CN109528217A - A kind of mood detection and method for early warning based on physiological vibrations analysis - Google Patents
A kind of mood detection and method for early warning based on physiological vibrations analysis Download PDFInfo
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Abstract
The invention discloses a kind of mood detection based on physiological vibrations analysis and method for early warning, the analysis to Human Physiology vibration signal can be passed through, it realizes the non-contact detection and early warning to the emotional state of people, specifically includes video data stream input, physiological vibrations signal extraction, physiological vibrations mood calculate, computation model training optimization, emotional state determines, abnormal emotion early warning pushes 6 functional modules.
Description
Technical field
The present invention relates to Emotion identification technical field, more particularly to a kind of mood detection based on physiological vibrations analysis and
Method for early warning.
Background technique
Mood is the feeling for combining people, a kind of state of thought and act, is played in the exchange of person to person important
Effect.Mood is a kind of feeling for combining people, the state of thought and act, it includes people to extraneous or autostimulation psychology
Reaction, including the physiological reaction with this psychoreaction.In the routine work and life of people, the effect of mood is nowhere not
?.In medical treatment and nursing, if it is possible to know patient, particularly have the emotional state of the patient of expression obstacle, so that it may according to
The mood of patient makes different nursing interventions, improves nursing quality.In product development process, if it is possible to identify user
Using the emotional state in product process, user experience is understood, so that it may improve product function, design and be more suitable for user demand
Product.In various man-machine interactive systems, if system can recognize that the emotional state of people, man-machine interaction will become
It obtains more friendly and natural.Therefore, analysis is carried out to mood and identification is Neuscience, psychology, cognitive science, computer section
Learn an important cross discipline research topic with fields such as artificial intelligence.
Generality viewpoint about Emotion identification can trace back to charles Robert Darwin in 1872 earliest
Written " expression of human and animal " book, he think the mood of people and expression be it is born, universal, people can identify
Mood and expression from Different Culture, the people of race.Many psychologists are obtained by research from the sixties in last century
Emotion identification has the conclusion of generality.Ekman and Izard proposes that the mankind share 6 kinds of basic facial expressions: glad, indignation is feared
Fear, is sad, detesting and is surprised.However some other psychologist then thinks the expression of mood and identification is the acquistion day after tomorrow, tool
Literate otherness, intensity of this cultural difference in facial expression and in terms of all body to emotional experience
It is existing.
Method is induced corresponding to different moods, Emotion identification method is also different, common Emotion identification method master
It is divided into two major classes: the identification based on non-physiological signal and the identification based on physiological signal.Mood based on non-physiological signal is known
Other method mainly includes the identification etc. to facial expression and speech intonation.Human facial expression recognition method is according between expression and mood
Corresponding relationship identify different moods, under specific emotional state people can generate specific facial muscle movements and expression
Mode, corners of the mouth angle upwarps when being such as in a cheerful frame of mind, and eye will appear annular fold；It can frown, open eyes wide when angry.Currently,
Human facial expression recognition mostly uses the method for image recognition to realize.Speech intonation recognition methods is according to different emotional state servants
Expression of language difference come what is realized, the intonation spoken when being such as in a cheerful frame of mind can be more cheerful and more light-hearted, intonation meeting when irritated
Compare dull.Be based on the advantages of non-physiological signal recognition methods it is easy to operate, do not need special installation.The disadvantage is that it cannot be guaranteed that
The reliability of Emotion identification, because people can cover up the true emotional of oneself by camouflage facial expression and speech intonation,
And this camouflage is often not easy to be found.Secondly, being based on non-physiological signal for the disabled person with certain special diseases
Know method for distinguishing to be often difficult to realize.
Emotion identification method based on physiological signal, mainly includes Emotion identification based on autonomic nerves system and is based on
The Emotion identification of pivot nervous system.Recognition methods based on autonomic nerves system refers to by measuring heart rate, Skin Resistance, breathing
Physiological signals are waited to identify corresponding emotional state；Recognition methods based on central nervous system refers to and is not sympathized with by analysis
The unlike signal that brain issues under not-ready status identifies corresponding mood.This Emotion identification method based on physiological signal is not easy
Pretended, and discrimination is higher compared with the recognition methods based on non-physiological signal.However in general, it is based on physiological signal
Although Emotion identification method can obtain true data, usually require tested individual and dress corresponding signal acquisition to set
Standby, information collection difficulty is big, and practical application scene is very limited.
