CN107440688A - Based on systolic pressure and the vision of pulse frequency power spectrum induction motion sickness detection method - Google Patents
Based on systolic pressure and the vision of pulse frequency power spectrum induction motion sickness detection method Download PDFInfo
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Abstract
The invention discloses a kind of based on systolic pressure and the vision of pulse frequency power spectrum induction motion sickness detection method, user is gathered respectively first in normal phase and the systolic pressure signal and pulse rate signals of detection-phase, the power spectrum of each signal is calculated, then the standard deviation of each power spectrum is calculated again, the relative deviation of two systolic pressure power spectrum standard deviations of calculating and the relative deviation of two pulse frequency power spectrum standard deviations respectively, when there is standard deviation decline compared with normal phase in detection-phase, there is vision induction motion sickness phenomenon in judgement, so as to realize the detection of vision induction motion sickness.
Description
Technical field
The invention belongs to stereo display technique field, more specifically, is related to one kind and is based on systolic pressure and pulse frequency work(
The vision induction motion sickness detection method of rate spectrum.
Background technology
In recent years, the fast development of Display Technique causes increasing people constantly to touch brand-new display environment,
Such as high-resolution and the wide-screen television of strong depth correlation, naked-eye 3 D television and used in virtual reality and game
Head mounted display.In addition, with the development of Video processing and computer graphics techniques, occur substantial amounts of comprising complexity
And the novel image that frequently viewpoint is moved, and these are that traditional camera technique institute is irrealizable.The development of these technologies
With utilization so that image is no longer limited only in the plane of display, but embodies the depth perception of image, stereovision, true
The display distribution situation of true feeling and image, picture is become three-dimensional true to nature, brought the unprecedented viewing body of spectators people
Test.At the same time, with the continuous development of these technologies with ripe, stereo display technique is in modern medical service, military and national defense, education
Many fields such as teaching, smart home also obtain huge utilization and popularization.
Advanced Display Technique largely advances it in every field because of its strong third dimension and feeling of immersion
Using with development, but there is also it is certain the drawbacks of, most distinct issues are exactly during viewing often to trigger vision to induce
Motion sickness (visually induced motion sickness, VIMS), including visual fatigue, eye-blurred, diplopia, evil
The symptoms such as the heart, vomiting, dizziness, these all serious threats the health of people, while also counteracts that Display Technique enters one
Step development and popularization.In order to reduce risk caused by vision induction motion sickness, it is necessary to which analysis causes vision to induce motion sickness
Factor and condition.And in order to realize this purpose, it is necessary to which motion sickness can be induced with qualitative assessment vision by mousing out one kind first
The method of influence.In terms of vision induces motion sickness appraisal procedure, the method for more main flow is subjective analysis method and subjective and objective phase
With reference to analytic approach.
Subjective analysis method be exactly subject in experimentation, according to simulation motion sickness questionnaire (Simulator
Sickness Question, SSQ) in the problem of and partition of the level answer, to complete the assessment to itself cinetosis rank.It is early
In nineteen sixty-five, Kellogg et al. has invented motion sickness questionnaire (Motion Sickness Questionnaire, MSQ) to study
Motion sickness, initial motion sickness questionnaire generally include 25-30 symptoms relevant with motion sickness, for each symptom, each
Subject will provide according to own situation can reflect that the grade of the severity of symptom is assessed, corresponding 0 grade when generally asymptomatic,
It is corresponding highest during symptom most serious.Afterwards, on MSQ basis, Frank et al. investigated simulation motion sickness questionnaire.
The content that the symptom and motion sickness questionnaire table that simulation motion sickness questionnaire table is included are included is different, relates generally to eye
Ball motion (Oculomotor), direction obstacle (Disorientation) and nauseous (Nausea) three aspects.
Many experts and scholars are made that effective assessment to motion sickness using this subjective analysis method, but subjective analysis method is true
Have the following disadvantages in fact：
1. use subjective analysis method, the classification for each symptom is limited, it is difficult to refine；
2. subjective analysis method is frequently in, experiment is front and rear to be carried out, it is difficult to measure in an experiment, thus its accuracy compared with
It is low；
3. involved symptom may form certain induction even misleading effect to subject in questionnaire, and then cause
Subject can not reflect the situation of itself vividly.
