WO2020211702A1 - 压力评估校准方法、装置及存储介质 - Google Patents

压力评估校准方法、装置及存储介质 Download PDF

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Publication number
WO2020211702A1
WO2020211702A1 PCT/CN2020/084229 CN2020084229W WO2020211702A1 WO 2020211702 A1 WO2020211702 A1 WO 2020211702A1 CN 2020084229 W CN2020084229 W CN 2020084229W WO 2020211702 A1 WO2020211702 A1 WO 2020211702A1
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user
pressure
state value
value
pressure state
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PCT/CN2020/084229
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English (en)
French (fr)
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傅小煜
许培达
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华为技术有限公司
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Priority to US17/594,053 priority Critical patent/US20220175286A1/en
Priority to EP20792106.5A priority patent/EP3928700A4/en
Publication of WO2020211702A1 publication Critical patent/WO2020211702A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/165—Evaluating the state of mind, e.g. depression, anxiety
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02405—Determining heart rate variability
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/0245—Detecting, measuring or recording pulse rate or heart rate by using sensing means generating electric signals, i.e. ECG signals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/40—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
    • A61B2560/02—Operational features
    • A61B2560/0223—Operational features of calibration, e.g. protocols for calibrating sensors
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4029—Detecting, measuring or recording for evaluating the nervous system for evaluating the peripheral nervous systems
    • A61B5/4035—Evaluating the autonomic nervous system
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/681—Wristwatch-type devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor

Definitions

  • This application relates to the field of information processing technology, and in particular to a method, device and storage medium for pressure evaluation and calibration.
  • Psychological stress is a person's physical changes and emotional fluctuations caused by changes in the external environment and the internal state of the body, usually accompanied by positive or negative emotions.
  • the qualitative and quantitative evaluation of users’ psychological stress is not only helpful in assisting early warning of physical conditions, but also assisting users in rationally arranging work plans, thereby improving work efficiency. Therefore, how to accurately assess people's psychological pressure has gradually become one of the important issues that the industry pays attention to and researches.
  • the embodiments of the present application provide a pressure evaluation and calibration method, device and storage medium to solve the problems of low accuracy of the existing pressure evaluation results and poor user experience.
  • the first aspect of this application provides a pressure assessment and calibration method, which is suitable for electronic devices or servers, and the method includes:
  • the calibration information of the stress assessment system is determined, and the calibration information is used to output the stress assessment system
  • the value of the pressure state is calibrated to determine the theoretical pressure state value of the user. That is, the technical solution does not require the user to provide self-evaluation opinions, and can automatically generate calibration information, realize the automatic calibration of the pressure evaluation results, and improve the evaluation Accuracy, does not require the subjective participation of users, and improves user experience.
  • the stress evaluation system based on the feature value vector of the physiological parameter signal and determining the minimum stress state value of the user within a preset time period includes:
  • the user's lowest pressure state value within the preset time period can be determined, that is, the pressure state value at the most relaxed moment, which provides a realization for the subsequent determination of calibration information may.
  • the feature value vector includes: at least one feature value component; the stress state value of the user at each moment is based on each feature value component in the feature value vector and the weight corresponding to each feature value component Values are obtained by weighted summation.
  • the method before determining the calibration information according to the lowest reference pressure value of the group where the user is located and the lowest pressure state value, the method further includes:
  • a pressure value database is queried to determine the lowest reference pressure value of the group where the user belongs, and the corresponding relationship between the group identification and the reference pressure range is stored in the pressure value database.
  • the lowest reference pressure value of the group where the user is located can be determined based on the user's basic information, so that the calibration information of the stress evaluation system can be automatically determined, without the user's active participation, and the user experience is improved.
  • the using the calibration information to calibrate the pressure state value output by the pressure evaluation system to determine the theoretical pressure state value of the user includes:
  • the technical solution uses calibration information to calibrate the predicted pressure state value output by the pressure evaluation system, and the obtained pressure evaluation result is highly accurate, and does not require the user to give an evaluation, which improves the user experience.
  • a second aspect of the present application provides a pressure evaluation and calibration device, including: an acquisition module, a processing module, and a calibration module;
  • the acquisition module is used to acquire physiological parameter signals of the user
  • the processing module is configured to determine the minimum pressure state value of the user within a preset time period based on the characteristic value vector of the physiological parameter signal and the pressure evaluation system, and according to the minimum reference pressure value of the user's population and The minimum pressure state value determines the calibration information;
  • the calibration module is configured to use the calibration information to calibrate the pressure state value output by the pressure evaluation system to determine the theoretical pressure state value of the user.
  • the acquiring module is further configured to acquire a feature value vector corresponding to each time of the physiological parameter signal within the preset time period;
  • the processing module is specifically configured to input the characteristic value vector into the stress evaluation system for the characteristic value vector at each moment to obtain the stress state value of the user at each moment, and according to the user
  • the pressure state value at each time within the preset time period determines the lowest pressure state value of the user within the preset time period.
  • the feature value vector includes: at least one feature value component; the stress state value of the user at each moment is based on each feature value component in the feature value vector and the weight corresponding to each feature value component Values are obtained by weighted summation.
  • the acquiring module is further configured to determine the calibration information before the processing module determines the calibration information according to the lowest reference pressure value of the user's population and the lowest pressure state value To obtain the basic information of the user;
  • the processing module is further configured to determine the identity of the group to which the user belongs based on the basic information, query a pressure value database based on the identity of the group to which the user belongs, and determine the lowest reference pressure value of the group of which the user belongs, so
  • the pressure value database stores the corresponding relationship between the group identification and the reference pressure range.
  • the calibration module is specifically configured to input the feature value vector of the physiological parameter signal into the pressure evaluation system to obtain a predicted pressure state value, and use the calibration Information is used to calibrate the predicted pressure state value to obtain the theoretical pressure state value of the user.
  • a third aspect of the present application provides a pressure assessment and calibration device, including a processor, a memory, and a computer program stored on the memory and capable of running on the processor.
  • the processor executes the program to implement the first Aspects and the methods described in the various possible implementations of the first aspect.
  • the fourth aspect of the present application provides a storage medium that stores instructions in the storage medium, which when run on a computer, causes the computer to execute the methods described in the first aspect and various possible implementations of the first aspect .
  • the fifth aspect of the present application provides a program product containing instructions, which when run on a computer, causes the computer to execute the methods described in the first aspect and various possible implementation manners of the first aspect.
  • a sixth aspect of the present application provides a chip, the chip includes a memory and a processor, the memory stores code and data, the memory is coupled to the processor, and the processor runs the code in the memory so that the chip is used to execute the first aspect described above And the methods described in the various possible implementations of the first aspect.
  • the stress evaluation and calibration method, device, and storage medium provided by the embodiments of the present application determine the user's lowest pressure state value within a preset time period by acquiring the user's physiological parameter signal, based on the characteristic value vector of the physiological parameter signal and the stress evaluation system , Determine the calibration information according to the lowest reference pressure value and the lowest pressure state value of the user's group, and use the calibration information to calibrate the pressure state value output by the pressure evaluation system to determine the user's theoretical pressure state value.
  • the automatic calibration of the stress evaluation result can be realized, the evaluation accuracy is improved, the subjective participation of the user is not required, and the user experience is improved.
  • FIG. 1 is a schematic structural diagram of a pressure evaluation and calibration system provided by an embodiment of the application
  • Embodiment 1 of a pressure evaluation and calibration method provided by an embodiment of this application;
  • FIG. 3 is a schematic flowchart of Embodiment 2 of the pressure evaluation and calibration method provided by an embodiment of the application;
  • FIG. 4 is a schematic flowchart of Embodiment 3 of a pressure evaluation and calibration method provided by an embodiment of this application;
  • FIG. 5 is a schematic flowchart of Embodiment 4 of a pressure evaluation and calibration method provided by an embodiment of this application;
  • Embodiment 1 of a pressure evaluation and calibration device provided by an embodiment of this application;
  • FIG. 7 is a schematic structural diagram of Embodiment 2 of a pressure evaluation and calibration device provided by an embodiment of the application.
  • FIG. 1 is a schematic structural diagram of a pressure evaluation and calibration system provided by an embodiment of the application.
  • the pressure evaluation and calibration system may include: a pressure evaluation system 11, a processing module 12, and a calibration module 13 which are connected to each other in pairs.
  • the stress assessment system 11 may be a device with stress assessment capability, which can obtain the physiological parameter signal of the user, analyze the physiological parameter signal, and output the psychological stress value of the user determined by the stress assessment system; the processing module 12 The user pressure value determined by the stress evaluation system 11 can be obtained, and the user pressure value can be processed based on the obtained reference pressure value of the group to which the user belongs to obtain calibration information of the user pressure value; the calibration module 13 can obtain the pressure evaluation The user pressure value determined by the system 11 and the calibration information obtained by the processing module 12, and the calibration information is used to calibrate the user pressure value to obtain the theoretical pressure state value.
  • the embodiment of the application does not limit the specific composition of the pressure evaluation and calibration system, it may also include other modules, for example, a storage module, a communication interface, etc.
  • the specific composition of the pressure evaluation and calibration system may be limited according to actual conditions, here No longer.
  • “multiple” refers to two or more.
