CN113288049B

CN113288049B - Data acquisition method, terminal equipment and storage medium

Info

Publication number: CN113288049B
Application number: CN202010115816.4A
Authority: CN
Inventors: 吴宙真; 吴黄伟; 黄曦
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2020-02-24
Filing date: 2020-02-24
Publication date: 2026-01-23
Anticipated expiration: 2040-02-24
Also published as: CN113288049A; WO2021169443A1

Abstract

This application relates to the field of electronic technology and provides a data acquisition method, terminal device, and storage medium. The data acquisition method includes: if an interference event is detected during the data acquisition process, and the interference event is one that requires real-time processing, then the acquired data is saved, and the interference event is connected; simultaneously, background data acquisition is initiated; and the target acquisition data is obtained based on the data segments acquired before the interference event is connected and the background data segments. This application can continuously acquire data in the background while processing interference events requiring real-time processing. This allows for timely processing of events requiring real-time processing, continuous data acquisition without affecting the measurement process, and ensures that valid information acquired before the interference occurs is not discarded, avoiding the omission of some valid data. This effectively improves the reliability and usability of the acquired data and shortens the total measurement time.

Description

Data acquisition method, terminal equipment and storage medium

Technical Field

The present application relates to the field of electronics, and in particular, to a data acquisition method, a terminal device, and a storage medium.

Background

With rapid development of electronic technology, the wearable device can realize more and more functions, for example, can collect various physiological data of human body such as electrocardiosignals, blood oxygen signals and the like of the human body. The auxiliary machine learning method can effectively help to screen paroxysmal cardiovascular diseases such as atrial fibrillation, premature beat and the like through multiple effective single measurement in a long time. When various interferences such as call interference, information interference and the like occur in the single measurement process, the traditional wearable equipment can directly shield the interference, and the user is notified after the measurement is finished. Direct interference shielding can lead to users missing some important information, which can not be processed in time. In order to ensure that important information is processed in time, the existing wearable equipment interrupts measurement, and resumes the measurement again after the interference is over. However, interrupting the measurement may result in a difficulty in accumulating a sufficient number of valid measurements during a period dean of time, a symptom of a burst being easily missed, and restarting a new measurement may also result in loss of part of the valid data;

Therefore, the traditional wearable equipment data acquisition process has the defects that part of effective data is easy to miss on the premise of ensuring that important information is processed in time, so that the reliability and the availability of the acquired data are low, and the measurement time is long.

Disclosure of Invention

The application provides a data acquisition method, terminal equipment and a storage medium, which solve the problems that part of effective data is easy to miss, the reliability and the availability of acquired data are low, and the measurement time is long under the premise of ensuring that important information is processed in time in the traditional wearable equipment data acquisition process.

In order to achieve the above purpose, the application adopts the following technical scheme:

in a first aspect, a data acquisition method is provided, which may include:

If an interference event is detected in the data acquisition process and is to be processed in real time, the acquired data are saved, the interference event is accessed, and background data acquisition is started while the interference event is accessed;

and obtaining target acquisition data according to the data fragments acquired before the interference event and the data fragments acquired in the background.

Here, the target acquisition data may be used to help screen for paroxysmal cardiovascular disease.

According to the data acquisition method provided by the embodiment of the application, the background can be started to continuously acquire data while the interference event to be processed in real time is processed, and then after the interference is finished, the data segment before the access of the interference event and the data segment acquired by the background are spliced to obtain the target acquisition data, so that the event to be processed in real time can be processed in time, the data can be continuously acquired, the measurement process is not influenced, the acquired effective information before the interference is not discarded, the measurement process of screening the paroxysmal cardiovascular diseases can be continuously performed, the condition of missing part of effective data is effectively avoided, the accuracy of the analysis result of paroxysmal cardiovascular disease analysis based on the target acquisition data is improved, the reliability and the availability of the data are effectively improved, and the total measurement time consumption is shortened.

In a possible implementation manner of the first aspect, if an interference event occurs in the data acquisition process and the interference event is an interference event to be processed in real time, the method stores the acquired data, accesses the interference event, and starts the background data acquisition while accessing the interference event, and further includes:

If the data segments collected by the background have interference data segments, deleting the interference data segments to obtain effective data segments;

correspondingly, the obtaining the target acquisition data according to the data segment acquired before the access of the interference event and the data segment acquired in the background comprises the following steps:

and performing data splicing on the data fragments acquired before the access interference event and the effective data fragments to obtain target acquisition data.

In the above embodiment, because there may be a case (such as a mobile terminal device, etc.) that interferes with the acquired data during the access interference event, when there is an interference data segment in the data segment acquired in the background, the interference data segment is deleted, and then the saved data segment and the valid data segment from which the interference data segment is deleted are subjected to data stitching to obtain the target acquired data, which can effectively reduce data interference, so as to improve the accuracy of the analysis result of performing the paroxysmal cardiovascular disease analysis based on the target acquired data.

In a possible implementation manner of the first aspect, before deleting the interference data segment if the interference data segment exists in the data segment collected in the background, the method further includes:

Collecting motion data and determining a motion amplitude of the motion data according to the motion data;

Determining a target data segment meeting a preset motion state in data acquired simultaneously with the motion data according to the motion amplitude of the motion data;

And if the interference degree of the target data segment exceeds a preset interference range, determining the target data segment as an interference data segment.

In the above embodiment, by combining the motion data and the target data segment, it can be effectively determined whether the interference data segment exists in the data segment collected in the background.

In a possible implementation manner of the first aspect, the obtaining the target collected data according to the data segment collected before the access to the interference event and the data segment collected in the background includes:

and performing data splicing according to the acquisition time of the data fragments acquired before the access interference event and the acquisition time of the data fragments acquired in the background to obtain the target acquisition data.

In the above embodiment, the data segments are spliced based on the acquisition time, so as to obtain a continuous acquisition data, and the continuous acquisition data is the target acquisition data for data analysis.