Therefore, it is not that a kind of ideal vision induces motion sickness appraisal procedure using single subjective analysis method.
Many scholars introduce objective physiological data on the basis of subjective analysis method, using the subjective and objective analysis side being combined come
VIMS is assessed.
There are some researches show, clectrogastrogram (Electrogastrogram, EGG), electrocardiogram (Electrocardiogram,
ECG), salivary cortisol rank (Salivary cortisol level), blood pressure (Blood pressure, BP), pulse frequency
(Pulse rate, PR) and electroencephalogram (Electroencephalogram, EEG) etc. can serve as VIMS evaluation index.
Meanwhile blood pressure (Blood pressure, BP), heart rate (Heart rate, HR), pulse frequency (Pulse rate, PR) are used as body
Now with reflection body heath most basic physiological parameter, be physical condition important physical signs, also result in many
The concern of scholar, they attempt to analyze VIMS based on blood pressure, heart rate, pulse frequency and studied.
Graybiel et al. research finds that blood pressure and heart rate do not change with subjective cinetosis change of rank.However, Lin
Et al. research find, blood pressure and changes in heart rate and subjective cinetosis degree are closely related.N.Sugita et al. proposes blood pressure and heart rate
Between dependency relation can reflect well vision induction motion sickness caused by physiological effect.When cinetosis shape occurs in subject
During state, blood pressure and changes in heart rate correlation reduce.Sayers et al. has found by carrying out analysis to the power spectrum of heart rate, heart rate
Increase and the suppression of parasympathetic activity and the lifting of sympathetic nerve activity have close relationship.Heart rate power spectrum it is low
What frequency range (0.04Hz-0.15Hz) reflected is the fluctuation for the sympathetic innervation for maintaining blood pressure balance, and the height of heart rate power spectrum
Frequent section (0.15-0.5Hz) reflection is regulation and control of the parasympathetic to cardiac stimulation.Research based on forefathers,
Sharon et al. proposes a kind of VIMS appraisal procedures based on heart rate power spectrum.
The vision induction motion sickness detection method for being currently based on blood pressure and pulse rate is individually to blood pressure and pulse rate mostly
Assessed, also do not consider power spectrum even if least a portion of comprehensive analysis, only heart rate is carried out at present in terms of power spectrumanalysis
Analysis.
The content of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of based on systolic pressure and pulse frequency power spectrum
Vision induces motion sickness detection method, and detection signal is obtained by analyzing the standard deviation of systolic pressure and pulse frequency power spectrum, real
The detection of existing vision induction motion sickness.
For achieving the above object, the present invention is based on systolic pressure and the induction motion sickness detection of the vision of pulse frequency power spectrum
Method comprises the following steps：
S1：Systolic pressure data of the user in normal phase (stereoscopic vision equipment is not used) are gathered respectivelyPulse frequency
DataWith the systolic pressure data of detection-phase (using in stereoscopic vision device procedures)Pulse rate data
S2：Systolic pressure data are calculatedPower spectrumAnd pulse rate data Power spectrum
S3：4 power spectrum are calculated respectivelyStandard deviation
S4：The relative deviation of two pairs of power spectrum standard deviations is calculated respectively Such as
Fruit ΔSYSLess than predetermined threshold value THSYS、ΔPRLess than predetermined threshold value THPRAny one situation meets in two kinds of situations, then judging should
There is vision induction motion sickness phenomenon in detection-phase in user, does not otherwise occur.
The present invention is based on systolic pressure and the vision of pulse frequency power spectrum induction motion sickness detection method, and collection is used respectively first
The power spectrum of each data is calculated, then in normal phase and the systolic pressure data and pulse rate data of detection-phase in family
The standard deviation of each power spectrum is calculated again, calculates the relative deviation and two pulse frequencies of two systolic pressure power spectrum standard deviations respectively
The relative deviation of power spectrum standard deviation, when detection-phase standard deviation decline occurs compared with normal phase, there is vision induction in judgement
Motion sickness phenomenon, so as to realize the detection of vision induction motion sickness.
