CN111803080A - Infant distortion otoacoustic detector and detection method thereof - Google Patents
Infant distortion otoacoustic detector and detection method thereof Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/12—Audiometering
- A61B5/121—Audiometering evaluating hearing capacity
- A61B5/125—Audiometering evaluating hearing capacity objective methods
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7221—Determining signal validity, reliability or quality
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
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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 acoustoelectric transducer for receiving sound are arranged in a probe shell, and an earphone silica gel sleeve placed in an ear is connected with the shell through a sound transmitting and receiving pipeline; the shell is provided with a pure sound stimulating sound system. The detection method comprises the steps that a probe emits stimulating sounds, a pure-tone stimulating sound system plays two paths of stimulating sounds, the generated basic stimulating data are stored in a head file of an otoacoustic detection project by simulation software, reflected sounds are received to calculate the noise level, the waveform characteristic value of an adjacent region interval in a trend graph is calculated, and the quality of the collected signals is determined. The invention can improve the noise influence in the distorted otoacoustic infant detection process, 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 emission (DPOAE) is an objective auditory function test that relies on the integrity of the overall cochlear function and is an otoacoustic emission produced by a cochlear nonlinear distortion mechanism. The 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 continuous, or can select pure sound signals with long time delay, the distorted otoacoustic emission stimulation sound is superposed in the time domain, and the frequency domain is separated. The relationship between F1 and F2 is F2/F1 equal to 1.21, the ratio of F2 to F1 ranges from 1.18 to 1.27 according to different frequency bands, and the frequency domain of the effective otoacoustic signal is conventionally taken as F3 equal to (2F 1-F2). Currently, clinical studies indicate that the intensity of 2F1-F2 is the most stable and highest. The intensity of the stimulating sound of the distorted otoacoustic emission is 65dB in general F1 and 55dB in general F2. Domestic and foreign products also analyze the distorted otoacoustic based on the characteristic of the distorted otoacoustic to extract effective signals, so that the distorted otoacoustic is used for clinical cochlear function test.
At present, the domestic infant otoacoustic screening equipment has few products with independent intellectual property rights, most of the products in the market are foreign product otoacoustic hearing screening equipment, and the precision difference of foreign products in clinical use is large. The method for detecting the distortion otoacoustic noise at home and abroad mainly performs band-pass filtering on an acquired time domain signal, and then performs coherent average calculation by prolonging acquisition time so as to achieve the purpose of eliminating white noise and improve the signal-to-noise ratio of detection.
In the prior art, a mute room is required to be arranged in a test environment, the data acquisition time in the test process is prolonged, and coherent averaging is carried out, so that the requirement on high test environment is high, and the requirement cannot be met in some primary screening hospitals. In the distorted otoacoustic detection process, the distorted otoacoustic detection accuracy rate for the early screening purpose is low due to the fact that the infant is subjected to body noise of the newborn and unconscious shaking of the newborn in the detection process, the coherent average noise reduction is difficult to detect the newborn, the testing time of the newborn is long, and anxiety is easily caused.
Disclosure of Invention
Aiming at the defects of 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 technical scheme adopted by the invention is as follows: an ear sound detector for infant distortion comprises a probe shell, wherein an electroacoustic ring energy device and an acoustoelectric transducer for receiving sound are arranged in the shell, and an earphone silica gel sleeve placed in an ear is connected with the shell through a sound transmitting and receiving pipeline; the shell is provided with a pure sound stimulating sound system.
