204, and a blockchain module 205.
In this embodiment, the user data module 201 is configured to collect physical parameter data and voice data of a user.
Specifically, the user data acquisition module 201 may be an internet device, such as a smart wearable device, a smart home, or the like. Physical parameter data such as blood pressure, heart rate, body temperature and the like of a user are collected through intelligent wearable equipment, such as an intelligent bracelet. The intelligent home is used for collecting voice data of a user, wherein the voice data comprise self-speaking of the user, talking voice data of the user, speaking interval frequency of the user and the like.
The organization module 202 is used for collecting service data generated when different service institutions and medical institutions serve users.
Specifically, the service institutions include other service institutions such as communities, and the medical institutions include hospitals, clinics, and the like. The service data can be an inspection report when a user arrives at a hospital for a doctor, and the user exchanges voice data with the doctor; the community staff may access the registration information of the user, the voice information of the community staff communicating with the old, etc.
The application module 203 is configured to obtain the body parameter data, the voice data, and the service data, and evaluate the physical health condition of the user according to the body parameter data and the service data to generate a physical health evaluation result.
Specifically, the application modules 203 include user-oriented applications and organization-oriented applications. And the user-oriented application program feeds the body health evaluation result back to the user, and provides health risk early warning and countermeasure for the user according to the body health evaluation result. For example, when the smart band worn by the user detects that the systolic blood pressure of the user is 140, the systolic blood pressure exceeds the range of the systolic blood pressure of the normal blood pressure, the user-oriented application program feeds back the detection result to the user in time and reminds the user not to do severe exercise. When the systolic pressure of the blood pressure of the user is 170, the user-oriented application program feeds back the detection result to the user in time near to the hypertension risk, and reminds the user to seek medical advice as soon as possible.
The organization-oriented application program is used for providing the physical health condition of all the old people in the service mechanism for the service mechanism; and the system is also used for classifying all the old people according to the health conditions of the old people in the service mechanism and reminding the service mechanism staff of carrying out different countermeasures for the old people with different health levels. In this embodiment, the health class may be classified into health, low risk, and high risk. For example, when the smart band worn by the user detects that the systolic blood pressure of the user is 140, the systolic blood pressure exceeds the range of the systolic blood pressure of the normal blood pressure, the organization-oriented application program feeds back the detection result to the service mechanism in time, and reminds the service mechanism staff to remind the user of not carrying out intense exercise by telephone. When the systolic pressure of the blood pressure of the user is 170, the user-oriented application program feeds back the detection result to the service mechanism in time near to the hypertension critical illness, and reminds the staff of the service mechanism to visit the user to assist the user to visit the medical mechanism.
In this embodiment, the tissue-oriented application is further configured to provide the physical health assessment results and mental health assessment results of the user to the medical institution, thereby assisting the doctor in diagnosis.
In this embodiment, the application module 203 is further configured to record the user's evaluation of the service quality of the service institution and the medical institution and store the evaluation result in the blockchain module 205
The automatic machine learning module 204 is configured to analyze the voice data and the service data to evaluate the mental health condition of the user to generate a mental health evaluation result, and feed back the mental health evaluation result to the application module.
Specifically, the automatic machine learning module 204 is a model that has been trained, integrates the iterative process of the traditional machine learning model, and constructs an automated process including automatic feature engineering, automatic model selection, automatic parameter adjustment, and automatic evaluation deployment, without requiring specialized engineers for data processing and model tuning, and reduces the labor cost and the computational cost of machine learning.
In this embodiment, the automatic machine learning module 204 analyzes the emotional state and psychological state of the user according to the voice data collected by the user data collection module 201 and the voice data in the service data, and evaluates the psychological health condition of the user according to the emotional state and the psychological state. The automatic machine learning module 204 evaluates the emotional state of the user according to the change of the sound characteristics, for example, if the sound of the user speaking is very low and slow, then the current emotion of the user is judged to be low; and if the voice tone of the user speaking is suddenly increased and the voice speed is accelerated, judging that the current emotion fluctuation of the user is larger. The automatic machine learning module 204 also evaluates the psychological state of the user by identifying negative words contained in the speech data, for example, when negative words such as "dead", "alive not significant" and the like appear in the speech data are identified, it determines that there is a greater psychological problem with the user. The automatic machine learning module 204 feeds back the mental health assessment results to the application module 203. At this time, the user-oriented application program feeds back the mental health assessment result to the user, and provides health risk early warning and countermeasure for the user according to the mental health assessment result. The organization-oriented application program is used for providing psychological health conditions of all the old people in the service mechanism for the service mechanism; and the system is also used for classifying all the old people according to the psychological health conditions of the old people in the service mechanism and reminding the service mechanism staff of carrying out different countermeasures for the old people with different physiological health levels. For example, for old people with very low emotion, staff of a reminding service mechanism can access users in time.
