Distributed autonomous pure tone test system and signal processing method

Abstract

The present application relates to the field of audiology medical equipment and electronic medical technology, and particularly relates to a distributed autonomous pure tone test system and a signal processing method, comprising: a strategy definition and distribution module, which is used for constructing and distributing customizable audiometry strategies based on the combination of parameters, capabilities and response units; an environment adaptation and signal generation module, which is used for detecting environmental noise and dynamically adjusting signal parameters in the strategy to generate and play pure tone test signals adapted to the environment; a response acquisition and local processing module, which is used for acquiring user responses and locally storing the responses after associating the responses with strategy execution states; and an intelligent synchronization module, which is used for intelligently triggering the synchronization of local data to a central server according to network and data attributes. The method realizes autonomous pure tone hearing test with high flexibility, high reliability and offline capability in a distributed multi-scene.

Description

Technical Field

[0001] This invention relates to the fields of audiological medical devices and electronic medical technology, and in particular to a distributed autonomous pure tone testing system and signal processing method. Background Technology

[0002] Pure-tone audiometry is a core clinical method for assessing hearing thresholds and diagnosing hearing impairment. Traditionally, it relies on professional audiologists operating centralized audiometry equipment in a standard soundproof room. In recent years, with the development of portable audiometry devices and mobile applications, technological solutions for hearing screening in non-professional environments have emerged, such as smartphone-based audiometry applications and portable audiometers using wireless transmission. These solutions have improved the convenience of audiometry to some extent, but their system architecture is still mostly centralized or standalone. The audiometry process, parameters, and result analysis methods are usually fixed, making it difficult to flexibly customize them according to different clinical scenarios, research needs, or user groups. At the same time, these systems generally rely on stable network connections for data management and analysis. In application scenarios with poor network conditions or complete offline access, such as communities, homes, and remote areas, their availability and reliability are severely limited.

[0003] However, existing technical solutions face a prominent common technical problem when implementing distributed, multi-scenario deployments: the system lacks a mechanism for executing and ensuring audiometry strategies autonomously, accurately, and flexibly in offline conditions. Specifically, existing systems either hardcode the audiometry logic into device firmware or applications, making it impossible to adjust test procedures and parameters according to specific needs; or, while supporting simple parameter settings, they cannot abstract complex audiometry behaviors into standardized strategy units that are editable, distributable, and consistently executed on heterogeneous hardware. This results in the system either failing to function at the edge without network connectivity or only being able to execute pre-set, fixed procedures, failing to meet personalized and diverse hearing testing needs, and struggling to guarantee medical-grade consistency of the same test results across different devices, thus limiting the widespread adoption and in-depth application of high-quality hearing testing services. Summary of the Invention

[0004] To overcome the above shortcomings, this invention provides a distributed autonomous pure tone testing system and signal processing method, aiming to improve the problem that traditional pure tone audiometry systems, due to their centralized architecture and fixed processes, cannot achieve personalized, highly reliable, and offline autonomous hearing testing in a distributed, multi-scenario environment.

[0005] In a first aspect, the present invention provides the following technical solution: a distributed autonomous pure tone testing system, comprising the following modules: The strategy definition and distribution module is used to construct an audiometry strategy, wherein the audiometry strategy is defined by decomposing the audiometry process into a combination of parameter units, capability units, and response units. The parameter units are used to characterize the pure tone frequency and loudness, the capability units are used to define the operation of playing pure tones, and the response units are used to define the acquisition of user input. The audiometry strategy is then distributed to one or more audiometry nodes. The environment adaptation and signal generation module is used to detect the current test environment parameters when the audiometry node starts the test; based on the current test environment parameters, adaptively adjust the signal generation parameters in the audiometry strategy; and generate and play the corresponding pure tone test signal according to the adjusted signal generation parameters. The response acquisition and local processing module is used to acquire response data input by the user in response to the pure tone test signal; associate the response data with the current execution state in the listening strategy, and store it in the local database of the listening node; The intelligent synchronization module is used to monitor the network status and data attributes of the listening nodes; when the preset synchronization trigger conditions are met, the listening data stored in the local database is synchronized to the central server.

