CN116887754A - Myoelectric potential measurer, method and system - Google Patents
Myoelectric potential measurer, method and system Download PDFInfo
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- CN116887754A CN116887754A CN202280015517.0A CN202280015517A CN116887754A CN 116887754 A CN116887754 A CN 116887754A CN 202280015517 A CN202280015517 A CN 202280015517A CN 116887754 A CN116887754 A CN 116887754A
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- 230000003183 myoelectrical effect Effects 0.000 title claims abstract description 156
- 238000000034 method Methods 0.000 title claims description 15
- 210000003205 muscle Anatomy 0.000 claims description 46
- 238000002567 electromyography Methods 0.000 claims description 13
- 230000008859 change Effects 0.000 claims description 2
- 238000010801 machine learning Methods 0.000 claims description 2
- 238000001514 detection method Methods 0.000 description 27
- 238000005259 measurement Methods 0.000 description 16
- 238000010586 diagram Methods 0.000 description 15
- 238000013500 data storage Methods 0.000 description 14
- 230000000630 rising effect Effects 0.000 description 9
- 210000000887 face Anatomy 0.000 description 7
- 230000008569 process Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 6
- 230000009471 action Effects 0.000 description 4
- 230000000875 corresponding effect Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000001174 ascending effect Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 3
- 230000002596 correlated effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000036982 action potential Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000008921 facial expression Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000036651 mood Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
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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
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
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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
- A61B5/389—Electromyography [EMG]
- A61B5/397—Analysis of electromyograms
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- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
Support the appearance of smiling face. The myoelectric potential measuring device according to an embodiment of the present invention is a myoelectric potential measuring device for measuring a myoelectric potential, comprising: a determination unit configured to determine whether or not a difference between the characteristic amount of the myoelectric potential measured by the myoelectric potential measuring device and the characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive is within a predetermined range; and an output unit that outputs the difference within a predetermined range or outside the predetermined range.
Description
Technical Field
The invention relates to a myoelectric potential meter, a myoelectric potential meter method and a myoelectric potential meter system.
Background
Conventionally, smiling faces have been required in many scenes in various professions, daily lives, and the like. Thus, a method for supporting the exposure of smiling faces is considered.
For example, patent document 1 describes the following method: a smile value of a user included in a captured image is measured, the smile value is converted into a smile level, and a face image having a smile level higher than the smile level is presented, thereby improving the smile level of the user.
Prior art literature
Patent literature
Patent document 1: japanese patent laid-open No. 2017-182594
Disclosure of Invention
Problems to be solved by the invention
However, in patent document 1, a smiling face value is measured from a still image, and a dynamic characteristic of the smiling face cannot be captured.
Also, in patent document 1, the user makes an expression toward the camera of the smiling face feedback device. The user may look at his face while watching his face while recognizing the camera, and thus may not be in a normal state, and may be an unnatural smiling face.
Accordingly, the present invention aims to support the appearance of smiling faces.
Means for solving the problems
The myoelectric potential measuring device according to an embodiment of the present invention is a myoelectric potential measuring device for measuring a myoelectric potential, comprising: a determination unit configured to determine whether or not a difference between the characteristic amount of the myoelectric potential measured by the myoelectric potential measuring device and the characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive is within a predetermined range; and an output unit that outputs the difference within a predetermined range or outside the predetermined range.
Effects of the invention
According to the present invention, the appearance of smiling face can be supported.
Drawings
Fig. 1 is a block diagram of the whole according to an embodiment of the present invention.
Fig. 2 is a functional block diagram of a smile detection system according to an embodiment of the present invention.
Fig. 3 is a diagram showing the results of evaluating the smiling face of a subject according to an embodiment of the present invention.
Fig. 4 is a diagram showing the results of evaluating the smiling face of a subject according to an embodiment of the present invention.
Fig. 5 is a graph showing the results of evaluating the charm of a smiling face of a subject according to an embodiment of the present invention.
Fig. 6 is a graph showing the results of evaluating the charm of a smiling face of a subject according to an embodiment of the present invention.
Fig. 7 is a diagram for explaining myoelectric potentials according to an embodiment of the present invention.
Fig. 8 is a diagram for explaining 8 feature amounts according to an embodiment of the present invention.
Fig. 9 is a diagram for explaining a relationship between the charm of a smile and the association between the size of the smile, the ascending speed, and the eye opening according to an embodiment of the present invention.
