WO2018090304A1 - 一种精神压力评测方法和装置 - Google Patents

一种精神压力评测方法和装置 Download PDF

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WO2018090304A1
WO2018090304A1 PCT/CN2016/106306 CN2016106306W WO2018090304A1 WO 2018090304 A1 WO2018090304 A1 WO 2018090304A1 CN 2016106306 W CN2016106306 W CN 2016106306W WO 2018090304 A1 WO2018090304 A1 WO 2018090304A1
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pressure
user
discrete
model
indicator
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PCT/CN2016/106306
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English (en)
French (fr)
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许培达
张安琪
朱萸
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华为技术有限公司
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Priority to PCT/CN2016/106306 priority Critical patent/WO2018090304A1/zh
Priority to CN201680080732.3A priority patent/CN108601566B/zh
Priority to US16/462,060 priority patent/US11547334B2/en
Publication of WO2018090304A1 publication Critical patent/WO2018090304A1/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
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14546—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring analytes not otherwise provided for, e.g. ions, cytochromes
    • 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
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • 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
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
    • 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
    • G16H40/60—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 operation of medical equipment or devices
    • G16H40/63—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 operation of medical equipment or devices for local operation
    • 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
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • 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
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02416—Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique
    • A61B5/1128—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique using image analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]

