CN216455039U - Wearable emotion state recognition device based on electroencephalogram signal - Google Patents
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Abstract
The utility model discloses a wearable emotion state recognition device based on an electroencephalogram signal, relates to the technical field of electroencephalogram signal analysis, and aims to improve the accuracy of electroencephalogram signal acquisition and analysis. Wearable emotion state recognition device based on brain electrical signal includes: the collecting electrode module takes a head band as a carrier; the host module is used for preprocessing the electroencephalogram signals and communicating the electroencephalogram signals; the upper computer analyzes the electroencephalogram signals; and an emotion indicating module. When the wearable emotion state recognition device based on the electroencephalogram signals is in a wearing state of a user, the eight acquisition electrodes are in one-to-one corresponding contact with two positions of the frontal lobe, four positions of the temporal lobe and two positions of the occipital lobe of the human body respectively.
Description
Technical Field
The utility model relates to the technical field of emotion classification based on electroencephalogram signals, in particular to a wearable emotion state recognition device based on the electroencephalogram signals.
Background
Among the means for studying emotion, electroencephalogram signals are regarded by many researchers as being of high time resolution and being not disguised, and are one of the common methods for studying emotion. The brain areas related to emotion are widely distributed, and the response amplitude of different brain areas to different emotions is different. Based on multi-channel electroencephalogram data, the electroencephalogram characteristics of all brain areas are integrated, and various scholars have obtained a plurality of valuable achievements.
At present, under the condition of adopting multi-channel electroencephalogram emotion classification, if a 32-bit electrode channel is adopted, although the signal sampling rate is high, a plurality of problems exist. For example, the manufacturing and using costs of the multi-channel electroencephalogram signal acquisition device are high, up to 32 acquisition electrodes are needed, and meanwhile, professional personnel are needed to assist in the installation and signal acquisition of the debugging device. In addition, from the aspect of signal accuracy, signal interference is generated among the acquisition electrodes, so that the contribution degree of a large number of acquisition electrodes in the signal acquisition process is low, and the effectiveness of the acquired electroencephalogram signals is not high.
SUMMERY OF THE UTILITY MODEL
The utility model aims to provide a wearable emotion state recognition device based on electroencephalogram signals, which is used for improving the accuracy of electroencephalogram signal acquisition and analysis.
The utility model provides a wearable emotion state recognition device based on electroencephalogram signals, which comprises: the system comprises an acquisition electrode module with a headband as a carrier, a host module for preprocessing and communicating electroencephalogram signals, an upper computer for analyzing the electroencephalogram signals and an emotion indicating module. The collecting electrode module is worn on the head of a user to collect electroencephalogram signals of the user, and the host module is arranged on the carrier, is respectively and electrically connected with the collecting electrode module and the emotion indicating module, and is communicated with an upper computer. The collecting electrode module comprises eight collecting electrodes which are distributed at the positions corresponding to the forehead, two sides of the head and the hindbrain of the human body. When the wearable emotion state recognition device based on the electroencephalogram signals is in a wearing state of a user, the eight acquisition electrodes are in one-to-one corresponding contact with two positions of the frontal lobe, four positions of the temporal lobe and two positions of the occipital lobe of the human body respectively.
Compared with the prior art, in the wearable emotion state recognition device based on the electroencephalogram signals, the eight acquisition electrodes and the host module are arranged on the carrier. The positions of the eight-channel acquisition electrode module correspond to two positions of the frontal lobe, four positions of the temporal lobe and two positions of the occipital lobe one by one. When the wearable emotion state recognition device based on the electroencephalogram signals is in a wearing state of a user, the eight acquisition electrodes are in one-to-one corresponding contact with the two positions of the frontal lobe, the four positions of the temporal lobe and the two positions of the occipital lobe, and the electroencephalogram signals of the eight positions are acquired respectively. The host module and the upper computer sequentially process the electroencephalogram signals to obtain the emotional state of the user, and the emotional state of the user is displayed through the emotion indicating module, so that the emotional state of the user can be intuitively known. The wearable emotion state recognition device based on the electroencephalogram signals is simple in structure and low in manufacturing and using cost. Meanwhile, the quantity of the collecting electrodes is reduced, invalid signals are reduced, the electroencephalogram signal collecting accuracy is improved, the accuracy of the host module and the upper computer on the electroencephalogram signal analysis result is improved, and the workload of the host module and the upper computer is reduced.
