Method and system for analyzing implantation effect of artificial cochlea of patient with senile deafness

Abstract

The invention relates to the field of hearing analysis, and discloses an artificial cochlea implantation effect analysis method and system for senile deafness patients, and the method comprises the steps: calculating the hearing loss degree of the senile deafness patients; the method comprises the following steps: constructing an auditory test environment of an implanted senile deafness patient, carrying out auditory test on the senile deafness patient, analyzing the comprehensive auditory level of the senile deafness patient, carrying out three-dimensional sound test on the implanted senile deafness patient, constructing a sound source localization analysis model of the senile deafness patient, and analyzing the sound source localization level of the senile deafness patient. Testing the auditory processing level of the senile deafness patient; effect influence factors of the senile deafness patients are analyzed, an auditory effect-time curve of the senile deafness patients is constructed, and effect influence coefficients of the auditory effect-time curve are analyzed; and constructing an implantation effect analysis model after the artificial cochlea corresponding to the senile deafness patient is implanted. According to the method, the comprehensiveness and accuracy of the artificial cochlea implantation effect analysis of the senile deafness patient can be improved.

Description

Technical Field

[0001] The invention relates to a method and system for analyzing the effect of cochlear implantation in patients with presbycusis, and belongs to the field of hearing analysis. Background Art

[0002] A cochlear implant is a small, special electronic device that can convert sound energy into electrical energy. External sound signals are converted and processed into electrical stimulation signals, which can directly avoid the damaged inner ear hair cells to stimulate the auditory nerve and ultimately produce hearing. For patients with presbycusis, cochlear implants bypass the damaged part and directly stimulate the auditory nerve, thereby restoring or providing auditory perception.

[0003] At present, the method for analyzing the effect of cochlear implants still relies on traditional hearing tests, which mainly analyze the implant effect by measuring the patient's hearing thresholds for pure tones of different frequencies in a quiet environment. This method ignores the importance of noise interference and speech comprehension and thus ignores other important aspects of auditory processing, resulting in a relatively simple and unrepresentative effect analysis method.

[0004] Therefore, there is an urgent need for a solution that can improve the comprehensiveness and accuracy of the analysis of cochlear implant effects in patients with presbycusis. Summary of the invention

[0005] The present invention provides a method and system for analyzing the effect of cochlear implantation on patients with presbycusis, the main purpose of which is to improve the comprehensiveness and accuracy of the analysis of the effect of cochlear implantation on patients with presbycusis.

[0006] To achieve the above object, the present invention provides a method for analyzing the effect of cochlear implantation in patients with presbycusis, comprising:

[0007] Obtaining patient data of a presbycusis patient before cochlear implantation, calculating the degree of hearing loss of the presbycusis patient according to the patient data, and analyzing the quality of life of the patient before cochlear implantation based on the degree of hearing loss;

[0008] Constructing a hearing test environment for the presbycusis patient after implantation, performing a hearing test on the presbycusis patient based on the hearing test environment to obtain hearing test data, and analyzing the comprehensive hearing level of the presbycusis patient according to the hearing test data, wherein the comprehensive hearing level includes: aided hearing threshold, speech recognition rate, and rhythm recognition rate;

[0009] Performing a three-dimensional sound test on the presbycusis patient after implantation to obtain patient behavior data, constructing a sound source localization analysis model for the presbycusis patient based on the patient behavior data, analyzing the sound source localization level of the presbycusis patient based on the sound source localization analysis model, constructing a complex auditory scene for the presbycusis patient, and testing the auditory processing level of the presbycusis patient based on the complex auditory scene;

[0010] Collecting the life data of the presbycusis patient after implantation in real time, extracting the auditory performance data in the life data, analyzing the effect influencing factors of the presbycusis patient according to the auditory performance data, constructing the auditory effect-time curve of the presbycusis patient based on the effect influencing factors, and analyzing the effect influence coefficient of the auditory effect-time curve;

[0011] According to the comprehensive hearing level, the sound source localization level, the auditory processing level and the effect influence coefficient, an implantation effect analysis model for the presbycusis patient after cochlear implantation is constructed; based on the patient's quality of life, the implantation effect analysis model is used to analyze the cochlear implant effect for the presbycusis patient.

[0012] Optionally, the process of calculating the hearing loss degree of the presbycusis patient according to the patient data includes:

[0013] According to the patient data, performing an air conduction test and a bone conduction test on the presbycusis patient to obtain air conduction test data and bone conduction test data;

[0014] Calculating the average test hearing of the presbycusis patient according to the air conduction test data and the bone conduction test data;

[0015] Classifying the hearing loss level of the presbycusis patient and determining the hearing loss threshold of the hearing loss level;

[0016] The degree of hearing loss of the presbycusis patient is determined based on the average test hearing and the hearing loss threshold.

[0017] Optionally, constructing a hearing test environment for the presbycusis patient after implantation includes:

[0018] providing a physical space for the presbycusis patient to undergo testing;

[0019] Constructing an acoustic processing module and a background noise module of the physical space;

[0020] Configuring a multi-dimensional testing device for the patient with presbycusis, wherein the multi-dimensional testing device includes: a hearing test device, a speech recognition device, and a rhythm recognition device;

[0021] Planning the testing process and signal processing mechanism for the presbycusis patient;

[0022] According to the test process and the signal processing mechanism, a test control module for the presbycusis patient is constructed;

[0023] According to the acoustic processing module, the background noise module, the multi-dimensional testing device and the test control module, a hearing test environment for the presbycusis patient after implantation is constructed.

[0024] Optionally, analyzing the comprehensive hearing level of the presbycusis patient according to the hearing test data includes:

[0025] Extracting the hearing thresholds of each frequency, quiet test data, noise test data and rhythm description data of the hearing test data;

[0026] Analyzing the post-implantation hearing loss coefficient and hearing loss type of the presbycusis patient according to the hearing thresholds of each frequency;

[0027] Determining the aided hearing threshold of the presbycusis patient based on the post-implantation hearing loss coefficient and the hearing loss type;

[0028] Calculating the quiet speech recognition rate and the noisy speech recognition rate of the presbycusis patient respectively according to the quiet test data and the noisy test data;

[0029] Comprehensively analyzing the speech recognition rate of the presbycusis patient according to the quiet speech recognition rate and the noise speech recognition rate;

[0030] Analyzing the rhythm recognition rate of the presbycusis patient according to the rhythm description data;

[0031] The comprehensive hearing level of the presbycusis patient is comprehensively analyzed based on the rhythm recognition rate, the speech recognition rate and the hearing aid threshold.