[0006] Preferably, in the strategy definition and distribution module, the step of constructing the listening strategy specifically includes: Define at least one frequency parameter and at least one loudness parameter; Define at least one playback capability unit, the playback capability unit being configured to play a pure tone test signal based on the frequency parameter and the loudness parameter; Define at least one response unit, the response unit being configured to acquire user input in response to a played pure tone test signal; The frequency parameter, the loudness parameter, the playback capability unit, and the response unit are associated to form an audiometric behavior unit. The audiometry strategy is generated based on at least one of the audiometry behavior units.

[0007] Preferably, in the strategy definition and distribution module, the step of distributing the listening strategy to one or more listening nodes specifically includes: Generate and associate a version identifier for the listening strategy; The listening policy carrying the version identifier is sent from the policy management node to the target listening node; The target listening node receives the listening strategy and the version identifier, and stores the listening strategy and the version identifier locally.

[0008] Preferably, in the environment adaptation and signal generation module, the step of detecting the current test environment parameters when the listening node starts the test specifically includes: The background sound signal of the current environment is collected through the microphone configured in the listening node; The sensors configured at the listening nodes collect interference signals from the current environment. Based on the background sound signal, determine the background noise level parameters; Based on the interference signal, determine the electromagnetic interference level parameters; The current test environment parameters include the background noise level parameters and the electromagnetic interference level parameters.

[0009] Preferably, in the environment adaptation and signal generation module, the step of adaptively adjusting the signal generation parameters in the listening strategy based on the current test environment parameters specifically includes: Obtain the reference loudness parameter defined in the audiometry strategy; The reference loudness parameter is compared with the background noise level parameter; Based on the comparison results, a loudness adjustment amount is generated to compensate for the background noise; Based on the loudness adjustment amount, the reference loudness parameter is corrected to obtain the adjusted loudness parameter; The signal generation parameters include at least the adjusted loudness parameter.

[0010] Preferably, in the environment adaptation and signal generation module, the step of generating and playing the corresponding pure tone test signal according to the adjusted signal generation parameters specifically includes: Based on the frequency and loudness parameters in the adjusted signal generation parameters, a corresponding digital audio signal is generated; The hardware abstraction layer is invoked to convert the digital audio signal into a drive signal suitable for the target audio output device; The drive signal is played through the target audio output device to generate the pure tone test signal.

[0011] Preferably, in the response acquisition and local processing module, the steps of acquiring the user's response data to the pure tone test signal, associating the response data with the current execution state in the listening strategy, and storing it in the local database of the listening node specifically include: Record the first timestamp when the user generates an input operation on the currently playing pure tone test signal; Record the frequency and loudness parameters corresponding to the currently playing pure tone test signal; Based on the execution logic of the audiometry strategy, determine the audiometry behavior unit corresponding to the response data; The first timestamp, the frequency parameter, the loudness parameter, and the determined audiometry behavior unit identifier are associated to form a structured response record; The structured response record is written into the local database of the listening node.

[0012] Preferably, in the intelligent synchronization module, the network status and data attributes of the listening node are monitored; when the preset synchronization trigger condition is met, the step of synchronizing the listening data stored in the local database to the central server specifically includes: Continuously monitor the network connection status of the listening node and the data attributes of the listening data to be synchronized in the local database; Determine whether the network connection status and the data attributes together satisfy a preset combination of synchronization triggering conditions; When it is determined that the combination of the synchronization triggering conditions is met, the listening data to be synchronized is extracted from the local database; The extracted audiometry data is sent to the central server.

[0013] Secondly, the present invention provides the following technical solution: a signal processing method, the method comprising: Obtain an audiometry strategy based on a combination of parameters, capabilities, and response units, wherein the parameter units include at least a target frequency and a reference loudness; When starting the audiometry test, the background noise level of the current test environment is detected; The reference loudness is compared with the background noise level, and a loudness compensation value is determined based on the comparison result; Based on the target frequency and the final loudness determined by the reference loudness and the loudness compensation value, a corresponding pure tone test signal is generated; Play the pure tone test signal and collect the user's input response to the played signal; The audiometry record containing the input response, the target frequency, and the final loudness is associated with the current execution context of the audiometry strategy and stored locally.

[0014] The present invention has the following beneficial effects: 1. In this invention, by abstracting the audiometry process into a combination of parameter units, capability units, and response units, and constructing a visual strategy editing and distribution module, this solution enables non-programmers to flexibly customize the complete audiometry process, including frequency sequences, loudness variation rules, and response logic, according to different clinical scenarios, research objectives, or user groups. This overcomes the drawbacks of fixed processes and rigid parameters in traditional systems, achieving highly personalized hearing testing.