Drawings
The accompanying drawings, which are included to provide a further understanding of the utility model and are incorporated in and constitute a part of this specification, illustrate embodiments of the utility model and together with the description serve to explain the utility model and not to limit the utility model. In the drawings:
FIG. 1 is an electrode distribution diagram of a multi-channel EEG signal acquisition device in the prior art;
fig. 2 is a wearing schematic diagram of the wearable emotion state recognition apparatus based on electroencephalogram signals according to the embodiment of the present invention;
fig. 3 is a block diagram of a wearable emotion state recognition apparatus based on electroencephalogram signals according to an embodiment of the present invention;
fig. 4 is a schematic partial structure diagram of a wearable emotion state recognition apparatus based on an electroencephalogram signal according to an embodiment of the present invention;
FIG. 5 is a prior art emotion recognition classification map;
fig. 6 is a flowchart illustrating an emotional state recognition method according to an embodiment of the present invention.
Detailed Description
In order to facilitate clear description of technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish the same items or similar items having substantially the same functions and actions. For example, the first threshold and the second threshold are only used for distinguishing different thresholds, and the sequence order of the thresholds is not limited. Those skilled in the art will appreciate that the terms "first," "second," etc. do not denote any order or quantity, nor do the terms "first," "second," etc. denote any order or importance.
It is to be understood that the terms "exemplary" or "such as" are used herein to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.
In the present invention, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, a and b combination, a and c combination, b and c combination, or a, b and c combination, wherein a, b and c can be single or multiple.
The emotion plays an important role in daily life, and positive emotion can not only improve subjective happiness, but also promote physical and psychological health. In contrast, the physical and mental health and working state of a person are affected by negative emotions.
At present, among a plurality of means for researching emotion, electroencephalogram signals are paid more and more attention by researchers due to the characteristics of high time resolution and unsusceptibility to disguising. Analyzing the electroencephalogram signals is one of the common methods in emotion research. The electroencephalogram signals related to the emotion are distributed in different areas of the head, the areas are wide, and the response amplitude of the different areas of the head to different emotions is different to a certain extent.
In the prior art, a certain research result is achieved in the aspect of dual-channel emotion classification. For example: by means of the brain electrical signals of the two channels on the forehead, the discrimination of happy emotions and sad emotions can reach 66% under the condition that the best feature and classifier are used. The result means that the two-channel electroencephalogram signals can be subjected to emotion classification, but the method has certain limitation and unsatisfactory classification effect.
However, if the user wants to obtain a more accurate emotional state, more electroencephalograms of different brain areas need to be collected and analyzed. In the prior art, on the basis of multi-channel electroencephalogram data, electroencephalogram characteristics of all brain areas are integrated, and various scholars have obtained a plurality of valuable achievements.
FIG. 1 illustrates an electrode distribution diagram of a multi-channel EEG signal acquisition device in the prior art. Referring to fig. 1, in the case of multi-channel electroencephalogram emotion classification, for example: with 32-bit electrode channels or 64-bit electrode channels, there are problems, although the signal sampling rate is high. For example: the manufacturing and using cost of the multi-channel electroencephalogram signal acquisition device is high, 32 acquisition electrodes or 64 acquisition electrodes are needed, and meanwhile, professional personnel are needed to assist in installation and signal acquisition of the debugging device. In addition, from the aspect of signal accuracy, signal interference is generated among the acquisition electrodes, so that the contribution degree of a large number of acquisition electrodes in the signal acquisition process is low, and the effectiveness of the acquired electroencephalogram signals is not high.
In order to solve the technical problem, the embodiment of the utility model provides a wearable emotion state recognition device based on an electroencephalogram signal. Fig. 2 illustrates a wearing schematic diagram of the wearable emotion state recognition apparatus based on electroencephalogram signals provided by the embodiment of the present invention, fig. 3 illustrates a structural block diagram of the wearable emotion state recognition apparatus based on electroencephalogram signals provided by the embodiment of the present invention, and fig. 4 illustrates a structural schematic diagram of the wearable emotion state recognition apparatus based on electroencephalogram signals provided by the embodiment of the present invention.
