CN110059232A - A kind of data visualization method based on user experience measurement - Google Patents
A kind of data visualization method based on user experience measurement Download PDFInfo
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- CN110059232A CN110059232A CN201910195684.8A CN201910195684A CN110059232A CN 110059232 A CN110059232 A CN 110059232A CN 201910195684 A CN201910195684 A CN 201910195684A CN 110059232 A CN110059232 A CN 110059232A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
- A61B3/113—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining or recording eye movement
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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
- A61B5/24—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]
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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
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9038—Presentation of query results
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
- G06F18/2135—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
Abstract
The invention discloses a kind of data visualization methods based on user experience measurement.The present invention establishes the measurement model of data visualization narration experience.It is proposed to be based on optokinetics and electrocardio research method, parallel nesting research method qualitative and the research method quantitatively combined.For proposition research method build by eye movement measurement and electrocardio measurement be integrated to data visualization narration example experimentation in, extract experience index quantized value, by experiment analysis results be applied to data visualization narration method optimization and improvement.The present invention can innovatively introduce electrocardio measure and eye movement measure for data visualization narrative research field, evade subjective error generally existing in traditional measure method by method that is qualitative and quantitatively combining.The space domain classification method based on factor analysis exploratory is proposed in eye movement tracking data analysis, provides the new method with more high accuracy for the interest region division that eye movement tracks data.
Description
Technical field
This research is related to a kind of data visualization method based on user experience measurement, belongs to information visualization field, energy
Enough theory and technology is provided for various fields interdisciplinary research such as data information propagation, user cognition behavioral studies to support.
Background technique
Affine understandable image, i.e. data visualization are converted by data set, is that the mankind see clearly data intension, understand
Data contain the important means of rule, can convert lengthy and jumbled data set to affine understandable image.Data visualization is comprehensive
The technologies such as computer graphics, image procossing, human-computer interaction have been used in conjunction, identifiable object are converted by data, to user
Valuable information is presented, to further obtain knowledge and wisdom, has important shadow to the data application development of information age
It rings.
The purpose of the present invention is the core concepts based on user experience based on ergonomics and can be used from user
Property principle, make data visualization product more meet audient habit.Although the research starting of user experience is more early, have many mature
Research achievement, but can not yet have with data visualization field it is good merge, to solve visual representation and interaction technique symbiosis
Data visualization interactive interface problem.Currently, for visualization visual representation field, user's vision is focused in research work more
Perception and cognition are lacked with foring some more authoritative design principles for distinct interaction skill in data visualisation system
Art promotes the systematic direction method and design principle of satisfaction of users especially by interaction design.Therefore, according to data
The self-characteristic of visualization system carries out optimization and improvement in user study method, improves the friendship in data visualisation system
Mutual design theory solves that key issues of how data are transmitted to the perception and understanding of spectators and people in interactive process seems
It is particularly important.Meanwhile the combination of data visualization and user experience research, it can help to solve current data visualization field
The problem of inside not meeting user demand and causing, for approach user in-mind anticipation data visualisation system design provide it is valuable
The guidance program of value is of great significance to Future Data visualization more fully development and in different field application.
Summary of the invention
This research is related to a kind of data visualization research for carrying out objective quantification to user experience based on physiological signal data
Method is introduced into field of human-computer interaction theoretical and model, and the objective quantification based on eye movement tracking data and physiological signal data
Method is evaluated in conjunction with subjective ego, carries out the measurement research of data visualization narration user experience, Develop Data visualization system
The researchs such as middle user interaction techniques, the building of user demand alienation, usability testing and Iterative Design, to optimize data visualization
Change narration model.To explore and push the data visualisation system of user to experience the in-mind anticipation of constantly approach user.The present invention
Technical solution used by its technical problem is solved to specifically comprise the following steps:
Step 1, the measurement model design of data visualization narration experience；
Step 2, eye movement test design；
Step 3, electrocardio experimental design；
Step 4 collects data based on parallel nesting hybrid method；
Step 5 carries out data analysis based on statistical method and visualization means；
Step 6, example process Optimized model derive.
In step 1, the quantization for lacking objective evaluation of measurement is experienced due to narrating outside Current Domestic data visualization
Data visualization of the objective quantification data in conjunction with traditional subjective matter data can be narrated and be experienced by data, design
Measurement model be very necessary.The basis of correlation and attribute of the present invention between analyzing user experience influence factor
On, according to the basic principle building data visualization narration experience measurement of the recursive hierarchy structures such as destination layer, solution layer, rule layer
Model.The model is specifically described as follows:
1. establishing the destination layer of model, target is exactly experience difference of being narrated according to evaluation index concentrated expression data visualization
The superiority and inferiority of level obtains the design method of the preferable data visualization narration application of user experience quality.
