CN109036469A - A kind of autonomic nervous function parameter acquiring method based on sound characteristic - Google Patents
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- G10L25/66—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
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Abstract
The invention discloses a kind of autonomic nervous function parameter acquiring method based on sound characteristic, pass through carry out stress stimulation experiment and record before stimulation and in stimulating course testee voice signal；Then excision mute to the voice signal of acquisition, preemphasis, framing and adding window pretreatment；Finally parameter calculating is carried out using to pretreated voice signal, the fundamental frequency of sound is obtained by auto-correlation function, obtain the fundamental frequency and standard deviation data of each testee's voice signal, then the frequency range is integrated, obtain base band power, the evaluation of autonomic nervous function is realized by fundamental frequency and base band power, fundamental frequency can be used as the parasympathetic efficiency index of evaluation；Base band power can be used as the efficiency index of evaluation sympathetic nerve；Compared to other physical signs, voice signal, which has, acquires convenient, the features such as speech processing system is adaptable and technology maturation, and adopting said method more quickly effectively can evaluate autonomic nervous function and change.
Description
Technical field
The invention belongs to processing of biomedical signals technical fields, it is intended to propose a kind of autonomic nerve based on sound characteristic
Functional parameter acquisition methods.
Background technique
Cardiovascular autonomic nervous function is unbalance have with the case fatality rate of cardiovascular disease it is close contact, about 90% it is cardiogenic sudden
It is extremely caused by malignant arrhythmia.Cardiovascular autonomic nervous function is unbalance to cause atrial fibrillation, ventricular arrhythmia, heart failure etc. pernicious
Cardiovascular event, and then lead to death.Meanwhile the diseases such as diabetes, hypertension and functional voice disorder also have proven to
It is unbalance related to autonomic nerve adjusting function.It can be seen that the evaluation and test of autonomic nervous function, for preventing and reducing pernicious painstaking effort
It runs affairs part, examines the curative effect of related drugs, there is important clinical value.
Current main neurologic score method is numerous.Such as Novak P et al. in 2011 publication presently, there are it is complete
The quantitative autonomic nervous function test protocol by clinical verification.Existing agreement mainly includes three kinds of autonomic nerve fields:
Heart fan walks, Adrenaline Level and sweat gland secretion nerve.Test includes deeply breathing, the changes in heart rate under Valsalva maneuver,
Inclining test and quantitatively urge sweat aixs cylinder test (QSART).By a series of test, then compare specific autonomic nervous function
Rating scale carries out comprehensive marking to autonomic nervous function and completes to test.But the shortcomings that these methods, is: test index list
One, it cuts respectively from independent, the signal processing method of utilization is too simple, is unable to further progress concrete analysis.In addition to above-mentioned
Means, the HRV analysis method based on electrocardiosignal are got more attention.Heart rate is as autonomic nerve directly to the regulation of sinoatrial node
As a result, its frequency analysis, it can embody sympathetic and parasympathetic branch activity level simultaneously, there is very significant diagnostic significance.
But currently, there is certain dispute to the versatility of its index, therefore the application of the evaluation method is also subject to certain restrictions.
Summary of the invention
The purpose of the present invention is to provide a kind of autonomic nervous function parameter acquiring method based on sound characteristic, to overcome
The deficiencies in the prior art.
In order to achieve the above objectives, the present invention adopts the following technical scheme:
A kind of autonomic nervous function parameter acquiring method based on sound characteristic, comprising the following steps:
Step 1) carries out stress stimulation experiment and records the voice signal for stimulating testee in preceding and stimulating course；
Step 2), the mute excision of voice signal to step 1) acquisition, preemphasis, framing and adding window pre-process；
Step 3) carries out parameter calculating to pretreated voice signal, and the fundamental frequency of sound is obtained by auto-correlation function,
The auto-correlation function of discrete voice signal x (n) are as follows:
R (k)=∑ x (n) (n-k) (4)
Wherein k is the retardation of time, and N is frame length；
Obtain the fundamental frequency and standard deviation data of each testee's voice signal, select the positive and negative 40Hz of each fundamental frequency for
Then frequency range integrates the frequency range, obtains base band power.
