CN110101395B - Self-service hearing rapid measurement system - Google Patents
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/12—Audiometering
- A61B5/121—Audiometering evaluating hearing capacity
- A61B5/123—Audiometering evaluating hearing capacity subjective methods
Abstract
The invention discloses a self-service hearing rapid measurement method and a self-service hearing rapid measurement system. Wherein the method comprises the following steps: manufacturing a hearing test material; carrying out homogenization treatment on the single number to obtain a first signal-to-noise ratio adjustment value; homogenizing the multi-digit according to the first signal-to-noise ratio adjustment value to obtain a second signal-to-noise ratio adjustment value; and the user performs audiometry by using the audiometric materials, and calculates the actual presented signal-to-noise ratio according to the first signal-to-noise ratio adjustment value and the second signal-to-noise ratio adjustment value to obtain an audiometric result. The method can be separated from a professional audiometric environment (a silence room or a sound attenuation room), professional acoustic equipment and professional testers, realize self-service hearing examination in a common environment, and quantitatively give out results related to the medical audiometric height; the convenience and the accuracy of the hearing test are improved.
Description
Technical Field
The invention relates to a self-service hearing rapid measurement method, and also relates to a system for realizing the method, belonging to the technical field of medical detection.
Background
In modern lifestyles, due to the widespread use of music, games, etc., about 11 hundred million people worldwide are at risk of hearing impairment; in addition, hearing impairment is one of the processes of aging, and the elderly over 65 years old are approximately 1/3 th of the time impaired by hearing. Besides the curative effect of temporary sudden hearing damage caused by trauma, drug poisoning, virus infection, immune system lesion, various middle ear lesions and the like can be achieved through drugs or operations, the rest more common hearing damage caused by natural aging and noise exposure is generally permanent damage, and the recovery cannot be carried out through medical means at present, so that prevention and early recovery are of great importance.
The biggest obstacle behind hearing impairment in most people is the decline in the ability to understand speech in noise. The most commonly used hearing tests at present are pure-tone hearing tests and speech tests in a quiet environment (a silence room), which have no good pertinence to speech recognition in noise, and have high requirements on test environments and hardware, and cannot be popularized. Speech recognition tests in general noise include sentence recognition, vocabulary recognition, etc. In 2004, the netherlands scientist Smits invented a telephone test for identifying triple numbers in noise based on the previous study, and compared with sentence identification and vocabulary identification, the test has the characteristics of less influence by individual experience, low guess ratio, no memory effect and the like. Hearing loss generally begins with high frequency sounds, and the ability of speech recognition in noise is also primarily affected by high frequency hearing, so focusing on high frequency hearing levels is particularly critical for early detection and prevention of hearing loss. Moore et al, 2014, a British scientist, improved the digital identification test to increase its sensitivity to high frequency hearing loss.
At present, most of risk groups cannot seek medical attention and detect due to extremely tense medical resources in China, so that the timely detection and prevention of hearing loss are greatly limited, and a hearing detection method which is free from the limitation of medical resources and can be used by an owner is urgently needed.
Disclosure of Invention
Aiming at the defects of the prior art, the primary technical problem to be solved by the invention is to provide a quick hearing measuring method which can be separated from professional environment and testers and can be widely applied.
The invention provides a self-service hearing rapid measurement system.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
according to a first aspect of an embodiment of the present invention, there is provided a self-service hearing rapid measurement method, including the steps of:
manufacturing a hearing test material;
carrying out homogenization treatment on the single number to obtain a first signal-to-noise ratio adjustment value;
homogenizing the multi-digit according to the first signal-to-noise ratio adjustment value to obtain a second signal-to-noise ratio adjustment value;
and the user performs audiometry by using the audiometric materials, and calculates the actual presented signal-to-noise ratio according to the first signal-to-noise ratio adjustment value and the second signal-to-noise ratio adjustment value to obtain an audiometric result.
Wherein preferably the hearing test material comprises a speech material and a noise material; a hearing test material is made comprising the steps of:
recording and editing prompt tones and digital voices as voice materials;
randomly extracting digital voice, splicing the digital voice into a random digital string, and superposing a plurality of random digital strings to obtain speech spectrum noise;
and filtering and amplitude reducing the speech spectrum noise to obtain a noise material.
Preferably, the number of the digital voices is determined according to the number of the digits, and when the number of the digits is N, the digital voices with 0-9 ten digits at N different positions are recorded respectively.
Preferably, the signal to noise ratio first adjustment value is obtained by carrying out the homogenization treatment on the single number, which comprises the following steps:
fitting test data of the single number identification by the subjects to obtain a first fitting equation of each subject for each number identification accuracy rate along with the change of the signal-to-noise ratio;
obtaining a speech recognition threshold and an average speech recognition threshold of each number according to the fitting result of the first fitting equation;
a first adjustment value for the signal-to-noise ratio is derived from the difference between the speech recognition threshold and the average speech recognition threshold for each number. Preferably, the first fitting equation adopts the following calculation formula:
wherein PC is the identification accuracy;the original signal to noise ratio for digital di;SRT single a speech recognition threshold for single number discrimination; gamma is the guess probability; lambda is the high limit of accuracy; θ is at SRT single A slope at; wherein->For known data, SRT, γ, λ, θ are equation fitting parameters.