[0015] 2. In this invention, by deploying audiometry nodes with environmental awareness capabilities, background noise and electromagnetic interference levels are detected in real time. Based on this, the signal generation parameters in the audiometry strategy are dynamically and adaptively adjusted. This solution can effectively compensate for the impact of environmental interference on the test signal. Combined with a hardware abstraction layer, consistent signal output is ensured across different devices, enabling audiometry results with near-professional audiometry accuracy to be obtained even in complex acoustic environments such as non-standard communities and homes.

[0016] 3. This invention employs an edge computing and central coordination architecture. The listening nodes possess complete offline working capabilities, enabling them to autonomously execute customized listening strategies and securely store data locally even without a network connection. When the network is restored, the intelligent synchronization module automatically triggers and completes data synchronization based on network status and data attributes. This ensures the continuous availability of the system in remote areas and mobile scenarios where the network is unstable or completely disconnected, and guarantees the complete collection of all listening data. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the system architecture of the distributed autonomous pure tone testing system proposed in this invention; Figure 2 This is a schematic diagram of the editing interface of the distributed autonomous pure tone testing system proposed in this invention; Figure 3 This is a schematic diagram of the custom algorithm formula editing interface of the distributed autonomous pure tone testing system proposed in this invention; Figure 4 This is a schematic diagram of the distributed data synchronization process of the distributed autonomous pure tone testing system proposed in this invention; Figure 5 This is a schematic flowchart of a signal processing method proposed in this invention. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1: In a first embodiment of the present invention, the present invention provides a distributed autonomous pure tone testing system, such as... Figures 1-4 As shown, it includes the following steps: The strategy definition and distribution module is used to construct the listening test strategy. The listening test strategy is defined by decomposing the listening test process into a combination of parameter units, capability units and response units. The parameter units are used to characterize the pure tone frequency and loudness, the capability units are used to define the operation of playing pure tone, and the response units are used to define the acquisition of user input. The listening test strategy is then distributed to one or more listening test nodes.

[0020] Furthermore, in the strategy definition and distribution module, the specific steps for constructing the listening strategy include: Define at least one frequency parameter and at least one loudness parameter; Define at least one playback capability unit, which is configured to play a pure tone test signal based on frequency and loudness parameters; Define at least one response unit, which is configured to acquire user input in response to the played pure tone test signal; The frequency parameters, loudness parameters, playback capability units, and response units are associated to form a listening behavior unit. A listening strategy is generated based on at least one listening behavior unit.

[0021] Furthermore, in the strategy definition and distribution module, the steps for distributing the listening strategy to one or more listening nodes specifically include: Generate and associate a version identifier for the listening strategy; The listening policy carrying the version identifier is sent from the policy management node to the target listening node; The target listening node receives the listening strategy and version identifier, and stores the listening strategy and version identifier locally.