  • “And/or” describes the association relationship of the associated objects, indicating that there can be three types of relationships, for example, A and/or B, which can mean: A alone exists, A and B exist at the same time, and B exists alone.
  • the character “/” generally indicates that the associated objects are in an "or” relationship.
  • qualitatively and quantitatively assessing the mental stress of users is also of certain value, which is helpful for the push of sports and service products, assists in early warning of physical conditions, and can be used to remind people of excessive stress, such as analyzing people In which time of day the mental state is better, this can make people arrange their work reasonably, thereby improving work efficiency.
  • wearable devices With the rise of wearable devices and the portability of wearable devices, wearable devices have gradually become a new carrier for mental stress evaluation. More and more wearable devices can collect people's physiological parameter signals in daily situations, such as , Heart rate, skin temperature, etc., to show the user.
  • the embodiments of the present application provide a stress evaluation and calibration method.
  • the minimum pressure state of the user within a preset period of time is determined According to the lowest reference pressure value and the lowest pressure state value of the user's population, the calibration information is determined, and the pressure state value output by the pressure evaluation system is calibrated using the calibration information to determine the user's theoretical pressure state value.
  • the automatic calibration of the stress evaluation result can be realized, the evaluation accuracy is improved, the subjective participation of the user is not required, and the user experience is improved.
  • FIG. 2 is a schematic flowchart of Embodiment 1 of a pressure evaluation and calibration method provided by an embodiment of the application. This method can be applied to the pressure evaluation and calibration system shown in Figure 1.
  • the system can be implemented by a server or by other electronic devices with evaluation and calibration capabilities.
  • the electronic device may be a wearable device such as a bracelet or a smart watch.
  • the pressure evaluation and calibration method may include the following steps:
  • Step 21 Acquire physiological parameter signals of the user.
  • a device with a heart rate collector such as a wristband and a smart watch
  • it can collect a user's heart rate value, and then evaluate the user's stress state value according to the user's heart rate value, and according to the user's preset time period
  • the value of the stress state is used to evaluate and track the psychological stress of users.
  • the server or the above electronic device can obtain the physiological parameter signal of the user, and then process the physiological parameter signal.
  • the physiological parameter signal may include different physiological signals such as heart rate information, electrocardiogram information, blood pressure information, and weight information.
  • the server or the above-mentioned electronic device may obtain the physiological parameter signal continuously collected by the device (for example, a wearable device) within a preset time period, which may include photoplethysmograph (photoplethysmograph).
  • graphy collects a pulse wave signal, and the heart rate information obtained based on the pulse wave signal may also include an electrocardio gram (ECG) collected by an electrocardiogram.
  • ECG electrocardio gram
  • Step 22 Based on the characteristic value vector of the physiological parameter signal and the pressure evaluation system, determine the lowest pressure state value of the user within a preset time period.
  • the server or the above-mentioned electronic device may analyze the acquired physiological parameter signal of the user to obtain the characteristic value vector of the physiological parameter signal.
  • the feature value vector of the physiological parameter signal corresponding to the user at each time within the preset time period can be obtained.
  • the eigenvalue vector corresponding to the heart rate information is obtained by performing heart rate variability (HRV) analysis on the heart rate information
  • the eigenvalue vector corresponding to the ECG information is obtained by performing frequency spectrum analysis on the ECG signal.
  • HRV heart rate variability
  • the stress assessment system may be an existing equipment or device with stress assessment capability.
  • the characteristic value vector of the physiological parameter signal corresponding to each moment is input into the stress assessment system, and the stress assessment system may Obtain the pressure state value at each moment, and compare the pressure state value at each moment to obtain the user's lowest pressure state value within the preset time period.
  • Step 23 Determine the calibration information according to the lowest reference pressure value of the user's group and the aforementioned lowest pressure state value.
  • the user’s lowest pressure state value within the preset time period determined in step 22 and the lowest reference pressure value of the user’s population are combined, and the user’s lowest pressure state value within the preset time period is compared with the user’s location.
  • the lowest reference pressure value of the crowd is matched, and the difference between the lowest reference pressure value and the lowest pressure state value is determined, and then the difference is used as the calibration information of the pressure assessment system.
  • the calibration information can be used to calibrate the pressure results later, can also be used to calibrate the pressure results of a certain user in a period of time before, and can also be used to calibrate the pressure evaluation system.
  • the specific application method of the calibration information please refer to the record in the following step 24, which will not be repeated here.
  • the lowest pressure state value in this embodiment can be the lowest value determined after vector sorting of the pressure state values at each moment in the preset time period, or it can be the user’s highest value in a day.
  • the pressure state value collected at the moment of relaxation may also be the lowest pressure state value of the user during deep sleep.
  • the embodiment of the present application does not limit the specific method of obtaining the minimum pressure state value of the user within the preset time period, which can be determined according to actual conditions.
  • Step 24 Use the above calibration information to calibrate the pressure state value output by the pressure evaluation system to determine the user's theoretical pressure state value.
  • a calibration module can be connected to the output part of the pressure evaluation system, and the calibration function of the calibration module can be obtained by using the calibration information, so that the pressure evaluation system outputs After the pressure state value is calibrated by the calibration module, the user's theoretical pressure state value can be obtained.
  • the electronic device or server can also use the above calibration information to process the eigenvalue vector of the physiological parameter signal, and then input the processed eigenvalue vector into the stress evaluation system, so that the The pressure evaluation system outputs the theoretical pressure state value of the user.
  • the electronic device or server may also input the calibration information and the characteristic value vector of the physiological parameter signal at the time corresponding to the lowest pressure state value into the pressure evaluation system to update the pressure evaluation
  • the parameters of the system make the output of the pressure evaluation system infinitely close to or equal to the above-mentioned lowest reference pressure value. Therefore, when the physiological parameter signal of the user is obtained, it can be directly input into the stress evaluation system, thereby obtaining the user's theoretical stress state value.
  • the embodiment of the present application does not limit the actual operation method of calibrating the output result of the pressure evaluation system by using the calibration information, which can be determined according to the actual situation, and will not be repeated here.
  • the user does not need to provide self-evaluation opinions, calibration information can be automatically generated, and automatic calibration of the pressure evaluation results is realized. It has a self-learning and real-time update mechanism, that is, a user-insensitive pressure calibration is realized. A good balance is achieved between the accuracy of the stress assessment and the user experience.
  • the stress evaluation and calibration method determines the user’s lowest stress state value within a preset period of time by acquiring the physiological parameter signal of the user, based on the characteristic value vector of the physiological parameter signal and the stress evaluation system, according to the user’s location
  • the minimum reference pressure value and the minimum pressure state value of the crowd determine the calibration information, and use the calibration information to calibrate the pressure state value output by the pressure evaluation system to determine the user's theoretical pressure state value.
  • the user does not need to provide self-evaluation opinions, and calibration information can be automatically generated, which realizes the automatic calibration of the pressure evaluation results, improves the evaluation accuracy, does not require the subjective participation of the user, and improves the user experience.
  • FIG. 3 is a schematic flowchart of Embodiment 2 of the pressure evaluation and calibration method provided by the embodiment of this application. As shown in Figure 3, the above step 22 can be implemented through the following steps:
  • Step 31 Obtain the eigenvalue vector corresponding to the physiological parameter signal at each time within the preset time period.
  • the eigenvalue vector includes: at least one eigenvalue component.
  • the physiological parameter signal may be extracted by feature extraction to obtain the characteristic corresponding to the physiological parameter signal of the user at each moment. Value vector and store it accordingly.
  • the feature value vector of the physiological parameter signal may include time domain and frequency domain features.
  • v_j ⁇ v_1j,v_2j,v_3j,...,v_nj ⁇
  • v_j represents the eigenvalue at the j-th time
  • v_nj represents the nth eigenvalue component in the eigenvalue vector at the jth time.
  • the feature value vector of the heart rate information includes time domain and frequency domain features obtained through heart rate variability analysis.
  • the eigenvalue vector of the heart rate information may include the total power (TP) spectrum, high frequency (HF) segment, and low frequency (LF) segment of the heart rate spectrum curve in the frequency domain. It may also include eigenvalue components such as the standard deviation of NN interval (SDNN) in the time domain feature.
  • SDNN standard deviation of NN interval
  • the LF segment reflects the dual regulation of sympathetic and vagus nerves
  • the HF segment only reflects the regulation of the vagus nerve
  • TP reflects the size of HRV
  • SDNN is used to evaluate the overall change in heart rate
  • the NN interval can be a preset time period.
  • HF 1.0
  • LF 2.0
  • SDNN 1.1 ⁇
  • the feature value vector of the central rate information in the embodiment of the present application is not limited to include the above-mentioned frequency domain feature index and time domain feature index, and it may also include other time domain feature indicators and frequency domain feature indicators.
  • the time-domain feature index may also include: HRV triangle index, standard deviation of the average of all NN intervals (SDANN), and root mean square value (RMSSD) of the difference between adjacent NN intervals throughout the entire process.
  • HRV triangle index is also used to evaluate the overall change in heart rate
  • SDANN is used to evaluate the long-term slow change component in the heart rate change
  • RMSSD reflects the size of the fast change component in the heart rate.
  • the frequency domain characteristic index may also include: very low frequency (VLF) segment and LF/HF ratio.