Preferably, the signal to noise ratio first adjustment value is each digital signal to noise ratio adjustment value, and is calculated by adopting the following formula:
wherein,a first adjustment value for the signal to noise ratio of the number di; d=0, 1,2,. The.a.. 9; i=1, 2,3;a speech recognition threshold for digit di single digit recognition; mSRT (mSRT) single An average speech recognition threshold for single number recognition.
Preferably, the multiple digits are triple digits, and the triple digits are homogenized according to the first signal-to-noise ratio adjustment value to obtain the second signal-to-noise ratio adjustment value; the method comprises the following steps:
fitting test data of the test subjects for identifying the triple numbers to obtain a second fitting equation of each test subject for changing the accuracy of each number identification along with the signal-to-noise ratio;
obtaining a speech recognition threshold and an average speech recognition threshold of each number according to the fitting result of the second fitting equation;
a second adjustment value for the signal-to-noise ratio is derived from the difference between the speech recognition threshold and the average speech recognition threshold for each number.
Preferably, a user performs audiometry by using an audiometric material, and a signal-to-noise ratio is calculated according to a first signal-to-noise ratio adjustment value and a second signal-to-noise ratio adjustment value to obtain an audiometric result; the method comprises the following steps:
the user performs audiometry by using the audiometric materials, and calculates an actual presented signal-to-noise ratio according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value;
after the test is finished, calculating the average value of the original signal to noise ratio to obtain a hearing test result value; comparing the test result value with a screening threshold value, and judging that the hearing of the user is normal when the hearing test result value is smaller than a mild threshold value; when the hearing test result value is larger than the severe threshold value, judging that the hearing of the user is severely lost; otherwise, judging the hearing loss of the user.
Preferably, the following formula is adopted for calculating the actual signal-to-noise ratio according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value:
wherein,the signal to noise ratio is actually presented; />Is the original signal to noise ratio;a first adjustment value for the signal-to-noise ratio; />And a second adjustment value of the signal-to-noise ratio.
According to a second aspect of embodiments of the present invention, there is provided a self-service hearing rapid measurement system comprising a processor and a memory; the memory has stored thereon a computer program operable on the processor, which when executed by the processor performs the steps of:
manufacturing a hearing test material;
carrying out homogenization treatment on the single number to obtain a first signal-to-noise ratio adjustment value;
homogenizing the multi-digit according to the first signal-to-noise ratio adjustment value to obtain a second signal-to-noise ratio adjustment value;
and the user performs audiometry by using the audiometric materials, and calculates the actual presented signal-to-noise ratio according to the first signal-to-noise ratio adjustment value and the second signal-to-noise ratio adjustment value to obtain an audiometric result.
According to the self-service hearing rapid measurement method provided by the invention, the homogeneity processing is respectively carried out based on single digital and triple digital noise identification experimental data, so as to obtain a signal-to-noise ratio first adjustment value and a signal-to-noise ratio second adjustment value; a user performs audiometry by using a audiometric material (based on trigeminal numbers), wherein each test time uses the obtained twice adjustment values (a signal-to-noise ratio first adjustment value and a signal-to-noise ratio second adjustment value) to adjust an original signal-to-noise ratio to present the signal-to-noise ratio so as to achieve the purpose of homogenization; and calculating the average value of all the test original signal to noise ratios to obtain a hearing test result. The method can be separated from a professional audiometric environment (a silence room or a sound attenuation room), professional acoustic equipment and professional testers, realize self-service hearing examination in a common environment, and quantitatively give out results related to the medical audiometric height; the convenience and the accuracy of the hearing test are improved.
Drawings
FIG. 1 is a flow chart of a method for self-service hearing rapid measurement provided by the invention;
FIG. 2 is a schematic diagram of a recording material according to an embodiment of the present invention;
FIG. 3 is a schematic diagram showing the comparison of power spectral densities of spectral noise before and after processing according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a test interface according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an interface for overall volume and initial raw SNR adjustment prior to measurement in one embodiment of the present invention;
fig. 6 is a schematic structural diagram of the self-service hearing rapid measurement system provided by the invention.
Detailed Description
The technical contents of the present invention will be described in detail with reference to the accompanying drawings and specific examples.
The invention provides a self-service hearing rapid measurement method, which combines the characteristics of Chinese in test development and evaluation, synthesizes the technical routes of Smits and Moore, provides the self-service hearing rapid measurement method suitable for various mobile terminals (mobile phones, pad, computers and the like), can be used for rapidly measuring household hearing loss (mainly aiming at aging and noise exposure hearing loss), and can also be used for screening hearing loss of different degrees in non-professional environments (hospital audiometric rooms), and professional equipment and personnel are not needed.
The measurement method tests hearing through digital recognition in noise, a user hears one prompt tone and three random numbers, such as 'please hear, 5-8-6', presented in the noise each time, and clicks the heard number according to subjective feeling. If all three numbers are correctly reflected, the next signal to noise ratio is reduced (increasing difficulty), otherwise, the signal to noise ratio is improved (reducing difficulty). The 50% speech acceptance threshold is estimated at the average raw signal-to-noise ratio during the test, the higher the value, the greater the degree of hearing loss, taking about a few minutes for a test. Because the perceived sharpness of different numbers in noise is very different, the actual presentation signal-to-noise ratio is subjected to homogenization adjustment (homogenization) according to experimental data, so that the discrimination-original signal-to-noise ratio functions of all numbers at all presentation positions are aggregated at the same level.
