CN104715129A - Mental health state assessment system and method based on mobile equipment using behavior - Google Patents
Mental health state assessment system and method based on mobile equipment using behavior Download PDFInfo
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Abstract
The invention provides a mental health state assessment system and method based on mobile equipment using behavior. The system comprises an information recording module, a behavior extracting module, an assessment model establishing module and an assessment module. The information recording module is used for recording and storing the using information of intelligent mobile equipment. The behavior extracting module is used for carrying out data preprocessing on recorded equipment using information, effective equipment using behavior for interaction between a user and equipment is extracted, and equipment using behavior features are mined. The assessment model establishing module is used for establishing a mental health state assessment model based on the relation between the intelligent mobile equipment using behavior features and mental health states obtained with a machine learning method. The assessment module is used for inputting the mined equipment using behavior features into the mental health state assessment model, and a mental health state assessment result is obtained.
Description
Technical field
The present invention relates to psychological health states assessment technology, more specifically, relate to a kind of psychological health states evaluating system based on Intelligent mobile equipment usage behavior and method, this system and method usage log carries out psychological health states assessment.
Background technology
Current, worldwide, Psychological Health Problem has become the first cause causing individuality " anergy " (disability), its passivity consequence accounts for 37% of all disease harm, in conjunction with the development trend of its " global " (global), " chronicity " (chronic) and " popularity " (prevalent), the existence of Psychological Health Problem not only can cause huge consumption and the waste of social resources, exacerbate the burden of entire society, and directly threaten individual daily life quality and Subjective Sense of Happiness.
Specific to the actual conditions of China, according to he result of investigation display, the integral level of common people's mental health allows of no optimist equally, and the overall incidence of Psychological Health Problem reaches 17.5%.Because China has huge population base, so it is more urgent to adopt efficient counter-measure to solve the demand of Psychological Health Problem.
Usually, the first step of mental health services is provided to carry out " psychological health states assessment " individuality exactly.The psychological assessment specificity behavior symptom related to for individuality carries out collecting, analyzes, comprehensively, judges, specifically can comprise the multiple technologies such as " interview ", " questionnaire test ", " projective test ".In the last few years, the structural and objectivity that " questionnaire test " had in instrument establishment, testing operation, result explanation etc. because of it obtains relative clinical practice widely." questionnaire test " technology can carry out the psychological health states of comprehensive consideration individuality usually from multiple angle by means of some comprehensive Evaluation on psychological health instruments (such as MMPI-2, SCL-90 questionnaire).
In psychometrics (Psychometrics), a kind of survey instrument of gained impression during measuring scale (rating scales) used by " questionnaire test " is used to quantize to observe is one of the important means of data collection in psychological condition assessment.Measuring scale is by some item design, and each project can be regarded as and describes the abstract of a series of behavioural characteristic, and these behavioural characteristics and psychological characteristics also exist certain relation.During by scale assessment psychological health states, first, individuality is needed to fill in scale according to the compatible degree of own situation and the contents of a project; Secondly, the methods of marking that assessment officer provides according to scale handbook calculates scoring; Finally, assessment officer, according to evaluating result, proposes conclusion, and makes an explanation to its meaning, be reported to individuality with word or oral form.
While " questionnaire test " technology is widely used in psychological assessment, also expose the deficiency of some himself existed.The data precision collected can be subject to the impact of tested subjective factor, because this technology makes individuality serve as under study for action " observed object " and " observation main body " two kinds of roles simultaneously, when individuality is when filling in scale, its answer inevitably can be subject to the impact of society's praise psychology, individual cognition ability.Although wherein some subjective bias factor can be investigated by some control devices (such as validity scale or experimental design), but in similar research, repeatedly like implementation of class, control but very loaded down with trivial details poor efficiency, and cannot exclusive segment invalid data (such as mistake is answered, leak and answer or blindly to answer).
In addition, the data details collected of " questionnaire test " technology and scale limited.First, due to the restriction by space-time and some social conditions, each experiment is difficult to convene the individuality of quantity abundance to fill in scale, and also more difficult to carrying out tracking measurement with a collection of individuality.Secondly, conveniently individuality completes investigation, and it is very many that the exercise question of scale can not design, thus collect the more details less than individual behavior sample.In addition, scale granting, collect and also bring adverse influence to extensive image data with typing.
Summary of the invention
For overcoming above-mentioned defect of the prior art, the present invention proposes a kind of psychological health states evaluating system based on Intelligent mobile equipment usage behavior and method.