In a possible implementation manner of the first aspect, if an interference event occurs in the process of monitoring data acquisition and the interference event is an interference event to be processed in real time, the method stores acquired data, accesses the interference event, and before starting background data acquisition while accessing the interference event, further includes:

monitoring whether an interference event occurs in the data acquisition process;

If an interference event occurs in the data acquisition process, judging whether the interference event is an interference event to be processed in real time.

In the embodiment, whether the interference event occurs in the data acquisition process is monitored in real time, and whether the interference event is the interference event to be processed in real time which needs to be processed in real time is identified under the condition that the interference event is monitored, so that a corresponding processing strategy can be effectively selected according to the type of the interference event, data for helping to screen the paroxysmal cardiovascular diseases can be continuously acquired, the reliability and the availability of the data are effectively improved, and the total time consumption is shortened.

In a possible implementation manner of the first aspect, the determining whether the interference event is an interference event to be processed in real time if the interference event occurs in the data acquisition process includes:

Acquiring the priority of the interference event;

If the priority of the interference event is a first preset priority level, determining that the interference event is an interference event to be processed in real time;

and if the priority of the interference event is a second preset priority level, determining that the interference event is an interference event which is not to be processed in real time.

In the embodiment, the priority of each interference event can be preset, when the interference event occurs, the priority of the interference event can be determined, and then the corresponding processing strategy is selected based on the priority of the interference event, so that the reliability and the availability of data acquisition in the data acquisition process are improved, and the total time consumption is shortened.

In a possible implementation manner of the first aspect, the data acquisition method further includes:

If the interference event is monitored to occur in the acquisition process and is not to be processed in real time, the interference event is accessed after the measurement is finished.

In the above embodiment, during the data acquisition process, the interference event which is not to be processed in real time may not be processed temporarily, and the data acquisition is continued until the measurement is completed, so that the measurement process is not affected, and the interference event is accessed after the measurement is completed, so that the interference event is ensured to be processed in time and not to be ignored.

In a second aspect, an embodiment of the present application provides a terminal device, including:

the first processing unit is used for storing the acquired data and accessing the interference event if the interference event occurs in the data acquisition process and the interference event is the interference event to be processed in real time, and starting background data acquisition while accessing the interference event;

And the splicing unit is used for obtaining target acquisition data according to the acquired data fragments before the access of the interference event and the acquired data fragments after the access of the interference event.

In a possible implementation manner of the second aspect, the terminal device further includes a deleting unit, where the deleting unit is configured to delete the interference data segment if the interference data segment exists in the data segment collected in the background, so as to obtain a valid data segment. Correspondingly, the splicing unit is specifically used for carrying out data splicing on the data segment acquired before the interference event and the effective data segment to obtain target acquisition data.

In a possible implementation manner of the second aspect, the terminal device further includes a first determining unit, a second determining unit, and a checking unit.

The first determining unit is used for collecting motion data and determining the motion amplitude of the motion data according to the motion data.

The second determining unit is configured to determine, according to the motion amplitude of the motion data, a target data segment meeting a preset motion state in data acquired simultaneously with the motion data.

And the verification unit is used for determining that the target data fragment is an interference data fragment if the interference degree of the target data fragment exceeds a preset interference range.

In a possible implementation manner of the second aspect, the above-mentioned splicing unit is specifically configured to perform data splicing according to an acquisition time of a data segment acquired before the access to the interference event and an acquisition time of a data segment acquired in the background, so as to obtain the target acquisition data.

In a possible implementation manner of the second aspect, the terminal device further includes a monitoring unit and an identifying unit.

The monitoring unit is used for monitoring whether an interference event occurs in the data acquisition process.

The identification unit is used for judging whether the interference event is an interference event to be processed in real time if the interference event occurs in the data acquisition process.

In a possible implementation manner of the second aspect, the identifying unit includes a priority acquiring unit and a judging unit.

The priority acquisition unit is used for acquiring the priority of the interference event.

The judging unit is used for determining that the interference event is an interference event to be processed in real time if the priority of the interference event is a first preset priority level, and determining that the interference event is an interference event not to be processed in real time if the priority of the interference event is a second preset priority level.

In a possible implementation manner of the second aspect, the terminal device further includes a second processing unit, where the second processing unit is configured to access the interference event after the measurement is finished if it is detected that the interference event occurs in the acquisition process and the interference event is an interference event that is not to be processed in real time.

In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the data collection method according to the first aspect when executing the computer program.

In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which, when executed by a processor, implements a data acquisition method as described in the first aspect above.

In a fifth aspect, an embodiment of the present application provides a computer program product, which, when run on a terminal device, causes the terminal device to perform the data acquisition method according to any one of the first aspects above.

It will be appreciated that the advantages of the second to fifth aspects may be found in the relevant description of the first aspect, and are not described here again.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic hardware structure diagram of a terminal device to which a data acquisition method according to an embodiment of the present application is applicable;

FIG. 2 is a block diagram illustrating a data acquisition system according to an embodiment of the present application;

fig. 3 is a schematic flow chart of a data acquisition method according to an embodiment of the present application;

FIG. 4 is a schematic flow chart of a process for identifying interference events to be processed in real time according to an embodiment of the present application;

fig. 5 is a schematic diagram of a data structure of target acquisition data obtained by splicing a data segment acquired before an access interference event and a data segment acquired in the background according to an embodiment of the present application;

fig. 6 is a schematic diagram of a data structure of target acquisition data obtained by splicing a data segment acquired before an access interference event and a valid data segment according to an embodiment of the present application

Fig. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present application;

Fig. 8 is a schematic structural diagram of another terminal device according to an embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

As used in the present description and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".

Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance.

Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

The data acquisition method provided by the embodiment of the application can be applied to terminal equipment, wherein the terminal equipment can be wearable equipment, mobile phones, tablet computers, vehicle-mounted equipment, augmented reality (augmented reality, AR)/Virtual Reality (VR) equipment, notebook computers, ultra-mobile personal computer (UMPC), netbooks, personal digital assistants (personal DIGITAL ASSISTANT, PDA) and other mobile terminals, and the embodiment of the application does not limit the specific types of the terminal equipment.

