CN105975943A - EEG-based meditation detection method - Google Patents

Abstract

The invention discloses an EEG-based meditation detection method, relating to the field of EEG signal emotion feature extraction and analysis. The method includes the steps of acquiring a section of EEG time domain signal data and converting the data into EEG frequency domain signal data; respectively calculating the energy absolute value of the alpha frequency range and the energy absolute value of the beta frequency range based on the EEG frequency domain signal data; calculating the energy relative value ratio of the alpha frequency range based on the energy absolute value of the alpha frequency range and the energy absolute value of the beta frequency range; and calculating the meditation score MedScore based on ratio. According to the invention, the interference immunity of meditation determination is enhanced, and the accuracy of meditation determination result is improved.

Description

A kind of meditation detection method based on brain wave

Technical field

The present invention relates to EEG signals emotional characteristics extract and analysis field, be specifically related to a kind of meditation based on brain wave Detection method.

Background technology

Meditation (meditation) is a kind of form changing consciousness in psychology, and it is by obtaining the quiet shape of the degree of depth State and strengthen self-knowledge and kilter.It is substantially by stopping intellectual and the cerebral cortex effect of rationality, and makes self-discipline Nerve presents active state.For popular, meditation is just off realizing external activities, and reaches the one in selfless border Soul behavior of personal control.Generally the mankind are only after eye closing, just can progress into by reducing conscious cerebral activity Meditation state, the brain wave that at this moment human brain is sent will relatively open eyes non-meditation or close one's eyes there is large change in bed.

Brain wave (EEG, Electroencephalogram) refer to brain when activity, a large amount of neurons synchronize occur The signal of telecommunication that postsynaptic potential is formed after summation.The mankind close one's eyes and make by meditation training brain entrance quiet state after, Can reflect that the brain wave of 7.5Hz to 13Hz frequency range is in active and this brain wave energy value higher.Academicly by 7.5Hz Brain wave to 13Hz frequency range is referred to as α frequency range E.E.G；The meditation activity of human brain can be entered by gathering, analyze brain wave Row detection.

But, when gathering and analyze α frequency range E.E.G, α frequency range E.E.G is easily subject to from extraneous Electromagnetic Interference, and then Cause energy absolute value bigger than normal；Or sensor component (electrode for encephalograms and drive circuit etc. thereof) in α frequency range E.E.G gatherer process There is performance degradation, in turn result in energy absolute value too small.Therefore, the energy absolute value of α frequency range E.E.G is not sufficiently stable, it is impossible to logical Cross this energy absolute value as judging meditation and analyzing the data foundation of meditation degree.

Summary of the invention

For defect present in prior art, present invention solves the technical problem that into: strengthen that meditation judges is anti-interference Property, and then improve the accuracy of meditation result of determination.

For reaching object above, the meditation detection method based on brain wave that the present invention provides, the method includes following step Suddenly；

S1: obtain 1 section of brain electricity time-domain signal data；

S2: brain electricity time-domain signal data are converted to brain electricity frequency-domain signal data；

S3: utilize brain electricity frequency-domain signal data to calculate the energy absolute value of α frequency range respectivelyAbsolute with the energy of β frequency range Value

S4: according toWithCalculate the energy relative value ratio of α frequency range；

S5: calculating meditation mark MedScore according to ratio, computing formula is:

In above-mentioned formula, upperLimit is self-defining meditation upper threshold, and lowerLimit is meditation bottom threshold.

On the basis of technique scheme, the frequency-domain signal data of brain electricity described in S2 includes the frequency of na α frequency range With the frequency of β β frequency range of n, on the basis of secondary, described in S3WithComputing formula be respectively as follows:

$\stackrel{\‾}{E}a=\frac{E1+E2+\mathrm{...}Ena}{na};\stackrel{\‾}{E}\mathrm{\β}=\frac{E1+E2+\mathrm{...}En\mathrm{\β}}{n\mathrm{\β}};$

In above-mentioned formula, E1a, E2a...Ena are that No. 1 frequency energy value of α frequency range is to the n-th a frequency energy value； E1a, E2a...En β is that No. 1 frequency energy value of β frequency range is to the n-th β frequency energy value.

On the basis of technique scheme, the computing formula of ratio described in S4 is:

On the basis of technique scheme, the idiographic flow of S2 is: use DFT brain electricity time-domain signal data to be converted to Brain electricity frequency-domain signal data.

On the basis of technique scheme, the mode obtaining 1 section of brain electricity time-domain signal data described in S1 is: at brain electricity The data that ripple collecting device sends intercept 1 section of brain electricity time-domain signal data.

On the basis of technique scheme, the EEG signals sample frequency of described acquiring brain waves equipment is 512Hz, institute State 1 section of brain electricity time-domain signal data and include 2048 data.

Compared with prior art, it is an advantage of the current invention that:

The present invention uses β frequency range as reference band to calculate the energy relative value ratio of α frequency range and to use innovation Computing formula calculates meditation mark MedScore according to ratio and carries out meditation judgement；Bigger than normal with energy absolute value in prior art Or too small α frequency range E.E.G compares, the present invention uses the β frequency range as reason and the advantage of reference band to be:

Open eyes non-meditation time, α band energy relative value too low can abnormal increase owing to reference band energy value is accidental.Therefore Need use compared with α frequency range, brain electricity frequency range definition on contrast more greatly, especially open eyes non-meditation time contrast bigger brain electricity Frequency range, as reference band, meditates the too high probability of relative value during to reduce and to open eyes.