Definitions

  • the present invention relates to the field of mental health application technologies, and in particular, to a mental stress evaluation method and apparatus.
  • wearable devices With the rise of wearable devices, more and more wearable devices can collect people's physiological parameters in daily situations: heart rate, skin temperature and so on. Through long-term collection of physiological data, statistics and predictions can be made more effectively on people's physical health. In addition to physical health, people's mental health problems can not be ignored, the main source of mental health problems is greater mental stress. The development of wearable devices has provided a new vehicle for the evaluation of mental stress.
  • the pressure level or pressure value of the user can be obtained by the user's subjective pressure value or pressure level, the pressure value or pressure level of the user determined according to the psychological statistical analysis according to the result of the pressure questionnaire filled out by the user, according to The pressure value or pressure level of the user determined by the user's cortisol concentration, the pressure value or pressure level of the user judged according to the user's transcript, expression, motion, motion state or audio, which cannot obtain the user's pressure at any time and at any time. Value or pressure rating.
  • the user's instantaneous pressure model can be obtained by modeling the user's bioelectrical signal, and then the user's pressure value or pressure level is determined according to the user's instantaneous pressure model.
  • the user's pressure value or pressure level is determined only based on the user's bioelectrical signal, the accuracy is low, and the user's bioelectrical signal is susceptible to transient factors (such as sudden changes in mood, temperature, light, etc.), resulting in user transients.
  • the pressure model is susceptible to transient factors and has poor robustness.
  • Embodiments of the present invention provide a mental stress evaluation method and apparatus for improving the accuracy of a user's mental stress evaluation result, and also for improving the robustness of a system for evaluating a user's mental stress.
  • a mental stress evaluation method includes: acquiring a physiological signal of a user at a current moment; determining a first pressure indicator of the user according to a current time and a periodic pressure model of the user, and the periodic pressure model is based on the user.
  • the pressure model determined by the pressure indicator of the moment and determined by the current moment can determine the pressure model of the current pressure indicator of the user;
  • the second pressure index of the user is determined according to the physiological signal of the user at the current moment and the instantaneous pressure model of the user, and the instantaneous pressure model is Determining a pressure model of the current pressure indicator of the user according to a physiological signal related to the current pressure state of the user, wherein the physiological signal is an input of the instantaneous pressure model; and determining a current pressure indicator of the user according to the first pressure indicator and the second pressure indicator;
  • the method comprises: obtaining a physiological signal of a user at a current moment; determining a pressure index of the user according to a physiological signal of the user at the current time and the current time; and the target pressure model is a pressure determined by integrating the periodic pressure model and the instantaneous pressure model The model; the periodic pressure model is a pressure model determined according to a pressure index of the user at a plurality of times and determining the current pressure index of the user based only on the current time; the instantaneous pressure model is based on a physiological signal related to the current pressure state of the user The pressure model of the user's current stress indicator is determined, and the physiological signal is the input of the instantaneous pressure model.
  • the first aspect provides a method for determining a current pressure indicator of a user according to a periodic pressure model and an instantaneous pressure model, wherein the periodic pressure model is determined according to a pressure index of the user at a plurality of times, and the current current of the user can be determined only according to the current time.
  • the periodic pressure model can describe the pressure index of the user over a period of time with a large keynote, and is not easily affected by the transient factors, ensuring the robustness of the mental stress evaluation system, and, in addition, due to the transient pressure
  • the model is a pressure model that needs to determine the current pressure indicator of the user according to the physiological signal related to the current stress state of the user, so that the mental stress evaluation system simultaneously combines the current pressure state of the user to determine the current pressure index of the user, and improves the mental stress evaluation. The accuracy of the system.
  • the periodic pressure model is a pressure model determined according to at least one discrete pressure indicator set
  • the discrete pressure indicator set is a pressure determined according to discrete pressure data of at least one time point acquired within a preset time period.
  • the set of indicators, a discrete pressure indicator in a discrete pressure indicator set is a pressure indicator determined according to the user's subjective evaluation result, the user's cortisol concentration or the user's external performance.
  • the periodic pressure model includes a subjective periodic pressure model and an objective periodic pressure model;
  • the subjective periodic pressure model is a pressure model determined according to the first discrete pressure indicator set and/or the second discrete pressure indicator set,
  • the discrete pressure index in the first discrete pressure indicator set is the pressure index determined according to the subjective evaluation result of the user, and the discrete pressure index in the second discrete pressure index set is the pressure index determined according to the external performance of the user;
  • the objective periodic pressure model For the pressure model determined according to the third discrete pressure index set, the discrete pressure indicator in the third discrete pressure indicator set is a pressure index determined according to the user's cortisol concentration; the discrete pressure indicator set is obtained according to the preset time period.
  • the discrete pressure data of at least one time point determines the set of pressure indicators.
  • the periodic pressure model is a pressure model determined according to a comprehensive discrete pressure index set
  • the integrated discrete pressure index set is a set of pressure indicators determined according to at least one discrete pressure indicator set
  • the integrated discrete pressure indicator set is integrated.
  • a comprehensive discrete pressure indicator is determined according to a plurality of discrete pressure indicators, and the plurality of discrete pressure indicators are all discrete pressure indicators corresponding to the same time point in at least one discrete pressure indicator set.
  • the discrete pressure indicator set is a set of pressure indicators determined according to discrete pressure data of at least one time point acquired in a preset time period, and the discrete pressure indicator in the discrete pressure indicator set is based on the subjective evaluation result of the user, the user's leather The pressure indicator determined by the alcohol concentration or the external performance of the user.
  • the periodic pressure model is a pressure model determined according to a comprehensive discrete pressure indicator set and a plurality of historical discrete pressure indicators
  • the integrated discrete pressure indicator set is a set of pressure indicators determined according to at least one discrete pressure indicator set.
  • a comprehensive discrete pressure index in the integrated discrete pressure indicator set is determined according to a plurality of discrete pressure indicators, wherein the plurality of discrete pressure indicators are all discrete pressure indicators corresponding to the same time point in at least one discrete pressure indicator set, and the discrete pressure indicator sets are based on The set of pressure indicators determined by the discrete pressure data of the at least one time point acquired within the preset time period, and the discrete pressure indicator of the discrete pressure indicator set is based on the subjective evaluation result of the user, the cortisol concentration of the user, or the user's
  • the performance indicator is determined by the performance; the historical discrete pressure indicator is the discrete pressure indicator obtained before the preset time period.
  • the determined periodic pressure model can be made more accurate by combining historical discrete pressure indicators.
  • the method before determining the second pressure indicator of the user according to the current physiological signal and the instantaneous pressure model of the user, the method further comprises: acquiring the M segment physiological signal of the user, and the physiological signal is within a time period Obtain the physiological signal of the user, M is an integer greater than 0; obtain the pressure index subjectively given by the user in M time periods, obtain M subjective pressure indicators, and M subjective pressure indicators respectively correspond to M time periods, M The time period is M time periods for acquiring the M segment physiological signal; the M segment physiological signal is used as the input of the general pressure model to obtain M general pressure indicators; the M subjective pressure indicators are subtracted from the M common pressure indicators, Obtaining M user bias items, wherein the subjective pressure index and the general pressure index corresponding to the same time period in the M time segments are subtracted; determining the sum of the average values of the M user bias terms and the general pressure model as Instantaneous pressure model.
  • the method before determining the second pressure indicator of the user according to the current physiological signal and the instantaneous pressure model of the user, the method further comprises: acquiring a user bias item, and the user bias item is stored in another device. An offset term associated with the user for calibrating the universal pressure model; determining the sum of the user bias term and the universal pressure model as the instantaneous pressure model of the user.
  • the physiological signal is a motion signal and/or a bioelectric signal.
  • a mental stress evaluation device having the function of implementing any of the methods provided by the first aspect.
  • This function can be implemented in hardware or in hardware by executing the corresponding software.
  • the hardware or software includes one or more units corresponding to the functions described above.
  • a mental stress evaluation apparatus including: a processor, a memory, a bus, and a communication interface; the memory is configured to store a computer execution instruction, the processor and the memory are connected by a bus, and the processor executes the memory execution computer execution instruction To perform any of the methods as provided by the first aspect.
  • FIG. 1 is a schematic structural diagram of an apparatus for implementing a method according to an embodiment of the present invention
  • FIG. 2 is a flowchart of a mental stress evaluation method according to an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of a periodic pressure model according to an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of an overall process of determining a target pressure model according to an embodiment of the present invention.
  • FIG. 5 is a schematic structural diagram of a mental stress evaluation apparatus according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of still another mental stress evaluation apparatus according to an embodiment of the present invention.
  • Cortisol is a hormone called corticosteroids that can be naturally produced by the body. Because humans produce more of this hormone when faced with significant stress, some people call it stress hormones.
  • the determination of cortisol is currently the gold standard for mental stress measurement. Through cortisol pressure measurement, it is found that cortisol itself is affected by the circadian clock, which means that the influence of user pressure is not only instantaneous factors (such as emotional mutation, temperature influence, light, etc.), but also related to time, therefore,
  • the embodiment of the invention provides a mental stress evaluation method, which improves the robustness and accuracy of the mental stress evaluation system by combining the instantaneous mental stress and the periodic mental stress evaluation results.
  • the pressure indicator of the user needs to be acquired, and the pressure indicator may be a pressure value or a pressure level.
  • the following describes a plurality of ways of obtaining the pressure indicator.
  • Method 1 The pressure indicator given by the user subjectively. Specifically, the method is that the user subjectively evaluates his current stress state and gives a pressure indicator.
  • Method 2 Determine the user's stress indicator according to the results of the stress questionnaire filled out by the user, which is specifically for the user to fill out the stress questionnaire and determine the pressure indicator device. (or others) can determine the user's stress indicator according to the preset rules (or psychological analysis) based on the results of the stress questionnaire filled out by the user.
  • Method 3 Determine the user's pressure index according to the cortisol concentration in the blood of the user. The method needs to extract the blood of the user. The higher the cortisol concentration in the blood, the higher the pressure index of the user.
  • Method 4 Determine the user's stress indicator according to the user's text record, and the text record in the mode may be a user's text record on the social networking site or an essay in life.
  • some keyword groups composed of keywords may be preset, different keyword groups correspond to different pressure indicators, and the text records are matched with the keyword groups, and the pressure indicators are determined according to the matching results.
  • Method 5 Determine the user's stress indicator according to the user's video.
  • the user's stress indicator may be determined according to the user's expression or action or voice in the video.
  • some expressions may be preset, and different expressions correspond to different stress indicators, and the user's expression in the video is matched with the preset expression to determine the pressure index.
  • Method 6 Determine the user's stress indicator according to the user's audio.
  • the user's stress indicator can be determined according to the user's tone, speech rate, and the like.
  • the physiological signal may be a motion signal and/or a bioelectric signal.
  • the motion signal of the user can be acquired by the motion sensor.
  • the bioelectric signal may specifically be an electrocardiogram (ECG) signal and/or a photoplethysmograph (PPG) signal.
  • ECG electrocardiogram
  • PPG photoplethysmograph
  • the bioelectric signal of the user may be collected through the wearable device for a period of time, for example, the PPG signal may be acquired through the smart watch.
  • Discrete Pressure indicator refers to the pressure index obtained from the user's discrete pressure data. Discrete pressure data is discrete in time, not continuous.
  • the integrated discrete pressure indicator refers to the pressure index determined based on multiple discrete pressure indicators obtained at the same time point.
  • Subjective stress indicator refers to the pressure indicator determined according to the subjectively given pressure index of the user within a period of time.
  • the general pressure indicator refers to the pressure index obtained by inputting a physiological signal as a general pressure model.
