CN106175752B - Brain wave signal acquisition device and method, and state evaluation system and method - Google Patents
Brain wave signal acquisition device and method, and state evaluation system and method Download PDFInfo
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Abstract
The invention belongs to the communication technology, and provides brain wave signal acquisition equipment and method and a state evaluation system and method, wherein the equipment comprises: the signal acquisition unit is used for acquiring brain wave signals through the sensor electrode group; the processing unit is used for receiving the collected brain wave signals, sequentially amplifying, filtering and performing analog-to-digital conversion on the collected brain wave signals to form brain wave data signals, and sending the brain wave data signals; and the signal output unit is used for receiving the brain wave data signals, sequentially carrying out digital filtering and frequency shift keying modulation on the brain wave data signals to form brain wave data, and sending the brain wave data through an audio interface. So as to evaluate the emotion and fatigue state of the individual to be tested according to the brain wave data, and enable the user to obtain the real-time brain wave data of the individual through the wearable device, and the wearable brain wave data is convenient to operate and easy to wear.
Description
Technical Field
The invention belongs to the field of medical data, and particularly relates to brain wave signal acquisition equipment and method and a state evaluation system and method.
Background
Fatigue refers to the state of a body that tends to decline in labor efficiency due to prolonged or overstrained physical or mental work under certain environmental conditions. In medicine, fatigue can be classified into physiological fatigue and psychological fatigue according to the nature of fatigue, and the evaluation of fatigue state can be performed by subjective and objective methods. The subjective evaluation method mainly evaluates the fatigue degree of a testee according to a subjective questionnaire, a self-recording table, a sleep habit questionnaire, a Stanford sleep scale table and the like. The objective evaluation method is mainly from the medical perspective, and the changes of some indexes in the aspects of human behavior, physiology and biochemistry of a human body of a testee are tested by means of auxiliary tools such as medical instruments and equipment, so that the fatigue degree of the testee is determined. Although the subjective evaluation method has the advantages of simple and direct operation, low cost, no interference to task completion, easy acceptance and the like, the subjective evaluation method is a widely adopted method for evaluating fatigue, but the method is difficult to quantify the grade and degree of fatigue, and the result is often unsatisfactory due to obvious difference of understanding of each person. In recent years, detection and analysis techniques such as electroencephalogram, electrooculogram, electrocardiogram and the like have been greatly advanced, and in the research of mental fatigue, electroencephalogram has become one of the most extensive indicators for evaluating changes in the central nervous system, but how to process the obtained electroencephalogram into objective and effective data to evaluate the individual state is a problem to be solved.
Disclosure of Invention
The embodiment of the invention aims to provide brain wave signal acquisition equipment and method and a state evaluation system and method, and aims to solve the problems that in the prior art, the accuracy of acquiring brain wave data is low, the acquisition mode is not convenient and fast, the pertinence of an evaluation result based on the acquired brain wave data is not strong, and the misjudgment rate is too high.
The present invention has been made in view of the above problems, and it is an object of the present invention to provide a brain wave signal acquiring apparatus including:
the signal acquisition unit is used for acquiring brain wave signals through the sensor electrode group;
the processing unit is used for receiving the collected brain wave signals, sequentially amplifying, filtering and performing analog-to-digital conversion on the collected brain wave signals to form brain wave data signals, and sending the brain wave data signals;
and the signal output unit is used for receiving the brain wave data signals, sequentially carrying out digital filtering and frequency shift keying modulation on the brain wave data signals to form brain wave data, and sending the brain wave data through an audio interface.