2. establishing the rule layer of model, rule layer is directed to user cognition and user experience, and wherein user experience includes sense organ
Experience, emotional experience, content experience, its corresponding sub- rule layer of the aspect of interactive experience four, and Consumer's Experience Measure Indexes with
It is corresponded to, composing indexes layer.
3. establishing the solution layer of model, solution layer is to carry out the corresponding method of user experience measurement.
Test assignment is set for user first in step 2, experiment.
It narrates for data visualization and experiences the target of measurement, the test being free to navigate through based on user is set, be only use
The fuzzy task object of family setting.It is free to navigate through by user in specific webpage region.
Experimental study must be set according to the complexity for the data visualization narration object self-information studied for user
Set the time restriction being free to navigate through.Method is the experiment duration of more several groups of testees by preliminary experiment, is executed with determining
Mission duration when experiment.
After being free to navigate through for task, asks user to carry out the entire navigation process that sound thinking looks back oneself, go forward side by side
Row user's interview, fills in the questionnaire of auxiliary, assists understanding cognitive assessment of user during task from qualitative angle,
Eye movement tracking data are supplemented in data analysis phase.Eye movement test detailed process is as follows:
2-1. determines research object, and research object is set as specific data according to the complexity that data visualization is narrated
Specific several chapters and sections in visualization narration；
2-2. proposes that experimental hypothesis, such as the present invention will be counted in the case where corresponding user experience measures model to research object
It is adopted according to the user experience quantitative study and the common method of the qualitative research of current data visualization narration experience of visualization narration
Be integrated with the method for parallel nesting, based on the data visualization narration example propose it is assumed hereinafter that:
From the angle of sensory experience:
H1: influence of the text with visualization two parts layout to user behavior symbolizes otherness；
H2: a variety of visualization views；
H3: legend influences user and learns to understand visual behavior；
H4: the influence of control distribution and its metaphor to user behavior embodies otherness.
From the angle of interactive experience:
H5: testee can quickly understand product structure, and find the correlation function of visualization narration.
From the angle of emotional experience:
H6: data visualization narration can be such that the mood of testee is invoked.
2-3. is divided based on the eye movement spatial domain of factor analysis exploratory, is convenient for later period extracted valid data feature.According to
The hot-zone figure (Heat Map) of eye movement data, experimental subjects is divided into advance several interest regions (Area of Interest,
AOI).9 regions AOI can be marked off according to hot-zone figure in experiment.Eye movement test in eye movement test is obtained in these AOI
Blinkpunkt duration, the measured value for watching 10 eye movement indexs such as duration summation, blinkpunkt number attentively.
Eye movement index has different measurement units, it is therefore desirable to first be standardized, then be classified as the inspection of interest region
Survey matrix.
It is examined by KMO, examines factorial analysis whether abundant, generally require test value KMO > 0.5.Bartlett is examined,
Examine whether population correlation coefficient matrix is unit battle array, to judge this group of data if appropriate for progress factorial analysis.
The modified likelihood ratio of Bartlett test statistics:
Wherein, n is the item number of data record, and p is the variables number of factorial analysis, and R is sample correlation matrix.
Using Principal Component Analysis identify common factor, data visualization narration technique classification method share 4 kinds it is public because
Son takes the m factor, factorial analysis principal component solution according to different research objects are as follows:
Wherein, the principal component factorial analysis of sample correlation matrix R is according to characteristic value-feature vector to (λi,ei), i=
1 ..., p and λ1≤λ2≤…≤λpIt is specified,For estimate factor loading matrix,For specific factor variance, S is covariance
Matrix,For factor loading of i-th of variable in j-th of factor.
It is the common factor number and indefinite of experiment case study setting in the case where having, it can be based on the fitting mould of different m
Type result is asked:
So that result is reached maximum is best factors number.
Several AOI of selection are classified according to the result that common factor is analyzed；
The orthogonal rotary process (Quartimax) of maximum biquadratic method is selected, this method can retain each variable in the factor
On have the overall factor of high load capacity so that the factor needed for explaining each variable is minimum, can satisfy this reality through examining
Test target.The postrotational factor still maintains independence, and twiddle iterative obtains rotation component matrix, ingredient therein to restraining
High several are selected as final AOI, are implemented as follows:
NoteFor the factor loading matrix of rotation, and enable:
Wherein, wherein whereinFor factor loading of i-th of variable in j-th of factor,For general character variance, V reaches
The rotation component matrix of available needs when maximum.