[0022] Specifically, the audiometry strategy is constructed based on a combined model of parameter units, capability units, and response units. The specific implementation steps are as follows: First, define the parameter units. The system provides a parameter definition interface for users to create or edit core parameters describing the audiometry state. Each defined parameter unit must include at least one frequency parameter and one loudness parameter. The frequency parameter specifies the frequency value of the pure-tone test signal; for example, it can be defined as a parameter... Its value can be set to 250 Hz, 500 Hz, 1000 Hz, etc. The loudness parameter is used to specify the intensity reference value of the pure tone test signal; for example, it can be defined as a parameter. Its value can be set to 20 decibels hearing level, 40 decibels hearing level, etc.; The second step is to define capability units. The system provides a capability definition interface for creating executable operation units. At least one playback capability unit must be defined. This playback capability unit is configured to play a specified pure-tone test signal based on the frequency and loudness parameters defined in the first step. For example, a capability can be defined... Its execution logic is as follows: call the audio playback interface to play an audio signal with a frequency equal to the parameter. Value, loudness equals parameter Pure tone signals with fixed values ​​and durations; The third step is to define the response unit. The system provides a response definition interface for creating listening units that respond to system or user input. At least one response unit must be defined. This response unit is configured to capture user input in response to the played pure tone test signal. For example, a response can be defined... Its logic is as follows: listen for events where a specified button on the user interface is pressed, and record the response when the event occurs; The fourth step involves assembling and generating audiometric behavioral units. The system uses a graphical editing interface or scripts to logically associate defined frequency parameters, loudness parameters, playback capability units, and response units to construct a complete audiometric behavioral unit. This unit represents a complete "stimulus-presentation-user response" basic audiometric beat. A single audiometric behavioral unit... Logically, it can be represented as a set of parameter units, capability units, and response units, that is: ; in, , and Represents other optional parameters, capabilities, and responses; The fifth step is to generate a complete audiometry strategy. The system allows users to combine and arrange multiple audiometry action units as described above to form complex audiometry processes. Logically, the entire audiometry strategy L is a sequential combination of all audiometry action units, denoted as L = Σ (audiometry action units). The system will save the final strategy structure, including the definitions of all units and the logical relationships between them, in a system-parseable structured data format, such as JSON or XML; The completed listening policy will be distributed to the target listening nodes through the following steps: When the listening policy is saved or updated on the policy management node (i.e., the central server or main workstation), the system automatically generates and associates a globally unique version identifier with the policy. This version identifier is used to uniquely identify and track policy changes in a distributed environment. One implementation method is to use a version vector containing a timestamp and node identifier; the policy management node sends the complete listening policy data packet carrying the version identifier to one or more designated target listening nodes via wired or wireless network. An encrypted channel is used during transmission to ensure data security; after receiving the listening policy data packet, the target listening node parses the listening policy content and its associated version identifier. Subsequently, the node stores the complete content of the listening policy and the version identifier in its local persistent storage, such as an embedded database or file system. This allows the listening node to independently load and execute the policy upon subsequent startup, without needing to connect to the policy management node in real time.

[0023] The environment adaptation and signal generation module is used to detect the current test environment parameters when the audiometry node starts the test; based on the current test environment parameters, it adaptively adjusts the signal generation parameters in the audiometry strategy; and generates and plays the corresponding pure tone test signal according to the adjusted signal generation parameters.

[0024] Furthermore, in the environment adaptation and signal generation module, the steps for detecting the current test environment parameters when the listening node starts the test specifically include: The background sound signal of the current environment is collected through the microphone configured in the listening node; The interference signals of the current environment are collected through the sensors configured at the listening nodes; Determine the background noise level parameters based on the background sound signal; Determine electromagnetic interference level parameters based on interference signals; The current test environment parameters include background noise level parameters and electromagnetic interference level parameters.

[0025] Furthermore, in the environment adaptation and signal generation module, the steps for adaptively adjusting the signal generation parameters in the listening strategy based on the current test environment parameters specifically include: Obtain the baseline loudness parameter defined in the audiometry strategy; Compare the reference loudness parameter with the background noise level parameter; Based on the comparison results, a loudness adjustment amount is generated to compensate for background noise; Based on the loudness adjustment amount, the reference loudness parameter is corrected to obtain the adjusted loudness parameter; Among them, the signal generation parameters include at least the adjusted loudness parameter.

[0026] Furthermore, in the environment adaptation and signal generation module, the steps of generating and playing the corresponding pure tone test signal based on the adjusted signal generation parameters specifically include: Based on the frequency and loudness parameters in the adjusted signal generation parameters, a corresponding digital audio signal is generated. The hardware abstraction layer is invoked to convert the digital audio signal into a drive signal suitable for the target audio output device; The drive signal is played through the target audio output device to generate a pure tone test signal.