[0032] Optionally, the three-dimensional sound test is performed on the presbycusis patient after implantation to obtain patient behavior data, including:

[0033] Analyze the testing needs of the presbycusis patients after implantation;

[0034] According to the test requirements, construct a three-dimensional sound test environment for the patient with presbycusis;

[0035] Based on the three-dimensional sound test environment, simulating a three-dimensional sound test scene for the presbycusis patient;

[0036] Determining test parameters and test protocols for testing the three-dimensional sound test scenario;

[0037] Based on the test parameters and the test protocol, the patient behavior data of the presbycusis patient after implantation is tested.

[0038] Optionally, constructing a sound source localization analysis model for the presbycusis patient based on the patient behavior data includes:

[0039] Extracting the patient positioning angle, actual sound source angle, and reaction time of the patient behavior data;

[0040] Calculating the angle error of the presbycusis patient according to the patient positioning angle and the actual sound source angle;

[0041] Based on the angle error and the reaction time, respectively calculating the average angle error and the average reaction time of the presbycusis patient;

[0042] Calculating the positioning consistency of the presbycusis patient according to the patient positioning angle;

[0043] Based on the average angle error, the positioning consistency and the average reaction time, a sound source localization analysis model for the presbycusis patient is constructed.

[0044] Optionally, extracting auditory performance data from the life data includes:

[0045] analyzing a data type of the life data, and formatting the life data based on the data type to obtain formatted data;

[0046] Performing data cleaning on the formatted data to obtain cleaned data;

[0047] Checking the data integrity of the cleaned data, and performing data conversion on the cleaned data according to the data integrity to obtain converted data;

[0048] defining an extraction index for the converted data, and determining an extraction mechanism for the converted data according to the extraction index;

[0049] According to the extraction mechanism, the converted data is mined to obtain auditory performance data.

[0050] Optionally, analyzing the effect influencing factors of the presbycusis patient according to the auditory performance data includes:

[0051] Analyzing the hearing effect of the patient with presbycusis according to the hearing performance data;

[0052] Preliminarily identifying the influencing factors to be analyzed of the patient with presbycusis according to the final hearing effect;

[0053] Calculating the correlation coefficient between the impact factor to be analyzed and the auditory effect;

[0054] According to the correlation coefficient, the effect influencing factors of the influencing factors to be analyzed are screened out.

[0055] Optionally, constructing the hearing effect-time curve of the patient with presbycusis based on the effect influencing factor includes:

[0056] Calculating the factor regression coefficient of the effect influencing factor to determine the corresponding initial hearing effect of the presbycusis patient;

[0057] Determining the effect analysis error of the presbycusis patient according to the corresponding hearing effect of the presbycusis patient;

[0058] Calculating the final hearing effect of the patient with presbycusis according to the factor regression coefficient, the initial hearing effect and the effect analysis error;

[0059] According to the final hearing effect, a hearing effect-time curve of the presbycusis patient is constructed.

[0060] In order to solve the above problems, the present invention also provides a cochlear implant effect analysis system for presbycusis patients, the system comprising:

[0061] A pre-implantation analysis module is used to obtain patient data of a presbycusis patient before cochlear implantation, calculate the hearing loss degree of the presbycusis patient according to the patient data, and analyze the quality of life of the patient before cochlear implantation based on the hearing loss degree;

[0062] A post-implantation hearing level module is used to construct a hearing test environment for the presbycusis patient after implantation, conduct a hearing test on the presbycusis patient based on the hearing test environment, obtain hearing test data, and analyze the comprehensive hearing level of the presbycusis patient according to the hearing test data, wherein the comprehensive hearing level includes: aided hearing threshold, speech recognition rate, and rhythm recognition rate;

[0063] An auditory localization analysis module is used to perform a three-dimensional sound test on the presbycusis patient after implantation to obtain patient behavior data, construct a sound source localization analysis model for the presbycusis patient based on the patient behavior data, analyze the sound source localization level of the presbycusis patient based on the sound source localization analysis model, construct a complex auditory scene for the presbycusis patient, and test the auditory processing level of the presbycusis patient based on the complex auditory scene;

[0064] An impact analysis module, for collecting the life data of the presbycusis patient after implantation in real time, extracting the auditory performance data in the life data, analyzing the effect influencing factors of the presbycusis patient according to the auditory performance data, constructing the auditory effect-time curve of the presbycusis patient based on the effect influencing factors, and analyzing the effect influence coefficient of the auditory effect-time curve;

[0065] The post-implantation effect analysis module is used to construct an implantation effect analysis model corresponding to the cochlear implant of the patient with presbycusis according to the comprehensive hearing level, the sound source localization level, the auditory processing level and the effect influence coefficient, and analyze the cochlear implant effect of the patient with presbycusis based on the patient's quality of life using the implantation effect analysis model.

[0066] The embodiment of the present invention can accurately quantify the hearing loss degree of the presbycusis patient by calculating the hearing loss degree of the patient according to the patient data, and provide a data basis for the subsequent analysis of the cochlear implant effect; optionally, the embodiment of the present invention can simulate different daily life scenes by constructing an auditory test environment for the presbycusis patient after implantation, and analyze the hearing level of the presbycusis patient in many aspects; the embodiment of the present invention can help to deeply understand the auditory cognitive process of the presbycusis patient by constructing a sound source localization analysis model for the presbycusis patient based on the patient behavior data, and determine the auditory localization ability of the presbycusis patient after implantation; the embodiment of the present invention can test the presbycusis patient based on the complex auditory scene, The auditory processing level of the presbycusis patient can more accurately evaluate the patient's auditory processing ability in a complex background, thereby analyzing the implant effect of the cochlear implant; the embodiment of the present invention can identify the long-term trend of the auditory effect by constructing the auditory effect-time curve of the presbycusis patient based on the effect influencing factor, and understand the improvement or degradation of the patient's auditory function over time. Finally, the embodiment of the present invention analyzes the cochlear implant effect of the presbycusis patient based on the patient's quality of life and uses the implant effect analysis model to predict the impact of cochlear implant on the quality of life of the presbycusis patient, and is used to track the patient's hearing recovery and quality of life changes in the long term, thereby evaluating the durability of the implant effect. Therefore, the method and system for analyzing the effect of cochlear implants on presbycusis patients provided by the embodiment of the present invention can improve the comprehensiveness and accuracy of the analysis of the effect of cochlear implants on presbycusis patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 A schematic flow chart of a method for analyzing the effect of cochlear implantation on presbycusis patients provided by one embodiment of the present invention;

[0068] Figure 2A schematic diagram of a module for implementing the method for analyzing the effect of cochlear implantation on patients with presbycusis provided in one embodiment of the present invention.