The blockchain module 205 is configured to synchronize the physical parameter data, the voice data, the service data, the physical health assessment result, and the mental health assessment result into each node of a blockchain.
Specifically, the blockchain module 205 provides secure and reliable service and data sharing, and is composed of a consensus module, a membership service module, an intelligent contract module, a transaction module, an event distribution module, and an asymmetric encryption module. The consensus module provides an important algorithm to achieve fast authentication and verification of transactions in the blockchain. The member service module provides an organization's management service. The smart contract module provides sharing of data between different organizations. The transaction module stores transaction data between different organizations in a blockchain. The event distribution module provides decentralized management of the blockchain such that all recorded data is stored in a decentralized manner. The asymmetric encryption module ensures the data security in the data conversion process.
The old people health detection system 200 provided in the embodiment collects physical parameter data of a user through the user data collection module and service data generated when different service institutions serve the user through the voice data and organization module; further, the physical health condition of the user is evaluated according to the physical parameter data and the service data through an application program module so as to generate a physical health evaluation result; and analyzing the voice data and the service data through an automatic machine learning module to evaluate the psychological health condition of the user to generate a psychological health evaluation result, and comprehensively and actively guaranteeing the physical and psychological health of the old. And the block chain module is used for storing and sharing data, so that the detection data sharing among service mechanisms is realized.
Further, based on the above-described first embodiment of the elderly health detection system 200 of the present invention, a second embodiment of the present invention (as shown in fig. 2) is proposed. In this embodiment, the senior health detection system 200 further comprises a data desensitization module 206, wherein:
a data desensitizing module 206, configured to perform data desensitization on the body parameter data, the voice data, and the service data acquired by the application module 204 to eliminate identifiable features in sensitive data.
Specifically, the data desensitization is also called data privacy removal or data deformation, is a technical mechanism for transforming and modifying sensitive data under given rules and strategies, and can solve the problem that the sensitive data is used in an untrusted environment to a great extent. Data desensitization transforms sensitive information content as needed under the condition of retaining original characteristics of data. Only authorized administrators or users, if necessary, can access the actual values of the data through specific applications and tools, thereby reducing the risk of these important data being shared and moved. Under the premise of not reducing the safety, the data desensitization expands the application range of the original data and the shared object, so that the method is the most effective sensitive data protection method in a big data environment.
In this embodiment, the data desensitizing module 206 mainly adopts the following method:
replacement: for example, the female user name is uniformly replaced with F.
And (3) transformation: for example, the sequence number 12345 is changed to 54321, and the information can be conveniently restored when needed, similar to the replacement method, by scrambling in a certain sequence.
Encryption: for example, the number 12345 is 23456, and the encryption method can be selected according to actual requirements.
Invalidation or deletion: 13811001111 truncates to 138, invalidates or deletes necessary information to ensure ambiguity of the data.
The mask is, for example, 123456- >1xxxx6, which retains part of the information and ensures that the length of the information is not changed, so that the information is easier to distinguish for the information holder, such as obtaining identity information on a train ticket.
Date offset rounding: for example 20130520 12:30:45- >20130520 12:00:00, the accuracy is discarded to ensure the security of the original data, and generally this method can protect the time distribution density of the data.
In this embodiment, the data desensitizing module 206 is further configured to send the desensitized data to the automatic machine learning module 204 for analysis by the automatic machine learning module, and send the desensitized data to the blockchain module 205 to realize data sharing, so as to realize privacy protection of a user and safe sharing of data.
In the old people health detection system 200 provided in this embodiment, the data desensitization module performs data desensitization on the data acquired by the application program module to eliminate identifiable features in the sensitive data, and then sends the desensitized data to the automatic machine learning module for data analysis and to the blockchain module for storage and sharing, so as to protect privacy of users and realize safe sharing of data.
The invention also provides a method for detecting the health of the aged, and the method is shown in fig. 3, and is a schematic flow chart of an embodiment of the method for detecting the health of the aged. The old person health detection method may include steps S301 to S304, wherein:
step S301: body parameter data and voice data of a user are acquired.