An embodiment of the present invention further provides a state evaluation system, which includes a brain wave signal acquisition device and an evaluation device, wherein the brain wave signal acquisition device includes:
the signal acquisition unit is used for acquiring brain wave signals through the sensor electrode group;
the processing unit is used for receiving the collected brain wave signals, sequentially amplifying, filtering and performing analog-to-digital conversion on the collected brain wave signals to form brain wave data signals, and sending the brain wave data signals;
the signal output unit is used for receiving the brain wave data signals, sequentially carrying out digital filtering and frequency shift keying modulation on the brain wave data signals to form brain wave data, and sending the brain wave data through an audio interface;
the evaluation device includes:
a signal receiving unit, configured to receive the brain wave data, where the brain wave data includes, according to a frequency band: alpha wave, beta wave, theta wave;
a fourier transform unit, configured to perform fourier transform on the brain wave data to obtain frequency band energy of a corresponding frequency band, where the frequency band energy includes: alpha wave frequency band energy, beta wave frequency band energy and theta wave frequency band energy;
the emotion and fatigue state characteristic value calculation unit is used for obtaining individual emotion and fatigue state characteristic values according to the frequency band energy of the corresponding frequency band, and the emotion and fatigue state comprises the following steps: the stimulation response intensity is the ratio of beta wave frequency band energy to alpha wave frequency band energy, the stimulation response is the difference value of the alpha wave frequency band energy of the left brain and the right brain of an individual, and the fatigue degree is the ratio of the sum of the alpha wave frequency band energy and the theta wave frequency band energy to the beta wave frequency band energy;
the emotion and fatigue state quantitative value calculation unit is specifically used for:
acquiring characteristic values of the emotion and fatigue states in a set time period, sampling the characteristic values of the emotion and fatigue states in the set time period, and forming a sequence;
calculating the curve length corresponding to each sequence according to the second sequence;
and obtaining the mean value of the curve length corresponding to each sequence, and further obtaining the fractal dimension value of the curve, wherein the fractal dimension value of the curve is the quantitative value of the emotion and fatigue state.
The embodiment of the invention further provides a brain wave signal acquisition method, which comprises the following steps:
collecting brain wave signals through a sensor electrode group, the sensor electrode group comprising: the sensor electrodes I are respectively arranged between the upper edges of the left and right ears of the human body and the hairline and used as input channels for collecting the brain waves of the temporal lobe, the sensor electrodes II are respectively arranged at the left and right auricles of the human body and close to earlobes and used as reference channels for collecting the brain waves of the temporal lobe, and the feedback electrodes are respectively arranged at the left and right external auditory canals of the human body;
receiving the collected brain wave signals, sequentially amplifying, filtering and carrying out analog-to-digital conversion on the collected brain wave signals to form brain wave data signals, and sending the brain wave data signals;
and receiving the brain wave data signals, sequentially carrying out digital filtering and frequency shift keying modulation on the brain wave data signals to form brain wave data, and sending the brain wave data through an audio interface.
The embodiment of the invention also provides a state evaluation method, which comprises the following steps:
collecting brain wave signals through a sensor electrode group; sequentially amplifying, filtering and carrying out analog-to-digital conversion on the collected brain wave signals to form brain wave data signals, and sending the brain wave data signals; the brain wave data signals are sequentially subjected to digital filtering and frequency shift keying modulation to form brain wave data, and the brain wave data comprises the following components according to frequency ranges: alpha wave, beta wave, theta wave;
carrying out Fourier transform on the electroencephalogram data to obtain frequency band energy of a corresponding frequency band, wherein the frequency band energy comprises: alpha wave frequency band energy, beta wave frequency band energy and theta wave frequency band energy;
obtaining characteristic values of individual emotion and fatigue states according to the frequency band energy of the corresponding frequency band, wherein the emotion and fatigue states comprise: the stimulation response intensity is the ratio of beta wave frequency band energy to alpha wave frequency band energy, the stimulation response is the difference value of the alpha wave frequency band energy of the left brain and the right brain of an individual, and the fatigue degree is the ratio of the sum of the alpha wave frequency band energy and the theta wave frequency band energy to the beta wave frequency band energy;
acquiring characteristic values of the emotion and fatigue states in a set time period, sampling the characteristic values of the emotion and fatigue states in the set time period, and forming a sequence; calculating the curve length corresponding to each sequence according to the second sequence; and obtaining the mean value of the curve length corresponding to each sequence, and further obtaining the fractal dimension value of the curve, wherein the fractal dimension value of the curve is the quantitative value of the emotion and fatigue state.
According to the brain wave signal acquisition equipment and the brain wave signal acquisition method provided by the embodiment of the invention, the sensor electrode group is used for acquiring the brain wave signals, the brain wave signals are processed to obtain the brain wave data, and the brain wave data is sent through the audio interface, so that the emotion and fatigue state of an individual to be detected can be evaluated according to the brain wave data, and a user can acquire the real-time brain wave data of the individual through wearing equipment, and the equipment and the method are convenient to operate and easy to wear.