[0069] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0070] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0071] The embodiment of the present application provides a method for analyzing the effect of cochlear implants on patients with presbycusis. The execution subject of the method for analyzing the effect of cochlear implants on patients with presbycusis includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the method for analyzing the effect of cochlear implants on patients with presbycusis can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0072] Embodiment 1:

[0073] Reference Figure 1 FIG. 1 is a flow chart of a method for analyzing the effect of cochlear implantation on patients with presbycusis provided in an embodiment of the present invention. In this embodiment, the method for analyzing the effect of cochlear implantation on patients with presbycusis includes:

[0074] S1. Obtain patient data of a presbycusis patient before cochlear implantation, calculate the degree of hearing loss of the presbycusis patient according to the patient data, and analyze the quality of life of the patient before cochlear implantation based on the degree of hearing loss.

[0075] The embodiment of the present invention can predict the effect of cochlear implantation by acquiring the patient data of the presbycusis patient before cochlear implantation, and provide the patient with an expectation of the recovery effect. The patient data refers to various medical information, test results and evaluation reports related to the presbycusis patient.

[0076] The embodiment of the present invention can accurately quantify the hearing loss degree of the patient with presbycusis by calculating the hearing loss degree of the patient according to the patient data, and provide a data basis for the subsequent analysis of the effect of cochlear implantation. The hearing loss degree refers to a quantitative indicator to measure the degree of decline in individual hearing function.

[0077] As an embodiment of the present invention, calculating the hearing loss degree of the presbycusis patient according to the patient data includes:

[0078] According to the patient data, performing an air conduction test and a bone conduction test on the presbycusis patient to obtain air conduction test data and bone conduction test data;

[0079] Calculating the average test hearing of the presbycusis patient according to the air conduction test data and the bone conduction test data;

[0080] Classifying the hearing loss level of the presbycusis patient and determining the hearing loss threshold of the hearing loss level;

[0081] The degree of hearing loss of the presbycusis patient is determined based on the average test hearing and the hearing loss threshold.

[0082] Among them, the hearing test environment refers to a room or space specially designed and configured for hearing assessment, which needs to meet specific acoustic and technical standards to ensure the accuracy and reliability of the test results. The air conduction test data refers to the hearing threshold data measured by the air conduction pathway in the hearing test. The bone conduction test data refers to the hearing threshold data measured by the bone conduction pathway in the hearing test. The average test hearing refers to the average value of the hearing threshold of the subject at each standard test frequency point calculated when conducting a hearing test. The hearing loss grade refers to the classification of the degree of individual hearing loss based on the hearing test results. The hearing loss threshold refers to the minimum sound intensity level at which the subject can hear sounds of a specific frequency when conducting a pure tone hearing test.

[0083] Optionally, the classification of the hearing loss level of the presbycusis patient may be performed by electrophysiological hearing assessment.

[0084] The embodiment of the present invention can determine the living standard of the patient with presbycusis before cochlear implantation by analyzing the patient's quality of life before cochlear implantation based on the degree of hearing loss, and provide reference data for subsequent analysis of the effect after implantation. The patient's quality of life refers to the overall living conditions of an individual in terms of physiology, psychology, social relations and environment.

[0085] Optionally, as an embodiment of the present invention, the analysis of the patient's quality of life before cochlear implantation based on the degree of hearing loss can be performed through a multifunctional hearing assessment.

[0086] S2. Constructing an auditory test environment for the patient with presbycusis after implantation, performing a hearing test on the patient with presbycusis based on the auditory test environment to obtain auditory test data, and analyzing the comprehensive hearing level of the patient with presbycusis based on the auditory test data, wherein the comprehensive hearing level includes: aided hearing threshold, speech recognition rate, and rhythm recognition rate.

[0087] The embodiment of the present invention can simulate different daily life scenes by constructing the hearing test environment of the presbycusis patient after implantation, and analyze the hearing level of the presbycusis patient in many aspects. The hearing test environment refers to the physical space and related technical equipment designed and configured for hearing assessment.

[0088] As an embodiment of the present invention, the construction of the hearing test environment for the presbycusis patient after implantation includes:

[0089] providing a physical space for the presbycusis patient to undergo testing;

[0090] Constructing an acoustic processing module and a background noise module of the physical space;

[0091] Configuring a multi-dimensional testing device for the patient with presbycusis, wherein the multi-dimensional testing device includes: a hearing test device, a speech recognition device, and a rhythm recognition device;

[0092] Planning the testing process and signal processing mechanism for the presbycusis patient;

[0093] According to the test process and the signal processing mechanism, a test control module for the presbycusis patient is constructed;

[0094] According to the acoustic processing module, the background noise module, the multi-dimensional testing device and the test control module, a hearing test environment for the presbycusis patient after implantation is constructed.

[0095] Among them, the physical space refers to an actual room or area designed and prepared specifically for hearing tests. The acoustic processing module refers to a component used to improve and optimize the acoustic characteristics in the hearing test environment. The background noise module refers to a component used to manage and control the background noise in the hearing test environment. The multidimensional test equipment refers to a comprehensive test system used to evaluate the hearing function of patients with presbycusis from different angles and levels. The hearing test equipment refers to instruments and tools used to evaluate personal hearing ability. The speech recognition equipment refers to a special equipment used to evaluate an individual's understanding and recognition ability of speech. The rhythm recognition equipment refers to a special equipment used to evaluate an individual's ability to perceive musical rhythm and beat. The test process refers to the steps and procedures performed in a certain order and standard when conducting a hearing test. The signal processing mechanism refers to the technical methods and algorithms for collecting, processing, analyzing and outputting sound signals during the hearing test process. The test control module refers to a software or hardware system used to manage and guide the hearing test process, which is responsible for coordinating various aspects of the test to ensure that the test is carried out in accordance with predetermined procedures and standards.

