CN115721283A - Heart rate health early warning method and system, computer equipment and medium - Google Patents
Heart rate health early warning method and system, computer equipment and medium Download PDFInfo
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Abstract
The invention relates to the technical field of computers and the field of digital medical treatment, and discloses a heart rate health early warning method, a heart rate health early warning system, computer equipment and a medium, wherein the method comprises the following steps: monitoring and acquiring a heart rate data sequence and a target human body state in a preset period; preprocessing the heart rate data sequence; determining a standard heart rate data interval value under a target human body state; and matching an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and performing heart rate health early warning based on the early warning level. Because this application is through monitoring and heart rate data sequence and the human state of target of acquireing in the cycle of predetermineeing, can obtain the heart rate data sequence in the period nearest apart from the present moment, whether the user appears the room speed or the room is pounded out to the heart rate data sequence in this period of time after combining the standard heart rate data interval value under the human state of target and can carrying out data analysis, and carry out the early warning in advance when the room speed or the room is pounded out, thereby the sudden death rate has been reduced.
Description
Technical Field
The invention relates to the technical field of computers and the field of digital medical treatment, in particular to a heart rate health early warning method, a heart rate health early warning system, computer equipment and a medium.
Background
With the rise of technologies related to intelligent wearable devices, the devices may support health management for users, for example, by monitoring data such as heart rate, respiration, and motion of users. Sudden death refers to death rapidly occurring in a short period of time, and sudden death due to insufficient blood supply to the heart. In sudden death, the loss of effective contraction of the heart for 4-15 seconds can lead to syncope and convulsion, and the respiration slows rapidly. Because sudden death happens suddenly and the effective rescue time is very short, only 7-10 minutes, the user can not complete self rescue usually, or no other person is present when sudden death happens, so that the rescue rate of the sudden death user is very low. Along with the continuous development of intelligent wearing equipment, research personnel desire to carry out effective early warning through intelligent wearing equipment in the golden time before the user takes place sudden death.
In some current early warning schemes, wearing equipment detects out user's rest heart rate, motion heart rate etc. at first through application, then directly shows the data that detect for the user to carry out simple early warning when the heart rate at a certain moment exceeds maximum heart rate or equals minimum heart rate. Because the room speed or the room flutter can occur in a short time before sudden death, the early warning of the room speed or the room flutter cannot adopt the existing early warning mode of the heart rate at a single moment to carry out early warning, so that a user cannot effectively and timely carry out early warning when the room speed or the room flutter occurs, and the sudden death rate is increased.
Disclosure of Invention
Based on this, it is necessary to provide a heart rate health early warning method, a heart rate health early warning system, a computer device and a medium for solving the problem that a user cannot effectively and timely perform early warning when the user experiences room speed or room flutter.
A heart rate health warning method comprises the following steps: monitoring and acquiring a heart rate data sequence and a target human body state in a preset period; preprocessing the heart rate data sequence to generate a preprocessed heart rate data sequence; determining a standard heart rate data interval value under a target human body state; and matching the early warning level according to the pre-processed heart rate data sequence and the standard heart rate data interval value, and performing heart rate health early warning based on the early warning level.
In one embodiment, before monitoring and acquiring the heart rate data sequence and the target human body state in the preset period, the method further includes: acquiring a historical heart rate data set, and constructing a dynamic historical heart rate database according to the historical heart rate data set; determining a first historical heart rate data set in a motion state and a second historical heart rate data set in a rest state according to data in the dynamic historical heart rate database; establishing a heart rate data interval value in a motion state according to the first historical heart rate data set and pre-recorded human body basic information; and constructing a heart rate data interval value in a resting state according to the second historical heart rate data set and the pre-recorded human body basic information.
In one embodiment, constructing a dynamic historical heart rate database from historical heart rate data sets includes: determining data extraction time according to the current time and a target time interval; deleting all data in the dynamic historical heart rate database, and extracting target historical heart rate data between the data extraction time and the current time from the historical heart rate data set; storing the target historical heart rate data to a dynamic historical heart rate database; and when the current time enters the next time, continuously executing the step of determining the data extraction time according to the current time and the target time interval.
In one embodiment, pre-processing the heart rate data sequence to generate a pre-processed heart rate data sequence includes: processing the heart rate data sequence by adopting a recursive average filtering algorithm to generate a preprocessed heart rate data sequence; or, a sliding window is established by adopting a sliding window algorithm; calculating an effective value according to the data of the dynamic historical heart rate database, and binding the effective value and the sliding window in a correlation manner to obtain a target sliding window; sequentially inputting the heart rate data sequence into a target sliding window according to the time sequence of acquisition for filtering, and outputting a plurality of effective heart rate data; a plurality of valid heart rate data is determined as a pre-processed heart rate data sequence.