As shown in fig. 1, the self-service hearing rapid measurement method provided by the invention comprises the following steps: firstly, preparing a hearing test material; secondly, carrying out homogenization treatment based on a single number identification experiment to obtain a first signal-to-noise ratio adjustment value; then, carrying out homogenization treatment by applying the first adjustment value of the signal to noise ratio based on a triple digital identification experiment to obtain a second adjustment value of the signal to noise ratio; finally, the user uses the hearing test material to conduct hearing measurement, wherein a signal-to-noise ratio first adjustment value and a signal-to-noise ratio second adjustment value are applied, and a hearing test result is obtained. This process is described in detail below.
S1, manufacturing a hearing test material.
The hearing test material, which in the embodiments provided by the present invention includes a speech material and a noise material, needs to be made before the user can make a quick hearing test. The method for manufacturing the hearing test material specifically comprises the following steps of:
s11, recording and editing prompt tones and digital voices as voice materials. The number of the digital voices is determined according to the read-through number, and when the number of the digital voices is N, the digital voices with the numbers of 0-9 at N different positions are obtained through recording.
In the embodiment provided by the invention, the explanation is given taking the reading number of 3 as an example. The voice material requires that the numbers played each time sound clear and natural under the noiseless condition, has a certain consistency and has controllable inter-number interval time. In the embodiment provided by the invention, the three-way digital word list pronunciation and the prompt pronunciation are recorded by the recruited number of Chinese Mandarin female volunteers, one of the volunteers is optimized, the most clear natural pronunciation is intercepted from the record of the volunteers, and finally 1 prompt voice and 30 digital voices (10 digits are multiplied by 3 positions) are obtained. Specifically, 3 female broadcasting volunteers with ages of 20-35 years and clear and smooth Chinese native language and Mandarin can be recruited for material recording. The recording sample rate 44100Hz, the recording material is a digital word list containing 20 sets of three digits (each digit appears 2 times at each location as shown in fig. 2), and several alternative prompts "please listen to digits", "listen to attention", "please listen". All materials are read for 6 times after being familiar, and after recording is finished, the record of one volunteer with best pronunciation, speech speed and volume control is selected. The invention uses voice processing software to cut the material, clips out the optimal pronunciation of each number at each position, finally obtains 30 digital voice materials (10 numbers×3 positions), and selects the most suitable prompt. The 30 digital voices can be randomly combined under the condition of keeping the positions of the 30 digital voices when recorded, 1000 (10 multiplied by 10) possible combinations are combined, and some combination conditions are eliminated, and the rest are used for the triple digital identification hearing test.
In the process of producing the voice material, the invention takes the age breadth of the user group into consideration, and adopts the female voice standard mandarin between male voice and childhood voice to produce the voice material. Other types of speech materials may also be used, such as male voices, child voices, mixed voices, machine synthesized voices, other chinese voices (e.g., cantonese), and the like.
S12, randomly extracting digital voice, splicing the digital voice into a random digital string, and superposing a plurality of random digital strings to obtain speech spectrum noise.
S13, filtering and amplitude reduction processing is carried out on the speech spectrum noise to obtain a noise material.
The noise material should be spectrally close to the speech, while the masking effect of the noise on the speech should be relatively weak in the high frequency part in order to make the test more sensitive to high frequency hearing loss. Therefore, in the embodiment provided by the invention, the manufactured digital voice is randomly spliced and overlapped for a plurality of times to form the voice spectrum noise, the noise is subjected to two processes of low-pass filtering and amplitude reduction, and finally, the two processing results are overlapped to prepare the noise material.
Specifically, the noise material is produced by using the obtained digital voice. In one embodiment provided by the invention, digital voice is randomly extracted, random digital strings of at least 10s are spliced before and after 100-200 ms intervals are taken as an example, 40 digital strings are manufactured in this way, 10s in each digital string are randomly intercepted, and all the digital strings are overlapped to manufacture speech spectrum noise. The first is filtering processing, namely, primitive spectrum noise is filtered by a 10-order Butterworth low-pass filter with sampling rate of 44100Hz and cut-off frequency of 1500 Hz; the second is the de-framing process, i.e., reducing the primitive spectral noise amplitude by 15dB. The two processing results are superimposed to obtain a noise material (power spectral density pairs before and after speech spectral noise processing, such as fig. 3).
In the embodiment provided by the invention, low-frequency speech spectrum noise (digital speech synthesis speech spectrum shape noise, 1500Hz low-pass filtering, 15dB amplitude reduction and superposition of low-pass noise and amplitude reduction noise) is adopted on the basis of early scientific research work so as to improve the sensitivity to high-frequency hearing impairment. Other types of noise, such as full band noise, bandwidth filtered noise, or parameters of noise filters, such as filter width, shape, upper and lower limits, or amplitude reduction, may be modified during actual operation to achieve similar objectives.
S2, carrying out homogenization treatment based on a single number identification experiment to obtain a first signal-to-noise ratio adjustment value.