2-4. determines the quantity and characteristic information of measured, such as gender, age, education degree.According to user study
Correlation theory, before experiment, it is necessary to assure the target group being selected is suitble to this experiment.Due to the limitation of eye movement tracing equipment,
Whether the physiological condition for also needing to investigate subject meets requirement of experiment, and testee requires binocular vision normal, no astigmatism.
2-5. chooses suitable eye-movement measurement index, such as eye movement, blinkpunkt number, watches duration, user experience attentively
Be it is various, experiment should select to characterize the eye-movement measurement index for the user experience index measured every time.
2-6. executes test of eye movement, and test needs to be divided into pretest and executes two stages of test, and pretest is formal
Execute the problem of influence experiment is checked out in test.
2-7. pre-processes collected eye-movement measurement achievement data.In data preprocessing phase, usually using sliding
Dynamic mean filter carried out noise filtering.Mean filter is slided based on neighborhood averaging, by constantly taking being averaged in interval
Value replacement script sequential value cancelling noise, and the window size that the filter effect for sliding mean filter can be taken by it is influenced,
Window size is controlled 3 or so in the noise reduction of general eye movement data.In addition to noise, the case where there is also loss of data, adopt
Compensation data is carried out with more universal interpolation method.
Step 3, according to the short-term psychological signal detection duration of the studies have shown that of electrocardiosignal need five minutes with
On, therefore need to understand user's experimental conditions by preliminary experiment for the electrocardio experiment of data visualization narration, and by reality
Test the screening and processing control Therapy lasted duration of object.
Based on cardiac electrical experimental design specific steps are as follows:
3-1. sits quietly after five minutes, records the electrocardiosignal of testee's period, with this data as later data processing
Reference standard；
3-2. formally starts to test, using the time as journal ecg signal data.
3-3. takes every 5 minutes as one section of ecg signal data section after testing, each data segment passes through data processing
Show that one group of experimental data is compared with reference standard.
3-4. pre-processes collected ecg signal data using Wavelet Denoising Method, and Wavelet Denoising Method can effectively remove the heart
White noise in electric signal also has good effect for extracting the live part in skin electric signal.
Wavelet noise-eliminating method mainly includes following steps:
(1) wavelet transformation is carried out to initial data；
(2) by carrying out threshold process with cancelling noise；
(3) wavelet inverse transformation is carried out, required denoising data are obtained.
3-5. calculates separately its time domain, frequency domain and nonlinear indicator to pretreated ecg signal data.
Step 4, parallel nesting method are applied to the experience research of data visualization narration, are the solutions in order to increase data source
Degree of releasing is aided with the data of another normal form with a kind of data source of normal form, i.e., a kind of data is embedded into another data
Frame and structure in, be presented as in the present invention with quantitative eye movement tracking and electrocardiosignal research method, be aided with qualitatively
User's subjective evaluation method.Research step and eye movement, the electrocardiosignal characteristic of experiment of integrating parallel nesting research method of the present invention,
It is proposed the data visualization narration system user experience measurement method model based on parallel nesting, the specific steps are that:
4-1. helps to reject the exceptional value in quantitative collection data by qualitative research, such as some region eye movement tracks number
According to missing.It is that user's subjective desire is browsed without this region, or visualization is narrated by studying the reason of exceptional value occurs
It is omitted caused by deficiency, in that case it can be decided that whether reject the data or this group of data are included in statistical analysis.
4-2. passes through the screening of qualitative research assisted quantitative collecting sample.Such as having conspicuousness change before and after battery of tests
The HRV index of change compares with the Affect Scale collection result of user, will wherein meet Experimental Research user's active mood purpose
Sample, which selects, to be come.
4-3. is improved same in the accuracy that result is analyzed in quantitative study, such as eye movement tracking data analysis by qualitative research
One result may be as caused by different user cognitions, and watching attentively for a long time may be the suction narrated due to data visualization
Gravitation, it is also possible to which, since user is difficult to extract information, qualitative research auxiliary more accurately analyzes user cognition.
4-4. improves the precision that result is analyzed in quantitative study by qualitative research.It such as is positive for a group analysis result
The HRV quantized data that mood is aroused, but the general of HRV measurement index to be handled so that the above are one section within 5 minutes.By with user
Interview and sounding thinking look back can further probe into data visualization narration in user mood highest point it is more accurate when
Between.
Data analysis is carried out in step 5, based on statistical method and visualization means.It is tested for the hypothesis of proposition
Card, respectively analyzes several groups of experimental datas, obtains analysis result；
In step 6, based on the analysis results experiments it is assumed that and propose corresponding data visualization narration prioritization scheme, build
Vertical process optimization model.