  • VLF very low frequency
  • LF/HF ratio reflects the balance state of the autonomic nervous system and basically represents the level of sympathetic nervous tension.
  • Step 32 For the eigenvalue vector at each time, input the eigenvalue vector into the pressure evaluation system to obtain the pressure state value of the user at each time.
  • the stress assessment system may be obtained by training based on the relationship between physiological parameter signals (for example, obtained through a physiological parameter signal sensor) and the user's stress state value (obtained through a psychological measurement scale). Therefore, the pressure evaluation system has the function of determining the pressure state value according to the characteristic value vector of the physiological parameter signal.
  • the eigenvalue vector can be input to the pressure evaluation system, and correspondingly, the pressure evaluation system can output the pressure state value of the user at the current time.
  • the stress assessment system can be stored locally, so that when the user's physiological parameter signals are obtained, the stress assessment model can be directly used for stress assessment, which can be operated anytime and anywhere, and is easy to implement; the stress assessment system It can also be stored in a cloud server, which can not only reduce the local memory occupied, but also enrich the data volume of the stress assessment system of the cloud server, and then update the general stress assessment system.
  • the embodiment of the present application does not limit the specific storage location of the pressure assessment system, which can be determined according to actual conditions.
  • the pressure state value of the user at each moment is obtained by weighted summation based on each feature value component in the feature value vector and the weight value corresponding to each feature value component.
  • the weight value corresponding to each characteristic value component can be determined based on the contribution value of each characteristic value component in the characteristic value vector to the pressure state value. Therefore, for the eigenvalue vector at each moment, each eigenvalue component in the eigenvalue vector at the current moment and the corresponding weight value can be weighted and summed to obtain the pressure state value of the user at the current moment.
  • Step 33 Determine the lowest pressure state value of the user in the preset time period according to the pressure state value of the user at each moment in the preset time period.
  • the lowest pressure state value with the smallest value can be determined by comparing the magnitude of each pressure state value one by one.
  • the pressure evaluation and calibration method obtaineds the eigenvalue vector corresponding to each time of the physiological parameter signal within a preset time period, and inputs the eigenvalue vector into the pressure evaluation system for the eigenvalue vector at each time, Obtain the pressure state value of the user at each moment, and finally determine the lowest pressure state value of the user in the preset time period according to the pressure state value of the user at each time in the preset time period.
  • the user's lowest pressure state value within a preset time period can be determined, that is, the pressure state value at the most relaxed moment, which provides the possibility to determine the calibration information later .
  • FIG. 4 is a schematic flowchart of Embodiment 3 of the pressure evaluation and calibration method provided by the embodiment of the application. As shown in Figure 4, before step 23, the method may further include the following steps:
  • Step 41 Obtain basic user information.
  • the basic information includes: height, weight, gender, and age.
  • the wearable device can collect the user's basic information, such as gender, height, weight, age, etc., and it can also obtain the wearable device when the wearable device is used by the user Other information about the user, such as sleep duration, sleep quality.
  • the electronic device, wearable device, or server needs to evaluate the stress state of the user, it can first obtain the above-mentioned basic information of the user, which lays the foundation for the subsequent determination of the reference pressure range of the group to which the user belongs.
  • the embodiment of the present application does not limit the basic information of the user to be acquired.
  • the basic information may also be basic information such as the user's age information, schedule information, travel information, and occupation information.
  • the content included in the basic user information can be determined according to the actual situation, and will not be repeated here.
  • Step 42 Determine the group identification to which the user belongs based on the above basic information.
  • each corresponding group has a corresponding Crowd logo.
  • the population participating in the survey may also be divided into different groups, such as scientific and technical personnel, medical personnel, and teachers. , Students, freelancers, etc. Correspondingly, each group has a corresponding group ID.
  • the group identification to which the user belongs can be determined.
  • Step 43 Based on the group identification to which the user belongs, query the pressure value database to determine the lowest reference pressure value of the group where the user belongs.
  • the pressure value database stores the corresponding relationship between the crowd identification and the reference pressure range.
  • the stress state values of different users in a preset time period through questionnaire surveys, or determine the stress state values of different users in a preset time period based on the user's subjective self-evaluation. Integrating the stress status values of all users participating in the survey, determine the benchmark pressure range corresponding to different groups of people.
  • different group identifications and reference pressure ranges corresponding to the group identifications may be stored in the pressure value database, so as to determine the lowest reference pressure value for evaluating the user.
  • the pressure value database can be stored in a cloud server, which not only can avoid occupying local memory, but also can enrich the data volume of the pressure value database in the cloud server, thereby realizing the update of the pressure value database.
  • the pressure value database can also be stored locally, so that when the group ID of the user is determined, the lowest reference pressure value of the group of the user can be queried based on the group ID of the user.
  • the response speed is relatively fast, anytime, anywhere It can be operated, for example, it can still be operated where there is no network, so as to obtain the lowest baseline pressure value of the user's group.
  • the minimum reference pressure value may be a value or a range, etc., which may be determined according to actual conditions, and this embodiment does not limit it.
  • the stress evaluation and calibration method obtained by the embodiments of the present application obtains the user’s basic information, determines the user’s identity based on the above basic information, and queries the stress database based on the user’s identity to determine the user’s population.
  • the lowest reference pressure value determines the lowest reference pressure value of the user's population, so that the calibration information of the pressure assessment system can be automatically determined, without the user's active participation, and the user experience is improved.
  • FIG. 5 is a schematic flowchart of Embodiment 4 of the pressure evaluation and calibration method provided by the embodiments of this application. As shown in Figure 5, the above step 24 can be implemented through the following steps:
  • Step 51 Input the eigenvalue vector of the physiological parameter signal into the pressure evaluation system to obtain the predicted pressure state value.
  • the pressure evaluation system since the pressure evaluation system has the function of pressure evaluation, but the accuracy is not high, therefore, after acquiring the physiological parameter signal, the eigenvalue vector of the physiological parameter signal can be first input into the pressure evaluation system, Obtain the predicted pressure state value output by the pressure evaluation system.
  • HF 1.0
  • LF 2.0
  • SDNN 1.1 ⁇
  • Step 52 Use the above calibration information to calibrate the predicted pressure state value to obtain the user's theoretical pressure state value.
  • the range of the pressure state value in the embodiment of the present application may be 0-100, but the embodiment of the present application does not limit the value.
  • the stress evaluation and calibration method provided by the embodiment of the application obtains the predicted pressure state value by inputting the characteristic value vector of the physiological parameter signal into the pressure evaluation system, and uses the calibration information to calibrate the predicted pressure state value to obtain the user’s State the theoretical pressure state value.
  • the obtained pressure evaluation result is highly accurate, and the user does not need to give an evaluation, which improves the user experience.
  • FIG. 6 is a schematic structural diagram of Embodiment 1 of a pressure evaluation and calibration device provided by an embodiment of the application.
  • the device can be integrated in an electronic device or server, and can also be implemented by an electronic device or server.
  • the device may include: an acquisition module 61, a processing module 62, and a calibration module 63.
  • the acquisition module 61 is used to acquire physiological parameter signals of the user
  • the processing module 62 is used to determine the minimum pressure state value of the user within a preset time period based on the characteristic value vector of the physiological parameter signal and the pressure evaluation system, and to determine the minimum reference pressure value of the user's population and The minimum pressure state value determines the calibration information;
  • the calibration module 63 is configured to use the calibration information to calibrate the pressure state value output by the pressure evaluation system to determine the theoretical pressure state value of the user.
  • the obtaining module 61 is further configured to obtain the feature value vector corresponding to each time of the physiological parameter signal within the preset time period;
  • the processing module 62 is specifically configured to input the eigenvalue vector into the stress evaluation system for the eigenvalue vector at each moment to obtain the stress state value of the user at each moment, and according to the user’s current
  • the pressure state value at each time within the preset time period determines the lowest pressure state value of the user within the preset time period.
  • the feature value vector includes: at least one feature value component; the pressure state value of the user at each moment is based on each feature value component and each feature value component in the feature value vector.
  • the weight value corresponding to the eigenvalue component is obtained by weighted summation.
  • the above-mentioned obtaining module 61 is further configured to, in the processing module 62, according to the lowest reference pressure value and the lowest pressure state value of the group where the user is located, Before the calibration information is determined, basic information of the user is obtained;
  • the processing module 62 is also configured to determine the identity of the group to which the user belongs based on the basic information, query the pressure value database based on the identity of the group to which the user belongs, and determine the lowest reference pressure value of the group where the user is located.
  • the pressure value database stores the corresponding relationship between the group identification and the reference pressure range.
  • the calibration module 63 is specifically configured to input the characteristic value vector of the physiological parameter signal into the pressure evaluation system to obtain the predicted pressure state value, Using the calibration information to calibrate the predicted pressure state value to obtain the theoretical pressure state value of the user.
  • the pressure evaluation and calibration device of this embodiment can be used to implement the implementation schemes of the method embodiments shown in FIGS. 2 to 5, and the specific implementation methods and technical effects are similar, and will not be repeated here.
  • the division of the various modules of the above device is only a division of logical functions. In actual implementation, it can be fully or partially integrated into a physical entity or physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be implemented in the form of hardware; some modules can be implemented in the form of calling software by processing elements, and some of the modules can be implemented in the form of hardware.