Specifically, body parameter data such as blood pressure, heart rate and body temperature of a user are collected through intelligent wearable equipment, such as an intelligent bracelet. The intelligent home is used for collecting voice data of a user, wherein the voice data comprise self-speaking of the user, talking voice data of the user, speaking interval frequency of the user and the like.
Step S302: and acquiring service data generated when different service institutions and medical institutions serve users.
Specifically, the service institutions include other service institutions such as communities, and the medical institutions include hospitals, clinics, and the like. The service data can be an inspection report when a user arrives at a hospital for a doctor, and the user exchanges voice data with the doctor; the community staff may access the registration information of the user, the voice information of the community staff communicating with the old, etc.
Step S303: and evaluating the physical health condition of the user according to the physical parameter data and the service data to generate a physical health evaluation result.
Specifically, step S203 may further include the following steps:
the body health assessment result is fed back to the user, and health risk early warning and countermeasure are provided for the user according to the body health assessment result;
for example, when the smart band worn by the user detects that the systolic blood pressure of the user is 140, the systolic blood pressure exceeds the range of the systolic blood pressure of the normal blood pressure, the detection result is fed back to the user in time, and the user is reminded not to do severe exercise. When the systolic pressure of the blood pressure of the user is 170, the user is close to the hypertension risk, the detection result is fed back to the user in time, and the user is reminded to seek medical advice as soon as possible.
Providing the physical health of all elderly people within the service facility;
classifying all the old people according to the health conditions of the old people in the service mechanism, and reminding the service mechanism staff to conduct different countermeasures for the old people with different health levels.
In this embodiment, the health class may be classified into health, low risk, and high risk. For example, when the smart band worn by the user detects that the systolic blood pressure of the user is 140, the systolic blood pressure exceeds the range of the systolic blood pressure of the normal blood pressure, the detection result is fed back to the service mechanism in time, and the service mechanism staff is reminded to remind the user of not carrying out severe exercise by telephone. When the systolic pressure of the blood pressure of the user is 170, the detection result is fed back to the service mechanism in time near to the hypertension critical disease, and the staff of the service mechanism is reminded to visit the user to assist the user to seek medical attention from the medical mechanism.
Step S304: analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result;
in this embodiment, the voice data in the voice data and the service data are analyzed to analyze the emotional state and the psychological state of the user, and the psychological health condition of the user is evaluated according to the emotional state and the psychological state. Specifically, the emotion state of the user is estimated according to the change of the sound characteristics, for example, the voice of the user speaking is very low and slow, and the current emotion of the user is judged to be low; and if the voice tone of the user speaking is suddenly increased and the voice speed is accelerated, judging that the current emotion fluctuation of the user is larger. And evaluating the psychological state of the user by identifying negative words contained in the voice data, for example, judging that a great psychological problem exists in the user when negative words such as death, liveness and meaningless are identified in the voice data.
Step S305: the body parameter data, the voice data, and the service data are synchronized into respective nodes of a blockchain.
Uploading the body parameter data, the voice data, and the service data into a blockchain: corresponding summary information is obtained based on the body parameter data, the voice data and the service data, and specifically, the summary information is obtained by hashing the body parameter data, the voice data and the service data, for example, the summary information is obtained by using a sha256s algorithm. Uploading summary information to the blockchain can ensure its security and fair transparency to the user. The user device may download the summary information from the blockchain to verify whether the body parameter data, the voice data, and the service data are tampered with. The blockchain referred to in this example is a novel mode of application for computer technology such as distributed data storage, point-to-point transmission, consensus mechanisms, encryption algorithms, and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
According to the old people health detection method provided by the embodiment, firstly, physical parameter data and voice data of a user are obtained, and service data generated when different service institutions and medical institutions serve the user are obtained; further, according to the body parameter data and the service data, the body health condition of the user is evaluated to generate a body health evaluation result; analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result; and finally, synchronizing the body parameter data, the voice data and the service data to each node of a block chain, so as to realize sharing of detection data among service institutions and comprehensively and actively ensure physical and mental health of the old.
The invention also provides a computer device, and referring to fig. 4, the hardware architecture diagram of the computer device is suitable for realizing the old people health detection method.