The present invention is effective as follows:
The present invention establishes the experience measurement model of data visualization narration, using eye movement and electrocardiosignal to user behavior
Quantitative study is carried out, the space domain classification method based on factor analysis exploratory is innovatively proposed, can effectively extract user
Eye movement information；It is proposed that the data visualization narration system user based on parallel nesting experiences measure, efficiently integration acquisition
Quantized data and matter data；Data analysis is carried out using statistical method and method for visualizing, obtains several innovation results
And it is applied to the improvement of related data visualization narration method；It is proposed the vision data story exploitation design stream based on user feedback
Journey Optimized model provides corresponding guidance for the exploitation of vision data story.
Detailed description of the invention
The measurement model of Fig. 1 data visualization narration experience, is made of destination layer, rule layer, indicator layer and solution layer,
Connection in model between a upper level and next level is indicated by position；
The research method that Fig. 2 is tracked based on eye movement；
Research method of Fig. 3 based on electrocardiosignal；
Fig. 4 is based on parallel nesting hybrid and builds user experience measurement method model, wherein QUAN quantitative study, and QUAL is
Qualitative research；
Fig. 5 data visualization narration process optimization model schematic；
Specific embodiment
The embodiment of technical solution of the present invention is described in further detail with reference to the accompanying drawing.
1, as shown in Figure 1, on the basis of analyzing the correlation and attribute between user experience influence factor, according to target
The basic principle building data visualization narration experience measurement model of the recursive hierarchy structures such as layer, solution layer, rule layer；
2, as shown in Fig. 2, design eye movement tracks data metric user experience research method；
3, as shown in figure 3, design ecg signal data measure user experiences research method；
4, as shown in figure 4, building user experience measurement method model based on parallel nesting hybrid；
5, as shown in figure 5, the exploitation for establishing data visualization narration product designs a model.
Step 1, the measurement model design of data visualization narration experience；
Step 2, eye movement test design；
Step 3, electrocardio experimental design；
Step 4 collects data based on parallel nesting hybrid method；
Step 5 carries out data analysis based on statistical method and visualization means；
Step 6, example process Optimized model derive.
In step 1, the quantization for lacking objective evaluation of measurement is experienced due to narrating outside Current Domestic data visualization
Data visualization of the objective quantification data in conjunction with traditional subjective matter data can be narrated and be experienced by data, design
Measurement model be very necessary.The basis of correlation and attribute of the present invention between analyzing user experience influence factor
On, according to the basic principle building data visualization narration experience measurement of the recursive hierarchy structures such as destination layer, solution layer, rule layer
Model.The model is specifically described as follows:
1. establishing the destination layer of model, target is exactly experience difference of being narrated according to evaluation index concentrated expression data visualization
The superiority and inferiority of level obtains the design method of the preferable data visualization narration application of user experience quality.
2. establishing the rule layer of model, rule layer is directed to user cognition and user experience, and wherein user experience includes sense organ
Experience, emotional experience, content experience, its corresponding sub- rule layer of the aspect of interactive experience four, and Consumer's Experience Measure Indexes with
It is corresponded to, composing indexes layer.
3. establishing the solution layer of model, solution layer is to carry out the corresponding method of user experience measurement.
Test assignment is set for user first in step 2, experiment.
It narrates for data visualization and experiences the target of measurement, the test being free to navigate through based on user is set, be only use
The fuzzy task object of family setting.It is free to navigate through by user in specific webpage region.
Experimental study must be set according to the complexity for the data visualization narration object self-information studied for user
Set the time restriction being free to navigate through.Method is the experiment duration of more several groups of testees by preliminary experiment, is executed with determining
Mission duration when experiment.
After being free to navigate through for task, asks user to carry out the entire navigation process that sound thinking looks back oneself, go forward side by side
Row user's interview, fills in the questionnaire of auxiliary, assists understanding cognitive assessment of user during task from qualitative angle,
Eye movement tracking data are supplemented in data analysis phase.Eye movement test detailed process is as follows:
2-1. determines research object, and research object is set as specific data according to the complexity that data visualization is narrated
Specific several chapters and sections in visualization narration；The object of this experiment is data visualization narration website The Stories
Behind a Line；
2-2. proposes that experimental hypothesis, such as the present invention will be counted in the case where corresponding user experience measures model to research object
It is adopted according to the user experience quantitative study and the common method of the qualitative research of current data visualization narration experience of visualization narration
Be integrated with the method for parallel nesting, based on the data visualization narration example propose it is assumed hereinafter that:
From the angle of sensory experience:
H1: influence of the text with visualization two parts layout to user behavior symbolizes otherness；
H2: a variety of visualization views；
H3: legend influences user and learns to understand visual behavior；
H4: the influence of control distribution and its metaphor to user behavior embodies otherness.