In one embodiment, determining the standard heart rate data interval value in the target human body state comprises: when the target human body state is a motion state, determining the heart rate data interval value in the motion state as a standard heart rate data interval value in the target human body state; or when the target human body state is a resting state, determining the heart rate data interval value in the resting state as a standard heart rate data interval value in the target human body state.
In one embodiment, matching the pre-warning level with the standard heart rate data interval value according to the pre-processed heart rate data sequence includes: judging whether low heart rate data smaller than the lower limit value of the standard heart rate data interval value exists in the preprocessed heart rate data sequence or not; if low heart rate data smaller than the lower limit value of the standard heart rate data interval value exist, determining that the heart rate data meet the sudden death condition, and matching the early warning level according to the duration of the low heart rate data; if the low heart rate data smaller than the lower limit value of the standard heart rate data interval value does not exist, judging whether the preprocessed heart rate data sequence has high heart rate data larger than the upper limit value of the standard heart rate data interval value; if high heart rate data larger than the upper limit value of the standard heart rate data interval value exist, determining that the heart rate data meet the sudden death condition, and matching the early warning level according to the duration of the high heart rate data; and if the high heart rate data larger than the upper limit value of the standard heart rate data interval value does not exist, continuing to return to the step of monitoring and acquiring the heart rate data sequence and the target human body state in the preset period.
In one embodiment, the heart rate health warning based on the warning level comprises: when the early warning level is greater than a preset level threshold, acquiring current position information; constructing heart rate health early warning information according to the current position information and the pre-input human body basic information; and sending the heart rate health early warning information to an early warning client, and starting a preset early warning service to perform early warning reminding.
A heart rate health warning system, the system comprising: the parameter monitoring and acquiring module is used for monitoring and acquiring a heart rate data sequence and a target human body state in a preset period; the data preprocessing module is used for preprocessing the heart rate data sequence to generate a preprocessed heart rate data sequence; the standard heart rate data interval value determining module is used for determining a standard heart rate data interval value in a target human body state; and the heart rate health early warning module is used for matching the early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value and carrying out heart rate health early warning based on the early warning level.
A computer device comprising a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the heart rate health warning method described above.
A medium having computer readable instructions stored thereon, which, when executed by one or more processors, cause the one or more processors to perform the steps of the heart rate health pre-warning method described above.
According to the heart rate health early warning method, the heart rate health early warning system, the heart rate data sequence and the target human body state in the preset period are firstly monitored and obtained by the heart rate health early warning system, then the heart rate data sequence is preprocessed, the preprocessed heart rate data sequence is generated, a standard heart rate data interval value in the target human body state is determined, an early warning level is matched according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and heart rate health early warning is carried out based on the early warning level. Because this application is through monitoring and heart rate data sequence and the human state of target of acquireing in the cycle of predetermineeing, can obtain the heart rate data sequence in the time of being nearest apart from the present moment, whether the user appears the room speed or the room is pounded to the heart rate data sequence in this time can accurate judgement in the standard heart rate data interval value under the human state of combination target to carry out the early warning in advance when the room speed appears or the room is pounded, thereby the sudden death rate has been reduced.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is an environment diagram for implementing a heart rate health warning method provided in an embodiment of the present application;
FIG. 2 is a schematic diagram of an internal structure of a computer device according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a method for heart rate health warning provided in an embodiment of the present application;
FIG. 4 is a schematic block diagram of a heart rate health warning process provided in one embodiment of the present application;
FIG. 5 is a schematic diagram of a method for heart rate health warning provided in another embodiment of the present application;
fig. 6 is a schematic system structure diagram of a heart rate health early warning system provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish one element from another.
Fig. 1 is a diagram of an implementation environment of a heart rate health warning method provided in an embodiment, as shown in fig. 1, in the implementation environment, including a server 110 and a client 120.
The server 110 may be a server, which may specifically be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like, for example, a server device for heart rate health warning. The server 110 monitors and acquires a heart rate data sequence and a target human body state in a preset period, the server 110 preprocesses the heart rate data sequence to generate a preprocessed heart rate data sequence, the server 110 determines a standard heart rate data interval value in the target human body state, the server 110 matches an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, carries out heart rate health early warning based on the early warning level, and sends an early warning result to the client 120.
It should be noted that the client 120 may be, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, and the like. The server 110 and the client 120 may be connected through bluetooth, USB (Universal Serial Bus), or other communication connection methods, which is not limited herein.