Fig. 10 is a flowchart of registration processing according to an embodiment of the present invention.
Fig. 11 is a flowchart of smile detection processing according to an embodiment of the present invention.
Fig. 12 is a block diagram showing an example of a hardware configuration of the myoelectric potential meter and smile-detection device according to an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
In this specification, an embodiment using myoelectric potentials at 4 places of the face of the user is described, but the present invention is not limited to this, and can detect smiling faces using myoelectric potentials at a plurality of places of the face of the user. For example, the plurality of sites is 2 or more sites including at least one of the periphery of the eye, the zygomatic small muscle, the zygomatic large muscle, and the laugh muscle.
< Structure of the whole >
Fig. 1 is a block diagram of the whole according to an embodiment of the present invention. As shown in fig. 1, the smile detection system 1 includes a myoelectric potential meter 10 and a smile detection device 20. The myoelectric potential meter 10 can transmit and receive data to and from the smile detection device 20 via wired communication or wireless communication. Hereinafter, each will be described.
The myoelectric potential meter 10 is a device for measuring myoelectric potential. The myoelectric potential meter 10 can determine whether the user is a smiling face based on the myoelectric potential of the user measured by the myoelectric potential meter 10 and output a determination result.
The smile detection device 20 can determine whether the user is a smile or not based on the myoelectric potential of the user measured by the myoelectric potential meter 10, and output a determination result. The smiling face detection device 20 may be any computer such as a personal computer, a tablet terminal, a smart phone, or the like.
< functional Box >
Fig. 2 is a functional block diagram of the smile detection system 1 according to an embodiment of the present invention. As shown in fig. 2, the smile detection system 1 may include a measurement unit 101, a registration unit 102, a determination unit 103, an output unit 104, and an electromyogram data storage unit 105. The smile detection system 1 can function as the measurement unit 101, the registration unit 102, the determination unit 103, and the output unit 104 by executing a program.
The electromyographic meter 10 may include the measurement unit 101, the registration unit 102, the determination unit 103, the output unit 104, and the electromyogram data storage unit 105 (that is, the smile detection device 20 is not used), or the smile detection device 20 may include at least a part of the registration unit 102, the determination unit 103, the output unit 104, and the electromyogram data storage unit 105 (that is, the smile detection device 20 is used).
The measurement unit 101 measures the myoelectric potential of the face of the user. The measurement unit 101 generates an electromyogram (a record of the action potential generated in the muscle over time).
For example, the measurement unit 101 measures myoelectric potentials at least 2 of orbicular, zygomatic small, zygomatic large, and laugh muscles of the face of the user.
For example, the measurement unit 101 measures the myoelectric potential (that is, 1 channel) at the right or left eye of the face of the user, and the myoelectric potential (that is, 1 channel) at one of the right or left zygomatic small muscle, the right or left zygomatic large muscle, and the right or left laugh muscle, for a total of 2 channels. For example, the measurement unit 101 measures the total of 4 channels, that is, the myoelectric potentials (that is, 2 channels) at the left and right eyes of the face of the user, and the myoelectric potentials (that is, 2 channels) at one of the left and right zygomatic small muscles, the left and right zygomatic large muscles, and the left and right laugh muscles. For example, the myoelectric potential at the eye is the myoelectric potential at the orbicularis oculi muscle, the myoelectric potential at the frontal muscle, or the like (hereinafter, in this specification, a case of the orbicularis oculi muscle is described).
The registration unit 102 causes the electromyogram data storage unit 105 to store the magnitude (for example, the maximum value and the minimum value (or the amplitude)) of the myoelectric potential of the user. In one embodiment of the present invention, the maximum value and the minimum value (or the amplitude) of the myoelectric potential when the user is a smiling face are registered in advance, and when the maximum value and the minimum value (or the amplitude) of the myoelectric potential are close to each other, it is possible to determine whether or not the user is a smiling face with a charm.
Information related to the myoelectric potential is stored in the electromyogram data storage unit 105. Hereinafter, description will be given of the maximum value and minimum value (or amplitude) of the myoelectric potential of the < < user > and the characteristic value of the myoelectric potential of the attractive smiling face >.
Maximum value and minimum value (or amplitude) of myoelectric potential of user
The electromyogram data storage unit 105 stores the maximum value and the minimum value (or the amplitude) of the user's myoelectric potential stored by the registration unit 102.