Brief description of the drawings
Fig. 1 is the embodiment stream based on systolic pressure and the vision of pulse frequency power spectrum induction motion sickness detection method
Cheng Tu；
Fig. 2 is the wireless blood pressure wrist detector schematic diagrames of i-Health；
Fig. 3 is the active automobile driving simulator picture based on virtual reality；
Fig. 4 is subjective VIMSL variation diagram of the subject in experimentation；
Fig. 5 is the exemplary plot of wherein one subject data cubic spline interpolation in the present embodiment；
Fig. 6 is the power spectrum schematic diagram in the present embodiment；
Fig. 7 is the systolic pressure power spectrum standard deviation comparison diagram of normal phase and detection-phase in the present embodiment；
Fig. 8 is the pulse frequency power spectrum standard deviation comparison diagram of normal phase and detection-phase in the present embodiment.
Embodiment
The embodiment of the present invention is described below in conjunction with the accompanying drawings, so as to those skilled in the art preferably
Understand the present invention.Requiring particular attention is that in the following description, when known function and the detailed description of design perhaps
When can desalinate the main contents of the present invention, these descriptions will be ignored herein.
Embodiment
Fig. 1 is the embodiment stream based on systolic pressure and the vision of pulse frequency power spectrum induction motion sickness detection method
Cheng Tu.As shown in figure 1, the present invention induces motion sickness detection method including following based on systolic pressure and the vision of pulse frequency power spectrum
Step：
S101：Gather systolic pressure and pulse rate data：
Systolic pressure data of the user in normal phase (stereoscopic vision equipment is not used) are gathered respectivelyPulse rate dataWith the systolic pressure data of detection-phase (using in stereoscopic vision device procedures)Pulse rate data
Limited by acquisition means, generally occur during collection data volume is smaller, time interval not etc. phenomena such as, therefore right
Before data carry out further calculating analysis, first data can be pre-processed.The preprocess method used in the present embodiment
For interpolation and resampling.
Interpolation is the interpolation continuous function on the basis of discrete data so that this full curve by all it is given from
Dissipate data point.Interpolation is the important method that discrete function approaches, using it can be by function at limited individual point value situation,
Estimate approximation of the function at other points.Cubic spline interpolation is used in the present embodiment.Cubic spline interpolation (Cubic
Spline Interpolation, abbreviation Spline interpolation) it is by an a series of smooth curve of shape value points, mathematically lead to
Cross the process that three moments euqation group draws curvilinear function group that solves.Cubic spline interpolation have preferable convergence, stability and
Slickness.Cubic spline interpolation is the common method of data processing field, and its specific method will not be repeated here.Resampling is exactly
Data after cubic spline interpolation are sampled.
S102：Calculate power spectrum：
Systolic pressure data are calculatedPower spectrumAnd pulse rate data
Power spectrum
Because data involved in the present invention are random signal train, and random signal is lacking beginning and end in time
, possessed energy is also unlimited, it is impossible to carry out Fourier transformation to it, but its power be it is limited,
Thus its frequency domain character can be described using the spectral characteristic of this statistical average of power spectrum.It should be understood that if
Stationary random process statistical property is calculated, then requires random signal endless, and this is that impossible realize in actually calculating
, so need to choose time-limited sequence as sample to be calculated, therefore obtained result of calculation is to random signal
Estimate, be not the real statistical value of random signal.
Power spectral density (Power Spectral Density, PSD), signal power is defined in per unit band with frequency
Situation of change, abbreviation power spectrum.A kind of more classical definition of power Spectral Estimation (Power spectrum estimation)
Method is to define spectrum density, this method with the Fourier transformation (Fourier transform) of the finite time of random process
By the N point observed data X of stationary random signal sequence X (n)N(n) it is considered as the signal of finite energy, and by XN(n) estimate X's (n)
Power spectrum, its specific method of estimation be --- calculate XN(n) Fourier transformation XN(k), then square of its amplitude is taken, and divided by
Data length N, this method are referred to as period map method (Periodogram method).This method is just comparable to endless
Sequence be subject to rectangular window, be allowed to be changed into time-limited data, data length N too conferences increase the fluctuating of spectral curve, and data
Length N is too small and the resolution ratio of frequency spectrum can be caused to decline.For this situation, a kind of data X that it is N length that improved though, which is,
(n) it is divided into L sections, obtains every section of power spectrum respectively, be then averaged.Wherein preferable improved method is Welch methods, also known as
To weight the overlapping method of average.It has done following improvement again under above-mentioned thought：When being segmented to sequence X (n), it is allowed to per segment data
There is part overlapping；The window function of other better performances can be selected per segment data, rectangular window is not necessarily, can so improve square
Spectrum distortion caused by shape window.The specific method of the overlapping method of average of weighting is：
Note data length is N, by data xN(n) it is divided into L sections, is M per segment length, seeks each section of power spectrum respectively
In formula, f expression frequencies, i=1,2 ..., L,It is normalization factor, ensure that what is obtained
Spectrum is progressive unbiased esti-mator；D (n) is selected windowed function.It is that the windowing portion of signal is entered
Fourier transformation is gone.