  • the first pressure indicator refers to the pressure index of the user determined according to the current time and the user's periodic pressure model.
  • the second pressure indicator refers to the pressure index of the user determined according to the physiological signal of the user at the current moment and the instantaneous pressure model of the user.
  • an embodiment of the present invention provides a device 10, which may be used to implement a method provided by an embodiment of the present invention.
  • the device 10 includes at least a memory 101 and a processor 102 connected to the memory 101.
  • the memory 101 can be used to store data and software programs, and the processor 102 can perform data processing by running a software program.
  • the processor 102 can be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), and field programmable. Field Programmable Gate Array (FPGA) or other programmable logic device, transistor logic device, hardware component, or any combination thereof.
  • the memory 101 may include a read only memory (ROM), a random access memory (RAM), or other types of dynamic storage devices that can store information and instructions, or may be a disk storage.
  • the device 10 may further include: an input device 103 connected to the processor 102, which may be used to input a pressure indicator into the device 10; a sensor 104 connected to the processor 102, may be used to acquire a motion signal or a bioelectric signal;
  • the 102 connected camera 105 can be used to capture video data of the user;
  • the collected user's voice signal may be converted into an electrical signal, which is received by the audio circuit 106 and converted into audio data; and the display 108 coupled to the processor 102 is configured to display the final user's pressure indicator for the user or for The entered pressure indicator is displayed.
  • the embodiment of the invention provides a mental stress evaluation method, as shown in FIG. 2, including:
  • the execution subject of the embodiment of the present invention may be a device having a data calculation and processing function, such as a computer, a wearable device (for example, a smart watch), or the like. Steps 201-204 may be performed by processor 102 in device 10 in particular.
  • the periodic pressure model is determined according to the pressure indicator of the user at multiple moments, and the pressure of the current pressure indicator of the user can be determined only according to the current moment. model.
  • the instantaneous pressure model determines a pressure model of the current pressure index of the user according to the physiological signal related to the current pressure state of the user, and the physiological signal is Input to the instantaneous pressure model.
  • the physiological signal can be a motion signal and/or a bioelectric signal.
  • the periodic pressure model and the instantaneous pressure model may be pre-stored in the device performing the method.
  • the first pressure indicator of the user at one moment can be determined according to the periodic pressure model, and the second pressure indicator of the user at the moment is determined according to the instantaneous pressure model, and the two pressure indicators are integrated to obtain the pressure of the user at the moment. index.
  • the first pressure indicator and the second pressure indicator are used to determine the pressure indicator of the user at the moment by weighted summation or averaging.
  • the target pressure model may also be pre-stored in the device performing the method, and the target pressure model is a pressure model determined by integrating the periodic pressure model and the instantaneous pressure model.
  • the method may be: obtaining the physiological signal of the user at the current time, and determining the pressure indicator of the user according to the current time and the physiological signal of the user and the target pressure model at the current time.
  • the target pressure model may specifically be a pressure model that combines the periodic pressure model and the instantaneous pressure model by means of a weighted sum method or a weighted geometric mean or a weighted harmonic mean.
  • the periodic pressure model is denoted as Y_cycle
  • the instantaneous pressure model is denoted as Y_instant
  • the method provided by the embodiment of the present invention determines the current pressure indicator of the user according to the periodic pressure model and the instantaneous pressure model.
  • the periodic pressure model is determined according to the pressure index of the user at multiple moments, and the user can be determined only according to the current moment.
  • the pressure model of the current pressure index therefore, the periodic pressure model can characterize the pressure index of the user over a period of time, and is not easily affected by the transient factors, ensuring the robustness of the mental stress evaluation system.
  • the instantaneous pressure model is a pressure model that needs to determine the current pressure indicator of the user according to physiological signals related to the current pressure state of the user, so that the mental stress evaluation system simultaneously combines the current user's current The stress state determines the user's current stress indicator and improves the accuracy of the mental stress assessment system.
  • the periodic pressure model may be a pressure model determined by any one of the following methods:
  • Method 1 A pressure model determined according to at least one discrete pressure indicator set.
  • the discrete pressure indicator set may be a set of pressure indicators determined according to discrete pressure data of at least one time point acquired within a preset time period, and the discrete pressure indicator of the discrete pressure indicator set is based on a subjective evaluation result of the user, The user's cortisol concentration or the user's external performance determines the stress indicator.
  • the pressure indicator determined according to the user's subjective evaluation result may specifically be: the user subjectively evaluates his current pressure state, and gives a pressure indicator, in which case the discrete pressure data may be the pressure indicator; or, according to The user fills in the pressure questionnaire to determine the user's stress indicator.
  • the discrete pressure data can be the result of the stress questionnaire filled out by the user.
  • the pressure indicator determined according to the external performance of the user may specifically be: a user's pressure indicator determined according to the user's transcript or expression or action or sound or audio. In this case, the discrete pressure data may be the user's transcript or expression or Action or sound or audio.
  • the discrete pressure indicators obtained by these methods are not susceptible to transient factors such as sudden changes in mood, temperature, and light, and the reliability is high, but the portability is poor. Therefore, it can be used to determine the user's periodic pressure model so that the periodic pressure model is not susceptible to transient factors.
  • a discrete pressure indicator may correspond to a time point, and a time point corresponding to a discrete pressure indicator acquires a time point for determining data of the discrete pressure indicator.
  • the preset time period may be any time period.
  • the preset time period may be a day, a week, or a working day within a week.
  • the pressure indicator can be a pressure value or a pressure level, and the greater the pressure value or the higher the pressure level, the greater the user's mental stress.
  • T0 to T9 are 10 time points within a preset time period, and Table 1 shows the first type, the second type, and the third type.
  • Discrete pressure indicators in discrete stress indicators is a pressure index determined according to the subjective evaluation result of the user, and specifically includes S10, S11, S14, S15, S17, and S19, and the six discrete pressure indicators correspond to time points T0 and T1, respectively. , T4, T5, T7 and T9.
  • the discrete pressure indicator in the second discrete pressure indicator set is a pressure indicator determined according to the external performance of the user, and specifically includes S20, S22, S23, S24, S25, S26, and S28, and the six discrete pressure indicators respectively correspond to the time point T0. , T2, T3, T4, T5, T6 and T8.
  • the discrete pressure indicator in the third discrete pressure indicator set is the pressure index determined according to the user's cortisol concentration, including S30, S31, S33, S34, S36, S37 and S39.
  • the seven discrete pressure indicators correspond to the time point T0. , T1, T3, T4, T6, T7 and T9.
  • the discrete pressure index in the first discrete pressure index set may be a set of pressure indicators given according to the user's subjective assessment of his current stress state, or may be determined according to the results of the stress questionnaire filled out by the user.
  • the first set of discrete pressure indicators may further include a set of pressure indicators given based on the subjective assessment of the user's current stress state, and a set of pressure indicators of the user determined based on the results of the stress questionnaire filled out by the user. Other types of discrete pressure indicators are similar.
  • the periodic pressure model can be implemented by using a cubic spline interpolation algorithm or multiple The fitting method is used to curve the discrete pressure indicators in the discrete pressure index.
  • Method 2 A pressure model determined according to a comprehensive discrete pressure indicator set.
  • the integrated discrete pressure indicator set may be a set of pressure indicators determined according to at least one discrete pressure indicator set, and a comprehensive discrete pressure indicator integrated in the discrete pressure indicator set is determined according to a plurality of discrete pressure indicators, and the plurality of discrete pressure indicators are at least one All discrete pressure indicators corresponding to the same time point in the discrete pressure indicator set.
  • a comprehensive discrete pressure indicator can be determined based on a plurality of discrete pressure indicators corresponding to the same point in time.
  • the discrete pressure indicator is a comprehensive discrete pressure indicator corresponding to the time point.
  • the comprehensive discrete pressure indicator corresponding to one time point may be obtained at the time point.
  • the pressure index obtained by averaging the plurality of discrete pressure indicators obtained may also be a pressure index determined by weighting the weights of the plurality of discrete pressure indicators acquired at the time point.
  • the comprehensive discrete pressure index corresponding to T0 can be (S10+S20+S30)/3, and the comprehensive discrete pressure index corresponding to T2 can be S22. .
  • the periodic pressure model can be obtained by curve fitting a comprehensive discrete pressure index in a comprehensive discrete pressure index set by using a cubic spline interpolation algorithm or a polynomial fitting method.
  • Illustrative as shown in Figure 3, can be a fitted periodic pressure model.
  • the historical discrete pressure indicator is a discrete pressure indicator obtained before the preset time period.
  • the historical discrete pressure indicator may be a discrete pressure indicator acquired on the day before or before the date on which the preset time period is located, and the preset time period is one in a week. Time. For example, when the preset time period is Monday, the historical discrete pressure indicator may be a discrete pressure indicator obtained in the week before or in the previous week of the date in which the preset time period is located. Historical discrete pressure indicators can also be discrete pressure indicators obtained at other times, just for illustrative purposes.
  • the error weight of the discrete pressure index obtained in the preset time period is 1, and the error weight of the historical discrete pressure index is less than 1, which may be: historical discrete pressure index The closer the discrete pressure index of the preset time period is, the closer the error weight is to 1, so that the newer discrete pressure index has a greater impact on the optimization result. Otherwise, the older discrete pressure index has less influence on the optimization result. To make the determined periodic pressure model more accurate.
  • the periodic pressure model may include a subjective periodic pressure model and an objective periodic pressure model; the subjective periodic pressure model is a pressure model determined according to the first discrete pressure indicator set and/or the second discrete pressure indicator set; objective periodic pressure The model is a pressure model determined from a third set of discrete pressure indicators.
  • first discrete pressure indicator set the second discrete pressure indicator set, and the third discrete pressure indicator set and the discrete pressure indicator set can be found above.
  • N1 discrete pressure indicators when the discrete pressure index set used to determine the objective periodic pressure model includes N1 discrete pressure indicators, and one or more discrete pressure index sets used to determine the subjective periodic pressure model include N2 discrete pressure indicators, N1' integrated discrete pressure indicators can be determined according to N1 discrete pressure indicators, N2' integrated discrete pressure indicators are determined according to N2 discrete pressure indicators, and objective periodic pressure models are determined according to N1' integrated discrete pressure indicators, according to N2' comprehensive Discrete pressure index to determine subjective periodic pressure model type.
  • N1' comprehensive discrete pressure indicators correspond to N1' time points, and the comprehensive discrete pressure index corresponding to one time point is determined by the discrete pressure index obtained at the time point among N1 discrete pressure indicators;
  • N2' comprehensive The discrete pressure indicators correspond to N2' time points, and the comprehensive discrete pressure index corresponding to one time point is determined by the discrete pressure index obtained at the time point among the N2 discrete pressure indicators.
  • the N1 discrete pressure indicators may be the cortisol concentration of the user acquired at the N1 fixed moments in the preset time period, and the objective periodic pressure model may be obtained by curve fitting the N1 discrete pressure indicators.
  • the preset time period is one day
  • N1 5
  • the N1 time points for obtaining N1 discrete pressure indicators may be 8 points, 10 points, 14 points, 16 points, and 20 points, when the pressure index is a pressure value.
  • the highest cortisol concentration measured at N1 time points corresponds to a pressure value of 100
  • the lowest cortisol concentration corresponds to a pressure value of 0.
  • the higher the cortisol concentration the greater the pressure value, thereby determining each dispersion at the N1 time point.
  • Pressure indicator is the cortisol concentration of the user acquired at the N1 fixed moments in the preset time period
  • the objective periodic pressure model may be obtained by curve fitting the N1 discrete pressure indicators.
  • the target pressure model may be specifically determined by combining a objective periodic pressure model, a subjective periodic pressure model, and an instantaneous pressure model by means of weighted sum or weighted geometric mean or weighted harmonic mean.
  • the user's instantaneous pressure model can be a universal pressure model.
  • the method for establishing a general stress model specifically includes: determining a preset number of individuals in a user age group as a sample, and obtaining sample information of each individual, and the sample information of an individual includes basic information of the individual (the gender of the individual, Age, height and weight, etc.), the physiological signal of the individual over a period of time and subjectively given by the individual