Characteristic quantity of myoelectric potential of attractive smiling face
The electromyogram data storage unit 105 stores a feature amount of the myoelectric potential of the smile objectively determined to be attractive (for example, an integral value of the myoelectric potential (the size of the smile), a rising speed, an association of eyes, and the like).
The determination unit 103 determines whether or not the difference between the characteristic amount of the myoelectric potential measured by the measurement unit 101 and the characteristic amount of the myoelectric potential of the smile objectively determined to be attractive (for example, the integral value of the myoelectric potential (the size of the smile), the rising speed, the correlation with the eye opening, and the like) stored in the electromyogram data storage unit 105 is within a predetermined range.
Specifically, the determination unit 103 extracts the feature value from the myoelectric potential measured by the measurement unit 101. For example, the determination unit 103 determines whether or not the difference between the integrated value of the myoelectric potential at each of 4 points on the face of the user (as described later, the size of the smiling face) and the size of the smiling face stored in the electromyogram data storage unit 105 is within a predetermined range. The determination unit 103 determines whether or not the difference between the speed (hereinafter described, the rising speed) at which the myoelectric potential at each of the 4 positions of the face of the user reaches the maximum value and the rising speed stored in the electromyogram data storage unit 105 falls within a predetermined range. The determination unit 103 determines whether or not the difference between the intensity of the association between the myoelectric potential at the principal orbicularis oculi muscle and the myoelectric potential at least one of the zygomatic small muscle, the zygomatic large muscle, and the laugh muscle (which will be described later, indicates the association of the eye opening) and the intensity of the association of the eye opening stored in the electromyogram data storage unit 105 is within a predetermined range. The determination unit 103 may determine only the integral value of the myoelectric potential (the size of the smile), may determine only the rising speed, and may determine only the correlation of the eyes.
In this way, the determination unit 103 can determine whether or not the characteristic amount of the myoelectric potential when the user is a smiling face is within a predetermined range of the smiling face determined to be attractive.
< predetermined range >
The predetermined range may be a range determined based on the result of machine learning, or may be a range determined by a person.
The output unit 104 outputs the difference determined by the determination unit 103 to be within or outside a predetermined range. Specifically, when the difference determined by the determining unit 103 is within a predetermined range or outside the range, the output unit 104 generates sound, vibration, light, a combination thereof, or the like, and notifies the user of the generated sound, vibration, light, or the like. The output unit 104 immediately notifies the user based on the result of the determination unit 103.
< characteristic quantity of myoelectric potential >
Here, a characteristic amount of myoelectric potential of a smiling face objectively determined to be attractive will be described. Hereinafter, the values of the integral of the myoelectric potential (smile size), the ascending rate, the correlation with the eye opening, and the other will be described.
Integral value of myoelectric potential (smiling face size)
For example, the characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive is an integral value of the myoelectric potential. More specifically, the feature quantity is an integral value of myoelectric potentials at each of 4 places (in addition, 2 places) of the face of the user. The integral value of the myoelectric potential represents the size of a smiling face. By using the size of the smiling face, a smiling face of insufficient size can be removed from a attractive smiling face.
< rise rate >
For example, the characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive is the speed up to the maximum value of the myoelectric potential. More specifically, the feature amount is a speed at which the myoelectric potential at each of 4 places (in addition, 2 places) of the face reaches a maximum value. The speed until the myoelectric potential at each of 4 places of the face becomes maximum represents the speed until laughing becomes maximum. By using the rising speed, a smiling face with a slow rising speed (i.e., an unnatural smiling face with a slow speed until the smiling is maximum) can be removed from a attractive smiling face.
Correlation of eyes
For example, the characteristic amount of the myoelectric potential of the attractive smiling face is objectively determined as the intensity of the correlation between the myoelectric potential around the eyes and the myoelectric potential around the mouth. More specifically, the feature quantity is the intensity of the correlation of the myoelectric potential at the principal orbicularis oculi muscle with the myoelectric potential at least one of the zygomatic small muscle, the zygomatic large muscle, and the laugh muscle. The intensity of the association of the myoelectric potential at the principal orbicular muscle with the myoelectric potential at least one of the zygomatic small muscle, the zygomatic large muscle, and the laugh muscle represents the intensity of the association of the action of the eye with the action of the mouth when the laugh face is present. By using the association of the eyes, a smile with weak strength of the association of the eyes (i.e., an unnatural smile with no association of the eyes (e.g., no movement of eyes)) can be removed from the attractive smile.