Obtained power spectrum is segmented to L to be averaged, what is obtained is the power Spectral Estimation of whole signal：
It can be seen from Probability Statistics Theory, the variance of the power spectrum estimated by the above method is about period map method estimation
1/L times of the variance of the power spectrum gone out.Random signal segmentation is more, and L is bigger, and variance is then smaller, but L increases can cause signal
The resolution ratio of frequency spectrum declines.So to consider requirement of the signal to variance and spectral resolution simultaneously in actual use, choose
Appropriate L and M values.
The present embodiment is exactly calculated when calculating power spectrum using Welch methods.For the On The Choice of window function,
It has been investigated that the analysis for random signal, more using Hanning window, hamming window or Brackman window.These three window functions exist
Main lobe widen it is less in the case of, the effectively height of suppressed sidelobes, improve power leakage problem to a certain extent.And hamming window
It is improved raised cosine window, further improvement has been done on the basis of Hanning window, employs more excellent weight coefficient, add main lobe
Width, secondary lobe reach minimum, are a kind of good window functions of performance.Therefore window function uses hamming window in the present embodiment.
S103：Calculate the standard deviation of power spectrum：
4 power spectrum are calculated respectivelyStandard deviation
VIMS can trigger various physiological activities, and then trigger sympathetic nerve and parasympathetic movable change, shrink
Pressure and pulse frequency can also reflect physiological effect caused by VIMS.And the present invention it has been investigated that, the mark of systolic pressure power spectrum
Quasi- difference and the standard deviation of pulse frequency power spectrum can decline to a certain extent, show physiology system caused by vision induction motion sickness
System fluctuation can be affected, that is to say, that due to the effect of environmental stimuli, the control of sympathetic nerve and parasympathetic nerve to human body
Effect may change.Therefore the present invention is come from the standard deviation of systolic pressure power spectrum and the standard deviation of pulse frequency power spectrum
Carry out the detection of vision induction motion sickness phenomenon.
S104：Vision induction motion sickness detection：
The relative deviation of two pairs of power spectrum standard deviations is calculated respectively Such as
Fruit ΔSYSLess than predetermined threshold value THSYS、ΔPRLess than predetermined threshold value THPRAny one situation meets in two kinds of situations, then judging should
There is vision induction motion sickness phenomenon in detection-phase in user, does not otherwise occur.
During due to vision induction motion sickness occurs, the standard deviation of systolic pressure power spectrum and the standard deviation meeting of pulse frequency power spectrum
Decline, it is clear that ideal situation lower threshold value THSYSAnd THPRValue be 1, but because detection signal during actually detected may
Fluctuate, therefore typically by threshold value THSYSAnd THPRSpan be arranged to 0.85≤THSYS≤ 0.95,0.85≤THPR≤
0.95, occurrence can determine according to actual conditions.
In order to which the technique effect of the present invention is better described, the present invention test using a concrete scene
Card.
It has chosen 10 subjects, wherein women 5 in the present embodiment, male 5, myope 4 in 10 subjects.
Every subject carries out 1 experimental data collection, obtains 10 groups of experimental datas altogether.
I-Health wireless blood pressure wrist detectors gather systolic pressure data and pulse rate data in the present embodiment.Fig. 2
It is the wireless blood pressure wrist detector schematic diagrames of i-Health.As shown in Fig. 2 the detector is (logical by bluetooth connection to logger
It is often smart mobile phone), the detector takes around and could obtain within 40 seconds single blood pressure and pulse rate reading (including cuff is swollen
Swollen and contraction), the pressure limit that the arm band of the equipment can provide is 0-300mmHg, and the scope of measurable systolic pressure is 60-
269mmHg, the scope for the diastolic pressure that can be measured is 40-199mmHg, and the pulse frequency that can be measured is 40-180bpm；Measure blood
Error range during pressure is ± 3mmHg, and the error range of measurement pulse frequency speed is ± 5%.