  • the pressure indicator determining the feature vector of each individual, the method for determining the feature vector of an individual may be: extracting the characteristics of the physiological signal of the individual in a time period, and composing the extracted feature and the basic information of the individual Eigenvectors; constructing a linear regression equation for each individual, the construction method of an individual's linear regression equation may be: constructing a linear regression equation according to the individual's eigenvector and the subjectively given pressure index, the subjectively given The pressure index is the output of the equation; the linear regression equations are constructed according to the preset number of individual linear regression equations, and the regression coefficients of the linear regression equations are obtained by the least
  • Basic information may include gender Gender, age Age, height height, weight weight; collect ECG signals for each person for 1 minute, and let each The individual gives his current stress value stress. For example, if the pressure value is a percentage system, the current pressure value given can be 75 points. Then, through the above process, 100 sample information can be obtained, and each sample information corresponds to one person, including the basic information of the person, the 1-minute ECG signal, and the subjectively given pressure value.
  • the heart rate HR is calculated according to the 1-minute ECG signal in the sample information, the standard deviation of the heart rate std_HR, and the basic information in the sample information constitute a feature vector [Gender, Age, Height, Weight, HR, std_HR
  • a linear regression equation consisting of 100 linear regression equations can be obtained, and the regression coefficients a1, a2, a3, a4, a5, a6 and b of the linear regression equations are obtained by the least squares method.
  • the method may further include: acquiring a M segment physiological signal of the user, the physiological signal is a physiological signal of the user acquired in a time period, and M is an integer greater than 0; M subjective pressure indicators are obtained subjectively, and M subjective pressure indicators are respectively corresponding to M time periods, and M time periods are M time periods for acquiring M-segment physiological signals;
  • the segment physiological signal is used as the input of the general pressure model to obtain M common pressure indicators; the M subjective pressure indicators are subtracted from the M common pressure indicators to obtain M user bias terms, wherein the corresponding M time segments are the same
  • the subjective pressure index of the time period is subtracted from the general pressure index; the sum of the average of the M user bias terms and the general pressure model is determined as the instantaneous pressure model.
  • the bioelectric signal may be an ECG signal and/or a PPG signal. Since the physiological signal is susceptible to transient factors, the reliability is low, but the physiological signal can be collected according to the device carried by the user, and therefore, portable. Higher sex. Therefore, it can be used to determine the instantaneous pressure model of the user and improve the accuracy of the determined user's pressure index.
  • the input of the universal pressure model includes other parameters in addition to the physiological signal, for example, the age, height, weight, etc. of the user mentioned in the above embodiments, which can be obtained by the user and stored in advance in the memory so as to be Called when calculating the general pressure indicator.
  • the physiological signal is a PPG signal
  • the user can obtain the pressure index subjectively given by the user within 2 minutes, and obtain M subjective pressure indicators, which are recorded as Y 11 , Y 12 , ..., Y 1M
  • M PPG signals within 2 minutes, as input to the general pressure model obtain M common pressure indicators, denoted as Y 01 , Y 02 , ..., Y 0M ; then M user bias terms are Y 11 -Y 01 , Y 12 -Y 02 ,...,Y 1M -Y 0M
  • the general pressure model is denoted as Y_general
  • the user's instantaneous pressure model Y_instant Y_general+[(Y 11 -Y 01 )+(Y 12 -Y 02 )+, ..., +(Y 1M -Y 0M )]/M.
  • the method may further include: acquiring a user bias item, where the user bias item is an offset item associated with the user and configured to calibrate the universal pressure model stored in the other device; The sum of the user bias term and the general pressure model is determined as the instantaneous pressure model of the user.
  • the user bias term may also be calculated not directly based on the acquired M segment physiological signal and M subjective stress indicators, but acquired in other devices (eg, servers).
  • the user can create an account, the user bias item, the user's age, height, weight and other information are associated with the account, the data can be stored in the server, when needed Obtain.
  • FIG. 4 shows the overall process of determining the target pressure model, wherein the user is subjectively evaluated on his current pressure state, and the given pressure is given.
  • the user's periodic pressure model is only related to time, but the user's instantaneous pressure model is related to the physiological signal and related to other parameters of the user (for example, the user's age, height, weight, etc.), therefore, the target pressure model Related to time, physiological signals, and other parameters.
  • other parameters of the user may be pre-stored in the memory of the device that implements the method provided by the embodiment of the present invention, and the time and physiological signals may be acquired in real time by the device carried by the user.
  • the preset time period may be one day.
  • the target pressure model is a user's day pressure model
  • the daily target pressure model of the week can be obtained by the above method, and the week is The daily target pressure model is combined to obtain the user's weekly stress model.
  • the preset time period can also be one week.
  • the target pressure model is the user's weekly stress model.
  • the ECG signal can be acquired for a period of time (for example, 1 minute or 2 minutes) by clicking a button for acquiring a physiological signal set on the device, and the ECG signal is implied. Current time.
  • the periodic pressure model can be a pressure model obtained by curve fitting according to a discrete pressure index or a comprehensive discrete pressure index.
  • the periodic pressure model is that the time is the independent variable, the pressure index is a function of the dependent variable, and the current time is used as the input of the periodic pressure model to obtain the first pressure index.
  • the user's Gender, Age, Height, and Weight can be obtained from the memory, and HR and std_HR can be calculated according to the ECG signal, according to The ECG signal and the instantaneous pressure model can calculate the user's second pressure indicator.
  • the user's current pressure indicator can be obtained by weighting the first pressure indicator and the second pressure indicator.
  • the periodic pressure model and the instantaneous pressure model may not be stored in advance in the device for performing the method provided by the embodiment of the present invention, but may be obtained by the device by using corresponding After determining the parameters of the periodic pressure model and the instantaneous pressure model (or target pressure model), it is determined by itself. After the device is self-determined, the periodic pressure model and the instantaneous pressure model (or target pressure model) can be stored in the device.
  • Embodiments of the present invention may exemplarily divide a functional unit for an apparatus for performing the above method according to the above method.
  • each functional unit may be divided corresponding to each function, or two or more functional units may be integrated into one processing unit.
  • the division of the functional unit in the embodiment of the present invention is schematic, and is only a logical function division, and may be further divided in actual implementation.
  • FIG. 5 shows a mental stress evaluation device 50, Including: an obtaining unit 501 and a processing unit 502;
  • the obtaining unit 501 is configured to acquire a physiological signal of the user at the current moment
  • the processing unit 502 is configured to determine a first pressure indicator of the user according to the current time and the periodic pressure model of the user, where the periodic pressure model is determined according to the pressure index of the user at multiple times, and the current current of the user can be determined only according to the current time.
  • Pressure model of the pressure indicator is configured to determine a first pressure indicator of the user according to the current time and the periodic pressure model of the user, where the periodic pressure model is determined according to the pressure index of the user at multiple times, and the current current of the user can be determined only according to the current time.
  • the processing unit 502 is further configured to determine a second pressure indicator of the user according to the physiological signal of the user at the current time and the instantaneous pressure model of the user, where the instantaneous pressure model determines the pressure of the current pressure indicator of the user according to the physiological signal related to the current pressure state of the user.
  • Model the physiological signal is the input of the instantaneous pressure model;
  • the processing unit 502 is further configured to determine a current pressure indicator of the user according to the first pressure indicator and the second pressure indicator.
  • the periodic pressure model is a pressure model determined according to at least one discrete pressure indicator set
  • the discrete pressure indicator set is a set of pressure indicators determined according to discrete pressure data of at least one time point acquired within a preset time period
  • a discrete pressure indicator in a discrete pressure indicator set is a pressure indicator determined according to a user's subjective evaluation result, a user's cortisol concentration, or a user's external performance.
  • the periodic pressure model includes a subjective periodic pressure model and an objective periodic pressure model;
  • the subjective periodic pressure model is a pressure model determined according to the first discrete pressure index set and/or the second discrete pressure index set, the first type of discrete
  • the discrete pressure indicator in the concentration index is the pressure index determined according to the subjective evaluation result of the user, and the discrete pressure index in the second discrete pressure index is the pressure index determined according to the external performance of the user;
  • the objective periodic pressure model is based on the third The pressure model determined by the discrete pressure index set, the discrete pressure index in the third discrete pressure index set is the pressure index determined according to the user's cortisol concentration; the discrete pressure index set is obtained according to the preset time period.
  • the discrete pressure data of at least one time point determines the set of pressure indicators.
  • the periodic pressure model is a pressure model determined according to the integrated discrete pressure indicator set
  • the integrated discrete pressure indicator set is a set of pressure indicators determined according to at least one discrete pressure indicator set, and a comprehensive discrete pressure in the integrated discrete pressure indicator set
  • the indicator is determined according to a plurality of discrete pressure indicators, wherein the plurality of discrete pressure indicators are all discrete pressure indicators corresponding to the same time point in the at least one discrete pressure indicator set, and the discrete pressure indicator set is at least one time acquired according to the preset time period.
  • the set of pressure indicators determined by the discrete pressure data of the point, and the discrete pressure index of the discrete pressure indicator set are pressure indicators determined according to the subjective evaluation result of the user, the cortisol concentration of the user, or the external performance of the user.
  • the periodic pressure model is a pressure model determined according to a comprehensive discrete pressure indicator set and a plurality of historical discrete pressure indicators
  • the integrated discrete pressure indicator set is a set of pressure indicators determined according to at least one discrete pressure indicator set, and the integrated discrete pressure is integrated.
  • a comprehensive discrete pressure indicator in the indicator set is determined according to a plurality of discrete pressure indicators, wherein the plurality of discrete pressure indicators are all discrete pressure indicators corresponding to the same time point in the at least one discrete pressure indicator set, and the discrete pressure indicator set is based on the preset time period
  • the set of pressure indicators determined by the discrete pressure data of the at least one time point acquired, and the discrete pressure index of the discrete pressure indicator set is determined according to the subjective evaluation result of the user, the cortisol concentration of the user, or the external performance of the user.
  • Pressure indicator; historical discrete pressure indicator is the discrete pressure indicator obtained before the preset time period.
  • the obtaining unit 501 is further configured to acquire the M segment physiological signal of the user, the physiological signal is a physiological signal of the user acquired in a time period, and M is an integer greater than 0; and acquiring the user in the M time period
  • M subjective pressure indicators are obtained, M subjective pressure indicators respectively correspond to M time periods, and M time periods are M time periods for acquiring M segment physiological signals;
  • the processing unit 502 is further configured to use the M segment physiological signal as a general pressure model Into, obtain M general pressure indicators; subtract M subjective pressure indicators and M common pressure indicators to obtain M user bias items, wherein the subjective pressure indicators and common times of the same time period in M time periods The pressure index is subtracted; the sum of the average of the M user bias terms and the general pressure model is determined as the instantaneous pressure model.
  • the obtaining unit 501 is further configured to acquire a user offset item, where the user bias item is an offset item associated with the user and configured to calibrate the universal pressure model stored in the other device;
  • the processing unit 502 is further configured to determine a sum of the user bias term and the universal pressure model as the instantaneous pressure model of the user.
  • the physiological signal is a motion signal and/or a bioelectric signal.
  • the various units in the device 50 are used to perform the above method. Therefore, the beneficial effects of the device 50 can be seen in the beneficial effects of the above method, and details are not described herein again.
  • FIG. 6 shows a simpler hardware structure diagram of a mental stress evaluation device 60.
  • the device 60 includes a memory 601, a processor 602, and a bus 603.
  • the communication interface 604 the memory 601 is used to store computer execution instructions
  • the processor 602 is connected to the memory 601 via a bus 603, and the processor 602 executes instructions by executing a computer stored in the memory 601 to implement the above method.
  • the bus 603 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus.
  • PCI peripheral component interconnect
  • EISA extended industry standard architecture
  • the bus can be divided into an address bus, Data bus, control bus, etc. For ease of representation, only one thick line is shown in Figure 6, but it does not mean that there is only one bus or one type of bus.
  • the functions described herein can be implemented in hardware, software, firmware, or any combination thereof.
  • the functions may be stored in a computer readable medium or transmitted as one or more instructions or code on a computer readable medium.
  • Computer readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another.
  • a storage medium may be any available media that can be accessed by a general purpose or special purpose computer.