Referring to fig. 2 and 3, the wearable emotion state recognition apparatus based on electroencephalogram signals provided by the embodiment of the present invention may include: the device comprises an acquisition electrode module taking a head band as a carrier, a host module for preprocessing and communicating electroencephalogram signals, an upper computer for analyzing the electroencephalogram signals and an emotion indicating module.
In a possible implementation manner, referring to fig. 3, since the wearable emotion state recognition apparatus based on electroencephalogram needs to contact with the head of the user during the process of acquiring electroencephalogram signals, the carrier 2 may be a ring-shaped structure, or a belt-shaped structure that can form a ring after being closed, but is not limited thereto.
In one example, the carrier 2 may be a flexible carrier. For example: the flexible carrier may be a tape carrier or a ring carrier. The material of the flexible carrier may be a silica gel material or a fiber material, but is not limited thereto.
In another example, the carrier 2 is a rigid carrier, and the rigid carrier 2 is a ring-shaped carrier. The material of the rigid carrier 2 may be a plastic material, but is not limited thereto.
In a possible implementation manner, referring to fig. 4, the eight-channel collecting electrode module may include eight collecting electrodes electrically connected to the host module, and the eight collecting electrodes are distributed at positions corresponding to the forehead, two sides of the head, and the back brain of the human body. When the wearable emotion state recognition device based on the electroencephalogram signals is in a wearing state of a user, the positions of the eight-channel acquisition electrode modules correspond to the two positions of the frontal lobe, the four positions of the temporal lobe and the two positions of the occipital lobe one by one, and each acquisition electrode can be a dry electrode or a wet electrode patch. That is to say, the eight collecting electrodes included in the eight-channel collecting electrode module 3 provided in the embodiment of the present invention may be dry electrodes, wet electrode patches, or both dry electrodes and wet electrode patches. It is to be understood that dry and wet electrode patches are broadly dry and wet electrode patches. Compared with the prior art, the wearable emotion state recognition device based on the electroencephalogram signals reduces the number of the acquisition electrodes and reduces the manufacturing cost. Meanwhile, the distance between the collecting electrodes in each area is relatively long, so that the interference of signals generated among the collecting electrodes can be reduced, and the effectiveness of the electroencephalogram signals collected by the collecting electrodes is further improved.
It should be understood that the electroencephalogram signals of different regions of the head have different response contribution degrees to the emotion, and therefore, the electroencephalogram signals of the region having a larger response contribution degree to the emotion need to be acquired. In practical application, the preset value may be 3%. That is, the regions having a response contribution degree of more than 3% are the two positions of the frontal lobe, the four positions of the temporal lobe, and the two positions of the occipital lobe. The response contribution degree refers to the amplitude of the waveform of the electroencephalogram signal obtained by processing the electroencephalogram signal acquired by the eight-channel acquisition electrode module 3 by the host module. The preset area in the embodiment of the present invention may be two positions of the frontal lobe, four positions of the temporal lobe and two positions of the occipital lobe of the head of the user.
In practical applications, the power supply is used to provide power to the host module. The power source may be a dry cell battery or a rechargeable battery, but is not limited thereto.
In one example, for a user with hair, the eight-channel collecting electrode module 3 may be selected to be a dry electrode because the eight-channel collecting electrode module 3 may be blocked from hair when in contact with the scalp. Whether a capacitive dry electrode or an impedance dry electrode is used may be selected according to actual conditions, and embodiments of the present invention are not particularly limited in this respect.
In another example, for a user with a head, the eight-channel collecting electrode module may be a wet electrode patch for all since the eight-channel collecting electrode module 3 may be in direct contact with the scalp.
In a possible implementation, referring to fig. 4, the eight collecting electrodes included in the eight-channel collecting electrode module 3 are detachably disposed on the side of the carrier 2 contacting the head of the user, so as to facilitate replacement.