In the present embodiment, the computer device 400 is a device capable of automatically performing numerical calculation and/or information processing in accordance with a preset or stored instruction. For example, it may be a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server, or a rack server (including a stand-alone server or a server cluster composed of a plurality of servers), etc. As shown in fig. 4, computer device 400 includes at least, but is not limited to: memory 410, processor 420, and network interface 430 may be communicatively linked to each other via a system bus. Wherein:
the memory 410 includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 410 may be an internal storage module of the computer device 500, such as a hard disk or memory of the computer device 400. In other embodiments, the memory 410 may also be an external storage device of the computer device 400, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the computer device 400. Of course, the memory 410 may also include both internal memory modules of the computer device 400 and external memory devices. In this embodiment, the memory 410 is typically used to store the operating system and various types of application software installed on the computer device 400, such as program code for a data processing method based on the QUIC protocol stack. In addition, the memory 410 may also be used to temporarily store various types of data that have been output or are to be output.
The processor 420 may be a central processing unit (Central Processing Unit, simply CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 520 is generally used to control overall operation of the computer device 400, such as performing control and processing related to data interaction or communication with the computer device 400, and the like. In this embodiment, the processor 420 is used to execute program code or process data stored in the memory 410.
The network interface 430 may include a wireless network interface or a wired network interface, the network interface 430 typically being used to establish a communication link between the computer device 400 and other computer devices. For example, the network interface 530 is used to connect the computer device 400 to an external terminal through a network, establish a data transmission channel and a communication link between the computer device 400 and the external terminal, and the like. The network may be a wireless or wired network such as an Intranet (Intranet), the Internet (Internet), a global system for mobile communications (Global System of Mobile communication, abbreviated as GSM), wideband code division multiple access (Wideband Code Division Multiple Access, abbreviated as WCDMA), a 4G network, a 5G network, bluetooth (Bluetooth), wi-Fi, etc.
It should be noted that FIG. 4 only shows a computer device having components 410-430, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead.
In this embodiment, the method for detecting the health of the elderly person stored in the memory 410 may be further divided into one or more program modules and executed by one or more processors (the processor 420 in this embodiment) to complete the present application.
The present invention also provides a readable storage medium having stored thereon computer readable instructions which when executed by a processor perform the steps of:
acquiring physical parameter data and voice data of a user;
acquiring service data generated when different service institutions and medical institutions serve users;
evaluating the physical health condition of the user according to the physical parameter data and the service data to generate a physical health evaluation result;
analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result;
the body parameter data, the voice data, and the service data are synchronized into respective nodes of a blockchain.
In this embodiment, the readable storage medium includes a flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the readable storage medium may be an internal storage unit of a computer device, such as a hard disk or a memory of the computer device. In other embodiments, the readable storage medium may also be an external storage device of a computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. that are provided on the computer device. Of course, the readable storage medium may also include both internal storage units of a computer device and external storage devices. In this embodiment, the readable storage medium is typically used to store an operating system installed on a computer device and various types of application software, such as program codes of the data processing method based on the QUIC protocol stack in the embodiment, and the like. In addition, the readable storage medium may also be used to temporarily store various types of data that have been output or are to be output.
The above-mentioned embodiment numbers of the present invention are merely for description and do not represent advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the methods of the embodiments described above may be implemented by means of software plus necessary general purpose hardware platforms, but of course also by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a mobile terminal, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (9)
1. An old person health detection system, the system comprising:
the user data acquisition module is used for acquiring physical parameter data and voice data of a user;
the organization module is used for collecting service data generated when different service institutions and medical institutions serve users; the application program module is used for acquiring the body parameter data, the voice data and the service data, and evaluating the body health condition of the user according to the body parameter data and the service data to generate a body health evaluation result;
the automatic machine learning module is used for analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result, and feeding back the psychological health evaluation result to the application program module;
the block chain module is used for synchronizing the physical parameter data, the voice data, the service data, the physical health evaluation result and the psychological health evaluation result into each node of a block chain;
the automatic machine learning module analyzes the emotion state and psychological state of the user according to the voice data collected by the user data collection module and the voice data in the service data, and evaluates the psychological health condition of the user according to the emotion state and the psychological state.
2. The elderly health detection system of claim 1, further comprising:
the data desensitization module is used for carrying out data desensitization on the body parameter data, the voice data and the service data acquired by the application program module so as to eliminate identifiable characteristics in sensitive data, and is also used for sending the desensitized data to the automatic machine learning module so as to be analyzed by the automatic machine learning module and sending the desensitized data to the blockchain module to realize data sharing.
3. The elderly health detection system of claim 1 wherein said application modules include a user-oriented application and an organization-oriented application; wherein,,
the application program facing the user is used for feeding back the physical health evaluation result and the psychological health evaluation result to the user, and providing health risk early warning and countermeasure for the user according to the physical health evaluation result and the psychological health evaluation result;
the organization-oriented application program is used for providing the physical health evaluation results and the mental health evaluation results of all the old people in the service mechanism to the service mechanism and providing the physical health evaluation results and the mental health evaluation results of the user to the medical mechanism.