The stereoscopic vision equipment used in the present embodiment is the active automobile driving simulator based on virtual reality
(Vehicle Driving Simulator, VDS), it is made up of a driver's cabin moved and 220 ° of scene projection screen.Due to
VR technologies can bring subject's third dimension and feeling of immersion, and inducing subject easily by visual stimulus in driving procedure produces
Vision induces motion sickness.Fig. 3 is the active automobile driving simulator picture based on virtual reality.By experiment it is known that
10 subjects in this experiment are when driving the active automobile driving simulator in the presence of different degrees of cinetosis sense.
Flow will be driven in this experiment and is divided into following three phases：
1) baseline period：Subject does not drive a car, eye opening standing 3min, eye closing standing 3min, and subject keeps left arm
Bend to heart to be highly used to measure blood pressure and pulse rate data, this stage, VIMS symptoms did not occur in subject；
2) the VIMS stages：Subject drives a car on the road of a bending, and this can trigger subject to produce VIMS, and
And as the increase of driving time, the cinetosis of subject strengthen, therefore the actual cinetosis shape for driving duration according to subject individual
State can change in a few minutes between more than 30 minutes；
3) rest period：Subject stops driving and rested, eye opening standing 3min, eye closing standing 3min, in this single order
The cinetosis sense of section subject is retarded, still needs to continue to measure blood pressure and pulse rate data in this process, until subject recovers
To not cinetosis state.
In entirely flow is driven, subject needs verbal report per minute once subjective vision induction motion sickness rank
(VIMS Level, VIMSL), VIMSL is divided into five ranks in this experiment：Non- cinetosis (0 grade), slight cinetosis (1 grade),
Moderate cinetosis (2 grades), serious cinetosis (3 grades) and excessive cinetosis (4 grades).Fig. 4 is subjective VIMSL of the subject in experimentation
Variation diagram.As shown in figure 4, when switching between different driving phases it is possible that a bit of interval, such as A, B, C and D in figure
It is shown.
For the systolic pressure (SYS) of every group of normal phase collected (baseline period) and detection-phase (VIMS stages) number
According to, pulse frequency (PR) data, cubic spline interpolation is carried out according to time interval Δ t=0.5s.Fig. 5 is wherein one in the present embodiment
The exemplary plot of name subject data cubic spline interpolation.As shown in figure 5, " star " point represents the data that acquired original arrives respectively,
And each bar curve presented in Fig. 5 is then that the result after cubic spline interpolation is used according to initial data.Observing each bar curve can
To find out, the data after interpolation have all been fitted to the data that acquired original arrives, and both variation tendencies are consistent, curvilinear motion
More gentle, interpolation is good.
Then the data data of interpolation obtained with time interval Δ t=1s progress resamplings, then carry out power spectrum and estimate
Meter, obtains power spectrum.Hamming window is used in the present embodiment, the size M of window function value is 512, i.e. the length per small segment data
Spend for 512, that is, systolic pressure data and pulse rate data are divided into the segment that length is 4min.So for the number of each segment
, then can be to asking for its power spectrum per a bit of according to can be regarded as stable data, and then obtain the power spectrum of whole data.Figure
6 be the power spectrum schematic diagram in the present embodiment.Because the power spectral value tried to achieve is larger, so shown in Fig. 6 being to power spectral value
Result after taking the logarithm (unit of systolic pressure power spectrum and pulse frequency power spectrum is respectively mmHg^2/Hz, bpm^2/Hz).