[0096] Optionally, the acoustic processing module and the background noise module for constructing the physical space can be constructed by environmental acoustic simulation.

[0097] The embodiment of the present invention performs a hearing test on the patient with presbycusis based on the hearing test environment, and obtains hearing test data that can objectively measure the effect of hearing recovery, improve the quality of life of the patient with presbycusis, and enhance their social participation and life independence. The hearing test data refers to a series of quantitative information collected during the hearing test, which reflects the hearing condition and hearing function of the subject.

[0098] The embodiment of the present invention analyzes the comprehensive hearing level of the presbycusis patient according to the hearing test data, wherein the comprehensive hearing level includes: aided hearing threshold, speech recognition rate and rhythm recognition rate, which can analyze the hearing recovery of the presbycusis patient after cochlear implantation, thereby providing data support for analyzing the effect of cochlear implantation. The comprehensive hearing level refers to the result of a comprehensive assessment of the individual's hearing ability, which includes not only hearing sensitivity (i.e., hearing threshold), but also multiple hearing-related functions and skills. The aided hearing threshold refers to the minimum sound intensity of the test sound that the subject can hear and correctly repeat a certain proportion (usually 50%) of after using a hearing aid when evaluating the hearing-impaired. The speech recognition rate refers to the ability of an individual to correctly recognize and understand the percentage of spoken words or sentences in a hearing test. The rhythm recognition rate refers to the percentage of an individual's ability to correctly recognize and distinguish different rhythm patterns in a hearing test.

[0099] As an embodiment of the present invention, analyzing the comprehensive hearing level of the patient with presbycusis according to the hearing test data includes:

[0100] Extracting the hearing thresholds of each frequency, quiet test data, noise test data and rhythm description data of the hearing test data;

[0101] Analyzing the post-implantation hearing loss coefficient and hearing loss type of the presbycusis patient according to the hearing thresholds of each frequency;

[0102] Determining the aided hearing threshold of the presbycusis patient based on the post-implantation hearing loss coefficient and the hearing loss type;

[0103] Calculating the quiet speech recognition rate and the noisy speech recognition rate of the presbycusis patient respectively according to the quiet test data and the noisy test data;

[0104] Comprehensively analyzing the speech recognition rate of the presbycusis patient according to the quiet speech recognition rate and the noise speech recognition rate;

[0105] Analyzing the rhythm recognition rate of the presbycusis patient according to the rhythm description data;

[0106] The comprehensive hearing level of the presbycusis patient is comprehensively analyzed based on the rhythm recognition rate, the speech recognition rate and the hearing aid threshold.

[0107] Among them, the hearing threshold of each frequency refers to the minimum sound intensity that the subject can hear at different frequencies. The quiet test data refers to the data collected from the hearing test conducted in a quiet environment. The noise test data refers to the data collected from the hearing test in an environment with background noise. The rhythm description data refers to information data related to the rhythm of music. The post-implantation hearing loss coefficient refers to a quantitative indicator used to describe the degree of loss of an individual at a specific frequency after cochlear implantation. The hearing loss type refers to the classification based on the nature and characteristics of the hearing loss. The quiet speech recognition rate refers to the percentage of subjects who can correctly recognize and repeat the speech content heard in a quiet environment without any background noise. The noise speech recognition rate refers to the percentage of subjects who can correctly recognize and repeat the speech content heard in the presence of background noise.

[0108] S3. Perform a three-dimensional sound test on the presbycusis patient after implantation to obtain patient behavior data, construct a sound source localization analysis model for the presbycusis patient based on the patient behavior data, analyze the sound source localization level of the presbycusis patient based on the sound source localization analysis model, construct a complex auditory scene for the presbycusis patient, and test the auditory processing level of the presbycusis patient based on the complex auditory scene.

[0109] In the embodiment of the present invention, by performing a three-dimensional sound test on the patient with presbycusis after implantation, the patient behavior data can provide a data basis for subsequent analysis of the patient's sound source localization ability. The patient behavior data refers to the data recorded on the reaction and performance of the patient with presbycusis to sound stimulation during the three-dimensional sound test.

[0110] As an embodiment of the present invention, the three-dimensional sound test is performed on the patient with presbycusis after implantation to obtain the patient behavior data, including:

[0111] Analyze the testing needs of the presbycusis patients after implantation;

[0112] According to the test requirements, construct a three-dimensional sound test environment for the patient with presbycusis;

[0113] Based on the three-dimensional sound test environment, simulating a three-dimensional sound test scene for the presbycusis patient;

[0114] Determining test parameters and test protocols for the three-dimensional sound test scenario;

[0115] Based on the test parameters and the test protocol, the patient behavior data of the presbycusis patient after implantation is tested.

[0116] Among them, the test requirements refer to the specific conditions and requirements that must be met in order to achieve the research purpose when conducting three-dimensional sound tests on patients with presbycusis. The three-dimensional sound test environment refers to a specially designed auditory test space that can simulate three-dimensional sound scenes in the real world so as to accurately evaluate the hearing ability of users of hearing implant devices. The three-dimensional sound test scene refers to a specific sound experimental scenario designed in a three-dimensional sound test environment to evaluate and train the sound source localization, identification and separation capabilities of users of hearing implant devices. The test parameters refer to various adjustable factors (such as test conditions, measurement techniques, and sound source properties) used to design and execute tests in three-dimensional sound tests. The test protocol refers to a set of detailed operating procedures and guidelines formulated to ensure the consistency, reliability and effectiveness of the test when conducting a three-dimensional sound test.

[0117] Optionally, the three-dimensional sound test scene simulating the presbycusis patient based on the three-dimensional sound test environment may be simulated by a three-dimensional virtual sound field technology.