4. The senior health detection system of claim 3, wherein the organization oriented application is further configured to categorize all seniors in the service facility based on their health assessment results and to alert the service facility staff to take different countermeasures for the seniors of different health levels.
5. The elderly health detection system of claim 4 wherein said application module is further configured to record user ratings of quality of service of said service and said medical facility and to store the ratings results to said blockchain module.
6. The elderly health detection system of claim 1 wherein the automated machine learning module evaluates a user's emotional state based on changes in sound characteristics by identifying negative words contained in the speech data.
7. A method for detecting the health of an elderly person, the method comprising:
acquiring physical parameter data and voice data of a user;
acquiring service data generated when different service institutions and medical institutions serve users;
evaluating the physical health condition of the user according to the physical parameter data and the service data to generate a physical health evaluation result;
analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result;
synchronizing the physical parameter data, the voice data, the service data, the physical health assessment results, and the mental health assessment results into each node of a blockchain;
the service data includes voice data of a user talking,
wherein analyzing the voice data and the service data to evaluate the mental health of the user generates a mental health evaluation result includes: analyzing the emotion state and the psychological state of the user according to the collected voice data and the voice data in the service data through an automatic machine learning algorithm, and evaluating the psychological health condition of the user according to the emotion state and the psychological state.
8. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
acquiring physical parameter data and voice data of a user;
acquiring service data generated when different service institutions and medical institutions serve users;
evaluating the physical health condition of the user according to the physical parameter data and the service data to generate a physical health evaluation result;
analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result;
synchronizing the physical parameter data, the voice data, the service data, the physical health assessment results, and the mental health assessment results into each node of a blockchain;
the service data includes voice data of a user talking,
wherein analyzing the voice data and the service data to evaluate the mental health of the user generates a mental health evaluation result includes: analyzing the emotion state and the psychological state of the user according to the collected voice data and the voice data in the service data through an automatic machine learning algorithm, and evaluating the psychological health condition of the user according to the emotion state and the psychological state.
9. A readable storage medium having stored thereon a computer program, characterized by: the computer program when executed by a processor performs the steps of:
acquiring physical parameter data and voice data of a user;
acquiring service data generated when different service institutions and medical institutions serve users;
evaluating the physical health condition of the user according to the physical parameter data and the service data to generate a physical health evaluation result;
analyzing the voice data and the service data to evaluate the psychological health condition of the user to generate a psychological health evaluation result;
synchronizing the physical parameter data, the voice data, the service data, the physical health assessment results, and the mental health assessment results into each node of a blockchain;
the service data includes voice data of a user talking,
wherein analyzing the voice data and the service data to evaluate the mental health of the user generates a mental health evaluation result includes: analyzing the emotion state and the psychological state of the user according to the collected voice data and the voice data in the service data through an automatic machine learning algorithm, and evaluating the psychological health condition of the user according to the emotion state and the psychological state.
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| CN202010752335.4A CN111899878B (en) | 2020-07-30 | 2020-07-30 | Old person health detection system, method, computer device and readable storage medium |
| PCT/CN2020/111627 WO2021174777A1 (en) | 2020-07-30 | 2020-08-27 | Elderly person health detection system and method, computer device, and readable storage medium |
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| CN112967806A (en) * | 2021-02-26 | 2021-06-15 | 平安科技（深圳）有限公司 | Health detection method, device, equipment and storage medium |
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| CN115456841B (en) * | 2022-09-14 | 2023-07-07 | 江苏护理职业学院 | Method and system for analyzing configuration current situation characteristics of pension service mechanism |
| CN115662631B (en) * | 2022-10-26 | 2023-11-17 | 上海柚纯数字科技有限公司 | Nursing home management system based on AI intelligent discrimination |
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| CN115760525A (en) * | 2022-11-28 | 2023-03-07 | 江苏中科西北星信息科技有限公司 | Intelligent old age care system and method based on Internet of things |
| CN116884611B (en) * | 2023-07-11 | 2024-02-13 | 浙江万航信息科技有限公司 | Teenager physical health intervention method and device, storage medium and electronic equipment |
| CN116913541A (en) * | 2023-09-12 | 2023-10-20 | 万链指数(青岛)信息科技有限公司 | Health data sharing method and system based on Internet of Things |
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