The pure tone stimulated sound system generates pure tone stimulated sounds aligned in phase for simulation software Matlab2015, wherein the intensity F1 corresponds to A of 65dB, the intensity B corresponds to F2 of 55dB of stimulated sounds, the intensity is a continuous waveform, the sampling frequency Fs is 48000HZ, the frequencies of the stimulated sounds are respectively 1000HZ, 2000HZ, 3000HZ and 4000HZ according to F2, and sound construction functions are as follows:
y1(t)＝Asin(2π×F1×t)，0≤t≤85ms (1)
y2(t)＝Bsin(2π×F2×t)，0≤t≤85ms (2)
wherein, the basic stimulus waveform is generated by the formulas (1) and (2), the time is started from 0, 4096 values are calculated at intervals to form a group of stimulus sound waveforms, and the stimulus sound waveforms are played circularly during the test; the intensities A and B are assumed to be fixed sizes, and the generated basic stimulation data is stored in a head file of an otoacoustic detection project by using simulation software.
The detection method of the infant distortion otoacoustic detector comprises the following steps:
the method includes the steps of placing a probe detector and calibrating a probe;
turning the first step if the probe is placed properly, and turning the second step if not;
emitting stimulation sound by the probe;
the pure-tone stimulation sound system plays two paths of stimulation sounds, and the generated basic stimulation data are stored in a head file of an otoacoustic detection project through simulation software;
receiving the reflected sound and calculating the noise level:
filtering processing by adopting Hamming window function
Wherein, alpha is 0.46, N is 2048, the function processes the unnecessary noise, the noise threshold (the noise threshold is set by the logarithmic energy after FFT) judgment is carried out on the data collected by each packet, if the threshold condition is met, the coherent average processing is carried out on the collected data, and each coherent processing is carried out on 420 ms data packets, and a frequency domain waveform trend graph after one FFT is calculated; calculating stability statistics of the received waveform once every two continuous trend graphs;
sixthly, respectively calculating 4 critical interval waveform characteristic values (1KHZ-50HZ, 1KHZ +50HZ), (2KHZ-50HZ, 2KHZ +50HZ), (3KHZ-50HZ, 3KHZ +50HZ), (4KHZ-50HZ, 4KHZ +50HZ) in the trend graph according to the waveform trend graph obtained in the step, wherein the parameters comprise an inflection point alpha 1, a height alpha 2 and a slope alpha 3; continuously acquiring 20 groups of data to perform characteristic clustering once, and using a K-Medians clustering algorithm, wherein the K-Medians is initially input into 2 groups, wherein the first group is initialized to the average intensity value of the neonatal statistical data;
judging whether the condition 1 is met or not according to the stability index calculated in the step sixteenth and the feature cluster classification result in the step sixteenth, determining the quality of the collected signals, and if the condition 1 is met, calculating the signal-to-noise ratio of the group of emission stimulation sound at the frequency point F3; if the condition 1 is not met after 20 times of continuous calculation, judging that the current test probe is not placed at a proper position and requiring manual adjustment of the earplug for testing; wherein
Condition 1: the stability is more than 70%, and the first group of feature classification results accounts for more than 80%;
taking different F2 and F1, repeating steps from first step to second step, using a 3dB threshold value method, namely judging signal-to-noise ratios of 4 groups of F3 points, and if 3 groups are more than 3dB, displaying to pass; otherwise, the display fails.
The step of fifthly, carrying out stability statistics:
stability of received wave: the similarity between the complete waveform received each time and the waveform received last time is more than 80%;
similarity: euclidean distance using two sets of discrete data
The similarity is calculated, wherein N is a group of received wave lengths, and 602, data1 and data2 are respectively the stimulation sound or the received reflected sound data of the two times before and after.
The sound emission rule is as follows: the distorted otoacoustic emission detection selects an earphone channel to circularly emit two paths of pure sound signals, and after delaying for 1800 milliseconds, a microphone is started to receive an auditory canal return sound signal.
By adopting the baby distorted otoacoustic detector and the detection method thereof designed by the technical scheme, the invention improves the noise influence in the distorted otoacoustic baby detection process, reduces the test environment requirement on the distorted otoacoustic detection of the newborn by using a digital signal processing technology and a machine learning method on the basis of not increasing the hardware cost, and reduces the uneasy emotion of the baby in the test process. The invention adds a feature extraction clustering method based on statistics in signal processing, improves the accuracy of infant detection, and shortens the detection time.