According to an aspect of the present invention, propose a kind of psychological health states evaluating system based on Intelligent mobile equipment usage behavior, comprising: information logging modle, behavior extraction module, assessment models set up module and and evaluation module; Wherein, information logging modle is for recording and store the use information of Intelligent mobile equipment; Behavior extraction module is used for carrying out data prediction to the device using information of record, extracts user and equipment carries out mutual effective equipment use behavior, excavating equipment usage behavior feature; Assessment models sets up module for obtaining contacting between Intelligent mobile equipment usage behavior feature and mental health state based on machine learning method, sets up the psychological health states assessment models based on Intelligent mobile equipment usage behavior feature; Evaluation module is used for the equipment use behavioural characteristic of excavation to be input to psychological health states assessment models, obtains psychological health states assessment result.
According to a further aspect in the invention, propose a kind of psychological health states appraisal procedure based on Intelligent mobile equipment usage behavior, comprising: step 1, the use information of record Intelligent mobile equipment; Step 2, carries out data prediction to this use information, and combined with intelligent mobile device usage behavior index system, excavates corresponding equipment use behavioural characteristic; Step 3, utilizes machine learning method, obtains contacting between Intelligent mobile equipment usage behavior feature and mental health state, sets up the psychological health states assessment models based on Intelligent mobile equipment usage behavior feature; Step 4, is input to psychological health states assessment models by the equipment use behavioural characteristic excavated, obtains psychological health states assessment result.
The application overcomes the current some shortcomings in Data Collection being widely used in " questionnaire test " technology of psychological health states assessment, not only eliminate the impact of individual subjective factor on Data Collection, more convenient, accurately, objectively collect psychological health states assessment needed for individual data items, and the advantage relying on smart machine to be popularized rapidly, large-scale individual data items collection can be carried out in wider scope, realize large-scale Mental health evaluation.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the psychological health states appraisal procedure based on Intelligent mobile equipment usage behavior according to the application.
In order to the structure of embodiments of the invention clearly can be realized, specific structure and device are marked in the drawings, but this is only signal needs, be not intended to limit the invention in this ad hoc structure, device and environment, according to specific needs, these devices and environment can carry out adjusting or revising by those of ordinary skill in the art, and the adjustment carried out or amendment are still included in the scope of accompanying claim.
Embodiment
Below in conjunction with the drawings and specific embodiments, a kind of psychological health states evaluating system based on Intelligent mobile equipment usage behavior provided by the invention and method are described in detail.
In the following description, by description multiple different aspect of the present invention, but, for those skilled in the art, can only utilize some or all structure of the present invention or flow process to implement the present invention.In order to the definition explained, set forth specific number, configuration and order, but clearly, also can implement the present invention when there is no these specific detail.In other cases, in order to not obscure the present invention, will no longer be described in detail for some well-known features.
In psychometrics, assessment psychological health states all carries out indirect inspection by individual outer aobvious " behavior sample " (behavior sample) index.Because the behavior of individuality is by the domination of its psychological condition and affect, the difference of mental health state can the difference of subordinate act embody, so can know individual mental health state by " behavior sample " that can observe from portion.
For today that Intelligent mobile equipment has been popularized, the psychological health states utilizing the Intelligent mobile equipment usage behavior of user to assess user has its optimized integration.Intelligent mobile equipment was popularized rapidly in recent years.Market research agency Canalys issues report and claims, and the first quarter in 2013 whole world Intelligent mobile equipment shipment amount is 3.087 hundred million, increases by 37.4% on a year-on-year basis.On September 24th, 2013, move consumer analyses according to the Asian-Pacific area of International Consultation company Nielsen issue and report display, Chinese smart mobile phone popularity rate reaches 71%.Chinese user more comprehensively enters the epoch of mobile than ever, embraces the arrival of mobile revolution.
Intelligent mobile equipment usage behavior has become the indispensable important component part of people's behavioral agent one.Along with smart mobile phone, the continuous of tablet device are popularized, the study of people, work, life closely combine with Intelligent mobile equipment, and people use the time of this kind equipment to get more and more.Meanwhile, Intelligent mobile equipment usage behavior also becomes an important component part of people's behavioral agent.
Chinese invention patent CN103430523 applicant Fujitsu Ltd. proposes in a kind of telephone call assistance device and call householder method, disclose the psychological condition that the phonetic feature that can be sent by client in parsing call measures client, but the method only simply judges by the expection of user the mood whether user is satisfied with, and can not go deep into and determine accurately the psychological characteristics of user.