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Abstract

一种精神压力评测方法和装置，涉及心理健康应用技术领域，用以提高用户的精神压力评测结果的准确性，还用以提高用于对用户的精神压力进行评测的系统的鲁棒性。该方法包括：获取当前时刻用户的生理信号（201）；根据当前时刻和用户的周期压力模型确定用户的第一压力指标（202）；根据当前时刻用户的生理信号和用户的瞬时压力模型确定用户的第二压力指标，生理信号为瞬时压力模型的输入（203）；根据第一压力指标和第二压力指标确定用户的当前压力指标（204）。

Description

一种精神压力评测方法和装置 技术领域
本发明涉及心理健康应用技术领域，尤其涉及一种精神压力评测方法和装置。
背景技术
随着可穿戴设备的兴起，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：如心率、皮肤温度等。通过长期采集生理数据，能够更加有效地对人们的生理健康情况做出统计和预测。除了生理健康之外，人们的心理健康问题也不容忽视，心理健康问题的主要来源是较大的精神压力。可穿戴设备的发展为精神压力的评测提供了新载体。
目前，可以通过以下方式获取用户的压力等级或压力值：用户主观给出的压力值或压力等级、根据用户填写的压力调查问卷结果进行心理学统计分析确定的用户的压力值或压力等级、根据用户的皮质醇浓度确定的用户的压力值或压力等级、根据用户的文字记录、表情、动作、运动状态或音频判断的用户的压力值或压力等级，这些方式无法随时随刻地获取用户的压力值或压力等级。
另外，还可以通过对用户的生物电信号进行建模得到用户的瞬时压力模型，再根据用户的瞬时压力模型确定用户的压力值或压力等级。但是仅仅根据用户的生物电信号确定用户的压力值或压力等级，准确度低，并且由于用户的生物电信号容易受到瞬时因素(如情绪突变、温度影响、光线等)的影响，导致用户的瞬时压力模型容易受到瞬时因素的干扰，鲁棒性差。
发明内容
本发明的实施例提供了一种精神压力评测方法和装置，用以提高用户的精神压力评测结果的准确性，还用以提高用于对用户的精神压力进行评测的系统的鲁棒性。
为达到上述目的，本发明的实施例采用如下技术方案：
第一方面，提供了一种精神压力评测方法，该方法包括：获取当前时刻用户的生理信号；根据当前时刻和用户的周期压力模型确定用户的第一压力指标，周期压力模型为根据用户在多个时刻的压力指标确定的、并且只根据当前时刻即可确定用户的当前压力指标的压力模型；根据当前时刻用户的生理信号和用户的瞬时压力模型确定用户的第二压力指标，瞬时压力模型为根据与用户的当前压力状态有关的生理信号确定用户当前压力指标的压力模型，生理信号为瞬时压力模型的输入；根据第一压力指标和第二压力指标确定用户的当前压力指标；
或者，
该方法包括：获取当前时刻用户的生理信号；根据当前时刻以及当前时刻用户的生理信号和目标压力模型确定用户的压力指标；目标压力模型为将周期压力模型和瞬时压力模型进行综合后确定的压力模型；周期压力模型为根据用户在多个时刻的压力指标确定的、并且只根据当前时刻即可确定用户的当前压力指标的压力模型；瞬时压力模型为根据与用户的当前压力状态有关的生理信号确定用户当前压力指标的压力模型，生理信号为瞬时压力模型的输入。
第一方面提供的方法，根据周期压力模型和瞬时压力模型确定用户的当前压力指标，由于周期压力模型为根据用户在多个时刻的压力指标确定的、并且只根据当前时刻就可以确定用户的当前压力 指标的压力模型，因此，周期压力模型可以大基调的刻画用户在一段时间段内的压力指标、并且不容易受到瞬时因素的影响，保证了精神压力评测系统的鲁棒性，另外，由于瞬时压力模型为需要根据与用户当前的压力状态有关的生理信号确定用户的当前压力指标的压力模型，从而使得精神压力评测系统同时结合了用户的当前压力状态确定用户的当前压力指标，提高了精神压力评测系统的准确性。
在一种可能的设计中，周期压力模型为根据至少一种离散压力指标集确定的压力模型，离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据用户的主观评测结果、用户的皮质醇浓度或用户的外在表现确定的压力指标。
在一种可能的设计中，周期压力模型包括主观周期压力模型和客观周期压力模型；主观周期压力模型为根据第一种离散压力指标集和/或第二种离散压力指标集确定的压力模型，第一种离散压力指标集中的离散压力指标为根据用户的主观评测结果确定的压力指标，第二种离散压力指标集中的离散压力指标为根据用户的外在表现确定的压力指标；客观周期压力模型为根据第三种离散压力指标集确定的压力模型，第三种离散压力指标集中的离散压力指标为根据用户的皮质醇浓度确定的压力指标；离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合。
在一种可能的设计中，周期压力模型为根据综合离散压力指标集确定的压力模型，综合离散压力指标集为根据至少一种离散压力指标集确定的压力指标的集合，综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，多个离散压力指标为至少一种离散压力指标集中的对应同一时间点的全部离散压力指标， 离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据用户的主观评测结果、用户的皮质醇浓度或用户的外在表现确定的压力指标。
在一种可能的设计中，周期压力模型为根据综合离散压力指标集和多个历史离散压力指标确定的压力模型，综合离散压力指标集为根据至少一种离散压力指标集确定的压力指标的集合，综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，多个离散压力指标为至少一种离散压力指标集中的对应同一时间点的全部离散压力指标，离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据用户的主观评测结果、用户的皮质醇浓度或用户的外在表现确定的压力指标；历史离散压力指标为在预设时间段之前获取到的离散压力指标。
在该种可能的设计中，通过结合历史离散压力指标可以使得确定的周期压力模型更加的准确。
在一种可能的设计中，在根据当前生理信号和用户的瞬时压力模型确定用户的第二压力指标之前，该方法还包括：获取用户的M段生理信号，一段生理信号为在一个时间段内获取到的用户的生理信号，M为大于0的整数；获取用户在M个时间段主观给出的压力指标，得到M个主观压力指标，M个主观压力指标分别对应M个时间段，M个时间段为用于获取M段生理信号的M个时间段；将M段生理信号作为通用压力模型的输入，得到M个通用压力指标；将M个主观压力指标与M个通用压力指标相减，得到M个用户偏置项，其中，对应M个时间段中的同一时间段的主观压力指标和通用压力指标相减；将M个用户偏置项的平均值与通用压力模型之和确定为 瞬时压力模型。
在一种可能的设计中，在根据当前生理信号和用户的瞬时压力模型确定用户的第二压力指标之前，该方法还包括：获取用户偏置项，用户偏置项为存储在其他设备中的与用户相关联的、用于校准通用压力模型的偏置项；将用户偏置项与通用压力模型之和确定为用户的瞬时压力模型。
在一种可能的设计中，生理信号为运动信号和/或生物电信号。
第二方面，提供了一种精神压力评测装置，该精神压力评测装置具有实现第一方面提供的任意一种方法的功能。该功能可以通过硬件实现，也可以通过硬件执行相应的软件实现。该硬件或软件包括一个或多个与上述功能相对应的单元。
第三方面，提供了一种精神压力评测装置，包括：处理器、存储器、总线和通信接口；存储器用于存储计算机执行指令，处理器与存储器通过总线连接，处理器执行存储器存储的计算机执行指令，以执行如第一方面提供的任意一种方法。
第二方面和第三方面中任一种设计方式所带来的技术效果可参见第一方面中不同设计方式所带来的技术效果，此处不再赘述。
附图说明
图1为本发明实施例提供的用于实现本发明实施例提供的方法的一种装置的组成示意图；
图2为本发明实施例提供的一种精神压力评测方法的流程图；
图3为本发明实施例提供的一种周期压力模型的示意图；
图4为本发明实施例提供的确定目标压力模型的整体过程示意图；
图5为本发明实施例提供的一种精神压力评测装置的组成示意图；
图6为本发明实施例提供的又一种精神压力评测装置的组成示意图。
具体实施方式
本文中术语“和/或”，仅仅是一种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。本文中的术语“多个”是指两个或两个以上。
皮质醇是一种可以由人体自然产生的、叫做皮质类固醇激素的荷尔蒙。由于人类在面临显著压力时会产生更多这种荷尔蒙，因此，也有人将其称为压力激素。皮质醇的测定是目前精神压力测量的金标准。通过皮质醇进行压力测定，发现皮质醇本身受到生物钟的影响，这说明：影响用户压力的不仅仅是瞬时的一些影响因素(如情绪突变、温度影响、光线等)，还和时间有关，因此，本发明实施例提供了一种精神压力评测方法，通过将瞬时的精神压力和周期性的精神压力的评测结果相结合，提高精神压力评测系统的鲁棒性和准确性。
在执行本发明实施例提供的方法的过程中，需要获取用户的压力指标，压力指标可以为压力值或者压力等级，以下对获取压力指标的多种方式进行简单介绍。
方式一、用户主观给出的压力指标。具体的，该种方式为用户主观对自己当前的压力状态进行评价，给出压力指标。
方式二、根据用户填写的压力调查问卷结果确定用户的压力指标，该种方式具体为用户填写压力调查问卷，确定压力指标的装置 (或其他人)可以根据用户填写的压力调查问卷结果根据预设规则(或进行心理学统计分析)确定用户的压力指标。
方式三、根据用户血液中的皮质醇浓度确定用户的压力指标，该方式需要抽取用户的血液，血液中的皮质醇浓度越高，用户的压力指标越高。
方式四、根据用户的文字记录确定用户的压力指标，该方式中的文字记录可以为用户在社交网站上的文字记录或生活中的随笔记录。示例性的，可以预设一些由关键词组成的关键词组，不同的关键词组对应不同的压力指标，将文字记录与关键词组进行匹配，根据匹配结果确定压力指标。
方式五、根据用户的视频确定用户的压力指标，具体的，可以根据用户在视频中的表情或动作或声音确定用户的压力指标。示例性的，可以预设一些表情，不同的表情对应不同的压力指标，将用户在视频中的表情与预设的表情进行匹配，从而确定压力指标。
方式六、根据用户的音频确定用户的压力指标。具体的，可以根据用户音调、语速等确定用户的压力指标。
另外，还有其他的获取压力指标的方法，在此不再一一说明。
在执行本发明实施例提供的方法的过程中，还需要获取用户的生理信号，生理信号可以为运动信号和/或生物电信号。具体的，可以通过运动传感器获取用户的运动信号。生物电信号具体可以为心电图(electrocardiogram，简称ECG)信号和/或光电容积脉搏波(photoplethysmograph，简称PPG)信号。具体的，可以通过可穿戴设备采集用户一段时间内的生物电信号，例如，可以通过智能手表获取PPG信号。
为了使得本发明实施例中的技术方案更加的清楚，首先对本发 明实施例中提到的相关名词做简单介绍：
离散压力指标：离散压力指标是指根据用户的离散压力数据获取的压力指标，离散压力数据在时间上是离散的，不是连续的。
综合离散压力指标：综合离散压力指标是指根据在同一时间点获取到的多个离散压力指标确定的压力指标。
主观压力指标：主观压力指标是指根据用户在一个时间段内主观给出的压力指标确定的压力指标。
通用压力指标：通用压力指标是指将一段生理信号作为通用压力模型的输入后得到的压力指标。
第一压力指标：第一压力指标是指根据当前时刻和用户的周期压力模型确定的用户的压力指标。
第二压力指标：第二压力指标是指根据当前时刻用户的生理信号和用户的瞬时压力模型确定的用户的压力指标。
参考图1，本发明实施例给出了一种装置10，可以用于实现本发明实施例提供的方法，装置10至少包括存储器101和与存储器101连接的处理器102。其中，存储器101可以用于存储数据和软件程序，处理器102可以通过运行软件程序执行数据处理。处理器102可以为中央处理器(Central Processing Unit，简称CPU)、通用处理器、数字信号处理器(Digital Signal Processor，简称DSP)、特定集成电路(Application Specific Integrated Circuit，简称ASIC)、现场可编程门阵列(Field Programmable Gate Array，简称FPGA)或者其他可编程逻辑器件、晶体管逻辑器件、硬件部件或者其任意组合。存储器101可包含只读存储器(Read Only Memory，简称ROM)，随机存取存储器(Random Access Memory，简称RAM)或者可存储信息和指令的其他类型的动态存储设备，也可以是磁盘存储器。