Drawings
FIG. 1 is a schematic diagram of an infant distorted otoacoustic detector according to the present invention;
FIG. 2 is a schematic view showing the flow structure of the detection method of the present invention.
Detailed Description
The invention provides a distorted otoacoustic detector for infants and a detection method thereof, which are specifically explained below with reference to the accompanying drawings.
The infant distortion otoacoustic detector comprises a probe shell 1, wherein an electroacoustic ring energy device 2 (a micro loudspeaker) and an acoustoelectric transducer 3 (a micro microphone) are arranged in the shell 1, the electroacoustic ring energy device 2 is used for playing stimulation sounds F1 and F2 respectively, and the acoustoelectric transducer 3 is used for receiving the sounds, and the sound is transmitted to the infant distortion otoacoustic detector through the acoustoelectric transducer 3. An earphone silica gel sleeve 5 placed in the ear is connected with the shell 1 through a transmitting and receiving sound pipeline 4, and the earphone silica gel sleeve 5 can be designed into different sizes according to the right ears of different ages of the month. A pure tone stimulating sound system is arranged in the shell 1, the pure tone stimulating sound system generates pure tone stimulating sounds with phase alignment for simulation software Matlab2015, the intensity F1 corresponds to A of 65dB, B corresponds to F2 of 55dB stimulating sounds, the pure tone stimulating sound system is a continuous waveform, the sampling frequency Fs is 48000HZ, the stimulating sound frequencies respectively adopt F2 of 1000HZ, 2000HZ, 3000HZ and 4000HZ, and the sound construction function is as follows:
y1(t)＝Asin(2π×F1×t)，0≤t≤85ms (1)
y2(t)＝Bsin(2π×F2×t)，0≤t≤85ms (2)
wherein, the basic stimulus waveform is generated by the formulas (1) and (2), the time is started from 0, 4096 values are calculated at intervals to form a group of stimulus sound waveforms, and the stimulus sound waveforms are played circularly during the test; the intensities A and B are assumed to be fixed sizes, and the generated basic stimulation data is stored in a head file of an otoacoustic detection project by using simulation software.
The detection method of the infant distorted otoacoustic detector disclosed by the invention is shown in figure 2 and comprises the following steps:
the method includes the steps of placing a probe detector and calibrating a probe;
turning the first step if the probe is placed properly, and turning the second step if not;
emitting stimulation sound by the probe;
the pure-tone stimulation sound system plays two paths of stimulation sounds, and the generated basic stimulation data are stored in a head file of an otoacoustic detection project through simulation software;
receiving the reflected sound and calculating the noise level:
filtering processing by adopting Hamming window function
Wherein, alpha is 0.46, N is 2048, the function processes the unnecessary noise, the noise threshold (the noise threshold is set by the logarithmic energy after FFT) judgment is carried out on the data collected by each packet, if the threshold condition is met, the coherent average processing is carried out on the collected data, and each coherent processing is carried out on 420 ms data packets, and a frequency domain waveform trend graph after one FFT is calculated; calculating stability statistics of the received waveform once every two continuous trend graphs;
the stability statistical method comprises the following steps:
stability index definition
Stability of received wave: the similarity between the complete waveform received each time and the waveform received last time is more than 80%;
similarity: euclidean distance using two sets of discrete data
The similarity is calculated, wherein N is a group of received wave lengths, and 602, data1 and data2 are respectively the stimulation sound or the received reflected sound data of the two times before and after.