Further, in step 1), the voice signal of testee is acquired under quiescent condition, then under quiescent condition
Testee carries out stress stimulation, then acquires the voice signal of the testee after stress stimulation.
Further, by KFW H902 microphone collected sound signal, MP150 record sound letter is transferred to data line
Number, sample rate 20kHz.
Further, in step 2), the mute excision of two ends is carried out to the voice signal of acquisition first, to mute excision
Voice signal afterwards carries out preemphasis processing, is then to strengthen pre-add by framing by carrying out exacerbation processing to high frequency section
Weight treated voice signal, the voice signal after then selecting smooth window to strengthen framing carry out adding window, and selection has
The window of transient characteristic can enhance the continuity of each frame voice signal.
Further, in preemphasis processing, a high-pass filter, such as formula:
H (z)=1-aZ-1(0.9 < a < 1) (1)
Signal is passed through into the result after the high-pass filter are as follows:
S ' (n)=S (n)-aS (n-1) (0.9 < a < 1) (2)
S (n) in formula is the sampled value at n moment.
Further, during framing, frame length 20ms, it is the 1/3 of frame length that frame, which moves,.
Further, windowing process is carried out by Hamming window:
Further, fundamental frequency and parasympathetic activity are negatively correlated, as the parasympathetic index of evaluation；Base band power
It is positively correlated with sympathetic nerve activity, the index as sympathetic nerve under evaluation state of activation.
Compared with prior art, the invention has the following beneficial technical effects:
A kind of autonomic nervous function parameter acquiring method based on sound characteristic of the present invention, by carrying out stress stimulation experiment
And record the voice signal for stimulating testee in preceding and stimulating course；Then to the mute excision of the voice signal of acquisition, pre-add
Weight, framing and adding window pretreatment；Parameter calculating finally is carried out using to pretreated voice signal, is obtained by auto-correlation function
The fundamental frequency for taking sound obtains the fundamental frequency and standard deviation data of each testee's voice signal, then to the frequency range into
Row integral, obtains base band power, the evaluation of autonomic nervous function is realized by fundamental frequency and base band power, it is secondary that fundamental frequency can be used as evaluation
The efficiency index of sympathetic nerve；Base band power can be used as the efficiency index of evaluation sympathetic nerve；Compared to other physical signs, language
Sound signal, which has, acquires convenient, the features such as speech processing system is adaptable and technology maturation, and adopting said method can more be accelerated
Speed effectively evaluates autonomic nervous function variation.
Detailed description of the invention
Fig. 1 is the voice signal schematic diagram after mute excision；
Fig. 2 is a frame voice signal schematic diagram.
Specific embodiment
The invention will be described in further detail with reference to the accompanying drawing:
A kind of autonomic nervous function parameter acquiring method based on sound characteristic, comprising the following steps:
Step 1) carries out stress stimulation experiment and records the voice signal for stimulating testee in preceding and stimulating course；
Step 2), the mute excision of voice signal to step 1) acquisition, preemphasis, framing and adding window pre-process；
Step 3) carries out parameter calculating to pretreated voice signal, and the fundamental frequency of sound is obtained by auto-correlation function,
The auto-correlation function of discrete voice signal x (n) are as follows:
R (k)=∑ x (n) (n-k) (4)
Wherein k is the retardation of time, and N is frame length；
The fundamental frequency and standard deviation data of each testee's voice signal are obtained, the positive and negative of each subject fundamental frequency is selected
40Hz is frequency range, then integrates to the frequency range, obtains base band power.
The voice signal of acquisition and record testee:
The voice signal that testee is acquired under quiescent condition, then stress pierce to the testee under quiescent condition
Swash, then acquires the voice signal of the testee after stress stimulation；
Specifically, the experimental paradigm selected is: mental arithmetic stress tests, detailed process: placing a computer screen in face of subject,
Experiment starts to have 6 minutes settling times, can prompt sounding " " on the screen 5 seconds every 60s in tranquillization, this sound is corresponding
Be vowel [a :].It is the mental arithmetic time after tranquillization, will appear the addition and subtraction formula within 100 on screen, subject has judge for 3 seconds
Formula is corrected errors, if formula is left button of correctly clicking the mouse, if formula is the click right mouse button of mistake.Mental arithmetic experiment is total
It is divided into 8 modules, 30 formulas of a module, each module sound is primary.Mental arithmetic is tested a total of 12 minutes.Entire experiment
Period requires subject eyes to rest on frequency curtain, not see everywhere.