  • the determining module may be a separately established processing element, or it may be integrated into a certain chip of the above-mentioned device for implementation. In addition, it may also be stored in the memory of the above-mentioned device in the form of program code, which is determined by a certain processing element of the above-mentioned device.
  • each step of the above method or each of the above modules can be completed by hardware integrated logic circuits in the processor element or instructions in the form of software.
  • the above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuit (ASIC), or one or more microprocessors (digital signal processor, DSP), or, one or more field programmable gate arrays (FPGA), etc.
  • ASIC application specific integrated circuit
  • DSP digital signal processor
  • FPGA field programmable gate arrays
  • the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call program codes.
  • CPU central processing unit
  • these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).
  • SOC system-on-a-chip
  • the above embodiments it may be implemented in whole or in part by software, hardware, firmware or any combination thereof.
  • software it can be implemented in the form of a computer program product in whole or in part.
  • the computer program product includes one or more computer instructions.
  • the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
  • the computer instructions may be stored in a readable storage medium, or transmitted from one readable storage medium to another readable storage medium.
  • the computer instructions may be transmitted from a website, computer, server, or data center through a wired (for example, coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) means to transmit to another website, computer, server or data center.
  • the readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center integrated with one or more available media.
  • the usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, and a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)).
  • FIG. 7 is a schematic structural diagram of Embodiment 2 of a pressure evaluation and calibration device provided by an embodiment of the application.
  • the device may include a processor 71, a memory 72, a communication interface 73, and a system bus 74.
  • the memory 72 and the communication interface 73 are connected to the processor 71 through the system bus 74 and To complete mutual communication, the memory 72 is used to store a computer program, the communication interface 73 is used to communicate with other devices, and the processor 71 executes the computer program as shown in FIGS. 2 to 5 above. Example method.
  • the system bus mentioned in FIG. 7 may be a peripheral component interconnect standard (PCI) bus or an extended industry standard architecture (EISA) bus, etc.
  • PCI peripheral component interconnect standard
  • EISA extended industry standard architecture
  • the system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.
  • the communication interface is used to realize the communication between the database access device and other devices (such as client, read-write library and read-only library).
  • the memory may include random access memory (RAM), and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
  • the above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (Network Processor, NP), etc.; it may also be a digital signal processor (Digital Signal Processing, DSP), a dedicated integrated Circuits (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.
  • CPU central processing unit
  • NP Network Processor
  • DSP Digital Signal Processing
  • ASIC Application Specific Integrated Circuit
  • FPGA Field-Programmable Gate Array
  • an embodiment of the present application further provides a storage medium that stores instructions in the storage medium, and when the storage medium runs on a computer, the computer executes the method of the embodiment shown in FIG. 2 to FIG. 5.
  • an embodiment of the present application further provides a chip for executing instructions, and the chip is configured to execute the method of the embodiment shown in FIG. 2 to FIG. 5.
  • An embodiment of the present application further provides a program product, the program product includes a computer program, the computer program is stored in a storage medium, at least one processor can read the computer program from the storage medium, and the at least one When the processor executes the computer program, the method of the embodiment shown in FIG. 2 to FIG. 5 can be implemented.
  • At least one refers to one or more, and “multiple” refers to two or more.
  • “And/or” describes the association relationship of the associated objects, indicating that there can be three relationships, for example, A and/or B, which can mean: A alone exists, both A and B exist, and B exists alone, where A, B can be singular or plural.