装置10还可以包括：与处理器102连接的输入设备103，可以用于向装置10中输入压力指标；与处理器102连接的传感器104，可以用于获取运动信号或生物电信号；与处理器102连接的摄像头105，可以用于采集用户的视频数据；与处理器102连接的音频电路106和与音频电路106连接的麦克风107，麦克风107可提供用户与装置10之间的音频接口，麦克风107可以将采集到的用户的声音信号转换为电信号，由音频电路106接收后转换为音频数据；与处理器102连接的显示器108，用于为用户显示最终得出的用户的压力指标或用于显示输入的压力指标。
本发明实施例提供了一种精神压力评测方法，如图2所示，包括：
201、获取当前时刻用户的生理信号。
本发明实施例的执行主体可以为具备数据计算和处理功能的设备，例如计算机、可穿戴设备(例如，智能手表)等。步骤201-步骤204具体可以由装置10中的处理器102执行。
202、根据当前时刻和用户的周期压力模型确定用户的第一压力指标，周期压力模型为根据用户在多个时刻的压力指标确定的、并且只根据当前时刻即可确定用户的当前压力指标的压力模型。
203、根据当前时刻用户的生理信号和用户的瞬时压力模型确定用户的第二压力指标，瞬时压力模型为根据与用户的当前压力状态有关的生理信号确定用户当前压力指标的压力模型，生理信号为瞬时压力模型的输入。
可选的，生理信号可以为运动信号和/或生物电信号。
其中，周期压力模型和瞬时压力模型可以预先存储在执行该方法的设备中。
204、根据第一压力指标和第二压力指标确定用户的当前压力指标。
该情况下，可以根据周期压力模型确定用户在一个时刻的第一压力指标，根据瞬时压力模型确定用户在该时刻的第二压力指标，将这两个压力指标进行综合得到用户在该时刻的压力指标。例如，将第一压力指标和第二压力指标通过加权求和的方式或取平均的方式确定用户在该时刻的压力指标。
另一种可实现的方式，执行该方法的设备中也可以预先存储目标压力模型，目标压力模型为将周期压力模型和瞬时压力模型进行综合后确定的压力模型。该情况下，上述方法在具体实现时可以为：获取当前时刻用户的生理信号，根据当前时刻以及当前时刻用户的生理信号和目标压力模型确定用户的压力指标。
目标压力模型具体可以为采用加权和的方式或加权几何平均的方式或加权调和平均的方式等对周期压力模型和瞬时压力模型进行综合后确定的压力模型。示例性的，若采用加权和的方式确定目标压力模型，将周期压力模型记为Y_cycle，瞬时压力模型记为Y_instant，则目标压力模型Y_final＝p·Y_cycle+q·Y_instant，其中，p+q＝1，例如，p＝0.8，q＝0.2。
本发明实施例提供的方法，根据周期压力模型和瞬时压力模型确定用户的当前压力指标，由于周期压力模型为根据用户在多个时刻的压力指标确定的、并且只根据当前时刻就可以确定用户的当前压力指标的压力模型，因此，周期压力模型可以大基调的刻画用户在一段时间段内的压力指标、并且不容易受到瞬时因素的影响，保证了精神压力评测系统的鲁棒性，另外，由于瞬时压力模型为需要根据与用户当前的压力状态有关的生理信号确定用户的当前压力指标的压力模型，从而使得精神压力评测系统同时结合了用户的当前 压力状态确定用户的当前压力指标，提高了精神压力评测系统的准确性。
具体的，周期压力模型可以为通过以下方式中的任意一种方式确定的压力模型：
方式一、根据至少一种离散压力指标集确定的压力模型。
其中，离散压力指标集可以为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据用户的主观评测结果、用户的皮质醇浓度或用户的外在表现确定的压力指标。
其中，根据用户的主观评测结果确定的压力指标具体可以为：用户主观对自己当前的压力状态进行评价，给出的压力指标，该情况下，离散压力数据即可以为该压力指标；或者，根据用户填写的压力调查问卷结果确定的用户的压力指标，该情况下，离散压力数据可以为用户填写的压力调查问卷结果。根据用户的外在表现确定的压力指标具体可以为：根据用户的文字记录或表情或动作或声音或音频确定的用户的压力指标，该情况下，离散压力数据可以为用户的文字记录或表情或动作或声音或音频。采用这些方式获取到的离散压力指标由于不容易受到情绪突变、温度影响、光线等瞬时因素的影响，可靠性较高，但是便携性较差。因此，可以用于确定用户的周期压力模型，使得周期压力模型不易受到瞬时因素的影响。
具体的，一个离散压力指标可以对应一个时间点，一个离散压力指标对应的时间点即获取用于确定该离散压力指标的数据的时间点。预设时间段可以为任意时间段，例如，预设时间段可以为一天、一周或一周内的工作日等。压力指标可以为压力值或压力等级，压力值越大或压力等级越高时，表明用户的精神压力越大。
示例性的，如果离散压力指标包括三种类型，如表1所示，T0至T9为预设时间段内的10个时间点，表1示出了第一种、第二种和第三种离散压力指标集中的离散压力指标。第一种离散压力指标集中的离散压力指标为根据用户的主观评测结果确定的压力指标，具体包括S10、S11、S14、S15、S17和S19，这6个离散压力指标分别对应时间点T0、T1、T4、T5、T7和T9。第二种离散压力指标集中的离散压力指标为根据用户的外在表现确定的压力指标，具体包括S20、S22、S23、S24、S25、S26和S28，这6个离散压力指标分别对应时间点T0、T2、T3、T4、T5、T6和T8。第三种离散压力指标集中的离散压力指标为根据用户的皮质醇浓度确定的压力指标，具体包括S30、S31、S33、S34、S36、S37和S39，这7个离散压力指标分别对应时间点T0、T1、T3、T4、T6、T7和T9。
表1
Figure PCTCN2016106306-appb-000001
需要说明的是，第一种离散压力指标集中的离散压力指标可以为根据用户主观对自己当前的压力状态进行评价，给出的压力指标的集合，也可以为根据用户填写的压力调查问卷结果确定的用户的压力指标的集合。第一种离散压力指标集还可以包括根据用户主观对自己当前的压力状态进行评价，给出的压力指标的集合和根据用户填写的压力调查问卷结果确定的用户的压力指标的集合。其他种类的离散压力指标集同理。
具体的，周期压力模型可以通过采用三次样条插值算法或多项 式拟合法等对离散压力指标集中的离散压力指标进行曲线拟合得到。
方式二、根据综合离散压力指标集确定的压力模型。
综合离散压力指标集可以为根据至少一种离散压力指标集确定的压力指标的集合，综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，多个离散压力指标为至少一种离散压力指标集中的对应同一时间点的全部离散压力指标。
一个综合离散压力指标可以为根据多个对应同一时间点的离散压力指标确定。当一个时间点仅获取到一个离散压力指标时，该离散压力指标即该时间点对应的综合离散压力指标。当一个时间点获取到多个离散压力指标、且该多个离散压力指标为采用不同的获取方式获取到的离散压力指标时，一个时间点对应的综合离散压力指标可以为对在该时间点获取到的多个离散压力指标取平均后得到的压力指标，也可以为对在该时间点获取到的多个离散压力指标赋予不同的权重后进行加权和的方式确定的压力指标。
示例性的，基于表1所示的示例，可以确定10个综合离散压力指标，T0对应的综合离散压力指标可以为(S10+S20+S30)/3，T2对应的综合离散压力指标可以为S22。
具体的，周期压力模型可以通过采用三次样条插值算法或多项式拟合法等对综合离散压力指标集中的综合离散压力指标进行曲线拟合得到。
示例性的，如图3所示，可以为拟合得到的周期压力模型。
方式三、根据综合离散压力指标集和多个历史离散压力指标确定的压力模型，历史离散压力指标为在预设时间段之前获取到的离散压力指标。
具体的，当预设时间段为一天时，历史离散压力指标可以为在预设时间段所处的日期的前一天或前多天获取到的离散压力指标，预设时间段为一周内的某天时。例如，预设时间段为周一时，历史离散压力指标可以为在预设时间段所处的日期的前一周或前多个周的周一获取到的离散压力指标。历史离散压力指标还可以为其他时间获取到的离散压力指标，此处仅仅为示例性说明。
该情况下，可以采用一元二次函数来建模，即周期压力模型＝ax2+bx+c，x为时间点，a、b和c为常数，使用最优化方法来确定系数项a、b、c，在计算所有离散压力指标的总误差中，预设时间段内获取到的离散压力指标的误差权重为1，历史离散压力指标的误差权重小于1，具体可以为：历史离散压力指标中的离预设时间段越近的离散压力指标的误差权重越接近1，从而使得越新的离散压力指标对最优化结果影响较大，反之，越旧的离散压力指标对最优化结果影响较小，使得确定的周期压力模型更准确。
可选的，周期压力模型可以包括主观周期压力模型和客观周期压力模型；主观周期压力模型为根据第一种离散压力指标集和/或第二种离散压力指标集确定的压力模型；客观周期压力模型为根据第三种离散压力指标集确定的压力模型。
关于第一种离散压力指标集、第二种离散压力指标集和第三种离散压力指标集以及离散压力指标集的概念可以参见上文。
具体的，当用于确定客观周期压力模型的离散压力指标集中共包括N1个离散压力指标、用于确定主观周期压力模型的一种或多种离散压力指标集中共包括N2个离散压力指标时，可以根据N1个离散压力指标确定N1'个综合离散压力指标，根据N2个离散压力指标确定N2'个综合离散压力指标，根据N1'个综合离散压力指标确定客观周期压力模型，根据N2'个综合离散压力指标确定主观周期压力模 型。其中，N1'个综合离散压力指标各对应N1'个时间点，一个时间点对应的综合离散压力指标由N1个离散压力指标中的在该时间点获取到的离散压力指标确定；N2'个综合离散压力指标各对应N2'个时间点，一个时间点对应的综合离散压力指标由N2个离散压力指标中的在该时间点获取到的离散压力指标确定。
示例性的，N1个离散压力指标可以为在预设时间段内的N1个固定时刻获取到的用户的皮质醇浓度，通过将N1个离散压力指标进行曲线拟合可以得到客观周期压力模型。例如，若预设时间段为一天，N1＝5，则获取N1个离散压力指标的N1个时间点可以为8点、10点、14点、16点和20点，当压力指标为压力值时，可以将N1个时间点测得的皮质醇浓度最高对应压力值100，皮质醇浓度最低对应压力值0，皮质醇浓度越高，压力值越大，从而可以确定N1时间点上的每个离散压力指标。
基于该可选的方法，目标压力模型具体可以为采用加权和的方式或加权几何平均的方式或加权调和平均的方式等对客观周期压力模型、主观周期压力模型和瞬时压力模型进行综合后确定的压力模型。示例性的，若采用加权和的方式，将主观周期压力模型记为Y_subject，客观周期压力模型记为Y_object，瞬时压力模型记为Y_instant，则目标压力模型Y_final＝p1·Y_subject+p2·Y_object+q·Y_instant，其中，p1+p2+q＝1，示例性的，p1＝0.5，p2＝0.3，q＝0.2。
可选的，用户的瞬时压力模型可以为通用压力模型。
建立通用压力模型的方法具体包括：确定用户所在的年龄段内的预设数量的个体作为样本，获取每个个体的样本信息，一个个体的样本信息包括该个体的基本信息(该个体的性别、年龄、身高和体重等)、该个体在一个时间段内的生理信号以及该个体主观给出的 压力指标；确定每个个体的特征向量，一个个体的特征向量的确定方法具体可以为：提取该个体在一个时间段内的生理信号的特征，并将提取出的特征与该个体的基本信息组成特征向量；构造每个个体的线性回归方程，一个个体的线性回归方程的构造方法可以为：根据该个体的特征向量和该个体主观给出的压力指标构造线性回归方程，该个体主观给出的压力指标为该方程的输出；根据预设数量的个体的线性回归方程构造线性回归方程组，使用最小二乘法求得线性回归方程组的回归系数；将特征向量中个各个参数作为自变量，各个自变量对应的回归系数中的系数作为各个自变量的系数，压力指标作为因变量，得到通用压力模型。
示例性的，确定20-30岁的男女各50人，记录每个人的基本信息，基本信息可以包括性别Gender、年龄Age、身高Height、体重Weight；采集每个人1分钟的ECG信号，并让每个人给出自己当前压力值stress，例如，若压力值为百分制，则给出的当前的压力值可以为75分。则通过上述过程可以得到100个样本信息，每个样本信息对应一个人，包含这个人的基本信息、1分钟的ECG信号和主观给出的压力值。
对于一个样本信息，根据该样本信息中的1分钟的ECG信号计算出心率HR，心率的标准偏差std_HR，和该样本信息中的基本信息构成特征向量[Gender，Age，Height，Weight，HR，std_HR]，根据该样本中的主观给出的压力值和该样本信息对应的特征向量构造的线性回归方程为：stress＝a1×Gender+a2×Age+a3×Height+a4×Weight+a5×HR+a6×std_HR+b。根据100个样本信息可以得到由100个线性回归方程组成的线性回归方程组，使用最小二乘法求得线性回归方程组的回归系数a1、a2、a3、a4、a5、a6和b。