For example, the terminal device may be in particular a cellular telephone, a cordless telephone, a session initiation protocol (Session Initiation Protocol, SIP) phone, a Personal digital processing (Personal DIGITAL ASSISTANT, PDA) device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, a handheld communication device, a handheld computing device and/or other devices for network communication over a wireless system as well as a next generation communication system, e.g. a mobile terminal in a 5G network or a mobile terminal in a future evolved public land mobile network (Public Land Mobile Network, PLMN) network, etc.

By way of example, but not limitation, when the terminal device is a wearable device, the wearable device may also be a generic name for applying wearable technology to intelligently design daily wear, developing wearable devices, such as glasses, gloves, watches, apparel, shoes, and the like. The wearable device is a portable device that is worn directly on the body or integrated into the clothing or accessories of the user. The wearable device is not only a hardware device, but also can realize a powerful function through software support, data interaction and cloud interaction. The generalized wearable intelligent device comprises full functions, large size, complete or partial functions which can be realized independent of the intelligent mobile phone, such as a smart watch or a smart glasses, and is only focused on certain application functions, and needs to be matched with other devices such as the intelligent mobile phone for use, such as various intelligent bracelets, intelligent jewelry and the like which can perform human physiological data acquisition, human motion data acquisition, vital sign monitoring and the like.

Referring to fig. 1, fig. 1 is a schematic hardware structure diagram of a terminal device to which a data acquisition method according to an embodiment of the present application is applicable. As shown in fig. 1, the terminal device 100 may be a wearable device, or may be a mobile terminal such as a mobile phone, a tablet computer, or the like. Specifically, taking the terminal device 100 as a wearable device as an example, the terminal device 100 may specifically include a Radio Frequency (RF) circuit 110, a memory 120, an input unit 130, a display unit 140, a sensor 150, an audio circuit 160, a short-range wireless communication module 170, a processor 180, and a power supply 190. It will be appreciated by those skilled in the art that the structure of the terminal device 100 shown in fig. 1 does not constitute a limitation of the terminal device, and the terminal device may comprise more or less components than illustrated, or may combine certain components, or may be arranged in different components.

The following describes the respective constituent elements of the terminal device 100 in detail with reference to fig. 1:

The RF circuit 110 may be used for receiving and transmitting information or receiving and transmitting signals during a call, specifically, receiving downlink information of a base station, processing the downlink information by the processor 180, and transmitting uplink data to the base station. Typically, RF circuitry includes, but is not limited to, antennas, at least one amplifier, transceivers, couplers, low noise amplifiers (Low Noise Amplifier, LNAs), diplexers, and the like. In addition, RF circuit 110 may also communicate with networks and other devices via wireless communications. The wireless communication may use any communication standard or protocol including, but not limited to, global System for Mobile communications (Global System of Mobile communication, GSM), general Packet Radio Service (GPRS), code division multiple Access (Code Division Multiple Access, CDMA), wideband code division multiple Access (Wideband Code Division Multiple Access, WCDMA), long term evolution (Long Term Evolution, LTE), email, short message Service (Short MESSAGING SERVICE, SMS), and the like.

The memory 120 may be used to store software programs and modules, and the processor 180 performs various functional applications and data processing of the terminal device 100 by running the software programs and modules stored in the memory 120. The memory 120 may mainly include a storage program area that may store an operating system, application programs required for at least one function (such as a human physiological data analysis function, a human motion data analysis function, etc.), and a storage data area that may store data created according to the use of the terminal device 100 (human physiological data, motion data of a human collected part), etc. The wearable device may store data collected by the sensor in a data storage area of the wearable device when the terminal device 100 is a wearable device, and may receive data sent by the wearable device and store the data in the data storage area of the mobile terminal when the terminal device 100 is a mobile terminal such as a mobile phone or a tablet computer. In addition, memory 120 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.

The input unit 130 may be used to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the terminal device 100. In particular, the input unit 130 may include a touch panel 131 and other input devices 132. The touch panel 131, also referred to as a touch screen, may collect touch operations thereon or thereabout by a user (e.g., operations of the user on the touch panel 131 or thereabout by using any suitable object or accessory such as a finger, a stylus, etc.), and drive the corresponding connection device according to a predetermined program.

The display unit 140 may be used to display information input by a user or information provided to the user and various menus of the terminal device 100, for example, to output received electrocardiographic signals. The display unit 140 may include a display panel 141, and alternatively, the display panel 141 may be configured in the form of a Liquid crystal display (Liquid CRYSTAL DISPLAY, LCD), an Organic Light-Emitting Diode (OLED), or the like. Further, the touch panel 131 may cover the display panel 141, and when the touch panel 131 detects a touch operation thereon or thereabout, the touch panel is transferred to the processor 180 to determine the type of the touch event, and then the processor 180 provides a corresponding visual output on the display panel 141 according to the type of the touch event. Although in fig. 1, the touch panel 131 and the display panel 141 implement the input and output functions of the terminal device 100 as two independent components, in some embodiments, the touch panel 131 and the display panel 141 may be integrated to implement the input and output functions of the terminal device 100.

The terminal device 100 may also include at least one sensor 150. By way of example, when the mobile terminal 100 is a wearable device, the sensor 150 may include, for example, a motion sensor, an electrocardio sensor, or the like. Specifically, as one of the motion sensors, the accelerometer sensor may detect acceleration in all directions (typically three axes), and may detect gravity and direction when stationary, and may be used for applications of recognizing the gesture of the terminal device 100 (such as landscape/portrait screen switching, related games, magnetometer gesture calibration), vibration recognition related functions (such as pedometer, and knocking), and other sensors such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, which may be further configured by the terminal device 100, are not described herein.

