CN111803080B - Infant distortion otoacoustic detector and detection method thereof - Google Patents
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Abstract
The invention provides an infant distortion otoacoustic detector, which is characterized in that an electroacoustic ring energy device and an electroacoustic transducer for receiving sound are arranged in a probe shell, and a silica gel sleeve of an earphone placed in an ear is connected with the shell through a transmitting and receiving sound pipeline; a pure tone stimulation sound system is arranged on the shell. The detection method comprises the steps of transmitting stimulating sound by a probe, playing two paths of stimulating sound by a pure-tone stimulating sound system, storing generated basic stimulating data into a head file of an ear sound detection project by simulation software, receiving reflected sound to calculate noise level, calculating waveform characteristic values of a critical region interval in a trend chart, and determining the quality of acquired signals. The invention can improve the noise influence in the process of detecting the distorted otoacoustic infants, improve the accuracy of infant detection and shorten the detection time.
Description
Technical Field
The invention relates to a medical hearing detection system, in particular to an infant distorted otoacoustic detector and a detection method thereof.
Background
Distorted otoacoustic emissions (DPOAEs) are an objective auditory function detection means that rely on the integrity of the overall function of the cochlea, an otoacoustic emission produced by the nonlinear distortion mechanism of the cochlea. Distorted otoacoustic emissions are OAEs induced by simultaneous stimulation of the cochlea with two initial pure tones F1 and F2 having a frequency ratio relationship. F1 and F2 can be either continuous or a pure tone signal with a long delay can be selected, and the distorted otoacoustic emission stimulus tones are superimposed in the time domain and separated in the frequency domain. The relation F2/f1=1.21 between F1 and F2, and the ratio of F2 to F1 ranges from 1.18 to 1.27 according to different frequency bands, and the frequency domain f3= (2F 1-F2) of the effective otoacoustic signal is conventionally taken. At present, clinical studies indicate that the intensity of 2F1-F2 is the most stable and the highest. The stimulus intensity of distorted otoacoustic emissions is typically 65dB for F1 and 55dB for F2. The method is characterized in that the method is also used for analyzing distorted otoacoustic based on the characteristics of the distorted otoacoustic at home and abroad, and extracting effective signals, so that the method is used for clinical cochlea function test.
At present, products with independent intellectual property rights of domestic infant otoacoustic screening equipment are few, and most of the products in the market use foreign product otoacoustic hearing screening equipment, and the foreign products have larger difference in accuracy in clinical use. The method for detecting the distorted ear sounds at home and abroad mainly comprises the steps of carrying out band-pass filtering on the acquired time domain signals, and then carrying out coherent average calculation by prolonging the acquisition time so as to achieve the purpose of eliminating white noise, thereby improving the detection signal-to-noise ratio.
In the prior art, a mute room is required to be arranged in a test environment, the data acquisition time of the test process is prolonged, and coherent averaging is carried out, so that the test environment is required to be high, and the test environment cannot be met in some base layer screening hospitals. In the distorted otoacoustic detection process, the accuracy of the distorted otoacoustic detection for early screening is low due to the fact that the detection of infants is subjected to neonatal body noise and neonatal unconscious shaking, the neonatal detection is difficult to simply use coherent average noise reduction, the neonatal test time is long, and dysphoria is easy to cause.
Disclosure of Invention
Aiming at the defects existing in the existing distorted otoacoustic detection, the invention aims to provide the infant distorted otoacoustic detector and the detection method thereof, which can improve the noise influence in the distorted otoacoustic infant detection process, improve the accuracy of infant detection and shorten the detection time.
In order to solve the technical problems, the invention adopts the following technical scheme: the infant distorted otoacoustic detector comprises a probe shell, wherein an electroacoustic transducer and an electroacoustic transducer for receiving sound are arranged in the shell, and a silica gel sleeve of an earphone placed in an ear is connected with the shell through a transmitting and receiving sound pipeline; a pure tone stimulation sound system is arranged on the shell.
The pure tone stimulation sound system generates phase-aligned pure tone stimulation sound for simulation software Matlab2015, intensity F1 corresponds to A and is 65dB, intensity F2 corresponds to B and is 55dB stimulation sound, the stimulation sound system is continuous waveform, sampling frequency Fs is 48000HZ, and the stimulation sound frequency is respectively 1000HZ, 2000HZ, 3000HZ and 4000HZ, and sound construction functions are obtained:
y1(t)＝Asin(2π×F1×t)，0≤t≤85ms (1)
y2(t)＝Bsin(2π×F2×t)，0≤t≤85ms (2)
the basic stimulus waveforms are generated by the formula (1) and the formula (2), the time is from 0, 4096 values are calculated as a group of stimulus waveforms every other time, and the stimulus waveforms are circularly played during testing; the intensities A and B are assumed to be fixed in size, and the generated basic stimulation data are stored in a head file of the otoacoustic detection engineering by using simulation software.