则通用压力模型为：S＝a1×Gender+a2×Age+a3×Height+a4×Weight+a5×HR+a6×std_HR+b，其中，a1、a2、a3、a4、a5、a6和b已知，Gender、Age、Height、Weight、HR、std_HR为自变量，S为压力值。
可选的，在步骤203之前，上述方法还可以包括：获取用户的M段生理信号，一段生理信号为在一个时间段内获取到的用户的生理信号，M为大于0的整数；获取用户在M个时间段主观给出的压力指标，得到M个主观压力指标，M个主观压力指标分别对应M个时间段，M个时间段为用于获取M段生理信号的M个时间段；将M段生理信号作为通用压力模型的输入，得到M个通用压力指标；将M个主观压力指标与M个通用压力指标相减，得到M个用户偏置项，其中，对应M个时间段中的同一时间段的主观压力指标和通用压力指标相减；将M个用户偏置项的平均值与通用压力模型之和确定为瞬时压力模型。
具体的，生物电信号具体可以为ECG信号和/或PPG信号，由于生理信号容易受到瞬时因素的影响，因此，可靠性较低，但是生理信号可以根据用户随身携带的设备采集得到，因此，便携性较高。因此，可以用于确定用户的瞬时压力模型，提高确定的用户的压力指标的准确性。
需要说明的是，在获取到通用压力模型之后，由于通用压力模型并不是用户的压力模型，因此，需要对通用压力模型进行校准得到用户的瞬时压力模型。
通用压力模型的输入除了生理信号之外，还包括其他参数，例如，上述实施例中提到的用户的年龄、身高、体重等，这些参数可以通过用户获得，并预先存储在存储器中，以便在计算通用压力指标时进行调用。
具体的，当生理信号为PPG信号时，可以获取用户在M个2分钟内主观给出的压力指标，得到M个主观压力指标，记为Y11、Y12、…、Y1M；采集用户在M个2分钟内的PPG信号，作为通用压力模型的输入，得到M个通用压力指标，记为Y01、Y02、…、Y0M；则M个用户偏置项为Y11-Y01、Y12-Y02、…、Y1M-Y0M；若将通用压力模型记为Y_general，则用户的瞬时压力模型Y_instant＝Y_general+[(Y11-Y01)+(Y12-Y02)+、…、+(Y1M-Y0M)]/M。
可选的，在步骤203之前，上述方法还可以包括：获取用户偏置项，用户偏置项为存储在其他设备中的与用户相关联的、用于校准通用压力模型的偏置项；将用户偏置项与通用压力模型之和确定为用户的瞬时压力模型。
用户偏置项也可以不直接根据获取到的M段生理信号和M个主观压力指标计算，而是在其他设备(例如，服务器)中获取得到。示例性的，在一种情况下，用户可以创建一个帐号，用户偏置项、用户的年龄、身高、体重等信息均与该帐号相关联，这些数据可以存储在服务器中，在需要的时候进行获取。
示例性的，在确定目标压力模型的情况下，如图4所示，图4示出了确定目标压力模型的整体过程，其中，由用户主观对自己当前的压力状态进行评价，给出的压力指标、根据用户填写的压力调查问卷结果确定的用户的压力指标、根据用户血液中的皮质醇浓度确定的用户的压力指标以及根据用户的文字记录或视频或音频确定的用户的压力指标中的至少一项构成N个离散压力指标，根据N个离散压力指标可以确定周期压力模型；根据用户的运动信号和/或生物电信号确定的用户的M段生理信号，根据M段生理信号可以确定瞬时压力模型；将周期压力模型和瞬时压力模型进行合成得到目标压力模型。
需要说明的是，用户的周期压力模型仅与时间有关，但是用户的瞬时压力模型与生理信号有关还与用户的其他参数(例如，用户的年龄、身高、体重等)有关，因此，目标压力模型与时间、生理信号以及其他参数有关。在具体实现时，用户的其他参数可以预存在实现本发明实施例提供的方法的装置的存储器中，时间和生理信号可以通过用户随身携带的设备实时获取。
在本发明实施例提供的方法中，预设时间段可以为一天，该情况下，目标压力模型为用户的天压力模型，通过上述方法可以得到一周中的每天的目标压力模型，将一周中的每天的目标压力模型进行组合得到用户的周压力模型，当然，预设时间段也可以为一周，该情况下，目标压力模型为用户的周压力模型。
一种场景下，当用户需要获取当前的压力指标时，可以通过点击该装置上设置的获取生理信号的按钮获取一段时间(例如，1分钟或2分钟)的ECG信号，该ECG信号隐含了当前时刻。
由于周期压力模型可以为根据离散压力指标或综合离散压力指标进行曲线拟合后得到的压力模型。该情况下，参见图3，周期压力模型为以时间为自变量，压力指标为因变量的函数，将当前时刻作为周期压力模型的输入，即可得到第一压力指标。
若通用压力模型为：S＝a1×Gender+a2×Age+a3×Height+a4×Weight+a5×HR+a6×std_HR+b，用户偏置项为c，则瞬时压力模型为：S＝a1×Gender+a2×Age+a3×Height+a4×Weight+a5×HR+a6×std_HR+b+c。其中，a1、a2、a3、a4、a5、a6、b和c均已知，用户的Gender，Age，Height和Weight可以从存储器中获取到，HR和std_HR可以根据ECG信号计算得出，则根据ECG信号和瞬时压力模型可以计算得到用户的第二压力指标。
将第一压力指标和第二压力指标加权求和即可得到用户的当前压力指标。
通过采用本发明实施例提供的方法定性或定量地评测用户的精神压力，有助于运动类、服务类商品的推送，以及身体情况的辅助预警，能进行压力过大提醒，还可以根据日常精神状态安排不同的事情或工作，从而提升生活或工作效率等。
另外，需要说明的是，上述周期压力模型和瞬时压力模型(或目标压力模型)也可以不是预先存储在执行本发明实施例提供的方法的设备中，而是由该设备通过获取相应的、用于确定周期压力模型和瞬时压力模型(或目标压力模型)的参数后，自行确定的。该设备在自行确定后，可以将周期压力模型和瞬时压力模型(或目标压力模型)存储在该设备中。
可以理解的是，用于实现上述方法的装置为了实现上述方法，包含了执行上述各个步骤相应的硬件结构和/或软件单元。本领域技术人员应该很容易意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，本发明能够以硬件或硬件和计算机软件的结合形式来实现。某个功能究竟以硬件还是计算机软件驱动硬件的方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本发明的范围。
本发明实施例可以根据上述方法示例性的对用于执行上述方法的装置进行功能单元的划分。例如，可以对应各个功能划分各个功能单元，也可以将两个或两个以上的功能单元集成在一个处理单元中。需要说明的是，本发明实施例中对功能单元的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。
示例性的，如图5所示，图5示出了一种精神压力评测装置50， 包括：获取单元501和处理单元502；
获取单元501，用于获取当前时刻用户的生理信号；
处理单元502，用于根据当前时刻和用户的周期压力模型确定用户的第一压力指标，周期压力模型为根据用户在多个时刻的压力指标确定的、并且只根据当前时刻即可确定用户的当前压力指标的压力模型；
处理单元502，还用于根据当前时刻用户的生理信号和用户的瞬时压力模型确定用户的第二压力指标，瞬时压力模型为根据与用户的当前压力状态有关的生理信号确定用户当前压力指标的压力模型，生理信号为瞬时压力模型的输入；
处理单元502，还用于根据第一压力指标和第二压力指标确定用户的当前压力指标。
可选的，周期压力模型为根据至少一种离散压力指标集确定的压力模型，离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据用户的主观评测结果、用户的皮质醇浓度或用户的外在表现确定的压力指标。
可选的，周期压力模型包括主观周期压力模型和客观周期压力模型；主观周期压力模型为根据第一种离散压力指标集和/或第二种离散压力指标集确定的压力模型，第一种离散压力指标集中的离散压力指标为根据用户的主观评测结果确定的压力指标，第二种离散压力指标集中的离散压力指标为根据用户的外在表现确定的压力指标；客观周期压力模型为根据第三种离散压力指标集确定的压力模型，第三种离散压力指标集中的离散压力指标为根据用户的皮质醇浓度确定的压力指标；离散压力指标集为根据预设时间段内获取到 的至少一个时间点的离散压力数据确定的压力指标的集合。
可选的，周期压力模型为根据综合离散压力指标集确定的压力模型，综合离散压力指标集为根据至少一种离散压力指标集确定的压力指标的集合，综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，多个离散压力指标为至少一种离散压力指标集中的对应同一时间点的全部离散压力指标，离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据用户的主观评测结果、用户的皮质醇浓度或用户的外在表现确定的压力指标。
可选的，周期压力模型为根据综合离散压力指标集和多个历史离散压力指标确定的压力模型，综合离散压力指标集为根据至少一种离散压力指标集确定的压力指标的集合，综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，多个离散压力指标为至少一种离散压力指标集中的对应同一时间点的全部离散压力指标，离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据用户的主观评测结果、用户的皮质醇浓度或用户的外在表现确定的压力指标；历史离散压力指标为在预设时间段之前获取到的离散压力指标。
可选的，获取单元501，还用于获取用户的M段生理信号，一段生理信号为在一个时间段内获取到的用户的生理信号，M为大于0的整数；获取用户在M个时间段主观给出的压力指标，得到M个主观压力指标，M个主观压力指标分别对应M个时间段，M个时间段为用于获取M段生理信号的M个时间段；
处理单元502，还用于将M段生理信号作为通用压力模型的输 入，得到M个通用压力指标；将M个主观压力指标与M个通用压力指标相减，得到M个用户偏置项，其中，对应M个时间段中的同一时间段的主观压力指标和通用压力指标相减；将M个用户偏置项的平均值与通用压力模型之和确定为瞬时压力模型。
可选的，获取单元501，还用于获取用户偏置项，用户偏置项为存储在其他设备中的与用户相关联的、用于校准通用压力模型的偏置项；
处理单元502，还用于将用户偏置项与通用压力模型之和确定为用户的瞬时压力模型。
可选的，生理信号为运动信号和/或生物电信号。
该装置50中的各个单元用于执行上述方法，因此，该装置50的有益效果可以参见上述方法的有益效果，在此不再赘述。
装置50中的各个单元执行的动作可以由精神压力评测装置中的处理器执行，例如，可以由图1所示的精神压力评测装置中的处理器102执行。相比图1所示的精神压力评测装置，如图6所示，图6示出了更加简单的一种精神压力评测装置60的硬件结构示意图，装置60包括存储器601、处理器602、总线603和通信接口604，存储器601用于存储计算机执行指令，处理器602与存储器601通过总线603连接，处理器602通过执行存储器601存储的计算机执行指令，以实现上述方法。
关于存储器601和处理器602的类型可以参照上文中的关于存储器101和处理器102的相关描述，在此不再赘述。
其中，总线603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。该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6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。
本领域技术人员应该可以意识到，在上述一个或多个示例中，本发明所描述的功能可以用硬件、软件、固件或它们的任意组合来实现。当使用软件实现时，可以将这些功能存储在计算机可读介质中或者作为计算机可读介质上的一个或多个指令或代码进行传输。计算机可读介质包括计算机存储介质和通信介质，其中通信介质包括便于从一个地方向另一个地方传送计算机程序的任何介质。存储介质可以是通用或专用计算机能够存取的任何可用介质。
以上所述的具体实施方式，对本发明的目的、技术方案和有益效果进行了进一步详细说明，所应理解的是，以上所述仅为本发明的具体实施方式而已，并不用于限定本发明的保护范围，凡在本发明的技术方案的基础之上，所做的任何修改、等同替换、改进等，均应包括在本发明的保护范围之内。