From the angle of interactive experience:
H5: testee can quickly understand product structure, and find the correlation function of visualization narration.
From the angle of emotional experience:
H6: data visualization narration can be such that the mood of testee is invoked.
2-3. is divided based on the eye movement spatial domain of factor analysis exploratory, is convenient for later period extracted valid data feature.According to
The hot-zone figure (Heat Map) of eye movement data, experimental subjects is divided into advance several interest regions (Area of Interest,
AOI).9 regions AOI can be marked off according to hot-zone figure in experiment.Eye movement test in eye movement test is obtained in these AOI
Blinkpunkt duration, the measured value for watching 10 eye movement indexs such as duration summation, blinkpunkt number attentively.
Eye movement index has different measurement units, it is therefore desirable to first be standardized, then be classified as the inspection of interest region
Survey matrix.
It is examined by KMO, examines factorial analysis whether abundant, generally require test value KMO > 0.5.Bartlett is examined,
Examine whether population correlation coefficient matrix is unit battle array, to judge this group of data if appropriate for progress factorial analysis.
The modified likelihood ratio of Bartlett test statistics:
Wherein, n is the item number of data record, and p is the variables number of factorial analysis, and R is sample correlation matrix.
For inspection result as shown in following table 4.1, KMO value can carry out factorial analysis, Bartlett between 0.6 and 0.7
Test statistics is significant, shows that factor-analysis approach can be used effectively in this process.
Using Principal Component Analysis identify common factor, data visualization narration technique classification method share 4 kinds it is public because
Son takes the m factor, factorial analysis principal component solution according to different research objects are as follows:
Wherein, the principal component factorial analysis of sample correlation matrix R is according to characteristic value-feature vector to (λi,ei), i=
1 ..., p and λ1≤λ2≤…≤λpIt is specifiedFor estimate factor loading matrix,For specific factor variance, S is covariance square
Battle array,For factor loading of i-th of variable in j-th of factor.
It is the common factor number and indefinite of experiment case study setting in the case where having, it can be based on the fitting mould of different m
Type result is asked:
So that result is reached maximum is best factors number.
Several AOI of selection are classified according to the result that common factor is analyzed；
The orthogonal rotary process (Quartimax) of maximum biquadratic method is selected, this method can retain each variable in the factor
On have the overall factor of high load capacity so that the factor needed for explaining each variable is minimum, can satisfy this reality through examining
Test target.The postrotational factor still maintains independence, and twiddle iterative obtains rotation component matrix, ingredient therein to restraining
High several are selected as final AOI, are implemented as follows:
NoteFor the factor loading matrix of rotation, and enable:
Wherein, wherein whereinFor factor loading of i-th of variable in j-th of factor,For general character variance, V reaches
The rotation component matrix of available needs when maximum.
Note: AOI selected in final experiment marks *
2-4. determines the quantity and characteristic information of measured, such as gender, age, education degree.According to user study
Correlation theory, before experiment, it is necessary to assure the target group being selected is suitble to this experiment.Due to the limitation of eye movement tracing equipment,
Whether the physiological condition for also needing to investigate subject meets requirement of experiment, and testee requires binocular vision normal, no astigmatism.
2-5. chooses suitable eye-movement measurement index, such as eye movement, blinkpunkt number, watches duration, user experience attentively
Be it is various, experiment should select to characterize the eye-movement measurement index for the user experience index measured every time.
2-6. executes test of eye movement, and test needs to be divided into pretest and executes two stages of test, and pretest is formal
Execute the problem of influence experiment is checked out in test.
2-7. pre-processes collected eye-movement measurement achievement data.In data preprocessing phase, usually using sliding
Dynamic mean filter carried out noise filtering.Mean filter is slided based on neighborhood averaging, by constantly taking being averaged in interval
Value replacement script sequential value cancelling noise, and the window size that the filter effect for sliding mean filter can be taken by it is influenced,
Window size is controlled 3 or so in the noise reduction of general eye movement data.In addition to noise, the case where there is also loss of data, adopt
Compensation data is carried out with more universal interpolation method.
Step 3, according to the short-term psychological signal detection duration of the studies have shown that of electrocardiosignal need five minutes with
On, therefore need to understand user's experimental conditions by preliminary experiment for the electrocardio experiment of data visualization narration, and by reality
Test the screening and processing control Therapy lasted duration of object.
Based on cardiac electrical experimental design specific steps are as follows:
3-1. sits quietly after five minutes, records the electrocardiosignal of testee's period, with this data as later data processing
Reference standard；
3-2. formally starts to test, using the time as journal ecg signal data.