Experimental subjects is healthy male student enrollment between 22 to 28 years old.Pass through KFW H902 specialized conference Mike
Wind collects voice signal, has recorded voice signal with the 6th channel that data line is transferred to MP150, sample rate 20kHz, together
When, electrocardiosignal (ECG) is had recorded also by MP150, to calculate HRV, the validity for the parameter that verifying this method is proposed.
2, voice signal pretreatment
(1) mute excision
There are many mute parts in the voice signal collected, and start point signal is indefinite.First to acquisition
Voice signal completes the mute excision to two ends, reduces the interference caused by subsequent step, finally obtains preferable number
Word signal is as shown in Figure 1 the voice signal schematic diagram after mute excision；
(2) preemphasis
To after mute excision voice signal carry out preemphasis processing, be by carrying out exacerbation processing to high frequency section, with
Achieve the purpose that improve high frequency resolution, this process plays the role of high-pass filter.
A high-pass filter is selected first, such as formula:
H (z)=1-aZ-1(0.9 < a < 1) (1)
Signal is passed through into the result after the high-pass filter are as follows:
S ' (n)=S (n)-aS (n-1) (0.9 < a < 1) (2)
S (n) in formula is the sampled value at n moment.
(3) framing
Voice signal belongs to nonlinear time varying signal, and the temporal characteristics of voice signal are in order to obtain it is necessary to short using it
When stable feature, we strengthen this feature using the means of framing, this experimental selection frame length is 20ms, and frame pipettes choosing
What is selected is the 1/3 of frame length, this is to illustrate showing for a frame voice signal to reduce the characteristic variations between each frame, such as Fig. 2
It is intended to；
(4) adding window
In order to further analyze using temporal characteristics voice signal, smooth window is selected to carry out adding window, choosing
The continuity of each frame voice signal can be enhanced by selecting the window with transient characteristic, and selection is Hamming window in this experiment process:
Hamming window (Hamming Window)
Mute excision, preemphasis are completed to voice signal is extracted, then the process of framing and adding window carries out feature and mentions
It takes.
3, audio parameter calculates
The former sound sound characteristic of testee's pronunciation is extracted first,
For the vowel [a :] acquired in this experiment, vowel is also voiced sound, so being first extracted traditional sound herein
Sound feature has fundamental frequency (Pitch), and calculates the power (EPITCH) of fundamental frequency frequency range on this basis as a characteristic parameter.
(1) fundamental frequency (Pitch)
The sound of people is divided into voiced sound and voiceless sound, and voiced sound is to be formed by vocal cord vibration, and voiceless sound is then by windage shape
At.The sounding of voiced sound is usually to remove impact glottis by the air-flow that lung generates, so that the movement of one one conjunction occurs in it, in turn
A series of air-flow pulse is generated, these pulses pass through the resonance of sound channel (including nasal cavity and oral cavity) and the radiation of lips and teeth generation,
Last voice signal is formd, process is generated by voiced sound and knows that its waveform has quasi periodic to a certain extent, and it is so-called
Pitch period be exactly it is this quasi-periodic for describing, it characterizes glottis at opening and closing interval twice in succession.
An important feature of the pitch period as voice signal, it also reflect simultaneously one of sound stimulation source it is important
Feature；The fundamental frequency of sound, the auto-correlation function of discrete voice signal x (n) are obtained by auto-correlation function are as follows:
R (k)=∑ x (n) (n-k) (4)
Wherein k is the retardation of time, and N is frame length.