The embodiment of the invention also provides a state evaluation system and method, which are characterized in that brain wave signals are collected through a sensor electrode group, the brain wave signals are processed to obtain brain wave data, the brain wave data are sent through an audio interface, then the brain wave data are further processed, frequency band energy of a corresponding frequency band is obtained according to the frequency band of the brain waves, and then characteristic values of the current emotion and fatigue state of an individual to be evaluated are obtained through calculation, the current emotion state, concentration level, relaxation level and other forms are reflected to the brain waves of the human body in a quantized form, the emotion and fatigue state is evaluated in a targeted manner, the misjudgment rate is reduced, and accurate evaluation of self emotion and fatigue state is realized.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a functional block diagram of a brain wave signal acquiring apparatus according to an embodiment of the present invention;
FIG. 2 is a functional block diagram of a state evaluation system provided by an embodiment of the present invention;
fig. 3 is a flowchart of a brain wave signal acquisition method according to an embodiment of the present invention;
FIG. 4 is a flow chart of a state evaluation method provided by an embodiment of the invention;
FIG. 5 is a waveform diagram of the response intensity to stimulation calculated by the state estimation method according to the embodiment of the present invention;
fig. 6 is a waveform diagram of a calculated likes-dislikes response to an event in a state assessment method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The Electroencephalogram (EEG) is a process in which a potential difference is formed between a cerebral cortex cell group when the brain is moving, and thus an electric current is generated outside the cerebral cortex cell group. It records the electrical wave changes during brain activity, which is a general reflection of the electrophysiological activity of brain neurons on the surface of the cerebral cortex or scalp.
The brain waves include, in terms of frequency: alpha wave (7-14Hz), beta wave (14-30Hz), theta wave (4-7 Hz). The brain electrical signals contain rich contents of activities including thinking, emotion, spirit and psychology, and can be distinguished from the electrical signal modes and frequencies thereof. Such as: when we are drowsy or in fatigue, the brain waves show that theta waves (4-7Hz) dominate; when people are in a daily waking state, the proportion of alpha waves (7-14Hz) is maintained at a common level; when the eyes are closed in a waking state, the alpha wave of the brain electricity is found to be greatly increased; under the conditions of relaxation and pleasure, the method has close relation with the proportion of alpha waves in the whole electroencephalogram distribution map; however, if the eyes are closed and the consciousness is fuzzy, the alpha wave disappears gradually; when people are in a normal waking state, the experience of surrounding environments including people, things and objects is mostly based on habitual alertness and reaction, monitoring and expecting that all things can happen as far as we know and wish, and electroencephalogram beta waves (14-30Hz) appear; in the daily life with the attention paid and the rapid pace, when people are nervous, anxious, excited or inattentive, the electric potential of the beta wave is stronger, and the state that the beta wave is always in the dominant position is fully displayed, which of course also indicates that the brain tends to be active, excited or excited. That is, the α wave (7-14Hz) in the brain waves is the main scale of the brain under low cognitive load, and when the brain is under low cognitive load, the frequency band energy of the frequency band corresponding to the α wave becomes stronger; beta waves (14-30Hz) in brain waves are the main scale of the brain under high cognitive load, and when the brain is under high cognitive load, the frequency band energy of the frequency band corresponding to the beta waves becomes stronger.
As shown in fig. 1, which is a schematic block diagram of a brain wave signal acquiring apparatus according to an embodiment of the present invention, only portions related to the embodiment of the present invention are shown for convenience of description, the brain wave signal acquiring apparatus according to an embodiment of the present invention including: signal acquisition unit 11, processing unit 12, and signal output unit 13, wherein:
and the signal acquisition unit 11 is used for acquiring brain wave signals through the sensor electrode group.
In this embodiment, the sensor electrode group includes: the sensor electrodes I are respectively arranged between the upper edges of the left and right ears of the human body and the hairline and used as input channels for collecting the brain waves of the temporal lobe, the sensor electrodes II are respectively arranged at the left and right auricles of the human body and close to earlobes and used as reference channels for collecting the brain waves of the temporal lobe, and the feedback electrodes are respectively arranged at the left and right external auditory canals of the human body.