FIG. 2 is a diagram showing an internal configuration of a computer device according to an embodiment. As shown in fig. 2, the computer device includes a processor, a medium, a memory, and a network interface connected through a system bus. The computer device comprises a medium, an operating system, a database and computer readable instructions, wherein the database can store control information sequences, and the computer readable instructions can enable a processor to realize a heart rate health early warning method when being executed by the processor. The processor of the computer device is used for providing calculation and control capability and supporting the operation of the whole device. The memory of the computer device may have computer readable instructions stored thereon that, when executed by the processor, cause the processor to perform a heart rate fitness pre-warning method. The network interface of the computer device is used for connecting and communicating with the terminal. Those skilled in the art will appreciate that the architecture shown in fig. 2 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components. Wherein the medium is a readable storage medium.
The heart rate health warning method provided by the embodiment of the present application will be described in detail below with reference to fig. 3 to 5. The method may be implemented in dependence on a computer program, operable on a heart rate health warning system based on a von neumann architecture. The computer program may be integrated into the application or may run as a separate tool-like application.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence base technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, large heart rate health early warning technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
Referring to fig. 3, a schematic flow chart of a heart rate health warning method is provided in the embodiment of the present application, and is applied to an intelligent wearable device. As shown in fig. 3, the method of the embodiment of the present application may include the following steps:
s101, monitoring and acquiring a heart rate data sequence and a target human body state in a preset period;
wherein, intelligence wearing equipment can be healthy bracelet, iWatch, other intelligent wrist-watches. The preset period is a period of time that can characterize the chamber velocity or the chamber flutter process, determined based on the user basic information. The heart rate data sequence is composed of heart rate data measured over a plurality of consecutive target times, for example each target time may be one minute, the heart rate data being the number of heart beats of the user within one minute. The target human body state may be specifically classified into a moving state and a resting state. Both ventricular flutter, also known as ventricular flutter, and ventricular velocity, also known as ventricular tachycardia, belong to the ventricular tachycardias.
In one possible implementation manner, the intelligent wearable device monitors and acquires a heart rate data sequence and a target human body state in a preset period. For example, the intelligent wearable device firstly monitors heart rate data of a user in real time, when the monitoring duration reaches one minute, the heart rate data of one minute can be taken as the heart rate data for caching, then the heart rate data of one minute is continuously monitored and taken as the heart rate data for caching, and when the duration formed by a plurality of one minutes reaches a preset period, the cached heart rate data of a plurality of one minutes is obtained, so that a heart rate data sequence is obtained.
The human body state per minute in the preset period can be determined according to the gyroscope or gps of the intelligent wearable device, a plurality of human body states are obtained, a target difference value of the number of times of the running state and the number of times of the resting state in the plurality of human body states is calculated, and when the difference value is larger than a preset threshold value, the motion state is determined to be the target human body state. Or when the difference value is less than or equal to the preset threshold value, determining the rest state as the target human body state.
Further, before monitoring and acquiring the heart rate data sequence and the target human body state in the preset period, a heart rate data interval value in a motion state and a heart rate data interval value in a rest state need to be established. The method comprises the steps of firstly obtaining a historical heart rate data set, constructing a dynamic historical heart rate database according to the historical heart rate data set, then determining a first historical heart rate data set in a motion state and a second historical heart rate data set in a rest state according to data in the dynamic historical heart rate database, secondly constructing a heart rate data interval value in the motion state according to the first historical heart rate data set and human body basic information recorded in advance, and finally constructing a heart rate data interval value in the rest state according to the second historical heart rate data set and the human body basic information recorded in advance. According to the heart rate data interval value establishing method and device, the heart rate data interval value of each user standard can be established by combining human body basic information input by each person in advance and historical heart rates, and reference data can be provided for actual sudden death to be compared and analyzed.
Specifically, when a dynamic historical heart rate database is built according to a historical heart rate data set, firstly, the data extraction time is determined according to the current time and the target time interval, then all data in the dynamic historical heart rate database are deleted, target historical heart rate data between the data extraction time and the current time are extracted from the historical heart rate data set, secondly, the target historical heart rate data are stored in the dynamic historical heart rate database, and finally, when the current time enters the next time, the step of determining the data extraction time according to the current time and the target time interval is continuously executed.
Specifically, the basic information of the human body can be medical data, such as personal health files, prescriptions, examination reports and the like.
In one possible implementation, the medical text may be a medical Electronic Record (Electronic Healthcare Record), an Electronic personal health Record, including a series of Electronic records with a stored value to be checked, such as a medical Record, an electrocardiogram, and a medical image.
S102, preprocessing the heart rate data sequence to generate a preprocessed heart rate data sequence;
the preprocessing is to remove the obviously higher or obviously lower error heart rate data in the heart rate data sequence to obtain a correct data set. This operation may be based on a recursive average filtering algorithm or a sliding window algorithm.
In a possible implementation manner, when the heart rate data sequence is preprocessed to generate a preprocessed heart rate data sequence, the heart rate data sequence is processed by adopting a recursive average filtering algorithm to generate the preprocessed heart rate data sequence. The method and the device can quickly remove abnormal data in the heart rate data sequence by adopting a recursive average filtering algorithm.