[0118] The embodiment of the present invention can help to deeply understand the auditory cognitive process of presbycusis patients and determine the auditory localization ability of presbycusis patients after implantation by constructing the sound source localization analysis model of the presbycusis patients based on the patient behavior data. The sound source localization analysis model refers to a computational model based on mathematical and statistical methods, which is used to analyze and evaluate an individual's ability to identify the location of a sound source in three-dimensional space.

[0119] As an embodiment of the present invention, constructing a sound source localization analysis model for the presbycusis patient based on the patient behavior data includes:

[0120] Extracting the patient positioning angle, actual sound source angle, and reaction time of the patient behavior data;

[0121] Calculating the angle error of the presbycusis patient according to the patient positioning angle and the actual sound source angle;

[0122] Based on the angle error and the reaction time, respectively calculating the average angle error and the average reaction time of the presbycusis patient;

[0123] According to the patient positioning angle, the positioning consistency of the presbycusis patient is calculated using the following formula:

[0124]

[0125] Among them, γ represents the positioning consistency, n represents the number of tests of patient behavior data, and d i represents the patient positioning angle for the i-th time;

[0126] Based on the average angle error, the positioning consistency and the average reaction time, a sound source localization analysis model for the presbycusis patient is constructed.

[0127] Among them, the patient positioning angle refers to the angle at which the patient judges the location of the sound source based on the sound heard and points to the location when performing a three-dimensional sound test. The actual sound source angle refers to the angle corresponding to the actual location of the sound source in three-dimensional space relative to a reference point (usually the center of the listener's head). The reaction time refers to the time from the sound source emitting the sound to the patient's reaction (i.e., pointing out the location of the sound source). The angular error refers to the error generated when the patient judges the location of the sound source in the sound source localization test, that is, the angular difference between the location of the sound source pointed by the patient and the actual location of the sound source. The average angular error refers to the average value of the angular errors in all tests in a series of sound source localization tests. The average reaction time refers to the average value of the time it takes for the patient to make a positioning reaction from the sound source emitting the sound in all tests in a series of sound source localization tests. The positioning consistency refers to the stability and repeatability of the patient's judgment of the same sound source location in multiple sound source localization tests.

[0128] Optionally, the sound source localization analysis model for the presbycusis patient based on the average angle error, the positioning consistency and the average reaction time may be constructed by a deep learning method.

[0129] The embodiment of the present invention can analyze the sound source localization level of the presbycusis patient based on the sound source localization analysis model to analyze the change of the sound source localization level before and after hearing intervention (such as cochlear implantation, etc.) to measure the recovery effect. The sound source localization level refers to a quantitative indicator of an individual's ability to determine the location of a sound source in an auditory environment.

[0130] The embodiment of the present invention can more realistically analyze the hearing challenges of presbycusis patients in their daily lives by constructing the complex auditory scene of the presbycusis patients, wherein the complex auditory scene refers to a carefully designed environment that simulates multiple sound sources and auditory challenges in real life.

[0131] Optionally, as an embodiment of the present invention, the complex auditory scene of the presbycusis patient may be constructed by virtual reality technology.

[0132] The embodiment of the present invention can more accurately evaluate the patient's auditory processing ability in a complex background by testing the auditory processing level of the patient with presbycusis based on the complex auditory scene, thereby analyzing the implant effect of the cochlear implant. The auditory processing level refers to the ability of the brain to perform cognitive processing such as recognition, understanding, positioning and memory of sound after receiving the sound signal.

[0133] Optionally, as an embodiment of the present invention, the test of the auditory processing level of the presbycusis patient based on the complex auditory scene can be obtained by binaural testing technology.

[0134] S4. Collect the life data of the presbycusis patient after implantation in real time, extract the auditory performance data in the life data, analyze the effect influencing factors of the presbycusis patient according to the auditory performance data, construct the auditory effect-time curve of the presbycusis patient based on the effect influencing factors, and analyze the effect influence coefficient of the auditory effect-time curve.

[0135] The embodiment of the present invention can continuously monitor the hearing recovery of the patient after cochlear implantation by collecting the life data of the patient with presbycusis in real time, and timely evaluate the implantation effect. The life data refers to various information and data related to the daily life of the patient with presbycusis after cochlear implantation.

[0136] Optionally, as an embodiment of the present invention, the real-time collection of the life data of the presbycusis patient after implantation can be collected through remote monitoring technology.

[0137] The embodiment of the present invention can accurately evaluate the hearing recovery effect of cochlear implant on patients by extracting auditory performance data from the life data. The auditory performance data refers to various data related to the hearing function of patients with presbycusis, which reflects the hearing ability and hearing recovery of patients after cochlear implant.

[0138] As an embodiment of the present invention, the extracting the auditory performance data from the life data includes:

[0139] analyzing a data type of the life data, and formatting the life data based on the data type to obtain formatted data;

[0140] Performing data cleaning on the formatted data to obtain cleaned data;

[0141] Checking the data integrity of the cleaned data, and performing data conversion on the cleaned data according to the data integrity to obtain converted data;

[0142] defining an extraction index for the converted data, and determining an extraction mechanism for the converted data according to the extraction index;

[0143] According to the extraction mechanism, the converted data is mined to obtain auditory performance data.

[0144] Among them, the data type refers to the different forms or structures in which data can be classified during the data analysis process. The formatted data refers to the data that is sorted and converted according to certain standards or specifications so that it has a unified format and structure. The cleaned data refers to the data that has been processed through a series of data cleaning steps (such as deleting missing values ​​and duplicate values, correcting erroneous values, converting abnormal values, etc.) to make the data consistency, accuracy and completeness more suitable for analysis, modeling or other data-driven tasks. The data integrity refers to the degree to which the data maintains accuracy and consistency during storage, processing and use. The converted data refers to the data that has been processed through a series of data conversion processes (such as normalization, standardization, dimensionality reduction and inverse transformation, etc.). The extraction index refers to a series of metrics or standards defined in order to obtain meaningful information from the data. The extraction mechanism refers to a series of methods, processes or techniques used to extract specific information or indicators from raw data.

[0145] Optionally, the extraction index for defining the converted data may be defined by a statistical method.