  • the character “/” generally indicates that the associated objects before and after are in an “or” relationship; in the formula, the character “/” indicates that the associated objects before and after are in a “division” relationship.
  • “The following at least one item (a)” or similar expressions refers to any combination of these items, including any combination of a single item (a) or plural items (a).
  • at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple One.
  • the size of the sequence numbers of the foregoing processes does not mean the order of execution.
  • the execution order of each process should be determined by its function and internal logic, and should not be implemented in this application.
  • the implementation process of the example constitutes any limitation.

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Abstract

一种压力评估校准方法、装置及存储介质。该压力评估校准方法包括：获取用户的生理参数信号（21）；基于该生理参数信号的特征值矢量和压力评估系统（11），确定用户在预设时长内的最低压力状态值（22）；根据该用户所在人群的最低基准压力值和最低压力状态值，确定出校准信息（23）；并且利用该校准信息对压力评估系统（11）输出的压力状态值进行校准，确定用户的理论压力状态值（24）。该压力评估校准方法和装置，可以实现对压力评估结果的自动校准，提高了评估的准确性，不需要用户的主观参与，提升了用户的体验。

Description

压力评估校准方法、装置及存储介质
本申请要求在2019年4月16日提交中国国家知识产权局、申请号为201910304393.8、发明名称为“压力评估校准方法、装置及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及信息处理技术领域，尤其涉及一种压力评估校准方法、装置及存储介质。
背景技术
心理压力是外界环境的变化和机体内部状态所造成的人的生理变化和情绪波动，通常伴随着正面或负面的情绪。定性定量地评测用户的心理压力不仅有助于身体情况的辅助预警，而且可以辅助用户合理安排工作计划，进而提高工作效率。因而，如何准确评估人们的心理压力逐渐成为业界关注和研究的重要问题之一。
现有技术中，随着可穿戴设备的兴起和便携性，其逐渐成为用户压力的新载体，基于可穿戴设备检测到的心理参数信号和现有评测系统可以得到压力评估结果，然后再基于在评估前或评估后采样得到的用户自评信息对上述压力评估结果进行校准，最后得到实际压力评测结果。
然而，上述对压力评估结果进行校准的方案中需要通过用户答题的方式获取用户自评信息，由于用户的主观不确定性，存在评估结果准确度低，用户体验差的问题。
发明内容
本申请实施例提供一种压力评估校准方法、装置及存储介质，以解决现有压力评估结果准确度低、用户体验差的问题。
本申请第一方面提供一种压力评估校准方法，适用于电子设备或服务器，所述方法包括：
获取用户的生理参数信号；
基于所述生理参数信号的特征值矢量和压力评估系统，确定所述用户在预设时长内的最低压力状态值；
根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息；
利用所述校准信息对所述压力评估系统输出的压力状态值进行校准，确定所述用户的理论压力状态值。
在本实施例中，基于获取到的用户的生理参数信号的特征值矢量以及该用户所在人群的最低基准压力值，确定出该压力评估系统的校准信息，并利用该校准信息对压力评估系统输出的压力状态值进行校准，从而确定出用户的理论压力状态值，也即，该技术方案不需要用户提供自评意见，可以自动生成校准信息，实现了对压力评估结果的自动校准，提高了评估准确性，不需要用户的主观参与，提升了用户体验。
在第一方面的一种可能实现方式中，所述基于所述生理参数信号的特征值矢量和压力评估系统，确定所述用户在预设时长内的最低压力状态值，包括：
获取所述生理参数信号在所述预设时长内各个时刻对应的特征值矢量；
对于每个时刻的特征值矢量，将所述特征值矢量输入到所述压力评估系统中，得到所述用户在每个时刻的压力状态值；
根据所述用户在所述预设时长内每个时刻的压力状态值，确定所述用户在所述预设时长内的最低压力状态值。
在本实施例中，基于生理参数信号的特征值矢量可以确定出用户在预设时长内的最低压力状态值，也即，最放松时刻的压力状态值，其为后续确定出校准信息提供了实现可能。
可选的，所述特征值矢量包括：至少一个特征值分量；所述用户在每个时刻的压力状态值是基于所述特征值矢量中每个特征值分量和每个特征值分量对应的权重值进行加权求和得到的。
在第一方面的另一种可能实现方式中，在所述根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息之前，所述方法还包括：
获取所述用户的基本信息；
根据所述基本信息，确定所述用户所属的人群标识；
基于所述用户所属的人群标识，查询压力值数据库，确定所述用户所在人群的最低基准压力值，所述压力值数据库中存储有人群标识与基准压力范围的对应关系。
在本实施例中，根据用户的基本信息可以确定出该用户所在人群的最低基准压力值，这样可以自动确定出压力评估系统的校准信息，不需要用户主动参与，提升了用户体验。
在第一方面的再一种可能实现方式中，所述利用所述校准信息对所述压力评估系统输出的压力状态值进行校准，确定所述用户的理论压力状态值，包括：
将所述生理参数信号的特征值矢量输入到所述压力评估系统中，得到预测压力状态值；
利用所述校准信息对所述预测压力状态值进行校准，得到所述用户的所述理论压力状态值。
该技术方案通过利用校准信息对压力评估系统输出的预测压力状态值进行校准，得到的压力评估结果准确度高，而且不需要用户给出测评，提高了用户体验。
本申请第二方面提供一种压力评估校准装置，包括：获取模块、处理模块和校准模块；
所述获取模块，用于获取用户的生理参数信号；
所述处理模块，用于基于所述生理参数信号的特征值矢量和压力评估系统，确定所述用户在预设时长内的最低压力状态值，以及根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息；
所述校准模块，用于利用所述校准信息对所述压力评估系统输出的压力状态值进行校准，确定所述用户的理论压力状态值。
在第二方面的一种可能实现方式中，所述获取模块，还用于获取所述生理参数信号在所述预设时长内各个时刻对应的特征值矢量；
所述处理模块，具体用于对于每个时刻的特征值矢量，将所述特征值矢量输入到所述压力评估系统中，得到所述用户在每个时刻的压力状态值，根据所述用户在所述预设时长内每个时刻的压力状态值，确定所述用户在所述预设时长内的最低压力状态值。
可选的，所述特征值矢量包括：至少一个特征值分量；所述用户在每个时刻的压力状态值是基于所述特征值矢量中每个特征值分量和每个特征值分量对应的权重值进行加权求和得到的。
在第二方面的另一种可能实现方式中，所述获取模块，还用于在所述处理模块根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息之前，获取所述用户的基本信息；
所述处理模块，还用于根据所述基本信息，确定所述用户所属的人群标识，基于所述用户所属的人群标识，查询压力值数据库，确定所述用户所在人群的最低基准压力值，所述压力值数据库中存储有人群标识与基准压力范围的对应关系。
在第二方面的再一种可能实现方式中，所述校准模块，具体用于将所述生理参数信号的特征值矢量输入到所述压力评估系统中，得到预测压力状态值，利用所述校准信息对所述预测压力状态值进行校准，得到所述用户的所述理论压力状态值。
关于第二方面中各可能实现方式未详尽的有益技术效果可以参见第一方面中的记载，此处不再赘述。
本申请第三方面提供一种压力评估校准装置，包括处理器、存储器及存储在所述存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现如上述第一方面以及第一方面各种可能实现方式中所述的方法。
本申请第四方面提供一种存储介质，所述存储介质中存储有指令，当其在计算机上运行时，使得计算机执行如上述第一方面以及第一方面各种可能实现方式中所述的方法。
本申请第五方面提供一种包含指令的程序产品，当其在计算机上运行时，使得计算机执行上述第一方面以及第一方面各种可能实现方式中所述的方法。
本申请第六方面提供一种芯片，所述芯片包括存储器、处理器，存储器中存储代码和数据，存储器与所述处理器耦合，处理器运行存储器中的代码使得芯片用于执行上述第一方面以及第一方面各种可能实现方式中所述的方法。
本申请实施例提供的压力评估校准方法、装置及存储介质，通过获取用户的生理参数信号，基于该生理参数信号的特征值矢量和压力评估系统，确定用户在预设时长内的最低压力状态值，根据该用户所在人群的最低基准压力值和最低压力状态值，确定出校准信息，并且利用该校准信息对压力评估系统输出的压力状态值进行校准，确定用户的理论压力状态值。该技术方案中，可以实现对压力评估结果的自动校准，提高了评估准确性，不需要用户的主观参与，提升了用户体验。
附图说明
图1为本申请实施例提供的压力评估校准系统的结构示意图；
图2为本申请实施例提供的压力评估校准方法实施例一的流程示意图；
图3为本申请实施例提供的压力评估校准方法实施例二的流程示意图；
图4为本申请实施例提供的压力评估校准方法实施例三的流程示意图；
图5为本申请实施例提供的压力评估校准方法实施例四的流程示意图；
图6为本申请实施例提供的压力评估校准装置实施例一的结构示意图；
图7为本申请实施例提供的压力评估校准装置实施例二的结构示意图。
具体实施方式
本申请下述各实施例提供的压力评估校准方法，可适用于压力评估校准系统。图1为本申请实施例提供的压力评估校准系统的结构示意图。如图1所示，该压力评估校准系统可以 包括：两两相互连接的压力评估系统11、处理模块12和校准模块13。
