CN106667429A - View induced motion sickness detecting method based on eye movement signals - Google Patents

View induced motion sickness detecting method based on eye movement signals Download PDF

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CN106667429A
CN106667429A CN201710089641.2A CN201710089641A CN106667429A CN 106667429 A CN106667429 A CN 106667429A CN 201710089641 A CN201710089641 A CN 201710089641A CN 106667429 A CN106667429 A CN 106667429A
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eye
cinetosis
experimenter
dynamic
state
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CN106667429B (en
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易琳
刘然
张艳珍
贾瑞双
李丽仙
辇伟奇
邓泽坤
徐苗
李德豪
刘明明
冉静
林昌海
何永鹏
陈超
陈一超
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Chongqing University
Chongqing Tumour Institute
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Chongqing Tumour Institute
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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
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4005—Detecting, measuring or recording for evaluating the nervous system for evaluating the sensory system
    • A61B5/4023—Evaluating sense of balance
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
    • 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

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  • Signal Processing (AREA)
  • Human Computer Interaction (AREA)
  • Ophthalmology & Optometry (AREA)
  • Neurology (AREA)
  • Neurosurgery (AREA)
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Abstract

The invention discloses a view induced motion sickness detecting method based on eye movement signals. The view induced motion sickness detecting method based on eye movement signals comprises the following steps: (1) wearing a heat-mounted brain wave sensor which detects eye movement frequency in an eye opening state and an eye closing state in real time on the head of a testee; (2) processing the eye movement frequency data acquired by the head-mounted brain wave sensor to obtain the average eye movement frequency in every minute in the eye opening state and the eye closing state of the testee; and (3) judging whether the testee is in a motion sickness state or not. According to the view induced motion sickness detecting method based on eye movement signals, whether the testee is in the motion sickness state or not is evaluated by the average eye movement frequency, evaluation is objective and accurate, evaluation operation is simple, and the problem of view induced motion sickness can be reserved conveniently.