< other >
For example, the characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive may be the magnitude of the myoelectric potential, the timing (timing) of measuring the myoelectric potential, the pattern of change of the myoelectric potential with time, and the rate of decrease (that is, information of the rate of return of the myoelectric potential from the state of the smiling face to the state of the facia-terless expression in each of 4 places of the face). The characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive may be a combination of a plurality of types of characteristic amounts of myoelectric potentials, an average or a deviation between 4 channels (4 places on the face) of the characteristic amounts of myoelectric potentials, or the like.
Hereinafter, experiments in which characteristic amounts of myoelectric potential are found will be described with reference to fig. 3 to 9.
First, videos of 7 smiling faces of each of subjects (5 persons (of which: 20 years: 3 persons, 40 years: 2 persons)) were photographed. Then, the evaluator (40 persons) observed the video, evaluated whether or not the smiling face was natural (evaluated in a total 11 scale of 5 scales corresponding to the degree of naturalness, neither natural nor unnatural, 5 scales corresponding to the degree of unnaturalness), and evaluated whether or not the smiling face was attractive (evaluated in a total 11 scale of 5 scales corresponding to the degree of attractiveness, neither attractive nor attractive, 5 scales corresponding to the degree of absence of attractive). Fig. 3 and 4 are diagrams showing the results of evaluating the smiling face of a subject according to an embodiment of the present invention.
As shown in fig. 3, it was evaluated whether or not each smiling face of each subject (5 persons of subject No.1, subject No.2, subject No.3, subject No.4, subject No. 5) was natural and attractive. The horizontal axis represents 7 smiling faces, and the vertical axis represents the average value of the evaluations of 40 evaluators.
As shown in fig. 4, the correlation between the degree of naturalness and unnaturalness and the degree of charm and no charm was examined using the data of all smiles of all subjects, and the results were correlated with each other. That is, it is known that: the more natural the smiling face, the more attractive the smiling face. Therefore, in the present invention, in order to detect a natural smiling face, it is determined whether the user is a smiling face based on the myoelectric potential of the user's face.
Fig. 5 is a graph showing the results of evaluating the charm of a smiling face of a subject according to an embodiment of the present invention. The results of evaluation of the charm of each smile (7 smiles of smile #1, smile #2, smile #3, smile #4, smile #5, smile #6, smile # 7) of each subject (5 persons of subject No.1, subject No.2, subject No.3, subject No.4, subject No. 5) by the evaluator (40) are shown. The horizontal axis represents the charm (that is, the degree of charm and the degree of no charm (further, standardized based on standard deviation)), and the vertical axis represents the number of panelists who evaluated the charm. As shown in fig. 5, there is a deviation in evaluation of the charm of the smiling face based on the evaluator. Accordingly, in one embodiment of the present invention, as shown in fig. 6, it is considered that the gladness of the smiling face can be evaluated with an accuracy of about 89% based on the deviation of the evaluator. In fig. 6, 25%, 50%, 75% represent the upper 25%, 50% (median), 75% level of the score of 40 evaluators. Here, the accuracy was determined as "correct" with the estimated value being 25 to 75% inside.
Fig. 7 is a diagram for explaining myoelectric potentials according to an embodiment of the present invention. In one embodiment of the present invention, as the feature amount of the myoelectric potential, an integral electromyogram as shown in fig. 7 can be used. In fig. 7, the start time is a period until the myoelectric potential at each of 4 places on the face becomes maximum. The release time is a period from the state of the smiling face to the state of the facial expression, in which the myoelectric potential at each of 4 points on the face is recovered.
Fig. 8 is a diagram for explaining 8 feature amounts according to an embodiment of the present invention. The total of 4 channels, that is, the myoelectric potential (that is, 2 channels) at the left and right principal orbicular muscles of the face and the myoelectric potential (that is, 2 channels) at one of the left and right zygomatic small muscles, the left and right zygomatic large muscles, and the left and right laugh muscles, were measured.
The iEMG is an integrated value of myoelectric potentials (that is, the size of a smiling face) at 4 places (that is, each channel of 4 channels) of the face. The iEMG is the area of the hatched portion of fig. 7.