In the first embodiment of the present invention, provide a kind of psychological health states evaluating system based on Intelligent mobile equipment usage behavior, this system comprises: information logging modle, behavior extraction module, assessment models set up module and and evaluation module.Wherein, information logging modle is for recording and store the use information of Intelligent mobile equipment; Behavior extraction module is used for carrying out data prediction to the device using information of record, extracts user and equipment carries out mutual effective equipment use behavior, excavating equipment usage behavior feature; Assessment models sets up module for obtaining contacting between Intelligent mobile equipment usage behavior feature and mental health state based on machine learning method, sets up the psychological health states assessment models based on Intelligent mobile equipment usage behavior feature; Evaluation module is used for the Intelligent mobile equipment usage behavior feature of user to be input to psychological health states assessment models, obtains its psychological health states assessment result.
Wherein, information logging modle is used for the equipment use daily record of user to store in local data base in an operating system.For Android intelligent operating system, Android defines a kind of permission scheme and comes resource on proterctive equipment and function, and when installing this program, if user has authorized all authorities needed for program, then program can the service condition of recording unit.The information of the program equipment service condition of behavior record module is mainly through three kinds of modes.Part information is obtained by content viewer, needs to set up content viewer when system starts, and detection is as this type of the information such as note, contact database change; Also some information is the service acquisition provided by system, as GPS information; System also has another one wake up procedure, periodically obtains information and the Web vector graphic information of system application.
Behavior extraction module is used for carrying out data prediction to the equipment use daily record of recording from system database, therefrom extract user and equipment carries out mutual effective equipment use behavior, combined with intelligent mobile device usage behavior index system, the equipment use behavioural characteristic of user is excavated from the equipment use daily record of user, the equipment use behavior of described user based on Intelligent mobile equipment usage behavior system, the more general and more representative behavioural characteristic taken out from the device using information record that user is concrete.
Assessment models sets up module for utilizing the method for existing machine learning, find contacting between Intelligent mobile equipment usage behavior feature and mental health state, set up the psychological health states assessment models based on Intelligent mobile equipment usage behavior feature, described machine learning method is classification wherein or homing method, described mental health state is the psychological health states of the individuality obtained by measuring scale measurement, and described psychological health states model is train by machine learning method the mathematical model obtained.
Wherein, behavior extraction module comprises data cleansing submodule and data transformation submodule.Wherein data cleansing submodule is for removing abnormal data in daily record, correcting a mistake, removing redundant data and standardization journal format; Data transformation submodule is used for by smoothly daily record is converted to the form being applicable to data mining by gathering, Data generalization and normalized mode.
Wherein, the Intelligent mobile equipment usage behavior index system in behavior extraction module is: according to the behavior collection describing user's Intelligent mobile equipment usage behavior, utilizes Intelligent mobile equipment to reach the target of oneself and to be contemplated to be a decision process.Decision process refers to the overall process selecting action scheme, namely effectively selects to can be used for the scheme reaching target in designated environment.
Wherein, in Intelligent mobile equipment use procedure, user attempts to find the selection about the systemic-function/service aid/Third party system application choice meeting self actual psychological needs most, this shows as and finds its each self-corresponding use effect when applying Intelligent mobile equipment, fed back by result (whether meeting psychological needs), more its unexpectedness effect produced when practical application that makes quickly are converted into intended effect, thus the final Intelligent mobile equipment use-pattern selecting that most probable to represent desirable intended effect.Selective Intelligent mobile equipment operational version specifically includes the combination of the different frequency of utilization results of the selection/Third party system application choice of systemic-function/service aid, the personal feature of behavioral agent is then for the selectivity execution of the Intelligent mobile equipment operational version of multiple combination provides according to (giving weight and layout execution sequence), therefore Intelligent mobile equipment usage behavior can be seen as the selectivity execution result of multiple Intelligent mobile equipment operational version or the outer aobvious of execution, it is personal feature (Demographics, psychological characteristics) function.Wherein, Demographics is outer aobvious observable, therefore can by the concrete selection result (the different frequencies of utilization of the selection/Third party system application choice of systemic-function/service aid) of user for Intelligent mobile equipment course of an action, in conjunction with the population statistics of himself, go back the psychological characteristics of original subscriber, in this, as the framework of Organizational Intelligence mobile device usage behavior index system.