[0027] Specifically, before a listening test node starts or is about to perform a listening test, the environment adaptation and signal generation module automatically executes the environment detection process. The first step is to collect background sound signals. The listening node uses its built-in or external high-precision microphone at a preset sampling rate, such as 44.1 kHz, to collect a duration of current environmental audio signal as the background sound signal. The second step is to collect environmental interference signals. The listening node uses its built-in electromagnetic sensor or analyzes the state of the audio codec circuit to collect signals reflecting the intensity of electromagnetic interference in the current environment as interference signals. The third step is to determine the background noise level parameters. The system analyzes and processes the collected background sound signals. First, the signal is bandpass filtered to remove components outside the pure tone test frequency range. Then, the effective value or equivalent sound pressure level of the filtered signal is calculated. This calculated value is the background noise level parameter. The unit is decibels; the fourth step is to determine the electromagnetic interference level parameters. The system analyzes the collected interference signals, such as calculating their signal strength or signal-to-noise ratio in a specific frequency band, thereby quantifying the electromagnetic interference level parameters. This parameter can be a dimensionless rank value or an intensity value in specific units. Ultimately, the current test environment parameter Env is determined by the background noise level parameter. Electromagnetic interference level parameters Together they constitute, i.e., Env={ }; After obtaining the current test environment parameters, the module dynamically adjusts the signal generation parameters in the upcoming audiometry strategy. The module parses the baseline loudness parameter defined in the current audiometry unit, which has not undergone environmental compensation, from the loaded audiometry strategy. The unit is decibel hearing; the module will use the reference loudness parameter. Compared with the detected background noise level parameter A comparison is performed. The purpose of the comparison is to determine whether ambient noise might mask the test pure tone. Based on the comparison results, the system calculates a loudness adjustment amount ΔL using a preset adjustment algorithm. This adjustment amount is calculated to compensate for the influence of background noise, ensuring that the signal-to-noise ratio of the test pure tone reaches a level that is clearly audible. A basic adjustment algorithm is as follows: If If it exceeds a certain threshold, then let ΔL = k. Where k is the compensation coefficient, The noise impact threshold is set; otherwise, ΔL=0, and the calculated loudness adjustment amount ΔL is compared with the reference loudness parameter. By performing algebraic addition, we obtain the adjusted loudness parameter used for generating the actual signal. ,Right now = +ΔL, the adjusted signal generation parameter set must include at least the frequency parameter F and the adjusted loudness parameter. ; Based on the adjusted signal generation parameters, the module generates and plays a physical pure tone signal. The digital signal processor then determines the frequency parameter F and loudness parameter from the adjusted signal generation parameters. This generates a corresponding digital audio signal. This signal is a sine wave, its digital frequency determined by the frequency parameter F and the audio sampling rate, and its digital amplitude determined by the adjusted loudness parameter. The signal is calculated using a decibel-to-linear amplitude conversion formula. This formula incorporates device calibration data. The system calls the unified interface of the hardware abstraction layer, taking the standard format digital audio signal generated in the previous step as input. The hardware abstraction layer performs necessary format conversion, resampling, and gain mapping based on the specific model and drive characteristics of the target audio output device actually connected to the current listening node, converting the standard digital audio signal into a specific format signal that the target audio output device can directly drive. This process decouples application logic from hardware details. The system instructs the target audio output device, such as air-conduction or bone-conduction headphones, to play the drive signal converted by the hardware abstraction layer, thereby physically generating the frequency parameter F and the adjusted loudness parameter. Correspondingly, pure tone test signals that meet hearing level requirements.

[0028] The response acquisition and local processing module is used to acquire response data from user input of pure tone test signals; associate the response data with the current execution status in the listening strategy; and store it in the local database of the listening node.

[0029] Furthermore, in the response acquisition and local processing module, the steps of acquiring user response data to the pure tone test signal, associating the response data with the current execution state in the listening strategy, and storing it in the local database of the listening node specifically include: Record the first timestamp when the user generates an input operation on the currently playing pure tone test signal; Record the frequency and loudness parameters corresponding to the currently playing pure tone test signal; Based on the execution logic of the audiometry strategy, determine the audiometry behavior unit corresponding to the response data; The first timestamp, frequency parameters, loudness parameters, and the identified listening behavior unit identifier are associated to form a structured response record; The structured response records are written to the local database of the listening node.

[0030] Specifically, after the system plays a pure tone test signal through the environment adaptation and signal generation module, the module starts a high-precision timer and listens for a preset user input interface. This interface can be a virtual button on the screen, a physical button, or an external responder. Once a valid input operation is detected from the user in response to the currently playing pure tone test signal, the module immediately records the precise moment of the operation as a first timestamp. This timestamp, typically in milliseconds or microseconds, is acquired from the start of the listening test or from the system clock. The module also records the key generation parameters corresponding to the pure-tone test signal that triggered the user response. These parameters are obtained directly from the output of the environment adaptation and signal generation module, and include at least the frequency parameters used in the current test. and the loudness parameter after adaptive adjustment Frequency parameters Loudness parameter in Hertz Hearing level is measured in decibels. The response acquisition and local processing module packages and logically associates the data elements obtained in the above three steps. Specifically, it creates a new data record object containing the following fields: user response timestamp. Stimulation frequency Stimulus and the corresponding audiometric behavior unit identifier This data record object is a complete structured response record R, which fully represents a user response event and its complete test context. Its logical relationship can be represented as follows: R={ }; The module writes the generated structured response record R to the local database of the listening node via a database operation interface. The local database is preferably an encrypted SQLite relational database, configured in WAL (Write-Ahead Log) mode to ensure transaction safety and data consistency. During the write process, the response record R is inserted into a dedicated table for storing the original response. This table is designed to support efficient querying and aggregation analysis based on listening strategies, listening behavior units, timestamps, or parameter ranges. This step ensures that all data is reliably persisted even when completely offline.