[0146] The embodiment of the present invention can identify factors that have a significant impact on the hearing effect by analyzing the effect influencing factors of the presbycusis patient according to the auditory performance data, so as to facilitate more accurate effect analysis. Among them, the effect influencing factors refer to those variables that can have a significant impact on the hearing recovery effect of the presbycusis patient after receiving hearing intervention (such as cochlear implantation).

[0147] As an embodiment of the present invention, analyzing the effect influencing factors of the presbycusis patient according to the auditory performance data includes:

[0148] Analyzing the hearing effect of the patient with presbycusis according to the hearing performance data;

[0149] Preliminarily identifying the influencing factors to be analyzed of the presbycusis patient according to the hearing effect of the presbycusis patient;

[0150] The correlation coefficient between the impact factor to be analyzed and the auditory effect is calculated using the following formula:

[0151]

[0152] Among them, μ represents the correlation coefficient, N represents the number of influencing factors to be analyzed, and pj represents the jth impact factor to be analyzed, q j represents the auditory effect corresponding to the jth influencing factor to be analyzed;

[0153] According to the correlation coefficient, the effect influencing factors of the influencing factors to be analyzed are screened out.

[0154] Among them, the hearing effect refers to the specific performance of the improvement of the patient's hearing function after receiving hearing intervention (such as cochlear implant). The influencing factors to be analyzed refer to various factors that may affect the patient's hearing recovery or function that need to be considered when analyzing the hearing effect of patients with presbycusis. The correlation coefficient refers to a statistic used to measure the strength and direction of the linear relationship between two variables.

[0155] The embodiment of the present invention can identify the long-term trend of the hearing effect by constructing the hearing effect-time curve of the patient with presbycusis based on the effect influencing factor, and understand the improvement or degradation of the patient's hearing function over time. The hearing effect-time curve refers to a chart that shows the trend of the hearing function of the patient with presbycusis changing over time after the cochlear implant is implanted.

[0156] As an embodiment of the present invention, constructing the hearing effect-time curve of the presbycusis patient based on the effect influencing factor includes:

[0157] Calculating the factor regression coefficient of the effect influencing factor to determine the corresponding initial hearing effect of the presbycusis patient;

[0158] Determining the effect analysis error of the presbycusis patient according to the hearing effect corresponding to the presbycusis patient;

[0159] According to the factor regression coefficient, the initial hearing effect and the effect analysis error, the final hearing effect of the presbycusis patient is calculated using the following formula:

[0160] q=q 0 +b 1 p 1 +b 2 p 2 +…+b m p m +w

[0161] Among them, q represents the final auditory effect, q 0 represents the initial auditory effect, b 1 represents the factor regression coefficient of the first effect influencing factor, b 2 represents the factor regression coefficient of the second effect influencing factor, b m represents the factor regression coefficient of the mth effect influencing factor, p1 Indicates the first effect influencing factor, p 2 Indicates the second effect factor, p m represents the mth effect influencing factor, and w represents the effect analysis error;

[0162] According to the final hearing effect, a hearing effect-time curve of the presbycusis patient is constructed.

[0163] Among them, the factor regression coefficient refers to the quantitative indicator of the relationship between each effect influencing factor and the hearing effect in the multivariate linear regression model. The initial hearing effect refers to the initial improvement of the patient's hearing function shortly after the implementation of hearing intervention measures (such as cochlear implants). The effect analysis error refers to the deviation or error that occurs when evaluating the hearing effect of patients with presbycusis.

[0164] The embodiment of the present invention can predict the patient's hearing changes in the future by analyzing the effect influence coefficient of the hearing effect-time curve, thereby providing data support for evaluating the effect of cochlear implants. The effect influence coefficient refers to an indicator used to measure the intensity of the effect influence factor on the hearing effect.

[0165] Optionally, as an embodiment of the present invention, the effect influence coefficient of analyzing the auditory effect-time curve may be calculated by a least square method.

[0166] S5. Construct an implant effect analysis model for the presbycusis patient after cochlear implantation based on the comprehensive hearing level, the sound source localization level, the auditory processing level and the effect influence coefficient; and analyze the cochlear implant effect of the presbycusis patient based on the patient's quality of life using the implant effect analysis model.

[0167] The embodiment of the present invention constructs an implantation effect analysis model for the patient with presbycusis corresponding to the cochlear implant according to the comprehensive hearing level, the sound source localization level, the auditory processing level and the effect influence coefficient, which can be used to track the patient's hearing effect in the long term, evaluate the long-term effect of the implanted device and the improvement of the patient's quality of life. The implantation effect analysis model refers to a statistical or machine learning model, which is used to evaluate and predict the hearing recovery effect of the patient with presbycusis after receiving the cochlear implant surgery.

[0168] Optionally, as an embodiment of the present invention, the implantation effect analysis model for the presbycusis patient after cochlear implantation based on the comprehensive hearing level, the sound source localization level, the auditory processing level and the effect influence coefficient can be constructed by a deep neural network method.

[0169] The embodiment of the present invention analyzes the cochlear implant effect of the presbycusis patient based on the patient's quality of life by using the implant effect analysis model, and can predict the impact of the cochlear implant on the quality of life of the presbycusis patient. It is also used for long-term tracking of the patient's hearing recovery and quality of life changes, thereby evaluating the durability of the implant effect.

[0170] The embodiment of the present invention can accurately quantify the hearing loss degree of the presbycusis patient by calculating the hearing loss degree of the patient according to the patient data, and provide a data basis for the subsequent analysis of the cochlear implant effect; optionally, the embodiment of the present invention can simulate different daily life scenes by constructing an auditory test environment for the presbycusis patient after implantation, and analyze the hearing level of the presbycusis patient in many aspects; the embodiment of the present invention can help to deeply understand the auditory cognitive process of the presbycusis patient by constructing a sound source localization analysis model for the presbycusis patient based on the patient behavior data, and determine the auditory localization ability of the presbycusis patient after implantation; the embodiment of the present invention can test the presbycusis patient based on the complex auditory scene, The auditory processing level of the presbycusis patient can more accurately evaluate the patient's auditory processing ability in a complex background, thereby analyzing the implant effect of the cochlear implant; the embodiment of the present invention can identify the long-term trend of the auditory effect by constructing the auditory effect-time curve of the presbycusis patient based on the effect influencing factor, and understand the improvement or degradation of the patient's auditory function over time. Finally, the embodiment of the present invention analyzes the cochlear implant effect of the presbycusis patient based on the patient's quality of life and uses the implant effect analysis model to predict the impact of cochlear implant on the quality of life of the presbycusis patient, and is used to track the patient's hearing recovery and quality of life changes in the long term, thereby evaluating the durability of the implant effect. Therefore, the method and system for analyzing the effect of cochlear implants on presbycusis patients provided by the embodiment of the present invention can improve the comprehensiveness and accuracy of the analysis of the effect of cochlear implants on presbycusis patients.