In the second embodiment of the present invention, provide a kind of psychological health states appraisal procedure based on Intelligent mobile equipment usage behavior, wherein, Fig. 1 is the method flow diagram of the assessment of the psychological health states based on Intelligent mobile equipment usage behavior of the second embodiment.As shown in Figure 1, the process of assessment comprises the following steps: first, the service condition of Intelligent mobile equipment is got off with logged; Secondly, carry out data prediction to daily record, combined with intelligent mobile device usage behavior feature architecture, excavates corresponding equipment use behavioural characteristic from the usage log of equipment; Again, utilize the method for existing machine learning, find contacting between Intelligent mobile equipment usage behavior feature and mental health state, set up the psychological health states assessment models based on Intelligent mobile equipment usage behavior feature; Finally, the equipment use behavioural characteristic excavated is input to psychological health states assessment models, obtains its psychological health states assessment result.
Further, step 101, obtains the rights of using of Intelligent mobile equipment, the service condition of recording unit, and is written in local data base.Wherein, the usage behavior of record can comprise 14 classes, and detailed content is as shown in table 1.Show systemsens in program data base and record all device using informations, its field structure is as shown in table 2 below.Different classes of usage behavior represents primarily of the field data_type in table 2.Corresponding to table 1, the value of data_type and the content of representative as shown in table 3.
Table 1 mobile phone usage behavior record data content
Table 2 mobile phone uses database of record storage list systemsens design
Table 3data_type span
Step 102, gets the device using information recorded from local data base, line number of going forward side by side Data preprocess.Data prediction comprises data cleansing, gets rid of noise data, removes the record not having actual content, and the information in daily record is regular by use classes classification.
Step 103, combined with intelligent mobile device usage behavior index system, extracts individual equipment use behavioural characteristic.
In the present embodiment, be extracted 48 Intelligent mobile equipment usage behavior features from the occurrence frequency of the behaviors such as Intelligent mobile equipment screen on-off, phone, note, system service (use as Global Positioning System), wallpaper replacing, different types of third party application, and combine as the behavioural characteristic set of this individuality with the demographic information of individuality.The detailed content of characteristic set is as shown in table 4.
Table 4
Step 104, utilizes the method for machine learning, sets up the psychological health states assessment models based on Intelligent mobile equipment usage behavior feature.
In the present embodiment, adopt a kind of regression model PaceRegression to set up psychological health states assessment models, PaceRegression is a kind of basic linear regression algorithm, is used for the linear relationship set up between parameter and independent variable.
In the present embodiment, the Intelligent mobile equipment usage behavior feature of individuality is considered as the proper vector of sample by PaceRegression, the psychological health states score of individuality is considered as the successive value variable needing prediction, by corresponding machine learning training algorithm, draw psychological health states assessment models, the psychological health states of the individuality wherein needed for training is measured by measuring scale in advance and collects.In the present embodiment, employ Machine learning tools bag WEKA and set up psychological health states forecast model based on PaceRegression.
Step 105, is input to psychological health states assessment models by new individual Intelligent mobile equipment usage behavior feature, just can obtains its psychological health states assessment result.
By the psychological health states evaluation process based on Intelligent mobile equipment usage log that the application provides, its behavioural characteristic is extracted from the mobile device usage log of individuality, and the model of network behavior feature evaluation psychological health states is passed through with the method establishment of machine learning, assess new individual psychological health states with this.Thus avoid the impact of the subjective factor that tradition " questionnaire test " technology is brought, more convenient, accurately, objectively collect psychological health states assessment needed for individual data items, simultaneously, by means of the popularization of intelligent mobile terminal, large-scale individual data items collection can be carried out in wider scope, realize large-scale Mental health evaluation.
Wherein, said system and method can dispose or operate on intelligent movable equipment, and this intelligent movable equipment can comprise mobile communication terminal, mobile data terminal, portable set or portable game terminal.Include but not limited to equipment such as the trip of mobile phone, panel computer, hand equipment, personal digital assistant etc.
Finally it should be noted that, above embodiment is only in order to describe technical scheme of the present invention instead of to limit this technical method, the present invention can extend in application other amendment, change, application and embodiment, and therefore think that all such amendments, change, application, embodiment are all in spirit of the present invention and teachings.