Audio circuitry 160, speaker 161, microphone 162 may provide an audio interface between the user and terminal device 100. The audio circuit 160 may transmit the received electrical signal converted from audio data to the speaker 161 to be converted into a sound signal for output by the speaker 161, and on the other hand, the microphone 162 converts the collected sound signal into an electrical signal to be received by the audio circuit 160 to be converted into audio data, and then the audio data is processed by the audio data output processor 180 to be transmitted to, for example, another terminal device 100 via the RF circuit 110, or the audio data is output to the memory 120 for further processing.

The terminal device 100 may perform wireless communication with other devices through a short-range wireless communication module 170, for example, the short-range wireless communication module 170 may be integrated with at least one of a near field communication module, a bluetooth communication module, a wireless local area network (WIRELESS FIDELITY, WIFI) module, and the like. For example, when the terminal device 100 is a wearable device, the wearable device may establish a wireless communication connection with a mobile terminal such as a mobile phone, a tablet computer, etc. through a short-distance wireless communication module, and send preset physiological data of a human body and/or motion data of a collected part of the human body, etc. collected by the sensor to the mobile terminal; when the terminal device 100 is a mobile terminal such as a mobile phone or a tablet computer, the mobile terminal may establish a wireless communication connection with the wearable device through the short-distance wireless communication module, and receive preset physiological data of a human body and/or motion data of a collected part of the human body sent by the wearable device.

It will be appreciated that although not shown in fig. 1, the terminal device 100 may also include a wired communication interface, such as a universal serial bus (Universal Serial Bus, USB) interface, through which the terminal device 100 may establish wired communication connections with other terminal devices 100 and perform wired communication. The mobile terminal may receive the preset human body physiological data and/or the motion data of the collected part of the human body and the like sent by the wearable device through the USB interface when the terminal device 100 is a mobile terminal such as a mobile phone or a tablet computer.

The processor 180 is a control center of the terminal device 100, connects respective parts of the entire terminal device 100 using various interfaces and lines, and performs various functions of the terminal device 100 and processes data by running or executing software programs and/or modules stored in the memory 120 and calling data stored in the memory 120, thereby performing overall monitoring of the terminal device 100. Alternatively, the processor 180 may include one or more processing units, and preferably the processor 180 may integrate an application processor that primarily processes operating systems, user interfaces, applications, etc., with a modem processor that primarily processes wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 180.

The terminal device 100 also includes a power supply 190 (e.g., a battery) for powering the various components, which may preferably be logically coupled to the processor 180 via a power management system so as to provide for managing charging, discharging, and power consumption by the power management system.

Referring to fig. 2, fig. 2 is an exemplary block diagram of a data acquisition system according to an embodiment of the present application, where data acquired by the data acquisition system is mainly used to help screen for paroxysmal cardiovascular diseases, and as shown in fig. 2, the data acquisition system includes a mobile terminal 210 and a wearable device 220. The wearable device 220 may establish a wireless communication connection with the mobile terminal 210 through a short-distance wireless communication manner, or the wearable device 220 may also establish a wired communication connection with the mobile terminal 210 through a wired communication manner, which is not limited in any way by the embodiment of the present application.

Specifically, when the user wears the wearable device 220 and starts the data acquisition function of the wearable device 220, the wearable device 220 may acquire data of the wearing user through its built-in sensor for acquiring data. The data may be set according to actual requirements, for example, the data may be electrocardiographic signals of a human body, acceleration motion data (auxiliary recognition interference data) of the human body, and the like.

The wearable device 220 may upload the data of the sensor to the mobile terminal 210. For example, the wearable device 220 may establish a communication connection with the mobile terminal 210 through a short-range wireless communication manner or a wired communication manner, and upload data of the sensor to the mobile terminal 210. The mobile terminal 210 may store data from the sensors of the wearable device 220. Here, the mobile terminal 210 may be used as a device for data processing, data analysis, and measurement result presentation. The wearable device 220 may send the acquired data to the mobile terminal 210, where the mobile terminal 210 processes the data (such as performing rectangular filtering, smoothing denoising, interference data deleting, data splicing, etc.), analyzes whether the user has paroxysmal cardiovascular diseases based on the existing machine learning method, and displays the measured result through a display unit of the mobile terminal 210, or performs voice notification through a speaker. It should be noted that the foregoing is merely illustrative of the manner in which the measurement results are displayed, and is not intended to limit the present application.

In addition, the mobile terminal 210 may be used only as a device for verifying the wearable device 220, based on the identity authentication of the wearable device by the mobile terminal 210, the logged-in wearable device is bound with the mobile terminal 210, and the bound wearable device can receive information such as a call notification, a short message notification, an instant messaging notification, and the like of the mobile device. Here, the above data collection, data processing, data analysis, and measurement result presentation are implemented by the wearable device 220. In this regard, after the wearable device bound to the mobile terminal 210 starts the measurement function (i.e., starts to collect data), data for helping to screen for paroxysmal cardiovascular diseases may be collected, and after the collected data is processed (e.g., rectangular filtering, smooth denoising, interference data deleting, data splicing, etc.), whether the user has paroxysmal cardiovascular diseases is analyzed from the processed data based on the existing machine learning method, and the measured result is displayed through the display unit of the wearable device 220, or a voice notification is performed through a speaker. It should be noted that the foregoing is merely illustrative of the manner in which the measurement results are displayed, and is not intended to limit the present application.

In addition, the wearable device 220 may also process the collected data, then upload the processed data to the mobile terminal 210, perform data analysis through the mobile terminal 210, and display the measurement result through the mobile terminal 210 after the mobile terminal 210 performs data analysis. It can be appreciated that the mobile terminal 210 may also send the analyzed measurement results to the wearable device 220, and display the measurement results through the wearable device 220.

It can be appreciated that the data acquisition system may further include only the wearable device 220, where a call function, an information receiving and transmitting function, and the like can be implemented in the wearable device 220, and meanwhile, the wearable device 220 further has a data acquisition function, a data processing function, a data analysis function, and a measurement result display function.