Summary of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a kind of mood detections based on physiological vibrations analysis
And method for early warning.This method can be realized the true acquisition to mood data, and does not need any signal of tested individual wearing and adopt
Collect equipment, therefore can be realized the non contact angle measurement to tested individual emotional state, multiple practical applications scene can be applicable in.
The technical scheme adopted by the invention is that:
Since the microvibration of human muscle is associated with emotion reflection, it can directly reflect the emotional state of people, therefore
The present invention is mainly in such a way that the muscle Vibration Condition of face and neck to people carries out video acquisition and analysis, to realize pair
The identification of the emotional state of people, concrete function process are as shown in Fig. 1.
Wherein, physiological vibrations signal extraction module is responsible for realizing the analysis to head end video data, therefrom to personage's individual
Positioning and feature extraction are carried out, each facial musculi colli Vibration Condition for being tested individual is tested and analyzed frame by frame, therefrom extracts
The related physiological parameters such as vibration amplitude and frequency, and export to physiological vibrations mood computing module.
Physiological vibrations mood computing module is responsible for carrying out the related physiological parameters such as the muscle vibration amplitude of typing and frequency
Analytical calculation is realized with this and is detected to the emotional status for being tested individual, show that this is tested the emotional state of individual with this
Value.
Computation model training optimization module is responsible for realizing by stochastic gradient descent method to physiological vibrations mood computation model
It is iterated optimization, to promote the accuracy rate that mood determines result.
The emotional state value that emotional state determination module is responsible for being tested this individual determines, sets in advance if the value is higher than
Fixed threshold value then triggers abnormal emotion early warning pushing module.
Abnormal emotion early warning pushing module is then responsible for the warning information that will be received, and is pushed to preset reception in real time
Terminal.
Compared with prior art, the beneficial effects of the present invention are: the present invention, which does not need tested individual, dresses corresponding signal
Equipment is acquired, therefore can be realized the contactless acquisition to physiological signal, so as to realize to tested individual emotional state
Non contact angle measurement, avoid bringing discomfort to related tested personnel；Meanwhile the present invention is due to can be realized to tested individual feelings
The non contact angle measurement of not-ready status, thus it is easy to use, and cost is relatively low, is difficult to be aware, and can be applicable in a variety of reality and answer
Use scene.
Detailed description of the invention
Fig. 1 is the concrete function flow chart of this method.
Specific embodiment
The following further describes the present invention with reference to the drawings.
Mood detection function principle is vibrated according to Human Physiology, Human Physiology vibrational image data can pass through standardized view
Frequency picture system is captured.Each pixel in image reflects the frequency or amplitude of the point, the group of frequency and amplitude parameter
Conjunction reflects mood and the physiological characteristic of people, can be with area by the difference of mathematic parameter and histogram frequency distribution diagram design conditions
Separate subtle emotional change.
If an individual adjacent spots are all different, the image that each point of object will occur during detection and analysis.Pass through
False colour scale shows the accumulation amplitude of the displacement on every bit, has image and the actual color image of object faint similar
Property, final result is obtained by colour code and display frequency (Hz).In particular technique realization, face view can be acquired by video camera
Frequency image, with the frequency and amplitude of video camera and software for calculation processing pixel variation, to measure the small fortune of facial neck
It is dynamic, and the emotional parameters such as calculation processing individual pressure, aggressiveness and anxiety degree based on amplitude and frequency, so that measurement is current
The emotional state of individual.
The core of the technology is to obtain visual a variety of variables as a result, come appraiser by video image analysis algorithm
Psychology and emotional state.Using video image analysis technology, mood testing principle analysis matching people is vibrated according to Human Physiology
Physiological parameter, changed by pixel between each frame image of several seconds tens frame images, analyzed by mathematical algorithm
The corresponding physiological signal parameter of the three-dimensional space state of people confirms mood shape of the people on different time space by special algorithm
State realizes the contactless Emotion identification based on video analysis.The amplitude and frequency generated due to the head vibration of people is in the time
With can all be changed in any point in space, by the amplitude of each pixel, the figure of system every frame per second in general movement
The relative motion of storage image is reflected as moving the ratio generated, these information can be reduced to millimeter or micro- in a manner of colour code
Rice.When facial identical position on the image, relative amplitude amplitude can be handled automatically by system.
It is a kind of realization process example of physiological vibrations mood computing module below.