The iEMG (min) represents the minimum value of the integral value of the myoelectric potential of each channel.
The iEMG (ave) represents the average between 4 channels of the integrated value of the myoelectric potential of each channel.
The iEMG (dev) represents the 4-channel variance of the integral value of the myoelectric potential of each channel.
The iEMG (w 1) is obtained by weighting the latter half of the measurement time.
The iEMG (w 2) is obtained by weighting the first half of the measurement time.
B (ave) represents a speed up to a maximum value of the myoelectric potential of each of 4 places (that is, each of 4 channels) of the face (that is, a speed up to a maximum smile). More specifically, the average of the speeds of the channels from the maximum myoelectric potential of each channel to the maximum value is 4 channels.
B (dev) represents the intensity of the association of the myoelectric potential at the principal orbicularis oculi muscle with the myoelectric potential at least one of the zygomatic small, large and laugh muscles (that is, the intensity of the association of the action of the eye with the action of the mouth when laughing the face). More specifically, the variance between 4 channels is the velocity at which the myoelectric potential of each channel reaches the maximum value. Can be explained as: if the variance is small, the correlation is strong, and if the variance is large, the correlation is weak.
Among the characteristic amounts of the myoelectric potential, the characteristic amount associated with the charm of the smiling face is found as shown in fig. 9.
Fig. 9 is a diagram for explaining a relationship between the charm of a smile and the association between the size of the smile, the ascending speed, and the eye opening according to an embodiment of the present invention. As shown in fig. 9, the attractive force of the smiling face is related to the size (iEMG) and the rising speed (B (ave)) of the smiling face and the association (B (dev)) of the eyes.
Thus, it is known that: the size (iEMG) and the rising speed (B (ave)) of the smile and the correlation (B (dev)) of the eyes among the feature amounts of the myoelectric potential of the face are correlated with the charm of the smile.
< method >
Hereinafter, the registration process will be described with reference to fig. 10, and the smile detection process will be described with reference to fig. 11.
< registration process >
Fig. 10 is a flowchart of registration processing according to an embodiment of the present invention.
In step 11 (S11), the measurement unit 101 measures the myoelectric potential of the face of the user when the user is a smiling face (for example, when the user shows the most attractive of the smiling faces). For example, the measurement unit 101 measures the myoelectric potential (that is, 2 channels) at the left and right principal orbicular muscles of the user's face, and the myoelectric potential (that is, 2 channels) at one of the left and right zygomatic small muscles, the left and right zygomatic large muscles, and the left and right laugh muscles.
In step 12 (S12), the registration unit 102 stores the magnitude of the myoelectric potential of the user (for example, the maximum value and the minimum value (or the amplitude)) in the electromyogram data storage unit 105.
< smile detection Process >
Fig. 11 is a flowchart of smile detection processing according to an embodiment of the present invention.
In step 21 (S21), the measurement unit 101 measures the myoelectric potential of the face of the user. For example, the measurement unit 101 measures the myoelectric potential (that is, 2 channels) at the left and right principal orbicular muscles of the user's face, and the myoelectric potential (that is, 2 channels) at one of the left and right zygomatic small muscles, the left and right zygomatic large muscles, and the left and right laugh muscles.
In step 22 (S22), the determination unit 103 extracts the characteristic amount of the myoelectric potential of S21.
In step 23 (S23), the determination unit 103 determines whether or not the difference between the characteristic amount of the myoelectric potential extracted in S22 and the registered characteristic amount (that is, the characteristic amount stored in the electromyogram data storage unit 105) is within a predetermined range. If the value is within the predetermined range, the process proceeds to step 24. If the output is not within the predetermined range, the process is ended (alternatively, the output may be not within the predetermined range).
In step 24 (S24), the output unit 104 outputs S23 within a predetermined range.
In one embodiment of the present invention, the myoelectric potential meter 10 can be used to support the appearance of an attractive smiling face. Specifically, the myoelectric potential of the face of the user can be measured by the myoelectric potential meter 10, and the user can be notified that the user is a glamorous smiling face based on the output of the myoelectric potential meter 10.