Sixthly, respectively calculating 4 critical interval waveform characteristic values (1KHZ-50HZ, 1KHZ +50HZ), (2KHZ-50HZ, 2KHZ +50HZ), (3KHZ-50HZ, 3KHZ +50HZ), (4KHZ-50HZ, 4KHZ +50HZ) in the trend graph according to the waveform trend graph obtained in the step, wherein the parameters comprise an inflection point alpha 1, a height alpha 2 and a slope alpha 3; continuously acquiring 20 groups of data to perform characteristic clustering once, and using a K-Medians clustering algorithm, wherein the K-Medians is initially input into 2 groups, wherein the first group is initialized to the average intensity value of the neonatal statistical data;
judging whether the condition 1 is met or not according to the stability index calculated in the step sixteenth and the feature cluster classification result in the step sixteenth, determining the quality of the collected signals, and if the condition 1 is met, calculating the signal-to-noise ratio of the group of emission stimulation sound at the frequency point F3; if the condition 1 is not met after 20 times of continuous calculation, judging that the current test probe is not placed at a proper position and requiring manual adjustment of the earplug for testing; wherein
Condition 1: the stability is more than 70%, and the first group of feature classification results accounts for more than 80%;
taking different F2 and F1, repeating steps from first step to second step, using a 3dB threshold value method, namely judging signal-to-noise ratios of 4 groups of F3 points, and if 3 groups are more than 3dB, displaying to pass; otherwise, the display fails.
The sound emission rule of the invention is as follows: the distorted otoacoustic emission detection selects an earphone channel to circularly emit two paths of pure sound signals, and after delaying for 1800 milliseconds, a microphone is started to receive an auditory canal return sound signal.
Because the detail features of the in-ear sounds received by the distorted otoacoustic emission are not obvious in the time domain, but are separated from each other in the frequency domain, in the actual infant test, signals in the frequency band below 3500HZ are particularly easily interfered, which brings great difficulty to the extraction of the effective induced sounds of the effective distorted otoacoustic emission. Therefore, the invention designs a statistical model based on 500 cases of original collecting receipts of 1000 ears and classifies the characteristics of noise, effective signals and emission stimulus sound of frequency domain signal curves of newborns of different ages and sexes respectively, thereby improving the accuracy of distorted otoacoustic detection of infants.
Claims (5)
1. An ear sound detector for baby distortion comprises a probe shell, and is characterized in that an electroacoustic ring energy device and an acoustoelectric transducer for receiving sound are arranged in the shell, and an earphone silica gel sleeve placed in an ear is connected with the shell through a sound transmitting and receiving pipeline; the shell is provided with a pure sound stimulating sound system.
2. The distorted acoustic otoacoustic detector of claim 1, wherein the pure tone sound system generates phase-aligned pure tone sound for simulation software Matlab2015, intensity F1 for a 65dB, F2 for B55 dB, continuous waveform, sampling frequency Fs 48000HZ, frequency of sound for stimulation sound taken as F2 for 1000HZ, 2000HZ, 3000HZ, 4000HZ, sound construction function:
y1(t)＝Asin(2π×F1×t)，0≤t≤85ms (1)
y2(t)＝Bsin(2π×F2×t)，0≤t≤85ms (2)
wherein, the basic stimulus waveform is generated by the formulas (1) and (2), the time is started from 0, 4096 values are calculated at intervals to form a group of stimulus sound waveforms, and the stimulus sound waveforms are played circularly during the test; the intensities A and B are assumed to be fixed sizes, and the generated basic stimulation data is stored in a head file of an otoacoustic detection project by using simulation software.