Under the same signal-to-noise ratio, the intelligibility of different numbers is different due to the difference of acoustic characteristics, and in order to improve the accuracy of the test, each number needs to be subjected to homogenization treatment, so that the perception level of a user on the different numbers is consistent under the same signal-to-noise ratio. Homogenizing treatment is carried out based on a single number identification experiment to obtain a first signal to noise ratio adjustment value, and the method specifically comprises the following steps:
and S21, fitting test data of the single number identification of the subjects to obtain a first fitting equation of each subject for each number identification accuracy rate changing along with the signal-to-noise ratio. Specifically, subjects are recruited to carry out a single-digit noise identification experiment, 1 digit embedded in noise is played each time in the process, user response is recorded, the next original signal-to-noise ratio is controlled to correspondingly change according to whether the response is correct or not, and further adjustment is not carried out on the original signal-to-noise ratio, so that experimental data are obtained. Then, equation fitting is performed on the correct rate of each subject to each number (30 in total) according to the experimental data according to the change of the original signal-to-noise ratio, so as to obtain the speech recognition threshold of each subject to each number.
The experimental program selects one from all digital materials to play, the subject identifies according to personal feeling, and clicks corresponding numbers, the original signal-to-noise ratio is changed along with the response condition of the subject, if the response is correct, the signal-to-noise ratio is reduced (the difficulty is increased), and if the response is incorrect, the difficulty is increased (the difficulty is reduced). Several hearing healthy subjects were then recruited to complete the test.
Specifically, in the embodiment provided by the invention, a digital voice with superimposed noise is played every time (34 times in total) in each round of test, the noise starts and ends at 300ms before and after the array, the numbers are selected in a pseudo-random mode, and each digital material appears once in the last 30 judgments; each time the subject selects the number heard on the test interface (e.g., fig. 4); the noise presented each time is obtained by randomly intercepting a proper length from the noise material manufactured in the first stage, and the noise volume is fixed to 65dB SPL; the initial original signal-to-noise ratio of each round of test is 0dB (very clear) or-30 dB (completely inaudible), then each time the original signal-to-noise ratio is changed along with the reaction condition of the subject, if the reaction is correct, the next signal-to-noise ratio is reduced (difficulty is increased), otherwise, the signal-to-noise ratio is improved (difficulty is reduced); the initial signal-to-noise ratio (0 or-30 dB) appears in a pseudo-random manner, and the same initial signal-to-noise ratio cannot be continuously generated for more than two rounds; original signal to noise ratio of digital di In this way, the calculation does not include the blank parts before and after the digits.
In the examples provided by the present invention, a total of 20 hearing healthy (i.e., binaural 125-8000 Hz pure tone thresholds all less than 20 dBHL) subjects were recruited for single digit identification testing in noise, with each completing 25 rounds of testing.
Wherein the 1 st round of test data (exercise effect) was removed for each subject, and the accuracy of the remaining data for each subject identification for each number (30 total) using the psigniit 4 kit was plotted against the original signal to noise Ratio (RMS) di /RMS noise ) Equation fitting is performed on the variation of (1) to obtain a first fitting equation (equation 1):
a first fitting equation:
wherein PC is the identification accuracy;the original signal to noise ratio for digital di;SRT single a speech recognition threshold for single number discrimination; gamma is the guess probability; lambda is the high limit of accuracy; θ is at SRT single A slope at; wherein->SRT is known as data single And gamma, lambda and theta are equation fitting parameters.
S22, obtaining the speech recognition threshold of each digit according to the fitting result of the first fitting equationAverage speech recognition threshold mSRT single 。
Calculating speech recognition threshold for each digit of a single digit discrimination based on inter-subject averageNamely:
wherein,a speech recognition threshold for single digit discrimination of digit di for the nth subject; n is the total number of subjects, n=20; n=1, 2,3,. The.; d=0, 1,2,. The.a.. 9; i=1, 2,3.
Then, an average speech recognition threshold mSRT for single digit discrimination is calculated from the inter-digit average single The method comprises the following steps:
wherein,a speech recognition threshold for the d-th digital single number discrimination; d is the largest number, d=9; i is the number of readouts, i=3; (d+1) I is the total number of digits, (d+1) i=30; d=0, 1,2,. The.a.. 9; i=1, 2,3.
S23, according to the speech recognition threshold of each digitWith average speech recognition threshold mSRT single The difference of (2) to obtain a first signal-to-noise ratio adjustment value, i.e., the first signal-to-noise ratio adjustment value of each digit +.>
S3, homogenizing the multi-digit according to the signal-to-noise ratio first adjustment value to obtain a signal-to-noise ratio second adjustment value.