< Effect >
In this way, in one embodiment of the present invention, the user is notified of the meaning in real time at the moment when the user becomes an attractive smiling face, so that the user can notice that "when what feeling is being felt" or "when what mood is being felt" is being felt. By remembering how "things" are the attractive smiling face and how "instant" are by the mind, he Shixiang, the user can naturally become the attractive smiling face.
< hardware Structure >
Fig. 12 is a block diagram showing an example of a hardware configuration of the myoelectric potential meter 10 and the smile-detection device 20 according to an embodiment of the present invention.
The myoelectric potential measuring device 10 includes a measuring device 1010 for measuring a myoelectric potential.
The electromyography apparatus 10 and the smile detection device 20 have a CPU (Central Processing Unit: central processing unit) 1001, a ROM (Read Only Memory) 1002, and a RAM (Random Access Memory: random access Memory) 1003. The CPU1001, ROM1002, and RAM1003 form a so-called computer.
The electromyography 10 and the smile-detection device 20 may include an auxiliary storage device 1004, a display device 1005, an operation device 1006, an I/F (Interface) device 1007, and a driving device 1008. The respective hardware of the electromyography 10 and the smile detection device 20 are connected to each other via a bus B.
The CPU1001 is an arithmetic device that executes various programs installed in the auxiliary storage device 1004.
The ROM1002 is a nonvolatile memory. The ROM1002 functions as a main storage device that holds various programs, data, and the like necessary for the CPU1001 to execute the various programs installed in the auxiliary storage device 1004. Specifically, the ROM1002 functions as a main storage device for storing a boot program or the like such as a BIOS (Basic Input/Output System) and an EFI (Extensible Firmware Interface: extensible firmware interface).
The RAM1003 is a volatile memory such as DRAM (Dynamic Random Access Memory: dynamic random access memory) or SRAM (Static Random Access Memory: static random access memory). The RAM1003 functions as a main storage device that provides a work area for various programs installed in the auxiliary storage device 1004 to be expanded when executed by the CPU 1001.
The auxiliary storage device 1004 is an auxiliary storage device that stores various programs and information used when executing the various programs.
The display device 1005 is a display device for displaying the internal states of the electromyography 10 and the smile detection device 20.
The operation device 1006 is an input device for inputting various instructions to the electromyograph 10 and the smile detection device 20 by the manager of the electromyograph 10 and the smile detection device 20.
The I/F device 1007 is a communication device for connecting to a network and communicating with the electromyograph 10 and smile detection device 20.
The drive device 1008 is a device for setting the storage medium 1009. The storage medium 1009 includes a medium such as a CD-ROM, a floppy disk, an optical magnetic disk, or the like, which optically, electrically, or magnetically records information. The storage medium 1009 may include a semiconductor memory or the like in which information is recorded electrically, such as EPROM (Erasable Programmable Read Only Memory: erasable programmable read only memory) or flash memory.
The various programs installed in the auxiliary storage device 1004 are installed by being installed in the drive device 1008 through the distributed storage medium 1009, for example, and the various programs recorded in the storage medium 1009 are read out by the drive device 1008. Alternatively, various programs to be installed in the auxiliary storage device 1004 may be installed by being downloaded from a network via the I/F device 1007.
The present invention has been described in detail with reference to the examples, but the present invention is not limited to the above-described specific embodiments, and various modifications and changes can be made within the scope of the present invention as set forth in the claims.
The international application claims that the entire contents of japanese patent application No. 2021-043016 are incorporated herein by reference into the international application based on the priority of japanese patent application No. 2021-043016 filed on 3 months of 2021.
Description of the reference numerals
1. Smiling face detection system
10. Myoelectric potential measurer
20. Smiling face detection device
101. Measuring unit
102. Registration unit
103. Judgment part
104. Output unit
105. Electromyogram data storage unit
1001 CPU
1002 ROM
1003 RAM
1004. Auxiliary storage device
1005. Display device
1006. Operating device
1007 I/F device
1008. Driving device
1009. Storage medium
1010. Measuring device
Claims (12)
1. A myoelectric potential measuring instrument for measuring myoelectric potential, comprising:
a determination unit configured to determine whether or not a difference between the characteristic amount of the myoelectric potential measured by the myoelectric potential measuring device and the characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive is within a predetermined range; and
And an output unit configured to output the difference in value within a predetermined range or outside the predetermined range.