其中，该压力评估系统11可以是具有压力评测能力的设备，其可以获取用户的生理参数信号，并对该生理参数信号进行分析，输出该压力评估系统确定的用户心理压力值；该处理模块12可以获取压力评估系统11确定的用户压力值，并基于获取到的该用户所属人群的基准压力值对上述用户压力值进行处理得到该用户压力值的校准信息；该校准模块13可以获取该压力评估系统11确定的用户压力值和该处理模块12得到的校准信息，并利用该校准信息对上述用户压力值进行校准处理，进而得到理论压力状态值。
本申请实施例并不限定压力评估校准系统的具体组成，其还可以包括其他的模块，例如，存储模块，通信接口等，关于该压力评估校准系统的具体组成可以根据实际情况进行限定，此处不再赘述。
本申请实施例中，“多个”是指两个或两个以上。“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。字符“/”一般表示前后关联对象是一种“或”的关系。
下面首先针对本申请实施例适用场景进行简要说明。
随着社会经济的飞速发展、生活节奏的加快，人们每时每刻都在承受着各种压力，竞争激烈使得心理健康问题日益凸显。心理学研究表明，生活中的一些事件是造成心理压力进而损害健康的主要压力源，而且工作绩效和压力呈倒U型曲线关系。适度的压力能够提高工作效率；高负荷的压力极有可能导致“压力危机”，从而影响到人们的心理健康。
精神压力对人们的工作生活效率、生活品质等方面都有重要影响。长期处于有压力状态会诱使各类疾病的发生，如易疲劳，记忆力下降，食欲不振，甚至心悸、呼吸不畅、腹部绞痛等。因而，全面评估人们的压力状态值可以使人们及时掌握自己的压力水平，以全面了解自身压力的具体来源，以便获得科学、专业、有针对性的压力调节方案，从而有效维护和促进自身的身心健康。
此外，定性定量地评测用户的精神压力也是有一定价值的，有助于运动类、服务类商品的推送，有助于身体情况的辅助预警，而且能够进行压力过大提醒，比如，分析出人们在日常的哪个时间段精神状态较好，这样可以使得人们合理安排工作，从而提升工作效率等。
随着可穿戴设备的兴起以及可穿戴设备的随身便携性，可穿戴设备逐渐成为精神压力评测的新载体，越来越多的可穿戴设备可以在日常的情景下采集人们的生理参数信号，例如，心率值、皮肤温度等，从而展示给用户。
目前，对于现有压力评估系统的压力评估结果，通常是在评估前或评估后采样得到的用户自评信息对上述压力评估结果进行校准，最后得到实际压力评测结果，但是上述校准方式均需要用户通过答题的方式获取用户自评信息，存在用户体验差以及主观不确定性等问题。
针对上述问题，本申请实施例提供了一种压力评估校准方法，通过获取用户的生理参数信号，基于该生理参数信号的特征值矢量和压力评估系统，确定用户在预设时长内的最低压力状态值，根据该用户所在人群的最低基准压力值和最低压力状态值，确定出校准信息，并且利用该校准信息对压力评估系统输出的压力状态值进行校准，确定用户的理论压力状态值。该技术方案中，可以实现对压力评估结果的自动校准，提高了评估准确性，不需要用户的主观参与，提升了用户体验。
下面，通过具体实施例对本申请的技术方案进行详细说明。需要说明的是，下面这几个具体的实施例可以相互结合，对于相同或相似的概念或过程可能在某些实施例中不再赘述。
图2为本申请实施例提供的压力评估校准方法实施例一的流程示意图。该方法可以适用 于图1所示的压力评估校准系统，该系统可以通过服务器实现，也可以通过其他具有评估和校准能力的电子设备实现。示例性的，该电子设备可以是手环、智能手表等可穿戴设备。可选的，如图2所示，该压力评估校准方法可以包括如下步骤：
步骤21：获取用户的生理参数信号。
可选的，日常情景中存在有较多具有生理参数信号采集的设备或装置，例如，手环、智能手表等设备，因而，其可以采集用户的生理参数信号，并基于采集到的生理参数信号对用户心理压力数值级别进行评测和跟踪。
示例性的，对于具有心率采集器的装置，例如，手环、智能手表，其可以采集用户的心率值，进而根据用户的心率值评估该用户的压力状态值，根据用户在预设时间段内的压力状态值对用户的心理压力进行评测和跟踪。
在本实施例中，服务器或上述电子设备可以获取用户的生理参数信号，进而对该生理参数信号进行处理。示例性的，该生理参数信号可以包括：心率信息、心电信息、血压信息、体重信息等不同的生理信号。
具体的，在本实施例中，服务器或上述电子设备可以获取设备(例如，可穿戴设备)在预设的时间段内持续采集的生理参数信号，其可以包括通过光电容积脉搏波描记(photo plethysmo graphy，PPG)采集脉搏波信号，并基于该脉搏波信号得到的心率信息，也可以包括通过心电图(electro cardio gram，ECG)采集的心电信号。
关于本申请实施例中，获取到的生理参数信号的具体参数，其可以根据实际情况确定，此处不再赘述。
步骤22：基于该生理参数信号的特征值矢量和压力评估系统，确定该用户在预设时长内的最低压力状态值。
示例性的，在本实施例中，服务器或上述电子设备可以对获取到的用户的生理参数信号进行分析，从而得出该生理参数信号的特征值矢量。同理，对用户在预设时长内每个时刻的生理参数信号进行分析，可以得到用户在该预设时长内每个时刻对应的该生理参数信号的特征值矢量。例如，通过对心率信息进行心率变异性分析(heart rate variability，HRV)得到该心率信息对应的特征值矢量，通过对心电信号进行频谱分析得到该心电信息对应的特征值矢量。
在本实施例中，该压力评估系统可以是现有的具有压力评估能力的设备或装置，将每个时刻对应的生理参数信号的特征值矢量输入到该压力评估系统中，该压力评估系统可以得到每个时刻的压力状态值，比较每个时刻的压力状态值可以得到用户在该预设时长内的最低压力状态值。
步骤23：根据该用户所在人群的最低基准压力值和上述最低压力状态值，确定出校准信息。
可选的，对于可采集用户生理参数信号的可穿戴设备，用户在使用可穿戴设备之前，可以首先采集用户的身高、体重、性别等基本信息，在用户使用该可穿戴设备时，该可穿戴设备还可以采集用户的睡眠时长、睡眠质量等其他的基本信息，因而，基于该用户的上述基本信息可以确定出该用户所属的人群，比如，婴幼儿、儿童、青少年、中年人、老年人等，最后根据该用户所在人群的基准压力值范围，确定出该用户所在人群的最低基准压力值。
在本实施例中，结合上述步骤22确定的用户在预设时长内的最低压力状态值和该用户所在人群的最低基准压力值，将用户在预设时长内的最低压力状态值与该用户所在人群的最低基准压力值进行匹配，确定出该最低基准压力值与该最低压力状态值之间的差值，进而将该 差值作为压力评估系统的校准信息。
可选的，该校准信息可以用于之后的压力结果校准，也可以用于某用户在之前的一段时间内的压力结果校准，还可以用于对压力评估系统的校准。关于校准信息的具体应用方式可以参照下述步骤24中的记载，此处不再赘述。
值得说明的是，在本实施例中，本实施例中的最低压力状态值可以是预设时长内每个时刻的压力状态值进行矢量排序后确定的最低值，也可以是用户在一天内最放松时刻采集到的压力状态值，还可以是用户在深度睡眠期间的最低压力状态值。本申请实施例并不限定用户在预设时长内最低压力状态值的具体获取方式，其可以根据实际情况确定。
步骤24：利用上述校准信息对压力评估系统输出的压力状态值进行校准，确定该用户的理论压力状态值。
示例性的，在本实施例中，当确定出上述校准信息后，可以在压力评估系统的输出部分连接一个校准模块，该校准模块的校准功能可以利用该校准信息得到，这样压力评估系统输出的压力状态值经过校准模块的校准后可以得到该用户的理论压力状态值。
在本实施例的一种可能设计中，电子设备或服务器也可以利用上述校准信息对生理参数信号的特征值矢量进行处理，再将处理后的特征值矢量输入到压力评估系统中，从而使得该压力评估系统输出该用户的理论压力状态值。
在本实施例的另一种可能设计中，电子设备或服务器也可以将该校准信息和最低压力状态值对应时刻的生理参数信号的特征值矢量一同输入到该压力评估系统中，更新该压力评估系统的参数，使得该压力评估系统的输出无限接近或者等于上述最低基准压力值。因而，当获取到用户的生理参数信号后，可以直接将其输入到该压力评估系统中，从而得到用户的理论压力状态值。
值得说明的是，本申请实施例并不限定利用校准信息对压力评估系统的输出结果进行校准的实际操作方式，其可以根据实际情况确定，此处不再赘述。
在本实施例中，不需要用户提供自评意见，可以自动生成校准信息，实现了对压力评估结果的自动校准，具有自学习、实时更新的机制，即实现了用户无感的压力校准，在压力评估精度和用户体验方面取得较好的平衡。
本申请实施例提供的压力评估校准方法，通过获取用户的生理参数信号，基于该生理参数信号的特征值矢量和压力评估系统，确定用户在预设时长内的最低压力状态值，根据该用户所在人群的最低基准压力值和最低压力状态值，确定出校准信息，并且利用该校准信息对压力评估系统输出的压力状态值进行校准，确定用户的理论压力状态值。该技术方案中，不需要用户提供自评意见，可以自动生成校准信息，实现了对压力评估结果的自动校准，提高了评估准确性，不需要用户的主观参与，提升了用户体验。
示例性的，在上述实施例的基础上，图3为本申请实施例提供的压力评估校准方法实施例二的流程示意图。如图3所示，上述步骤22可以通过如下步骤实现：
步骤31：获取上述生理参数信号在预设时长内各个时刻对应的特征值矢量。
其中，该特征值矢量包括：至少一个特征值分量。
可选的，在本实施例中，电子设备(例如，可穿戴设备)或服务器获取到生理参数信号后可以通过对生理参数信号进行特征提取，获取用户在每个时刻的生理参数信号对应的特征值矢量，并对其进行相应的存储。其中，生理参数信号的特征值矢量可以包括时域和频域的特征。
示例性的，对于预设时长内的第j时刻，假设用户的生理参数信号对应的特征值矢量为 v_j＝{v_1j,v_2j,v_3j,…,v_nj}，其中，v_j表示第j时刻的特征值矢量，v_nj表示第j时刻的特征值矢量中的第n个特征值分量。
例如，当上述生理参数信号为心率信息时，该心率信息的特征值矢量包括通过心率变异性分析得到的时域和频域特征。可选的，心率信息的特征值矢量可以包括频域特征中的心率谱曲线的总功率(total power，TP)谱、高频(high frequency，HF)段、低频(low frequency，LF)段，也可以包括时域特征中的NN间期的标准差(standard deviation of NN interval，SDNN)等特征值分量。
其中，LF段反映交感和迷走神经的双重调节，HF段只反映迷走神经的调节，TP反映HRV的大小，SDNN用于评估心率总体变化的大小，NN间期可以是预设的一个时间段。
例如，对于包括TP谱、HF段、LF段和SDNN等特征值分量的特征值矢量，生理参数信号在第1时刻的特征值矢量v_1可以表示为v_1＝{TP＝1.1，HF＝2.0，LF＝3.0，SDNN＝3.1}，在第2时刻的特征值矢量v_2可以表示为v_2＝{TP＝1.2，HF＝1.0，LF＝2.0，SDNN＝1.1}，在第3时刻的特征值矢量v_3可以表示为v_3＝{TP＝1.5，HF＝3.0，LF＝6.0，SDNN＝0}，类似的，对于其他时刻的特征值矢量可以采用相同的方式表示。
值得说明的是，本申请实施例中心率信息的特征值矢量并不局限于包括上述频域特征指标和时域特征指标，其还可以包括其他的时域特征指标和频域特征指标。