Description

Vision induction cinetosis detection method based on the dynamic signal of eye
Technical field
The present invention relates to vision induction cinetosis state inspection field, more particularly to a kind of vision based on the dynamic signal of eye Induction cinetosis detection method.
Background technology
In recent years, the fast development of Display Technique causes increasing people constantly to touch brand-new display environment, Such as wide-screen television of high-resolution and strong depth correlation, naked-eye 3 D television and used in virtual reality and game Head mounted display.Additionally, with the development of Video processing and computer graphics techniques, occurring in that substantial amounts of comprising complexity And the frequently image of the novelty of viewpoint cinetosis, 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 embody the depth perception of image, stereovision, true The display distribution situation of true feeling and image, makes picture become three-dimensional true to nature, and band gives spectators people unprecedented viewing body Test.
Advanced Display Technique largely advances which in every field because of its strong third dimension and feeling of immersion The drawbacks of being applied to develop, but there is also certain, most distinct issues are exactly during viewing often to cause viewing person to go out Existing vision induction cinetosis (visually induced motion, VIM), occur visual fatigue, blurred vision, diplopia, nausea, The phenomenons such as vomiting, dizziness, impact people's are healthy, while also counteracts that the further development of Display Technique and promote.
In order to reduce the vision induction risk brought of cinetosis, we are necessary to analyze and cause vision induction cinetosis shape body Factor and condition.And in order to realize this purpose, we must mouse out one kind first and can induce cinetosis with qualitative assessment vision The method of shape body.
At present, the method being estimated for sense of discomfort in three-dimensional viewing mainly has subjective evaluation method and objective evaluation method two Big class.Subjective evaluation method refers to and VIM is estimated by subjective questionnaire that experimenter needs to answer a questionnaire according to autoscopia, then Statistical analysiss assessment VIM degree is carried out to questionnaire by research worker, the method is simple, convenient, but subjectivity is big, reliability Low, assessment result is not accurate enough.Objective evaluation method to refer to and carry out formula to the VIM degree of experimenter by defining some objective indicators Change assessment, the method is not affected by subjective factorss, but the selection of index is difficult, test complicated.
The content of the invention
In view of also there are many deficiencies in the method for existing assessment vision induction cinetosis state, it is an object of the invention to provide one Vision induction cinetosis detection method kind based on the dynamic signal of eye, with realize it is more objective and accurate, more easily assess regarding for viewing person Feel induction cinetosis state.
The present invention is comprised the following steps based on the vision induction cinetosis detection method of the dynamic signal of eye：
1) the wear-type brain electricity of the dynamic number of times of eye under real-time detection eye opening and eye closing two states is worn in subject's head Wave sensor；
2) the dynamic number of times data of the eye collected to wear-type brain wave sensor are processed, by formula：
Per minute average eye of the experimenter under eye opening, eye closing two states is calculated respectively Dynamic number of times, in formula, BR is that average eye per minute moves number of times, s1For the initial time of data segment, s2For the finish time of data segment, Unit is the second, and blink (i) is wear-type brain wave sensor in s1-s2The eye that each sampling instant in time period is collected is moved Data, it is 1 to collect dynamic signal blink (i) of eye, and it is 0 not collect dynamic signal blink (i) of eye；
If 3) experimenter is under eyes-open state, the dynamic number of times of its average eye per minute is more than 27 times, then judge that experimenter sends out Raw cinetosis, on the contrary then judge that experimenter does not occur cinetosis；If experimenter is under closed-eye state, dynamic time of its average eye per minute Number judges that more than 4 times, then experimenter occurs cinetosis, otherwise then judges that experimenter does not occur cinetosis.
Beneficial effects of the present invention：
Vision induction cinetosis detection method of the present invention based on the dynamic signal of eye, which is tested to assess by the dynamic number of times of average eye Whether person there is cinetosis, assesses more objective and accurate, and evaluation operation is simpler, and more easily vision induction cinetosis problem can be entered Row research.
Specific embodiment
With reference to embodiment, the invention will be further described.
Vision induction cinetosis detection method of the present embodiment based on the dynamic signal of eye, comprises the following steps：
1) the wear-type brain electricity of the dynamic number of times of eye under real-time detection eye opening and eye closing two states is worn in subject's head Wave sensor；
2) the dynamic number of times data of the eye collected to wear-type brain wave sensor are processed, by formula：
Per minute average eye of the experimenter under eye opening, eye closing two states is calculated respectively Dynamic number of times, in formula, BR is that average eye per minute moves number of times, s1For the initial time of data segment, s2For the finish time of data segment, Unit is the second, and blink (i) is wear-type brain wave sensor in s1-s2The eye that each sampling instant in time period is collected is moved Data, it is 1 to collect dynamic signal blink (i) of eye, and it is 0 not collect dynamic signal blink (i) of eye；
If 3) experimenter is under eyes-open state, the dynamic number of times of its average eye per minute is more than 27 times, then judge that experimenter sends out Raw cinetosis, on the contrary then judge that experimenter does not occur cinetosis；If experimenter is under closed-eye state, dynamic time of its average eye per minute Number judges that more than 4 times, then experimenter occurs cinetosis, otherwise then judges that experimenter does not occur cinetosis.