[0031] The intelligent synchronization module is used to monitor the network status and data attributes of the listening nodes; when the preset synchronization trigger conditions are met, the listening data stored in the local database is synchronized to the central server.

[0032] Furthermore, in the intelligent synchronization module, the network status and data attributes of the listening nodes are monitored; when the preset synchronization trigger conditions are met, the listening data stored in the local database is synchronized to the central server. The specific steps include: Continuously monitor the network connection status of the listening nodes and the data attributes of the listening data to be synchronized in the local database; Determine whether the network connection status and data attributes together meet the preset combination of synchronization triggering conditions; When the combination of synchronization triggering conditions is determined to be met, the listening data to be synchronized is extracted from the local database. The extracted audiometry data is sent to the central server.

[0033] Specifically, the intelligent synchronization module starts a background service to continuously monitor two key pieces of information. The first is the network connection status of the listening nodes. This status not only includes whether there is a network connection, but also further distinguishes the connection type, such as Wi-Fi connection and cellular network connection, and assesses the signal strength and stability of the current connection. The second item is the data attribute of the listening data to be synchronized in the local database. This attribute includes the urgency of the data, the time the data was generated, and the size of the data. The urgency of the data can be determined according to preset rules. For example, data marked as emergency patients or data that has exceeded a certain storage time limit can be assigned a high urgency attribute. The module incorporates a context-aware synchronous decision-making logic. This logic will consider the network connection status detected in the first step. With data attributes With a set of preset synchronization trigger conditions The module performs comparisons and logical operations. This set of conditions is a combination of multiple dimensions, designed to balance data timeliness with system resource consumption. Examples of preset synchronization trigger condition combinations are as follows: network is available and the connection type is Wi-Fi; or, the data urgency is high and the network is available; or, the device is charging and it is during off-peak power consumption hours. The module determines the current situation in real time. and Whether they jointly satisfy at least one of the above combinations of conditions; Once the module determines that the combination of synchronization trigger conditions is met, it immediately initiates a data synchronization task. First, based on the data attribute filtering rules associated with the trigger conditions, the module queries and extracts all eligible but not yet synchronized audiometry data from the local database. This data includes the aforementioned structured response records, associated patient identification information, and snapshots of test environment parameters. The extraction process ensures data atomicity and consistency. The module compresses and encrypts the extracted audiometry data packets to be synchronized, and then sends them to the designated central server via the currently available network connection. The transmission process uses a secure transmission protocol. After successfully receiving and processing the data, the central server returns an acknowledgment response to the audiometry node. Upon receiving the acknowledgment, the audiometry node marks the corresponding data in its local database as "synchronized," or migrates it to the archive storage area according to a strategy, thus completing a full data synchronization cycle. If transmission fails, the module will retry synchronization at a later, appropriate time based on a preset retry strategy and updated context state.

[0034] Example 2: A signal processing method, the steps of which are as follows: Figure 5 As shown, the method includes: Obtain an audiometry strategy based on a combination of parameters, capabilities, and response units, wherein the parameter units include at least the target frequency and the reference loudness; When starting the audiometry test, the background noise level of the current test environment is detected; The reference loudness is compared with the background noise level, and a loudness compensation value is determined based on the comparison result; Based on the target frequency and the final loudness determined by the reference loudness and loudness compensation value, the corresponding pure tone test signal is generated; Play a pure tone test signal and collect the user's input response to the played signal; The audiometry record, which includes the input response, target frequency, and final loudness, is associated with the current execution context of the audiometry strategy and stored locally.