On the basis of completing the single number identification homogenization treatment, the multi-digit homogenization treatment is performed, so that errors caused by subtle changes of the identification rate relative to the single number identification are avoided. In the embodiments provided by the invention, three words are taken as examples for illustration. And carrying out homogenization treatment on the triple digital based on the triple digital identification experiment by using the first adjustment value to obtain a signal-to-noise ratio second adjustment value, namely carrying out homogenization treatment on the triple digital according to the signal-to-noise ratio first adjustment value to obtain the signal-to-noise ratio second adjustment value, wherein the method specifically comprises the following steps of:
and S31, fitting test data of the test subjects for identifying the triple numbers to obtain a second fitting equation of each test subject for changing the accuracy of the identification of each number along with the signal to noise ratio. Specifically, subjects are recruited to carry out a triple digital noise identification experiment, triple digital embedded in noise is played each time in the process, user response is recorded, the original signal to noise ratio is controlled to correspondingly change next time according to whether the response is correct or not, the original signal to noise ratio is adjusted to the triple digital actual presentation signal to noise ratio according to a first adjustment value, and experimental data are obtained. Then, equation fitting was performed on each subject's accuracy of recognition for each number (30 total) as a function of the original signal-to-noise ratio, based on experimental data, with each subject's speech recognition threshold for each number.
The experimental program sequentially clicks corresponding numbers according to the playing sequence after the test subjects hear the three numbers each time, the original signal to noise ratio is changed along with the response condition of the test subjects, if the response is correct, the difficulty is reduced (increased), and if the response is incorrect, the difficulty is increased (reduced); the first adjustment value obtained in the previous stage is used for further adjusting the original signal-to-noise ratio to the triple digital actual representation signal-to-noise ratio. Several hearing healthy subjects were then recruited to complete the test.
Specifically, in the embodiment provided by the invention, one voice embedded in noise is played each time in each round of test, the voice comprises three digits connected in series with a voice prompt, such as 'please listen, 638', the interval between the prompt and the first digit is 200ms, the interval between the three digits is 100-200 ms, and the noise starts and ends at 500ms before and after the whole voice section; the numbers presented each time are random, but the same number combination does not occur (e.g. 5-5-5, 6-6-7) or a combination of sequential increments (e.g., 1-2-3); requiring the subject to sequentially click on the heard numbers on the test interface (e.g., fig. 4); each round of test is carried out for 25 times; the noise presented each time is obtained by randomly intercepting a proper length from the noise material manufactured in the first stage, and the noise volume is fixed to 65dB SPL; the original signal-to-noise ratio of each round of test is-6 dB or-24 dB, then the original signal-to-noise ratio changes along with the reaction condition of the subject each time, if all three numbers are judged to be correct, the signal-to-noise ratio of the next time is reduced, otherwise, the signal-to-noise ratio is improved; the initial signal-to-noise ratio for each round of test was-6 dB (very clear) or-24 dB (completely inaudible); for the d-th digit, the triplet actually presents the signal-to-noise ratio to Mode calculation, wherein->For actually presenting the signal-to-noise ratio +.>For the original signal-to-noise ratio +.>A first adjustment value for the signal-to-noise ratio; RMS calculation does not contain space and interval parts; the signal to noise ratio of the cue is at least 3dB higher than the number and not lower than-10 dB, so as to ensure that the subjects can obviously hear the cue.
In the examples provided herein, 20 hearing healthy subjects were re-recruited for the triple digital identification in noise test, each completed 20 rounds of testing.
The test data of the 1 st round of each subject is removed, and the accuracy of the residual data for each digital identification of each subject is carried out by using a psigniit 4 kit along with the original signal to noise Ratio (RMS) di /RMS noise ) Performing an equation fit for the change in (a); obtaining a second fitting equation:
second fitting equation:
wherein PC is the identification accuracy;the original signal to noise ratio for digital di; />SRT triplet Speech recognition threshold for triple digital discrimination; gamma is the guess probability; lambda is the high limit of accuracy; θ is at SRT triplet A slope at; wherein->SRT is known as data single And gamma, lambda and theta are equation fitting parameters.
S32, obtaining the speech recognition threshold of each digit according to the fitting result of the second fitting equationAverage speech recognition threshold mSRT triplet 。
Calculating speech recognition threshold for each digital triplet digital discrimination based on inter-subject averageNamely:
wherein,a speech recognition threshold for the nth subject for the number di; n is the total number of subjects, n=20; n=1, 2,3,. The.; d=0, 1,2,. The.a.. 9; i=1, 2,3.
Then, an average speech recognition threshold mSRT is calculated from the inter-digit average triplet The method comprises the following steps:
wherein,a speech recognition threshold for the number di; d is the largest number, d=9; i is the number of readouts, i=3; (d+1) I is the total number of digits, (d+1) i=30; d=0, 1,2,. The.a.. 9; i=1, 2,3.
S33, according to the speech recognition threshold of each digitWith average speech recognition threshold mSRT triplet The second adjustment value of the signal to noise ratio is obtained by the difference of the signal to noise ratio, namely, the second adjustment value of each digital signal to noise ratio:
s4, the user uses the hearing test material to conduct hearing measurement, wherein the signal to noise ratio of the actual presentation is calculated by applying the first signal to noise ratio adjustment value and the second signal to noise ratio adjustment value, and a hearing test result is obtained.
In an embodiment of the present invention, the method further comprises the following steps before the user takes an audiometric measurement using the audiometric test material:
the user adjusts the overall volume and starting signal to noise ratio to a comfortable and clearer degree before testing.
Before the test starts, the user clicks "test" on the interface shown in fig. 5, and will hear the speech embedded in the noise, including the alert tone and three subsequent random numbers, such as "please hear 579". The user actively or assisted by other people adjusts the whole volume and the initial signal-to-noise ratio according to own feeling, clicks on the test sound, and repeats the above processes until the whole volume feels comfortable, and the initial signal-to-noise ratio feels clearer.