The detection method of the infant distorted otoacoustic detector comprises the following steps:
placing a probe detector and calibrating a probe;
secondly, if the probe is properly placed, the method is carried out, otherwise, the method is carried out;
the probe emits stimulating sound;
fourthly, the pure tone stimulation sound system plays two paths of stimulation sounds, and simulation software is used for storing the generated basic stimulation data into a head file of the otoacoustic detection project;
fifthly, receiving reflected sound to calculate noise level:
filtering with a Hamming window function
Wherein, alpha takes 0.46, N takes 2048 points, the function will exceed the unnecessary noise to be processed, the noise threshold value (the noise threshold value is set to the logarithmic energy after FFT conversion) is judged for the data collected by each packet, if the threshold value condition is met, the collected data is processed by coherent average, each time of coherent processing of 420 millisecond data packet, the frequency domain waveform trend graph after FFT conversion is calculated; calculating stability statistics of the received waveforms once every two continuous trend graphs;
according to the waveform trend graph of the step, respectively calculating waveform characteristic values of 4 adjacent domain intervals in the trend graph, wherein the waveform characteristic values comprise inflection points alpha 1, heights alpha 2 and slopes alpha 3; continuously acquiring 20 groups of data to perform feature clustering once, and using a K-Medians clustering algorithm, wherein the K-Medians is initially input into 2 groups, and the first group is initialized to be the average intensity value of the neonatal statistical data;
judging whether the condition 1 is satisfied according to the stability index calculated in the step and the characteristic clustering classification result in the step so as to determine the quality of the collected signals, and if the condition 1 is satisfied, calculating the signal to noise ratio of the group of emission stimulation sounds at the F3 frequency point; if the condition 1 is not met after 20 times of continuous calculation, judging that the proper position of the current test probe is not placed and manually adjusting the earplug for testing; wherein the method comprises the steps of
Condition 1: stability is more than 70%, and the first group of characteristic classification results accounts for more than 80%;
taking different F2 and F1 to repeat the steps from step I to step II, and using a 3dB threshold method, namely judging the signal-to-noise ratio of 4 groups of F3 points, and if 3 groups are more than 3dB, displaying passing; otherwise, the display does not pass.
And (3) carrying out stability statistics in the step (iii):
stability of the received wave: the similarity between the received complete waveform and the waveform received last time is more than 80%;
similarity: euclidean distance using two sets of discrete data
To calculate the similarity, where N is a set of received wave lengths, where 602, data1, data2 are stimulus sounds or received reflected sound data, respectively, twice before and after.
The sound emission rule is as follows: the distorted otoacoustic emission detection always selects an earphone channel to circularly transmit two paths of pure sound signals, and after 1800 milliseconds of delay, a microphone is started to receive the acoustic signals returned by the auditory canal.
According to the infant distorted ear sound detector and the infant distorted ear sound detection method, which are designed by the technical scheme, the noise influence in the infant distorted ear sound detection process is improved, the digital signal processing technology and the machine learning method are used, the requirements on the testing environment of infant distorted ear sound detection are reduced on the basis of not increasing the hardware cost, and the uneasy emotion of an infant in the testing process is reduced. According to the invention, a feature extraction clustering method based on statistics is added in signal processing, so that the accuracy of infant detection is improved, and meanwhile, the detection time is shortened.
Drawings
FIG. 1 is a schematic diagram showing the structure of an infant distorted otoacoustic detector of the present invention;
FIG. 2 is a schematic flow chart of the detection method of the present invention.
Detailed Description
The invention relates to an infant distorted ear sound detector and a detection method thereof, which are specifically described below with reference to the accompanying drawings.