10 groups of experimental datas of 10 subjects are calculated in this experiment in normal phase (baseline period) and detection rank
The systolic pressure power spectrum standard deviation and pulse frequency power spectrum standard deviation of section (VIMS stages).Fig. 7 is normal phase in the present embodiment
With the systolic pressure power spectrum standard deviation comparison diagram of detection-phase.Fig. 8 is the pulse of normal phase and detection-phase in the present embodiment
Rate power spectrum standard deviation comparison diagram.As shown in Figure 7 and Figure 8, abscissa represents the systolic pressure work(under normal phase (baseline period)
Rate composes standard deviation or pulse frequency power spectrum standard deviation, and ordinate represents the systolic pressure power spectrum mark under detection-phase (VIMS stages)
Quasi- difference or pulse frequency power spectrum standard deviation, solid line are threshold value THSYSOr THPRValue is 1 (i.e. ideal situation), and dotted line is threshold value
THSYSOr THPRValue is 0.9 (being set in the present embodiment).According to Fig. 7 and Fig. 8, it is apparent that vision occurs in subject
When inducing motion sickness, systolic pressure power spectrum standard deviation and pulse frequency power spectrum standard deviation have aobvious in normal phase and detection-phase
Difference is write, if asking for central point to the scatterplot of 10 groups of experimental datas, it is clear that the relative scale corresponding to the central point is less than 1
's.But because actually detected error and threshold value usually require to set certain tolerance limit, it is every in not every group of experimental data
Correct testing result can be obtained to the relative scale between detection signal, therefore the present invention uses systolic pressure power spectrum standard
Difference and pulse frequency power spectrum standard deviation carry out comprehensive descision, so as to improve the degree of accuracy of detection.
Although the illustrative embodiment of the present invention is described above, in order to the technology of the art
Personnel understand the present invention, it should be apparent that the invention is not restricted to the scope of embodiment, to the common skill of the art
For art personnel, if various change in the spirit and scope of the present invention that appended claim limits and determines, these
Change is it will be apparent that all utilize the innovation and creation of present inventive concept in the row of protection.
Claims (5)
1. it is a kind of based on systolic pressure and the vision of pulse frequency power spectrum induction motion sickness detection method, it is characterised in that including with
Lower step：
S1：Systolic pressure data of the user in normal phase (stereoscopic vision equipment is not used) are gathered respectivelyPulse rate dataWith the systolic pressure data D of detection-phase (using in stereoscopic vision device procedures)SYS, pulse rate data DPR；
S2：Systolic pressure data are calculatedDSYSPower spectrumSSYSAnd pulse rate dataDPRPower
SpectrumSPR；
S3：4 power spectrum are calculated respectivelySSYS、SPRStandard deviationStdSYS、StdPR；
S4：The relative deviation of two pairs of power spectrum standard deviations is calculated respectively
If ΔSYSLess than predetermined threshold value THSYS、ΔPRLess than predetermined threshold value THPRAny one situation meets in two kinds of situations, then judges
There is vision induction motion sickness phenomenon in detection-phase in the user, does not otherwise occur.
2. vision according to claim 1 induces cinetosis detection method, it is characterised in that 4 obtained in the step S1
Interpolation is respectively adopted in individual data and resampling is pre-processed.
3. vision according to claim 2 induces motion sickness detection method, it is characterised in that the interpolation method is three times
Spline interpolation.
4. vision according to claim 1 induces motion sickness detection method, it is characterised in that power spectrum uses in the S2
Welch methods calculate.
5. vision according to claim 1 induces motion sickness detection method, it is characterised in that threshold value in the step S3
THSYS, threshold value THPRSpan be respectively 0.85≤THSYS≤ 0.95,0.85≤THPR≤0.95。
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| CN109308341A (en) * | 2018-09-20 | 2019-02-05 | 扬州大学 | Based on the method that can quickly calculate turbulence power spectrum density that weighting is overlapping |
| WO2020162059A1 (en) * | 2019-02-05 | 2020-08-13 | ソニーセミコンダクタソリューションズ株式会社 | Intoxication state determination system, biological information acquisition device, surrounding environment information acquisition device, intoxication state determination device, and method of determining intoxication state |
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| CN108542355A (en) * | 2018-05-04 | 2018-09-18 | 成都泰和万钟科技有限公司 | A kind of bore hole 3D display vision induction motion sickness appraisal procedure |
| CN109308341A (en) * | 2018-09-20 | 2019-02-05 | 扬州大学 | Based on the method that can quickly calculate turbulence power spectrum density that weighting is overlapping |
| WO2020162059A1 (en) * | 2019-02-05 | 2020-08-13 | ソニーセミコンダクタソリューションズ株式会社 | Intoxication state determination system, biological information acquisition device, surrounding environment information acquisition device, intoxication state determination device, and method of determining intoxication state |
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Application publication date: 20171208 |