The processing unit 12 is configured to receive the acquired brain wave signals, sequentially amplify, filter, and perform analog-to-digital conversion on the acquired brain wave signals to form brain wave data signals, and send the brain wave data signals.
In this implementation, the processing unit includes an amplifying and filtering module and an analog-to-digital conversion module, where: the amplifying and filtering module is used for amplifying the difference value between the input electrode and the reference electrode, inhibiting common-mode noise, obtaining the inverse value of the common-mode noise through the negative feedback circuit, and filtering through the filter; and the analog-to-digital conversion module is used for performing analog-to-digital conversion on the filtered brain wave signals and sending the converted brain wave data signals.
And the signal output unit 13 is configured to receive the electroencephalogram data signal, perform digital filtering and frequency shift keying modulation on the electroencephalogram data signal in sequence to form electroencephalogram data, and send the electroencephalogram data through an audio interface.
As shown in fig. 2, which is a schematic block diagram of a state evaluation system provided by an embodiment of the present invention, and only a part related to the embodiment of the present invention is shown for convenience of description, the system provided by the embodiment of the present invention includes a brain wave signal acquiring apparatus 21 and an evaluation apparatus 22, wherein the brain wave signal acquiring apparatus 21 includes:
the signal acquisition unit 211 is used for acquiring brain wave signals through the sensor electrode group;
the processing unit 212 is configured to receive the acquired brain wave signals, sequentially amplify, filter and perform analog-to-digital conversion on the acquired brain wave signals to form brain wave data signals, and send the brain wave data signals;
and the signal output unit 213 is configured to receive the brain wave data signal, perform digital filtering and frequency shift keying modulation on the brain wave data signal in sequence to form brain wave data, and send the brain wave data through an audio interface.
The evaluation device 22 includes:
a signal receiving unit 221, configured to receive the brain wave data, where the brain wave data includes, according to a frequency band: alpha wave, beta wave, theta wave;
a fourier transform unit 222, configured to perform fourier transform on the brain wave data to obtain frequency band energy of a corresponding frequency band, where the frequency band energy includes: alpha wave frequency band energy, beta wave frequency band energy and theta wave frequency band energy;
the emotion and fatigue state characteristic value calculation unit 223 is configured to obtain characteristic values of an individual emotion and fatigue state according to the frequency band energy of the corresponding frequency band, where the emotion and fatigue state includes: the stimulation response intensity is the ratio of beta wave frequency band energy to alpha wave frequency band energy, the stimulation response is the difference value of the alpha wave frequency band energy of the left brain and the right brain of an individual, and the fatigue degree is the ratio of the sum of the alpha wave frequency band energy and the theta wave frequency band energy to the beta wave frequency band energy;
the emotion and fatigue state quantitative value calculating unit 224 is specifically configured to:
acquiring characteristic values of the emotion and fatigue states in a set time period, sampling the characteristic values of the emotion and fatigue states in the set time period, and forming a sequence;
calculating the curve length corresponding to each sequence according to the second sequence;
and obtaining the mean value of the curve length corresponding to each sequence, and further obtaining the fractal dimension value of the curve, wherein the fractal dimension value of the curve is the quantitative value of the emotion and fatigue state.
In this embodiment, further, the evaluation device 22 further includes: evaluation data broadcasts unit 225 and evaluation data transmission unit 226, wherein:
and an evaluation data broadcasting unit 225 for broadcasting the evaluation data through an audio device according to the emotion and fatigue state quantized values.
An evaluation data transmitting unit 226 for transmitting the evaluation data according to the quantitative values of emotion and fatigue state.
In this embodiment, the brain wave signal acquiring apparatus 21 further includes an evaluation feedback unit 214, and the evaluation feedback unit 214 is configured to receive the evaluation data through an audio interface, demodulate the evaluation data, and feed back the evaluation data according to a corresponding relationship between a set evaluation level state and a display state of the brain wave signal generating apparatus.