Referring to fig. 1, the infant distortion otoacoustic detector comprises a probe shell 1, wherein an electroacoustic transducer 2 (micro-speaker) and an electroacoustic transducer 3 (micro-microphone) are arranged in the shell 1, the electroacoustic transducer 2 is used for playing stimulation sounds F1 and F2 respectively, and the electroacoustic transducer 3 is used for receiving sound. The earphone silica gel sleeve 5 placed in the ear is connected with the shell 1 through the transmitting and receiving sound pipeline 4, and the earphone silica gel sleeve 5 can be designed to be of a size according to the right ear of different ages of moon. A pure tone stimulation sound system is arranged in the shell 1, the pure tone stimulation sound system generates phase-aligned pure tone stimulation sound for simulation software Matlab2015, the intensity F1 corresponds to a stimulation sound with the intensity A of 65dB and the intensity B corresponds to F2 of 55dB, the stimulation sound system is a continuous waveform, the sampling frequency Fs is 48000HZ, the stimulation sound frequency is respectively 1000HZ, 2000HZ, 3000HZ and 4000HZ, and the sound construction function is that:
y1(t)＝Asin(2π×F1×t)，0≤t≤85ms (1)
y2(t)＝Bsin(2π×F2×t)，0≤t≤85ms (2)
the basic stimulus waveforms are generated by the formula (1) and the formula (2), the time is from 0, 4096 values are calculated as a group of stimulus waveforms every other time, and the stimulus waveforms are circularly played during testing; the intensities A and B are assumed to be fixed in size, and the generated basic stimulation data are stored in a head file of the otoacoustic detection engineering by using simulation software.
The detection method of the infant distorted ear sound detector disclosed by the invention, referring to fig. 2, comprises the following steps of:
placing a probe detector and calibrating a probe;
secondly, if the probe is properly placed, the method is carried out, otherwise, the method is carried out;
the probe emits stimulating sound;
fourthly, the pure tone stimulation sound system plays two paths of stimulation sounds, and simulation software is used for storing the generated basic stimulation data into a head file of the otoacoustic detection project;
fifthly, receiving reflected sound to calculate noise level:
filtering with a Hamming window function
Wherein, alpha takes 0.46, N takes 2048 points, the function will exceed the unnecessary noise to be processed, the noise threshold value (the noise threshold value is set to the logarithmic energy after FFT conversion) is judged for the data collected by each packet, if the threshold value condition is met, the collected data is processed by coherent average, each time of coherent processing of 420 millisecond data packet, the frequency domain waveform trend graph after FFT conversion is calculated; calculating stability statistics of the received waveforms once every two continuous trend graphs;
wherein, the stability statistical method comprises the following steps:
stability index definition
Stability of the received wave: the similarity between the received complete waveform and the waveform received last time is more than 80%;
similarity: euclidean distance using two sets of discrete data
To calculate the similarity, where N is a set of received wave lengths, where 602, data1, data2 are stimulus sounds or received reflected sound data, respectively, twice before and after.
According to the waveform trend graph of the step, respectively calculating waveform characteristic values of 4 adjacent domain intervals in the trend graph, wherein the waveform characteristic values comprise inflection points alpha 1, heights alpha 2 and slopes alpha 3; continuously acquiring 20 groups of data to perform feature clustering once, and using a K-Medians clustering algorithm, wherein the K-Medians is initially input into 2 groups, and the first group is initialized to be the average intensity value of the neonatal statistical data;
judging whether the condition 1 is satisfied according to the stability index calculated in the step and the characteristic clustering classification result in the step so as to determine the quality of the collected signals, and if the condition 1 is satisfied, calculating the signal to noise ratio of the group of emission stimulation sounds at the F3 frequency point; if the condition 1 is not met after 20 times of continuous calculation, judging that the proper position of the current test probe is not placed and manually adjusting the earplug for testing; wherein the method comprises the steps of
Condition 1: stability is more than 70%, and the first group of characteristic classification results accounts for more than 80%;
taking different F2 and F1 to repeat the steps from step I to step II, and using a 3dB threshold method, namely judging the signal-to-noise ratio of 4 groups of F3 points, and if 3 groups are more than 3dB, displaying passing; otherwise, the display does not pass.
The sound emission rule of the invention is: the distorted otoacoustic emission detection always selects an earphone channel to circularly transmit two paths of pure sound signals, and after 1800 milliseconds of delay, a microphone is started to receive the acoustic signals returned by the auditory canal.
Since the in-ear sounds received by distorted otoacoustic emissions are not clearly characterized in time domain details, but are separated from each other in the frequency domain, however, in practical infant tests, signals in the frequency range below 3500HZ are particularly susceptible to interference, which makes extraction of effective evoked sounds of effective distorted otoacoustic emissions very difficult. Therefore, the invention designs a statistical model based on 500 cases and 1000 cases of original acquisition receipts of ears, and classifies the noise, effective signals and emission stimulation sound characteristics of frequency domain signal curves of newborns with different ages and sexes respectively so as to improve the accuracy of detecting distorted otosound of the infants.