Wherein, the amplitude of point each in video image is determined by following formula:
Wherein in x, y representative image the point coordinate value, the totalframes of n representative image, Vx,y,iRepresenting should in the i-th frame
The displacement amplitude of point.
The frequency of each point is that following formula determines:
ΔiThe i-th point of difference between different frame of-image；
According to the reflex control relationship of Human Physiology vibration and emotional state, the feelings for being tested individual are calculated by following formula
Thread tensity:
Wherein:The thermal vibration image net amplitude of tested individual left part is represented,Represent tested individual right part
Thermal vibration image net amplitude,Represent fromStart toBetween maximum value,Represent tested individual left part
Vibrational image maximum frequency,The maximum frequency of the thermal vibration image of tested individual right part is represented,Represent from
Start toBetween maximum value, n represents tested individual and occupies maximum calorific value.
Claims (9)
1. a kind of mood detection and method for early warning based on physiological vibrations analysis, can be by dividing Human Physiology vibration signal
Non-contact detection and early warning to the emotional state of people are realized in analysis, specifically include video data stream input, physiological vibrations signal
It extracts, physiological vibrations mood calculates, computation model training optimization, emotional state determines, abnormal emotion early warning pushes 5 function moulds
Block.
2. according to the method described in claim 1, it is characterized by: the Human Physiology vibration signal is by the face to people
And the muscle Vibration Condition of neck carries out video and captures to obtain；The Human Physiology vibration signal be embodied in frequency and
The other form of amplitude two major classes.
3. according to the method described in claim 1, it is characterized by: the physiological vibrations signal extraction module is responsible for from video counts
According to positioning in stream to personage's individual and feature extraction, the facial musculi colli vibration of each personage's individual is tested and analyzed frame by frame
Situation therefrom extracts the amplitude of physiological vibrations and the relevant parameter of frequency, and exports to physiological vibrations mood computing module.
4. according to the method described in claim 1, it is characterized by: the physiological vibrations mood computing module is responsible for typing
The amplitude and frequency dependence parameter of physiological vibrations carry out quantum chemical method, show that this is tested the emotional state value of individual with this.
5. according to the method described in claim 1, it is characterized by: computation model training optimization module passes through stochastic gradient
Descent method realizes the iteration optimization to physiological vibrations mood computation model, to promote the accuracy rate that mood determines result.
6. according to the method described in claim 1, it is characterized by: the emotional state determination module is responsible for the tested individual
Emotional state value determined, if the value be higher than preset threshold value, trigger abnormal emotion early warning pushing module.
7. according to the method described in claim 3, it is characterized by: the amplitude parameter is by formulaDetermine, wherein in x, y representative image the point coordinate value, total frame of n representative image
Number, Vx,y,iRepresent the displacement amplitude of the point in the i-th frame.
8. according to the method described in claim 3, it is characterized by: the frequency parameter is by formulaIt determines, wherein ΔiThe i-th point of difference between different frame of representative image.
9. according to the method described in claim 4, it is characterized by: the physiological vibrations mood computing module passes through formulaThe nervous degree for being tested individual is calculated, whereinRepresent tested individual left side
Partial thermal vibration image net amplitude,The thermal vibration image net amplitude of tested individual right part is represented,Represent from
Start toBetween maximum value,The vibrational image maximum frequency of tested individual left part is represented,Represent tested individual
The maximum frequency of the thermal vibration image of right part,Represent fromStart toBetween maximum value, n represents tested individual
Occupy maximum calorific value.
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| CN111524601A (en) * | 2020-04-26 | 2020-08-11 | 华东师范大学 | Psychological state testing and evaluating method based on vestibular nerve reflex |
| CN111631735A (en) * | 2020-04-26 | 2020-09-08 | 华东师范大学 | Abnormal emotion monitoring and early warning method based on video data vibration frequency |
| CN112150759A (en) * | 2020-09-23 | 2020-12-29 | 北京安信智文科技有限公司 | Real-time monitoring and early warning system and method based on video algorithm |
| CN112932485A (en) * | 2021-01-03 | 2021-06-11 | 金纪高科智能科技(北京)有限公司 | Non-contact type conversation confidence rate testing system and method |
| CN113647950A (en) * | 2021-08-23 | 2021-11-16 | 北京图安世纪科技股份有限公司 | Psychological emotion detection method and system |
| CN113837125A (en) * | 2021-09-28 | 2021-12-24 | 杭州聚视鼎特科技有限公司 | Cadre psychological mood trend digital management system |
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