3-3. takes every 5 minutes as one section of ecg signal data section after testing, each data segment passes through data processing
Show that one group of experimental data is compared with reference standard.
3-4. pre-processes collected ecg signal data using Wavelet Denoising Method, and Wavelet Denoising Method can effectively remove the heart
White noise in electric signal also has good effect for extracting the live part in skin electric signal.
Wavelet noise-eliminating method mainly includes following steps:
(1) wavelet transformation is carried out to initial data；
(2) by carrying out threshold process with cancelling noise；
(3) wavelet inverse transformation is carried out, required denoising data are obtained.
3-5. calculates separately its time domain, frequency domain and nonlinear indicator to pretreated ecg signal data.
The present invention evaluates the impaired overall degree with recovery of autonomic nerves system using SDNN, and LF, LFnorm are sympathetic
Neural activity index, HF, HFnorm are parasympathetic nerve activity index, the C0 complexity of R -- R interval sequence and R wave crest value sequence
Degree then reflects the degree that cardiac sympathetic nerve and vagus nerve are adjusted mutually.To carry out user's feelings to selected electrocardiographicdata data
Feel the evaluation aroused, receive variance test in 5% significance, analysis result is as shown in the table:
As can be seen from the results, there are significant changes, SDNN experiments for this few associated frequency-domain index of class of LF, LFnorm, LF/HF
Front and back variation is also very significant.It can analyze and obtain according to the theoretical basis that electrocardiosignal generates:
1. sympathetic activity index LF and LFnorm
There is significant become in the sympathetic nerve that LF index is characterized activity in the navigation process of data visualization narration system
Change, LFnorm index significantly rises.It may determine that the case where user arouses there are emotion in reading process according to this group of data, and
The concrete reason for generating emotion variation then needs to determine by the interview with user.
2. parasympathetic nerve activity index HF and HFnorm
Experiment front and back user sends out HFnorm and is risen but change not significant, and HFnorm index can be by the shadow of LF index
It rings, is declined because of its rising, this is as a result, can be used for supporting a upper conclusion.
3. sympathetic/parasympathetic balanced index LF/HF
Since this group of numerical value ascendant trend is obvious in sympathetic activity increase experiment.
Step 4, parallel nesting method are applied to the experience research of data visualization narration, are the solutions in order to increase data source
Degree of releasing is aided with the data of another normal form with a kind of data source of normal form, i.e., a kind of data is embedded into another data
Frame and structure in, be presented as in the present invention with quantitative eye movement tracking and electrocardiosignal research method, be aided with qualitatively
User's subjective evaluation method.Quantitative data collection is carried out using parallel nesting hybrid method, the user's body established according to this method
Measure model is tested as shown in figure 4, having eye movement to track data, the heart to carry out quantitative data collection in data acquisition phase
Electric HRV data, interaction statistics amount etc., qualitative data are adopted by the methods of literature reading, the interview of user's questionnaire, generation thinking
Collection, specific implementation step are as follows:
4-1. helps to reject the exceptional value in quantitative collection data by qualitative research, such as some region eye movement tracks number
According to missing.It is that user's subjective desire is browsed without this region, or visualization is narrated by studying the reason of exceptional value occurs
It is omitted caused by deficiency, in that case it can be decided that whether reject the data or this group of data are included in statistical analysis.
4-2. passes through the screening of qualitative research assisted quantitative collecting sample.Such as having conspicuousness change before and after battery of tests
The HRV index of change compares with the Affect Scale collection result of user, will wherein meet Experimental Research user's active mood purpose
Sample, which selects, to be come.
4-3. is improved same in the accuracy that result is analyzed in quantitative study, such as eye movement tracking data analysis by qualitative research
One result may be as caused by different user cognitions, and watching attentively for a long time may be the suction narrated due to data visualization
Gravitation, it is also possible to which, since user is difficult to extract information, qualitative research auxiliary more accurately analyzes user cognition.
4-4. improves the precision that result is analyzed in quantitative study by qualitative research.It such as is positive for a group analysis result
The HRV quantized data that mood is aroused, but the general of HRV measurement index to be handled so that the above are one section within 5 minutes.By with user
Interview and sounding thinking look back can further probe into data visualization narration in user mood highest point it is more accurate when
Between.