Short-time autocorrelation function has following critical nature, if original signal exists periodically, auto-correlation function is also deposited
In periodicity, and it is periodically consistent with the period of original signal.Peak value will be had when K is the integral multiple in period to generate.Voiced sound tool
There is periodicity, can be generated when R (k) is in pitch period integral multiple with peak value, first maximal peak point is generally taken as base
Sound periodic point.Pitch Detection based on auto-relativity function method is exactly to pass through this property to check pitch period.
(2) base band power (EPITCH) calculates；
In from the above, the fundamental frequency and standard deviation data of each subject have been obtained, has selected each subject fundamental frequency just
Negative 40Hz is frequency range, then integrates to the frequency range, obtains base band power, as EPITCH.
4, HRV Parameters variation results
It, will be collected in this citing in order to be compared with the autonomic nervous function evaluation method based on electrocardiosignal
Electrocardiosignal first uses conventional method, and by noise remove, R wave crest is extracted, and two for finally calculating HRV are commonly used to characterization friendship
Feel, the parameter of parasympathetic function, the results are shown in Table 1.
1 HRV paired t-test statistical result of table
(note: compared with tranquillization,*Indicate p < 0.05, data are expressed as mean ± SEM)
By statistical result, it can be seen that, compared to quiescent condition, nLF is significantly increased under mental arithmetic state, and HF is in mental arithmetic state
Under be substantially reduced.It draws a conclusion, is increased in mental arithmetic whole process sympathetic activation degree, and parasympathetic nerve excitability reduces.
5, audio parameter analysis of statistical results
By the processing and statistics to voice signal, result and conspicuousness of the audio parameter before and after mental arithmetic have been obtained, has been had
Body result such as table 2:
2 vowel of table [a :] parametric statistics result
(note: compared with tranquillization,*Indicate p < 0.05,**Indicate p < 0.01, data are expressed as mean ± SEM)
It can see from the result of table 2, when compared with quiescent condition, mental arithmetic task increases fundamental frequency (Pitch) obviously.
The main reason for corresponding phenomenon occur is that mental arithmetic task reduces vagal tone.It is analyzed in conjunction with Physiological background, musculus vocalis
(thyroarytehoid) is dominated by recurrent nerve, and recurrent nerve belongs to Mi Zou branch, when under mental arithmetic state, sympathetic activation and be confused
Active reduction is walked, musculus vocalis diastole keeps vocal cords elongated and nervous, so that fundamental frequency rises.I.e. it is living to can be used as vagus nerve for fundamental frequency
The characterization of property.
In addition, the base band power (EPITCH) under mental arithmetic state is than there is apparent increase under quiescent condition.Analysis obtains, hands over
So that subject palpitating speed, blood pressure increase, at this moment this, which may cause, is tested the voice signal of sounding in first harmonic for grateful work
On have relatively high energy, the base band power so as to cause subject has a significant raising.I.e. base band power can be used as
The characterization of sympathetic activity.
6, audio parameter and HRV relation analysis of parameter
With two audio parameters: fundamental frequency and base band power carry out Pearson correlation analysis with nLF, HF respectively, as a result such as
Shown in table 3 and table four:
The correlated results of table 3 fundamental frequency and autonomic nerve
(note:*Indicate p < 0.05)
By fundamental frequency and the autonomic nerve correlated results of table 3, it can be concluded that, fundamental frequency is regardless of in quiescent condition or mental arithmetic shape
There is significant negative correlation under state with parasympathetic nerve, this is illustrated regardless of in the state that whether vagus nerve activates, musculus vocalis
All in the domination of recurrent nerve；And when under mental arithmetic state, fan walks active reduction, and musculus vocalis diastole keeps vocal cords elongated and tight
, so that it is also reasonable that fundamental frequency, which has conspicuousness to rise,.And sympathetic nerve there is no and fundamental frequency have apparent correlation.So base
Frequency can be used as the parasympathetic efficiency index of evaluation.
The correlated results of table 4 base band power and autonomic nerve
(note:*Indicate p < 0.05)
It is can analyze out by the correlated results of table 4 to draw a conclusion, although base band power does not have with the sympathetic nerve under tranquillization
There is good correlation, but shows good correlation with the sympathetic nerve activated under mental arithmetic state.The activation of sympathetic nerve
So that the palpitating speed of subject, blood pressure is increased, and result in the voice signal that subject issues in this case has on fundamental tone harmonic wave
Relatively high energy, the base band power so as to cause subject have significant raising.It is commented so base band power can be used as
The efficiency index of sympathetic nerve under valence state of activation.