Claims (17)

  1. 一种精神压力评测方法，其特征在于，包括：
    获取当前时刻用户的生理信号；
    根据所述当前时刻和所述用户的周期压力模型确定所述用户的第一压力指标，所述周期压力模型为根据所述用户在多个时刻的压力指标确定的、并且只根据所述当前时刻即可确定所述用户的当前压力指标的压力模型；
    根据所述当前时刻用户的生理信号和所述用户的瞬时压力模型确定所述用户的第二压力指标，所述瞬时压力模型为根据与所述用户的当前压力状态有关的生理信号确定所述用户当前压力指标的压力模型，所述生理信号为所述瞬时压力模型的输入；
    根据所述第一压力指标和所述第二压力指标确定所述用户的当前压力指标。
  2. 根据权利要求1所述的方法，其特征在于，所述周期压力模型为根据至少一种离散压力指标集确定的压力模型，所述离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据所述用户的主观评测结果、所述用户的皮质醇浓度或所述用户的外在表现确定的压力指标。
  3. 根据权利要求1所述的方法，其特征在于，所述周期压力模型包括主观周期压力模型和客观周期压力模型；所述主观周期压力模型为根据第一种离散压力指标集和/或第二种离散压力指标集确定的压力模型，所述第一种离散压力指标集中的离散压力指标为根据所述用户的主观评测结果确定的压力指标，所述第二种离散压力指标集中的离散压力指标为根据所述用户的外在表现确定的压力指标；所述客观周期压力模型为根据第三种离散压力指标集确定的压力模型，所述第三种离散压力指标集中的离散压力指标为根据所述用户的皮质醇 浓度确定的压力指标；所述离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合。
  4. 根据权利要求1所述的方法，其特征在于，所述周期压力模型为根据综合离散压力指标集确定的压力模型，所述综合离散压力指标集为根据至少一种离散压力指标集确定的压力指标的集合，所述综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，所述多个离散压力指标为所述至少一种离散压力指标集中的对应同一时间点的全部离散压力指标，所述离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据所述用户的主观评测结果、所述用户的皮质醇浓度或所述用户的外在表现确定的压力指标。
  5. 根据权利要求1所述的方法，其特征在于，所述周期压力模型为根据综合离散压力指标集和多个历史离散压力指标确定的压力模型，所述综合离散压力指标集为根据至少一种离散压力指标集确定的压力指标的集合，所述综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，所述多个离散压力指标为所述至少一种离散压力指标集中的对应同一时间点的全部离散压力指标，所述离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据所述用户的主观评测结果、所述用户的皮质醇浓度或所述用户的外在表现确定的压力指标；所述历史离散压力指标为在所述预设时间段之前获取到的离散压力指标。
  6. 根据权利要求1-5任一项所述的方法，其特征在于，在根据所述当前生理信号和所述用户的瞬时压力模型确定所述用户的第二压力指标之前，所述方法还包括：
    获取所述用户的M段生理信号，一段生理信号为在一个时间段 内获取到的所述用户的生理信号，M为大于0的整数；
    获取所述用户在M个时间段主观给出的压力指标，得到M个主观压力指标，所述M个主观压力指标分别对应M个时间段，所述M个时间段为用于获取所述M段生理信号的M个时间段；
    将所述M段生理信号作为通用压力模型的输入，得到M个通用压力指标；
    将所述M个主观压力指标与所述M个通用压力指标相减，得到M个用户偏置项，其中，对应所述M个时间段中的同一时间段的主观压力指标和通用压力指标相减；
    将所述M个用户偏置项的平均值与所述通用压力模型之和确定为所述瞬时压力模型。
  7. 根据权利要求1-5任一项所述的方法，其特征在于，在根据所述当前生理信号和所述用户的瞬时压力模型确定所述用户的第二压力指标之前，所述方法还包括：
    获取用户偏置项，所述用户偏置项为存储在其他设备中的与所述用户相关联的、用于校准通用压力模型的偏置项；
    将所述用户偏置项与所述通用压力模型之和确定为所述用户的瞬时压力模型。
  8. 根据权利要求1-7任一项所述的方法，其特征在于，所述生理信号为运动信号和/或生物电信号。
  9. 一种精神压力评测装置，其特征在于，包括：
    获取单元，用于获取当前时刻用户的生理信号；
    处理单元，用于根据所述当前时刻和所述用户的周期压力模型确定所述用户的第一压力指标，所述周期压力模型为根据所述用户在多个时刻的压力指标确定的、并且只根据所述当前时刻即可确定所述用户的当前压力指标的压力模型；
    所述处理单元，还用于根据所述当前时刻用户的生理信号和所述 用户的瞬时压力模型确定所述用户的第二压力指标，所述瞬时压力模型为根据与所述用户的当前压力状态有关的生理信号确定所述用户当前压力指标的压力模型，所述生理信号为所述瞬时压力模型的输入；
    所述处理单元，还用于根据所述第一压力指标和所述第二压力指标确定所述用户的当前压力指标。
  10. 根据权利要求9所述的装置，其特征在于，所述周期压力模型为根据至少一种离散压力指标集确定的压力模型，所述离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据所述用户的主观评测结果、所述用户的皮质醇浓度或所述用户的外在表现确定的压力指标。
  11. 根据权利要求9所述的装置，其特征在于，所述周期压力模型包括主观周期压力模型和客观周期压力模型；所述主观周期压力模型为根据第一种离散压力指标集和/或第二种离散压力指标集确定的压力模型，所述第一种离散压力指标集中的离散压力指标为根据所述用户的主观评测结果确定的压力指标，所述第二种离散压力指标集中的离散压力指标为根据所述用户的外在表现确定的压力指标；所述客观周期压力模型为根据第三种离散压力指标集确定的压力模型，所述第三种离散压力指标集中的离散压力指标为根据所述用户的皮质醇浓度确定的压力指标；所述离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合。
  12. 根据权利要求9所述的装置，其特征在于，所述周期压力模型为根据综合离散压力指标集确定的压力模型，所述综合离散压力指标集为根据至少一种离散压力指标集确定的压力指标的集合，所述综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，所述多个离散压力指标为所述至少一种离散压力指标集中的 对应同一时间点的全部离散压力指标，所述离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据所述用户的主观评测结果、所述用户的皮质醇浓度或所述用户的外在表现确定的压力指标。
  13. 根据权利要求9所述的装置，其特征在于，所述周期压力模型为根据综合离散压力指标集和多个历史离散压力指标确定的压力模型，所述综合离散压力指标集为根据至少一种离散压力指标集确定的压力指标的集合，所述综合离散压力指标集中的一个综合离散压力指标根据多个离散压力指标确定，所述多个离散压力指标为所述至少一种离散压力指标集中的对应同一时间点的全部离散压力指标，所述离散压力指标集为根据预设时间段内获取到的至少一个时间点的离散压力数据确定的压力指标的集合，一种离散压力指标集中的离散压力指标为根据所述用户的主观评测结果、所述用户的皮质醇浓度或所述用户的外在表现确定的压力指标；所述历史离散压力指标为在所述预设时间段之前获取到的离散压力指标。
  14. 根据权利要求9-13任一项所述的装置，其特征在于，
    所述获取单元，还用于获取所述用户的M段生理信号，一段生理信号为在一个时间段内获取到的所述用户的生理信号，M为大于0的整数；获取所述用户在M个时间段主观给出的压力指标，得到M个主观压力指标，所述M个主观压力指标分别对应M个时间段，所述M个时间段为用于获取所述M段生理信号的M个时间段；
    所述处理单元，还用于将所述M段生理信号作为通用压力模型的输入，得到M个通用压力指标；将所述M个主观压力指标与所述M个通用压力指标相减，得到M个用户偏置项，其中，对应所述M个时间段中的同一时间段的主观压力指标和通用压力指标相减；将所述M个用户偏置项的平均值与所述通用压力模型之和确定为所述瞬 时压力模型。
  15. 根据权利要求9-13任一项所述的装置，其特征在于，
    所述获取单元，还用于获取用户偏置项，所述用户偏置项为存储在其他设备中的与所述用户相关联的、用于校准通用压力模型的偏置项；
    所述处理单元，还用于将所述用户偏置项与所述通用压力模型之和确定为所述用户的瞬时压力模型。
  16. 根据权利要求9-15任一项所述的装置，其特征在于，所述生理信号为运动信号和/或生物电信号。
  17. 一种精神压力评测装置，其特征在于，包括：处理器、存储器、总线和通信接口；
    所述存储器用于存储计算机执行指令，所述处理器与所述存储器通过所述总线连接，所述处理器执行所述存储器存储的所述计算机执行指令，以执行如权利要求1-8中任一项所述的方法。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110251147A (zh) * 2019-06-03 2019-09-20 常州为伊心理咨询有限公司 一种面向中小学生心理测评用信息采集系统

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11024329B2 (en) * 2018-03-28 2021-06-01 International Business Machines Corporation Word repetition in separate conversations for detecting a sign of cognitive decline
CN111341416B (zh) * 2018-12-18 2023-09-29 华为技术有限公司 一种心理压力评估模型处理方法以及相关设备
CN110025321B (zh) * 2019-03-20 2021-08-31 华为技术有限公司 一种心理压力评估方法及相关设备
CN110192872B (zh) * 2019-04-16 2020-09-11 华为技术有限公司 压力评估校准方法、装置及存储介质
CN111080247A (zh) * 2019-12-09 2020-04-28 珠海格力电器股份有限公司 一种员工培训日程调整方法及装置
JP2021101846A (ja) * 2019-12-25 2021-07-15 富士フイルムビジネスイノベーション株式会社 情報処理装置及びプログラム
CN112022172B (zh) * 2020-09-03 2023-03-28 北京中科心研科技有限公司 一种基于多模态生理数据的压力检测方法和装置
CN112168188B (zh) * 2020-10-09 2023-07-25 北京中科心研科技有限公司 一种用于压力检测数据的处理方法和装置
CN113421647A (zh) * 2021-07-20 2021-09-21 上海暖禾临床心理诊所有限公司 基于二维码的心理状态数据采集、处理和输出系统及方法

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103202699A (zh) * 2013-03-25 2013-07-17 苏州德鲁克供应链管理有限公司 心理健康监测系统
CN104239288A (zh) * 2014-09-18 2014-12-24 清华大学 基于微博的青少年心理压力检测和疏导的方法及系统
CN104490407A (zh) * 2014-12-08 2015-04-08 清华大学 一种可穿戴式心理压力评测装置及方法
US20150120205A1 (en) * 2013-10-24 2015-04-30 Samsung Electronics Co., Ltd. System and method for managing stress
CN104688249A (zh) * 2015-02-13 2015-06-10 北京康源互动健康科技有限公司 一种基于云平台的心理健康监测方法及系统
CN105232063A (zh) * 2015-10-22 2016-01-13 广东小天才科技有限公司 用户心理健康检测方法及智能终端
CN105559803A (zh) * 2015-12-17 2016-05-11 国家电网公司 一种电网企业工作人员心理压力状况评估方法

Family Cites Families (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH01119076A (ja) * 1987-10-30 1989-05-11 Nec Corp 酸化物超伝導体膜の製造方法
JPH01138004A (ja) * 1987-11-25 1989-05-30 Kobe Steel Ltd 内部品質の良好な厚鋼板の製造方法
JPH1119076A (ja) 1997-07-07 1999-01-26 Pola Chem Ind Inc 香りの抗ストレス効果の測定法
JPH1138004A (ja) 1997-07-16 1999-02-12 Pola Chem Ind Inc ストレスの定量法
JP2000126143A (ja) * 1998-10-26 2000-05-09 Sysmex Corp 胃電図によるストレス耐性評価方法
JP4453142B2 (ja) 2000-01-31 2010-04-21 パナソニック電工株式会社 電子血圧計
JP3953024B2 (ja) 2003-11-20 2007-08-01 ソニー株式会社 感情算出装置及び感情算出方法、並びに携帯型通信装置
RU2299681C1 (ru) * 2005-11-17 2007-05-27 Государственное образовательное учреждение высшего профессионального образования "БАШКИРСКИЙ ГОСУДАРСТВЕННЫЙ МЕДИЦИНСКИЙ УНИВЕРСИТЕТ Федерального Агентства по здравоохранению и социальному развитию" (ГОУ ВПО БГМУ РОСЗДРАВА) Способ оценки степени тяжести психовегетативных расстройств при синдроме постовариэктомии
JP5328030B2 (ja) * 2008-07-11 2013-10-30 学校法人東京理科大学 脳情報から人間の選好を判別する方法及びその装置
US8540629B2 (en) * 2011-05-13 2013-09-24 Fujitsu Limited Continuous monitoring of stress using a stress profile created by renal doppler sonography
BR112014012033B1 (pt) * 2011-11-22 2022-03-29 Koninklijke Philips N.V. Sistema de estimativa de equilíbrio ou desequilíbrio mental, dispositivo utilizável por um usuário e método de estimativa de equilíbrio ou desequilíbrio mental
BR112017009795A2 (pt) * 2014-11-11 2017-12-19 Global Stress Index Pty Ltd sistema e método para gerar um perfil de níveis de estresse e de níveis de resiliência de estresse em uma população
CN104983434B (zh) * 2015-06-17 2018-05-01 重庆邮电大学 基于层次分析法的多参数心理压力评估方法及装置
CN105193431B (zh) * 2015-09-02 2017-12-01 杨静 一种人体精神压力状态分析装置
WO2017078759A1 (en) * 2015-11-06 2017-05-11 Lifeq Global Limited Non-invasive physiological quantification of stress levels
CN105679333B (zh) * 2016-03-03 2019-04-12 河海大学常州校区 声带-喉室-声道联动的物理模型及精神压力检测方法
CN106037764B (zh) * 2016-05-20 2019-02-19 包磊 一种压力管理方法及系统

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103202699A (zh) * 2013-03-25 2013-07-17 苏州德鲁克供应链管理有限公司 心理健康监测系统
US20150120205A1 (en) * 2013-10-24 2015-04-30 Samsung Electronics Co., Ltd. System and method for managing stress
CN104239288A (zh) * 2014-09-18 2014-12-24 清华大学 基于微博的青少年心理压力检测和疏导的方法及系统
CN104490407A (zh) * 2014-12-08 2015-04-08 清华大学 一种可穿戴式心理压力评测装置及方法
CN104688249A (zh) * 2015-02-13 2015-06-10 北京康源互动健康科技有限公司 一种基于云平台的心理健康监测方法及系统
CN105232063A (zh) * 2015-10-22 2016-01-13 广东小天才科技有限公司 用户心理健康检测方法及智能终端
CN105559803A (zh) * 2015-12-17 2016-05-11 国家电网公司 一种电网企业工作人员心理压力状况评估方法

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110251147A (zh) * 2019-06-03 2019-09-20 常州为伊心理咨询有限公司 一种面向中小学生心理测评用信息采集系统

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