The following embodiments will take the terminal device 100 as an example, to describe a data acquisition method provided in the embodiments of the present application.

Referring to fig. 3, fig. 3 is a schematic flowchart of a data collection method according to an embodiment of the present application, in this embodiment, an execution subject of the flowchart is a terminal device, which may be, by way of example and not limitation, a wearable device 220 as shown in fig. 2 or a mobile terminal 210 as shown in fig. 2.

As shown in fig. 3, the data acquisition method provided in this embodiment specifically includes S110 to S190, which are described in detail as follows:

s110, starting a data acquisition function.

In this embodiment, when the terminal device is a wearable device, that is, when the execution body of the process is the wearable device, the user may start the data acquisition function of the wearable device after wearing the wearable device, and when the data acquisition function of the wearable device is turned on, the wearable device may acquire the physiological data of the wearer through its built-in sensor for acquiring the physiological data (such as an electrocardiograph signal). Here, the user may send an instruction for starting the measurement function of the wearable device to the wearable device through the mobile terminal, so as to start the measurement function of the wearable device, or may directly start the measurement function through the wearable device starter, for example, press a button or a control for starting the function, so as to generate a corresponding starting instruction, so as to start the measurement function of the wearable device. In addition, the measurement function is started, and besides physiological data, motion data of a specific position of a human body can be acquired. The motion data can be used to assist in detecting whether the user moves the wearable device and whether the magnitude of the motion meets a preset motion state (e.g., an action of answering a phone call).

In this embodiment, the sensor may be a sensor provided in the wearable device. The specific type of the data may be set according to actual requirements, which is not limited herein, and when the detection of the preset physiological characteristic of the human body is required, the data may include physiological data of the human body capable of representing the preset physiological characteristic, for example, when the detection of the activity characteristic of the heart of the human body is required, the data may include an electrocardiograph capable of representing the activity characteristic of the heart of the human body, or when the detection of the motion state of the human body is required, the data may also include motion data capable of representing the motion state of the human body, such as acceleration of the human body, and the like.

In a specific application, different sensors corresponding to the data may be configured in the wearable device according to the different data types. For example, when the data includes an electrocardiograph signal of a human body, an electrocardiograph sensor for acquiring the electrocardiograph signal of the human body may be configured in the wearable device, wherein the electrocardiograph sensor may include, but is not limited to, a photoplethysmograph (Photo plethysmograph, PPG) sensor or an Electrocardiogram (ECG) sensor, or the like. Specifically, by way of example and not limitation, when the wearable device is an electronic device such as a bracelet or a wristwatch that can be in direct contact with the skin of a user, and the electrocardiograph sensor is a PPG sensor, the PPG sensor may be disposed in an area of the dial of the bracelet or the wristwatch that is near the back of the dial, so that when the user wears the bracelet or the wristwatch and further brings the area of the back of the dial of the bracelet or the wristwatch into contact with the skin of the user, the PPG sensor in the bracelet or the wristwatch may collect electrocardiographic signals of the user based on the change in the blood volume of the wearing part of the user. Further, when the electrocardiosignal of the human body is acquired, if the data further comprises the motion data of the acquired part of the human body, a motion sensor for acquiring the motion data of the human body can be configured in the wearable device, wherein the motion sensor can comprise but is not limited to an acceleration sensor and the like. The collected part of the human body is the part of the human body wearing the wearable equipment.

In this embodiment, when the user wears the wearable device and starts the data acquisition function of the wearable device, the wearable device may control the corresponding sensor to acquire data for the user. The method comprises the steps that when data comprise electrocardiosignals of a human body, a user can start an electrocardiosignal acquisition function of the wearable device, when the wearable device detects that the user starts the electrocardiosignal acquisition function, the electrocardiosignals of the user are acquired by controlling the electrocardiosignals of the user, the electrocardiosignals of the user acquired by the sensor are data to be acquired by the method, when the data also comprise motion data of the acquired part of the human body, the user can start a motion data acquisition function of the wearable device, and when the wearable device detects that the user starts the motion data acquisition function, the motion sensor is controlled to acquire the motion data of the acquired part of the user.

In this embodiment, when the terminal device is a mobile terminal such as a mobile phone or a tablet computer, that is, when the execution subject of the process is a mobile terminal such as a mobile phone or a tablet computer, the data acquisition starting function may be to send an instruction for starting the data acquisition function to the wearable device through the mobile terminal, so as to further realize the data acquisition starting function.

In this embodiment, after the data acquisition function is started, the terminal device may perform relevant data acquisition, and the terminal device may further store the acquired data in a local storage for storage.

In this embodiment, when the terminal device is a wearable device, that is, the execution subject of the process is the wearable device, the wearable device may store the data from the sensor in its local memory, based on which, when performing data analysis based on the acquired data, the wearable device may acquire the data from its local memory. In another possible implementation manner of this embodiment, when the terminal device is a mobile terminal such as a mobile phone or a tablet computer, that is, when the execution subject of the process is a mobile terminal such as a mobile phone or a tablet computer, the wearable device may upload data from the sensor to the mobile terminal, and the mobile terminal may store the data sent by the wearable device in a local memory of the mobile terminal, based on which, when performing data analysis based on the collected data, the mobile terminal may obtain the data from the local memory thereof.

And S120, monitoring whether an interference event occurs in the data acquisition process, if so, executing S130, otherwise, continuing to monitor until the measurement is finished.

In this embodiment, since a long period of time is required in the measurement process, an interference event is likely to occur in the measurement process, and therefore, in the process of performing data acquisition, the terminal device also monitors whether an interference event occurs in real time. It can be understood that some of the above-mentioned interference events are events that require the user to process in time so as not to miss important information, such as real-time call events, some of the interference events are events that can be processed after the measurement is finished, such as information check events, and some of the interference events are interference events caused by the user greatly moving the terminal device, such as actions such as the user answering a call.