In another possible implementation manner, when the heart rate data sequence is preprocessed to generate the preprocessed heart rate data sequence, firstly, a sliding window is created by adopting a sliding window algorithm, then, an effective value is calculated according to data of a dynamic historical heart rate database, the effective value and the sliding window are associated and bound to obtain a target sliding window, secondly, the heart rate data sequence is sequentially input into the target sliding window according to the collected time sequence to be filtered, a plurality of effective heart rate data are output, and finally, the plurality of effective heart rate data are determined to be the preprocessed heart rate data sequence. The abnormal data in the heart rate data sequence can be accurately removed by adopting a sliding window algorithm.
In an actual application scenario, a recursive average filtering algorithm may be used for processing in order to increase the speed, and a sliding window algorithm may be used for increasing the accuracy. The specific setting can be set according to actual conditions, and is not limited here.
S103, determining a standard heart rate data interval value under the target human body state;
the standard heart rate data interval value comprises a heart rate data interval value in a motion state and a heart rate data interval value in a rest state.
In the embodiment of the application, when the standard heart rate data interval value in the target human body state is determined, firstly, when the target human body state is in a motion state, the heart rate data interval value in the motion state is determined as the standard heart rate data interval value in the target human body state; or when the target human body state is a resting state, determining the heart rate data interval value in the resting state as a standard heart rate data interval value in the target human body state.
For example, the resting state adult male heart rate is 75-90, which is consistent with the resting state adult male heart rate of 60-100, and the resting state heart rate data interval value with the maximum value of 90 and the minimum value of 75 can be obtained.
And S104, matching an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and performing heart rate health early warning based on the early warning level.
In the embodiment of the application, when the pre-warning level is matched according to the pre-processed heart rate data sequence and the standard heart rate data interval value, firstly, whether low heart rate data smaller than the lower limit value of the standard heart rate data interval value exists in the pre-processed heart rate data sequence is judged; if low heart rate data smaller than the lower limit value of the standard heart rate data interval value exist, determining that the heart rate data meet the sudden death condition, and matching the early warning level according to the duration of the low heart rate data; if the low heart rate data smaller than the lower limit value of the standard heart rate data interval value does not exist, judging whether the preprocessed heart rate data sequence has high heart rate data larger than the upper limit value of the standard heart rate data interval value; if so, determining that the heart rate data meets the sudden death condition, and matching the early warning level according to the duration of the high heart rate data; and if not, continuously returning to the step of monitoring and acquiring the heart rate data sequence and the target human body state in the preset period.
In the embodiment of the application, when the heart rate health early warning is carried out based on the early warning level, firstly, when the early warning level is larger than a preset level threshold value, current position information is obtained, then, heart rate health early warning information is constructed according to the current position information and human body basic information which is input in advance, finally, the heart rate health early warning information is sent to an early warning client side, and pre-set early warning service is started to carry out early warning reminding.
In a possible implementation manner, the preset level threshold is a level threshold at which sudden death of a current user may occur, and if the preset level threshold is exceeded, heart rate health early warning needs to be performed in time, for example, the preset level threshold is level 2, and the current early warning level is level 4, it is described that the sudden death risk of the user may occur at this time.
For example, as shown in fig. 4, fig. 4 is a schematic block diagram of a flow of a heart rate health early warning process provided by the present application, first obtaining heart rate data and pre-entered human body basic information, then constructing a heart rate data interval value in a sport state and a heart rate data interval value in a rest state according to the heart rate data and the pre-entered human body basic information, then determining a heart rate data sequence and a target human body state in a preset period, preprocessing the heart rate data sequence, and finally matching an early warning level according to the preprocessed heart rate data sequence and the pre-processed heart rate data interval value, and performing heart rate health early warning based on the early warning level.
In the embodiment of the application, the heart rate health early warning system firstly monitors and acquires a heart rate data sequence and a target human body state in a preset period, then preprocesses the heart rate data sequence, generates a preprocessed heart rate data sequence, secondly determines a standard heart rate data interval value in the target human body state, finally matches an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and carries out heart rate health early warning based on the early warning level. Because this application is through monitoring and heart rate data sequence and the human state of target of acquireing in the cycle of predetermineeing, can obtain the heart rate data sequence in the time of being nearest apart from the present moment, whether the user appears the room speed or the room is pounded to the heart rate data sequence in this time can accurate judgement in the standard heart rate data interval value under the human state of combination target to carry out the early warning in advance when the room speed appears or the room is pounded, thereby the sudden death rate has been reduced.