Claims (11)
1., based on a psychological health states evaluating system for Intelligent mobile equipment usage behavior, comprising: information logging modle, behavior extraction module, assessment models set up module and and evaluation module; Wherein, information logging modle is for recording and store the use information of Intelligent mobile equipment; Behavior extraction module is used for carrying out data prediction to the device using information of record, extracts user and equipment carries out mutual effective equipment use behavior, excavating equipment usage behavior feature; Assessment models sets up module for obtaining contacting between Intelligent mobile equipment usage behavior feature and mental health state based on machine learning method, sets up the psychological health states assessment models based on Intelligent mobile equipment usage behavior feature; Evaluation module is used for the equipment use behavioural characteristic of excavation to be input to psychological health states assessment models, obtains psychological health states assessment result.
2. psychological health states evaluating system according to claim 1, wherein, the equipment use daily record of user, also for obtaining operating system authority, stores in local data base in an operating system by information logging modle.
3. psychological health states evaluating system according to claim 1, wherein, behavior extraction module also for combined with intelligent mobile device usage behavior index system, excavates the equipment use behavioural characteristic of user from the equipment use daily record of user; Wherein, the equipment use behavior of described user is based on Intelligent mobile equipment usage behavior system.
4. psychological health states evaluating system according to claim 1, wherein, assessment models is set up in module, described machine learning method is classification or homing method, described mental health state is the psychological health states of the individuality obtained by measuring scale measurement, and described psychological health states model is train by machine learning method the mathematical model obtained.
5. psychological health states evaluating system according to claim 1, wherein, behavior extraction module comprises data cleansing submodule and data transformation submodule; Wherein data cleansing submodule is for removing abnormal data in daily record, correcting a mistake, removing redundant data and standardization journal format; Data transformation submodule is used for by smoothly daily record is converted to the form being applicable to data mining by gathering, Data generalization and normalized mode.
6. psychological health states evaluating system according to claim 3, wherein, Intelligent mobile equipment usage behavior index system in behavior extraction module is the behavior collection according to describing user's Intelligent mobile equipment usage behavior, utilizes Intelligent mobile equipment to the overall process of the selection action scheme of the target and expectation of reaching oneself.
7., based on a psychological health states appraisal procedure for Intelligent mobile equipment usage behavior, comprising:
Step 1, the use information of record Intelligent mobile equipment;
Step 2, carries out data prediction to this use information, and combined with intelligent mobile device usage behavior index system, excavates corresponding equipment use behavioural characteristic;
Step 3, utilizes machine learning method, obtains contacting between Intelligent mobile equipment usage behavior feature and mental health state, sets up the psychological health states assessment models based on Intelligent mobile equipment usage behavior feature;
Step 4, is input to psychological health states assessment models by the equipment use behavioural characteristic excavated, obtains psychological health states assessment result.
8. psychological health states appraisal procedure according to claim 7, wherein, step 1 also comprises: the rights of using obtaining Intelligent mobile equipment operating system, the service condition of recording unit, and is written in local data base.
9. psychological health states appraisal procedure according to claim 7, wherein, in step 3, described machine learning method is classification or homing method, described mental health state is the psychological health states of the individuality obtained by measuring scale measurement, and described psychological health states model is train by machine learning method the mathematical model obtained.
10. psychological health states appraisal procedure according to claim 7, wherein, in step 2, the equipment use behavior of described user is based on Intelligent mobile equipment usage behavior system; Intelligent mobile equipment usage behavior index system is the behavior collection according to describing user's Intelligent mobile equipment usage behavior, utilizes Intelligent mobile equipment to the overall process of the selection action scheme of the target and expectation of reaching oneself.
11. psychological health states appraisal procedures according to claim 7, wherein, in step 3, regression model PaceRegression is adopted to set up psychological health states assessment models, the Intelligent mobile equipment usage behavior feature of individuality is considered as the proper vector of sample, the psychological health states score of individuality is considered as the successive value variable needing prediction, by corresponding machine learning training algorithm, draws psychological health states assessment models.
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| CN114098729B (en) * | 2020-08-27 | 2023-11-10 | 中国科学院心理研究所 | Heart interval-based emotion state objective measurement method |
| CN112951350A (en) * | 2021-02-02 | 2021-06-11 | 同济大学 | Behavior information-based college student psychological state assessment method |
| CN113793687A (en) * | 2021-09-27 | 2021-12-14 | 盐城师范学院 | Mental health dynamic management system and method |
| CN117257302A (en) * | 2023-09-20 | 2023-12-22 | 湖北万维科技发展有限责任公司 | Personnel mental health state assessment method and system |
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