例如，时域特征指标还可以包括：HRV三角形指数、全部NN间期平均值的标准差(SDANN)和全程相邻NN间期之差的均方根值(RMSSD)。其中，该HRV三角形指数也用于评估心率总体变化的大小，该SDANN用于评估心率变化中的长期慢变化成分，该RMSSD反映心率快变化成分的大小。
频域特征指标还可以包括：极低频(VLF)段和LF/HF比值。其中，该VLF反映心率变化受热调节(体温)，血管舒缩张力和肾血管紧张素系统的影响，该LF/HF比值反映自主神经系统的平衡状态，基本上代表交感神经张力的高低。
步骤32：对于每个时刻的特征值矢量，将该特征值矢量输入到压力评估系统中，得到该用户在每个时刻的压力状态值。
可选的，在本实施例中，压力评估系统可以是根据生理参数信号(例如，通过生理参数信号传感器获得)与用户压力状态值(通过心理测评量表获得)之间的关系训练得到的。因而，该压力评估系统具有根据生理参数信号的特征值矢量确定压力状态值的功能。
相应的，对于每个时刻的特征值矢量，可以将该特征值矢量输入到该压力评估系统中，相应的，该压力评估系统可以输出用户在当前时刻的压力状态值。
在本实施例中，该压力评估系统可以存储在本地，这样当获取到用户的生理参数信号时，可以直接利用该压力评估模型进行压力评估，随时随地均可以操作，易于实现；该压力评估系统还可以存储在云端服务器，这样不但可以减少占用的本地内存，而且可以丰富云端服务器的压力评估系统的数据量，进而对通用的压力评估系统进行更新。本申请实施例并不限定压力评估系统的具体存储位置，其可以根据实际情况确定。
值得说明的是，用户在每个时刻的压力状态值是基于特征值矢量中每个特征值分量和每个特征值分量对应的权重值进行加权求和得到的。
具体的，对于某个生理参数信号，在压力评估模型的训练过程中，可以基于特征值矢量中每个特征值分量对压力状态值的贡献值确定出每个特征值分量对应的权重值。所以，对于每个时刻的特征值矢量，可以将当前时刻的特征值矢量中每个特征值分量与对应的权重值进 行加权求和运算，从而得到用户在当前时刻的压力状态值。
在本实施例中，对于第j时刻的特征值矢量，该第j时刻的压力状态值等于y_j＝v_1j*m_1+v_2j*m_2+…+v_nj*m_n，其中，该m_n为第n个特征值分量的权重值。
例如，本实施例中，假设m_1＝0.1，m_2＝0.2，m_3＝0.5，m_4＝0.2，且第1时刻的特征值矢量v_1＝{TP＝1.1，HF＝2.0，LF＝3.0，SDNN＝3.1}，第2时刻的特征值矢量v_2＝{TP＝1.2，HF＝1.0，LF＝2.0，SDNN＝1.1}，第3时刻的特征值矢量v_3＝{TP＝1.5，HF＝3.0，LF＝6.0，SDNN＝0}，所以，基于公式y_j＝v_1j*m_1+v_2j*m_2+…+v_nj*m_n，可以求出第1时刻的压力状态值y_1＝0.1*1.1+0.2*2.0+0.5*3.0+0.2*3.1＝2.63，第2时刻的压力状态值y_2＝0.1*1.2+0.2*1.0+0.5*2.0+0.2*1.1＝1.54，第3时刻的压力状态值y_3＝0.1*1.5+0.2*3.0+0.5*6.0+0.2*0＝3.75。
步骤33：根据该用户在预设时长内每个时刻的压力状态值，确定该用户在预设时长内的最低压力状态值。
可选的，在本实施例中，通过上述步骤32的方式得到用户在每个时刻的压力状态值之后，可以通过逐个比较每个压力状态值的大小，从中确定出数值最小的最低压力状态值，也可以通过对所有时刻的压力状态值按照预设的顺序(从小到大，或从大到小)进行排序，从而得到数据最低的压力状态值。
示例性，对于该用户的心率信息，根据上述步骤31和步骤32可知，上述3个时刻的压力状态值分别如下：y_1＝2.63、y_2＝1.54和y_3＝3.75，通过比较或排序可知，其中的最低压力状态值为y_2＝1.54，对应的特征值矢量为v_2＝{TP＝1.2，HF＝1.0，LF＝2.0，SDNN＝1.1}。
本申请实施例提供的压力评估校准方法，通过获取生理参数信号在预设时长内各个时刻对应的特征值矢量，对于每个时刻的特征值矢量，将该特征值矢量输入到压力评估系统中，得到用户在每个时刻的压力状态值，最后根据该用户在预设时长内每个时刻的压力状态值，确定该用户在预设时长内的最低压力状态值。该技术方案中，基于生理参数信号的特征值矢量可以确定出用户在预设时长内的最低压力状态值，也即，最放松时刻的压力状态值，其为后续确定出校准信息提供了实现可能。
示例性的，在上述任一实施例的基础上，图4为本申请实施例提供的压力评估校准方法实施例三的流程示意图。如图4所示，在上述步骤23之前，该方法还可以包括如下步骤：
步骤41：获取用户的基本信息。
其中，该基本信息包括：身高、体重、性别、年龄。
通常情况下，可穿戴设备被用户使用之前，该可穿戴设备可以采集用户的基本信息，例如，性别、身高、体重、年龄等，而且在可穿戴设备被用户使用的过程中，其还可以获取用户的其他信息，例如，睡眠时长、睡眠质量。这样，电子设备或可穿戴设备或服务器需要评估用户的压力状态时，可以首先获取该用户的上述基本信息，其为后续确定该用户所属人群的基准压力范围奠定基础。
值得说明的是，本申请实施例并不限定获取的用户的基本信息，例如，该基本信息还可以是用户的年龄信息、作息信息、行程信息、职业信息等基本信息。对于用户基本信息所包括的内容可以根据实际情况确定，此处不再赘述。
步骤42：根据上述基本信息，确定该用户所属的人群标识。
可选的，针对高矮胖瘦、性别、年龄均不相同的用户，将其划分为不同的人群例如，婴幼儿、儿童、青少年、中年人、老年人等，相应的每个人群具有对应的人群标识。
示例性的，在本实施例中，针对用户的年龄信息、作息信息、行程信息、职业信息等基本信息，也可以将参与调查的人群划分为不同的人群，例如，科技人员、医护人员、教师、学生、自由职业者等，相应的，每个人群具有对应的人群标识。
因而，在本实施例中，根据上述获取到的用户的基本信息，可以确定该用户所属的人群标识。
步骤43：基于该用户所属的人群标识，查询压力值数据库，确定该用户所在人群的最低基准压力值。
其中，该压力值数据库中存储有人群标识与基准压力范围的对应关系。
可选的，针对不同的人群，可以通过问卷调查并跟踪不同用户在预设时间段内的压力状态值，或者基于用户的主观自评确定出不同用户在预设时间段内的压力状态值，综合所有参与调查的用户的压力状态值，确定出不同人群对应的基准压力范围。相应的，可以将不同人群标识和该人群标识对应的基准压力范围存储至压力值数据库中，以便确定出评估用户的最低基准压力值。
可选的，该压力值数据库可以存储在云端服务器，这样不但可以避免占用本地内存，而且可以丰富云端服务器中压力值数据库的数据量，进而实现对压力值数据库的更新。该压力值数据库也可以存储在本地，这样当确定出该用户所属的人群标识时，可以基于该用户所属的人群标识查询到该用户所在人群的最低基准压力值，响应速度相对较快，随时随地可以操作，例如，在没有网络的地方仍可操作，从而得到用户所在人群的最低基准压力值。
值得说明的是，该最低基准压力值可以是一个值，也可以为一个范围等，其可以根据实际情况确定，本实施例不对其进行限定。
本申请实施例提供的压力评估校准方法，通过获取用户的基本信息，根据上述基本信息，确定该用户所属的人群标识，以及基于该用户所属的人群标识，查询压力值数据库，确定该用户所在人群的最低基准压力值。该技术方案确定了该用户所在人群的最低基准压力值，这样可以自动确定出压力评估系统的校准信息，不需要用户主动参与，提升了用户体验。
进一步的，在上述任一实施例的基础上，图5为本申请实施例提供的压力评估校准方法实施例四的流程示意图。如图5所示，上述步骤24可以通过如下步骤实现：
步骤51：将上述生理参数信号的特征值矢量输入到该压力评估系统中，得到预测压力状态值。
可选的，由于该压力评估系统具有压力评估的功能，但是准确度不高，因而，在获取到生理参数信号之后，可以首先将上述生理参数信号的特征值矢量输入到该压力评估系统中，获取该压力评估系统输出的预测压力状态值。
例如，根据上述图3所示实施例可知，对于心率信息，该用户在预设时间段内的第一预测压力状态值为y_1＝2.63，对应的特征值矢量为v_1＝{TP＝1.1，HF＝2.0，LF＝3.0，SDNN＝3.1}，第二预测压力状态值为y_2＝1.54，对应的特征值矢量为v_2＝{TP＝1.2，HF＝1.0，LF＝2.0，SDNN＝1.1}，第三预测压力状态值为y_3＝3.75，对应的特征值矢量为v_3＝{TP＝1.5，HF＝3.0，LF＝6.0，SDNN＝0}。
步骤52：利用上述校准信息对该预测压力状态值进行校准，得到用户的理论压力状态值。
在本实施例中，由上述图2所示实施例中的步骤23可知，可以将用户所在人群的最低基准压力值与该用户在预设时长内的最低压力状态值之间的差值作为压力评估系统的校准信息，因而，针对上述用户的心率信息，若用户所在人群的最低基准压力值为Y_min＝15，且上述最低压力状态值为y_2＝1.54，则该压力评估系统的校准信息可以表示为Y_min-y_2＝15- 1.54＝13.46。
因而，在本实施例中，用户的理论压力状态值可以等于上述的预测压力状态值与该校准信息的和，也即，该第一预测压力状态值y_1＝2.63对应的理论压力状态值为y_1+校准信息＝2.63+13.46＝16.09，该第三预测压力状态值y_3＝3.75对应的理论压力状态值为y_3+校准信息＝3.75+13.46＝17.21。
值得说明的是，本申请实施例中的压力状态值的范围可以为0-100，但本申请实施例并不对该数值进行限定。
本申请实施例提供的压力评估校准方法，通过将生理参数信号的特征值矢量输入到压力评估系统中，得到预测压力状态值，利用该校准信息对预测压力状态值进行校准，得到该用户的所述理论压力状态值。该技术方案中，通过利用校准信息对压力评估系统输出的预测压力状态值进行校准，得到的压力评估结果准确度高，而且不需要用户给出测评，提高了用户体验。
图6为本申请实施例提供的压力评估校准装置实施例一的结构示意图。该装置可以集成在电子设备或服务器中，也可以通过电子设备或服务器实现。如图6所示，该装置可以包括：获取模块61、处理模块62和校准模块63。
其中，该获取模块61，用于获取用户的生理参数信号；
该处理模块62，用于基于所述生理参数信号的特征值矢量和压力评估系统，确定所述用户在预设时长内的最低压力状态值，以及根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息；
该校准模块63，用于利用所述校准信息对所述压力评估系统输出的压力状态值进行校准，确定所述用户的理论压力状态值。
示例性的，在本申请实施例的一种可能设计中，该获取模块61，还用于获取所述生理参数信号在所述预设时长内各个时刻对应的特征值矢量；
该处理模块62，具体用于对于每个时刻的特征值矢量，将所述特征值矢量输入到所述压力评估系统中，得到所述用户在每个时刻的压力状态值，根据所述用户在所述预设时长内每个时刻的压力状态值，确定所述用户在所述预设时长内的最低压力状态值。
可选的，在本实施例中，所述特征值矢量包括：至少一个特征值分量；所述用户在每个时刻的压力状态值是基于所述特征值矢量中每个特征值分量和每个特征值分量对应的权重值进行加权求和得到的。
示例性的，在本申请实施例的另一种可能设计中，上述获取模块61，还用于在所述处理模块62根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息之前，获取所述用户的基本信息；