[0035] Specifically, the listening node loads the listening policy from its local storage or receives it from the network. This listening policy is a structured document defined based on a combination of parameter units, capability units, and response units. The system parses this policy and extracts the key parameter units associated with the listening action unit that needs to be executed. Among these, the extracted parameter units must include at least one target frequency parameter. and a reference loudness parameter Target frequency parameters The target frequency value for the pure tone in this test is specified, in Hertz. Reference loudness parameter. The reference intensity value for playing this pure tone in a standard quiet environment is specified, in decibels (hearing level). When the listening test task is initiated according to the strategy, the system calls the audio input device of the listening node to collect the audio signal of the current environment. This signal is then filtered and analyzed to remove frequency bands irrelevant to the target frequency, and its equivalent sound pressure level is calculated to determine the background noise level parameters of the current test environment. The unit is decibels (dB). This parameter characterizes the intensity of the masking effect that ambient noise may have on the test pure tone; The system will use the reference loudness parameters obtained above. Compared with the detected background noise level parameter A comparison is performed. The purpose of the comparison is to assess whether environmental noise is sufficient to interfere with the user's perception of a reference loudness pure tone. Based on the comparison results, the system calculates a loudness compensation value ΔL using a preset compensation algorithm. A basic algorithm is: when... When the loudness compensation value ΔL is greater than or equal to a preset perception threshold Th, the loudness compensation value is ΔL = , where K is a compensation coefficient greater than zero; when When the loudness is less than Th, the loudness compensation value ΔL = 0. This loudness compensation value ΔL is designed to increase the loudness of the test pure tone to a level that can overcome the masking effect of background noise; The system is based on the acquired target frequency parameters and from the reference loudness parameter The final loudness parameter determined together with the loudness compensation value ΔL This generates the corresponding digital pure tone test signal. Final loudness parameters. The calculation formula is: The digital signal processor is based on the target frequency parameters. Generate a digital sequence of sine waves corresponding to the frequency, and based on the final loudness parameter... In addition, specific calibration parameters for the device are used to adjust the amplitude of the digital sequence to the corresponding digital amplitude value, thereby completing the generation of the digital audio signal; The system plays the pure tone test signal generated in step four through the audio output device. Simultaneously, the system starts a response monitoring thread to listen for user input. When the user perceives the pure tone and performs an input operation, the system immediately captures the input response. And record the precise moment the response occurred. ; The system integrates the key information from this interaction into a single audio recording. This recording must include at least: the user's input response. Target frequency parameters Final loudness parameters Response timestamp The system determines the context of the audiometry behavior unit to which the current interaction belongs based on the logic of the audiometry strategy being executed. Finally, the system links this complete audiometry record with its corresponding audiometry behavior unit context. Logical associations are established and written to the local non-volatile memory of the listening node in a structured format, such as database records. This ensures that all relevant information for a single test interaction is completely and traceably stored locally, laying the foundation for subsequent offline analysis or synchronization after network recovery.

[0036] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A distributed autonomous pure tone testing system, characterized in that, Includes the following modules: The strategy definition and distribution module is used to construct an audiometry strategy, wherein the audiometry strategy is defined by decomposing the audiometry process into a combination of parameter units, capability units, and response units. The parameter units are used to characterize the pure tone frequency and loudness, the capability units are used to define the operation of playing pure tones, and the response units are used to define the acquisition of user input. The audiometry strategy is then distributed to one or more audiometry nodes. The specific steps in constructing an audiometry strategy include: Define at least one frequency parameter and at least one loudness parameter; Define at least one playback capability unit, the playback capability unit being configured to play a pure tone test signal based on the frequency parameter and the loudness parameter; Define at least one response unit, the response unit being configured to acquire user input in response to a played pure tone test signal; The frequency parameter, the loudness parameter, the playback capability unit, and the response unit are associated to form an audiometric behavior unit. The listening strategy is generated based on at least one of the listening behavior units; The environment adaptation and signal generation module is used to detect the current test environment parameters when the audiometry node starts the test; based on the current test environment parameters, adaptively adjust the signal generation parameters in the audiometry strategy; and generate and play the corresponding pure tone test signal according to the adjusted signal generation parameters. The response acquisition and local processing module is used to acquire response data input by the user in response to the pure tone test signal; associate the response data with the current execution state in the listening strategy, and store it in the local database of the listening node; The intelligent synchronization module is used to monitor the network status and data attributes of the listening nodes; when the preset synchronization trigger conditions are met, the listening data stored in the local database is synchronized to the central server.