3. A method of detecting a distorted ear sound detector of an infant as claimed in claim 1 or 2, comprising the steps of:
the method includes the steps of placing a probe detector and calibrating a probe;
turning the first step if the probe is placed properly, and turning the second step if not;
emitting stimulation sound by the probe;
the pure-tone stimulation sound system plays two paths of stimulation sounds, and the generated basic stimulation data are stored in a head file of an otoacoustic detection project through simulation software;
receiving the reflected sound and calculating the noise level:
filtering processing by adopting Hamming window function
Wherein, alpha is 0.46, N is 2048, the function processes the unnecessary noise, the noise threshold (the noise threshold is set by the logarithmic energy after FFT) judgment is carried out on the data collected by each packet, if the threshold condition is met, the coherent average processing is carried out on the collected data, and each coherent processing is carried out on 420 ms data packets, and a frequency domain waveform trend graph after one FFT is calculated; calculating stability statistics of the received waveform once every two continuous trend graphs;
sixthly, respectively calculating 4 critical interval waveform characteristic values (1KHZ-50HZ, 1KHZ +50HZ), (2KHZ-50HZ, 2KHZ +50HZ), (3KHZ-50HZ, 3KHZ +50HZ), (4KHZ-50HZ, 4KHZ +50HZ) in the trend graph according to the waveform trend graph obtained in the step, wherein the parameters comprise an inflection point alpha 1, a height alpha 2 and a slope alpha 3; continuously acquiring 20 groups of data to perform characteristic clustering once, and using a K-Medians clustering algorithm, wherein the K-Medians is initially input into 2 groups, wherein the first group is initialized to the average intensity value of the neonatal statistical data;
judging whether the condition 1 is met or not according to the stability index calculated in the step sixteenth and the feature cluster classification result in the step sixteenth, determining the quality of the collected signals, and if the condition 1 is met, calculating the signal-to-noise ratio of the group of emission stimulation sound at the frequency point F3; if the condition 1 is not met after 20 times of continuous calculation, judging that the current test probe is not placed at a proper position and requiring manual adjustment of the earplug for testing; wherein
Condition 1: the stability is more than 70%, and the first group of feature classification results accounts for more than 80%;
taking different F2 and F1, repeating steps from first step to second step, using a 3dB threshold value method, namely judging signal-to-noise ratios of 4 groups of F3 points, and if 3 groups are more than 3dB, displaying to pass; otherwise, the display fails.
4. The method for detecting the distorted ear sound detector of the baby as claimed in claim 3, wherein the stability statistics in step fifthly:
stability of received wave: the similarity between the complete waveform received each time and the waveform received last time is more than 80%;
similarity: euclidean distance using two sets of discrete data
The similarity is calculated, wherein N is a group of received wave lengths, and 602, data1 and data2 are respectively the stimulation sound or the received reflected sound data of the two times before and after.
5. The method as claimed in claim 3 or 4, wherein the sound emission rules are as follows: the distorted otoacoustic emission detection selects an earphone channel to circularly emit two paths of pure sound signals, and after delaying for 1800 milliseconds, a microphone is started to receive an auditory canal return sound signal.
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Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2148340A1 (en) * | 1995-05-01 | 1996-11-02 | Gianni Di Pietro | Method and apparatus for automatically and reproducibly rating the transmission quality of a speech transmission system |
| US5810740A (en) * | 1995-11-13 | 1998-09-22 | Heart Rhythm Technologies, Inc. | System and method for analyzing electrogram waveforms |