The wear-type brain wave sensor of the dynamic number of times of detection eye worn in subject's head in the present embodiment is Muse Brain wave intelligence headband, its sample frequency can sets itself, the sampling period is short, and sampling accuracy is high.Certainly in being embodied as, The wear-type brain wave sensor of other forms can also be adopted.
Vision induction cinetosis detection method of the present embodiment based on the dynamic signal of eye, which is received to assess by the dynamic number of times of average eye Whether examination person there is cinetosis, assesses more objective and accurate, and evaluation operation is simpler, more easily can induce cinetosis problem to vision Studied.
This is verified based on the reliability of the vision induction cinetosis detection method of the dynamic signal of eye below by experiment：
In test, number of subjects is 30 people, and everyone wears Muse brain waves intelligence headband, and experimenter is by driving mould Intend device induction vision cinetosis, driving simulator is made up of the scene projection screen of a moveable driver's cabin and 220 °, and each is received Examination person is once tested under eyes-open state and closed-eye state respectively.
Experimentation under eyes-open state is：
The NON-VIM stages：Experimenter does not drive a car simulator, eye opening standing 3min, and this stage, experimenter did not go out Existing VIMS symptoms；
The VIM stages：Experimenter's eye opening driving simulator on the road of a bending, induction experimenter produce vision Cinetosis, after there is cinetosis, experimenter still persistently keeps eye opening driving condition, until continuing to drive, is returned to not by rest , there is cinetosis to this stage of not dizzy state is returned to for the VIM stages in dizzy state, the time span foundation of this phase experiments is received Depending on the personal cinetosis state of examination person.
Drive in flow process, when experimenter's cinetosis starts whole, experimenter needs verbal report per minute once subjective Whether cinetosis state is in, while the dynamic signal of eye that Muse brain waves intelligence headband is collected is divided into two groups, one group is NON- The non-cinetosis eye movement data in VIM stages, one group of cinetosis eye movement data for the VIM stages.
Table one is that, under eyes-open state, each tester moves number of times in the average eye per minute of cinetosis state and non-cinetosis state Table：
Table one
Experimentation under closed-eye state is：
The NON-VIM stages：Experimenter does not drive a car, eye closing standing 3min, and this stage, VIM diseases did not occur in experimenter Shape；
The VIM stages：Experimenter opens eyes on the road of a bending and drives a car, and induction experimenter produces vision cinetosis, After generation cinetosis, experimenter still persistently keeps eye opening driving condition, until continuing to drive, is returned to not by eye closing rest Dizzy state.Closing one's eyes and this stage being rested for the VIM stages, the time span of this phase experiments is according to the personal cinetosis state of experimenter Depending on.
Drive in flow process, from experimenter's cinetosis starts whole, experimenter needs verbal report per minute once subjective Whether cinetosis state is in, while the dynamic signal of eye that Muse brain waves intelligence headband is collected is divided into two groups, one group is NON- The non-cinetosis eye movement data in VIM stages, one group of cinetosis eye movement data for the VIM stages.
Table two is that, under closed-eye state, each tester moves number of times in the average eye per minute of cinetosis state and non-cinetosis state Table：
Table two
We using paired t-test come BR values under non-cinetosis state in check table one and cinetosis state statistically whether There were significant differences, as a result for：T (29)=2.05, P=0.00, this shows under eyes-open state, non-cinetosis state and cinetosis state Statistically there were significant differences for BR values.Likewise, using paired t-test come non-cinetosis state and cinetosis state in check table two Whether there were significant differences for lower BR values, as a result for：T (29)=2.05, P=0.00, this shows under closed-eye state, non-cinetosis state and Statistically also there were significant differences for the BR values of cinetosis state.The above results move secondary with average minute clock eye in demonstrating the present invention Number is come whether judge experimenter be correct in cinetosis state.
In the present embodiment, judge whether the average eye per minute in cinetosis state moves secondary to experimenter under eyes-open state Number is taken as 27 times, finds out from table one, and the non-cinetosis BR of experiment number 11 is 27.32, and the non-cinetosis BR of experiment number 20 is 30.17, the cinetosis BR of experiment number 28 is 25.32, in addition to this three groups of data, can be to eyes-open state using the present embodiment method Under vision induction cinetosis state carry out correct detection and judge that Detection accuracy is 90%.
In the present embodiment, judge whether the average eye per minute in cinetosis state moves secondary to experimenter under closed-eye state Number is taken as 4 times, finds out from table two, and the cinetosis BR of experiment number 9 is 3.21, and the cinetosis BR of experiment number 25 is 2.46, except this two Outside group data, correct detection can be carried out to the vision induction cinetosis state under eyes-open state using the present embodiment method and sentenced Fixed, Detection accuracy is 93.3%.
Knowable to above-mentioned analysis, accurate vision induction cinetosis shape can be carried out using the present embodiment method to vast majority of people State is detected.
Finally illustrate, above example is only unrestricted to illustrate technical scheme, although with reference to compared with Good embodiment has been described in detail to the present invention, it will be understood by those within the art that, can be to the skill of the present invention Art scheme is modified or equivalent, and without deviating from the objective and scope of technical solution of the present invention, which all should be covered at this In the middle of the right of invention.