In this embodiment, the following two cases may be classified as the mobile terminal monitors whether an interference event occurs in the data acquisition process:

1.it is monitored whether a clearly defined disturbance event occurs.

The terminal device can determine the interference event of the meaning of the interference event explicitly, such as a real-time call event, a short message check event, an instant message check event, an information push event of an application program of the terminal device, etc. For these nuisance events, the terminal device can directly determine which nuisance event is in particular. For example, when a call is made (i.e. when a real-time call event occurs), the terminal device receives a corresponding message alert requesting a real-time call, and further can determine that the interference event is a real-time call event. That is, when the terminal device receives a message alert requesting a real-time call, it can be determined that an interference event, that is, a real-time call event, occurs during the data acquisition process. For another example, when the terminal device receives the short message, the terminal device receives a message alert corresponding to the received short message, so as to determine that the interference event is a short message check event. That is, when the terminal device receives the message alert of the received short message, it can be determined that the interference event of short message check occurs in the data acquisition process.

When monitoring whether an interference event with explicit meaning occurs, only monitoring whether a corresponding message reminder is received or not is needed, and if the corresponding message reminder is received, the condition that the interference event corresponding to the message reminder occurs is indicated.

2. Monitoring whether an unequivocal disturbance event occurs.

Here, during the data acquisition process, a user wearing the wearable device may inadvertently lift a hand or tremble a hand, or the like, and the action interference event may not be able to determine what interference specifically occurs for the wearable device. I.e. an interference event without explicit meaning. For such disturbance events, it is possible to identify whether a disturbance event occurs based on assistance data of an assistance sensor (e.g., acceleration sensor, etc.) of the terminal device, and based on an existing motion gesture algorithm.

S130, judging whether the interference event is an interference event to be processed in real time, executing S140 if a plurality of interference events are the interference event to be processed in real time, otherwise executing S200

In this embodiment, when it is monitored that an interference event occurs in the data acquisition process, the terminal device may determine which interference event is the interference event, and further determine whether the interference event is an interference event to be processed in real time. In this embodiment, the above-mentioned interference event to be processed in real time refers to an event that needs to be processed by the user in real time. Here, it is possible to determine whether the disturbance event is a disturbance event to be processed in real time by presetting priorities of various disturbance events and then based on the priorities of the disturbance events.

In addition, the interference event sent by the specific user may be set as an interference event to be processed in real time, for example, a call made by the specific user, information sent by the specific user (including but not limited to a short message, an instant messaging message), and the like. It should be noted that the specific user may be one or a plurality of users, which is not limited herein. The specific user can be added into the specific user list by setting the specific user list, each time the terminal equipment receives the interference event, the user initiating the interference event is obtained, whether the user is the specific user or not is judged, and if the user is the specific user (in the specific user list), the interference event is determined to be the interference event to be processed in real time. If the user is not a specific user (not in the specific user list), the priority corresponding to the interference event may be further determined, and then whether the interference event is an interference event to be processed in real time is determined based on the priority of the interference event. The above specific user list may be defined by a user, and the user adds a user that considers itself to be important to the list, where the list may include a user identifier (such as a plurality of identifiers of a phone number, a name, a nickname, etc.), and the user identifier determines whether the user initiating the interference event is in the specific user list, which will not be described in detail.

Referring to fig. 4, as an implementation manner of the present embodiment, the process of identifying whether the interference event is an interference event to be processed in real time may specifically include the following steps:

s131, acquiring the priority of the interference event.

S132, if the priority of the interference event is a first preset priority level, determining that the interference event is an interference event to be processed in real time, and if the priority of the interference event is a second preset priority level, determining that the interference event is an interference event not to be processed in real time.

In a specific application, the priorities of the types of the interference events can be preset. The interference event can be divided into three types in advance, wherein the first type is the interference event which needs to be processed in real time, the second type is the interference event which can be processed after the measurement is finished, and the third type is the motion interference event. The priority of the first type of interference event is set to a first preset priority level in advance, the priority of the second type of interference event is set to a second preset priority level, and the priority of the third type of interference event is set to a third preset priority level. When the terminal equipment monitors the occurrence of the interference event, the corresponding processing strategy can be adopted to process the interference event by determining the priority of the interference event.

It should be noted that, the first preset priority level, the second preset priority level, and the third preset priority level are preset for distinguishing various interference events, and the user may preset which interference events are included in various interference events according to actual application requirements, and may also preset the priority order of the preset priority levels. Here, the first preset priority level may be set to have a higher priority than the second preset priority level. Similarly, the priority of the first preset priority level may be set lower than the priority of the second preset priority level, which is not limited herein.

And S140, storing the acquired data, accessing the interference event, and starting background data acquisition while accessing the interference event.

In this embodiment, in the case where it is determined that the interference event is an interference event to be processed in real time that needs to be processed in real time, the acquired data is first saved, for example, the acquired data is saved in a memory of the terminal device. And after the acquired data is stored, accessing the interference event to be processed in real time, such as accessing a real-time call event, and simultaneously starting a background of the terminal equipment to continuously acquire the data so as to ensure that the data acquisition process is not interrupted.

And S150, collecting motion data and determining the motion amplitude of the motion data according to the motion data.

And S160, determining a target data segment meeting a preset motion state in data acquired simultaneously with the motion data according to the motion amplitude of the motion data.

S170, if the interference degree of the target data segment exceeds a preset interference range, determining that the target data segment is an interference data segment.

In this embodiment, during the process of collecting data, the mobile wearable device or the mobile terminal (such as lifting the hand or picking up the mobile phone when answering the phone) may generate interference to the collected data, so that interference information exists in the collected data. By acquiring motion data based on a motion sensor while acquiring target data (i.e. physiological data for analyzing cardiovascular diseases), and then determining a target data segment satisfying a preset motion state based on a motion amplitude of the motion data. And determining whether the target data segment is an interference data segment based on the signal interference degree of the target data segment. Because some action interferences have smaller interferences to the acquired data, whether the data are the interference data fragments or not needs to be further determined according to the signal interference degree of the target data fragments, the target data fragments are considered as the interference data fragments only when the interference degree of the target data fragments exceeds a preset interference range, the effective data are reserved as far as possible, the interference data are deleted when the background data are saved, the influence of the interference data on analysis results is avoided, and the accuracy of the measurement results is improved.