| CN1245048A (en) * | 1999-07-23 | 2000-02-23 | 清华大学 | Audibility measurement instrument emitting sound to ear and its test method |
| US6231521B1 (en) * | 1998-12-17 | 2001-05-15 | Peter Zoth | Audiological screening method and apparatus |
| CN1315032A (en) * | 1998-06-26 | 2001-09-26 | 阿斯科姆股份公司 | Method for executing automatic evaluation of transmission quality of audio signals |
| CN1356881A (en) * | 1999-04-29 | 2002-07-03 | 埃尔维·考斯维克 | Handheld audiometric device and method of testing hearing |
| CN200980674Y (en) * | 2006-10-16 | 2007-11-28 | 河南迈松医用设备制造有限公司 | Ear sound emitting detecting probe |
| CN101593517A (en) * | 2009-06-29 | 2009-12-02 | 北京市博汇科技有限公司 | A kind of audio frequency comparison system and audio power comparison method thereof |
| CN102892069A (en) * | 2012-09-10 | 2013-01-23 | 清华大学 | Stimulus frequency otoacoustic emission tuning curve detection and calibration system |
| CN103239235A (en) * | 2013-04-25 | 2013-08-14 | 清华大学深圳研究生院 | Multifunctional comprehensive otoacoustic emission detector |
| CN104921734A (en) * | 2015-07-03 | 2015-09-23 | 谢清华 | Newborn hearing screening instrument |
| CN107582068A (en) * | 2017-10-12 | 2018-01-16 | 南阳师范学院 | A kind of distortion product otoacoustic emissions detecting strategy based on the cycle from relevant principle |
| CN108209934A (en) * | 2018-01-11 | 2018-06-29 | 清华大学 | Hearing sensitivity detecting system based on frequency of stimulation otoacoustic emission |
| CN109350037A (en) * | 2018-10-26 | 2019-02-19 | 安徽智云医疗科技有限公司 | A method of identifying atrial fibrillation and atrial premature beats from 10 seconds electrocardiograms |
-
2020
- 2020-06-11 CN CN202010529414.9A patent/CN111803080B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2148340A1 (en) * | 1995-05-01 | 1996-11-02 | Gianni Di Pietro | Method and apparatus for automatically and reproducibly rating the transmission quality of a speech transmission system |
| US5810740A (en) * | 1995-11-13 | 1998-09-22 | Heart Rhythm Technologies, Inc. | System and method for analyzing electrogram waveforms |
| CN1315032A (en) * | 1998-06-26 | 2001-09-26 | 阿斯科姆股份公司 | Method for executing automatic evaluation of transmission quality of audio signals |
| US6231521B1 (en) * | 1998-12-17 | 2001-05-15 | Peter Zoth | Audiological screening method and apparatus |
| CN1356881A (en) * | 1999-04-29 | 2002-07-03 | 埃尔维·考斯维克 | Handheld audiometric device and method of testing hearing |
| CN1245048A (en) * | 1999-07-23 | 2000-02-23 | 清华大学 | Audibility measurement instrument emitting sound to ear and its test method |
| CN200980674Y (en) * | 2006-10-16 | 2007-11-28 | 河南迈松医用设备制造有限公司 | Ear sound emitting detecting probe |
| CN101593517A (en) * | 2009-06-29 | 2009-12-02 | 北京市博汇科技有限公司 | A kind of audio frequency comparison system and audio power comparison method thereof |
| CN102892069A (en) * | 2012-09-10 | 2013-01-23 | 清华大学 | Stimulus frequency otoacoustic emission tuning curve detection and calibration system |
| CN103239235A (en) * | 2013-04-25 | 2013-08-14 | 清华大学深圳研究生院 | Multifunctional comprehensive otoacoustic emission detector |
| CN104921734A (en) * | 2015-07-03 | 2015-09-23 | 谢清华 | Newborn hearing screening instrument |
| CN107582068A (en) * | 2017-10-12 | 2018-01-16 | 南阳师范学院 | A kind of distortion product otoacoustic emissions detecting strategy based on the cycle from relevant principle |
| CN108209934A (en) * | 2018-01-11 | 2018-06-29 | 清华大学 | Hearing sensitivity detecting system based on frequency of stimulation otoacoustic emission |
| WO2019137079A1 (en) * | 2018-01-11 | 2019-07-18 | 清华大学 | Auditory sensitivity detection system based on stimulus-frequency otoacoustic emissions |
| CN109350037A (en) * | 2018-10-26 | 2019-02-19 | 安徽智云医疗科技有限公司 | A method of identifying atrial fibrillation and atrial premature beats from 10 seconds electrocardiograms |
Non-Patent Citations (2)
| Title |
|---|
| 李晋等: "基于递归分析和聚类的大地电磁信噪辨识及分离", 《地球物理学报》 * |
| 李晋等: "基于递归分析和聚类的大地电磁信噪辨识及分离", 《地球物理学报》, vol. 60, no. 05, 31 May 2017 (2017-05-31), pages 1918 - 1936 * |
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