In a possible implementation manner, referring to fig. 3, the host module may include: a pre-processing circuit, a controller 44 electrically connected to the pre-processing circuit, and a communication interface 45. Each collecting electrode is electrically connected with the preprocessing circuit, and the emotion indicating module 46 and the communication interface 45 are electrically connected with the controller 44. The preprocessing circuit may be configured to preprocess the electroencephalogram signals collected by each of the collection electrodes and transmit the preprocessed electroencephalogram signals to the controller 44. The controller 44 performs secondary processing on the preprocessed electroencephalogram signal to obtain a oscillogram of the electroencephalogram signal, and transmits the oscillogram of the electroencephalogram signal to the upper computer 1 by using the communication interface 45, or receives the emotional state processed by the upper computer 1 by using the communication interface 45.
In one example, referring to fig. 3, the preprocessing circuit may include: a signal amplification circuit 41, a filter circuit 42, and an analog-to-digital conversion circuit 43. The input end of the signal amplifying circuit 41 is electrically connected with the eight-channel collecting electrode module 3, the output end of the signal amplifying circuit 41 is electrically connected with the input end of the filter circuit 42, the output end of the filter circuit 42 is electrically connected with the analog-to-digital conversion circuit 43, and the output end of the analog-to-digital conversion circuit 43 is electrically connected with the controller 44.
The signal amplification circuit 41 can be used for amplifying the electroencephalogram signals collected by the eight-channel collecting electrode module 3. The filter circuit 42 is used for reducing alternating current components in the amplified electroencephalogram signal as much as possible, and retaining direct current components in the electroencephalogram signal, so that the voltage ripple coefficient of the filtered electroencephalogram signal is reduced, and the waveform becomes smoother. The electroencephalogram signals acquired by the eight-channel acquisition electrode module 3 are analog signals, however, the controller 44 can only process digital signals in general. The analog-to-digital conversion circuit 43 is used for converting the analog signal into a digital signal, so that the subsequent controller 44 can analyze the electroencephalogram signal conveniently.
In one example, referring to FIG. 3, the controller 44 may be an ADS129X family physiological signal processing chip that may support eight low noise programmable gain amplifiers and eight high resolution synchronous sampling analog-to-digital converters, and support 250HZ/S data samples.
In one example, the communication interface 45 may include one or both of a wired communication interface 45 and a wireless communication interface 45. That is, the host module may have only the wired communication interface 45 or the wireless communication interface 45, or the host module may have both the wired communication interface 45 and the wireless communication interface 45.
In the practical application process, the host module can be detachably arranged on the carrier 2 in the form of a packaging circuit board so as not to influence the wearing of a user. For example: the host module may be provided at a position of the carrier 2 corresponding to the rear, left or right side of the head. When any one of the host module, the carrier 2 or the eight-channel collecting electrode module is damaged, the electrode module can be replaced, and more cost can be saved.
In a possible implementation manner, the upper computer 1 may be a terminal device such as a desktop computer, a tablet computer, or the like, which has at least a communication function, a data processing function, and a graphical user interface. The upper computer 1 is internally provided with at least one emotion state recognition algorithm for analyzing and processing a oscillogram of an electroencephalogram signal of the upper computer 1. For example: the emotional state recognition algorithm built in the upper computer 1 may at least include a feature extraction algorithm and an emotion classification algorithm, and is used for processing the oscillogram of the electroencephalogram signal to obtain the emotional state of the user, but is not limited thereto. The upper computer 1 may have a communication interface 45, and the communication interface 45 may include one or both of a wired communication interface 45 and a wireless communication interface 45. That is, the upper computer 1 may have only the wired communication interface 45 or the wireless communication interface 45, and the upper computer 1 may also have both the wired communication interface 45 and the wireless communication interface 45.
In an actual application process, the feature values extracted by the feature extraction algorithm may include: the method includes, but is not limited to, an original feature classification level effect, an energy ratio and differential entropy feature classification effect, different frequency band differential entropy feature classification effects, and different brain region differential entropy feature classification effects. And obtaining the corresponding emotional state by adopting an emotion classifier and utilizing the characteristic values. The emotion classifier has a corresponding emotion classification algorithm, and the emotion classifier may include: support vector machine, decision tree BP neural network, nearest neighbor algorithm, but not limited thereto. By adopting the wearable emotion state recognition device based on the electroencephalogram signals, the emotion state recognition accuracy is 60% -90%.