[0171] Embodiment 2:

[0172] like Figure 2 The figure shows a functional module diagram of a cochlear implant effect analysis system for presbycusis patients according to the present invention.

[0173] The cochlear implant effect analysis system 200 for patients with presbycusis described in the present invention can be installed in an electronic device. According to the functions to be implemented, the cochlear implant effect analysis system for patients with presbycusis can include a pre-implantation analysis module 201, a post-implantation hearing level module 202, an auditory localization analysis module 203, an effect impact analysis module 204, and a post-implantation effect analysis module 205. The module described in the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0174] In the embodiment of the present invention, the functions of each module / unit are as follows:

[0175] The pre-implantation analysis module 201 is used to obtain patient data of the presbycusis patient before cochlear implantation, calculate the hearing loss degree of the presbycusis patient according to the patient data, and analyze the quality of life of the patient before cochlear implantation based on the hearing loss degree;

[0176] The post-implantation hearing level module 202 is used to construct a hearing test environment for the presbycusis patient after implantation, conduct a hearing test on the presbycusis patient based on the hearing test environment, obtain hearing test data, and analyze the comprehensive hearing level of the presbycusis patient according to the hearing test data, wherein the comprehensive hearing level includes: aided hearing threshold, speech recognition rate, and rhythm recognition rate;

[0177] The auditory localization analysis module 203 is used to perform a three-dimensional sound test on the presbycusis patient after implantation to obtain patient behavior data, construct a sound source localization analysis model for the presbycusis patient based on the patient behavior data, analyze the sound source localization level of the presbycusis patient based on the sound source localization analysis model, construct a complex auditory scene for the presbycusis patient, and test the auditory processing level of the presbycusis patient based on the complex auditory scene;

[0178] The effect impact analysis module 204 is used to collect the life data of the presbycusis patient after implantation in real time, extract the auditory performance data in the life data, analyze the effect impact factor of the presbycusis patient according to the auditory performance data, construct the auditory effect-time curve of the presbycusis patient based on the effect impact factor, and analyze the effect impact coefficient of the auditory effect-time curve;

[0179] The post-implantation effect analysis module 205 is used to construct an implantation effect analysis model corresponding to the cochlear implant of the presbycusis patient according to the comprehensive hearing level, the sound source localization level, the auditory processing level and the effect influence coefficient, and analyze the cochlear implant effect of the presbycusis patient based on the patient's quality of life using the implantation effect analysis model.

[0180] In detail, the modules in the cochlear implant effect analysis system 200 for presbycusis patients in the embodiment of the present invention are used in the same manner as described above. Figure 1 The same technical means are used as the method for analyzing the effect of cochlear implantation on patients with presbycusis described in , and can produce the same technical effects, so they will not be repeated here.

[0181] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0182] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for analyzing the effect of cochlear implantation in patients with presbycusis, characterized in that: The method comprises: Obtaining patient data of a presbycusis patient before cochlear implantation, calculating the degree of hearing loss of the presbycusis patient according to the patient data, and analyzing the quality of life of the patient before cochlear implantation based on the degree of hearing loss; Constructing a hearing test environment for the presbycusis patient after implantation, performing a hearing test on the presbycusis patient based on the hearing test environment to obtain hearing test data, and analyzing the comprehensive hearing level of the presbycusis patient according to the hearing test data, wherein the comprehensive hearing level includes: aided hearing threshold, speech recognition rate, and rhythm recognition rate; Performing a three-dimensional sound test on the presbycusis patient after implantation to obtain patient behavior data, constructing a sound source localization analysis model for the presbycusis patient based on the patient behavior data, analyzing the sound source localization level of the presbycusis patient based on the sound source localization analysis model, constructing a complex auditory scene for the presbycusis patient, and testing the auditory processing level of the presbycusis patient based on the complex auditory scene; Collecting the life data of the presbycusis patient after implantation in real time, extracting the auditory performance data in the life data, analyzing the effect influencing factors of the presbycusis patient according to the auditory performance data, constructing the auditory effect-time curve of the presbycusis patient based on the effect influencing factors, and analyzing the effect influence coefficient of the auditory effect-time curve; According to the comprehensive hearing level, the sound source localization level, the auditory processing level and the effect influence coefficient, an implantation effect analysis model for the presbycusis patient after cochlear implantation is constructed; based on the patient's quality of life, the implantation effect analysis model is used to analyze the cochlear implant effect for the presbycusis patient.

2. The method for analyzing the effect of cochlear implantation in patients with presbycusis according to claim 1, characterized in that: The process of calculating the hearing loss degree of the presbycusis patient according to the patient data comprises: According to the patient data, performing an air conduction test and a bone conduction test on the presbycusis patient to obtain air conduction test data and bone conduction test data; Calculating the average test hearing of the presbycusis patient according to the air conduction test data and the bone conduction test data; Classifying the hearing loss level of the presbycusis patient and determining the hearing loss threshold of the hearing loss level; The degree of hearing loss of the presbycusis patient is determined based on the average test hearing and the hearing loss threshold.

3. The method for analyzing the effect of cochlear implantation in patients with presbycusis according to claim 1, characterized in that: The method of constructing a hearing test environment for the patient with presbycusis after implantation comprises: providing a physical space for the presbycusis patient to undergo testing; Constructing an acoustic processing module and a background noise module of the physical space; Configuring a multi-dimensional testing device for the patient with presbycusis, wherein the multi-dimensional testing device includes: a hearing test device, a speech recognition device, and a rhythm recognition device; Planning the testing process and signal processing mechanism for the presbycusis patient; According to the test process and the signal processing mechanism, a test control module for the presbycusis patient is constructed; According to the acoustic processing module, the background noise module, the multi-dimensional testing device and the test control module, a hearing test environment for the presbycusis patient after implantation is constructed.