The user performs audiometry by using the audiometric test, wherein the first and second adjustment values of the signal to noise ratio are applied to obtain the audiometric test result, and the method specifically comprises the following steps:
s41, a user performs audiometry by using the audiometric materials, and calculates an actual presented signal-to-noise ratio according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value; wherein, for digital di, the following formula is adopted for calculating the actual signal-to-noise ratio according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value:
wherein,the signal to noise ratio is actually presented; />Is the original signal to noise ratio;a first adjustment value for the signal-to-noise ratio; />And a second adjustment value of the signal-to-noise ratio. The method comprises the steps of carrying out a first treatment on the surface of the When a user performs a test, the test flow is similar to the triple digital identification for the homogenization processing stage
S42, calculating the average value of the original signal to noise ratio after the test is finished to obtain a hearing test result value; comparing the test result value with a screening threshold value, and judging that the hearing of the user is normal when the hearing test result value is smaller than a mild threshold value; when the hearing test result value is larger than the severe threshold value, judging that the hearing of the user is severely lost; otherwise, judging the slight hearing loss of the user; wherein the screening threshold is determined by the test and data analysis performed by the enrolled subject.
The effect of the self-service hearing rapid measurement method and the screening threshold acquisition provided by the invention are described in the following by specific tests. Audiometry will be performed using the completed hearing test based on triple digital identification. The hearing test results need to provide reliable assessment of the degree of hearing loss, so that the test is required to have higher stability and accuracy, and screening standards are provided for different degrees of hearing loss, and the screening has higher sensitivity and specificity. The test performance and screening standard are obtained by adopting an experimental method, a plurality of subjects with healthy hearing and impaired hearing are recruited, and the digital identification test and the pure-tone hearing test are completed according to a certain experimental design. Measuring the stability of the test according to the variation degree of the results among a plurality of tests and the exercise effect; measuring the accuracy of the test according to the correlation between the test score and the high-frequency average hearing threshold of the pure-tone hearing test; on the basis of the correlation, two screening standards are respectively divided according to slight hearing damage (high-frequency average hearing threshold >20 dB) and heavier hearing damage (high-frequency average hearing threshold >60 dB), and the sensitivity and specificity of the test for screening the slight and severe hearing loss are calculated by using an operator characteristic curve.
Specifically, 90 subjects (aged 20-80 years) were enrolled, 66 of which had varying degrees of hearing impairment (125-8000 Hz pure tone threshold of either side greater than 25 dBHL), and the remaining 24 were healthy. When the final version number identification test is carried out, the main test firstly inquires the current heard content of the subject while adjusting the volume, the signal to noise ratio and playing sound at an adjusting interface (shown in figure 5) until the subject feels comfortable and the number can be clearly identified. The test then begins and each time a set of numbers is played, the subject clicks on the heard number in sequence. For a subject unfamiliar with a computer, it is required that his oral head include the number heard, and the host test is used to click. According to the experimental design, when all subjects receive the test in the first period, the pure tone threshold test and the digital recognition test of noise are completed, wherein the noise test is completed for 3-4 rounds. 14 hearing healthy subjects (age 20-25 years) were then subjected to three additional periods (1 day, 3 days, 7 days apart) with only 4 rounds of digital identification testing completed each period.
Analysis of results: each round of digital recognition testing contained 20 identifications, and the average signal-to-noise ratio of the last 20 was the result of this round of testing, which is an estimate representing the 50% speech acceptance threshold (SRT).
The standard deviation between the multiple rounds of measurement of the digital identification test in the 1 st period is analyzed, and found to be 1.0dB in the hearing impaired people and 0.7dB in the hearing healthy people, which are smaller than 1.3dB and 1.3dB reported by Moore et al, so that the test result has higher credibility.
The analysis of learning effect of multi-period and multi-round digital identification test by using the analysis of variance method finds that learning effect is about 1.3dB in young people with healthy hearing, no obvious learning is available in elderly people with healthy hearing, about 0.7dB in people with impaired hearing, which is equivalent to 0.6dB reported by Moore et al, and learning is available only between the previous two tests, which indicates that the test has performance accompanying time stability when applied to elderly people with risk of hearing impairment.
The correlation analysis of the speech acceptance threshold of the digital test and the high frequency average hearing threshold of the pure tone test shows that the correlation coefficient is 0.92 in the hearing threshold impaired population, which is higher than 0.79 reported by Moore et al, which shows that the test has higher accuracy in reflecting the high frequency hearing loss degree.
On the basis of high correlation, according to the slight hearing damage (the high-frequency average hearing threshold is more than 20 dB) and the severe hearing damage (the high-frequency average hearing threshold is more than 60 dB), two screening standards of a digital identification test are divided, an operator characteristic curve is used for calculating that the optimal standard for slight hearing damage of the test is-13.5 dB, the sensitivity is 90%, the specificity is 96%, and the sensitivity is higher than 87% and 92% reported by Moore et al respectively; the optimal standard for screening severe hearing impairment is-1.9 dB, the sensitivity is 100%, the specificity is 98%, and the sensitivity is higher than 90% and 81% of Moore et al, respectively, which shows that the hearing test has good screening effect on both mild and severe hearing impairment.