In a possible implementation manner, the upper computer 1 may further have a data statistics function. That is to say, the emotional state of the user in the preset time period can be counted and analyzed through the upper computer 1, so as to obtain the emotional analysis report of the user in the preset time period. For example: the user identifies emotional states for several times in the month/week, and the user has different emotional states in the time period, and has corresponding emotional states and health care reminding in the time periods.
In one possible implementation, referring to fig. 3, the emotion indicating module 46 may include an audio and/or visual indication, and the turning on and off of the indication is controlled by the controller. After the controller 44 receives the emotional state transmitted by the upper computer 1, the emotion indicating module 46 may be controlled to perform voice prompt or picture display on the processing result, so as to display the emotional state of the user.
In one example, referring to FIG. 3, emotion indication module 46 may be an audio playback component. For example: the audio playing component can be a buzzer or a loudspeaker.
In another example, referring to fig. 3, the emotion indicating module 46 may be a visual playing component, and the visual playing component is an indicator light or a display.
Fig. 5 illustrates an emotional state classification diagram provided by an embodiment of the utility model. Referring to fig. 5, in practical application, the emotion indicating module 46 may be four LED lamps located at the front side of the carrier 2 for displaying the emotional state of the user. For example: when the emotional state of the user is happy, displaying a cyan LED lamp; when the emotional state of the user is calm, a green LED lamp is displayed; when the emotional state of the user is sad, the LED lamp displays gray; when the emotional state of the user is fear, an orange LED lamp is displayed. Another example is: the emotional state of the user can also be indicated by voice, for example, when the emotion of the user is happy, the 'your current mood is very pleasant and is really beautiful time' is sent out by a loudspeaker. Or, when the user is sad, send "i feel you are a little sad and do not have a strong force on the body", but not limited to this.
In a possible implementation manner, referring to fig. 1, the wearable emotional state recognition device based on electroencephalogram signals may further include a memory 47 electrically connected to the controller 44, for storing a waveform diagram of the electroencephalogram signals processed by the controller 44. The memory 47 may be a memory 47 in a broad sense, and may have a storage function, which is not limited in this embodiment of the present invention.
In practical applications, when the host module only includes the wired communication interface 45, the waveform of the electroencephalogram signal after the secondary processing by the controller 44 can be directly stored in the memory 47. When the upper computer 1 needs to call the oscillogram of the electroencephalogram signal after the secondary processing by the controller 44, the host module can be electrically connected with the upper computer 1 through the data transmission line. When the host module at least comprises the wireless communication interface 45, the oscillogram of the brain electrical signals after the secondary processing by the controller 44 can be transmitted to the host computer 1 in real time.
The embodiment of the utility model also provides an emotion state identification method, and the wearable emotion state identification device based on the electroencephalogram signals is applied. Fig. 6 illustrates a flow chart of an emotional state recognition method according to an embodiment of the present invention. Referring to fig. 6, the emotional state recognition method may include the steps of:
step S101: whether the wearable emotion recognition device based on the electroencephalogram signals is worn correctly by a user is detected through the host module.
Step S201: and acquiring the electroencephalogram signals of the corresponding positions through the eight acquisition electrodes.
In the practical application process, before the wearable emotion state recognition device based on the electroencephalogram signals collects the electroencephalogram signals, whether the user correctly wears the wearable emotion state recognition device based on the electroencephalogram signals needs to be judged. When the user correctly wears the wearable emotion state recognition device based on the electroencephalogram signal, in a fixed time, for example: in 10S, the eight collecting electrodes 31 included in the eight-channel collecting electrode module 3 can collect corresponding electroencephalogram signals. If any one of the collecting electrodes 31 does not collect the electroencephalogram signal, it indicates that the user does not wear the wearable emotion state recognition apparatus based on the electroencephalogram signal correctly. At this point, controller 44 may control emotion indication module 46 to issue a corresponding prompt. For example: the buzzer or the loudspeaker gives out alarm sound, or the indicator light displays a red light to indicate warning.
Step S301: and analyzing the electroencephalogram signals through an upper computer to obtain the emotional state of the user.
Step S401: and displaying the emotional state of the user through an emotion indicating module.