During this is illustrated, especially select data of the Healthy subjects under mental arithmetic stress situation for process object.The heart
Calculating stress be a kind of experimental paradigm for being usually used in autonomic nerves system activation, and sound is believed under record state of activation and quiescent condition
Number, and the audio signal processing method that application this method proposes, obtain two indices: fundamental frequency and base band power.And herein
Electrocardio has been handled simultaneously, and has calculated traditional HRV analysis method.It is compared with HRV parameter and proposed index
Analysis and correlation analysis.As a result, it was confirmed that fundamental frequency can be used as the parasympathetic efficiency index of evaluation；Base band power can be used as evaluation
The efficiency index of sympathetic nerve；Compared to electrocardiosignal, voice signal have acquire it is convenient, speech processing system it is adaptable and
The features such as technology maturation, therefore, adopting said method, more quickly effectively can evaluate autonomic nervous function variation.
Claims (8)
1. a kind of autonomic nervous function parameter acquiring method based on sound characteristic, which comprises the following steps:
Step 1) carries out stress stimulation experiment and records the voice signal for stimulating testee in preceding and stimulating course；
Step 2), the mute excision of voice signal to step 1) acquisition, preemphasis, framing and adding window pre-process；
Step 3) carries out parameter calculating to pretreated voice signal, and the fundamental frequency of sound is obtained by auto-correlation function, discrete
The auto-correlation function of voice signal x (n) are as follows:
R (k)=∑ x (n) (n-k) (4)
Wherein k is the retardation of time, and N is frame length；
The fundamental frequency and standard deviation data of each testee's voice signal are obtained, selecting the positive and negative 40Hz of each fundamental frequency is frequency
Then range integrates the frequency range, obtains base band power.
2. a kind of autonomic nervous function parameter acquiring method based on sound characteristic according to claim 1, feature exist
In in step 1), the voice signal of acquisition testee, then answers the testee under quiescent condition under quiescent condition
Swash stimulation, then acquires the voice signal of the testee after stress stimulation.
3. a kind of autonomic nervous function parameter acquiring method based on sound characteristic according to claim 1 or 2, feature
It is, by KFW H902 microphone collected sound signal, is transferred to MP150 record voice signal with data line, sample rate is
20kHz。
4. a kind of autonomic nervous function parameter acquiring method based on sound characteristic according to claim 1, feature exist
In, in step 2), the mute excision of two ends is carried out to the voice signal of acquisition first, to the voice signal after mute excision into
The processing of row preemphasis is then to pass through framing reinforcing preemphasis treated voice by carrying out exacerbation processing to high frequency section
Signal, the voice signal after then selecting smooth window to strengthen framing carry out adding window, select the window with transient characteristic
The continuity of each frame voice signal can be enhanced.
5. a kind of autonomic nervous function parameter acquiring method based on sound characteristic according to claim 4, feature exist
In, in preemphasis processing, a high-pass filter, such as formula:
H (z)=1-aZ-1(0.9 < a < 1) (1)
Signal is passed through into the result after the high-pass filter are as follows:
S ' (n)=S (n)-aS (n-1) (0.9 < a < 1) (2)
S (n) in formula is the sampled value at n moment.
6. a kind of autonomic nervous function parameter acquiring method based on sound characteristic according to claim 4, feature exist
During framing, frame length 20ms, it is the 1/3 of frame length that frame, which moves,.
7. a kind of autonomic nervous function parameter acquiring method based on sound characteristic according to claim 4, feature exist
In, pass through Hamming window carry out windowing process:
8. a kind of autonomic nervous function parameter acquiring method based on sound characteristic according to claim 1, feature exist
In fundamental frequency and parasympathetic activity are negatively correlated, as the parasympathetic index of evaluation；Base band power and sympathetic nerve activity
It is positively correlated, the index as sympathetic nerve under evaluation state of activation.
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