Meanwhile, when selecting reference band, in order to strengthen anti-interference and the elimination erroneous judgement that meditation judges, need to select Neighbouring with α frequency range and that self-characteristic is contrary with α frequency range frequency range.Than the adjacent band β frequency of α frequency range higher frequency in brain wave Section self-characteristic be when psychentonia and excited or excited time this ripple occurs, himself characteristic is contrary with α frequency range, and With represent the degree of depth loosen, compared with the θ frequency range of stress-free subconsciousness state, β frequency range has bigger contrast.

In sum, the present invention is carried out β frequency range and α combination of frequency ranges when meditation judges, it is possible to strengthen the anti-of meditation judgement Interference, and then improve the accuracy of meditation result of determination.

Accompanying drawing explanation

Fig. 1 is the flow chart of meditation detection method based on brain wave in the embodiment of the present invention.

Detailed description of the invention

Below in conjunction with drawings and Examples, the present invention is described in further detail.

Meditation detection method based on brain wave in the embodiment of the present invention, according to acquiring brain waves equipment (such as brain electricity Instrument) capture eeg signal detection human brain meditation activity；Acquiring brain waves equipment is used for needing to gather and analyze the mankind The eeg signal of brain, and the detection unit of human brain meditation activity or region (such as family, mental health clinic and Yoga classroom etc.).

Meditation detection method based on brain wave shown in Figure 1, in the embodiment of the present invention, comprises the following steps:

S1: intercept 1 section of brain electricity time-domain signal data in the data that acquiring brain waves equipment sends；The present embodiment midbrain electricity The EEG signals sample frequency of ripple collecting device is 512Hz, and 1 section of brain electricity time-domain signal data includes 2048 data；Again The time interval that during data intercept, 2 times intercept is 1s.

S2: use DFT (Discrete Fourier Transform, discrete Fourier transform) by brain electricity time-domain signal number According to being converted to brain electricity frequency-domain signal data, brain electricity frequency-domain signal data includes frequency and the frequency of β β frequency range of n of na α frequency range Point.

S3: utilize brain electricity frequency-domain signal data to calculate the energy absolute value of α frequency range respectivelyAbsolute with the energy of β frequency range ValueComputing formula is:

$\stackrel{\‾}{E}a=\frac{E1+E2+\mathrm{...}Ena}{na};\stackrel{\‾}{E}\mathrm{\β}=\frac{E1+E2+\mathrm{...}En\mathrm{\β}}{n\mathrm{\β}};$

In above-mentioned formula, E1a, E2a...Ena are that No. 1 frequency energy value of α frequency range is to the n-th a frequency energy value； E1a, E2a...En β is that No. 1 frequency energy value of β frequency range is to the n-th β frequency energy value.

S4: according toWithCalculating the energy relative value ratio of α frequency range, computing formula is:

S5: calculating meditation mark MedScore according to ratio, computing formula is:

In above-mentioned formula, upperLimit is self-defining meditation upper threshold, and lowerLimit is meditation bottom threshold.

The present invention, after MedScore has calculated, carries out meditation according to MedScore and judges.

The present invention is not limited to above-mentioned embodiment, for those skilled in the art, without departing from On the premise of the principle of the invention, it is also possible to make some improvements and modifications, these improvements and modifications are also considered as the protection of the present invention Within the scope of.The content not being described in detail in this specification belongs to prior art known to professional and technical personnel in the field.

Claims (6)

1. a meditation detection method based on brain wave, it is characterised in that: the method comprises the following steps；

S1: obtain 1 section of brain electricity time-domain signal data；

S2: brain electricity time-domain signal data are converted to brain electricity frequency-domain signal data；

S3: utilize brain electricity frequency-domain signal data to calculate the energy absolute value of α frequency range respectivelyEnergy absolute value with β frequency range

S4: according toWithCalculate the energy relative value ratio of α frequency range；

S5: calculating meditation mark MedScore according to ratio, computing formula is:

$MedScore=\frac{ratio-lowerLimit}{upperLimit-lowerLimit};$

In above-mentioned formula, upperLimit is self-defining meditation upper threshold, and lowerLimit is meditation bottom threshold.

2. meditation detection method based on brain wave as claimed in claim 1, it is characterised in that: the frequency domain of brain electricity described in S2 is believed Number includes frequency and the frequency of β β frequency range of n of na α frequency range, on the basis of secondary, described in S3WithMeter Calculation formula is respectively as follows:

$\stackrel{\‾}{E}a=\frac{E1+E2+...Ena}{na};\stackrel{\‾}{E}\mathrm{\β}=\frac{E1+E2+...En\mathrm{\β}}{n\mathrm{\β}};$

E1a, E2a in above-mentioned formula ... Ena is that No. 1 frequency energy value of α frequency range is to the n-th a frequency energy value；E1a、 E2a ... En β is that No. 1 frequency energy value of β frequency range is to the n-th β frequency energy value.

3. meditation detection method based on brain wave as claimed in claim 2, it is characterised in that: the meter of ratio described in S4 Calculation formula is:

4. meditation detection method based on brain wave as claimed in claim 1, it is characterised in that the idiographic flow of S2 is: adopt With DFT, brain electricity time-domain signal data are converted to brain electricity frequency-domain signal data.

5. the meditation detection method based on brain wave as described in any one of Claims 1-4, it is characterised in that: described in S1 The mode obtaining 1 section of brain electricity time-domain signal data is: intercept 1 section of brain electricity time domain letter in the data that acquiring brain waves equipment sends Number.

6. meditation detection method based on brain wave as claimed in claim 5, it is characterised in that: described acquiring brain waves equipment EEG signals sample frequency be 512Hz, described 1 section of brain electricity time-domain signal data include 2048 data.