In the practical application process, the host module processes the eight-channel electroencephalogram signals collected by the eight-channel collecting electrode module 3 to obtain an electroencephalogram waveform diagram, and sends the electroencephalogram waveform diagram to the upper computer 1 through the communication interface 45, and the upper computer 1 classifies the emotional state of the electroencephalogram waveform diagram by using a built-in emotion classification algorithm. After the emotional state classification result is obtained, the upper computer 1 sends the emotional state result to the controller 44 of the electroencephalogram processing signal, and the controller 44 controls the emotion indicating module 46 to feed back the emotional state, so that the user can visually know the emotional state of the user.
In a possible implementation manner, the emotional state recognition method may further include: and the upper computer performs statistical analysis on the emotional state of the user in a preset time period to obtain an emotional analysis report of the user in the preset time period.
In practical application, the above steps may be performed before step S401, after step S301, or after step S401.
While the utility model has been described in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a review of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the word "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.
While the utility model has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the utility model. Accordingly, the specification and figures are merely exemplary of the utility model as defined in the appended claims and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the utility model. It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the utility model. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. The utility model provides a wearable emotion state recognition device based on brain electrical signal which characterized in that includes: the collecting electrode module takes a head band as a carrier; the host module is used for preprocessing the electroencephalogram signals and communicating the electroencephalogram signals; the upper computer analyzes the electroencephalogram signals; and an emotion indicating module; wherein the content of the first and second substances,
the collection electrode module is worn on the head of a user to collect electroencephalograms of the user, and the host module is arranged on the carrier, is respectively and electrically connected with the collection electrode module and the emotion indication module, and is communicated with the upper computer;
the acquisition electrode module is an eight-channel acquisition electrode module, and the eight-channel acquisition electrode module comprises eight acquisition electrodes which are distributed at positions corresponding to the forehead, two sides of the head and the back brain of a human body;
when the wearable emotion state recognition device based on the electroencephalogram signals is in a wearing state of a user, the eight acquisition electrodes are in one-to-one corresponding contact with two positions of the frontal lobe, four positions of the temporal lobe and two positions of the occipital lobe of the human body respectively.
2. The electroencephalogram signal-based wearable emotional state recognition device according to claim 1, wherein each of the acquisition electrodes is a dry electrode or a wet electrode patch.
3. The electroencephalograph signal-based wearable emotional state recognition device according to claim 1, wherein the host module comprises a preprocessing circuit and a controller electrically connected to the preprocessing circuit, each of the acquisition electrodes is electrically connected to the preprocessing circuit, and the emotion indicating module is electrically connected to the controller.
4. The electroencephalogram signal-based wearable emotion state recognition device of claim 3, wherein the preprocessing circuit comprises a signal amplification circuit, a filter circuit, and an analog-to-digital conversion circuit;
the input end of the signal amplification circuit is electrically connected with the eight-channel acquisition electrode module, the output end of the signal amplification circuit is electrically connected with the input end of the filter circuit, the output end of the filter circuit is electrically connected with the analog-to-digital conversion circuit, and the output end of the analog-to-digital conversion circuit is electrically connected with the controller.
5. The electroencephalogram signal-based wearable emotional state recognition device according to claim 3, further comprising a memory electrically connected to the controller and storing the preprocessed electroencephalogram signal of the host module.
6. The electroencephalogram signal-based wearable emotional state recognition device according to claim 3, wherein the host module further comprises a communication interface electrically connected to the controller, and the communication interface comprises one or both of a wired communication interface and a wireless communication interface.
7. The electroencephalogram signal-based wearable emotional state recognition device according to claim 3, wherein the emotion indication module comprises audio and/or visual indications, and the controller controls the turning on and off of the indications.
8. The electroencephalogram signal-based wearable emotion state recognition device of claim 7, wherein the emotion indication module includes an audio playing component, and the audio playing component is a buzzer or a speaker; or the like, or, alternatively,
the emotion indicating module comprises a visual playing component which is an indicating lamp or a display.
9. The electroencephalogram signal-based wearable emotional state recognition device according to claim 1, wherein the upper computer is a device having at least a communication function and a data processing function, and the upper computer has a graphical user interface.
10. The electroencephalogram signal-based wearable emotion state recognition device of claim 1, wherein at least one emotion state recognition algorithm is built in the upper computer.
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| CN202120644189.3U Expired - Fee Related CN216455039U (en) | 2021-03-30 | 2021-03-30 | Wearable emotion state recognition device based on electroencephalogram signal |
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