Data analysis is carried out in step 5, based on statistical method and visualization means.It is tested for the hypothesis of proposition
Card, respectively analyzes several groups of experimental datas, obtains analysis result；Following groups experimental data is analyzed respectively, and
It is proposed corresponding prioritization scheme:
1) text and visualization are to user behavior impact analysis
2) different visualization formulations are to user behavior impact analysis
3) correlation analysis of legend and visualization learnability
4) impact analysis of control distribution and its metaphor to user behavior
5) system arouses analysis to user emotion
6) system ease for use is to user behavior impact analysis
In step 6, based on the analysis results experiments it is assumed that and propose corresponding data visualization narration prioritization scheme, build
Vertical process optimization model.Specific Optimized model schematic diagram is as shown in Figure 5.
In conclusion the present invention establishes the experience measurement model of data visualization narration, using eye movement and electrocardiosignal
Quantitative study is carried out to user behavior, innovatively proposes the space domain classification method based on factor analysis exploratory, Ke Yiyou
Effect extracts user's eye movement information；It is proposed that the data visualization narration system user based on parallel nesting experiences measure, efficiently
The quantized data and matter data of ground integration acquisition；Data analysis is carried out using statistical method and method for visualizing, if obtaining
Dry innovation result and the improvement for being applied to related data visualization narration method；It is proposed the vision data story based on user feedback
Design cycle Optimized model is developed, provides corresponding guidance for the exploitation of vision data story.
Finally, it should be noted that the foregoing is only a preferred embodiment of the present invention, it is not intended to restrict the invention,
While in accordance with previous embodiment, invention is explained in detail, for those skilled in the art, still can be with
It modifies to technical solution documented by previous embodiment or equivalent replacement of some of the technical features.It is all
Within the spirit and principles in the present invention, any modification, equivalent replacement, improvement and so on should be included in protection of the invention
Within the scope of.
The foregoing describe basic principles and main features of the invention and advantages of the present invention.Industry technical staff answers
The understanding, the present invention is not limited to the above embodiments, and the above embodiments and description only describe of the invention
Principle, without departing from the spirit and scope of the present invention, various changes and improvements may be made to the invention, these change and change
Into all fall within the protetion scope of the claimed invention.
Claims (4)
1. a kind of data visualization method based on user experience measurement, it is characterised in that include the following steps:
Step 1, the measurement model design of data visualization narration experience；
Step 2, eye movement test design；
Step 3, electrocardio experimental design；
Step 4 collects data based on parallel nesting hybrid method；
Step 5 carries out data analysis based on statistical method and visualization means；It is verified for the hypothesis of proposition, respectively
Several groups of experimental datas are analyzed, obtain analysis result；
Step 6, example process Optimized model derive, and experiments are it is assumed that and propose that corresponding data visualizes based on the analysis results
Narration prioritization scheme, Establishing process Optimized model；
Step 1 is implemented as follows:
On the basis of analyzing the correlation and attribute between user experience influence factor, according to destination layer, solution layer, rule layer
The basic principle building data visualization narration experience measurement model model of equal recursive hierarchy structures is specifically described as follows:
(1) establish the destination layer of model: target is experience different level of being narrated according to evaluation index concentrated expression data visualization
Superiority and inferiority obtains the design method of the preferable data visualization narration application of user experience quality；
(2) establish the rule layer of model: rule layer is directed to user cognition and user experience, wherein user experience include sensory experience,
Emotional experience, content experience, its corresponding sub- rule layer of four aspects of interactive experience, and Consumer's Experience Measure Indexes are right with it
It answers, composing indexes layer；
(3) establish the solution layer of model: solution layer is to carry out the corresponding method of user experience measurement.