Claims (1)

1. cinetosis detection method is induced based on the vision of the dynamic signal of eye, it is characterised in that：Comprise the following steps：
1) the wear-type brain wave that the dynamic number of times of eye under real-time detection eye opening and eye closing two states is worn in subject's head is passed Sensor；
2) the dynamic number of times data of the eye collected to wear-type brain wave sensor are processed, by formula：
It is dynamic secondary that per minute average eye of the experimenter under eye opening, eye closing two states is calculated respectively Number, in formula, BR is that average eye per minute moves number of times, s1For the initial time of data segment, s2For the finish time of data segment, unit For the second, blink (i) is wear-type brain wave sensor in s1-s2The dynamic number of eye that each sampling instant in time period is collected According to it is 1 to collect dynamic signal blink (i) of eye, and it is 0 not collect dynamic signal blink (i) of eye；
If 3) experimenter is under eyes-open state, the dynamic number of times of its average eye per minute is more than 27 times, then judge that experimenter occurs dizzy It is dynamic, on the contrary then judge that experimenter does not occur cinetosis；If experimenter is under closed-eye state, the dynamic number of times of its average eye per minute is big In 4 times, then judge that experimenter occurs cinetosis, otherwise then judge that experimenter does not occur cinetosis.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108836322A (en) * 2018-05-04 2018-11-20 成都泰和万钟科技有限公司 A kind of naked eye 3D display vision induction motion sickness detection method
CN112957046A (en) * 2021-03-05 2021-06-15 清华大学 Method and apparatus for assessing motion sickness

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102133099A (en) * 2011-01-27 2011-07-27 中国医学科学院生物医学工程研究所 Device and method for estimating discomfort in watching 3D images by bioelectricity
KR20120109160A (en) * 2011-03-28 2012-10-08 한국과학기술원 Apparatus for measuring 3d display-induced visual discomfort, apparatus for extracting 3d visual discomfort-inducing components automatically, and method thereof
CN102908152A (en) * 2012-10-07 2013-02-06 西安信唯信息科技有限公司 Fatigue detection eyeglasses
CN104146701A (en) * 2014-07-22 2014-11-19 南京航空航天大学 Multi-mode 3D (three-dimensional) television health detecting system
CN106073805A (en) * 2016-05-30 2016-11-09 南京大学 A kind of fatigue detection method based on eye movement data and device
CN205903240U (en) * 2016-06-02 2017-01-25 西南交通大学 Eyes fatigue detection device

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102133099A (en) * 2011-01-27 2011-07-27 中国医学科学院生物医学工程研究所 Device and method for estimating discomfort in watching 3D images by bioelectricity
KR20120109160A (en) * 2011-03-28 2012-10-08 한국과학기술원 Apparatus for measuring 3d display-induced visual discomfort, apparatus for extracting 3d visual discomfort-inducing components automatically, and method thereof
CN102908152A (en) * 2012-10-07 2013-02-06 西安信唯信息科技有限公司 Fatigue detection eyeglasses
CN104146701A (en) * 2014-07-22 2014-11-19 南京航空航天大学 Multi-mode 3D (three-dimensional) television health detecting system
CN106073805A (en) * 2016-05-30 2016-11-09 南京大学 A kind of fatigue detection method based on eye movement data and device
CN205903240U (en) * 2016-06-02 2017-01-25 西南交通大学 Eyes fatigue detection device

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
JAE WON BANG ET.AL: "Assessment of Eye Fatigue Caused by 3D Displays Based on Multimodal Measurements", <SENSORS> *
张莉等: "应用眼动仪评价观看立体显示视频诱导的视疲劳程度的实验研究", 《眼科》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108836322A (en) * 2018-05-04 2018-11-20 成都泰和万钟科技有限公司 A kind of naked eye 3D display vision induction motion sickness detection method
CN108836322B (en) * 2018-05-04 2020-11-06 成都泰和万钟科技有限公司 Naked eye 3D display vision-induced motion sickness detection method
CN112957046A (en) * 2021-03-05 2021-06-15 清华大学 Method and apparatus for assessing motion sickness

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