The test method is tested by experiments: the test result is stable, the influence of exercise is small, and the repeatability of retest is high; highly relevant to the pure-tone audiometer test, the test accuracy is high; has high sensitivity and specificity for screening mild and severe hearing loss. The user can finish self-test in a short time under a general quiet environment by using the self-contained earphone at the application end, so that the user can use the earphone in daily families conveniently.
In the embodiment provided by the invention, the self-service hearing rapid measurement method can be installed in a mobile phone, a tablet computer or other electronic equipment to form a self-service hearing rapid measurement tool for testing the hearing of a user. Because the method is a voice recognition test in noise, the method can accurately evaluate the daily hearing level without being carried out in a particularly quiet environment; the number is used as a voice material, so that the influence of additional factors such as individual knowledge experience, memory, guess and the like is reduced, and the method is suitable for users in various social groups and ages; the invention is sensitive to high-frequency hearing loss, so that the hearing loss can be found to be reduced in advance, and an early warning signal is provided to remind a user to prevent the hearing loss in advance.
In the embodiments provided by the invention, the noise-in-noise triple digital voice hearing is used for illustration to avoid the interference of environmental noise. Other types of in-noise speech recognition tests, such as in-noise single-tone, sentence, vocabulary, or non-triple digital speech recognition, may also be used during actual use.
The invention also provides a self-service hearing rapid measurement system. As shown in fig. 6, the system includes a processor 62 and a memory 61 storing instructions executable by the processor 62;
processor 62 may be a general-purpose processor, such as a Central Processing Unit (CPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.
Wherein the memory 61 is used for storing the program code and transmitting the program code to the CPU. Memory 61 may include volatile memory such as Random Access Memory (RAM); the memory 61 may also include a nonvolatile memory such as read only memory, flash memory, hard disk, or solid state disk; the memory 61 may also comprise a combination of memories of the kind described above.
Specifically, the self-service hearing rapid measurement system provided by the embodiment of the invention comprises a processor 62 and a memory 61; the memory 61 has stored thereon a computer program operable on the processor 62, which when executed by the processor 62 performs the steps of:
manufacturing a hearing test material;
carrying out homogenization treatment on the single number to obtain a first signal-to-noise ratio adjustment value;
homogenizing the multi-digit according to the first signal-to-noise ratio adjustment value to obtain a second signal-to-noise ratio adjustment value;
and the user performs audiometry by using the audiometric materials, and calculates the actual presented signal-to-noise ratio according to the first signal-to-noise ratio adjustment value and the second signal-to-noise ratio adjustment value to obtain an audiometric result.
Wherein when the hearing test material comprises a speech material and a noise material; in making the hearing test material, the computer program is executed by the processor 62 to perform the following steps;
recording and editing prompt tones and digital voices as voice materials;
randomly extracting digital voice, splicing the digital voice into a random digital string, and superposing a plurality of random digital strings to obtain speech spectrum noise;
and filtering and amplitude reducing the speech spectrum noise to obtain a noise material.
Wherein the following steps are implemented when a computer program is executed by the processor 62;
the number of the digital voices is determined according to the number of the digits, and when the number of the digits is N, the digital voices of 0-9 ten digits in N different positions are recorded respectively.
Wherein when the single number is subjected to the homogenization treatment to obtain the signal-to-noise ratio first adjustment value, the computer program is executed by the processor 62 to realize the following steps;
fitting test data of the single number identification by the subjects to obtain a first fitting equation of each subject for each number identification accuracy rate along with the change of the signal-to-noise ratio;
obtaining a speech recognition threshold and an average speech recognition threshold of each number according to the fitting result of the first fitting equation;
a first adjustment value for the signal-to-noise ratio is derived from the difference between the speech recognition threshold and the average speech recognition threshold for each number. Wherein the following steps are implemented when a computer program is executed by the processor 62;
the first fitting equation uses the following calculation formula:
wherein PC is the identification accuracy;the original signal to noise ratio for digital di;SRT single a speech recognition threshold for single number discrimination; gamma is the guess probability; lambda is the high limit of accuracy; θ is at SRT single A slope at; wherein->For known data, SRT, γ, λ, θ are equation fitting parameters.
Wherein the following steps are implemented when a computer program is executed by the processor 62;
the first signal-to-noise ratio adjustment value is calculated by adopting the following formula:
wherein,a first adjustment value for the signal to noise ratio of the number di; d=0, 1,2,. The.a.. 9; i=1, 2,3;a speech recognition threshold for digit di single digit recognition; mSRT (mSRT) single An average speech recognition threshold for single number recognition.
When the multiple digits are triple digits, and the homogenization processing is performed on the triple digits according to the first adjustment value of the signal to noise ratio to obtain the second adjustment value of the signal to noise ratio, the computer program is executed by the processor 62 to implement the following steps;
fitting test data of the test subjects for identifying the triple numbers to obtain a second fitting equation of each test subject for changing the accuracy of each number identification along with the signal-to-noise ratio;
obtaining a speech recognition threshold and an average speech recognition threshold of each number according to the fitting result of the second fitting equation; a second adjustment value for the signal-to-noise ratio is derived from the difference between the speech recognition threshold and the average speech recognition threshold for each number.