2. a kind of data visualization method based on user experience measurement according to claim 1, it is characterised in that step 2
Test assignment is set for user first in the experiment, is implemented as follows:
It narrates for data visualization and experiences the target of measurement, the test being free to navigate through based on user is set；By preliminary experiment,
The experiment duration of more several groups of testees, to determine mission duration when executing experiment；Terminate in being free to navigate through for task
Afterwards, user carries out sound thinking and looks back entire navigation process, and carries out user's interview while filling in the questionnaire of auxiliary, from calmly
Property angle auxiliary understand cognitive assessment of user during task, eye movement tracking data are mended in data analysis phase
It fills；
Eye movement test detailed process is as follows:
2-1. determines research object: it is visual that research object is set as specific data according to the complexity of data visualization narration
Change specific several chapters and sections in narration；
2-2. proposes experimental hypothesis to research object:
It, can by the user experience quantitative study of data visualization narration and current data in the case where corresponding user experience measures model
Common method depending on changing the qualitative research of narration experience is integrated using parallel nested method, is narrated based on the data visualization
Example propose it is assumed hereinafter that:
From the angle of sensory experience:
H1: influence of the text with visualization two parts layout to user behavior symbolizes otherness；
H2: a variety of visualization views；
H3: legend influences user and learns to understand visual behavior；
H4: the influence of control distribution and its metaphor to user behavior embodies otherness；
From the angle of interactive experience:
H5: testee can quickly understand product structure, and find the correlation function of visualization narration；
From the angle of emotional experience:
H6: data visualization narration can be such that the mood of testee is invoked；
2-3. is divided based on the eye movement spatial domain of factor analysis exploratory:
(1), according to the hot-zone figure of eye movement data, experimental subjects is divided into several interest regions AOI in advance；It will be obtained in eye movement test
The eye movement index of these AOI measured value, including the blinkpunkt duration, watch duration summation, blinkpunkt number attentively；Due to eye
Dynamic index has different measurement units, it is therefore desirable to first be standardized, then be classified as interest region detection matrix；
(2) examined by KMO, examine factorial analysis whether abundant, need test value KMO > 0.5；
Bartlett examine, examine population correlation coefficient matrix whether be unit battle array, with judge this group of data if appropriate for into
Row factorial analysis, the modified likelihood ratio of Bartlett test statistics:
Wherein, n is the item number of data record, and p is the variables number of factorial analysis, and R is sample correlation matrix；
(4) common factor is identified using Principal Component Analysis, data visualization narration technique classification method shares 4 kinds of common factors,
The m factor, factorial analysis principal component solution are taken according to different research objects are as follows:
Wherein, the principal component factorial analysis of sample correlation matrix R is according to characteristic value-feature vector to (λi,ei), i=1 ..., p
And λ1≤λ2≤…≤λp, specifyFor estimate factor loading matrix,For specific factor variance, S is covariance matrix,For
Factor loading of i-th of variable in j-th of factor；
Model of fit result based on different m is asked:
So that result is reached maximum is best factors number；
Several AOI of selection are classified according to the result that common factor is analyzed；
(5) select the orthogonal rotary process of maximum biquadratic method to obtain rotation component matrix, high several of ingredient therein are selected as final
AOI, be implemented as follows:
NoteFor the factor loading matrix of rotation, and enable:
Wherein, whereinFor factor loading of i-th of variable in j-th of factor,It can be with for general character variance, when V reaches maximum
The rotation component matrix needed；
2-4. determines the quantity and characteristic information of measured, and characteristic information includes gender, age, education degree, while requiring quilt
The physiological condition of survey person meets the requirements, i.e., binocular vision is normal, no astigmatism；
2-5. chooses eye-movement measurement index, and eye-movement measurement index includes eye movement, blinkpunkt number, watches duration attentively；According to every
Secondary requirement of experiment selection can characterize the eye-movement measurement index for the user experience index measured；
2-6. executes test of eye movement, and test needs to be divided into pretest and executes two stages of test, and pretest is formal execution
The problem of influence experiment, is checked out in test；
2-7. pre-processes collected eye-movement measurement achievement data, carrys out noise filtering using sliding mean filter, and adopt
Compensation data is carried out with interpolation method.
3. a kind of data visualization method based on user experience measurement according to claim 2, it is characterised in that step 3
Based on cardiac electrical experimental design, specific step is as follows::
3-1. sits quietly after five minutes, records the electrocardiosignal of testee's period, is used as later data with this ecg signal data
Handle reference standard；
3-2. formally starts to test, using the time as journal ecg signal data；
3-3. takes every 5 minutes as one section of ecg signal data section after testing, each data segment is obtained by data processing
One group of experimental data is compared with reference standard；
3-4. pre-processes collected ecg signal data using Wavelet Denoising Method；
3-5. calculates separately its time domain, frequency domain and nonlinear indicator to pretreated ecg signal data.
4. a kind of data visualization method based on user experience measurement according to claim 3, it is characterised in that step 4
It is implemented as follows:
Research step and eye movement, the electrocardiosignal characteristic of experiment of integrating parallel nesting research method are proposed based on parallel nesting
Data visualization narration system user experience measurement method model, the specific steps are that:
4-1. helps to reject the exceptional value in quantitative collection data, and the original occurred by research exceptional value by qualitative research
Cause decides whether to reject the data or this group of data is included in statistical analysis；
4-2. passes through the screening of qualitative research assisted quantitative collecting sample；
4-3. improves the accuracy that result is analyzed in quantitative study by qualitative research, and eye movement tracks the same result in data analysis
It may be as caused by different user cognitions, watching attentively for a long time may be the attraction narrated due to data visualization,
It may be since user is difficult to extract information, qualitative research auxiliary more accurately analyzes user cognition；
4-4. improves the precision that result is analyzed in quantitative study by qualitative research.
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