As shown in fig. 3, which is a flowchart illustrating a brain wave signal acquiring method according to an embodiment of the present invention, and only a portion related to the embodiment of the present invention is shown for convenience of description, the embodiment of the present invention provides a brain wave signal acquiring method including:
in step S301, brain wave signals are collected by a sensor electrode group including: the sensor electrodes I are respectively arranged between the upper edges of the left and right ears of the human body and the hairline and used as input channels for collecting the brain waves of the temporal lobe, the sensor electrodes II are respectively arranged at the left and right auricles of the human body and close to earlobes and used as reference channels for collecting the brain waves of the temporal lobe, and the feedback electrodes are respectively arranged at the left and right external auditory canals of the human body;
in step S302, the collected brain wave signals are received, amplified, filtered, and analog-to-digital converted in sequence to form brain wave data signals, and the brain wave data signals are sent;
the method for sequentially amplifying, filtering and performing analog-to-digital conversion on the collected brain wave signals to form brain wave data signals specifically comprises the following steps:
amplifying the difference between the input electrode and the reference electrode, inhibiting common-mode noise, obtaining the reverse value of the common-mode noise through a negative feedback circuit, and filtering through a filter;
and performing analog-to-digital conversion on the filtered brain wave signals, and transmitting the converted brain wave data signals.
In step S303, the brain wave data signal is received, the brain wave data signal is subjected to digital filtering and frequency shift keying modulation in sequence to form brain wave data, and the brain wave data is sent through an audio interface.
As shown in fig. 4, which is a flowchart illustrating a state evaluating method provided by an embodiment of the present invention, and only a part related to the embodiment of the present invention is shown for convenience of description, the embodiment of the present invention provides a state evaluating method, including:
in step S401, brain wave signals are collected through a sensor electrode group; sequentially amplifying, filtering and carrying out analog-to-digital conversion on the collected brain wave signals to form brain wave data signals, and sending the brain wave data signals; the brain wave data signals are sequentially subjected to digital filtering and frequency shift keying modulation to form brain wave data, and the brain wave data comprises the following components according to frequency ranges: alpha wave, beta wave, theta wave;
in step S402, fourier transform is performed on the brain wave data to obtain frequency band energy of a corresponding frequency band, where the frequency band energy includes: alpha wave frequency band energy, beta wave frequency band energy and theta wave frequency band energy.
In this embodiment, the β wave is further divided into: beta is a1Wave, beta2Wave, beta3Wave, in particular, the beta1The frequency band of the wave is 14-16 Hz; beta is the same as2The frequency band of the wave is 16.5-20 Hz; beta is the same as3The frequency band of the wave is 20.5-28 Hz. Further, the frequency band energy of the corresponding frequency band may also be obtained according to fourier transform, where the frequency band energy of the corresponding frequency band includes: beta is a1Energy in the wave band, beta2Energy in the wave band, beta3Wave band energy.
In step S403, obtaining feature values of an individual emotion and fatigue state according to the frequency band energy of the corresponding frequency band, where the emotion and fatigue state includes: the stimulation response intensity is the ratio of beta wave frequency band energy to alpha wave frequency band energy, the stimulation response is the difference value of the alpha wave frequency band energy of the left brain and the right brain of an individual, and the fatigue degree is the ratio of the sum of the alpha wave frequency band energy and the theta wave frequency band energy to the beta wave frequency band energy.