Referring to fig. 5, a schematic flow chart of a heart rate health warning method is provided in the embodiment of the present application. As shown in fig. 5, the method of the embodiment of the present application may include the following steps:
s201, acquiring a historical heart rate data set, and constructing a dynamic historical heart rate database according to the historical heart rate data set;
s202, determining a first historical heart rate data set in a motion state and a second historical heart rate data set in a rest state according to data in a dynamic historical heart rate database;
s203, establishing a heart rate data interval value in a motion state according to the first historical heart rate data set and the pre-recorded human body basic information;
s204, establishing a heart rate data interval value in a resting state according to a second historical heart rate data set and pre-recorded human body basic information;
s205, monitoring and acquiring a heart rate data sequence and a target human body state in a preset period;
s206, preprocessing the heart rate data sequence to generate a preprocessed heart rate data sequence;
s207, when the target human body state is the motion state, determining the heart rate data interval value in the motion state as a standard heart rate data interval value in the target human body state; or when the target human body state is a resting state, determining the heart rate data interval value in the resting state as a standard heart rate data interval value in the target human body state;
s208, matching an early warning level according to the pre-processed heart rate data sequence and the standard heart rate data interval value, and acquiring current position information when the early warning level is greater than a preset level threshold value;
s209, heart rate health early warning information is constructed according to the current position information and the pre-recorded human body basic information;
and S210, sending the heart rate health early warning information to an early warning client, and starting a preset early warning service to perform early warning reminding.
In the embodiment of the application, the heart rate health early warning system firstly monitors and acquires a heart rate data sequence and a target human body state in a preset period, then preprocesses the heart rate data sequence, generates a preprocessed heart rate data sequence, secondly determines a standard heart rate data interval value in the target human body state, finally matches an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and carries out heart rate health early warning based on the early warning level. Because this application is through monitoring and heart rate data sequence and the human state of target of acquireing in the cycle of predetermineeing, can obtain the heart rate data sequence in the time of being nearest apart from the present moment, whether the user appears the room speed or the room is pounded to the heart rate data sequence in this time can accurate judgement in the standard heart rate data interval value under the human state of combination target to carry out the early warning in advance when the room speed appears or the room is pounded, thereby the sudden death rate has been reduced.
The following are embodiments of systems of the present invention that may be used to perform embodiments of methods of the present invention. For details which are not disclosed in the embodiments of the system of the present invention, reference is made to the embodiments of the method of the present invention.
Referring to fig. 6, a schematic structural diagram of a heart rate health warning system according to an exemplary embodiment of the present invention is shown. The heart rate health warning system may be implemented as all or part of a device, in software, hardware, or a combination of both. The system 1 comprises a parameter monitoring and acquiring module 10, a data preprocessing module 20, a standard heart rate data interval value determining module 30 and a heart rate health early warning module 40.
The parameter monitoring and acquiring module 10 is used for monitoring and acquiring a heart rate data sequence and a target human body state in a preset period;
the data preprocessing module 20 is configured to preprocess the heart rate data sequence to generate a preprocessed heart rate data sequence;
the standard heart rate data interval value determining module 30 is used for determining a standard heart rate data interval value in a target human body state;
and the heart rate health early warning module 40 is used for matching the early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and performing heart rate health early warning based on the early warning level.
It should be noted that, when the heart rate health early warning system provided in the foregoing embodiment executes the heart rate health early warning method, only the division of the functional modules is illustrated, and in practical application, the functions may be distributed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the heart rate health early warning system provided by the above embodiment and the heart rate health early warning method embodiment belong to the same concept, and the embodiment of the implementation process is described in detail in the method embodiment, which is not described herein again.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the embodiment of the application, the heart rate health early warning system firstly monitors and acquires a heart rate data sequence and a target human body state in a preset period, then preprocesses the heart rate data sequence, generates a preprocessed heart rate data sequence, secondly determines a standard heart rate data interval value in the target human body state, finally matches an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and carries out heart rate health early warning based on the early warning level. Because this application is through monitoring and heart rate data sequence and the human state of target of acquireing in the cycle of predetermineeing, can obtain the heart rate data sequence in the time of being nearest apart from the present moment, whether the user appears the room speed or the room is pounded to the heart rate data sequence in this time can accurate judgement in the standard heart rate data interval value under the human state of combination target to carry out the early warning in advance when the room speed appears or the room is pounded, thereby the sudden death rate has been reduced.
In one embodiment, a computer device is provided, the device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
monitoring and acquiring a heart rate data sequence and a target human body state in a preset period;
preprocessing the heart rate data sequence to generate a preprocessed heart rate data sequence;
determining a standard heart rate data interval value under a target human body state;
and matching an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and performing heart rate health early warning based on the early warning level.