2. The distributed autonomous pure tone testing system according to claim 1, characterized in that, In the policy definition and distribution module, the step of distributing the listening policy to one or more listening nodes specifically includes: Generate and associate a version identifier for the listening strategy; The listening policy carrying the version identifier is sent from the policy management node to the target listening node; The target listening node receives the listening strategy and the version identifier, and stores the listening strategy and the version identifier locally.

3. The distributed autonomous pure tone testing system according to claim 1, characterized in that, In the environment adaptation and signal generation module, the step of detecting the current test environment parameters when the listening node starts the test specifically includes: The background sound signal of the current environment is collected through the microphone configured in the listening node; The sensors configured at the listening nodes collect interference signals from the current environment. Based on the background sound signal, determine the background noise level parameters; Based on the interference signal, determine the electromagnetic interference level parameters; The current test environment parameters include the background noise level parameters and the electromagnetic interference level parameters.

4. The distributed autonomous pure tone testing system according to claim 3, characterized in that, In the environment adaptation and signal generation module, the step of adaptively adjusting the signal generation parameters in the audiometry strategy based on the current test environment parameters specifically includes: Obtain the reference loudness parameter defined in the audiometry strategy; The reference loudness parameter is compared with the background noise level parameter; Based on the comparison results, a loudness adjustment amount is generated to compensate for the background noise; Based on the loudness adjustment amount, the reference loudness parameter is corrected to obtain the adjusted loudness parameter; The signal generation parameters include at least the adjusted loudness parameter.

5. The distributed autonomous pure tone testing system according to claim 1, characterized in that, In the environment adaptation and signal generation module, the steps of generating and playing the corresponding pure tone test signal based on the adjusted signal generation parameters specifically include: Based on the frequency and loudness parameters in the adjusted signal generation parameters, a corresponding digital audio signal is generated; The hardware abstraction layer is invoked to convert the digital audio signal into a drive signal suitable for the target audio output device; The drive signal is played through the target audio output device to generate the pure tone test signal.

6. The distributed autonomous pure tone testing system according to claim 1, characterized in that, In the response acquisition and local processing module, the steps of acquiring user response data to the pure tone test signal, associating the response data with the current execution state in the listening strategy, and storing it in the local database of the listening node specifically include: Record the first timestamp when the user generates an input operation on the currently playing pure tone test signal; Record the frequency and loudness parameters corresponding to the currently playing pure tone test signal; Based on the execution logic of the audiometry strategy, determine the audiometry behavior unit corresponding to the response data; The first timestamp, the frequency parameter, the loudness parameter, and the determined audiometry behavior unit identifier are associated to form a structured response record; The structured response record is written into the local database of the listening node.

7. The distributed autonomous pure tone testing system according to claim 1, characterized in that, In the intelligent synchronization module, the network status and data attributes of the listening nodes are monitored; when the preset synchronization trigger conditions are met, the listening data stored in the local database is synchronized to the central server. The specific steps include: Continuously monitor the network connection status of the listening node and the data attributes of the listening data to be synchronized in the local database; Determine whether the network connection status and the data attributes together satisfy a preset combination of synchronization triggering conditions; When it is determined that the combination of the synchronization triggering conditions is met, the listening data to be synchronized is extracted from the local database; The extracted audiometry data is sent to the central server.

8. A signal processing method, characterized in that, The method applied to the distributed autonomous pure tone testing system according to any one of claims 1-7 is characterized in that the method comprises: Obtain an audiometry strategy based on a combination of parameters, capabilities, and response units, wherein the parameter units include at least a target frequency and a reference loudness; The acquisition of the listening strategy based on the combination of parameters, capabilities, and response units includes: Define at least one frequency parameter and at least one loudness parameter; Define at least one playback capability unit, the playback capability unit being configured to play a pure tone test signal based on the frequency parameter and the loudness parameter; Define at least one response unit, the response unit being configured to acquire user input in response to a played pure tone test signal; The frequency parameter, the loudness parameter, the playback capability unit, and the response unit are associated to form an audiometric behavior unit. The listening strategy is generated based on at least one of the listening behavior units; When starting the audiometry test, the background noise level of the current test environment is detected; The reference loudness is compared with the background noise level, and a loudness compensation value is determined based on the comparison result; Based on the target frequency and the final loudness determined by the reference loudness and the loudness compensation value, a corresponding pure tone test signal is generated; Play the pure tone test signal and collect the user's input response to the played signal; The audiometry record containing the input response, the target frequency, and the final loudness is associated with the current execution context of the audiometry strategy and stored locally.

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