In this embodiment, the characteristic values of the emotion and fatigue state of the individual are obtained according to the frequency band energy of the corresponding frequency band, the reaction strength to the stimulus is a ratio of the β -wave frequency band energy to the α -wave frequency band energy, and the calculation formula is:
the likes and dislikes of the event are the left brain of the individualThe difference between the energy of the alpha wave frequency band and the energy of the alpha wave frequency band of the right brain is calculated as follows: the reaction of the event on the likes and dislikes is left brain alpha wave frequency band energy-right brain alpha wave frequency band energy; the fatigue degree is the ratio of the sum of the energy of the alpha wave frequency band and the energy of the theta wave frequency band to the energy of the beta wave frequency band, and the calculation formula is as follows:
by using the above-described calculation expressions for the intensity of response to a stimulus, the like-or-dislike response to an event, and the fatigue level, waveform diagrams of the intensity of response to a stimulus, the like-or-dislike response to an event, and the fatigue level can be drawn over time. Fig. 5 shows a waveform diagram of the response intensity to the stimulus calculated in the state evaluation method provided by the embodiment of the invention, wherein, it is assumed that the center value of the waveform diagram of the response intensity to the stimulus (Arousal) of the individual X to be tested is a0If the value of the response intensity of the individual X to be tested to the stimulus is A at the time tt(ii) a Fig. 6 shows a waveform diagram of the above calculated adverse and active reactions to the event in the state evaluation method provided in the embodiment of the present invention, wherein, it is assumed that the center value of the waveform diagram of the adverse and active reactions (Valence) to the event of the individual X to be tested is V0Then at time t, the value of the response intensity of the individual X to be tested to the stimulus is Vt. Theoretically, when the emotion of the individual X to be measured is always balanced, the value of the intensity of the response to the stimulus: a. thet-A00, the value of the aversive response to the event: vt-V00. In this case, the waveform of the function that is always kept in balance will appear as a straight line parallel to the X axis in the corresponding waveform diagram, and in practical applications, the emotion of the individual X to be measured will deviate from balance, and accordingly, the waveform diagram of the response intensity to the stimulus (Arousal) and the waveform diagram of the reaction of likes and dislikes to the event (Valence) will appear as irregular curves in fig. 5 and 6.
In step S404, characteristic values of emotion and fatigue states are obtained in a set time period, and the characteristic values of the emotion and fatigue states are sampled in the set time period to form a sequence; calculating the curve length corresponding to each sequence according to the second sequence; and obtaining the mean value of the curve length corresponding to each sequence, and further obtaining the fractal dimension value of the curve, wherein the fractal dimension value of the curve is the quantitative value of the emotion and fatigue state.
Furthermore, in order to realize the consideration of the degree of change, the fractal dimension values of the individual response intensity to stimulation, the individual aversion response to events and the individual fatigue degree of the waveform curve are further respectively calculated, the degree of change of the individual emotion is obtained through fractal dimension, and the inaccuracy of linear results of characteristic values of the individual emotion and fatigue state is avoided.
In step S404, the calculation dimensionality is specifically: acquiring a characteristic value of an emotion and fatigue state of an individual in a set time period, sampling the characteristic value of the emotion and fatigue state in the set time period, and forming a sequence I, wherein the sequence I is recorded as: x (1), X (2), X (3) … … X (n);
introducing a scale k into the sequence I to form a sequence II, wherein the sequence II is represented as:
wherein, m ═ is (1,2, 3.. k);
and calculating the curve length corresponding to each sequence according to the second sequence, wherein the curve length calculation formula is as follows:
wherein, the normalization factor is;
obtaining a mean value of the curve lengths corresponding to each sequence, wherein the mean value (l (k)) is: when L (k) ° k-DAnd then obtaining the fractal dimension value of the curve, wherein the fractal dimension value is as follows:
for example, in a waveform plot of the intensity of response to a stimulus (Arousal), n samples are taken in the trend curve to form a sequence: x (1), X (2), X (3) … … X (n);
introducing a new scale k to construct a new sequence
if k is 4, then:
……
the length of the curve represented by each sequence can be calculated by the following formula:
l (k) is Lm(k) The average value of (a) of (b),
when L (k) ° k-DAnd then obtaining the fractal dimension value of the curve, wherein the fractal dimension value is as follows:
the fractal dimension value D obtained in the above calculation formula can be used to calculate the individual response intensity to stimuli, the individual aversion response to events, and the individual fatigue waveform curve quantitative values, thereby further evaluating the individual emotion and fatigue.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (3)
1. A system for evaluating emotion and fatigue states based on brain wave signals, comprising an acquiring brain wave signal device and an evaluating device, wherein the acquiring brain wave signal device comprises:
the signal acquisition unit is used for acquiring brain wave signals through the sensor electrode group;
the processing unit is used for receiving the collected brain wave signals, sequentially amplifying, filtering and performing analog-to-digital conversion on the collected brain wave signals to form brain wave data signals, and sending the brain wave data signals;
the signal output unit is used for receiving the brain wave data signals, sequentially carrying out digital filtering and frequency shift keying modulation on the brain wave data signals to form brain wave data, and sending the brain wave data through an audio interface;
the evaluation device includes:
a signal receiving unit, configured to receive the brain wave data, where the brain wave data includes, according to a frequency band: alpha wave, beta wave, theta wave;
a fourier transform unit, configured to perform fourier transform on the brain wave data to obtain frequency band energy of a corresponding frequency band, where the frequency band energy includes: alpha wave frequency band energy, beta wave frequency band energy and theta wave frequency band energy;
the emotion and fatigue state characteristic value calculation unit is used for obtaining individual emotion and fatigue state characteristic values according to the frequency band energy of the corresponding frequency band, and the emotion and fatigue state comprises the following steps: the stimulation response intensity is the ratio of beta wave frequency band energy to alpha wave frequency band energy, the stimulation response is the difference value of the alpha wave frequency band energy of the left brain and the right brain of an individual, and the fatigue degree is the ratio of the sum of the alpha wave frequency band energy and the theta wave frequency band energy to the beta wave frequency band energy;
the emotion and fatigue state quantitative value calculation unit is specifically used for:
acquiring characteristic values of emotion and fatigue states in a set time period, sampling the characteristic values of the emotion and fatigue states in the set time period, forming a sequence I, introducing a scale k into the sequence I, and forming a sequence II;
calculating the curve length corresponding to each sequence according to the second sequence;
and obtaining the mean value of the curve length corresponding to each sequence, and further obtaining the fractal dimension value of the curve, wherein the fractal dimension value of the curve is the quantitative value of the emotion and fatigue state.
2. A method for evaluating emotion and fatigue states based on brain wave signals, the method comprising:
collecting brain wave signals through a sensor electrode group; sequentially amplifying, filtering and carrying out analog-to-digital conversion on the collected brain wave signals to form brain wave data signals, and sending the brain wave data signals; the brain wave data signals are sequentially subjected to digital filtering and frequency shift keying modulation to form brain wave data, and the brain wave data comprises the following components according to frequency ranges: alpha wave, beta wave, theta wave;
carrying out Fourier transform on the electroencephalogram data to obtain frequency band energy of a corresponding frequency band, wherein the frequency band energy comprises: alpha wave frequency band energy, beta wave frequency band energy and theta wave frequency band energy;
obtaining characteristic values of individual emotion and fatigue states according to the frequency band energy of the corresponding frequency band, wherein the emotion and fatigue states comprise: the stimulation response intensity is the ratio of beta wave frequency band energy to alpha wave frequency band energy, the stimulation response is the difference value of the alpha wave frequency band energy of the left brain and the right brain of an individual, and the fatigue degree is the ratio of the sum of the alpha wave frequency band energy and the theta wave frequency band energy to the beta wave frequency band energy;
acquiring characteristic values of emotion and fatigue states in a set time period, sampling the characteristic values of the emotion and fatigue states in the set time period, forming a sequence I, introducing a scale k into the sequence I, and forming a sequence II; calculating the curve length corresponding to each sequence according to the second sequence; and obtaining the mean value of the curve length corresponding to each sequence, and further obtaining the fractal dimension value of the curve, wherein the fractal dimension value of the curve is the quantitative value of the emotion and fatigue state.
3. The method for estimating emotional and fatigue states based on brain wave signals according to claim 2, wherein the method for calculating the quantitative values of emotional and fatigue states comprises:
acquiring a characteristic value of an emotion and fatigue state of an individual in a set time period, sampling the characteristic value of the emotion and fatigue state in the set time period, and forming a sequence I, wherein the sequence I is recorded as: x (1), X (2), X (3) … … X (n);
introducing a scale k into the sequence I to form a sequence II
Is recorded as:
wherein m ═ (1,2,3 … … k);
and calculating the curve length corresponding to each sequence according to the second sequence, wherein the curve length calculation formula is as follows:
obtaining each ofThe mean value of the lengths of the curves corresponding to the sequence is:
when L (k) ° k-DAnd then, obtaining fractal dimension values of the curve, namely quantized values of the emotion and fatigue states, wherein the fractal dimension values are as follows:
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