In one embodiment, before the processor performs monitoring and acquiring the heart rate data sequence and the target human body state in the preset period, the following operations are further performed:
acquiring a historical heart rate data set, and constructing a dynamic historical heart rate database according to the historical heart rate data set;
determining a first historical heart rate data set in a motion state and a second historical heart rate data set in a rest state according to data in the dynamic historical heart rate database;
constructing a heart rate data interval value in a motion state according to a first historical heart rate data set and pre-input human body basic information;
and constructing a heart rate data interval value in a resting state according to the second historical heart rate data set and the pre-recorded human body basic information.
In one embodiment, the processor, when executing the construction of the dynamic historical heart rate database from the historical heart rate data set, specifically performs the following operations:
determining data extraction time according to the current time and a target time interval;
deleting all data in the dynamic historical heart rate database, and extracting target historical heart rate data between the data extraction time and the current time from the historical heart rate data set;
storing the target historical heart rate data to a dynamic historical heart rate database;
and when the current time enters the next time, continuously executing the step of determining the data extraction time according to the current time and the target time interval.
In one embodiment, the processor performs the following operation when performing the pre-processing on the heart rate data sequence and generating the pre-processed heart rate data sequence:
processing the heart rate data sequence by adopting a recursive average filtering algorithm to generate a preprocessed heart rate data sequence;
alternatively, the first and second electrodes may be,
adopting a sliding window algorithm to create a sliding window;
calculating an effective value according to the data of the dynamic historical heart rate database, and binding the effective value and the sliding window in a correlation manner to obtain a target sliding window;
sequentially inputting the heart rate data sequence into a target sliding window according to the time sequence of acquisition for filtering, and outputting a plurality of effective heart rate data;
a plurality of valid heart rate data is determined as a pre-processed heart rate data sequence.
In one embodiment, when the processor determines the standard heart rate data interval value in the target human body state, the following operations are specifically performed:
when the target human body state is a motion state, determining the heart rate data interval value in the motion state as a standard heart rate data interval value in the target human body state;
alternatively, the first and second electrodes may be,
and when the target human body state is a resting state, determining the heart rate data interval value in the resting state as a standard heart rate data interval value in the target human body state.
In one embodiment, when the pre-processed heart rate data sequence is matched with the standard heart rate data interval value according to the pre-processed heart rate data sequence, the following operations are specifically performed:
judging whether low heart rate data smaller than a lower limit value of a standard heart rate data interval value exists in the preprocessed heart rate data sequence or not;
if low heart rate data smaller than the lower limit value of the standard heart rate data interval value exist, determining that the heart rate data meet the sudden death condition, and matching the early warning level according to the duration of the low heart rate data;
if the low heart rate data smaller than the lower limit value of the standard heart rate data interval value does not exist, judging whether the preprocessed heart rate data sequence has high heart rate data larger than the upper limit value of the standard heart rate data interval value;
if high heart rate data larger than the upper limit value of the standard heart rate data interval value exists, determining that the heart rate data accords with the sudden death condition, and matching the early warning level according to the duration of the high heart rate data;
and if the high heart rate data larger than the upper limit value of the standard heart rate data interval value does not exist, continuously returning to the step of monitoring and acquiring the heart rate data sequence and the target human body state in the preset period.
In one embodiment, when the processor performs the heart rate health warning based on the warning level, the following operations are specifically performed:
when the early warning level is larger than a preset level threshold value, acquiring current position information;
constructing heart rate health early warning information according to the current position information and the pre-input human body basic information;
and sending the heart rate health early warning information to an early warning client, and starting a preset early warning service to perform early warning reminding.
In the embodiment of the application, the heart rate health early warning system firstly monitors and acquires a heart rate data sequence and a target human body state in a preset period, then preprocesses the heart rate data sequence, generates a preprocessed heart rate data sequence, secondly determines a standard heart rate data interval value in the target human body state, finally matches an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and carries out heart rate health early warning based on the early warning level. Because this application is through monitoring and heart rate data sequence and the human state of target of acquireing in the cycle of predetermineeing, can obtain the heart rate data sequence in the time of being nearest apart from the present moment, whether the user appears the room speed or the room is pounded to the heart rate data sequence in this time can accurate judgement in the standard heart rate data interval value under the human state of combination target to carry out the early warning in advance when the room speed appears or the room is pounded, thereby the sudden death rate has been reduced.
In one embodiment, a medium is presented having computer-readable instructions stored thereon which, when executed by one or more processors, cause the one or more processors to perform the steps of:
monitoring and acquiring a heart rate data sequence and a target human body state in a preset period;
preprocessing the heart rate data sequence to generate a preprocessed heart rate data sequence;
determining a standard heart rate data interval value under a target human body state;
and matching an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and performing heart rate health early warning based on the early warning level.