2. The electromyography apparatus of claim 1,
the characteristic amount of the myoelectric potential further includes information of the magnitude of the myoelectric potential, the pattern of change with time of the myoelectric potential, the speed of descent, a combination of a plurality of kinds of the information, and the average and deviation among a plurality of places of the face of the user of the information.
3. The electromyography apparatus of claim 1,
the characteristic amount of the myoelectric potential is an integral value of the myoelectric potential everywhere on the face of the user.
4. The electromyography apparatus of claim 1,
the characteristic amount of the myoelectric potential is a speed at which the myoelectric potential at each of a plurality of places on the face of the user reaches a maximum value.
5. The electromyography apparatus of claim 1,
the characteristic amount of the myoelectric potential is the intensity of the correlation of the myoelectric potential at the periphery of the eye with the myoelectric potential at least one of the zygomatic small muscle, the zygomatic large muscle, and the laugh muscle.
6. The electromyography apparatus according to any one of claims 1 to 5,
the output unit immediately notifies the user based on the result of the determination unit.
7. The electromyography apparatus according to any one of claims 1 to 6,
the output section notifies the user by generating sound, vibration, light, a combination thereof.
8. The electromyography apparatus according to any one of claims 1 to 7,
the predetermined range is a range decided based on the result of machine learning.
9. The electromyography apparatus according to any one of claims 2 to 4,
the plurality of sites is more than 2 sites including at least one of a circumference of an eye, a zygomatic small muscle, a zygomatic large muscle, and a laugh muscle.
10. A method performed by a myoelectric potential meter for measuring a myoelectric potential, comprising:
judging whether or not a difference between the characteristic amount of the myoelectric potential measured by the myoelectric potential measuring device and the characteristic amount of the myoelectric potential of the smiling face objectively judged to be attractive is within a predetermined range; and
And outputting the difference in the predetermined range or out of the range.
11. A system including a myoelectric potential meter for measuring a myoelectric potential and a computer, comprising:
a determination unit configured to determine whether or not a difference between the characteristic amount of the myoelectric potential measured by the myoelectric potential measuring device and the characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive is within a predetermined range; and
And an output unit configured to output the difference in value within a predetermined range or outside the predetermined range.
12. A method for supporting the appearance of an attractive smiling face by using a myoelectric potential meter for measuring myoelectric potential, wherein,
the myoelectric potential meter includes:
a determination unit configured to determine whether or not a difference between the characteristic amount of the myoelectric potential measured by the myoelectric potential measuring device and the characteristic amount of the myoelectric potential of the smiling face objectively determined to be attractive is within a predetermined range; and
An output unit configured to output the difference within a predetermined range or outside the predetermined range,
the method comprises the following steps:
a step of causing the myoelectric potential measuring device to measure the myoelectric potential of the face of the user; and
And notifying the user of the attractive smiling face based on the output of the electromyography.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2021-043016 | 2021-03-17 | ||
| JP2021043016 | 2021-03-17 | ||
| PCT/JP2022/009796 WO2022196419A1 (en) | 2021-03-17 | 2022-03-07 | Myoelectric potential measuring instrument, method, and system |
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| Publication Number | Publication Date |
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| CN116887754A true CN116887754A (en) | 2023-10-13 |
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| CN202280015517.0A Pending CN116887754A (en) | 2021-03-17 | 2022-03-07 | Myoelectric potential measurer, method and system |
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| JP (1) | JPWO2022196419A1 (en) |
| CN (1) | CN116887754A (en) |
| WO (1) | WO2022196419A1 (en) |
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| JP7477000B1 (en) | 2023-02-22 | 2024-05-01 | Smk株式会社 | Muscle activity analysis device, muscle activity analysis method, and muscle activity analysis program |
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| JP5574407B2 (en) * | 2010-01-14 | 2014-08-20 | 国立大学法人 筑波大学 | Facial motion estimation apparatus and facial motion estimation method |
| JP6521778B2 (en) * | 2015-07-15 | 2019-05-29 | Kddi株式会社 | Program, terminal and system for giving emotional identifier to application using myoelectric signal |
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2022
- 2022-03-07 JP JP2023506985A patent/JPWO2022196419A1/ja active Pending
- 2022-03-07 WO PCT/JP2022/009796 patent/WO2022196419A1/en active Application Filing
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| JPWO2022196419A1 (en) | 2022-09-22 |
| WO2022196419A1 (en) | 2022-09-22 |
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