该处理模块62，还用于根据所述基本信息，确定所述用户所属的人群标识，基于所述用户所属的人群标识，查询压力值数据库，确定所述用户所在人群的最低基准压力值，所述压力值数据库中存储有人群标识与基准压力范围的对应关系。
示例性的，在本申请实施例的再一种可能设计中，该校准模块63，具体用于将所述生理参数信号的特征值矢量输入到所述压力评估系统中，得到预测压力状态值，利用所述校准信息对所述预测压力状态值进行校准，得到所述用户的所述理论压力状态值。
本实施例的压力评估校准装置可用于执行图2至图5所示方法实施例的实现方案，具体实现方式和技术效果类似，这里不再赘述。
需要说明的是，应理解以上装置的各个模块的划分仅仅是一种逻辑功能的划分，实际实 现时可以全部或部分集成到一个物理实体上，也可以物理上分开。且这些模块可以全部以软件通过处理元件调用的形式实现；也可以全部以硬件的形式实现；还可以部分模块通过处理元件调用软件的形式实现，部分模块通过硬件的形式实现。例如，确定模块可以为单独设立的处理元件，也可以集成在上述装置的某一个芯片中实现，此外，也可以以程序代码的形式存储于上述装置的存储器中，由上述装置的某一个处理元件调用并执行以上确定模块的功能。其它模块的实现与之类似。此外这些模块全部或部分可以集成在一起，也可以独立实现。这里所述的处理元件可以是一种集成电路，具有信号的处理能力。在实现过程中，上述方法的各步骤或以上各个模块可以通过处理器元件中的硬件的集成逻辑电路或者软件形式的指令完成。
例如，以上这些模块可以是被配置成实施以上方法的一个或多个集成电路，例如：一个或多个特定集成电路(application specific integrated circuit，ASIC)，或，一个或多个微处理器(digital signal processor，DSP)，或，一个或者多个现场可编程门阵列(field programmable gate array，FPGA)等。再如，当以上某个模块通过处理元件调度程序代码的形式实现时，该处理元件可以是通用处理器，例如中央处理器(central processing unit，CPU)或其它可以调用程序代码的处理器。再如，这些模块可以集成在一起，以片上系统(system-on-a-chip，SOC)的形式实现。
在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。所述计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行所述计算机程序指令时，全部或部分地产生按照本申请实施例所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在可读存储介质中，或者从一个可读存储介质向另一个可读存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线(DSL))或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质，(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘solid state disk(SSD))等。
图7为本申请实施例提供的压力评估校准装置实施例二的结构示意图。如图7所示，该装置可以包括：处理器71、存储器72、通信接口73和系统总线74，所述存储器72和所述通信接口73通过所述系统总线74与所述处理器71连接并完成相互间的通信，所述存储器72用于存储计算机程序，所述通信接口73用于和其他设备进行通信，所述处理器71执行所述计算机程序时实现如上述图2至图5所示实施例的方法。
该图7中提到的系统总线可以是外设部件互连标准(peripheral component interconnect，PCI)总线或扩展工业标准结构(extended industry standard architecture，EISA)总线等。所述系统总线可以分为地址总线、数据总线、控制总线等。为便于表示，图中仅用一条粗线表示，但并不表示仅有一根总线或一种类型的总线。通信接口用于实现数据库访问装置与其他设备(例如客户端、读写库和只读库)之间的通信。存储器可能包含随机存取存储器(random access memory，RAM)，也可能还包括非易失性存储器(non-volatile memory)，例如至少一个磁盘存储器。
上述的处理器可以是通用处理器，包括中央处理器(Central Processing Unit，CPU)、网络处理器(Network Processor，NP)等；还可以是数字信号处理器(Digital Signal Processing， DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field－Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。
可选的，本申请实施例还提供一种存储介质，所述存储介质中存储有指令，当其在计算机上运行时，使得计算机执行如上述图2至图5所示实施例的方法。
可选的，本申请实施例还提供一种运行指令的芯片，所述芯片用于执行上述图2至图5所示实施例的方法。
本申请实施例还提供一种程序产品，所述程序产品包括计算机程序，所述计算机程序存储在存储介质中，至少一个处理器可以从所述存储介质读取所述计算机程序，所述至少一个处理器执行所述计算机程序时可实现上述图2至图5所示实施例的方法。
本申请中，“至少一个”是指一个或者多个，“多个”是指两个或两个以上。“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B的情况，其中A，B可以是单数或者复数。字符“/”一般表示前后关联对象是一种“或”的关系；在公式中，字符“/”，表示前后关联对象是一种“相除”的关系。“以下至少一项(个)”或其类似表达，是指的这些项中的任意组合，包括单项(个)或复数项(个)的任意组合。例如，a，b，或c中的至少一项(个)，可以表示：a，b，c，a-b，a-c，b-c，或a-b-c，其中，a，b，c可以是单个，也可以是多个。
可以理解的是，在本申请的实施例中涉及的各种数字编号仅为描述方便进行的区分，并不用来限制本申请的实施例的范围。
可以理解的是，在本申请的实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请的实施例的实施过程构成任何限定。

Claims (12)

  1. 一种压力评估校准方法，其特征在于，包括：
    获取用户的生理参数信号；
    基于所述生理参数信号的特征值矢量和压力评估系统，确定所述用户在预设时长内的最低压力状态值；
    根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息；
    利用所述校准信息对所述压力评估系统输出的压力状态值进行校准，确定所述用户的理论压力状态值。
  2. 根据权利要求1所述的方法，其特征在于，所述基于所述生理参数信号的特征值矢量和压力评估系统，确定所述用户在预设时长内的最低压力状态值，包括：
    获取所述生理参数信号在所述预设时长内各个时刻对应的特征值矢量；
    对于每个时刻的特征值矢量，将所述特征值矢量输入到所述压力评估系统中，得到所述用户在每个时刻的压力状态值；
    根据所述用户在所述预设时长内每个时刻的压力状态值，确定所述用户在所述预设时长内的最低压力状态值。
  3. 根据权利要求2所述的方法，其特征在于，所述特征值矢量包括：至少一个特征值分量；所述用户在每个时刻的压力状态值是基于所述特征值矢量中每个特征值分量和每个特征值分量对应的权重值进行加权求和得到的。
  4. 根据权利要求1-3任一项所述的方法，其特征在于，在所述根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息之前，所述方法还包括：
    获取所述用户的基本信息；
    根据所述基本信息，确定所述用户所属的人群标识；
    基于所述用户所属的人群标识，查询压力值数据库，确定所述用户所在人群的最低基准压力值，所述压力值数据库中存储有人群标识与基准压力范围的对应关系。
  5. 根据权利要求1-4任一项所述的方法，其特征在于，所述利用所述校准信息对所述压力评估系统输出的压力状态值进行校准，确定所述用户的理论压力状态值，包括：
    将所述生理参数信号的特征值矢量输入到所述压力评估系统中，得到预测压力状态值；
    利用所述校准信息对所述预测压力状态值进行校准，得到所述用户的所述理论压力状态值。
  6. 一种压力评估校准装置，其特征在于，包括：获取模块、处理模块和校准模块；
    所述获取模块，用于获取用户的生理参数信号；
    所述处理模块，用于基于所述生理参数信号的特征值矢量和压力评估系统，确定所述用户在预设时长内的最低压力状态值，以及根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息；
    所述校准模块，用于利用所述校准信息对所述压力评估系统输出的压力状态值进行校准，确定所述用户的理论压力状态值。
  7. 根据权利要求6所述的装置，其特征在于，所述获取模块，还用于获取所述生理参数信号在所述预设时长内各个时刻对应的特征值矢量；
    所述处理模块，具体用于对于每个时刻的特征值矢量，将所述特征值矢量输入到所述压力评估系统中，得到所述用户在每个时刻的压力状态值，根据所述用户在所述预设时长内每 个时刻的压力状态值，确定所述用户在所述预设时长内的最低压力状态值。
  8. 根据权利要求7所述的装置，其特征在于，所述特征值矢量包括：至少一个特征值分量；所述用户在每个时刻的压力状态值是基于所述特征值矢量中每个特征值分量和每个特征值分量对应的权重值进行加权求和得到的。
  9. 根据权利要求6-8任一项所述的装置，其特征在于，所述获取模块，还用于在所述处理模块根据所述用户所在人群的最低基准压力值和所述最低压力状态值，确定出校准信息之前，获取所述用户的基本信息；
    所述处理模块，还用于根据所述基本信息，确定所述用户所属的人群标识，基于所述用户所属的人群标识，查询压力值数据库，确定所述用户所在人群的最低基准压力值，所述压力值数据库中存储有人群标识与基准压力范围的对应关系。
  10. 根据权利要求6-9任一项所述的装置，其特征在于，所述校准模块，具体用于将所述生理参数信号的特征值矢量输入到所述压力评估系统中，得到预测压力状态值，利用所述校准信息对所述预测压力状态值进行校准，得到所述用户的所述理论压力状态值。
  11. 一种压力评估校准装置，包括处理器、存储器及存储在所述存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述程序时实现如上述权利要求1-5任一项所述的方法。
  12. 一种存储介质，其特征在于，所述存储介质中存储有指令，当其在计算机上运行时，使得计算机执行如权利要求1-5任一项所述的方法。
PCT/CN2020/084229 2019-04-16 2020-04-10 压力评估校准方法、装置及存储介质 WO2020211702A1 (zh)

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