In one embodiment, before the processor performs monitoring and acquiring the heart rate data sequence and the target human body state in the preset period, the following operations are further performed:
acquiring a historical heart rate data set, and constructing a dynamic historical heart rate database according to the historical heart rate data set;
determining a first historical heart rate data set in a motion state and a second historical heart rate data set in a rest state according to data in the dynamic historical heart rate database;
establishing a heart rate data interval value in a motion state according to the first historical heart rate data set and pre-recorded human body basic information;
and constructing a heart rate data interval value in a resting state according to the second historical heart rate data set and the pre-recorded human body basic information.
In one embodiment, the processor, when executing the construction of the dynamic historical heart rate database from the historical heart rate data set, specifically performs the following operations:
determining data extraction time according to the current time and a target time interval;
deleting all data in the dynamic historical heart rate database, and extracting target historical heart rate data between the data extraction time and the current time from the historical heart rate data set;
storing the target historical heart rate data to a dynamic historical heart rate database;
and when the current time enters the next time, continuously executing the step of determining the data extraction time according to the current time and the target time interval.
In one embodiment, the processor performs the following operation when performing the pre-processing on the heart rate data sequence and generating the pre-processed heart rate data sequence:
processing the heart rate data sequence by adopting a recursive average filtering algorithm to generate a preprocessed heart rate data sequence;
alternatively, the first and second electrodes may be,
adopting a sliding window algorithm to create a sliding window;
calculating an effective value according to the data of the dynamic historical heart rate database, and binding the effective value and the sliding window in a correlation manner to obtain a target sliding window;
sequentially inputting the heart rate data sequence into a target sliding window according to the time sequence of acquisition for filtering, and outputting a plurality of effective heart rate data;
a plurality of valid heart rate data is determined as a pre-processed heart rate data sequence.
In one embodiment, when the processor determines the standard heart rate data interval value in the target human body state, the following operations are specifically performed:
when the target human body state is a motion state, determining the heart rate data interval value in the motion state as a standard heart rate data interval value in the target human body state;
alternatively, the first and second electrodes may be,
and when the target human body state is a resting state, determining the heart rate data interval value in the resting state as a standard heart rate data interval value in the target human body state.
In one embodiment, when the pre-processed heart rate data sequence is matched with the standard heart rate data interval value according to the pre-warning level, the processor specifically performs the following operations:
judging whether low heart rate data smaller than the lower limit value of the standard heart rate data interval value exists in the preprocessed heart rate data sequence or not;
if low heart rate data smaller than the lower limit value of the standard heart rate data interval value exist, determining that the heart rate data meet the sudden death condition, and matching the early warning level according to the duration of the low heart rate data;
if the low heart rate data smaller than the lower limit value of the standard heart rate data interval value does not exist, judging whether the preprocessed heart rate data sequence has high heart rate data larger than the upper limit value of the standard heart rate data interval value;
if high heart rate data larger than the upper limit value of the standard heart rate data interval value exist, determining that the heart rate data meet the sudden death condition, and matching the early warning level according to the duration of the high heart rate data;
and if the high heart rate data larger than the upper limit value of the standard heart rate data interval value does not exist, continuing to return to the step of monitoring and acquiring the heart rate data sequence and the target human body state in the preset period.
In one embodiment, when the processor performs the heart rate health warning based on the warning level, the following operations are specifically performed:
when the early warning level is larger than a preset level threshold value, acquiring current position information;
constructing heart rate health early warning information according to the current position information and the pre-input human body basic information;
and sending the heart rate health early warning information to an early warning client, and starting a preset early warning service to perform early warning reminding.
In the embodiment of the application, the heart rate health early warning system firstly monitors and acquires a heart rate data sequence and a target human body state in a preset period, then preprocesses the heart rate data sequence, generates a preprocessed heart rate data sequence, secondly determines a standard heart rate data interval value in the target human body state, finally matches an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and carries out heart rate health early warning based on the early warning level. Because this application is through monitoring and heart rate data sequence and the human state of target of acquireing in the cycle of predetermineeing, can obtain the heart rate data sequence in the time of being nearest apart from the present moment, whether the user appears the room speed or the room is pounded to the heart rate data sequence in this time can accurate judgement in the standard heart rate data interval value under the human state of combination target to carry out the early warning in advance when the room speed appears or the room is pounded, thereby the sudden death rate has been reduced.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer readable medium, and when executed, can include the processes of the embodiments of the methods described above. The medium may be a non-volatile medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a Random Access Memory (RAM).
All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above examples only show some embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that various changes and modifications can be made by those skilled in the art without departing from the spirit of the invention, and these changes and modifications are all within the scope of the invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A heart rate health early warning method is applied to intelligent wearable equipment and comprises the following steps:
monitoring and acquiring a heart rate data sequence and a target human body state in a preset period;
preprocessing the heart rate data sequence to generate a preprocessed heart rate data sequence;
determining a standard heart rate data interval value under the target human body state;
and matching an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value, and performing heart rate health early warning based on the early warning level.