It should be noted that, the above meeting the preset motion state means that the motion amplitude of the motion data is greater than a certain preset amplitude threshold, and the preset amplitude threshold may be set according to the actual requirement, which is not limited herein. It should be further noted that the interference degree may be determined according to the signal-to-noise ratio of the acquired data, and the preset interference range may be set according to the actual situation, which is not limited herein.

And S180, deleting the interference data fragments if the interference data fragments exist in the data fragments acquired by the background, so as to obtain effective data fragments.

In order to avoid the influence of interference data on the analysis result when the interference data segment exists in the data segment collected in the background, the accuracy of the measurement result is provided, and the interference data segment can be deleted from the data segment collected in the background, so that the effective data segment without interference is obtained.

And S190, obtaining target acquisition data according to the data segments acquired before the interference event and the data segments acquired in the background.

In this embodiment, the terminal device may perform data splicing on the data segment collected before the access to the interference event and the data segment collected in the background based on the collection time of each data segment, so as to obtain the target collection data.

Referring to fig. 5, DP1 is a data segment collected before an access interference event, DP2 is a data segment collected in the background, and based on the collection time of the data segment before the access interference event and the collection time of the data segment collected in the background, the terminal device may splice DP1 and DP2 in order from early to late, so as to obtain the target collected data 1.

Referring to fig. 6, as a possible implementation manner of this embodiment, when the data segment DP2 collected in the background has the interference data segment DP3, the interference data segment DP3 may be deleted from the data segment DP2 collected in the background to obtain the remaining valid data segment DP4, and then the data segment DP1 collected before the interference event is accessed and the valid data segment DP4 are subjected to data splicing to obtain the target collected data 2.

It should be noted that, the terminal device may also splice the data segment collected before the access interference event with the data segment collected in the background, then screen out the interference data segment in the spliced data, and delete the interference data segment from the spliced data, so as to obtain the target data segment.

It should be noted that, the data segments collected in the background may not have any interference data segments, may have only one interference data segment, and may have multiple interference data segments, which is not limited herein. And deleting the multi-section interference data fragments from the data fragments acquired in the background under the condition that the multi-section interference data fragments exist in the data fragments acquired in the background, and then obtaining a plurality of effective data fragments, wherein at the moment, only data splicing is carried out according to the acquisition time of each effective data fragment and the sequence from early to late, so that a section of continuous acquired data can be obtained, and the continuous liniment data is the target acquired data for data analysis.

And S200, accessing the interference event after the measurement is finished.

In this embodiment, under the condition that it is determined that the interference event is a non-real-time processing interference event that does not need real-time processing, the non-real-time processing interference event may not be processed temporarily in the data acquisition process, and the terminal device may continue to acquire data until the measurement is completed, so that the interference event will not affect the measurement process, and access the interference event after the measurement is completed, so as to ensure that the interference event can be processed in time, but not ignored. For example, after the measurement is completed, a short message notification, an instant messaging notification, an application push notification, etc. are displayed.

According to the data acquisition method provided by the embodiment of the application, the background can be started to continuously acquire data while the interference event to be processed in real time is processed, and then after the interference is finished, the data segment before the access of the interference event and the data segment acquired by the background are spliced to obtain the target acquisition data, so that the event to be processed in real time can be processed in time, the data can be continuously acquired, the measurement process is not influenced, the acquired effective information before the interference is not discarded, the condition of missing part of effective data is avoided, the reliability and the availability of the acquired data are effectively improved, and the total time consumption of measurement is shortened. The interference event which is not to be processed in real time can be not processed temporarily in the data acquisition process, the data acquisition is continued until the measurement is finished, the measurement process is not affected, the interference event is accessed after the measurement is finished, and further, the interference event can be processed in time and is not ignored. Different processing strategies are adopted for interference events with different priority levels, so that the efficiency of data acquisition is improved, and important information is not missed. The method effectively solves the problems that part of effective data is easy to miss, the reliability and the availability of the acquired data are low, and the measurement time is long in the traditional wearable equipment data acquisition process under the premise of ensuring that important information is processed in time.

Fig. 7 shows a block diagram of a terminal device according to an embodiment of the present application, where each unit of the terminal device is configured to perform each step in the foregoing embodiment, and specifically please refer to the related description in the foregoing embodiment, and only the portion related to the embodiment of the present application is shown for convenience of explanation. In practical application, the terminal device may be a wearable device, or may be a mobile terminal such as a mobile phone, a tablet computer, or the like. Referring to fig. 7, the terminal device 100 includes a first processing unit 110 and a splicing unit 120. Wherein:

The first processing unit 110 is configured to store the acquired data and access the interference event if it is detected that the interference event occurs in the data acquisition process and the interference event is an interference event to be processed in real time, and start background data acquisition while accessing the interference event.

The splicing unit 120 is configured to obtain target acquisition data according to the data segment acquired before the interference event and the acquired data segment after the interference event.

In an embodiment of the present application, the terminal device further includes a deleting unit, where the deleting unit is configured to delete the interference data segment if the interference data segment exists in the data segment collected in the background, so as to obtain an effective data segment. Correspondingly, the splicing unit is specifically used for carrying out data splicing on the data segment acquired before the interference event and the effective data segment to obtain target acquisition data.

In an embodiment of the present application, the terminal device further includes a first determining unit, a second determining unit, and a checking unit. Wherein:

the first determining unit is used for acquiring motion data and determining the motion amplitude of the motion data according to the motion data.

The second determining unit is used for determining a target data segment meeting a preset motion state in data acquired simultaneously with the motion data according to the motion amplitude of the motion data.