Wherein, when the user performs audiometry by using the audiometric material, the signal-to-noise ratio is calculated according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value, and a audiometric result is obtained, the computer program is executed by the processor 62 to realize the following steps;
the user performs audiometry by using the audiometric materials, and calculates an actual presented signal-to-noise ratio according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value;
after the test is finished, calculating the average value of the original signal to noise ratio to obtain a hearing test result value; comparing the test result value with a screening threshold value, and judging that the hearing of the user is normal when the hearing test result value is smaller than a mild threshold value; when the hearing test result value is larger than the severe threshold value, judging that the hearing of the user is severely lost; otherwise, judging the hearing loss of the user.
Wherein the following steps are implemented when a computer program is executed by the processor 62;
according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value, the actual signal-to-noise ratio is calculated by adopting the following formula:
wherein,the signal to noise ratio is actually presented; />Is the original signal to noise ratio;a first adjustment value for the signal-to-noise ratio; />And a second adjustment value of the signal-to-noise ratio.
The embodiment of the invention also provides a computer readable storage medium. The computer-readable storage medium here stores one or more programs. Wherein the computer readable storage medium may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, hard disk, or solid state disk; the memory may also comprise a combination of the above types of memories. The one or more programs, when executed on the computer-readable storage medium, may be configured to implement some or all of the steps described above for implementing the rapid self-hearing measurement method of the method embodiments described above.
The self-service hearing rapid measurement method and the system provided by the invention are described in detail. Any obvious modifications to the present invention, as would be apparent to those skilled in the art, would constitute an infringement of the patent rights of the invention and would take on corresponding legal liabilities without departing from the true spirit of the invention.
Claims (6)
1. The self-service hearing rapid measurement system is characterized by comprising a processor and a memory; the memory has stored thereon a computer program operable on the processor, which when executed by the processor performs the steps of:
manufacturing a hearing test material;
fitting test data of the single number identification by the subjects to obtain a first fitting equation of each subject for each number identification accuracy rate along with the change of the signal-to-noise ratio;
obtaining a speech recognition threshold and an average speech recognition threshold of each number according to the fitting result of the first fitting equation;
obtaining a first adjustment value of the signal to noise ratio according to the difference between the speech recognition threshold of each number and the average speech recognition threshold;
homogenizing the multi-digit according to the first signal-to-noise ratio adjustment value to obtain a second signal-to-noise ratio adjustment value; fitting test data of the subjects for identifying the multi-digit, and obtaining a second fitting equation of each subject for changing the accuracy of each digit identification along with the signal-to-noise ratio; obtaining a speech recognition threshold and an average speech recognition threshold of each number according to the fitting result of the second fitting equation; obtaining a second adjustment value of the signal to noise ratio according to the difference between the speech recognition threshold of each number and the average speech recognition threshold;
the user performs audiometry by using the audiometric materials, and calculates an actual presented signal-to-noise ratio according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value;
after the test is finished, calculating the average value of the original signal to noise ratio to obtain a hearing test result value; comparing the test result value with a screening threshold value, and judging that the hearing of the user is normal when the hearing test result value is smaller than a mild threshold value; when the hearing test result value is larger than the severe threshold value, judging that the hearing of the user is severely lost; otherwise, judging the hearing loss of the user.
2. The self-service hearing rapid measurement system of claim 1, wherein the hearing test material comprises a speech material and a noise material; a hearing test material is made comprising the steps of:
recording and editing prompt tones and digital voices as voice materials;
randomly extracting digital voice, splicing the digital voice into a random digital string, and superposing a plurality of random digital strings to obtain speech spectrum noise;
and filtering and amplitude reducing the speech spectrum noise to obtain a noise material.
3. The self-service hearing rapid measurement system of claim 2, wherein:
and the number of the digital voices is determined according to the number of the digits, and when the number of the digits is N, 0-9 digital voices with the digits at N different positions are recorded respectively.
4. The self-service hearing rapid measurement system of claim 1, wherein:
the first fitting equation adopts the following calculation formula:
wherein PC is the identification accuracy;the original signal to noise ratio for digital di; />SRT single A speech recognition threshold for single number discrimination; gamma is the guess probability; lambda is the high limit of accuracy; θ is at SRT single A slope at; wherein PC (personal computer) is (are) a->For known data, SRT, γ, λ, θ are equation fitting parameters.
5. The self-service hearing rapid measurement system of claim 1, wherein:
the first adjustment value is each digital signal to noise ratio adjustment value and is calculated by adopting the following formula;
wherein,a first adjustment value for the signal to noise ratio of the number di; d=0, 1,2,. The.a.. 9; i=1, 2,3; />A speech recognition threshold for digit di single digit recognition; mSRT (mSRT) single An average speech recognition threshold for single number recognition.
6. The self-service hearing rapid measurement system of claim 1, wherein:
according to the signal-to-noise ratio first adjustment value and the signal-to-noise ratio second adjustment value, the actual signal-to-noise ratio is calculated by adopting the following formula:
wherein,the signal to noise ratio is actually presented; />Is the original signal to noise ratio; />A first adjustment value for the signal-to-noise ratio; />And a second adjustment value of the signal-to-noise ratio.
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