4. The method for analyzing the effect of cochlear implantation in patients with presbycusis according to claim 1, characterized in that: Analyzing the comprehensive hearing level of the patient with presbycusis according to the hearing test data includes: Extracting the hearing thresholds of each frequency, quiet test data, noise test data and rhythm description data of the hearing test data; Analyzing the post-implantation hearing loss coefficient and hearing loss type of the presbycusis patient according to the hearing thresholds of each frequency; Determining the aided hearing threshold of the presbycusis patient based on the post-implantation hearing loss coefficient and the hearing loss type; Calculating the quiet speech recognition rate and the noisy speech recognition rate of the presbycusis patient respectively according to the quiet test data and the noisy test data; Comprehensively analyzing the speech recognition rate of the presbycusis patient according to the quiet speech recognition rate and the noise speech recognition rate; Analyzing the rhythm recognition rate of the presbycusis patient according to the rhythm description data; The comprehensive hearing level of the presbycusis patient is comprehensively analyzed based on the rhythm recognition rate, the speech recognition rate and the hearing aid threshold.

5. The method for analyzing the effect of cochlear implantation in patients with presbycusis according to claim 1, characterized in that: The three-dimensional sound test is performed on the patient with presbycusis after implantation to obtain patient behavior data, including: Analyze the testing needs of the presbycusis patients after implantation; According to the test requirements, construct a three-dimensional sound test environment for the patient with presbycusis; Based on the three-dimensional sound test environment, simulating a three-dimensional sound test scene for the presbycusis patient; Determining test parameters and test protocols for testing the three-dimensional sound test scenario; Based on the test parameters and the test protocol, the patient behavior data of the presbycusis patient after implantation is tested.

6. The method for analyzing the effect of cochlear implantation in patients with presbycusis according to claim 1, characterized in that: The step of constructing a sound source localization analysis model for the presbycusis patient based on the patient behavior data comprises: Extracting the patient positioning angle, actual sound source angle, and reaction time of the patient behavior data; Calculating the angle error of the presbycusis patient according to the patient positioning angle and the actual sound source angle; Based on the angle error and the reaction time, respectively calculating the average angle error and the average reaction time of the presbycusis patient; Calculating the positioning consistency of the presbycusis patient according to the patient positioning angle; Based on the average angle error, the positioning consistency and the average reaction time, a sound source localization analysis model for the presbycusis patient is constructed.

7. The method for analyzing the effect of cochlear implantation in patients with presbycusis according to claim 1, characterized in that: The extracting of auditory performance data from the life data includes: analyzing a data type of the life data, and formatting the life data based on the data type to obtain formatted data; Performing data cleaning on the formatted data to obtain cleaned data; Checking the data integrity of the cleaned data, and performing data conversion on the cleaned data according to the data integrity to obtain converted data; defining an extraction index for the converted data, and determining an extraction mechanism for the converted data according to the extraction index; According to the extraction mechanism, the converted data is mined to obtain auditory performance data.

8. The method for analyzing the effect of cochlear implantation in patients with presbycusis according to claim 1, characterized in that: The step of analyzing the effect influencing factors of the presbycusis patient according to the auditory performance data includes: Analyzing the hearing effect of the patient with presbycusis according to the hearing performance data; Preliminarily identifying the influencing factors to be analyzed of the patient with presbycusis according to the final hearing effect; Calculate the correlation coefficient between the impact factor to be analyzed and the auditory effect: According to the correlation coefficient, the effect influencing factors of the influencing factors to be analyzed are screened out.

9. The method for analyzing the effect of cochlear implantation in patients with presbycusis according to claim 1, characterized in that: The step of constructing the hearing effect-time curve of the patient with presbycusis based on the effect influencing factor comprises: Calculating the factor regression coefficient of the effect influencing factor to determine the corresponding initial hearing effect of the presbycusis patient; Determining the effect analysis error of the presbycusis patient according to the corresponding hearing effect of the presbycusis patient; Calculating the final hearing effect of the patient with presbycusis according to the factor regression coefficient, the initial hearing effect and the effect analysis error; According to the final hearing effect, a hearing effect-time curve of the presbycusis patient is constructed.

10. A system for analyzing the effect of cochlear implantation in patients with presbycusis, the system implementing the method according to claim 1, characterized in that: The system comprises: A pre-implantation analysis module is used to obtain patient data of a presbycusis patient before cochlear implantation, calculate the hearing loss degree of the presbycusis patient according to the patient data, and analyze the quality of life of the patient before cochlear implantation based on the hearing loss degree; A post-implantation hearing level module is used to construct a hearing test environment for the presbycusis patient after implantation, conduct a hearing test on the presbycusis patient based on the hearing test environment, obtain hearing test data, and analyze the comprehensive hearing level of the presbycusis patient according to the hearing test data, wherein the comprehensive hearing level includes: aided hearing threshold, speech recognition rate, and rhythm recognition rate; An auditory localization analysis module is used to perform a three-dimensional sound test on the presbycusis patient after implantation to obtain patient behavior data, construct a sound source localization analysis model for the presbycusis patient based on the patient behavior data, analyze the sound source localization level of the presbycusis patient based on the sound source localization analysis model, construct a complex auditory scene for the presbycusis patient, and test the auditory processing level of the presbycusis patient based on the complex auditory scene; An impact analysis module, for collecting the life data of the presbycusis patient after implantation in real time, extracting the auditory performance data in the life data, analyzing the effect influencing factors of the presbycusis patient according to the auditory performance data, constructing the auditory effect-time curve of the presbycusis patient based on the effect influencing factors, and analyzing the effect influence coefficient of the auditory effect-time curve; The post-implantation effect analysis module is used to construct an implantation effect analysis model corresponding to the cochlear implant of the patient with presbycusis according to the comprehensive hearing level, the sound source localization level, the auditory processing level and the effect influence coefficient, and analyze the cochlear implant effect of the patient with presbycusis based on the patient's quality of life using the implantation effect analysis model.

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