2. The method of claim 1, wherein prior to the monitoring and acquiring the heart rate data sequence and the target human body state within the preset period, further comprising:
acquiring a historical heart rate data set, and constructing a dynamic historical heart rate database according to the historical heart rate data set;
determining a first historical heart rate data set in a motion state and a second historical heart rate data set in a rest state according to data in the dynamic historical heart rate database;
establishing a heart rate data interval value in a motion state according to the first historical heart rate data set and pre-recorded human body basic information;
and constructing a heart rate data interval value in a resting state according to the second historical heart rate data set and the pre-recorded human body basic information.
3. The method of claim 2, wherein the building a dynamic historical heart rate database from the historical heart rate data set comprises:
determining data extraction time according to the current time and a target time interval;
deleting all data in the dynamic historical heart rate database, and extracting target historical heart rate data between the data extraction time and the current time from the historical heart rate data set;
saving the target historical heart rate data to the dynamic historical heart rate database;
and when the current time enters the next time, continuously executing the step of determining the data extraction time according to the current time and the target time interval.
4. The method of claim 1, wherein the pre-processing the heart rate data sequence to generate a pre-processed heart rate data sequence comprises:
processing the heart rate data sequence by adopting a recursive average filtering algorithm to generate a preprocessed heart rate data sequence;
alternatively, the first and second electrodes may be,
adopting a sliding window algorithm to create a sliding window;
calculating an effective value according to data of the dynamic historical heart rate database, and performing associated binding on the effective value and the sliding window to obtain a target sliding window;
sequentially inputting the heart rate data sequence into the target sliding window according to the collected time sequence for filtering, and outputting a plurality of effective heart rate data;
determining the plurality of valid heart rate data as a pre-processed heart rate data sequence.
5. The method of claim 2, wherein the determining the standard heart rate data interval value for the target human state comprises:
when the target human body state is a motion state, determining the heart rate data interval value in the motion state as a standard heart rate data interval value in the target human body state;
alternatively, the first and second electrodes may be,
and when the target human body state is a resting state, determining the heart rate data interval value in the resting state as a standard heart rate data interval value in the target human body state.
6. The method of claim 1, wherein matching the pre-alarm level to the standard heart rate data interval value based on the pre-processed heart rate data sequence comprises:
judging whether low heart rate data smaller than the lower limit value of the standard heart rate data interval value exists in the preprocessed heart rate data sequence or not;
if low heart rate data smaller than the lower limit value of the standard heart rate data interval value exists, determining that the heart rate data meets a sudden death condition, and matching an early warning level according to the duration of the low heart rate data;
if the low heart rate data smaller than the lower limit value of the standard heart rate data interval value does not exist, judging whether the preprocessed heart rate data sequence has high heart rate data larger than the upper limit value of the standard heart rate data interval value;
if high heart rate data larger than the upper limit value of the standard heart rate data interval value exists, determining that the heart rate data meets a sudden death condition, and matching an early warning level according to the duration of the high heart rate data;
and if the high heart rate data larger than the upper limit value of the standard heart rate data interval value does not exist, continuing to return to the step of executing the monitoring and acquiring the heart rate data sequence and the target human body state in the preset period.
7. The method of claim 6, wherein the performing a heart rate health alert based on the alert level comprises:
when the early warning level is larger than a preset level threshold value, acquiring current position information;
constructing heart rate health early warning information according to the current position information and the pre-input human body basic information;
and sending the heart rate health early warning information to an early warning client, and starting a preset early warning service to perform early warning reminding.
8. The utility model provides a healthy early warning system of heart rate which characterized in that is applied to intelligent wearing equipment, the system includes:
the parameter monitoring and acquiring module is used for monitoring and acquiring a heart rate data sequence and a target human body state in a preset period;
the data preprocessing module is used for preprocessing the heart rate data sequence to generate a preprocessed heart rate data sequence;
the standard heart rate data interval value determining module is used for determining a standard heart rate data interval value under the target human body state;
and the heart rate health early warning module is used for matching an early warning level according to the preprocessed heart rate data sequence and the standard heart rate data interval value and carrying out heart rate health early warning based on the early warning level.
9. A computer device comprising a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the heart rate health warning method as claimed in any one of claims 1 to 7.
10. A medium having computer-readable instructions stored thereon, which, when executed by one or more processors, cause the one or more processors to perform the steps of the heart rate health warning method of any one of claims 1-7.
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| CN117874689B (en) * | 2024-03-13 | 2024-05-24 | 青岛云智霄凡科技有限公司 | Intelligent processing method for heart rate monitoring data |
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