Claims (3)
1. The infant distorted otoacoustic detector is characterized by comprising a probe shell, wherein an electroacoustic transducer and an electroacoustic transducer for receiving sound are arranged in the shell, and a silica gel sleeve of an earphone placed in an ear is connected with the shell through a transmitting and receiving sound pipeline; the method comprises the steps that a pure tone stimulation sound system is arranged in a shell, the pure tone stimulation sound system generates phase-aligned pure tone stimulation sounds for simulation software Matlab2015, F1 corresponds to stimulation sounds with the intensity A of 65dB, F2 corresponds to stimulation sounds with the intensity B of 55dB, the stimulation sounds are continuous waveforms, the sampling frequency Fs is 48000HZ, the stimulation sound frequencies are respectively 1000HZ, 2000HZ, 3000HZ and 4000HZ, and sound construction functions are adopted for the stimulation sound frequencies:
y1(t)＝Asin(2π×F1×t)，0≤t≤85ms (1)
y2(t)＝Bsin(2π×F2×t)，0≤t≤85ms (2)
the basic stimulus waveforms are generated by the formula (1) and the formula (2), the time is from 0, 4096 values are calculated as a group of stimulus waveforms, and the stimulus waveforms are circularly played during testing; using simulation software to store the generated basic stimulation data into a head file of the otoacoustic detection project;
the infant distorted otoacoustic detector detection method comprises the following steps:
(1) Placing a probe detector and calibrating the probe;
(2) Turning (3) if the probe is properly placed, otherwise turning (1);
(3) Transmitting stimulating sound by the probe;
(4) The pure tone stimulation sound system plays two paths of stimulation sounds, and simulation software is used for storing the generated basic stimulation data into a head file of the otoacoustic detection project;
(5) Receiving reflected sound to calculate noise level:
filtering with a Hamming window function
Wherein, alpha is 0.46, N is 2048 points, the function is used for processing the noise exceeding the unnecessary noise, the noise threshold value judgment is carried out on the collected data, if the threshold value condition is met, the coherent average processing is carried out on the collected data, each time the coherent processing is carried out on a 420 millisecond data packet, and the frequency domain waveform trend graph after FFT conversion is calculated; calculating stability statistics of the received waveforms once every two continuous trend graphs;
according to the waveform trend graph of the step, respectively calculating waveform characteristic values of 4 adjacent domain intervals in the trend graph, wherein the waveform characteristic values comprise inflection points alpha 1, heights alpha 2 and slopes alpha 3; continuously acquiring 20 groups of data to perform feature clustering once, and using a K-Medians clustering algorithm, wherein the K-Medians is initially input into 2 groups, and the first group is initialized to be the average intensity value of the neonatal statistical data;
judging whether the condition 1 is satisfied according to the stability index calculated in the step and the characteristic clustering classification result in the step, so as to determine the quality of the collected signals, if the condition 1 is satisfied, calculating the signal-to-noise ratio of the group of emission stimulation sounds at the F3 frequency point, wherein F3 is the effective otoacoustic signal frequency domain; if the condition 1 is not met after 20 times of continuous calculation, judging that the proper position of the current test probe is not placed and the earplug is required to be manually adjusted for retesting; wherein the method comprises the steps of
Condition 1: stability is more than 70%, and the first group of characteristic classification results accounts for more than 80%;
taking different F2 and F1 to repeat the steps from step I to step II, and using a 3dB threshold method, namely judging the signal-to-noise ratio of 4 groups of F3 points, and if 3 groups are more than 3dB, displaying passing; otherwise, the display does not pass.
2. An infant distorted otoacoustic detector according to claim 1, wherein the stability statistics of step:
stability of the received wave: the similarity between the received complete waveform and the waveform received last time is more than 80%;
similarity: euclidean distance using two sets of discrete data
To calculate the similarity, where N is a set of received wave lengths, where 602, data1, data2 are received reflected sound data twice before and after, respectively.
3. The infant distorted otoacoustic detector of claim 1, wherein the sound emission rules are: the distorted otoacoustic emission detection always selects an earphone channel to circularly transmit two paths of pure sound signals, and after 1800 milliseconds of delay, a microphone is started to receive the acoustic signals returned by the auditory canal.
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