And the verification unit is used for determining the target data fragment as the interference data fragment if the interference degree of the target data fragment exceeds a preset interference range.

In an embodiment of the present application, the above-mentioned splicing unit is specifically configured to perform data splicing according to an acquisition time of a data segment acquired before the access to the interference event and an acquisition time of a data segment acquired in the background, so as to obtain the target acquisition data.

In an embodiment of the present application, the terminal device further includes a monitoring unit and an identifying unit. Wherein:

In an embodiment of the present application, the identification unit includes a priority acquisition unit and a judgment unit. Wherein:

In an embodiment of the present application, the terminal device further includes a second processing unit, where the second processing unit is configured to access the interference event after the measurement is finished if it is detected that the interference event occurs in the acquisition process and the interference event is an interference event that is not to be processed in real time.

It can be seen from the above that, according to the terminal device provided by the embodiment of the application, the background can be started to continuously collect data while the interference event to be processed in real time is processed, and then after the interference is finished, the data segment before the interference event is accessed and the data segment collected in the background are spliced to obtain target collected data, so that the event needing to be processed in real time can be processed in time, the data can be continuously collected, the measurement process is not influenced, the collected effective information before the interference is not discarded, the condition of missing part of effective data is avoided, the reliability and the availability of the collected data are effectively improved, and the total measurement time consumption is shortened.

Referring to fig. 8, fig. 8 is a schematic structural diagram of a terminal device according to another embodiment of the present application. As shown in fig. 8, the terminal device 100 of this embodiment comprises at least one processor 80 (only one is shown in fig. 8), a memory 81 and a computer program 82 stored in said memory 81 and executable on said at least one processor 80, said processor 80 implementing the steps of any of the respective data acquisition method embodiments described above when executing said computer program 82.

The terminal device 100 may be a computing device such as a desktop computer, a notebook computer, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor 80, a memory 81. It will be appreciated by those skilled in the art that fig. 8 is merely an example of the terminal device 100 and is not meant to be limiting as to the terminal device 100, and may include more or fewer components than shown, or may combine certain components, or may include different components, such as input-output devices, network access devices, etc.

The Processor 80 may be a central processing unit (Central Processing Unit, CPU), the Processor 80 may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL processors, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), off-the-shelf Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 81 may in some embodiments be an internal storage unit of the terminal device 100, such as a hard disk or a memory of the terminal device 100. The memory 81 may in other embodiments also be an external storage device of the terminal device 100, such as a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD) or the like, which are provided on the terminal device 100. Further, the memory 81 may also include both an internal storage unit and an external storage device of the terminal device 100. The memory 81 is used for storing an operating system, application programs, boot Loader (Boot Loader), data, other programs, etc., such as program codes of the computer program. The memory 81 may also be used to temporarily store data that has been output or is to be output.

It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program can realize the steps in the data acquisition method when being executed by a processor.

Embodiments of the present application provide a computer program product which, when run on a mobile terminal, causes the mobile terminal to perform the steps of the data acquisition method described above.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least any entity or device capable of carrying computer program code to a camera device/terminal equipment, a recording medium, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other manners. For example, the apparatus/network device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.

The units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be respectively located on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

It should be noted that the above description is only a specific embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. The data acquisition method is characterized in that the data acquisition method is applied to a wearable device, the wearable device is used for acquiring physiological data, and the data acquisition method comprises the following steps:

After a data acquisition function is started, monitoring whether an interference event occurs in the data acquisition process, wherein the interference event is an event which causes interference to the data acquisition function;

If the interference event occurs in the data acquisition process, judging whether the interference event is an interference event to be processed in real time;

If the interference event occurs in the data acquisition process and the interference event is an interference event to be processed in real time, saving the acquired data, processing the interference event, and starting background data acquisition while processing the interference event;

And performing data splicing according to the acquisition time of the data fragments acquired before the processing of the interference event and the acquisition time of the data fragments acquired in the background to obtain target acquisition data.

2. The data collection method according to claim 1, wherein if the disturbance event occurs during the data collection and the disturbance event is a disturbance event to be processed in real time, storing the collected data, processing the disturbance event, and starting the background data collection while processing the disturbance event, further comprising:

Correspondingly, the data splicing is performed according to the acquisition time of the data segment acquired before the processing of the interference event and the acquisition time of the data segment acquired in the background, so as to obtain target acquisition data, which comprises the following steps:

And performing data splicing on the data fragments acquired before the interference event is processed and the effective data fragments to obtain the target acquisition data.

3. The data acquisition method according to claim 2, wherein, before deleting the interference data segment if there is an interference data segment in the data segments acquired in the background, the method further comprises:

4. The method for data collection according to claim 1, wherein if an interference event occurs in the data collection process, determining whether the interference event is an interference event to be processed in real time includes:

Acquiring the priority of the interference event;

5. The data acquisition method according to any one of claims 1 to 4, characterized in that the data acquisition method further comprises:

and if the interference event is monitored to occur in the acquisition process and is not to be processed in real time, processing the interference event after the measurement is finished.

6. A terminal device, characterized in that the terminal device is a wearable device for acquiring physiological data, the wearable device comprising:

The detection unit is used for monitoring whether an interference event occurs in the data acquisition process after the data acquisition function is started, wherein the interference event is an event which causes interference to the data acquisition function;

The identification unit is used for judging whether the interference event is an interference event to be processed in real time or not if the interference event occurs in the data acquisition process;

The first processing unit is used for storing the acquired data and processing the interference event if the interference event occurs in the data acquisition process and the interference event is the interference event to be processed in real time, and starting background data acquisition while processing the interference event;

And the splicing unit is used for carrying out data splicing according to the acquisition time of the data fragments acquired before the processing of the interference event and the acquisition time of the data fragments acquired in the background to obtain target acquisition data.

7. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the data acquisition method according to any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the data acquisition method according to any one of claims 1 to 5.